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737 Commits
v0.9.5
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201
.agents/skills/lora-manager-e2e/SKILL.md
Normal file
201
.agents/skills/lora-manager-e2e/SKILL.md
Normal file
@@ -0,0 +1,201 @@
|
||||
---
|
||||
name: lora-manager-e2e
|
||||
description: End-to-end testing and validation for LoRa Manager features. Use when performing automated E2E validation of LoRa Manager standalone mode, including starting/restarting the server, using Chrome DevTools MCP to interact with the web UI at http://127.0.0.1:8188/loras, and verifying frontend-to-backend functionality. Covers workflow validation, UI interaction testing, and integration testing between the standalone Python backend and the browser frontend.
|
||||
---
|
||||
|
||||
# LoRa Manager E2E Testing
|
||||
|
||||
This skill provides workflows and utilities for end-to-end testing of LoRa Manager using Chrome DevTools MCP.
|
||||
|
||||
## Prerequisites
|
||||
|
||||
- LoRa Manager project cloned and dependencies installed (`pip install -r requirements.txt`)
|
||||
- Chrome browser available for debugging
|
||||
- Chrome DevTools MCP connected
|
||||
|
||||
## Quick Start Workflow
|
||||
|
||||
### 1. Start LoRa Manager Standalone
|
||||
|
||||
```python
|
||||
# Use the provided script to start the server
|
||||
python .agents/skills/lora-manager-e2e/scripts/start_server.py --port 8188
|
||||
```
|
||||
|
||||
Or manually:
|
||||
```bash
|
||||
cd /home/miao/workspace/ComfyUI/custom_nodes/ComfyUI-Lora-Manager
|
||||
python standalone.py --port 8188
|
||||
```
|
||||
|
||||
Wait for server ready message before proceeding.
|
||||
|
||||
### 2. Open Chrome Debug Mode
|
||||
|
||||
```bash
|
||||
# Chrome with remote debugging on port 9222
|
||||
google-chrome --remote-debugging-port=9222 --user-data-dir=/tmp/chrome-lora-manager http://127.0.0.1:8188/loras
|
||||
```
|
||||
|
||||
### 3. Connect Chrome DevTools MCP
|
||||
|
||||
Ensure the MCP server is connected to Chrome at `http://localhost:9222`.
|
||||
|
||||
### 4. Navigate and Interact
|
||||
|
||||
Use Chrome DevTools MCP tools to:
|
||||
- Take snapshots: `take_snapshot`
|
||||
- Click elements: `click`
|
||||
- Fill forms: `fill` or `fill_form`
|
||||
- Evaluate scripts: `evaluate_script`
|
||||
- Wait for elements: `wait_for`
|
||||
|
||||
## Common E2E Test Patterns
|
||||
|
||||
### Pattern: Full Page Load Verification
|
||||
|
||||
```python
|
||||
# Navigate to LoRA list page
|
||||
navigate_page(type="url", url="http://127.0.0.1:8188/loras")
|
||||
|
||||
# Wait for page to load
|
||||
wait_for(text="LoRAs", timeout=10000)
|
||||
|
||||
# Take snapshot to verify UI state
|
||||
snapshot = take_snapshot()
|
||||
```
|
||||
|
||||
### Pattern: Restart Server for Configuration Changes
|
||||
|
||||
```python
|
||||
# Stop current server (if running)
|
||||
# Start with new configuration
|
||||
python .agents/skills/lora-manager-e2e/scripts/start_server.py --port 8188 --restart
|
||||
|
||||
# Wait and refresh browser
|
||||
navigate_page(type="reload", ignoreCache=True)
|
||||
wait_for(text="LoRAs", timeout=15000)
|
||||
```
|
||||
|
||||
### Pattern: Verify Backend API via Frontend
|
||||
|
||||
```python
|
||||
# Execute script in browser to call backend API
|
||||
result = evaluate_script(function="""
|
||||
async () => {
|
||||
const response = await fetch('/loras/api/list');
|
||||
const data = await response.json();
|
||||
return { count: data.length, firstItem: data[0]?.name };
|
||||
}
|
||||
""")
|
||||
```
|
||||
|
||||
### Pattern: Form Submission Flow
|
||||
|
||||
```python
|
||||
# Fill a form (e.g., search or filter)
|
||||
fill_form(elements=[
|
||||
{"uid": "search-input", "value": "character"},
|
||||
])
|
||||
|
||||
# Click submit button
|
||||
click(uid="search-button")
|
||||
|
||||
# Wait for results
|
||||
wait_for(text="Results", timeout=5000)
|
||||
|
||||
# Verify results via snapshot
|
||||
snapshot = take_snapshot()
|
||||
```
|
||||
|
||||
### Pattern: Modal Dialog Interaction
|
||||
|
||||
```python
|
||||
# Open modal (e.g., add LoRA)
|
||||
click(uid="add-lora-button")
|
||||
|
||||
# Wait for modal to appear
|
||||
wait_for(text="Add LoRA", timeout=3000)
|
||||
|
||||
# Fill modal form
|
||||
fill_form(elements=[
|
||||
{"uid": "lora-name", "value": "Test LoRA"},
|
||||
{"uid": "lora-path", "value": "/path/to/lora.safetensors"},
|
||||
])
|
||||
|
||||
# Submit
|
||||
click(uid="modal-submit-button")
|
||||
|
||||
# Wait for success message or close
|
||||
wait_for(text="Success", timeout=5000)
|
||||
```
|
||||
|
||||
## Available Scripts
|
||||
|
||||
### scripts/start_server.py
|
||||
|
||||
Starts or restarts the LoRa Manager standalone server.
|
||||
|
||||
```bash
|
||||
python scripts/start_server.py [--port PORT] [--restart] [--wait]
|
||||
```
|
||||
|
||||
Options:
|
||||
- `--port`: Server port (default: 8188)
|
||||
- `--restart`: Kill existing server before starting
|
||||
- `--wait`: Wait for server to be ready before exiting
|
||||
|
||||
### scripts/wait_for_server.py
|
||||
|
||||
Polls server until ready or timeout.
|
||||
|
||||
```bash
|
||||
python scripts/wait_for_server.py [--port PORT] [--timeout SECONDS]
|
||||
```
|
||||
|
||||
## Test Scenarios Reference
|
||||
|
||||
See [references/test-scenarios.md](references/test-scenarios.md) for detailed test scenarios including:
|
||||
- LoRA list display and filtering
|
||||
- Model metadata editing
|
||||
- Recipe creation and management
|
||||
- Settings configuration
|
||||
- Import/export functionality
|
||||
|
||||
## Network Request Verification
|
||||
|
||||
Use `list_network_requests` and `get_network_request` to verify API calls:
|
||||
|
||||
```python
|
||||
# List recent XHR/fetch requests
|
||||
requests = list_network_requests(resourceTypes=["xhr", "fetch"])
|
||||
|
||||
# Get details of specific request
|
||||
details = get_network_request(reqid=123)
|
||||
```
|
||||
|
||||
## Console Message Monitoring
|
||||
|
||||
```python
|
||||
# Check for errors or warnings
|
||||
messages = list_console_messages(types=["error", "warn"])
|
||||
```
|
||||
|
||||
## Performance Testing
|
||||
|
||||
```python
|
||||
# Start performance trace
|
||||
performance_start_trace(reload=True, autoStop=False)
|
||||
|
||||
# Perform actions...
|
||||
|
||||
# Stop and analyze
|
||||
results = performance_stop_trace()
|
||||
```
|
||||
|
||||
## Cleanup
|
||||
|
||||
Always ensure proper cleanup after tests:
|
||||
1. Stop the standalone server
|
||||
2. Close browser pages (keep at least one open)
|
||||
3. Clear temporary data if needed
|
||||
324
.agents/skills/lora-manager-e2e/references/mcp-cheatsheet.md
Normal file
324
.agents/skills/lora-manager-e2e/references/mcp-cheatsheet.md
Normal file
@@ -0,0 +1,324 @@
|
||||
# Chrome DevTools MCP Cheatsheet for LoRa Manager
|
||||
|
||||
Quick reference for common MCP commands used in LoRa Manager E2E testing.
|
||||
|
||||
## Navigation
|
||||
|
||||
```python
|
||||
# Navigate to LoRA list page
|
||||
navigate_page(type="url", url="http://127.0.0.1:8188/loras")
|
||||
|
||||
# Reload page with cache clear
|
||||
navigate_page(type="reload", ignoreCache=True)
|
||||
|
||||
# Go back/forward
|
||||
navigate_page(type="back")
|
||||
navigate_page(type="forward")
|
||||
```
|
||||
|
||||
## Waiting
|
||||
|
||||
```python
|
||||
# Wait for text to appear
|
||||
wait_for(text="LoRAs", timeout=10000)
|
||||
|
||||
# Wait for specific element (via evaluate_script)
|
||||
evaluate_script(function="""
|
||||
() => {
|
||||
return new Promise((resolve) => {
|
||||
const check = () => {
|
||||
if (document.querySelector('.lora-card')) {
|
||||
resolve(true);
|
||||
} else {
|
||||
setTimeout(check, 100);
|
||||
}
|
||||
};
|
||||
check();
|
||||
});
|
||||
}
|
||||
""")
|
||||
```
|
||||
|
||||
## Taking Snapshots
|
||||
|
||||
```python
|
||||
# Full page snapshot
|
||||
snapshot = take_snapshot()
|
||||
|
||||
# Verbose snapshot (more details)
|
||||
snapshot = take_snapshot(verbose=True)
|
||||
|
||||
# Save to file
|
||||
take_snapshot(filePath="test-snapshots/page-load.json")
|
||||
```
|
||||
|
||||
## Element Interaction
|
||||
|
||||
```python
|
||||
# Click element
|
||||
click(uid="element-uid-from-snapshot")
|
||||
|
||||
# Double click
|
||||
click(uid="element-uid", dblClick=True)
|
||||
|
||||
# Fill input
|
||||
fill(uid="search-input", value="test query")
|
||||
|
||||
# Fill multiple inputs
|
||||
fill_form(elements=[
|
||||
{"uid": "input-1", "value": "value 1"},
|
||||
{"uid": "input-2", "value": "value 2"},
|
||||
])
|
||||
|
||||
# Hover
|
||||
hover(uid="lora-card-1")
|
||||
|
||||
# Upload file
|
||||
upload_file(uid="file-input", filePath="/path/to/file.safetensors")
|
||||
```
|
||||
|
||||
## Keyboard Input
|
||||
|
||||
```python
|
||||
# Press key
|
||||
press_key(key="Enter")
|
||||
press_key(key="Escape")
|
||||
press_key(key="Tab")
|
||||
|
||||
# Keyboard shortcuts
|
||||
press_key(key="Control+A") # Select all
|
||||
press_key(key="Control+F") # Find
|
||||
```
|
||||
|
||||
## JavaScript Evaluation
|
||||
|
||||
```python
|
||||
# Simple evaluation
|
||||
result = evaluate_script(function="() => document.title")
|
||||
|
||||
# Async evaluation
|
||||
result = evaluate_script(function="""
|
||||
async () => {
|
||||
const response = await fetch('/loras/api/list');
|
||||
return await response.json();
|
||||
}
|
||||
""")
|
||||
|
||||
# Check element existence
|
||||
exists = evaluate_script(function="""
|
||||
() => document.querySelector('.lora-card') !== null
|
||||
""")
|
||||
|
||||
# Get element count
|
||||
count = evaluate_script(function="""
|
||||
() => document.querySelectorAll('.lora-card').length
|
||||
""")
|
||||
```
|
||||
|
||||
## Network Monitoring
|
||||
|
||||
```python
|
||||
# List all network requests
|
||||
requests = list_network_requests()
|
||||
|
||||
# Filter by resource type
|
||||
xhr_requests = list_network_requests(resourceTypes=["xhr", "fetch"])
|
||||
|
||||
# Get specific request details
|
||||
details = get_network_request(reqid=123)
|
||||
|
||||
# Include preserved requests from previous navigations
|
||||
all_requests = list_network_requests(includePreservedRequests=True)
|
||||
```
|
||||
|
||||
## Console Monitoring
|
||||
|
||||
```python
|
||||
# List all console messages
|
||||
messages = list_console_messages()
|
||||
|
||||
# Filter by type
|
||||
errors = list_console_messages(types=["error", "warn"])
|
||||
|
||||
# Include preserved messages
|
||||
all_messages = list_console_messages(includePreservedMessages=True)
|
||||
|
||||
# Get specific message
|
||||
details = get_console_message(msgid=1)
|
||||
```
|
||||
|
||||
## Performance Testing
|
||||
|
||||
```python
|
||||
# Start trace with page reload
|
||||
performance_start_trace(reload=True, autoStop=False)
|
||||
|
||||
# Start trace without reload
|
||||
performance_start_trace(reload=False, autoStop=True, filePath="trace.json.gz")
|
||||
|
||||
# Stop trace
|
||||
results = performance_stop_trace()
|
||||
|
||||
# Stop and save
|
||||
performance_stop_trace(filePath="trace-results.json.gz")
|
||||
|
||||
# Analyze specific insight
|
||||
insight = performance_analyze_insight(
|
||||
insightSetId="results.insightSets[0].id",
|
||||
insightName="LCPBreakdown"
|
||||
)
|
||||
```
|
||||
|
||||
## Page Management
|
||||
|
||||
```python
|
||||
# List open pages
|
||||
pages = list_pages()
|
||||
|
||||
# Select a page
|
||||
select_page(pageId=0, bringToFront=True)
|
||||
|
||||
# Create new page
|
||||
new_page(url="http://127.0.0.1:8188/loras")
|
||||
|
||||
# Close page (keep at least one open!)
|
||||
close_page(pageId=1)
|
||||
|
||||
# Resize page
|
||||
resize_page(width=1920, height=1080)
|
||||
```
|
||||
|
||||
## Screenshots
|
||||
|
||||
```python
|
||||
# Full page screenshot
|
||||
take_screenshot(fullPage=True)
|
||||
|
||||
# Viewport screenshot
|
||||
take_screenshot()
|
||||
|
||||
# Element screenshot
|
||||
take_screenshot(uid="lora-card-1")
|
||||
|
||||
# Save to file
|
||||
take_screenshot(filePath="screenshots/page.png", format="png")
|
||||
|
||||
# JPEG with quality
|
||||
take_screenshot(filePath="screenshots/page.jpg", format="jpeg", quality=90)
|
||||
```
|
||||
|
||||
## Dialog Handling
|
||||
|
||||
```python
|
||||
# Accept dialog
|
||||
handle_dialog(action="accept")
|
||||
|
||||
# Accept with text input
|
||||
handle_dialog(action="accept", promptText="user input")
|
||||
|
||||
# Dismiss dialog
|
||||
handle_dialog(action="dismiss")
|
||||
```
|
||||
|
||||
## Device Emulation
|
||||
|
||||
```python
|
||||
# Mobile viewport
|
||||
emulate(viewport={"width": 375, "height": 667, "isMobile": True, "hasTouch": True})
|
||||
|
||||
# Tablet viewport
|
||||
emulate(viewport={"width": 768, "height": 1024, "isMobile": True, "hasTouch": True})
|
||||
|
||||
# Desktop viewport
|
||||
emulate(viewport={"width": 1920, "height": 1080})
|
||||
|
||||
# Network throttling
|
||||
emulate(networkConditions="Slow 3G")
|
||||
emulate(networkConditions="Fast 4G")
|
||||
|
||||
# CPU throttling
|
||||
emulate(cpuThrottlingRate=4) # 4x slowdown
|
||||
|
||||
# Geolocation
|
||||
emulate(geolocation={"latitude": 37.7749, "longitude": -122.4194})
|
||||
|
||||
# User agent
|
||||
emulate(userAgent="Mozilla/5.0 (Custom)")
|
||||
|
||||
# Reset emulation
|
||||
emulate(viewport=None, networkConditions="No emulation", userAgent=None)
|
||||
```
|
||||
|
||||
## Drag and Drop
|
||||
|
||||
```python
|
||||
# Drag element to another
|
||||
drag(from_uid="draggable-item", to_uid="drop-zone")
|
||||
```
|
||||
|
||||
## Common LoRa Manager Test Patterns
|
||||
|
||||
### Verify LoRA Cards Loaded
|
||||
|
||||
```python
|
||||
navigate_page(type="url", url="http://127.0.0.1:8188/loras")
|
||||
wait_for(text="LoRAs", timeout=10000)
|
||||
|
||||
# Check if cards loaded
|
||||
result = evaluate_script(function="""
|
||||
() => {
|
||||
const cards = document.querySelectorAll('.lora-card');
|
||||
return {
|
||||
count: cards.length,
|
||||
hasData: cards.length > 0
|
||||
};
|
||||
}
|
||||
""")
|
||||
```
|
||||
|
||||
### Search and Verify Results
|
||||
|
||||
```python
|
||||
fill(uid="search-input", value="character")
|
||||
press_key(key="Enter")
|
||||
wait_for(timeout=2000) # Wait for debounce
|
||||
|
||||
# Check results
|
||||
result = evaluate_script(function="""
|
||||
() => {
|
||||
const cards = document.querySelectorAll('.lora-card');
|
||||
const names = Array.from(cards).map(c => c.dataset.name || c.textContent);
|
||||
return { count: cards.length, names };
|
||||
}
|
||||
""")
|
||||
```
|
||||
|
||||
### Check API Response
|
||||
|
||||
```python
|
||||
# Trigger API call
|
||||
evaluate_script(function="""
|
||||
() => window.loraApiCallPromise = fetch('/loras/api/list').then(r => r.json())
|
||||
""")
|
||||
|
||||
# Wait and get result
|
||||
import time
|
||||
time.sleep(1)
|
||||
|
||||
result = evaluate_script(function="""
|
||||
async () => await window.loraApiCallPromise
|
||||
""")
|
||||
```
|
||||
|
||||
### Monitor Console for Errors
|
||||
|
||||
```python
|
||||
# Before test: clear console (navigate reloads)
|
||||
navigate_page(type="reload")
|
||||
|
||||
# ... perform actions ...
|
||||
|
||||
# Check for errors
|
||||
errors = list_console_messages(types=["error"])
|
||||
assert len(errors) == 0, f"Console errors: {errors}"
|
||||
```
|
||||
272
.agents/skills/lora-manager-e2e/references/test-scenarios.md
Normal file
272
.agents/skills/lora-manager-e2e/references/test-scenarios.md
Normal file
@@ -0,0 +1,272 @@
|
||||
# LoRa Manager E2E Test Scenarios
|
||||
|
||||
This document provides detailed test scenarios for end-to-end validation of LoRa Manager features.
|
||||
|
||||
## Table of Contents
|
||||
|
||||
1. [LoRA List Page](#lora-list-page)
|
||||
2. [Model Details](#model-details)
|
||||
3. [Recipes](#recipes)
|
||||
4. [Settings](#settings)
|
||||
5. [Import/Export](#importexport)
|
||||
|
||||
---
|
||||
|
||||
## LoRA List Page
|
||||
|
||||
### Scenario: Page Load and Display
|
||||
|
||||
**Objective**: Verify the LoRA list page loads correctly and displays models.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to `http://127.0.0.1:8188/loras`
|
||||
2. Wait for page title "LoRAs" to appear
|
||||
3. Take snapshot to verify:
|
||||
- Header with "LoRAs" title is visible
|
||||
- Search/filter controls are present
|
||||
- Grid/list view toggle exists
|
||||
- LoRA cards are displayed (if models exist)
|
||||
- Pagination controls (if applicable)
|
||||
|
||||
**Expected Result**: Page loads without errors, UI elements are present.
|
||||
|
||||
### Scenario: Search Functionality
|
||||
|
||||
**Objective**: Verify search filters LoRA models correctly.
|
||||
|
||||
**Steps**:
|
||||
1. Ensure at least one LoRA exists with known name (e.g., "test-character")
|
||||
2. Navigate to LoRA list page
|
||||
3. Enter search term in search box: "test"
|
||||
4. Press Enter or click search button
|
||||
5. Wait for results to update
|
||||
|
||||
**Expected Result**: Only LoRAs matching search term are displayed.
|
||||
|
||||
**Verification Script**:
|
||||
```python
|
||||
# After search, verify filtered results
|
||||
evaluate_script(function="""
|
||||
() => {
|
||||
const cards = document.querySelectorAll('.lora-card');
|
||||
const names = Array.from(cards).map(c => c.dataset.name);
|
||||
return { count: cards.length, names };
|
||||
}
|
||||
""")
|
||||
```
|
||||
|
||||
### Scenario: Filter by Tags
|
||||
|
||||
**Objective**: Verify tag filtering works correctly.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to LoRA list page
|
||||
2. Click on a tag (e.g., "character", "style")
|
||||
3. Wait for filtered results
|
||||
|
||||
**Expected Result**: Only LoRAs with selected tag are displayed.
|
||||
|
||||
### Scenario: View Mode Toggle
|
||||
|
||||
**Objective**: Verify grid/list view toggle works.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to LoRA list page
|
||||
2. Click list view button
|
||||
3. Verify list layout
|
||||
4. Click grid view button
|
||||
5. Verify grid layout
|
||||
|
||||
**Expected Result**: View mode changes correctly, layout updates.
|
||||
|
||||
---
|
||||
|
||||
## Model Details
|
||||
|
||||
### Scenario: Open Model Details
|
||||
|
||||
**Objective**: Verify clicking a LoRA opens its details.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to LoRA list page
|
||||
2. Click on a LoRA card
|
||||
3. Wait for details panel/modal to open
|
||||
|
||||
**Expected Result**: Details panel shows:
|
||||
- Model name
|
||||
- Preview image
|
||||
- Metadata (trigger words, tags, etc.)
|
||||
- Action buttons (edit, delete, etc.)
|
||||
|
||||
### Scenario: Edit Model Metadata
|
||||
|
||||
**Objective**: Verify metadata editing works end-to-end.
|
||||
|
||||
**Steps**:
|
||||
1. Open a LoRA's details
|
||||
2. Click "Edit" button
|
||||
3. Modify trigger words field
|
||||
4. Add/remove tags
|
||||
5. Save changes
|
||||
6. Refresh page
|
||||
7. Reopen the same LoRA
|
||||
|
||||
**Expected Result**: Changes persist after refresh.
|
||||
|
||||
### Scenario: Delete Model
|
||||
|
||||
**Objective**: Verify model deletion works.
|
||||
|
||||
**Steps**:
|
||||
1. Open a LoRA's details
|
||||
2. Click "Delete" button
|
||||
3. Confirm deletion in dialog
|
||||
4. Wait for removal
|
||||
|
||||
**Expected Result**: Model removed from list, success message shown.
|
||||
|
||||
---
|
||||
|
||||
## Recipes
|
||||
|
||||
### Scenario: Recipe List Display
|
||||
|
||||
**Objective**: Verify recipes page loads and displays recipes.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to `http://127.0.0.1:8188/recipes`
|
||||
2. Wait for "Recipes" title
|
||||
3. Take snapshot
|
||||
|
||||
**Expected Result**: Recipe list displayed with cards/items.
|
||||
|
||||
### Scenario: Create New Recipe
|
||||
|
||||
**Objective**: Verify recipe creation workflow.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to recipes page
|
||||
2. Click "New Recipe" button
|
||||
3. Fill recipe form:
|
||||
- Name: "Test Recipe"
|
||||
- Description: "E2E test recipe"
|
||||
- Add LoRA models
|
||||
4. Save recipe
|
||||
5. Verify recipe appears in list
|
||||
|
||||
**Expected Result**: New recipe created and displayed.
|
||||
|
||||
### Scenario: Apply Recipe
|
||||
|
||||
**Objective**: Verify applying a recipe to ComfyUI.
|
||||
|
||||
**Steps**:
|
||||
1. Open a recipe
|
||||
2. Click "Apply" or "Load in ComfyUI"
|
||||
3. Verify action completes
|
||||
|
||||
**Expected Result**: Recipe applied successfully.
|
||||
|
||||
---
|
||||
|
||||
## Settings
|
||||
|
||||
### Scenario: Settings Page Load
|
||||
|
||||
**Objective**: Verify settings page displays correctly.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to `http://127.0.0.1:8188/settings`
|
||||
2. Wait for "Settings" title
|
||||
3. Take snapshot
|
||||
|
||||
**Expected Result**: Settings form with various options displayed.
|
||||
|
||||
### Scenario: Change Setting and Restart
|
||||
|
||||
**Objective**: Verify settings persist after restart.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to settings page
|
||||
2. Change a setting (e.g., default view mode)
|
||||
3. Save settings
|
||||
4. Restart server: `python scripts/start_server.py --restart --wait`
|
||||
5. Refresh browser page
|
||||
6. Navigate to settings
|
||||
|
||||
**Expected Result**: Changed setting value persists.
|
||||
|
||||
---
|
||||
|
||||
## Import/Export
|
||||
|
||||
### Scenario: Export Models List
|
||||
|
||||
**Objective**: Verify export functionality.
|
||||
|
||||
**Steps**:
|
||||
1. Navigate to LoRA list
|
||||
2. Click "Export" button
|
||||
3. Select format (JSON/CSV)
|
||||
4. Download file
|
||||
|
||||
**Expected Result**: File downloaded with correct data.
|
||||
|
||||
### Scenario: Import Models
|
||||
|
||||
**Objective**: Verify import functionality.
|
||||
|
||||
**Steps**:
|
||||
1. Prepare import file
|
||||
2. Navigate to import page
|
||||
3. Upload file
|
||||
4. Verify import results
|
||||
|
||||
**Expected Result**: Models imported successfully, confirmation shown.
|
||||
|
||||
---
|
||||
|
||||
## API Integration Tests
|
||||
|
||||
### Scenario: Verify API Endpoints
|
||||
|
||||
**Objective**: Verify backend API responds correctly.
|
||||
|
||||
**Test via browser console**:
|
||||
```javascript
|
||||
// List LoRAs
|
||||
fetch('/loras/api/list').then(r => r.json()).then(console.log)
|
||||
|
||||
// Get LoRA details
|
||||
fetch('/loras/api/detail/<id>').then(r => r.json()).then(console.log)
|
||||
|
||||
// Search LoRAs
|
||||
fetch('/loras/api/search?q=test').then(r => r.json()).then(console.log)
|
||||
```
|
||||
|
||||
**Expected Result**: APIs return valid JSON with expected structure.
|
||||
|
||||
---
|
||||
|
||||
## Console Error Monitoring
|
||||
|
||||
During all tests, monitor browser console for errors:
|
||||
|
||||
```python
|
||||
# Check for JavaScript errors
|
||||
messages = list_console_messages(types=["error"])
|
||||
assert len(messages) == 0, f"Console errors found: {messages}"
|
||||
```
|
||||
|
||||
## Network Request Verification
|
||||
|
||||
Verify key API calls are made:
|
||||
|
||||
```python
|
||||
# List XHR requests
|
||||
requests = list_network_requests(resourceTypes=["xhr", "fetch"])
|
||||
|
||||
# Look for specific endpoints
|
||||
lora_list_requests = [r for r in requests if "/api/list" in r.get("url", "")]
|
||||
assert len(lora_list_requests) > 0, "LoRA list API not called"
|
||||
```
|
||||
193
.agents/skills/lora-manager-e2e/scripts/example_e2e_test.py
Executable file
193
.agents/skills/lora-manager-e2e/scripts/example_e2e_test.py
Executable file
@@ -0,0 +1,193 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Example E2E test demonstrating LoRa Manager testing workflow.
|
||||
|
||||
This script shows how to:
|
||||
1. Start the standalone server
|
||||
2. Use Chrome DevTools MCP to interact with the UI
|
||||
3. Verify functionality end-to-end
|
||||
|
||||
Note: This is a template. Actual execution requires Chrome DevTools MCP.
|
||||
"""
|
||||
|
||||
import subprocess
|
||||
import sys
|
||||
import time
|
||||
|
||||
|
||||
def run_test():
|
||||
"""Run example E2E test flow."""
|
||||
|
||||
print("=" * 60)
|
||||
print("LoRa Manager E2E Test Example")
|
||||
print("=" * 60)
|
||||
|
||||
# Step 1: Start server
|
||||
print("\n[1/5] Starting LoRa Manager standalone server...")
|
||||
result = subprocess.run(
|
||||
[sys.executable, "start_server.py", "--port", "8188", "--wait", "--timeout", "30"],
|
||||
capture_output=True,
|
||||
text=True
|
||||
)
|
||||
if result.returncode != 0:
|
||||
print(f"Failed to start server: {result.stderr}")
|
||||
return 1
|
||||
print("Server ready!")
|
||||
|
||||
# Step 2: Open Chrome (manual step - show command)
|
||||
print("\n[2/5] Open Chrome with debug mode:")
|
||||
print("google-chrome --remote-debugging-port=9222 --user-data-dir=/tmp/chrome-lora-manager http://127.0.0.1:8188/loras")
|
||||
print("(In actual test, this would be automated via MCP)")
|
||||
|
||||
# Step 3: Navigate and verify page load
|
||||
print("\n[3/5] Page Load Verification:")
|
||||
print("""
|
||||
MCP Commands to execute:
|
||||
1. navigate_page(type="url", url="http://127.0.0.1:8188/loras")
|
||||
2. wait_for(text="LoRAs", timeout=10000)
|
||||
3. snapshot = take_snapshot()
|
||||
""")
|
||||
|
||||
# Step 4: Test search functionality
|
||||
print("\n[4/5] Search Functionality Test:")
|
||||
print("""
|
||||
MCP Commands to execute:
|
||||
1. fill(uid="search-input", value="test")
|
||||
2. press_key(key="Enter")
|
||||
3. wait_for(text="Results", timeout=5000)
|
||||
4. result = evaluate_script(function="""
|
||||
() => {
|
||||
const cards = document.querySelectorAll('.lora-card');
|
||||
return { count: cards.length };
|
||||
}
|
||||
""")
|
||||
""")
|
||||
|
||||
# Step 5: Verify API
|
||||
print("\n[5/5] API Verification:")
|
||||
print("""
|
||||
MCP Commands to execute:
|
||||
1. api_result = evaluate_script(function="""
|
||||
async () => {
|
||||
const response = await fetch('/loras/api/list');
|
||||
const data = await response.json();
|
||||
return { count: data.length, status: response.status };
|
||||
}
|
||||
""")
|
||||
2. Verify api_result['status'] == 200
|
||||
""")
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Test flow completed!")
|
||||
print("=" * 60)
|
||||
|
||||
return 0
|
||||
|
||||
|
||||
def example_restart_flow():
|
||||
"""Example: Testing configuration change that requires restart."""
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Example: Server Restart Flow")
|
||||
print("=" * 60)
|
||||
|
||||
print("""
|
||||
Scenario: Change setting and verify after restart
|
||||
|
||||
Steps:
|
||||
1. Navigate to settings page
|
||||
- navigate_page(type="url", url="http://127.0.0.1:8188/settings")
|
||||
|
||||
2. Change a setting (e.g., theme)
|
||||
- fill(uid="theme-select", value="dark")
|
||||
- click(uid="save-settings-button")
|
||||
|
||||
3. Restart server
|
||||
- subprocess.run([python, "start_server.py", "--restart", "--wait"])
|
||||
|
||||
4. Refresh browser
|
||||
- navigate_page(type="reload", ignoreCache=True)
|
||||
- wait_for(text="LoRAs", timeout=15000)
|
||||
|
||||
5. Verify setting persisted
|
||||
- navigate_page(type="url", url="http://127.0.0.1:8188/settings")
|
||||
- theme = evaluate_script(function="() => document.querySelector('#theme-select').value")
|
||||
- assert theme == "dark"
|
||||
""")
|
||||
|
||||
|
||||
def example_modal_interaction():
|
||||
"""Example: Testing modal dialog interaction."""
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Example: Modal Dialog Interaction")
|
||||
print("=" * 60)
|
||||
|
||||
print("""
|
||||
Scenario: Add new LoRA via modal
|
||||
|
||||
Steps:
|
||||
1. Open modal
|
||||
- click(uid="add-lora-button")
|
||||
- wait_for(text="Add LoRA", timeout=3000)
|
||||
|
||||
2. Fill form
|
||||
- fill_form(elements=[
|
||||
{"uid": "lora-name", "value": "Test Character"},
|
||||
{"uid": "lora-path", "value": "/models/test.safetensors"},
|
||||
])
|
||||
|
||||
3. Submit
|
||||
- click(uid="modal-submit-button")
|
||||
|
||||
4. Verify success
|
||||
- wait_for(text="Successfully added", timeout=5000)
|
||||
- snapshot = take_snapshot()
|
||||
""")
|
||||
|
||||
|
||||
def example_network_monitoring():
|
||||
"""Example: Network request monitoring."""
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Example: Network Request Monitoring")
|
||||
print("=" * 60)
|
||||
|
||||
print("""
|
||||
Scenario: Verify API calls during user interaction
|
||||
|
||||
Steps:
|
||||
1. Clear network log (implicit on navigation)
|
||||
- navigate_page(type="url", url="http://127.0.0.1:8188/loras")
|
||||
|
||||
2. Perform action that triggers API call
|
||||
- fill(uid="search-input", value="character")
|
||||
- press_key(key="Enter")
|
||||
|
||||
3. List network requests
|
||||
- requests = list_network_requests(resourceTypes=["xhr", "fetch"])
|
||||
|
||||
4. Find search API call
|
||||
- search_requests = [r for r in requests if "/api/search" in r.get("url", "")]
|
||||
- assert len(search_requests) > 0, "Search API was not called"
|
||||
|
||||
5. Get request details
|
||||
- if search_requests:
|
||||
details = get_network_request(reqid=search_requests[0]["reqid"])
|
||||
- Verify request method, response status, etc.
|
||||
""")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("LoRa Manager E2E Test Examples\n")
|
||||
print("This script demonstrates E2E testing patterns.\n")
|
||||
print("Note: Actual execution requires Chrome DevTools MCP connection.\n")
|
||||
|
||||
run_test()
|
||||
example_restart_flow()
|
||||
example_modal_interaction()
|
||||
example_network_monitoring()
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("All examples shown!")
|
||||
print("=" * 60)
|
||||
169
.agents/skills/lora-manager-e2e/scripts/start_server.py
Executable file
169
.agents/skills/lora-manager-e2e/scripts/start_server.py
Executable file
@@ -0,0 +1,169 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Start or restart LoRa Manager standalone server for E2E testing.
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import subprocess
|
||||
import sys
|
||||
import time
|
||||
import socket
|
||||
import signal
|
||||
import os
|
||||
|
||||
|
||||
def find_server_process(port: int) -> list[int]:
|
||||
"""Find PIDs of processes listening on the given port."""
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["lsof", "-ti", f":{port}"],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
check=False
|
||||
)
|
||||
if result.returncode == 0 and result.stdout.strip():
|
||||
return [int(pid) for pid in result.stdout.strip().split("\n") if pid]
|
||||
except FileNotFoundError:
|
||||
# lsof not available, try netstat
|
||||
try:
|
||||
result = subprocess.run(
|
||||
["netstat", "-tlnp"],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
check=False
|
||||
)
|
||||
pids = []
|
||||
for line in result.stdout.split("\n"):
|
||||
if f":{port}" in line:
|
||||
parts = line.split()
|
||||
for part in parts:
|
||||
if "/" in part:
|
||||
try:
|
||||
pid = int(part.split("/")[0])
|
||||
pids.append(pid)
|
||||
except ValueError:
|
||||
pass
|
||||
return pids
|
||||
except FileNotFoundError:
|
||||
pass
|
||||
return []
|
||||
|
||||
|
||||
def kill_server(port: int) -> None:
|
||||
"""Kill processes using the specified port."""
|
||||
pids = find_server_process(port)
|
||||
for pid in pids:
|
||||
try:
|
||||
os.kill(pid, signal.SIGTERM)
|
||||
print(f"Sent SIGTERM to process {pid}")
|
||||
except ProcessLookupError:
|
||||
pass
|
||||
|
||||
# Wait for processes to terminate
|
||||
time.sleep(1)
|
||||
|
||||
# Force kill if still running
|
||||
pids = find_server_process(port)
|
||||
for pid in pids:
|
||||
try:
|
||||
os.kill(pid, signal.SIGKILL)
|
||||
print(f"Sent SIGKILL to process {pid}")
|
||||
except ProcessLookupError:
|
||||
pass
|
||||
|
||||
|
||||
def is_server_ready(port: int, timeout: float = 0.5) -> bool:
|
||||
"""Check if server is accepting connections."""
|
||||
try:
|
||||
with socket.create_connection(("127.0.0.1", port), timeout=timeout):
|
||||
return True
|
||||
except (socket.timeout, ConnectionRefusedError, OSError):
|
||||
return False
|
||||
|
||||
|
||||
def wait_for_server(port: int, timeout: int = 30) -> bool:
|
||||
"""Wait for server to become ready."""
|
||||
start = time.time()
|
||||
while time.time() - start < timeout:
|
||||
if is_server_ready(port):
|
||||
return True
|
||||
time.sleep(0.5)
|
||||
return False
|
||||
|
||||
|
||||
def main() -> int:
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Start LoRa Manager standalone server for E2E testing"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--port",
|
||||
type=int,
|
||||
default=8188,
|
||||
help="Server port (default: 8188)"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--restart",
|
||||
action="store_true",
|
||||
help="Kill existing server before starting"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--wait",
|
||||
action="store_true",
|
||||
help="Wait for server to be ready before exiting"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--timeout",
|
||||
type=int,
|
||||
default=30,
|
||||
help="Timeout for waiting (default: 30)"
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
# Get project root (parent of .agents directory)
|
||||
script_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
skill_dir = os.path.dirname(script_dir)
|
||||
project_root = os.path.dirname(os.path.dirname(os.path.dirname(skill_dir)))
|
||||
|
||||
# Restart if requested
|
||||
if args.restart:
|
||||
print(f"Killing existing server on port {args.port}...")
|
||||
kill_server(args.port)
|
||||
time.sleep(1)
|
||||
|
||||
# Check if already running
|
||||
if is_server_ready(args.port):
|
||||
print(f"Server already running on port {args.port}")
|
||||
return 0
|
||||
|
||||
# Start server
|
||||
print(f"Starting LoRa Manager standalone server on port {args.port}...")
|
||||
cmd = [sys.executable, "standalone.py", "--port", str(args.port)]
|
||||
|
||||
# Start in background
|
||||
process = subprocess.Popen(
|
||||
cmd,
|
||||
cwd=project_root,
|
||||
stdout=subprocess.PIPE,
|
||||
stderr=subprocess.PIPE,
|
||||
start_new_session=True
|
||||
)
|
||||
|
||||
print(f"Server process started with PID {process.pid}")
|
||||
|
||||
# Wait for ready if requested
|
||||
if args.wait:
|
||||
print(f"Waiting for server to be ready (timeout: {args.timeout}s)...")
|
||||
if wait_for_server(args.port, args.timeout):
|
||||
print(f"Server ready at http://127.0.0.1:{args.port}/loras")
|
||||
return 0
|
||||
else:
|
||||
print(f"Timeout waiting for server")
|
||||
return 1
|
||||
|
||||
print(f"Server starting at http://127.0.0.1:{args.port}/loras")
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
61
.agents/skills/lora-manager-e2e/scripts/wait_for_server.py
Executable file
61
.agents/skills/lora-manager-e2e/scripts/wait_for_server.py
Executable file
@@ -0,0 +1,61 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
Wait for LoRa Manager server to become ready.
|
||||
"""
|
||||
|
||||
import argparse
|
||||
import socket
|
||||
import sys
|
||||
import time
|
||||
|
||||
|
||||
def is_server_ready(port: int, timeout: float = 0.5) -> bool:
|
||||
"""Check if server is accepting connections."""
|
||||
try:
|
||||
with socket.create_connection(("127.0.0.1", port), timeout=timeout):
|
||||
return True
|
||||
except (socket.timeout, ConnectionRefusedError, OSError):
|
||||
return False
|
||||
|
||||
|
||||
def wait_for_server(port: int, timeout: int = 30) -> bool:
|
||||
"""Wait for server to become ready."""
|
||||
start = time.time()
|
||||
while time.time() - start < timeout:
|
||||
if is_server_ready(port):
|
||||
return True
|
||||
time.sleep(0.5)
|
||||
return False
|
||||
|
||||
|
||||
def main() -> int:
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Wait for LoRa Manager server to become ready"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--port",
|
||||
type=int,
|
||||
default=8188,
|
||||
help="Server port (default: 8188)"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--timeout",
|
||||
type=int,
|
||||
default=30,
|
||||
help="Timeout in seconds (default: 30)"
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
print(f"Waiting for server on port {args.port} (timeout: {args.timeout}s)...")
|
||||
|
||||
if wait_for_server(args.port, args.timeout):
|
||||
print(f"Server ready at http://127.0.0.1:{args.port}/loras")
|
||||
return 0
|
||||
else:
|
||||
print(f"Timeout: Server not ready after {args.timeout}s")
|
||||
return 1
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
4
.github/FUNDING.yml
vendored
4
.github/FUNDING.yml
vendored
@@ -1,5 +1,5 @@
|
||||
# These are supported funding model platforms
|
||||
|
||||
patreon: PixelPawsAI
|
||||
ko_fi: pixelpawsai
|
||||
custom: ['paypal.me/pixelpawsai']
|
||||
patreon: PixelPawsAI
|
||||
custom: ['paypal.me/pixelpawsai', 'https://afdian.com/a/pixelpawsai']
|
||||
|
||||
93
.github/workflows/backend-tests.yml
vendored
Normal file
93
.github/workflows/backend-tests.yml
vendored
Normal file
@@ -0,0 +1,93 @@
|
||||
name: Backend Tests
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
- master
|
||||
paths:
|
||||
- 'py/**'
|
||||
- 'standalone.py'
|
||||
- 'tests/**'
|
||||
- 'requirements.txt'
|
||||
- 'requirements-dev.txt'
|
||||
- 'pyproject.toml'
|
||||
- 'pytest.ini'
|
||||
- '.github/workflows/backend-tests.yml'
|
||||
pull_request:
|
||||
paths:
|
||||
- 'py/**'
|
||||
- 'standalone.py'
|
||||
- 'tests/**'
|
||||
- 'requirements.txt'
|
||||
- 'requirements-dev.txt'
|
||||
- 'pyproject.toml'
|
||||
- 'pytest.ini'
|
||||
- '.github/workflows/backend-tests.yml'
|
||||
|
||||
jobs:
|
||||
pytest:
|
||||
name: Run pytest with coverage
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Check out repository
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Python 3.11
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: '3.11'
|
||||
cache: 'pip'
|
||||
cache-dependency-path: |
|
||||
requirements.txt
|
||||
requirements-dev.txt
|
||||
|
||||
- name: Install dependencies
|
||||
run: |
|
||||
python -m pip install --upgrade pip
|
||||
pip install -r requirements-dev.txt
|
||||
|
||||
- name: Verify symlink support
|
||||
run: |
|
||||
python - <<'PY'
|
||||
import os
|
||||
import pathlib
|
||||
import tempfile
|
||||
|
||||
root = pathlib.Path(tempfile.mkdtemp(prefix="lm-symlink-check-"))
|
||||
target = root / "target"
|
||||
target.mkdir()
|
||||
link = root / "link"
|
||||
try:
|
||||
link.symlink_to(target, target_is_directory=True)
|
||||
except OSError as exc:
|
||||
raise SystemExit(f"Failed to create directory symlink in CI: {exc}")
|
||||
|
||||
is_link = os.path.islink(link)
|
||||
is_dir = os.path.isdir(link)
|
||||
realpath = os.path.realpath(link)
|
||||
print(f"islink={is_link} isdir={is_dir} realpath={realpath}")
|
||||
if not (is_link and is_dir and realpath == str(target)):
|
||||
raise SystemExit("Directory symlink is not functioning correctly in CI; aborting.")
|
||||
PY
|
||||
|
||||
- name: Run pytest with coverage
|
||||
env:
|
||||
COVERAGE_FILE: coverage/backend/.coverage
|
||||
run: |
|
||||
mkdir -p coverage/backend
|
||||
python -m pytest \
|
||||
--cov=py \
|
||||
--cov=standalone \
|
||||
--cov-report=term-missing \
|
||||
--cov-report=xml:coverage/backend/coverage.xml \
|
||||
--cov-report=html:coverage/backend/html \
|
||||
--cov-report=json:coverage/backend/coverage.json
|
||||
|
||||
- name: Upload coverage artifact
|
||||
if: always()
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: backend-coverage
|
||||
path: coverage/backend
|
||||
if-no-files-found: warn
|
||||
52
.github/workflows/frontend-tests.yml
vendored
Normal file
52
.github/workflows/frontend-tests.yml
vendored
Normal file
@@ -0,0 +1,52 @@
|
||||
name: Frontend Tests
|
||||
|
||||
on:
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
- master
|
||||
paths:
|
||||
- 'package.json'
|
||||
- 'package-lock.json'
|
||||
- 'vitest.config.js'
|
||||
- 'tests/frontend/**'
|
||||
- 'static/js/**'
|
||||
- 'scripts/run_frontend_coverage.js'
|
||||
- '.github/workflows/frontend-tests.yml'
|
||||
pull_request:
|
||||
paths:
|
||||
- 'package.json'
|
||||
- 'package-lock.json'
|
||||
- 'vitest.config.js'
|
||||
- 'tests/frontend/**'
|
||||
- 'static/js/**'
|
||||
- 'scripts/run_frontend_coverage.js'
|
||||
- '.github/workflows/frontend-tests.yml'
|
||||
|
||||
jobs:
|
||||
vitest:
|
||||
name: Run Vitest with coverage
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Check out repository
|
||||
uses: actions/checkout@v4
|
||||
|
||||
- name: Use Node.js 20
|
||||
uses: actions/setup-node@v4
|
||||
with:
|
||||
node-version: 20
|
||||
cache: 'npm'
|
||||
|
||||
- name: Install dependencies
|
||||
run: npm ci
|
||||
|
||||
- name: Run frontend tests with coverage
|
||||
run: npm run test:coverage
|
||||
|
||||
- name: Upload coverage artifact
|
||||
if: always()
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: frontend-coverage
|
||||
path: coverage/frontend
|
||||
if-no-files-found: warn
|
||||
11
.gitignore
vendored
11
.gitignore
vendored
@@ -1,4 +1,5 @@
|
||||
__pycache__/
|
||||
.pytest_cache/
|
||||
settings.json
|
||||
path_mappings.yaml
|
||||
output/*
|
||||
@@ -8,3 +9,13 @@ cache/
|
||||
civitai/
|
||||
node_modules/
|
||||
coverage/
|
||||
.coverage
|
||||
model_cache/
|
||||
|
||||
# agent
|
||||
.opencode/
|
||||
|
||||
# Vue widgets development cache (but keep build output)
|
||||
vue-widgets/node_modules/
|
||||
vue-widgets/.vite/
|
||||
vue-widgets/dist/
|
||||
|
||||
199
AGENTS.md
199
AGENTS.md
@@ -1,19 +1,192 @@
|
||||
# Repository Guidelines
|
||||
# AGENTS.md
|
||||
|
||||
## Project Structure & Module Organization
|
||||
ComfyUI LoRA Manager pairs a Python backend with lightweight browser scripts. Backend modules live in `py/`, organized by responsibility: HTTP entry points under `routes/`, feature logic in `services/`, reusable helpers within `utils/`, and custom nodes in `nodes/`. Front-end widgets that extend the ComfyUI interface sit in `web/comfyui/`, while static images and templates are in `static/` and `templates/`. Shared localization files are stored in `locales/`, with workflow examples under `example_workflows/`. Tests currently reside alongside the source (`test_i18n.py`) until a dedicated `tests/` folder is introduced.
|
||||
This file provides guidance for agentic coding assistants working in this repository.
|
||||
|
||||
## Build, Test, and Development Commands
|
||||
Install dependencies with `pip install -r requirements.txt` from the repo root. Launch the standalone server for iterative work via `python standalone.py --port 8188`; ComfyUI users can also load the extension directly through ComfyUI's custom node manager. Run backend checks with `python -m pytest test_i18n.py`, and target new test files explicitly (e.g. `python -m pytest tests/test_recipes.py` once added). Use `python scripts/sync_translation_keys.py` to reconcile locale keys after updating UI strings.
|
||||
## Development Commands
|
||||
|
||||
## Coding Style & Naming Conventions
|
||||
Follow PEP 8 with four-space indentation and descriptive snake_case module/function names, mirroring files such as `py/services/settings_manager.py`. Classes remain PascalCase, constants UPPER_SNAKE_CASE, and loggers retrieved via `logging.getLogger(__name__)`. Prefer explicit type hints for new public APIs and docstrings that clarify side effects. JavaScript in `web/comfyui/` is modern ES modules; keep imports relative, favor camelCase functions, and mirror existing file suffixes like `_widget.js` for UI components.
|
||||
### Backend Development
|
||||
|
||||
## Testing Guidelines
|
||||
Extend pytest coverage by co-locating tests near the code under test or in `tests/` with names like `test_<feature>.py`. When introducing new routes or services, add regression cases that mock ComfyUI dependencies (see the standalone mocking helpers in `standalone.py`). Prioritize deterministic fixtures for filesystem interactions and ensure translations include coverage when adding new locale keys. Always run `python -m pytest` before submitting work.
|
||||
```bash
|
||||
# Install dependencies
|
||||
pip install -r requirements.txt
|
||||
pip install -r requirements-dev.txt
|
||||
|
||||
## Commit & Pull Request Guidelines
|
||||
Commits follow the conventional pattern seen in `git log` (`feat(scope):`, `fix(scope):`, `chore(scope):`). Keep messages imperative and scoped to a single change. Pull requests should summarize the problem, detail the solution, list manual test evidence, and link any GitHub issues. Include UI screenshots or GIFs when front-end behavior changes, and call out migration steps (e.g., settings updates) in the PR description.
|
||||
# Run standalone server (port 8188 by default)
|
||||
python standalone.py --port 8188
|
||||
|
||||
# Run all backend tests
|
||||
pytest
|
||||
|
||||
# Run specific test file
|
||||
pytest tests/test_recipes.py
|
||||
|
||||
# Run specific test function
|
||||
pytest tests/test_recipes.py::test_function_name
|
||||
|
||||
# Run backend tests with coverage
|
||||
COVERAGE_FILE=coverage/backend/.coverage pytest \
|
||||
--cov=py \
|
||||
--cov=standalone \
|
||||
--cov-report=term-missing \
|
||||
--cov-report=html:coverage/backend/html \
|
||||
--cov-report=xml:coverage/backend/coverage.xml \
|
||||
--cov-report=json:coverage/backend/coverage.json
|
||||
```
|
||||
|
||||
### Frontend Development
|
||||
|
||||
```bash
|
||||
# Install frontend dependencies
|
||||
npm install
|
||||
|
||||
# Run frontend tests
|
||||
npm test
|
||||
|
||||
# Run frontend tests in watch mode
|
||||
npm run test:watch
|
||||
|
||||
# Run frontend tests with coverage
|
||||
npm run test:coverage
|
||||
```
|
||||
|
||||
## Python Code Style
|
||||
|
||||
### Imports
|
||||
|
||||
- Use `from __future__ import annotations` for forward references in type hints
|
||||
- Group imports: standard library, third-party, local (separated by blank lines)
|
||||
- Use absolute imports within `py/` package: `from ..services import X`
|
||||
- Mock ComfyUI dependencies in tests using `tests/conftest.py` patterns
|
||||
|
||||
### Formatting & Types
|
||||
|
||||
- PEP 8 with 4-space indentation
|
||||
- Type hints required for function signatures and class attributes
|
||||
- Use `TYPE_CHECKING` guard for type-checking-only imports
|
||||
- Prefer dataclasses for simple data containers
|
||||
- Use `Optional[T]` for nullable types, `Union[T, None]` only when necessary
|
||||
|
||||
### Naming Conventions
|
||||
|
||||
- Files: `snake_case.py` (e.g., `model_scanner.py`, `lora_service.py`)
|
||||
- Classes: `PascalCase` (e.g., `ModelScanner`, `LoraService`)
|
||||
- Functions/variables: `snake_case` (e.g., `get_instance`, `model_type`)
|
||||
- Constants: `UPPER_SNAKE_CASE` (e.g., `VALID_LORA_TYPES`)
|
||||
- Private members: `_single_underscore` (protected), `__double_underscore` (name-mangled)
|
||||
|
||||
### Error Handling
|
||||
|
||||
- Use `logging.getLogger(__name__)` for module-level loggers
|
||||
- Define custom exceptions in `py/services/errors.py`
|
||||
- Use `asyncio.Lock` for thread-safe singleton patterns
|
||||
- Raise specific exceptions with descriptive messages
|
||||
- Log errors at appropriate levels (DEBUG, INFO, WARNING, ERROR, CRITICAL)
|
||||
|
||||
### Async Patterns
|
||||
|
||||
- Use `async def` for I/O-bound operations
|
||||
- Mark async tests with `@pytest.mark.asyncio`
|
||||
- Use `async with` for context managers
|
||||
- Singleton pattern with class-level locks: see `ModelScanner.get_instance()`
|
||||
- Use `aiohttp.web.Response` for HTTP responses
|
||||
|
||||
### Testing Patterns
|
||||
|
||||
- Use `pytest` with `--import-mode=importlib`
|
||||
- Fixtures in `tests/conftest.py` handle ComfyUI mocking
|
||||
- Use `@pytest.mark.no_settings_dir_isolation` for tests needing real paths
|
||||
- Test files: `tests/test_*.py`
|
||||
- Use `tmp_path_factory` for temporary directory isolation
|
||||
|
||||
## JavaScript Code Style
|
||||
|
||||
### Imports & Modules
|
||||
|
||||
- ES modules with `import`/`export`
|
||||
- Use `import { app } from "../../scripts/app.js"` for ComfyUI integration
|
||||
- Export named functions/classes: `export function foo() {}`
|
||||
- Widget files use `*_widget.js` suffix
|
||||
|
||||
### Naming & Formatting
|
||||
|
||||
- camelCase for functions, variables, object properties
|
||||
- PascalCase for classes/constructors
|
||||
- Constants: `UPPER_SNAKE_CASE` (e.g., `CONVERTED_TYPE`)
|
||||
- Files: `snake_case.js` or `kebab-case.js`
|
||||
- 2-space indentation preferred (follow existing file conventions)
|
||||
|
||||
### Widget Development
|
||||
|
||||
- Use `app.registerExtension()` to register ComfyUI extensions
|
||||
- Use `node.addDOMWidget(name, type, element, options)` for custom widgets
|
||||
- Event handlers attached via `addEventListener` or widget callbacks
|
||||
- See `web/comfyui/utils.js` for shared utilities
|
||||
|
||||
## Architecture Patterns
|
||||
|
||||
### Service Layer
|
||||
|
||||
- Use `ServiceRegistry` singleton for dependency injection
|
||||
- Services follow singleton pattern via `get_instance()` class method
|
||||
- Separate scanners (discovery) from services (business logic)
|
||||
- Handlers in `py/routes/handlers/` implement route logic
|
||||
|
||||
### Model Types
|
||||
|
||||
- BaseModelService is abstract base for LoRA, Checkpoint, Embedding services
|
||||
- ModelScanner provides file discovery and hash-based deduplication
|
||||
- Persistent cache in SQLite via `PersistentModelCache`
|
||||
- Metadata sync from CivitAI/CivArchive via `MetadataSyncService`
|
||||
|
||||
### Routes & Handlers
|
||||
|
||||
- Route registrars organize endpoints by domain: `ModelRouteRegistrar`, etc.
|
||||
- Handlers are pure functions taking dependencies as parameters
|
||||
- Use `WebSocketManager` for real-time progress updates
|
||||
- Return `aiohttp.web.json_response` or `web.Response`
|
||||
|
||||
### Recipe System
|
||||
|
||||
- Base metadata in `py/recipes/base.py`
|
||||
- Enrichment adds model metadata: `RecipeEnrichmentService`
|
||||
- Parsers for different formats in `py/recipes/parsers/`
|
||||
|
||||
## Important Notes
|
||||
|
||||
- Always use English for comments (per copilot-instructions.md)
|
||||
- Dual mode: ComfyUI plugin (uses folder_paths) vs standalone (reads settings.json)
|
||||
- Detection: `os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1"`
|
||||
- Settings auto-saved in user directory or portable mode
|
||||
- WebSocket broadcasts for real-time updates (downloads, scans)
|
||||
- Symlink handling requires normalized paths
|
||||
- API endpoints follow `/loras/*`, `/checkpoints/*`, `/embeddings/*` patterns
|
||||
- Run `python scripts/sync_translation_keys.py` after UI string updates
|
||||
|
||||
## Frontend UI Architecture
|
||||
|
||||
This project has two distinct UI systems:
|
||||
|
||||
### 1. Standalone Lora Manager Web UI
|
||||
- Location: `./static/` and `./templates/`
|
||||
- Purpose: Full-featured web application for managing LoRA models
|
||||
- Tech stack: Vanilla JS + CSS, served by the standalone server
|
||||
- Development: Uses npm for frontend testing (`npm test`, `npm run test:watch`, etc.)
|
||||
|
||||
### 2. ComfyUI Custom Node Widgets
|
||||
- Location: `./web/comfyui/`
|
||||
- Purpose: Widgets and UI logic that ComfyUI loads as custom node extensions
|
||||
- Tech stack: Vanilla JS + Vue.js widgets (in `./vue-widgets/` and built to `./web/comfyui/vue-widgets/`)
|
||||
- Widget styling: Primary styles in `./web/comfyui/lm_styles.css` (NOT `./static/css/`)
|
||||
- Development: No npm build step for these widgets (Vue widgets use build system)
|
||||
|
||||
### Widget Development Guidelines
|
||||
- Use `app.registerExtension()` to register ComfyUI extensions (ComfyUI integration layer)
|
||||
- Use `node.addDOMWidget()` for custom DOM widgets
|
||||
- Widget styles should follow the patterns in `./web/comfyui/lm_styles.css`
|
||||
- Selected state: `rgba(66, 153, 225, 0.3)` background, `rgba(66, 153, 225, 0.6)` border
|
||||
- Hover state: `rgba(66, 153, 225, 0.2)` background
|
||||
- Color palette matches the Lora Manager accent color (blue #4299e1)
|
||||
- Use oklch() for color values when possible (defined in `./static/css/base.css`)
|
||||
- Vue widget components are in `./vue-widgets/src/components/` and built to `./web/comfyui/vue-widgets/`
|
||||
- When modifying widget styles, check `./web/comfyui/lm_styles.css` for consistency with other ComfyUI widgets
|
||||
|
||||
## Configuration & Localization Tips
|
||||
Sample configuration defaults live in `settings.json.example`; copy it to `settings.json` and adjust model directories before running the standalone server. Whenever you add UI text, update `locales/<lang>.json` and run the translation sync script. Store reference assets in `civitai/` or `docs/` rather than mixing them with production templates, keeping the runtime folders (`static/`, `templates/`) deploy-ready.
|
||||
|
||||
211
CLAUDE.md
Normal file
211
CLAUDE.md
Normal file
@@ -0,0 +1,211 @@
|
||||
# CLAUDE.md
|
||||
|
||||
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
|
||||
|
||||
## Overview
|
||||
|
||||
ComfyUI LoRA Manager is a comprehensive LoRA management system for ComfyUI that combines a Python backend with browser-based widgets. It provides model organization, downloading from CivitAI/CivArchive, recipe management, and one-click workflow integration.
|
||||
|
||||
## Development Commands
|
||||
|
||||
### Backend Development
|
||||
```bash
|
||||
# Install dependencies
|
||||
pip install -r requirements.txt
|
||||
|
||||
# Install development dependencies (for testing)
|
||||
pip install -r requirements-dev.txt
|
||||
|
||||
# Run standalone server (port 8188 by default)
|
||||
python standalone.py --port 8188
|
||||
|
||||
# Run backend tests with coverage
|
||||
COVERAGE_FILE=coverage/backend/.coverage pytest \
|
||||
--cov=py \
|
||||
--cov=standalone \
|
||||
--cov-report=term-missing \
|
||||
--cov-report=html:coverage/backend/html \
|
||||
--cov-report=xml:coverage/backend/coverage.xml \
|
||||
--cov-report=json:coverage/backend/coverage.json
|
||||
|
||||
# Run specific test file
|
||||
pytest tests/test_recipes.py
|
||||
```
|
||||
|
||||
### Frontend Development
|
||||
```bash
|
||||
# Install frontend dependencies
|
||||
npm install
|
||||
|
||||
# Run frontend tests
|
||||
npm test
|
||||
|
||||
# Run frontend tests in watch mode
|
||||
npm run test:watch
|
||||
|
||||
# Run frontend tests with coverage
|
||||
npm run test:coverage
|
||||
```
|
||||
|
||||
### Localization
|
||||
```bash
|
||||
# Sync translation keys after UI string updates
|
||||
python scripts/sync_translation_keys.py
|
||||
```
|
||||
|
||||
## Architecture
|
||||
|
||||
### Backend Structure (Python)
|
||||
|
||||
**Core Entry Points:**
|
||||
- `__init__.py` - ComfyUI plugin entry point, registers nodes and routes
|
||||
- `standalone.py` - Standalone server that mocks ComfyUI dependencies
|
||||
- `py/lora_manager.py` - Main LoraManager class that registers HTTP routes
|
||||
|
||||
**Service Layer** (`py/services/`):
|
||||
- `ServiceRegistry` - Singleton service registry for dependency management
|
||||
- `ModelServiceFactory` - Factory for creating model services (LoRA, Checkpoint, Embedding)
|
||||
- Scanner services (`lora_scanner.py`, `checkpoint_scanner.py`, `embedding_scanner.py`) - Model file discovery and indexing
|
||||
- `model_scanner.py` - Base scanner with hash-based deduplication and metadata extraction
|
||||
- `persistent_model_cache.py` - SQLite-based cache for model metadata
|
||||
- `metadata_sync_service.py` - Syncs metadata from CivitAI/CivArchive APIs
|
||||
- `civitai_client.py` / `civarchive_client.py` - API clients for external services
|
||||
- `downloader.py` / `download_manager.py` - Model download orchestration
|
||||
- `recipe_scanner.py` - Recipe file management and image association
|
||||
- `settings_manager.py` - Application settings with migration support
|
||||
- `websocket_manager.py` - WebSocket broadcasting for real-time updates
|
||||
- `use_cases/` - Business logic orchestration (auto-organize, bulk refresh, downloads)
|
||||
|
||||
**Routes Layer** (`py/routes/`):
|
||||
- Route registrars organize endpoints by domain (models, recipes, previews, example images, updates)
|
||||
- `handlers/` - Request handlers implementing business logic
|
||||
- Routes use aiohttp and integrate with ComfyUI's PromptServer
|
||||
|
||||
**Recipe System** (`py/recipes/`):
|
||||
- `base.py` - Base recipe metadata structure
|
||||
- `enrichment.py` - Enriches recipes with model metadata
|
||||
- `merger.py` - Merges recipe data from multiple sources
|
||||
- `parsers/` - Parsers for different recipe formats (PNG, JSON, workflow)
|
||||
|
||||
**Custom Nodes** (`py/nodes/`):
|
||||
- `lora_loader.py` - LoRA loader nodes with preset support
|
||||
- `save_image.py` - Enhanced save image with pattern-based filenames
|
||||
- `trigger_word_toggle.py` - Toggle trigger words in prompts
|
||||
- `lora_stacker.py` - Stack multiple LoRAs
|
||||
- `prompt.py` - Prompt node with autocomplete
|
||||
- `wanvideo_lora_select.py` - WanVideo-specific LoRA selection
|
||||
|
||||
**Configuration** (`py/config.py`):
|
||||
- Manages folder paths for models, checkpoints, embeddings
|
||||
- Handles symlink mappings for complex directory structures
|
||||
- Auto-saves paths to settings.json in ComfyUI mode
|
||||
|
||||
### Frontend Structure (JavaScript)
|
||||
|
||||
**ComfyUI Widgets** (`web/comfyui/`):
|
||||
- Vanilla JavaScript ES modules extending ComfyUI's LiteGraph-based UI
|
||||
- `loras_widget.js` - Main LoRA selection widget with preview
|
||||
- `loras_widget_events.js` - Event handling for widget interactions
|
||||
- `autocomplete.js` - Autocomplete for trigger words and embeddings
|
||||
- `preview_tooltip.js` - Preview tooltip for model cards
|
||||
- `top_menu_extension.js` - Adds "Launch LoRA Manager" menu item
|
||||
- `trigger_word_highlight.js` - Syntax highlighting for trigger words
|
||||
- `utils.js` - Shared utilities and API helpers
|
||||
|
||||
**Widget Development:**
|
||||
- Widgets use `app.registerExtension` and `getCustomWidgets` hooks
|
||||
- `node.addDOMWidget(name, type, element, options)` embeds HTML in nodes
|
||||
- See `docs/dom_widget_dev_guide.md` for complete DOMWidget development guide
|
||||
|
||||
**Web Source** (`web-src/`):
|
||||
- Modern frontend components (if migrating from static)
|
||||
- `components/` - Reusable UI components
|
||||
- `styles/` - CSS styling
|
||||
|
||||
### Key Patterns
|
||||
|
||||
**Dual Mode Operation:**
|
||||
- ComfyUI plugin mode: Integrates with ComfyUI's PromptServer, uses folder_paths
|
||||
- Standalone mode: Mocks ComfyUI dependencies via `standalone.py`, reads paths from settings.json
|
||||
- Detection: `os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1"`
|
||||
|
||||
**Settings Management:**
|
||||
- Settings stored in user directory (via `platformdirs`) or portable mode (in repo)
|
||||
- Migration system tracks settings schema version
|
||||
- Template in `settings.json.example` defines defaults
|
||||
|
||||
**Model Scanning Flow:**
|
||||
1. Scanner walks folder paths, computes file hashes
|
||||
2. Hash-based deduplication prevents duplicate processing
|
||||
3. Metadata extracted from safetensors headers
|
||||
4. Persistent cache stores results in SQLite
|
||||
5. Background sync fetches CivitAI/CivArchive metadata
|
||||
6. WebSocket broadcasts updates to connected clients
|
||||
|
||||
**Recipe System:**
|
||||
- Recipes store LoRA combinations with parameters
|
||||
- Supports import from workflow JSON, PNG metadata
|
||||
- Images associated with recipes via sibling file detection
|
||||
- Enrichment adds model metadata for display
|
||||
|
||||
**Frontend-Backend Communication:**
|
||||
- REST API for CRUD operations
|
||||
- WebSocket for real-time progress updates (downloads, scans)
|
||||
- API endpoints follow `/loras/*` pattern
|
||||
|
||||
## Code Style
|
||||
|
||||
**Python:**
|
||||
- PEP 8 with 4-space indentation
|
||||
- snake_case for files, functions, variables
|
||||
- PascalCase for classes
|
||||
- Type hints preferred
|
||||
- English comments only (per copilot-instructions.md)
|
||||
- Loggers via `logging.getLogger(__name__)`
|
||||
|
||||
**JavaScript:**
|
||||
- ES modules with camelCase
|
||||
- Files use `*_widget.js` suffix for ComfyUI widgets
|
||||
- Prefer vanilla JS, avoid framework dependencies
|
||||
|
||||
## Testing
|
||||
|
||||
**Backend Tests:**
|
||||
- pytest with `--import-mode=importlib`
|
||||
- Test files: `tests/test_*.py`
|
||||
- Fixtures in `tests/conftest.py`
|
||||
- Mock ComfyUI dependencies using standalone.py patterns
|
||||
- Markers: `@pytest.mark.asyncio` for async tests, `@pytest.mark.no_settings_dir_isolation` for real paths
|
||||
|
||||
**Frontend Tests:**
|
||||
- Vitest with jsdom environment
|
||||
- Test files: `tests/frontend/**/*.test.js`
|
||||
- Setup in `tests/frontend/setup.js`
|
||||
- Coverage via `npm run test:coverage`
|
||||
|
||||
## Important Notes
|
||||
|
||||
**Settings Location:**
|
||||
- ComfyUI mode: Auto-saves folder paths to user settings directory
|
||||
- Standalone mode: Use `settings.json` (copy from `settings.json.example`)
|
||||
- Portable mode: Set `"use_portable_settings": true` in settings.json
|
||||
|
||||
**API Integration:**
|
||||
- CivitAI API key required for downloads (add to settings)
|
||||
- CivArchive API used as fallback for deleted models
|
||||
- Metadata archive database available for offline metadata
|
||||
|
||||
**Symlink Handling:**
|
||||
- Config scans symlinks to map virtual paths to physical locations
|
||||
- Preview validation uses normalized preview root paths
|
||||
- Fingerprinting prevents redundant symlink rescans
|
||||
|
||||
**ComfyUI Node Development:**
|
||||
- Nodes defined in `py/nodes/`, registered in `__init__.py`
|
||||
- Frontend widgets in `web/comfyui/`, matched by node type
|
||||
- Use `WEB_DIRECTORY = "./web/comfyui"` convention
|
||||
|
||||
**Recipe Image Association:**
|
||||
- Recipes scan for sibling images in same directory
|
||||
- Supports repair/migration of recipe image paths
|
||||
- See `py/services/recipe_scanner.py` for implementation details
|
||||
119
README.md
119
README.md
@@ -34,7 +34,53 @@ Enhance your Civitai browsing experience with our companion browser extension! S
|
||||
|
||||
## Release Notes
|
||||
|
||||
### v0.9.3
|
||||
### v0.9.15
|
||||
* **Filter Presets** - Save filter combinations as presets for quick switching and reapplication.
|
||||
* **Bug Fixes** - Fixed various bugs for improved stability.
|
||||
|
||||
### v0.9.14
|
||||
* **LoRA Cycler Node** - Introduced a new LoRA Cycler node that enables iteration through specified LoRAs with support for repeat count and pause iteration functionality. Refer to the new "Lora Cycler" template workflow for concrete example.
|
||||
* **Enhanced Prompt Node with Tag Autocomplete** - Enhanced the Prompt node with comprehensive tag autocomplete based on merged Danbooru + e621 tags. Supports tag search and autocomplete functionality. Implemented a command system with shortcuts like `/char` or `/artist` for category-specific tag searching. Added `/ac` or `/noac` commands to quickly enable or disable autocomplete. Refer to the "Lora Manager Basic" template workflow in ComfyUI -> Templates -> ComfyUI-Lora-Manager for detailed tips.
|
||||
* **Bug Fixes & Stability** - Addressed multiple bugs and improved overall stability.
|
||||
|
||||
### v0.9.12
|
||||
* **LoRA Randomizer System** - Introduced a comprehensive LoRA randomization system featuring LoRA Pool and LoRA Randomizer nodes for flexible and dynamic generation workflows.
|
||||
* **LoRA Randomizer Template** - Refer to the new "LoRA Randomizer" template workflow for detailed examples of flexible randomization modes, lock & reuse options, and other features.
|
||||
* **Recipe Folders** - Introduced a folder system for the Recipes page, allowing users to freely organize recipes just like they do with models.
|
||||
* **Recipe Bulk Operations** - Added bulk mode support for batch moving, deleting, and setting base models for selected recipes with intuitive controls like click-and-drag selection, drag-to-folder, and Ctrl+A (Select All).
|
||||
* **Prompt Search & Sorting** - Search recipes by prompt content and sort by Recipe Name, Imported Date, or LoRA Count for better browsing.
|
||||
* **Recipe Favorites** - Mark specific recipes as favorites for quick access.
|
||||
* **Video Recipe Support** - Enabled support for video recipes (import via LM extension or URL; video file import not supported).
|
||||
* **Performance Improvements** - Fixed performance issues for dramatically improved startup and loading speed. After first scan, subsequent loads are instant regardless of collection size.
|
||||
* **ComfyUI Nodes 2.0 Support** - Basic support for ComfyUI Nodes 2.0.
|
||||
|
||||
### v0.9.10
|
||||
* **Smarter Update Matching** - Users can now choose to check and group updates by matching base model only or with no base-model constraint; version lists also support toggling between same-base versions or all versions.
|
||||
* **Flexible Tag Filtering** - The filter panel now supports tag exclusion: click a tag to include, click again to exclude, and click a third time to clear, enabling stronger and more flexible tag filters.
|
||||
* **License Visibility & Controls** - Model detail headers and ComfyUI preview popups now show Civitai license icons. The filter panel gains license include/exclude options, and a new global context menu action, "Refresh license metadata," fetches missing license data.
|
||||
* **Recipe Improvements** - Recipes now allow importing with zero LoRAs, and recipe detail pages show the related checkpoint for easier reference.
|
||||
* **Better ZIP Downloads** - When downloading models packaged in ZIPs, model files are extracted into the target model folder; ZIPs containing multiple model files (e.g., WanVideo high/low LoRA pairs) are added as separate models.
|
||||
* **Template Workflow Update** - Refreshed the "Illustrious Pony Example" template workflow with usage guidance for each LoRA Manager node.
|
||||
* **Bug Fixes & Stability** - General fixes and stability improvements.
|
||||
|
||||
### v0.9.9
|
||||
* **Check for Updates Feature** - Users can now check for updates for all models or selected models in bulk mode. Models with available updates will display an "update available" badge on their model card, and users can filter to show only models with updates.
|
||||
* **Model Versions Management** - Added a new Versions tab in the model modal that centralizes all versions of a model, providing download, delete, and ignore update functions.
|
||||
* **Send Checkpoint to ComfyUI** - Users can now click the send button on a checkpoint card to send the checkpoint directly to the current workflow's checkpoint or diffusion model loader node in ComfyUI.
|
||||
* **Customizable Model Card Display** - Added a new setting that allows users to choose whether to display the model name or filename on model cards.
|
||||
* **New Path Template Placeholders** - Added new path template placeholders: `{model_name}` and `{version_name}` for more flexible organization.
|
||||
* **ComfyUI Auto Path Correction Setting** - Added a new setting within ComfyUI to enable or disable the auto path correction feature.
|
||||
|
||||
### v0.9.8
|
||||
* **Full CivArchive API Support** - Added complete support for the CivArchive API as a fallback metadata source beyond Civitai API. Models deleted from Civitai can now still retrieve metadata through the CivArchive API.
|
||||
* **Download Models from CivArchive** - Added support for downloading models directly from CivArchive, similar to downloading from Civitai. Simply click the Download button and paste the model URL to download the corresponding model.
|
||||
* **Custom Priority Tags** - Introduced Custom Priority Tags feature, allowing users to define custom priority tags. These tags will appear as suggestions when editing tags or during auto organization/download using default paths, providing more precise and controlled folder organization. [Guide](https://github.com/willmiao/ComfyUI-Lora-Manager/wiki/Priority-Tags-Configuration-Guide)
|
||||
* **Drag and Drop Tag Reordering** - Added drag and drop functionality to reorder tags in the tags edit mode for improved usability.
|
||||
* **Download Control in Example Images Panel** - Added stop control in the Download Example Images Panel for better download management.
|
||||
* **Prompt (LoraManager) Node with Autocomplete** - Added new Prompt (LoraManager) node with autocomplete feature for adding embeddings.
|
||||
* **Lora Manager Nodes in Subgraphs** - Lora Manager nodes now support being placed within subgraphs for more flexible workflow organization.
|
||||
|
||||
### v0.9.6
|
||||
* **Metadata Archive Database Support** - Added the ability to download and utilize a metadata archive database, enabling access to metadata for models that have been deleted from CivitAI.
|
||||
* **App-Level Proxy Settings** - Introduced support for configuring a global proxy within the application, making it easier to use the manager behind network restrictions.
|
||||
* **Bug Fixes** - Various bug fixes for improved stability and reliability.
|
||||
@@ -54,34 +100,6 @@ Enhance your Civitai browsing experience with our companion browser extension! S
|
||||
* **Automatic Filename Conflict Resolution** - Implemented automatic file renaming (`original name + short hash`) to prevent conflicts when downloading or moving models.
|
||||
* **Performance Optimizations & Bug Fixes** - Various performance improvements and bug fixes for a more stable and responsive experience.
|
||||
|
||||
### v0.8.30
|
||||
* **Automatic Model Path Correction** - Added auto-correction for model paths in built-in nodes such as Load Checkpoint, Load Diffusion Model, Load LoRA, and other custom nodes with similar functionality. Workflows containing outdated or incorrect model paths will now be automatically updated to reflect the current location of your models.
|
||||
* **Node UI Enhancements** - Improved node interface for a smoother and more intuitive user experience.
|
||||
* **Bug Fixes** - Addressed various bugs to enhance stability and reliability.
|
||||
|
||||
### v0.8.29
|
||||
* **Enhanced Recipe Imports** - Improved recipe importing with new target folder selection, featuring path input autocomplete and interactive folder tree navigation. Added a "Use Default Path" option when downloading missing LoRAs.
|
||||
* **WanVideo Lora Select Node Update** - Updated the WanVideo Lora Select node with a 'merge_loras' option to match the counterpart node in the WanVideoWrapper node package.
|
||||
* **Autocomplete Conflict Resolution** - Resolved an autocomplete feature conflict in LoRA nodes with pysssss autocomplete.
|
||||
* **Improved Download Functionality** - Enhanced download functionality with resumable downloads and improved error handling.
|
||||
* **Bug Fixes** - Addressed several bugs for improved stability and performance.
|
||||
|
||||
### v0.8.28
|
||||
* **Autocomplete for Node Inputs** - Instantly find and add LoRAs by filename directly in Lora Loader, Lora Stacker, and WanVideo Lora Select nodes. Autocomplete suggestions include preview tooltips and preset weights, allowing you to quickly select LoRAs without opening the LoRA Manager UI.
|
||||
* **Duplicate Notification Control** - Added a switch to duplicates mode, enabling users to turn off duplicate model notifications for a more streamlined experience.
|
||||
* **Download Example Images from Context Menu** - Introduced a new context menu option to download example images for individual models.
|
||||
|
||||
### v0.8.27
|
||||
* **User Experience Enhancements** - Improved the model download target folder selection with path input autocomplete and interactive folder tree navigation, making it easier and faster to choose where models are saved.
|
||||
* **Default Path Option for Downloads** - Added a "Use Default Path" option when downloading models. When enabled, models are automatically organized and stored according to your configured path template settings.
|
||||
* **Advanced Download Path Templates** - Expanded path template settings, allowing users to set individual templates for LoRA, checkpoint, and embedding models for greater flexibility. Introduced the `{author}` placeholder, enabling automatic organization of model files by creator name.
|
||||
* **Bug Fixes & Stability Improvements** - Addressed various bugs and improved overall stability for a smoother experience.
|
||||
|
||||
### v0.8.26
|
||||
* **Creator Search Option** - Added ability to search models by creator name, making it easier to find models from specific authors.
|
||||
* **Enhanced Node Usability** - Improved user experience for Lora Loader, Lora Stacker, and WanVideo Lora Select nodes by fixing the maximum height of the text input area. Users can now freely and conveniently adjust the LoRA region within these nodes.
|
||||
* **Compatibility Fixes** - Resolved compatibility issues with ComfyUI and certain custom nodes, including ComfyUI-Custom-Scripts, ensuring smoother integration and operation.
|
||||
|
||||
[View Update History](./update_logs.md)
|
||||
|
||||
---
|
||||
@@ -139,9 +157,10 @@ Enhance your Civitai browsing experience with our companion browser extension! S
|
||||
|
||||
### Option 2: **Portable Standalone Edition** (No ComfyUI required)
|
||||
|
||||
1. Download the [Portable Package](https://github.com/willmiao/ComfyUI-Lora-Manager/releases/download/v0.9.2/lora_manager_portable.7z)
|
||||
2. Copy the provided `settings.json.example` file to create a new file named `settings.json` in `comfyui-lora-manager` folder
|
||||
3. Edit `settings.json` to include your correct model folder paths and CivitAI API key
|
||||
1. Download the [Portable Package](https://github.com/willmiao/ComfyUI-Lora-Manager/releases/download/v0.9.8/lora_manager_portable.7z)
|
||||
2. Copy the provided `settings.json.example` file to create a new file named `settings.json` in `comfyui-lora-manager` folder.
|
||||
3. Edit the new `settings.json` to include your correct model folder paths and CivitAI API key
|
||||
- Set `"use_portable_settings": true` if you want the configuration to remain inside the repository folder instead of your user settings directory.
|
||||
4. Run run.bat
|
||||
- To change the startup port, edit `run.bat` and modify the parameter (e.g. `--port 9001`)
|
||||
|
||||
@@ -209,7 +228,7 @@ You can combine multiple patterns to create detailed, organized filenames for yo
|
||||
You can now run LoRA Manager independently from ComfyUI:
|
||||
|
||||
1. **For ComfyUI users**:
|
||||
- Launch ComfyUI with LoRA Manager at least once to initialize the necessary path information in the `settings.json` file.
|
||||
- Launch ComfyUI with LoRA Manager at least once to initialize the necessary path information in the `settings.json` file located in your user settings folder (see paths above).
|
||||
- Make sure dependencies are installed: `pip install -r requirements.txt`
|
||||
- From your ComfyUI root directory, run:
|
||||
```bash
|
||||
@@ -222,8 +241,9 @@ You can now run LoRA Manager independently from ComfyUI:
|
||||
```
|
||||
|
||||
2. **For non-ComfyUI users**:
|
||||
- Copy the provided `settings.json.example` file to create a new file named `settings.json`
|
||||
- Edit `settings.json` to include your correct model folder paths and CivitAI API key
|
||||
- Copy the provided `settings.json.example` file to create a new file named `settings.json`. Update the API key, optional language, and folder paths only—the library registry is created automatically when LoRA Manager starts.
|
||||
- Edit `settings.json` to include your correct model folder paths and CivitAI API key (you can leave the defaults until ready to configure them)
|
||||
- Enable portable mode by setting `"use_portable_settings": true` if you prefer LoRA Manager to read and write the `settings.json` located in the project directory.
|
||||
- Install required dependencies: `pip install -r requirements.txt`
|
||||
- Run standalone mode:
|
||||
```bash
|
||||
@@ -231,8 +251,37 @@ You can now run LoRA Manager independently from ComfyUI:
|
||||
```
|
||||
- Access the interface through your browser at: `http://localhost:8188/loras`
|
||||
|
||||
> **Note:** Existing installations automatically migrate the legacy `settings.json` from the plugin folder to the user settings directory the first time you launch this version.
|
||||
|
||||
This standalone mode provides a lightweight option for managing your model and recipe collection without needing to run the full ComfyUI environment, making it useful even for users who primarily use other stable diffusion interfaces.
|
||||
|
||||
## Testing & Coverage
|
||||
|
||||
### Backend
|
||||
|
||||
Install the development dependencies and run pytest with coverage reports:
|
||||
|
||||
```bash
|
||||
pip install -r requirements-dev.txt
|
||||
COVERAGE_FILE=coverage/backend/.coverage pytest \
|
||||
--cov=py \
|
||||
--cov=standalone \
|
||||
--cov-report=term-missing \
|
||||
--cov-report=html:coverage/backend/html \
|
||||
--cov-report=xml:coverage/backend/coverage.xml \
|
||||
--cov-report=json:coverage/backend/coverage.json
|
||||
```
|
||||
|
||||
HTML, XML, and JSON artifacts are stored under `coverage/backend/` so you can inspect hot spots locally or from CI artifacts.
|
||||
|
||||
### Frontend
|
||||
|
||||
Run the Vitest coverage suite to analyze widget hot spots:
|
||||
|
||||
```bash
|
||||
npm run test:coverage
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Contributing
|
||||
|
||||
100
__init__.py
100
__init__.py
@@ -1,14 +1,21 @@
|
||||
try: # pragma: no cover - import fallback for pytest collection
|
||||
from .py.lora_manager import LoraManager
|
||||
from .py.nodes.lora_loader import LoraManagerLoader, LoraManagerTextLoader
|
||||
from .py.nodes.trigger_word_toggle import TriggerWordToggle
|
||||
from .py.nodes.lora_stacker import LoraStacker
|
||||
from .py.nodes.save_image import SaveImage
|
||||
from .py.nodes.debug_metadata import DebugMetadata
|
||||
from .py.nodes.wanvideo_lora_select import WanVideoLoraSelect
|
||||
from .py.nodes.wanvideo_lora_select_from_text import WanVideoLoraSelectFromText
|
||||
from .py.nodes.lora_loader import LoraLoaderLM, LoraTextLoaderLM
|
||||
from .py.nodes.trigger_word_toggle import TriggerWordToggleLM
|
||||
from .py.nodes.prompt import PromptLM
|
||||
from .py.nodes.text import TextLM
|
||||
from .py.nodes.lora_stacker import LoraStackerLM
|
||||
from .py.nodes.save_image import SaveImageLM
|
||||
from .py.nodes.debug_metadata import DebugMetadataLM
|
||||
from .py.nodes.wanvideo_lora_select import WanVideoLoraSelectLM
|
||||
from .py.nodes.wanvideo_lora_select_from_text import WanVideoLoraTextSelectLM
|
||||
from .py.nodes.lora_pool import LoraPoolLM
|
||||
from .py.nodes.lora_randomizer import LoraRandomizerLM
|
||||
from .py.nodes.lora_cycler import LoraCyclerLM
|
||||
from .py.metadata_collector import init as init_metadata_collector
|
||||
except ImportError: # pragma: no cover - allows running under pytest without package install
|
||||
except (
|
||||
ImportError
|
||||
): # pragma: no cover - allows running under pytest without package install
|
||||
import importlib
|
||||
import pathlib
|
||||
import sys
|
||||
@@ -17,33 +24,76 @@ except ImportError: # pragma: no cover - allows running under pytest without pa
|
||||
if str(package_root) not in sys.path:
|
||||
sys.path.append(str(package_root))
|
||||
|
||||
PromptLM = importlib.import_module("py.nodes.prompt").PromptLM
|
||||
TextLM = importlib.import_module("py.nodes.text").TextLM
|
||||
LoraManager = importlib.import_module("py.lora_manager").LoraManager
|
||||
LoraManagerLoader = importlib.import_module("py.nodes.lora_loader").LoraManagerLoader
|
||||
LoraManagerTextLoader = importlib.import_module("py.nodes.lora_loader").LoraManagerTextLoader
|
||||
TriggerWordToggle = importlib.import_module("py.nodes.trigger_word_toggle").TriggerWordToggle
|
||||
LoraStacker = importlib.import_module("py.nodes.lora_stacker").LoraStacker
|
||||
SaveImage = importlib.import_module("py.nodes.save_image").SaveImage
|
||||
DebugMetadata = importlib.import_module("py.nodes.debug_metadata").DebugMetadata
|
||||
WanVideoLoraSelect = importlib.import_module("py.nodes.wanvideo_lora_select").WanVideoLoraSelect
|
||||
WanVideoLoraSelectFromText = importlib.import_module("py.nodes.wanvideo_lora_select_from_text").WanVideoLoraSelectFromText
|
||||
LoraLoaderLM = importlib.import_module(
|
||||
"py.nodes.lora_loader"
|
||||
).LoraLoaderLM
|
||||
LoraTextLoaderLM = importlib.import_module(
|
||||
"py.nodes.lora_loader"
|
||||
).LoraTextLoaderLM
|
||||
TriggerWordToggleLM = importlib.import_module(
|
||||
"py.nodes.trigger_word_toggle"
|
||||
).TriggerWordToggleLM
|
||||
LoraStackerLM = importlib.import_module("py.nodes.lora_stacker").LoraStackerLM
|
||||
SaveImageLM = importlib.import_module("py.nodes.save_image").SaveImageLM
|
||||
DebugMetadataLM = importlib.import_module("py.nodes.debug_metadata").DebugMetadataLM
|
||||
WanVideoLoraSelectLM = importlib.import_module(
|
||||
"py.nodes.wanvideo_lora_select"
|
||||
).WanVideoLoraSelectLM
|
||||
WanVideoLoraTextSelectLM = importlib.import_module(
|
||||
"py.nodes.wanvideo_lora_select_from_text"
|
||||
).WanVideoLoraTextSelectLM
|
||||
LoraPoolLM = importlib.import_module("py.nodes.lora_pool").LoraPoolLM
|
||||
LoraRandomizerLM = importlib.import_module(
|
||||
"py.nodes.lora_randomizer"
|
||||
).LoraRandomizerLM
|
||||
LoraCyclerLM = importlib.import_module(
|
||||
"py.nodes.lora_cycler"
|
||||
).LoraCyclerLM
|
||||
init_metadata_collector = importlib.import_module("py.metadata_collector").init
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
LoraManagerLoader.NAME: LoraManagerLoader,
|
||||
LoraManagerTextLoader.NAME: LoraManagerTextLoader,
|
||||
TriggerWordToggle.NAME: TriggerWordToggle,
|
||||
LoraStacker.NAME: LoraStacker,
|
||||
SaveImage.NAME: SaveImage,
|
||||
DebugMetadata.NAME: DebugMetadata,
|
||||
WanVideoLoraSelect.NAME: WanVideoLoraSelect,
|
||||
WanVideoLoraSelectFromText.NAME: WanVideoLoraSelectFromText
|
||||
PromptLM.NAME: PromptLM,
|
||||
TextLM.NAME: TextLM,
|
||||
LoraLoaderLM.NAME: LoraLoaderLM,
|
||||
LoraTextLoaderLM.NAME: LoraTextLoaderLM,
|
||||
TriggerWordToggleLM.NAME: TriggerWordToggleLM,
|
||||
LoraStackerLM.NAME: LoraStackerLM,
|
||||
SaveImageLM.NAME: SaveImageLM,
|
||||
DebugMetadataLM.NAME: DebugMetadataLM,
|
||||
WanVideoLoraSelectLM.NAME: WanVideoLoraSelectLM,
|
||||
WanVideoLoraTextSelectLM.NAME: WanVideoLoraTextSelectLM,
|
||||
LoraPoolLM.NAME: LoraPoolLM,
|
||||
LoraRandomizerLM.NAME: LoraRandomizerLM,
|
||||
LoraCyclerLM.NAME: LoraCyclerLM,
|
||||
}
|
||||
|
||||
WEB_DIRECTORY = "./web/comfyui"
|
||||
|
||||
# Check and build Vue widgets if needed (development mode)
|
||||
try:
|
||||
from .py.vue_widget_builder import check_and_build_vue_widgets
|
||||
|
||||
# Auto-build in development, warn only if fails
|
||||
check_and_build_vue_widgets(auto_build=True, warn_only=True)
|
||||
except ImportError:
|
||||
# Fallback for pytest
|
||||
import importlib
|
||||
|
||||
check_and_build_vue_widgets = importlib.import_module(
|
||||
"py.vue_widget_builder"
|
||||
).check_and_build_vue_widgets
|
||||
check_and_build_vue_widgets(auto_build=True, warn_only=True)
|
||||
except Exception as e:
|
||||
import logging
|
||||
|
||||
logging.warning(f"[LoRA Manager] Vue widget build check skipped: {e}")
|
||||
|
||||
# Initialize metadata collector
|
||||
init_metadata_collector()
|
||||
|
||||
# Register routes on import
|
||||
LoraManager.add_routes()
|
||||
__all__ = ['NODE_CLASS_MAPPINGS', 'WEB_DIRECTORY']
|
||||
__all__ = ["NODE_CLASS_MAPPINGS", "WEB_DIRECTORY"]
|
||||
|
||||
34
docs/architecture/multi_library_design.md
Normal file
34
docs/architecture/multi_library_design.md
Normal file
@@ -0,0 +1,34 @@
|
||||
# Multi-Library Management for Standalone Mode
|
||||
|
||||
## Requirements Summary
|
||||
- **Independent libraries**: In standalone mode, users can maintain multiple libraries, where each library represents a distinct set of model folders (LoRAs, checkpoints, embeddings, etc.). Only one library is active at any given time, but users need a fast way to switch between them.
|
||||
- **Library-specific settings**: The fields that vary per library are `folder_paths`, `default_lora_root`, `default_checkpoint_root`, and `default_embedding_root` inside `settings.json`.
|
||||
- **Persistent caches**: Every library must have its own SQLite persistent model cache so that metadata generated for one library does not leak into another.
|
||||
- **Backward compatibility**: Existing single-library setups should continue to work. When no multi-library configuration is provided, the application should behave exactly as before.
|
||||
|
||||
## Proposed Design
|
||||
1. **Library registry**
|
||||
- Extend the standalone configuration to hold a list of libraries, each identified by a unique name.
|
||||
- Each entry stores the folder path configuration plus any library-scoped metadata (e.g. creation time, display name).
|
||||
- The active library key is stored separately to allow quick switching without rewriting the full config.
|
||||
2. **Settings management**
|
||||
- Update `settings_manager` to load and persist the library registry. When a library is activated, hydrate the in-memory settings object with that library's folder configuration.
|
||||
- Provide helper methods for creating, renaming, and deleting libraries, ensuring validation for duplicate names and path collisions.
|
||||
- Continue writing the active library settings to `settings.json` for compatibility, while storing the registry in a new section such as `libraries`.
|
||||
3. **Persistent model cache**
|
||||
- Derive the SQLite file path from the active library, e.g. `model_cache_<library>.sqlite` or a nested directory structure like `model_cache/<library>/models.sqlite`.
|
||||
- Update `PersistentModelCache` so it resolves the database path dynamically whenever the active library changes. Ensure connections are closed before switching to avoid locking issues.
|
||||
- Migrate existing single cache files by treating them as the default library's cache.
|
||||
4. **Model scanning workflow**
|
||||
- Modify `ModelScanner` and related services to react to library switches by clearing in-memory caches, re-reading folder paths, and rehydrating metadata from the library-specific SQLite cache.
|
||||
- Provide API endpoints in standalone mode to list libraries, activate one, and trigger a rescan.
|
||||
5. **UI/UX considerations**
|
||||
- In the standalone UI, introduce a library selector component that surfaces available libraries and offers quick switching.
|
||||
- Offer feedback when switching libraries (e.g. spinner while rescanning) and guard destructive actions with confirmation prompts.
|
||||
|
||||
## Implementation Notes
|
||||
- **Data migration**: On startup, detect if the old `settings.json` structure is present. If so, create a default library entry using the current folder paths and point the active library to it.
|
||||
- **Thread safety**: Ensure that any long-running scans are cancelled or awaited before switching libraries to prevent race conditions in cache writes.
|
||||
- **Testing**: Add unit tests for the settings manager to cover library CRUD operations and cache path resolution. Include integration tests that simulate switching libraries and verifying that the correct models are loaded.
|
||||
- **Documentation**: Update user guides to explain how to define libraries, switch between them, and where the new cache files are stored.
|
||||
- **Extensibility**: Keep the design open to future per-library settings (e.g. auto-refresh intervals, metadata overrides) by storing library data as objects instead of flat maps.
|
||||
46
docs/custom_priority_tags_format.md
Normal file
46
docs/custom_priority_tags_format.md
Normal file
@@ -0,0 +1,46 @@
|
||||
# Custom Priority Tag Format Proposal
|
||||
|
||||
To support user-defined priority tags with flexible aliasing across different model types, the configuration will be stored as editable strings. The format balances readability with enough structure for parsing on both the backend and frontend.
|
||||
|
||||
## Format Overview
|
||||
|
||||
- Each model type is declared on its own line: `model_type: entries`.
|
||||
- Entries are comma-separated and ordered by priority from highest to lowest.
|
||||
- An entry may be a single canonical tag (e.g., `realistic`) or a canonical tag with aliases.
|
||||
- Canonical tags define the final folder name that should be used when matching that entry.
|
||||
- Aliases are enclosed in parentheses and separated by `|` (vertical bar).
|
||||
- All matching is case-insensitive; stored canonical names preserve the user-specified casing for folder creation and UI suggestions.
|
||||
|
||||
### Grammar
|
||||
|
||||
```
|
||||
priority-config := model-config { "\n" model-config }
|
||||
model-config := model-type ":" entry-list
|
||||
model-type := <identifier without spaces>
|
||||
entry-list := entry { "," entry }
|
||||
entry := canonical [ "(" alias { "|" alias } ")" ]
|
||||
canonical := <tag text without parentheses or commas>
|
||||
alias := <tag text without parentheses, commas, or pipes>
|
||||
```
|
||||
|
||||
Examples:
|
||||
|
||||
```
|
||||
lora: celebrity(celeb|celebrity), stylized, character(char)
|
||||
checkpoint: realistic(realism|realistic), anime(anime-style|toon)
|
||||
embedding: face, celeb(celebrity|celeb)
|
||||
```
|
||||
|
||||
## Parsing Notes
|
||||
|
||||
- Whitespace around separators is ignored to make manual editing more forgiving.
|
||||
- Duplicate canonical tags within the same model type collapse to a single entry; the first definition wins.
|
||||
- Aliases map to their canonical tag. When generating folder names, the canonical form is used.
|
||||
- Tags that do not match any alias or canonical entry fall back to the first tag in the model's tag list, preserving current behavior.
|
||||
|
||||
## Usage
|
||||
|
||||
- **Backend:** Convert each model type's string into an ordered list of canonical tags with alias sets. During path generation, iterate by priority order and match tags against both canonical names and their aliases.
|
||||
- **Frontend:** Surface canonical tags as suggestions, optionally displaying aliases in tooltips or secondary text. Input validation should warn about duplicate aliases within the same model type.
|
||||
|
||||
This format allows users to customize priority tag handling per model type while keeping editing simple and avoiding proliferation of folder names through alias normalization.
|
||||
28
docs/dom-widgets/README.md
Normal file
28
docs/dom-widgets/README.md
Normal file
@@ -0,0 +1,28 @@
|
||||
# DOM Widgets Documentation
|
||||
|
||||
Documentation for custom DOM widget development in ComfyUI LoRA Manager.
|
||||
|
||||
## Files
|
||||
|
||||
- **[Value Persistence Best Practices](value-persistence-best-practices.md)** - Essential guide for implementing text input DOM widgets that persist values correctly
|
||||
|
||||
## Key Lessons
|
||||
|
||||
### Common Anti-Patterns
|
||||
|
||||
❌ **Don't**: Create internal state variables
|
||||
❌ **Don't**: Use v-model for text inputs
|
||||
❌ **Don't**: Add serializeValue, onSetValue callbacks
|
||||
❌ **Don't**: Watch props.widget.value
|
||||
|
||||
### Best Practices
|
||||
|
||||
✅ **Do**: Use DOM element as single source of truth
|
||||
✅ **Do**: Store DOM reference on widget.inputEl
|
||||
✅ **Do**: Direct getValue/setValue to DOM
|
||||
✅ **Do**: Clean up reference on unmount
|
||||
|
||||
## Related Documentation
|
||||
|
||||
- [DOM Widget Development Guide](../dom_widget_dev_guide.md) - Comprehensive guide for building DOM widgets
|
||||
- [ComfyUI Built-in Example](../../../../code/ComfyUI_frontend/src/renderer/extensions/vueNodes/widgets/composables/useStringWidget.ts) - Reference implementation
|
||||
225
docs/dom-widgets/value-persistence-best-practices.md
Normal file
225
docs/dom-widgets/value-persistence-best-practices.md
Normal file
@@ -0,0 +1,225 @@
|
||||
# DOM Widget Value Persistence - Best Practices
|
||||
|
||||
## Overview
|
||||
|
||||
DOM widgets require different persistence patterns depending on their complexity. This document covers two patterns:
|
||||
|
||||
1. **Simple Text Widgets**: DOM element as source of truth (e.g., textarea, input)
|
||||
2. **Complex Widgets**: Internal value with `widget.callback` (e.g., LoraPoolWidget, RandomizerWidget)
|
||||
|
||||
## Understanding ComfyUI's Built-in Callback Mechanism
|
||||
|
||||
When `widget.value` is set (e.g., during workflow load), ComfyUI's `domWidget.ts` triggers this flow:
|
||||
|
||||
```typescript
|
||||
// From ComfyUI_frontend/src/scripts/domWidget.ts:146-149
|
||||
set value(v: V) {
|
||||
this.options.setValue?.(v) // 1. Update internal state
|
||||
this.callback?.(this.value) // 2. Notify listeners for UI updates
|
||||
}
|
||||
```
|
||||
|
||||
This means:
|
||||
- `setValue()` handles storing the value
|
||||
- `widget.callback()` is automatically called to notify the UI
|
||||
- You don't need custom callback mechanisms like `onSetValue`
|
||||
|
||||
---
|
||||
|
||||
## Pattern 1: Simple Text Input Widgets
|
||||
|
||||
For widgets where the value IS the DOM element's text content (textarea, input fields).
|
||||
|
||||
### When to Use
|
||||
|
||||
- Single text input/textarea widgets
|
||||
- Value is a simple string
|
||||
- No complex state management needed
|
||||
|
||||
### Implementation
|
||||
|
||||
**main.ts:**
|
||||
```typescript
|
||||
const widget = node.addDOMWidget(name, type, container, {
|
||||
getValue() {
|
||||
return widget.inputEl?.value ?? ''
|
||||
},
|
||||
setValue(v: string) {
|
||||
if (widget.inputEl) {
|
||||
widget.inputEl.value = v ?? ''
|
||||
}
|
||||
}
|
||||
})
|
||||
```
|
||||
|
||||
**Vue Component:**
|
||||
```typescript
|
||||
onMounted(() => {
|
||||
if (textareaRef.value) {
|
||||
props.widget.inputEl = textareaRef.value
|
||||
}
|
||||
})
|
||||
|
||||
onUnmounted(() => {
|
||||
if (props.widget.inputEl === textareaRef.value) {
|
||||
props.widget.inputEl = undefined
|
||||
}
|
||||
})
|
||||
```
|
||||
|
||||
### Why This Works
|
||||
|
||||
- Single source of truth: the DOM element
|
||||
- `getValue()` reads directly from DOM
|
||||
- `setValue()` writes directly to DOM
|
||||
- No sync issues between multiple state variables
|
||||
|
||||
---
|
||||
|
||||
## Pattern 2: Complex Widgets
|
||||
|
||||
For widgets with structured data (JSON configs, arrays, objects) where the value cannot be stored in a DOM element.
|
||||
|
||||
### When to Use
|
||||
|
||||
- Value is a complex object/array (e.g., `{ loras: [...], settings: {...} }`)
|
||||
- Multiple UI elements contribute to the value
|
||||
- Vue reactive state manages the UI
|
||||
|
||||
### Implementation
|
||||
|
||||
**main.ts:**
|
||||
```typescript
|
||||
let internalValue: MyConfig | undefined
|
||||
|
||||
const widget = node.addDOMWidget(name, type, container, {
|
||||
getValue() {
|
||||
return internalValue
|
||||
},
|
||||
setValue(v: MyConfig) {
|
||||
internalValue = v
|
||||
// NO custom onSetValue needed - widget.callback is called automatically
|
||||
},
|
||||
serialize: true // Ensure value is saved with workflow
|
||||
})
|
||||
```
|
||||
|
||||
**Vue Component:**
|
||||
```typescript
|
||||
const config = ref<MyConfig>(getDefaultConfig())
|
||||
|
||||
onMounted(() => {
|
||||
// Set up callback for UI updates when widget.value changes externally
|
||||
// (e.g., workflow load, undo/redo)
|
||||
props.widget.callback = (newValue: MyConfig) => {
|
||||
if (newValue) {
|
||||
config.value = newValue
|
||||
}
|
||||
}
|
||||
|
||||
// Restore initial value if workflow was already loaded
|
||||
if (props.widget.value) {
|
||||
config.value = props.widget.value
|
||||
}
|
||||
})
|
||||
|
||||
// When UI changes, update widget value
|
||||
function onConfigChange(newConfig: MyConfig) {
|
||||
config.value = newConfig
|
||||
props.widget.value = newConfig // This also triggers callback
|
||||
}
|
||||
```
|
||||
|
||||
### Why This Works
|
||||
|
||||
1. **Clear separation**: `internalValue` stores the data, Vue ref manages the UI
|
||||
2. **Built-in callback**: ComfyUI calls `widget.callback()` automatically after `setValue()`
|
||||
3. **Bidirectional sync**:
|
||||
- External → UI: `setValue()` updates `internalValue`, `callback()` updates Vue ref
|
||||
- UI → External: User interaction updates Vue ref, which updates `widget.value`
|
||||
|
||||
---
|
||||
|
||||
## Common Mistakes
|
||||
|
||||
### ❌ Creating custom callback mechanisms
|
||||
|
||||
```typescript
|
||||
// Wrong - unnecessary complexity
|
||||
setValue(v: MyConfig) {
|
||||
internalValue = v
|
||||
widget.onSetValue?.(v) // Don't add this - use widget.callback instead
|
||||
}
|
||||
```
|
||||
|
||||
Use the built-in `widget.callback` instead.
|
||||
|
||||
### ❌ Using v-model for simple text inputs in DOM widgets
|
||||
|
||||
```html
|
||||
<!-- Wrong - creates sync issues -->
|
||||
<textarea v-model="textValue" />
|
||||
|
||||
<!-- Right for simple text widgets -->
|
||||
<textarea ref="textareaRef" @input="onInput" />
|
||||
```
|
||||
|
||||
### ❌ Watching props.widget.value
|
||||
|
||||
```typescript
|
||||
// Wrong - creates race conditions
|
||||
watch(() => props.widget.value, (newValue) => {
|
||||
config.value = newValue
|
||||
})
|
||||
```
|
||||
|
||||
Use `widget.callback` instead - it's called at the right time in the lifecycle.
|
||||
|
||||
### ❌ Multiple sources of truth
|
||||
|
||||
```typescript
|
||||
// Wrong - who is the source of truth?
|
||||
let internalValue = '' // State 1
|
||||
const textValue = ref('') // State 2
|
||||
const domElement = textarea // State 3
|
||||
props.widget.value // State 4
|
||||
```
|
||||
|
||||
Choose ONE source of truth:
|
||||
- **Simple widgets**: DOM element
|
||||
- **Complex widgets**: `internalValue` (with Vue ref as derived UI state)
|
||||
|
||||
### ❌ Adding serializeValue for simple widgets
|
||||
|
||||
```typescript
|
||||
// Wrong - getValue/setValue handle serialization
|
||||
props.widget.serializeValue = async () => textValue.value
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Decision Guide
|
||||
|
||||
| Widget Type | Source of Truth | Use `widget.callback` | Example |
|
||||
|-------------|-----------------|----------------------|---------|
|
||||
| Simple text input | DOM element (`inputEl`) | Optional | AutocompleteTextWidget |
|
||||
| Complex config | `internalValue` | Yes, for UI sync | LoraPoolWidget |
|
||||
| Vue component widget | Vue ref + `internalValue` | Yes | RandomizerWidget |
|
||||
|
||||
---
|
||||
|
||||
## Testing Checklist
|
||||
|
||||
- [ ] Load workflow - value restores correctly
|
||||
- [ ] Switch workflow - value persists
|
||||
- [ ] Reload page - value persists
|
||||
- [ ] UI interaction - value updates
|
||||
- [ ] Undo/redo - value syncs with UI
|
||||
- [ ] No console errors
|
||||
|
||||
---
|
||||
|
||||
## References
|
||||
|
||||
- ComfyUI DOMWidget implementation: `ComfyUI_frontend/src/scripts/domWidget.ts`
|
||||
- Simple text widget example: `ComfyUI_frontend/src/renderer/extensions/vueNodes/widgets/composables/useStringWidget.ts`
|
||||
546
docs/dom_widget_dev_guide.md
Normal file
546
docs/dom_widget_dev_guide.md
Normal file
@@ -0,0 +1,546 @@
|
||||
# DOMWidget Development Guide
|
||||
|
||||
This document provides a comprehensive guide for developing custom DOMWidgets in ComfyUI using Vanilla JavaScript. DOMWidgets allow you to embed standard HTML elements (div, video, canvas, input, etc.) into ComfyUI nodes while benefitting from the frontend's automatic layout and zoom management.
|
||||
|
||||
## 1. Core Concepts
|
||||
|
||||
In ComfyUI, a `DOMWidget` extends the default LiteGraph Canvas rendering logic. It maintains an HTML layer on top of the Canvas, making complex interactions and media displays significantly easier to implement than pure Canvas drawing.
|
||||
|
||||
### Key APIs
|
||||
* **`app.registerExtension`**: The entry point for registering extensions.
|
||||
* **`getCustomWidgets`**: A hook for defining new widget types associated with specific input types.
|
||||
* **`node.addDOMWidget`**: The core method to add HTML elements to a node.
|
||||
|
||||
---
|
||||
|
||||
## 2. Basic Structure
|
||||
|
||||
A standard custom DOMWidget extension typically follows this structure:
|
||||
|
||||
```javascript
|
||||
import { app } from "../../scripts/app.js";
|
||||
|
||||
app.registerExtension({
|
||||
name: "My.Custom.Extension",
|
||||
async getCustomWidgets() {
|
||||
return {
|
||||
// Define a new widget type named "MY_WIDGET_TYPE"
|
||||
MY_WIDGET_TYPE(node, inputName, inputData, app) {
|
||||
// 1. Create the HTML element
|
||||
const container = document.createElement("div");
|
||||
container.innerHTML = "Hello <b>DOMWidget</b>!";
|
||||
|
||||
// 2. Setup styles (Optional but recommended)
|
||||
container.style.color = "white";
|
||||
container.style.backgroundColor = "#222";
|
||||
container.style.padding = "5px";
|
||||
|
||||
// 3. Add the DOMWidget and return the result
|
||||
const widget = node.addDOMWidget(inputName, "MY_WIDGET_TYPE", container, {
|
||||
// Configuration options
|
||||
getValue() {
|
||||
return container.innerText;
|
||||
},
|
||||
setValue(v) {
|
||||
container.innerText = v;
|
||||
}
|
||||
});
|
||||
|
||||
// 4. Return in the standard format
|
||||
return { widget };
|
||||
}
|
||||
};
|
||||
}
|
||||
});
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## ComfyUI Dual Rendering Modes
|
||||
|
||||
ComfyUI frontend supports two rendering modes:
|
||||
|
||||
| Mode | Description | DOM Structure |
|
||||
| :--- | :--- | :--- |
|
||||
| **Canvas Mode** | Traditional rendering where widgets are rendered on top of canvas using absolute positioning | Uses `.dom-widget` class on containers |
|
||||
| **Vue DOM Mode** | New rendering mode where nodes and widgets are rendered as Vue components | Uses `.lg-node-widget` class on containers with dynamic IDs (e.g., `v-1-0`) |
|
||||
|
||||
### Mode Switching
|
||||
|
||||
The frontend switches between modes via `LiteGraph.vueNodesMode` boolean:
|
||||
- `LiteGraph.vueNodesMode = true` → Vue DOM Mode
|
||||
- `LiteGraph.vueNodesMode = false` → Canvas Mode
|
||||
|
||||
**Key Behavior**: Mode switching triggers DOM re-rendering WITHOUT page reload. Widget elements are destroyed and recreated, so any event listeners or references to old DOM elements become invalid.
|
||||
|
||||
### Testing Mode Switches via Chrome DevTools MCP
|
||||
|
||||
```javascript
|
||||
// Trigger render mode change
|
||||
LiteGraph.vueNodesMode = !LiteGraph.vueNodesMode;
|
||||
|
||||
// Force canvas redraw (optional but helps trigger re-render)
|
||||
if (app.canvas) {
|
||||
app.canvas.draw(true, true);
|
||||
}
|
||||
```
|
||||
|
||||
### Development Notes
|
||||
|
||||
When implementing widgets that attach event listeners or maintain external references:
|
||||
1. **Use `node.onRemoved`** to clean up when node is deleted
|
||||
2. **Detect DOM changes** by checking if widget input element is still in document: `document.body.contains(inputElement)`
|
||||
3. **Poll for mode changes** by watching `LiteGraph.vueNodesMode` and re-initializing when it changes
|
||||
4. **Use `loadedGraphNode` hook** for initial setup (guarantees DOM is fully rendered)
|
||||
|
||||
|
||||
---
|
||||
|
||||
## 3. The `addDOMWidget` API
|
||||
|
||||
```javascript
|
||||
node.addDOMWidget(name, type, element, options)
|
||||
```
|
||||
|
||||
### Parameters
|
||||
1. **`name`**: The internal name of the widget (usually matches the input name).
|
||||
2. **`type`**: The type identifier for the widget.
|
||||
3. **`element`**: The actual HTMLElement to embed.
|
||||
4. **`options`**: (Object) Configuration for lifecycle, sizing, and persistence.
|
||||
|
||||
### Common `options` Fields
|
||||
| Field | Type | Description |
|
||||
| :--- | :--- | :--- |
|
||||
| `getValue` | `Function` | Defines how to retrieve the widget's value for serialization. |
|
||||
| `setValue` | `Function` | Defines how to restore the widget's state from workflow data. |
|
||||
| `getMinHeight` | `Function` | Returns the minimum height in pixels. |
|
||||
| `getHeight` | `Function` | Returns the preferred height (supports numbers or percentage strings like `"50%"`). |
|
||||
| `onResize` | `Function` | Callback triggered when the widget is resized. |
|
||||
| `hideOnZoom`| `Boolean` | Whether to hide the DOM element when zoomed out to improve performance (default: `true`). |
|
||||
| `selectOn` | `string[]` | Events on the element that should trigger node selection (default: `['focus', 'click']`). |
|
||||
|
||||
---
|
||||
|
||||
## 4. Size Control
|
||||
|
||||
Custom DOMWidgets must actively inform the parent Node of their size requirements to ensure the Node layout is calculated correctly and connection wires remain aligned.
|
||||
|
||||
### 4.1 Core Mechanism
|
||||
|
||||
Whether in Canvas Mode or Vue Mode, the underlying logic model (`LGraphNode`) calls the widget's `computeLayoutSize` method to determine dimensions. This logic is used to calculate the Node's total size and the position of input/output slots.
|
||||
|
||||
### 4.2 Controlling Height
|
||||
|
||||
It is recommended to use the `options` parameter to define height behavior.
|
||||
|
||||
**Performance Note:** providing `getMinHeight` and `getHeight` via `options` allows the system to skip expensive DOM measurements (`getComputedStyle`) during rendering loop. This significantly improves performance and prevents FPS drops during node resizing.
|
||||
|
||||
**Method 1: Using `options` (Recommended)**
|
||||
|
||||
```javascript
|
||||
const widget = node.addDOMWidget("MyWidget", "custom", element, {
|
||||
// Specify minimum height in pixels
|
||||
getMinHeight: () => 150,
|
||||
|
||||
// Or specify preferred height (pixels or percentage string)
|
||||
// getHeight: () => "50%",
|
||||
});
|
||||
```
|
||||
|
||||
**Method 2: Using CSS Variables**
|
||||
|
||||
You can also set specific CSS variables on the root element:
|
||||
|
||||
```javascript
|
||||
element.style.setProperty("--comfy-widget-min-height", "150px");
|
||||
// or --comfy-widget-height
|
||||
```
|
||||
|
||||
### 4.3 Controlling Width
|
||||
|
||||
By default, a DOMWidget's width automatically stretches to fit the Node's width (which is determined by the Title or other Input Slots).
|
||||
|
||||
If you must **force the Node to be wider** to accommodate your widget, you need to override the widget instance's `computeLayoutSize` method:
|
||||
|
||||
```javascript
|
||||
const widget = node.addDOMWidget("WideWidget", "custom", element);
|
||||
|
||||
// Override the default layout calculation
|
||||
widget.computeLayoutSize = (targetNode) => {
|
||||
return {
|
||||
minHeight: 150, // Must return height
|
||||
minWidth: 300 // Force the Node to be at least 300px wide
|
||||
};
|
||||
};
|
||||
```
|
||||
|
||||
### 4.4 Dynamic Resizing
|
||||
|
||||
If your widget's content changes dynamically (e.g., expanding sections, loading images, or CSS changes), the DOM element will resize, but the Canvas-rendered Node background and Slots will not automatically follow. You must manually trigger a synchronization.
|
||||
|
||||
**The Update Sequence:**
|
||||
Whenever the **actual rendering height** of your DOM element changes, execute the following "three-step combo":
|
||||
|
||||
```javascript
|
||||
// 1. Calculate the new optimal size for the node based on current widget requirements
|
||||
const newSize = node.computeSize();
|
||||
|
||||
// 2. Apply the new size to the node model (updates bounding box and slot positions)
|
||||
node.setSize(newSize);
|
||||
|
||||
// 3. Mark the canvas as dirty to trigger a redraw in the next animation frame
|
||||
node.setDirtyCanvas(true, true);
|
||||
```
|
||||
|
||||
**Common Scenarios:**
|
||||
|
||||
| Scenario | Actual Height Change? | Update Required? |
|
||||
| :--- | :--- | :--- |
|
||||
| **Expand/Collapse content** | **Yes** | ✅ **Yes**. Prevents widget from overflowing node boundaries. |
|
||||
| **Image/Video finished loading** | **Yes** | ✅ **Yes**. Initial height might be 0 until the media loads. |
|
||||
| **Changing `minHeight`** | **Maybe** | ❓ **Only if** the change causes the element's actual height to shift. |
|
||||
| **Changing font size/styles** | **Yes** | ✅ **Yes**. Text reflow often changes the total height. |
|
||||
| **User dragging node corner** | **Yes** | ❌ **No**. LiteGraph handles this internally. |
|
||||
|
||||
---
|
||||
|
||||
## 5. State Persistence (Serialization)
|
||||
|
||||
### 5.1 Default Behavior
|
||||
|
||||
DOMWidgets have **serialization enabled** by default (`serialize` property is `true`).
|
||||
* **Saving**: ComfyUI attempts to read the widget's value to save into the Workflow file.
|
||||
* **Loading**: ComfyUI reads the value from the Workflow file and assigns it to the widget.
|
||||
|
||||
### 5.2 Custom Serialization
|
||||
|
||||
To make persistence work effectively (saving internal DOM state and restoring it), you must implement `getValue` and `setValue` in the `options`:
|
||||
|
||||
* **`getValue`**: Returns the state to be saved (Number, String, or Object).
|
||||
* **`setValue`**: Receives the restored value and updates the DOM element.
|
||||
|
||||
**Example:**
|
||||
|
||||
```javascript
|
||||
const inputEl = document.createElement("input");
|
||||
const widget = node.addDOMWidget("MyInput", "custom", inputEl, {
|
||||
// 1. Called during Save
|
||||
getValue: () => {
|
||||
return inputEl.value;
|
||||
},
|
||||
// 2. Called during Load or Copy/Paste
|
||||
setValue: (value) => {
|
||||
inputEl.value = value || "";
|
||||
}
|
||||
});
|
||||
|
||||
// Optional: Listen for changes to update widget.value immediately
|
||||
inputEl.addEventListener("change", () => {
|
||||
widget.value = inputEl.value; // Triggers callbacks
|
||||
});
|
||||
```
|
||||
|
||||
> **⚠️ Important**: For Vue-based DOM widgets with text inputs, follow the [Value Persistence Best Practices](dom-widgets/value-persistence-best-practices.md) to avoid sync issues. Key takeaway: use DOM element as single source of truth, avoid internal state variables and v-model.
|
||||
|
||||
### 5.3 The Restoration Mechanism (`configure`)
|
||||
|
||||
* **`configure(data)`**: When a Workflow is loaded, `LGraphNode` calls its `configure(data)` method.
|
||||
* **`setValue` Chain**: During `configure`, the Node iterates over the saved `widgets_values` array and assigns each value (`widget.value = savedValue`). For DOMWidgets, this assignment triggers the `setValue` callback defined in your options.
|
||||
|
||||
Therefore, `options.setValue` is the critical hook for restoring widget state.
|
||||
|
||||
### 5.4 Disabling Serialization
|
||||
|
||||
If your widget is purely for display (e.g., a real-time monitor or generated chart) and doesn't need to save state, disable serialization to reduce workflow file size.
|
||||
|
||||
**Note**: You cannot set this via `options`. You must modify the widget instance directly.
|
||||
|
||||
```javascript
|
||||
const widget = node.addDOMWidget("DisplayOnly", "custom", element);
|
||||
widget.serialize = false; // Explicitly disable
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 6. Lifecycle & Events
|
||||
|
||||
### 6.1 `onResize`
|
||||
|
||||
When the Node size changes (e.g., user drags the corner), the widget can receive a notification via `options`:
|
||||
|
||||
```javascript
|
||||
const widget = node.addDOMWidget("ResizingWidget", "custom", element, {
|
||||
onResize: (w) => {
|
||||
// 'w' is the widget instance
|
||||
// Adjust internal DOM layout here if necessary
|
||||
console.log("Widget resized");
|
||||
}
|
||||
});
|
||||
```
|
||||
|
||||
### 6.2 Construction & Mounting
|
||||
|
||||
* **Construction**: Occurs immediately when `addDOMWidget` is called.
|
||||
* **Mounting**:
|
||||
* **Canvas Mode**: Appended to `.dom-widget-container` via `DomWidget.vue`.
|
||||
* **Vue Mode**: Appended inside the Node component via `WidgetDOM.vue`.
|
||||
* **Caution**: When `addDOMWidget` returns, the element may not be in the `document.body` yet. If you need to access layout properties like `getBoundingClientRect`, use `setTimeout` or wait for the first `onResize`.
|
||||
|
||||
### 6.3 Cleanup
|
||||
|
||||
If you create external references (like `setInterval` or global event listeners), ensure you clean them up using `node.onRemoved`:
|
||||
|
||||
```javascript
|
||||
node.onRemoved = function() {
|
||||
clearInterval(myInterval);
|
||||
// Call original onRemoved if it existed
|
||||
};
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 7. Styling & Best Practices
|
||||
|
||||
### 7.1 Styling
|
||||
Since DOMWidgets are placed in absolute positioned containers or managed by Vue, ensure your container handles sizing gracefully:
|
||||
|
||||
```javascript
|
||||
container.style.width = "100%";
|
||||
container.style.boxSizing = "border-box";
|
||||
```
|
||||
|
||||
### 7.2 Path References
|
||||
When importing `app`, adjust the path based on your extension's folder depth. Typically:
|
||||
`import { app } from "../../scripts/app.js";`
|
||||
|
||||
### 7.3 Security
|
||||
If setting `innerHTML` dynamically, ensure the content is sanitized or trusted to prevent XSS attacks.
|
||||
|
||||
### 7.4 UI Constraints for ComfyUI Custom Node Widgets
|
||||
|
||||
When developing DOMWidgets as internal UI widgets for ComfyUI custom nodes, keep the following constraints in mind:
|
||||
|
||||
#### 7.4.1 Minimize Vertical Space
|
||||
|
||||
ComfyUI nodes are often displayed in a compact graph view with many nodes visible simultaneously. Avoid excessive vertical spacing that could clutter the workspace.
|
||||
|
||||
- Keep layouts compact and efficient
|
||||
- Use appropriate padding and margins (4-8px typically)
|
||||
- Stack related controls vertically but avoid unnecessary spacing
|
||||
|
||||
#### 7.4.2 Avoid Dynamic Height Changes
|
||||
|
||||
Dynamic height changes (expand/collapse sections, showing/hiding content) can cause node layout recalculations and affect connection wire positioning.
|
||||
|
||||
- Prefer static layouts over expandable/collapsible sections
|
||||
- Use tooltips or overlays for additional information instead
|
||||
- If dynamic height is unavoidable, manually trigger layout updates (see Section 4.4)
|
||||
|
||||
#### 7.4.3 Keep UI Simple and Intuitive
|
||||
|
||||
As internal widgets for ComfyUI custom nodes, the UI should be accessible to users without technical implementation details.
|
||||
|
||||
- Use clear, user-friendly terminology (avoid "frontend/backend roll" in favor of "fixed/always randomize")
|
||||
- Focus on user intent rather than implementation details
|
||||
- Avoid complex interactions that may confuse users
|
||||
|
||||
#### 7.4.4 Forward Middle Mouse Events to Canvas
|
||||
|
||||
By default, when a DOM widget receives pointer events (e.g., mouse clicks, drags), these events are captured by the widget and not forwarded to the ComfyUI canvas. This prevents users from panning the workflow using the middle mouse button when the cursor is over a DOM widget.
|
||||
|
||||
To enable workflow panning over your widget, you should forward middle mouse events (button 1) to the canvas using the `forwardMiddleMouseToCanvas` utility function:
|
||||
|
||||
```javascript
|
||||
import { forwardMiddleMouseToCanvas } from "./utils.js";
|
||||
|
||||
// In your widget creation function
|
||||
const container = document.createElement("div");
|
||||
container.style.width = "100%";
|
||||
container.style.height = "100%";
|
||||
// ... other styles ...
|
||||
|
||||
// Forward middle mouse events to canvas for panning
|
||||
forwardMiddleMouseToCanvas(container);
|
||||
|
||||
const widget = node.addDOMWidget(name, type, container, { ... });
|
||||
```
|
||||
|
||||
The `forwardMiddleMouseToCanvas` function:
|
||||
- Forwards `pointerdown` events with button 1 (middle mouse button) to `app.canvas.processMouseDown`
|
||||
- Forwards `pointermove` events while middle mouse button is pressed to `app.canvas.processMouseMove`
|
||||
- Forwards `pointerup` events with button 1 to `app.canvas.processMouseUp`
|
||||
|
||||
This allows users to pan the workflow canvas even when their mouse cursor is hovering over your DOM widget.
|
||||
|
||||
---
|
||||
|
||||
## 8. Event Handling in Vue DOM Render Mode
|
||||
|
||||
ComfyUI frontend supports two rendering modes for nodes:
|
||||
- **Legacy Canvas Mode**: Traditional rendering where widgets are rendered on top of the canvas using absolute positioning
|
||||
- **Vue DOM Render Mode**: New rendering mode where nodes and widgets are rendered as Vue components
|
||||
|
||||
In Vue DOM render mode, event handling works differently. The frontend uses `useCanvasInteractions` composable to manage event forwarding to the canvas. This can cause custom event handlers in your widgets (e.g., mouse wheel for sliders, custom drag operations) to be intercepted by the canvas.
|
||||
|
||||
### 8.1 Wheel Event Handling
|
||||
|
||||
By default in Vue DOM render mode, wheel events on widgets may be forwarded to the canvas for workflow zoom, overriding your custom wheel handlers (e.g., adjusting slider values with mouse wheel).
|
||||
|
||||
To fix this, use the `data-capture-wheel="true"` attribute on elements that should capture wheel events:
|
||||
|
||||
```vue
|
||||
<!-- Vue component template -->
|
||||
<div class="my-slider" data-capture-wheel="true" @wheel="onWheel">
|
||||
<!-- Slider content -->
|
||||
</div>
|
||||
|
||||
<script setup lang="ts">
|
||||
const onWheel = (event: WheelEvent) => {
|
||||
event.preventDefault()
|
||||
// Custom wheel handling logic here
|
||||
}
|
||||
</script>
|
||||
```
|
||||
|
||||
**How it works:**
|
||||
- ComfyUI's `useCanvasInteractions.ts` checks `target?.closest('[data-capture-wheel="true"]')` before forwarding wheel events
|
||||
- If an element (or its ancestor) has this attribute, wheel events are not forwarded to canvas
|
||||
- Your custom `@wheel` handler will work as expected
|
||||
|
||||
**Granular control:**
|
||||
- Apply `data-capture-wheel="true"` to specific interactive elements (e.g., sliders, scrollable areas)
|
||||
- Widget container without this attribute will allow workflow zoom when wheel is used elsewhere
|
||||
- This allows users to both: adjust widget values with wheel, and zoom workflow with wheel in widget's non-interactive areas
|
||||
|
||||
**Example from DualRangeSlider.vue:**
|
||||
```vue
|
||||
<template>
|
||||
<div
|
||||
class="dual-range-slider"
|
||||
:class="{ disabled, 'is-dragging': dragging !== null }"
|
||||
data-capture-wheel="true"
|
||||
@wheel="onWheel"
|
||||
>
|
||||
<!-- Slider tracks and handles -->
|
||||
</div>
|
||||
</template>
|
||||
```
|
||||
|
||||
### 8.2 Pointer Event Handling
|
||||
|
||||
In Vue DOM render mode, pointer events (click, drag, etc.) may also be captured by the canvas system. For custom drag operations:
|
||||
|
||||
1. **Use event modifiers to stop propagation:**
|
||||
```vue
|
||||
<div
|
||||
@pointerdown.stop="startDrag"
|
||||
@pointermove.stop="onDrag"
|
||||
@pointerup.stop="stopDrag"
|
||||
>
|
||||
```
|
||||
|
||||
2. **Use pointer capture for reliable drag tracking:**
|
||||
```javascript
|
||||
const startDrag = (event: PointerEvent) => {
|
||||
const target = event.currentTarget as HTMLElement
|
||||
target.setPointerCapture(event.pointerId)
|
||||
// ... drag initialization
|
||||
}
|
||||
|
||||
const stopDrag = (event: PointerEvent) => {
|
||||
const target = event.currentTarget as HTMLElement
|
||||
target.releasePointerCapture(event.pointerId)
|
||||
// ... drag cleanup
|
||||
}
|
||||
```
|
||||
|
||||
3. **Use `touch-action: none` CSS for touch devices:**
|
||||
```css
|
||||
.my-draggable {
|
||||
touch-action: none;
|
||||
}
|
||||
```
|
||||
|
||||
### 8.3 Compatibility Checklist
|
||||
|
||||
Ensure your widget works in both rendering modes:
|
||||
|
||||
| Feature | Canvas Mode | Vue DOM Mode | Solution |
|
||||
|---------|-------------|--------------|----------|
|
||||
| Mouse wheel on sliders | Works by default | Needs `data-capture-wheel` | Add `data-capture-wheel="true"` to slider elements |
|
||||
| Custom drag operations | Works with `stopPropagation()` | Needs `stopPropagation()` | Use `.stop` modifier and pointer capture |
|
||||
| Middle mouse panning | Manual forwarding required | Manual forwarding required | Use `forwardMiddleMouseToCanvas()` |
|
||||
| Workflow zoom on widget edges | Works by default | Works by default | No action needed (works by default) |
|
||||
|
||||
### 8.4 Testing Recommendations
|
||||
|
||||
Test your widget in both rendering modes:
|
||||
1. Toggle between Canvas Mode and Vue DOM Mode in ComfyUI settings
|
||||
2. Verify custom interactions (wheel, drag, etc.) work in both modes
|
||||
3. Verify canvas interactions (zoom, pan) still work when cursor is over non-interactive widget areas
|
||||
4. Test with touch devices if applicable
|
||||
|
||||
---
|
||||
|
||||
## 9. Complete Example: Text Counter
|
||||
|
||||
This example implements a simple widget that displays the character count of another text widget in the same node.
|
||||
|
||||
```javascript
|
||||
import { app } from "../../scripts/app.js";
|
||||
|
||||
app.registerExtension({
|
||||
name: "Comfy.TextCounter",
|
||||
getCustomWidgets() {
|
||||
return {
|
||||
TEXT_COUNTER(node, inputName) {
|
||||
const el = document.createElement("div");
|
||||
Object.assign(el.style, {
|
||||
background: "#222",
|
||||
border: "1px solid #444",
|
||||
padding: "8px",
|
||||
borderRadius: "4px",
|
||||
fontSize: "12px",
|
||||
color: "#eee"
|
||||
});
|
||||
|
||||
const label = document.createElement("span");
|
||||
label.innerText = "Characters: 0";
|
||||
el.appendChild(label);
|
||||
|
||||
const widget = node.addDOMWidget(inputName, "TEXT_COUNTER", el, {
|
||||
getValue() { return ""; }, // Nothing to save
|
||||
setValue(v) { }, // Nothing to restore
|
||||
getMinHeight() { return 40; }
|
||||
});
|
||||
|
||||
// Disable serialization for this display-only widget
|
||||
widget.serialize = false;
|
||||
|
||||
// Custom method to update UI
|
||||
widget.updateCount = (text) => {
|
||||
label.innerText = `Characters: ${text.length}`;
|
||||
};
|
||||
|
||||
return { widget };
|
||||
}
|
||||
};
|
||||
},
|
||||
nodeCreated(node) {
|
||||
// Logic to link widgets after the node is initialized
|
||||
if (node.comfyClass === "MyTextNode") {
|
||||
const counterWidget = node.widgets.find(w => w.type === "TEXT_COUNTER");
|
||||
const textWidget = node.widgets.find(w => w.name === "text");
|
||||
|
||||
if (counterWidget && textWidget) {
|
||||
// Hook into the text widget's callback
|
||||
const oldCallback = textWidget.callback;
|
||||
textWidget.callback = function(v) {
|
||||
if (oldCallback) oldCallback.apply(this, arguments);
|
||||
counterWidget.updateCount(v);
|
||||
};
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
```
|
||||
51
docs/frontend-dom-fixtures.md
Normal file
51
docs/frontend-dom-fixtures.md
Normal file
@@ -0,0 +1,51 @@
|
||||
# Frontend DOM Fixture Strategy
|
||||
|
||||
This guide outlines how to reproduce the markup emitted by the Django templates while running Vitest in jsdom. The aim is to make it straightforward to write integration-style unit tests for managers and UI helpers without having to duplicate template fragments inline.
|
||||
|
||||
## Loading Template Markup
|
||||
|
||||
Vitest executes inside Node, so we can read the same HTML templates that ship with the extension:
|
||||
|
||||
1. Use the helper utilities from `tests/frontend/utils/domFixtures.js` to read files under the `templates/` directory.
|
||||
2. Mount the returned markup into `document.body` (or any custom container) before importing the module under test so its query selectors resolve correctly.
|
||||
|
||||
```js
|
||||
import { renderTemplate } from '../utils/domFixtures.js'; // adjust the relative path to your spec
|
||||
|
||||
beforeEach(() => {
|
||||
renderTemplate('loras.html', {
|
||||
dataset: { page: 'loras' }
|
||||
});
|
||||
});
|
||||
```
|
||||
|
||||
The helper ensures the dataset is applied to the container, which mirrors how Django sets `data-page` in production.
|
||||
|
||||
## Working with Partial Components
|
||||
|
||||
Many features are implemented as template partials located under `templates/components/`. When a test only needs a fragment (for example, the progress panel or context menu markup), load the component file directly:
|
||||
|
||||
```js
|
||||
const container = renderTemplate('components/progress_panel.html');
|
||||
|
||||
const progressPanel = container.querySelector('#progress-panel');
|
||||
```
|
||||
|
||||
This pattern avoids hand-written fixture strings and keeps the tests aligned with the actual markup.
|
||||
|
||||
## Resetting Between Tests
|
||||
|
||||
The shared Vitest setup clears `document.body` and storage APIs before each test. If a suite adds additional DOM nodes outside of the body or needs to reset custom attributes mid-test, use `resetDom()` exported from `domFixtures.js`.
|
||||
|
||||
```js
|
||||
import { resetDom } from '../utils/domFixtures.js';
|
||||
|
||||
afterEach(() => {
|
||||
resetDom();
|
||||
});
|
||||
```
|
||||
|
||||
## Future Enhancements
|
||||
|
||||
- Provide typed helpers for injecting mock script tags (e.g., replicating ComfyUI globals).
|
||||
- Compose higher-level fixtures that mimic specific pages (loras, checkpoints, recipes) once those managers receive dedicated suites.
|
||||
44
docs/frontend-filtering-test-matrix.md
Normal file
44
docs/frontend-filtering-test-matrix.md
Normal file
@@ -0,0 +1,44 @@
|
||||
# LoRA & Checkpoints Filtering/Sorting Test Matrix
|
||||
|
||||
This matrix captures the scenarios that Phase 3 frontend tests should cover for the LoRA and Checkpoint managers. It focuses on how search, filter, sort, and duplicate badge toggles interact so future specs can share fixtures and expectations.
|
||||
|
||||
## Scope
|
||||
|
||||
- **Components**: `PageControls`, `FilterManager`, `SearchManager`, and `ModelDuplicatesManager` wiring invoked through `CheckpointsPageManager` and `LorasPageManager`.
|
||||
- **Templates**: `templates/loras.html` and `templates/checkpoints.html` along with shared filter panel and toolbar partials.
|
||||
- **APIs**: Requests issued through `baseModelApi.fetchModels` (via `resetAndReload`/`refreshModels`) and duplicates badge updates.
|
||||
|
||||
## Shared Setup Considerations
|
||||
|
||||
1. Render full page templates using `renderLorasPage` / `renderCheckpointsPage` helpers before importing modules so DOM queries resolve.
|
||||
2. Stub storage helpers (`getStorageItem`, `setStorageItem`, `getSessionItem`, `setSessionItem`) to observe persistence behavior without mutating real storage.
|
||||
3. Mock `sidebarManager` to capture refresh calls triggered after sort/filter actions.
|
||||
4. Provide fake API implementations exposing `resetAndReload`, `refreshModels`, `fetchFromCivitai`, `toggleBulkMode`, and `clearCustomFilter` so control events remain asynchronous but deterministic.
|
||||
5. Supply a minimal `ModelDuplicatesManager` mock exposing `toggleDuplicateMode`, `checkDuplicatesCount`, and `updateDuplicatesBadgeAfterRefresh` to validate duplicate badge wiring.
|
||||
|
||||
## Scenario Matrix
|
||||
|
||||
| ID | Feature | Scenario | LoRAs Expectations | Checkpoints Expectations | Notes |
|
||||
| --- | --- | --- | --- | --- | --- |
|
||||
| F-01 | Search filter | Typing a query updates `pageState.filters.search`, persists to session, and triggers `resetAndReload` on submit | Validate `SearchManager` writes query and reloads via API stub; confirm LoRA cards pass query downstream | Same as LoRAs | Cover `enter` press and clicking search icon |
|
||||
| F-02 | Tag filter | Selecting a tag chip cycles include ➜ exclude ➜ clear, updates storage, and reloads results | Tag state stored under `filters.tags[tagName] = 'include'|'exclude'`; `FilterManager.applyFilters` persists and triggers `resetAndReload(true)` | Same; ensure base model tag set is scoped to checkpoints dataset | Include removal path |
|
||||
| F-03 | Base model filter | Toggling base model checkboxes updates `filters.baseModel`, persists, and reloads | Ensure only LoRA-supported models show; toggle multi-select | Ensure SDXL/Flux base models appear as expected | Capture UI state restored from storage on next init |
|
||||
| F-04 | Favorites-only | Clicking favorites toggle updates session flag and calls `resetAndReload(true)` | Button gains `.active` class and API called | Same | Verify duplicates badge refresh when active |
|
||||
| F-05 | Sort selection | Changing sort select saves preference (legacy + new format) and reloads | Confirm `PageControls.saveSortPreference` invoked with option and API called | Same with checkpoints-specific defaults | Cover `convertLegacySortFormat` branch |
|
||||
| F-06 | Filter persistence | Re-initializing manager loads stored filters/sort and updates DOM | Filters pre-populate chips/checkboxes; favorites state restored | Same | Requires simulating repeated construction |
|
||||
| F-07 | Combined filters | Applying search + tag + base model yields aggregated query params for fetch | Assert API receives merged filter payload | Same | Validate toast messaging for active filters |
|
||||
| F-08 | Clearing filters | Using "Clear filters" resets state, storage, and reloads list | `FilterManager.clearFilters` empties `filters`, removes active class, shows toast | Same | Ensure favorites-only toggle unaffected |
|
||||
| F-09 | Duplicate badge toggle | Pressing "Find duplicates" toggles duplicate mode and updates badge counts post-refresh | `ModelDuplicatesManager.toggleDuplicateMode` invoked and badge refresh called after API rebuild | Same plus checkpoint-specific duplicate badge dataset | Connects to future duplicate-specific specs |
|
||||
| F-10 | Bulk actions menu | Opening bulk dropdown keeps filters intact and closes on outside click | Validate dropdown class toggling and no unintended reload | Same | Guard against regression when dropdown interacts with filters |
|
||||
|
||||
## Automation Coverage Status
|
||||
|
||||
- ✅ F-01 Search filter, F-02 Tag filter, F-03 Base model filter, F-04 Favorites-only toggle, F-05 Sort selection, and F-09 Duplicate badge toggle are covered by `tests/frontend/components/pageControls.filtering.test.js` for both LoRA and checkpoint pages.
|
||||
- ⏳ F-06 Filter persistence, F-07 Combined filters, F-08 Clearing filters, and F-10 Bulk actions remain to be automated alongside upcoming bulk mode refinements.
|
||||
|
||||
## Coverage Gaps & Follow-Ups
|
||||
|
||||
- Write Vitest suites that exercise the matrix for both managers, sharing fixtures through page helpers to avoid duplication.
|
||||
- Capture API parameter assertions by inspecting `baseModelApi.fetchModels` mocks rather than relying solely on state mutations.
|
||||
- Add regression cases for legacy storage migrations (old filter keys) once fixtures exist for older payloads.
|
||||
- Extend duplicate badge coverage with scenarios where `checkDuplicatesCount` signals zero duplicates versus pending calculations.
|
||||
@@ -8,16 +8,26 @@ This roadmap tracks the planned rollout of automated testing for the ComfyUI LoR
|
||||
| --- | --- | --- | --- | --- |
|
||||
| Phase 0 | Establish baseline tooling | Add Node test runner, jsdom environment, and seed smoke tests | ✅ Complete | Vitest + jsdom configured, example state tests committed |
|
||||
| Phase 1 | Cover state management logic | Unit test selectors, derived data helpers, and storage utilities under `static/js/state` and `static/js/utils` | ✅ Complete | Storage helpers and state selectors now exercised via deterministic suites |
|
||||
| Phase 2 | Test AppCore orchestration | Simulate page bootstrapping, infinite scroll hooks, and manager registration using JSDOM DOM fixtures | 🟡 In Progress | AppCore initialization specs landed; expand to additional page wiring and scroll hooks |
|
||||
| Phase 3 | Validate page-specific managers | Add focused suites for `loras`, `checkpoints`, `embeddings`, and `recipes` managers covering filtering, sorting, and bulk actions | ⚪ Not Started | Consider shared helpers for mocking API modules and storage |
|
||||
| Phase 4 | Interaction-level regression tests | Exercise template fragments, modals, and menus to ensure UI wiring remains intact | ⚪ Not Started | Evaluate Playwright component testing or happy-path DOM snapshots |
|
||||
| Phase 5 | Continuous integration & coverage | Integrate frontend tests into CI workflow and track coverage metrics | ⚪ Not Started | Align reporting directories with backend coverage for unified reporting |
|
||||
| Phase 2 | Test AppCore orchestration | Simulate page bootstrapping, infinite scroll hooks, and manager registration using JSDOM DOM fixtures | ✅ Complete | AppCore initialization + page feature suites now validate manager wiring, infinite scroll hooks, and onboarding gating |
|
||||
| Phase 3 | Validate page-specific managers | Add focused suites for `loras`, `checkpoints`, `embeddings`, and `recipes` managers covering filtering, sorting, and bulk actions | ✅ Complete | LoRA/checkpoint suites expanded; embeddings + recipes managers now covered with initialization, filtering, and duplicate workflows |
|
||||
| Phase 4 | Interaction-level regression tests | Exercise template fragments, modals, and menus to ensure UI wiring remains intact | ✅ Complete | Vitest DOM suites cover NSFW selector, recipe modal editing, and global context menus |
|
||||
| Phase 5 | Continuous integration & coverage | Integrate frontend tests into CI workflow and track coverage metrics | ✅ Complete | CI workflow runs Vitest and aggregates V8 coverage into `coverage/frontend` via a dedicated script |
|
||||
|
||||
## Next Steps Checklist
|
||||
|
||||
- [x] Expand unit tests for `storageHelpers` covering migrations and namespace behavior.
|
||||
- [ ] Document DOM fixture strategy for reproducing template structures in tests.
|
||||
- [x] Document DOM fixture strategy for reproducing template structures in tests.
|
||||
- [x] Prototype AppCore initialization test that verifies manager bootstrapping with stubbed dependencies.
|
||||
- [ ] Evaluate integrating coverage reporting once test surface grows (> 20 specs).
|
||||
- [x] Add AppCore page feature suite exercising context menu creation and infinite scroll registration via DOM fixtures.
|
||||
- [x] Extend AppCore orchestration tests to cover manager wiring, bulk menu setup, and onboarding gating scenarios.
|
||||
- [x] Add interaction regression suites for context menus and recipe modals to complete Phase 4.
|
||||
- [x] Evaluate integrating coverage reporting once test surface grows (> 20 specs).
|
||||
- [x] Create shared fixtures for the loras and checkpoints pages once dedicated manager suites are added.
|
||||
- [x] Draft focused test matrix for loras/checkpoints manager filtering and sorting paths ahead of Phase 3.
|
||||
- [x] Implement LoRAs manager filtering/sorting specs for scenarios F-01–F-05 & F-09; queue remaining edge cases after duplicate/bulk flows stabilize.
|
||||
- [x] Implement checkpoints manager filtering/sorting specs for scenarios F-01–F-05 & F-09; cover remaining paths alongside bulk action work.
|
||||
- [x] Implement checkpoints page manager smoke tests covering initialization and duplicate badge wiring.
|
||||
- [x] Outline focused checkpoints scenarios (filtering, sorting, duplicate badge toggles) to feed into the shared test matrix.
|
||||
- [ ] Add duplicate badge regression coverage for zero/pending states after API refreshes.
|
||||
|
||||
Maintaining this roadmap alongside code changes will make it easier to append new automated test tasks and update their progress.
|
||||
|
||||
28
docs/library-switching.md
Normal file
28
docs/library-switching.md
Normal file
@@ -0,0 +1,28 @@
|
||||
# Library Switching and Preview Routes
|
||||
|
||||
Library switching no longer requires restarting the backend. The preview
|
||||
thumbnails shown in the UI are now served through a dynamic endpoint that
|
||||
resolves files against the folders registered for the active library at request
|
||||
time. This allows the multi-library flow to update model roots without touching
|
||||
the aiohttp router, so previews remain available immediately after a switch.
|
||||
|
||||
## How the dynamic preview endpoint works
|
||||
|
||||
* `config.get_preview_static_url()` now returns `/api/lm/previews?path=<encoded>`
|
||||
for any preview path. The raw filesystem location is URL encoded so that it
|
||||
can be passed through the query string without leaking directory structure in
|
||||
the route itself.【F:py/config.py†L398-L404】
|
||||
* `PreviewRoutes` exposes the `/api/lm/previews` handler which validates the
|
||||
decoded path against the directories registered for the current library. The
|
||||
request is rejected if it falls outside those roots or if the file does not
|
||||
exist.【F:py/routes/preview_routes.py†L5-L21】【F:py/routes/handlers/preview_handlers.py†L9-L48】
|
||||
* `Config` keeps an up-to-date cache of allowed preview roots. Every time a
|
||||
library is applied the cache is rebuilt using the declared LoRA, checkpoint
|
||||
and embedding directories (including symlink targets). The validation logic
|
||||
checks preview requests against this cache.【F:py/config.py†L51-L68】【F:py/config.py†L180-L248】【F:py/config.py†L332-L346】
|
||||
|
||||
Both the ComfyUI runtime (`LoraManager.add_routes`) and the standalone launcher
|
||||
(`StandaloneLoraManager.add_routes`) register the new preview routes instead of
|
||||
mounting a static directory per root. Switching libraries therefore works
|
||||
without restarting the application, and preview URLs generated before or after a
|
||||
switch continue to resolve correctly.【F:py/lora_manager.py†L21-L82】【F:standalone.py†L302-L315】
|
||||
449
docs/plan/model-modal-redesign.md
Normal file
449
docs/plan/model-modal-redesign.md
Normal file
@@ -0,0 +1,449 @@
|
||||
# Model Modal UI/UX 重构计划
|
||||
|
||||
> **Status**: Phase 1 Complete ✓
|
||||
> **Created**: 2026-02-06
|
||||
> **Target**: v2.x Release
|
||||
|
||||
---
|
||||
|
||||
## 1. 项目概述
|
||||
|
||||
### 1.1 背景与问题
|
||||
|
||||
当前 Model Modal 存在以下 UX 问题:
|
||||
|
||||
1. **空间利用率低** - 固定 800px 宽度,大屏环境下大量留白
|
||||
2. **Tab 切换繁琐** - 4 个 Tab(Examples/Description/Versions/Recipes)隐藏了重要信息
|
||||
3. **Examples 浏览不便** - 需持续向下滚动,无快速导航
|
||||
4. **添加自定义示例困难** - 需滚动到底部,操作路径长
|
||||
|
||||
### 1.2 设计目标
|
||||
|
||||
- **空间效率**: 利用 header 以下、sidebar 右侧的全部可用空间
|
||||
- **浏览体验**: 类似 Midjourney 的沉浸式图片浏览
|
||||
- **信息架构**: 关键元数据固定可见,次要信息可折叠
|
||||
- **操作效率**: 直觉化的键盘导航,减少点击次数
|
||||
|
||||
---
|
||||
|
||||
## 2. 设计方案
|
||||
|
||||
### 2.1 布局架构: Split-View Overlay
|
||||
|
||||
```
|
||||
┌──────────────────────────────────────────────────────────────────────┐
|
||||
│ HEADER (保持现有) │
|
||||
├──────────┬───────────────────────────────────────────────────────────┤
|
||||
│ │ ┌───────────────────────────┬────────────────────────┐ │
|
||||
│ FOLDER │ │ │ MODEL HEADER │ │
|
||||
│ SIDEBAR │ │ EXAMPLES SHOWCASE │ ├─ Name │ │
|
||||
│ (可折叠) │ │ │ ├─ Creator + Actions │ │
|
||||
│ │ │ ┌─────────────────┐ │ ├─ Tags │ │
|
||||
│ │ │ │ │ ├────────────────────────┤ │
|
||||
│ │ │ │ MAIN IMAGE │ │ COMPACT METADATA │ │
|
||||
│ │ │ │ (自适应高度) │ │ ├─ Ver | Base | Size │ │
|
||||
│ │ │ │ │ │ ├─ Location │ │
|
||||
│ │ │ └─────────────────┘ │ ├─ Usage Tips │ │
|
||||
│ │ │ │ ├─ Trigger Words │ │
|
||||
│ │ │ [PARAMS PREVIEW] │ ├─ Notes │ │
|
||||
│ │ │ (Prompt + Copy) ├────────────────────────┤ │
|
||||
│ │ │ │ CONTENT TABS │ │
|
||||
│ │ │ ┌─────────────────┐ │ [Desc][Versions][Rec] │ │
|
||||
│ │ │ │ THUMBNAIL RAIL │ │ │ │
|
||||
│ │ │ │ [1][2][3][4][+]│ │ TAB CONTENT AREA │ │
|
||||
│ │ │ └─────────────────┘ │ (Accordion / List) │ │
|
||||
│ │ └───────────────────────────┴────────────────────────┘ │
|
||||
└──────────┴───────────────────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
**尺寸规格**:
|
||||
- Sidebar 展开: Left 60% | Right 40%
|
||||
- Sidebar 折叠: Left 65% | Right 35%
|
||||
- 最小宽度: 1200px (低于此值触发移动端适配)
|
||||
|
||||
### 2.2 左侧: Examples Showcase
|
||||
|
||||
#### 2.2.1 组件结构
|
||||
|
||||
| 组件 | 描述 | 优先级 |
|
||||
|------|------|--------|
|
||||
| Main Image | 自适应容器,保持原始比例,最大高度 70vh | P0 |
|
||||
| Params Panel | 底部滑出面板,显示 Prompt/Negative/Params | P0 |
|
||||
| Thumbnail Rail | 底部横向滚动条,支持点击跳转 | P0 |
|
||||
| Add Button | Rail 最右侧 "+" 按钮,打开上传区 | P0 |
|
||||
| Nav Arrows | 图片左右两侧悬停显示 | P1 |
|
||||
|
||||
#### 2.2.2 图片悬停操作
|
||||
|
||||
```
|
||||
┌─────────────────┐
|
||||
│ [👁] [📌] [🗑] │ ← 查看参数 | 设为预览 | 删除
|
||||
│ │
|
||||
│ IMAGE │
|
||||
│ │
|
||||
└─────────────────┘
|
||||
```
|
||||
|
||||
#### 2.2.3 键盘导航
|
||||
|
||||
| 按键 | 功能 | 说明 |
|
||||
|------|------|------|
|
||||
| ← | 上一个 Example | 循环(首张时到最后一张) |
|
||||
| → | 下一个 Example | 循环(末张时到第一张) |
|
||||
| I | Toggle Params Panel | 显示/隐藏图片参数 |
|
||||
| C | Copy Prompt | 复制当前 Prompt 到剪贴板 |
|
||||
|
||||
### 2.3 右侧: Metadata + Content
|
||||
|
||||
#### 2.3.1 固定头部 (不可折叠)
|
||||
|
||||
```
|
||||
┌────────────────────────┐
|
||||
│ MODEL NAME [×] │
|
||||
│ [👤 Creator] [🌐 Civ] │
|
||||
│ [tag1] [tag2] [tag3] │
|
||||
├────────────────────────┤
|
||||
│ Ver: v1.0 Size: 96MB │
|
||||
│ Base: SDXL │
|
||||
│ 📁 /path/to/file │
|
||||
├────────────────────────┤
|
||||
│ USAGE TIPS [✏️] │
|
||||
│ [strength: 0.8] [+] │
|
||||
├────────────────────────┤
|
||||
│ TRIGGER WORDS [✏️] │
|
||||
│ [word1] [word2] [📋] │
|
||||
├────────────────────────┤
|
||||
│ NOTES [✏️] │
|
||||
│ "Add your notes..." │
|
||||
└────────────────────────┘
|
||||
```
|
||||
|
||||
#### 2.3.2 Tabs 设计
|
||||
|
||||
保留横向 Tab 切换,但优化内容展示:
|
||||
|
||||
| Tab | 内容 | 交互方式 |
|
||||
|-----|------|----------|
|
||||
| Description | About this version + Model Description | Accordion 折叠 |
|
||||
| Versions | 版本列表卡片 | 完整列表视图 |
|
||||
| Recipes | Recipe 卡片网格 | 网格布局 |
|
||||
|
||||
**Accordion 行为**:
|
||||
- 手风琴模式:同时只能展开一个 section
|
||||
- 默认:About this version 展开,Description 折叠
|
||||
- 动画:300ms ease-out
|
||||
|
||||
### 2.4 全局导航
|
||||
|
||||
#### 2.4.1 Model 切换
|
||||
|
||||
| 按键 | 功能 |
|
||||
|------|------|
|
||||
| ↑ | 上一个 Model |
|
||||
| ↓ | 下一个 Model |
|
||||
|
||||
**切换动画**:
|
||||
1. 当前 Modal 淡出 (150ms)
|
||||
2. 加载新 Model 数据
|
||||
3. 新 Modal 淡入 (150ms)
|
||||
4. 保持当前 Tab 状态(不重置到默认)
|
||||
|
||||
#### 2.4.2 首次使用提示
|
||||
|
||||
Modal 首次打开时,顶部显示提示条:
|
||||
```
|
||||
┌─────────────────────────────────────────────────────────────┐
|
||||
│ 💡 Tip: ↑↓ 切换模型 | ←→ 浏览示例 | I 查看参数 | ESC 关闭 │
|
||||
└─────────────────────────────────────────────────────────────┘
|
||||
```
|
||||
- 3 秒后自动淡出
|
||||
- 提供 "不再显示" 选项
|
||||
|
||||
---
|
||||
|
||||
## 3. 技术实现
|
||||
|
||||
### 3.1 文件结构变更
|
||||
|
||||
```
|
||||
static/
|
||||
├── js/
|
||||
│ └── components/
|
||||
│ └── model-modal/ # 新目录
|
||||
│ ├── index.js # 主入口
|
||||
│ ├── ModelModal.js # Modal 容器
|
||||
│ ├── ExampleShowcase.js # 左侧展示
|
||||
│ ├── ThumbnailRail.js # 缩略图导航
|
||||
│ ├── MetadataPanel.js # 右侧元数据
|
||||
│ ├── ContentTabs.js # Tabs 容器
|
||||
│ └── accordions/ # Accordion 组件
|
||||
│ ├── DescriptionAccordion.js
|
||||
│ └── VersionsList.js
|
||||
├── css/
|
||||
│ └── components/
|
||||
│ └── model-modal/ # 新目录
|
||||
│ ├── modal-overlay.css
|
||||
│ ├── showcase.css
|
||||
│ ├── thumbnail-rail.css
|
||||
│ ├── metadata.css
|
||||
│ └── tabs.css
|
||||
```
|
||||
|
||||
### 3.2 核心 CSS 架构
|
||||
|
||||
```css
|
||||
/* modal-overlay.css */
|
||||
.model-overlay {
|
||||
position: fixed;
|
||||
top: var(--header-height);
|
||||
left: var(--sidebar-width, 250px);
|
||||
right: 0;
|
||||
bottom: 0;
|
||||
z-index: var(--z-modal);
|
||||
|
||||
display: grid;
|
||||
grid-template-columns: 1.2fr 0.8fr;
|
||||
gap: 0;
|
||||
|
||||
background: var(--bg-color);
|
||||
animation: modalSlideIn 0.2s ease-out;
|
||||
}
|
||||
|
||||
.model-overlay.sidebar-collapsed {
|
||||
left: var(--sidebar-collapsed-width, 60px);
|
||||
grid-template-columns: 1.3fr 0.7fr;
|
||||
}
|
||||
|
||||
/* 移动端适配 */
|
||||
@media (max-width: 768px) {
|
||||
.model-overlay {
|
||||
left: 0;
|
||||
grid-template-columns: 1fr;
|
||||
grid-template-rows: auto 1fr;
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### 3.3 响应式断点
|
||||
|
||||
| 断点 | 布局 | 说明 |
|
||||
|------|------|------|
|
||||
| > 1400px | Split 60/40 | 大屏优化 |
|
||||
| 1200-1400px | Split 50/50 | 标准桌面 |
|
||||
| 768-1200px | Split 50/50 | 小屏桌面/平板 |
|
||||
| < 768px | Stack | 移动端:Examples 在上,Metadata 在下 |
|
||||
|
||||
---
|
||||
|
||||
## 4. 实施阶段
|
||||
|
||||
### Phase 1: 核心重构 (预计 2-3 周)
|
||||
|
||||
**目标**: MVP 可用,基础功能完整
|
||||
|
||||
**任务清单**:
|
||||
|
||||
- [ ] 创建新的文件结构和基础组件
|
||||
- [ ] 实现 Split-View Overlay 布局
|
||||
- [ ] CSS Grid 布局系统
|
||||
- [ ] Sidebar 状态联动
|
||||
- [ ] 响应式断点处理
|
||||
- [ ] 迁移左侧 Examples 区域
|
||||
- [ ] Main Image 自适应容器
|
||||
- [ ] Thumbnail Rail 组件
|
||||
- [ ] Params Panel 滑出动画
|
||||
- [ ] 实现新的快捷键系统
|
||||
- [ ] ↑↓ 切换 Model
|
||||
- [ ] ←→ 切换 Example
|
||||
- [ ] I/C/ESC 功能键
|
||||
- [ ] 移除旧 Modal 的 max-width 限制
|
||||
- [ ] 基础动画过渡
|
||||
|
||||
**验收标准**:
|
||||
- [ ] 新布局在各种屏幕尺寸下正常显示
|
||||
- [ ] 键盘导航正常工作
|
||||
- [ ] 无阻塞性 Bug
|
||||
|
||||
---
|
||||
|
||||
### Phase 2: 体验优化 (预计 1-2 周)
|
||||
|
||||
**目标**: 信息架构优化,交互细节完善
|
||||
|
||||
**任务清单**:
|
||||
|
||||
- [ ] Accordion 组件实现
|
||||
- [ ] Description Tab 的折叠面板
|
||||
- [ ] 手风琴交互逻辑
|
||||
- [ ] 动画优化
|
||||
- [ ] 右侧 Metadata 区域固定化
|
||||
- [ ] 滚动行为优化
|
||||
- [ ] 编辑功能迁移
|
||||
- [ ] Example 添加流程优化
|
||||
- [ ] Rail 上的 "+" 按钮
|
||||
- [ ] Inline Upload Area
|
||||
- [ ] 拖拽上传支持
|
||||
- [ ] Model 切换动画优化
|
||||
- [ ] 淡入淡出效果
|
||||
- [ ] 加载状态指示
|
||||
- [ ] 首次使用提示
|
||||
|
||||
**验收标准**:
|
||||
- [ ] Accordion 交互流畅
|
||||
- [ ] 添加 Example 操作路径 < 2 步
|
||||
- [ ] Model 切换视觉反馈清晰
|
||||
|
||||
---
|
||||
|
||||
### Phase 3: 功能完整化 (预计 1-2 周)
|
||||
|
||||
**目标**: 所有现有功能迁移完成
|
||||
|
||||
**任务清单**:
|
||||
|
||||
- [ ] Versions Tab 完整实现
|
||||
- [ ] 版本列表卡片
|
||||
- [ ] 下载/忽略/删除操作
|
||||
- [ ] 更新状态 Badge
|
||||
- [ ] Recipes Tab 完整实现
|
||||
- [ ] Recipe 卡片网格
|
||||
- [ ] 复制/应用操作
|
||||
- [ ] Tab 状态保持
|
||||
- [ ] 切换 Model 时保持当前 Tab
|
||||
- [ ] Tab 内容滚动位置记忆
|
||||
- [ ] 所有编辑功能迁移
|
||||
- [ ] Model Name 编辑
|
||||
- [ ] Base Model 编辑
|
||||
- [ ] File Name 编辑
|
||||
- [ ] Tags 编辑
|
||||
- [ ] Usage Tips 编辑
|
||||
- [ ] Notes 编辑
|
||||
|
||||
**验收标准**:
|
||||
- [ ] 所有现有功能可用
|
||||
- [ ] 单元测试覆盖率 > 80%
|
||||
|
||||
---
|
||||
|
||||
### Phase 4: 打磨与优化 (预计 1 周)
|
||||
|
||||
**目标**: 性能优化,边缘 case 处理
|
||||
|
||||
**任务清单**:
|
||||
|
||||
- [ ] 移动端适配完善
|
||||
- [ ] Stack 布局优化
|
||||
- [ ] 触摸手势支持(滑动切换)
|
||||
- [ ] 性能优化
|
||||
- [ ] 图片懒加载优化
|
||||
- [ ] 虚拟滚动(大量 Examples 时)
|
||||
- [ ] 减少重渲染
|
||||
- [ ] 无障碍支持
|
||||
- [ ] ARIA 标签
|
||||
- [ ] 键盘导航焦点管理
|
||||
- [ ] 屏幕阅读器测试
|
||||
- [ ] 动画性能优化
|
||||
- [ ] will-change 优化
|
||||
- [ ] 减少 layout thrashing
|
||||
|
||||
**验收标准**:
|
||||
- [ ] Lighthouse Performance > 90
|
||||
- [ ] 无障碍检查无严重问题
|
||||
|
||||
---
|
||||
|
||||
### Phase 5: 发布准备 (预计 3-5 天)
|
||||
|
||||
**目标**: 稳定版本,文档完整
|
||||
|
||||
**任务清单**:
|
||||
|
||||
- [ ] Bug 修复
|
||||
- [ ] 用户测试
|
||||
- [ ] 更新文档
|
||||
- [ ] README 更新
|
||||
- [ ] 快捷键说明
|
||||
- [ ] 截图/GIF 演示
|
||||
- [ ] 发布说明
|
||||
|
||||
---
|
||||
|
||||
## 5. 风险与应对
|
||||
|
||||
| 风险 | 影响 | 应对策略 |
|
||||
|------|------|----------|
|
||||
| 用户不适应新布局 | 中 | 提供设置选项,允许切换回旧版(临时) |
|
||||
| 性能问题(大量 Examples) | 高 | Phase 4 重点优化,必要时虚拟滚动 |
|
||||
| 移动端体验不佳 | 中 | 单独设计移动端布局,非简单缩放 |
|
||||
| 与现有扩展冲突 | 低 | 充分的回归测试 |
|
||||
|
||||
---
|
||||
|
||||
## 6. 关联文件
|
||||
|
||||
### 6.1 需修改的现有文件
|
||||
|
||||
```
|
||||
static/js/components/shared/ModelModal.js # 完全重构
|
||||
static/js/components/shared/showcase/ # 迁移至新目录
|
||||
static/css/components/lora-modal/ # 样式重写
|
||||
static/css/components/modal/_base.css # Overlay 样式调整
|
||||
```
|
||||
|
||||
### 6.2 参考资源
|
||||
|
||||
- [Midjourney Explore](https://www.midjourney.com/explore) - 交互参考
|
||||
- [Pinterest Pin View](https://www.pinterest.com) - 布局参考
|
||||
- [AGENTS.md](/AGENTS.md) - 项目代码规范
|
||||
|
||||
---
|
||||
|
||||
## 7. Checklist
|
||||
|
||||
### 7.1 启动前
|
||||
|
||||
- [ ] 创建 feature branch: `feature/model-modal-redesign`
|
||||
- [ ] 设置开发环境
|
||||
- [ ] 准备测试数据集(多种 Model 类型)
|
||||
|
||||
### 7.2 每个 Phase 完成时
|
||||
|
||||
- [ ] 代码审查
|
||||
- [ ] 功能测试
|
||||
- [ ] 更新本文档状态
|
||||
|
||||
### 7.3 发布前
|
||||
|
||||
- [ ] 完整回归测试
|
||||
- [ ] 更新 CHANGELOG
|
||||
- [ ] 更新版本号
|
||||
|
||||
---
|
||||
|
||||
## 8. 附录
|
||||
|
||||
### 8.1 命名规范
|
||||
|
||||
| 类型 | 规范 | 示例 |
|
||||
|------|------|------|
|
||||
| 文件 | kebab-case | `thumbnail-rail.js` |
|
||||
| 组件 | PascalCase | `ThumbnailRail` |
|
||||
| CSS 类 | BEM | `.thumbnail-rail__item--active` |
|
||||
| 变量 | camelCase | `currentExampleIndex` |
|
||||
|
||||
### 8.2 颜色规范
|
||||
|
||||
使用现有 CSS 变量,不引入新颜色:
|
||||
|
||||
```css
|
||||
--lora-accent: #4299e1;
|
||||
--lora-accent-l: 60%;
|
||||
--lora-accent-c: 0.2;
|
||||
--lora-accent-h: 250;
|
||||
--lora-surface: var(--card-bg);
|
||||
--lora-border: var(--border-color);
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
*Last Updated: 2026-02-06*
|
||||
71
docs/priority_tags_help.md
Normal file
71
docs/priority_tags_help.md
Normal file
@@ -0,0 +1,71 @@
|
||||
# Priority Tags Configuration Guide
|
||||
|
||||
This guide explains how to tailor the tag priority order that powers folder naming and tag suggestions in the LoRA Manager. You only need to edit the comma-separated list of entries shown in the **Priority Tags** field for each model type.
|
||||
|
||||
## 1. Pick the Model Type
|
||||
|
||||
In the **Priority Tags** dialog you will find one tab per model type (LoRA, Checkpoint, Embedding). Select the tab you want to update; changes on one tab do not affect the others.
|
||||
|
||||
## 2. Edit the Entry List
|
||||
|
||||
Inside the textarea you will see a line similar to:
|
||||
|
||||
```
|
||||
character, concept, style(toon|toon_style)
|
||||
```
|
||||
|
||||
This entire line is the **entry list**. Replace it with your own ordered list.
|
||||
|
||||
### Entry Rules
|
||||
|
||||
Each entry is separated by a comma, in order from highest to lowest priority:
|
||||
|
||||
- **Canonical tag only:** `realistic`
|
||||
- **Canonical tag with aliases:** `character(char|chars)`
|
||||
|
||||
Aliases live inside `()` and are separated with `|`. The canonical name is what appears in folder names and UI suggestions when any of the aliases are detected. Matching is case-insensitive.
|
||||
|
||||
## Use `{first_tag}` in Path Templates
|
||||
|
||||
When your path template contains `{first_tag}`, the app picks a folder name based on your priority list and the model’s own tags:
|
||||
|
||||
- It checks the priority list from top to bottom. If a canonical tag or any of its aliases appear in the model tags, that canonical name becomes the folder name.
|
||||
- If no priority tags are found but the model has tags, the very first model tag is used.
|
||||
- If the model has no tags at all, the folder falls back to `no tags`.
|
||||
|
||||
### Example
|
||||
|
||||
With a template like `/{model_type}/{first_tag}` and the priority entry list `character(char|chars), style(anime|toon)`:
|
||||
|
||||
| Model Tags | Folder Name | Why |
|
||||
| --- | --- | --- |
|
||||
| `["chars", "female"]` | `character` | `chars` matches the `character` alias, so the canonical wins. |
|
||||
| `["anime", "portrait"]` | `style` | `anime` hits the `style` entry, so its canonical label is used. |
|
||||
| `["portrait", "bw"]` | `portrait` | No priority match, so the first model tag is used. |
|
||||
| `[]` | `no tags` | Nothing to match, so the fallback is applied. |
|
||||
|
||||
## 3. Save the Settings
|
||||
|
||||
After editing the entry list, press **Enter** to save. Use **Shift+Enter** whenever you need a new line. Clicking outside the field also saves automatically. A success toast confirms the update.
|
||||
|
||||
## Examples
|
||||
|
||||
| Goal | Entry List |
|
||||
| --- | --- |
|
||||
| Prefer people over styles | `character, portraits, style(anime\|toon)` |
|
||||
| Group sci-fi variants | `sci-fi(scifi\|science_fiction), cyberpunk(cyber\|punk)` |
|
||||
| Alias shorthand tags | `realistic(real\|realisim), photorealistic(photo_real)` |
|
||||
|
||||
## Tips
|
||||
|
||||
- Keep canonical names short and meaningful—they become folder names.
|
||||
- Place the most important categories first; the first match wins.
|
||||
- Avoid duplicate canonical names within the same list; only the first instance is used.
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
- **Unexpected folder name?** Check that the canonical name you want is placed before other matches.
|
||||
- **Alias not working?** Ensure the alias is inside parentheses and separated with `|`, e.g. `character(char|chars)`.
|
||||
- **Validation error?** Look for missing parentheses or stray commas. Each entry must follow the `canonical(alias|alias)` pattern or just `canonical`.
|
||||
|
||||
With these basics you can quickly adapt Priority Tags to match your library’s organization style.
|
||||
69
docs/reference/danbooru_e621_categories.md
Normal file
69
docs/reference/danbooru_e621_categories.md
Normal file
@@ -0,0 +1,69 @@
|
||||
# Danbooru/E621 Tag Categories Reference
|
||||
|
||||
Reference for category values used in `danbooru_e621_merged.csv` tag files.
|
||||
|
||||
## Category Value Mapping
|
||||
|
||||
### Danbooru Categories
|
||||
|
||||
| Value | Description |
|
||||
|-------|-------------|
|
||||
| 0 | General |
|
||||
| 1 | Artist |
|
||||
| 2 | *(unused)* |
|
||||
| 3 | Copyright |
|
||||
| 4 | Character |
|
||||
| 5 | Meta |
|
||||
|
||||
### e621 Categories
|
||||
|
||||
| Value | Description |
|
||||
|-------|-------------|
|
||||
| 6 | *(unused)* |
|
||||
| 7 | General |
|
||||
| 8 | Artist |
|
||||
| 9 | Contributor |
|
||||
| 10 | Copyright |
|
||||
| 11 | Character |
|
||||
| 12 | Species |
|
||||
| 13 | *(unused)* |
|
||||
| 14 | Meta |
|
||||
| 15 | Lore |
|
||||
|
||||
## Danbooru Category Colors
|
||||
|
||||
| Description | Normal Color | Hover Color |
|
||||
|-------------|--------------|-------------|
|
||||
| General | #009be6 | #4bb4ff |
|
||||
| Artist | #ff8a8b | #ffc3c3 |
|
||||
| Copyright | #c797ff | #ddc9fb |
|
||||
| Character | #35c64a | #93e49a |
|
||||
| Meta | #ead084 | #f7e7c3 |
|
||||
|
||||
## CSV Column Structure
|
||||
|
||||
Each row in the merged CSV file contains 4 columns:
|
||||
|
||||
| Column | Description | Example |
|
||||
|--------|-------------|---------|
|
||||
| 1 | Tag name | `1girl`, `highres`, `solo` |
|
||||
| 2 | Category value (0-15) | `0`, `5`, `7` |
|
||||
| 3 | Post count | `6008644`, `5256195` |
|
||||
| 4 | Aliases (comma-separated, quoted) | `"1girls,sole_female"`, empty string |
|
||||
|
||||
### Sample Data
|
||||
|
||||
```
|
||||
1girl,0,6008644,"1girls,sole_female"
|
||||
highres,5,5256195,"high_res,high_resolution,hires"
|
||||
solo,0,5000954,"alone,female_solo,single,solo_female"
|
||||
long_hair,0,4350743,"/lh,longhair"
|
||||
mammal,12,3437444,"cetancodont,cetancodontamorph,feralmammal"
|
||||
anthro,7,3381927,"adult_anthro,anhtro,antho,anthro_horse"
|
||||
skirt,0,1557883,
|
||||
```
|
||||
|
||||
## Source
|
||||
|
||||
- [PR #312: Add danbooru_e621_merged.csv](https://github.com/DominikDoom/a1111-sd-webui-tagcomplete/pull/312)
|
||||
- [DraconicDragon/dbr-e621-lists-archive](https://github.com/DraconicDragon/dbr-e621-lists-archive)
|
||||
191
docs/technical/model_type_refactoring_todo.md
Normal file
191
docs/technical/model_type_refactoring_todo.md
Normal file
@@ -0,0 +1,191 @@
|
||||
# Model Type 字段重构 - 遗留工作清单
|
||||
|
||||
> **状态**: Phase 1-4 已完成 | **创建日期**: 2026-01-30
|
||||
> **相关文件**: `py/utils/models.py`, `py/services/model_query.py`, `py/services/checkpoint_scanner.py`, etc.
|
||||
|
||||
---
|
||||
|
||||
## 概述
|
||||
|
||||
本次重构旨在解决 `model_type` 字段语义不统一的问题。系统中有两个层面的"类型"概念:
|
||||
|
||||
1. **Scanner Type** (`scanner_type`): 架构层面的大类 - `lora`, `checkpoint`, `embedding`
|
||||
2. **Sub Type** (`sub_type`): 业务层面的细分类型 - `lora`/`locon`/`dora`, `checkpoint`/`diffusion_model`, `embedding`
|
||||
|
||||
重构目标是统一使用 `sub_type` 表示细分类型,保留 `model_type` 作为向后兼容的别名。
|
||||
|
||||
---
|
||||
|
||||
## 已完成工作 ✅
|
||||
|
||||
### Phase 1: 后端字段重命名
|
||||
- [x] `CheckpointMetadata.model_type` → `sub_type`
|
||||
- [x] `EmbeddingMetadata.model_type` → `sub_type`
|
||||
- [x] `model_scanner.py` `_build_cache_entry()` 同时处理 `sub_type` 和 `model_type`
|
||||
|
||||
### Phase 2: 查询逻辑更新
|
||||
- [x] `model_query.py` 新增 `resolve_sub_type()` 和 `normalize_sub_type()`
|
||||
- [x] ~~保持向后兼容的别名 `resolve_civitai_model_type`, `normalize_civitai_model_type`~~ (已在 Phase 5 移除)
|
||||
- [x] `ModelFilterSet.apply()` 更新为使用新的解析函数
|
||||
|
||||
### Phase 3: API 响应更新
|
||||
- [x] `LoraService.format_response()` 返回 `sub_type` ~~+ `model_type`~~ (已移除 `model_type`)
|
||||
- [x] `CheckpointService.format_response()` 返回 `sub_type` ~~+ `model_type`~~ (已移除 `model_type`)
|
||||
- [x] `EmbeddingService.format_response()` 返回 `sub_type` ~~+ `model_type`~~ (已移除 `model_type`)
|
||||
|
||||
### Phase 4: 前端更新
|
||||
- [x] `constants.js` 新增 `MODEL_SUBTYPE_DISPLAY_NAMES`
|
||||
- [x] `MODEL_TYPE_DISPLAY_NAMES` 作为别名保留
|
||||
|
||||
### Phase 5: 清理废弃代码 ✅
|
||||
- [x] 从 `ModelScanner._build_cache_entry()` 中移除 `model_type` 向后兼容代码
|
||||
- [x] 从 `CheckpointScanner` 中移除 `model_type` 兼容处理
|
||||
- [x] 从 `model_query.py` 中移除 `resolve_civitai_model_type` 和 `normalize_civitai_model_type` 别名
|
||||
- [x] 更新前端 `FilterManager.js` 使用 `sub_type` (已在使用 `MODEL_SUBTYPE_DISPLAY_NAMES`)
|
||||
- [x] 更新所有相关测试
|
||||
|
||||
---
|
||||
|
||||
## 遗留工作 ⏳
|
||||
|
||||
### Phase 5: 清理废弃代码 ✅ **已完成**
|
||||
|
||||
所有 Phase 5 的清理工作已完成:
|
||||
|
||||
#### 5.1 移除 `model_type` 字段的向后兼容代码 ✅
|
||||
- 从 `ModelScanner._build_cache_entry()` 中移除了 `model_type` 的设置
|
||||
- 现在只设置 `sub_type` 字段
|
||||
|
||||
#### 5.2 移除 CheckpointScanner 的 model_type 兼容处理 ✅
|
||||
- `adjust_metadata()` 现在只处理 `sub_type`
|
||||
- `adjust_cached_entry()` 现在只设置 `sub_type`
|
||||
|
||||
#### 5.3 移除 model_query 中的向后兼容别名 ✅
|
||||
- 移除了 `resolve_civitai_model_type = resolve_sub_type`
|
||||
- 移除了 `normalize_civitai_model_type = normalize_sub_type`
|
||||
|
||||
#### 5.4 前端清理 ✅
|
||||
- `FilterManager.js` 已经在使用 `MODEL_SUBTYPE_DISPLAY_NAMES` (通过别名 `MODEL_TYPE_DISPLAY_NAMES`)
|
||||
- API list endpoint 现在只返回 `sub_type`,不再返回 `model_type`
|
||||
- `ModelCard.js` 现在设置 `card.dataset.sub_type` (所有模型类型通用)
|
||||
- `CheckpointContextMenu.js` 现在读取 `card.dataset.sub_type`
|
||||
- `MoveManager.js` 现在处理 `cache_entry.sub_type`
|
||||
- `RecipeModal.js` 现在读取 `checkpoint.sub_type`
|
||||
|
||||
---
|
||||
|
||||
## 数据库迁移评估
|
||||
|
||||
### 当前状态
|
||||
- `persistent_model_cache.py` 使用 `civitai_model_type` 列存储 CivitAI 原始类型
|
||||
- 缓存 entry 中的 `sub_type` 在运行期动态计算
|
||||
- 数据库 schema **无需立即修改**
|
||||
|
||||
### 未来可选优化
|
||||
```sql
|
||||
-- 可选:在 models 表中添加 sub_type 列(与 civitai_model_type 保持一致但语义更清晰)
|
||||
ALTER TABLE models ADD COLUMN sub_type TEXT;
|
||||
|
||||
-- 数据迁移
|
||||
UPDATE models SET sub_type = civitai_model_type WHERE sub_type IS NULL;
|
||||
```
|
||||
|
||||
**建议**: 如果决定添加 `sub_type` 列,应与 Phase 5 一起进行。
|
||||
|
||||
---
|
||||
|
||||
## 测试覆盖率
|
||||
|
||||
### 新增/更新测试文件(已全部通过 ✅)
|
||||
|
||||
| 测试文件 | 数量 | 覆盖内容 |
|
||||
|---------|------|---------|
|
||||
| `tests/utils/test_models_sub_type.py` | 7 | Metadata sub_type 字段 |
|
||||
| `tests/services/test_model_query_sub_type.py` | 19 | sub_type 解析和过滤 |
|
||||
| `tests/services/test_checkpoint_scanner_sub_type.py` | 6 | CheckpointScanner sub_type |
|
||||
| `tests/services/test_service_format_response_sub_type.py` | 6 | API 响应 sub_type 包含 |
|
||||
| `tests/services/test_checkpoint_scanner.py` | 1 | Checkpoint 缓存 sub_type |
|
||||
| `tests/services/test_model_scanner.py` | 1 | adjust_cached_entry hook |
|
||||
| `tests/services/test_download_manager.py` | 1 | Checkpoint 下载 sub_type |
|
||||
|
||||
### 需要补充的测试(可选)
|
||||
|
||||
- [ ] 集成测试:验证前端过滤使用 sub_type 字段
|
||||
- [ ] 数据库迁移测试(如果执行可选优化)
|
||||
- [ ] 性能测试:确认 resolve_sub_type 的优先级查找没有显著性能影响
|
||||
|
||||
---
|
||||
|
||||
## 兼容性检查清单
|
||||
|
||||
### 已完成 ✅
|
||||
|
||||
- [x] 前端代码已全部改用 `sub_type` 字段
|
||||
- [x] API list endpoint 已移除 `model_type`,只返回 `sub_type`
|
||||
- [x] 后端 cache entry 已移除 `model_type`,只保留 `sub_type`
|
||||
- [x] 所有测试已更新通过
|
||||
- [x] 文档已更新
|
||||
|
||||
---
|
||||
|
||||
## 相关文件清单
|
||||
|
||||
### 核心文件
|
||||
```
|
||||
py/utils/models.py
|
||||
py/utils/constants.py
|
||||
py/services/model_scanner.py
|
||||
py/services/model_query.py
|
||||
py/services/checkpoint_scanner.py
|
||||
py/services/base_model_service.py
|
||||
py/services/lora_service.py
|
||||
py/services/checkpoint_service.py
|
||||
py/services/embedding_service.py
|
||||
```
|
||||
|
||||
### 前端文件
|
||||
```
|
||||
static/js/utils/constants.js
|
||||
static/js/managers/FilterManager.js
|
||||
static/js/managers/MoveManager.js
|
||||
static/js/components/shared/ModelCard.js
|
||||
static/js/components/ContextMenu/CheckpointContextMenu.js
|
||||
static/js/components/RecipeModal.js
|
||||
```
|
||||
|
||||
### 测试文件
|
||||
```
|
||||
tests/utils/test_models_sub_type.py
|
||||
tests/services/test_model_query_sub_type.py
|
||||
tests/services/test_checkpoint_scanner_sub_type.py
|
||||
tests/services/test_service_format_response_sub_type.py
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 风险评估
|
||||
|
||||
| 风险项 | 影响 | 缓解措施 |
|
||||
|-------|------|---------|
|
||||
| ~~第三方代码依赖 `model_type`~~ | ~~高~~ | ~~保持别名至少 1 个 major 版本~~ ✅ 已完成移除 |
|
||||
| ~~数据库 schema 变更~~ | ~~中~~ | ~~暂缓 schema 变更,仅运行时计算~~ ✅ 无需变更 |
|
||||
| ~~前端过滤失效~~ | ~~中~~ | ~~全面的集成测试覆盖~~ ✅ 测试通过 |
|
||||
| CivitAI API 变化 | 低 | 保持多源解析策略 |
|
||||
|
||||
---
|
||||
|
||||
## 时间线
|
||||
|
||||
- **v1.x**: Phase 1-4 已完成,保持向后兼容
|
||||
- **v2.0 (当前)**: ✅ Phase 5 已完成 - `model_type` 兼容代码已移除
|
||||
- API list endpoint 只返回 `sub_type`
|
||||
- Cache entry 只保留 `sub_type`
|
||||
- 移除了 `resolve_civitai_model_type` 和 `normalize_civitai_model_type` 别名
|
||||
|
||||
---
|
||||
|
||||
## 备注
|
||||
|
||||
- 重构期间发现 `civitai_model_type` 数据库列命名尚可,但语义上应理解为存储 CivitAI API 返回的原始类型值
|
||||
- Checkpoint 的 `diffusion_model` sub_type 不能通过 CivitAI API 获取,必须通过文件路径(model root)判断
|
||||
- LoRA 的 sub_type(lora/locon/dora)直接来自 CivitAI API 的 `version_info.model.type`
|
||||
26
docs/testing/coverage_analysis.md
Normal file
26
docs/testing/coverage_analysis.md
Normal file
@@ -0,0 +1,26 @@
|
||||
# Backend Test Coverage Notes
|
||||
|
||||
## Pytest Execution
|
||||
- Command: `python -m pytest`
|
||||
- Result: All 283 collected tests passed in the current environment.
|
||||
- Coverage tooling (``pytest-cov``/``coverage``) is unavailable in the offline sandbox, so line-level metrics could not be generated. The earlier attempt to install ``pytest-cov`` failed because the package index cannot be reached from the container.
|
||||
|
||||
## High-Priority Gaps to Address
|
||||
|
||||
### 1. Standalone server bootstrapping
|
||||
* **Source:** [`standalone.py`](../../standalone.py)
|
||||
* **Why it matters:** The standalone entry point wires together the aiohttp application, static asset routes, model-route registration, and configuration validation. None of these behaviours are covered by automated tests, leaving regressions in bootstrapping logic undetected.
|
||||
* **Suggested coverage:** Add integration-style tests that instantiate `StandaloneServer`/`StandaloneLoraManager` with temporary settings and assert that routes (HTTP + websocket) are registered, configuration warnings fire for missing paths, and the mock ComfyUI shims behave as expected.
|
||||
|
||||
### 2. Model service registration factory
|
||||
* **Source:** [`py/services/model_service_factory.py`](../../py/services/model_service_factory.py)
|
||||
* **Why it matters:** The factory coordinates which model services and routes the API exposes, including error handling when unknown model types are requested. No current tests verify registration, memoization of route instances, or the logging path on failures.
|
||||
* **Suggested coverage:** Unit tests that exercise `register_model_type`, `get_route_instance`, error branches in `get_service_class`/`get_route_class`, and `setup_all_routes` when a route setup raises. Use lightweight fakes to confirm the logger is called and state is cleared via `clear_registrations`.
|
||||
|
||||
### 3. Server-side i18n helper
|
||||
* **Source:** [`py/services/server_i18n.py`](../../py/services/server_i18n.py)
|
||||
* **Why it matters:** Template rendering relies on the `ServerI18nManager` to load locale JSON, perform key lookups, and format parameters. The fallback logic (dot-notation lookup, English fallbacks, placeholder substitution) is untested, so malformed locale files or regressions in placeholder handling would slip through.
|
||||
* **Suggested coverage:** Tests that load fixture locale dictionaries, assert `set_locale` fallbacks, verify nested key resolution and placeholder substitution, and ensure missing keys return the original identifier.
|
||||
|
||||
## Next Steps
|
||||
Prioritize creating focused unit tests around these modules, then re-run pytest once coverage tooling is available to confirm the new tests close the identified gaps.
|
||||
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|
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example_workflows/Lora_Cycler.jpg
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|
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1
example_workflows/Lora_Cycler.json
Normal file
1
example_workflows/Lora_Cycler.json
Normal file
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BIN
example_workflows/Lora_Manager_Basic.jpg
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example_workflows/Lora_Manager_Basic.jpg
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|
After Width: | Height: | Size: 668 KiB |
1
example_workflows/Lora_Manager_Basic.json
Normal file
1
example_workflows/Lora_Manager_Basic.json
Normal file
File diff suppressed because one or more lines are too long
BIN
example_workflows/Lora_Randomizer.jpg
Normal file
BIN
example_workflows/Lora_Randomizer.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 739 KiB |
1
example_workflows/Lora_Randomizer.json
Normal file
1
example_workflows/Lora_Randomizer.json
Normal file
File diff suppressed because one or more lines are too long
413
locales/de.json
413
locales/de.json
@@ -10,7 +10,8 @@
|
||||
"next": "Weiter",
|
||||
"backToTop": "Nach oben",
|
||||
"settings": "Einstellungen",
|
||||
"help": "Hilfe"
|
||||
"help": "Hilfe",
|
||||
"add": "Hinzufügen"
|
||||
},
|
||||
"status": {
|
||||
"loading": "Wird geladen...",
|
||||
@@ -31,7 +32,8 @@
|
||||
"japanese": "日本語",
|
||||
"korean": "한국어",
|
||||
"french": "Français",
|
||||
"spanish": "Español"
|
||||
"spanish": "Español",
|
||||
"Hebrew": "עברית"
|
||||
},
|
||||
"fileSize": {
|
||||
"zero": "0 Bytes",
|
||||
@@ -100,7 +102,12 @@
|
||||
"checkpointNameCopied": "Checkpoint-Name kopiert",
|
||||
"toggleBlur": "Unschärfe umschalten",
|
||||
"show": "Anzeigen",
|
||||
"openExampleImages": "Beispielbilder-Ordner öffnen"
|
||||
"openExampleImages": "Beispielbilder-Ordner öffnen",
|
||||
"replacePreview": "Vorschau ersetzen",
|
||||
"copyCheckpointName": "Checkpoint-Name kopieren",
|
||||
"copyEmbeddingName": "Embedding-Name kopieren",
|
||||
"sendCheckpointToWorkflow": "An ComfyUI senden",
|
||||
"sendEmbeddingToWorkflow": "An ComfyUI senden"
|
||||
},
|
||||
"nsfw": {
|
||||
"matureContent": "Nicht jugendfreie Inhalte",
|
||||
@@ -114,12 +121,20 @@
|
||||
"updateFailed": "Fehler beim Aktualisieren des Favoriten-Status"
|
||||
},
|
||||
"sendToWorkflow": {
|
||||
"checkpointNotImplemented": "Checkpoint an Workflow senden - Funktion wird implementiert"
|
||||
"checkpointNotImplemented": "Checkpoint an Workflow senden - Funktion wird implementiert",
|
||||
"missingPath": "Modellpfad für diese Karte konnte nicht ermittelt werden"
|
||||
},
|
||||
"exampleImages": {
|
||||
"checkError": "Fehler beim Überprüfen der Beispielbilder",
|
||||
"missingHash": "Fehlende Modell-Hash-Informationen.",
|
||||
"noRemoteImagesAvailable": "Keine Remote-Beispielbilder für dieses Modell auf Civitai verfügbar"
|
||||
},
|
||||
"badges": {
|
||||
"update": "Update",
|
||||
"updateAvailable": "Update verfügbar"
|
||||
},
|
||||
"usage": {
|
||||
"timesUsed": "Verwendungsanzahl"
|
||||
}
|
||||
},
|
||||
"globalContextMenu": {
|
||||
@@ -128,12 +143,33 @@
|
||||
"missingPath": "Bitte legen Sie einen Speicherort fest, bevor Sie Beispielbilder herunterladen.",
|
||||
"unavailable": "Beispielbild-Downloads sind noch nicht verfügbar. Versuchen Sie es erneut, nachdem die Seite vollständig geladen ist."
|
||||
},
|
||||
"checkModelUpdates": {
|
||||
"label": "Auf Updates prüfen",
|
||||
"loading": "Prüfe auf {type}-Updates...",
|
||||
"success": "{count} Update(s) für {type} gefunden",
|
||||
"none": "Alle {type} sind auf dem neuesten Stand",
|
||||
"error": "Fehler beim Prüfen auf {type}-Updates: {message}"
|
||||
},
|
||||
"cleanupExampleImages": {
|
||||
"label": "Beispielbild-Ordner bereinigen",
|
||||
"success": "{count} Ordner wurden in den Papierkorb verschoben",
|
||||
"none": "Keine Beispielbild-Ordner mussten bereinigt werden",
|
||||
"partial": "Bereinigung abgeschlossen, {failures} Ordner übersprungen",
|
||||
"error": "Fehler beim Bereinigen der Beispielbild-Ordner: {message}"
|
||||
},
|
||||
"fetchMissingLicenses": {
|
||||
"label": "Refresh license metadata",
|
||||
"loading": "Refreshing license metadata for {typePlural}...",
|
||||
"success": "Updated license metadata for {count} {typePlural}",
|
||||
"none": "All {typePlural} already have license metadata",
|
||||
"error": "Failed to refresh license metadata for {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Recipe-Daten reparieren",
|
||||
"loading": "Recipe-Daten werden repariert...",
|
||||
"success": "{count} Rezepte erfolgreich repariert.",
|
||||
"cancelled": "Reparatur abgebrochen. {count} Rezepte wurden repariert.",
|
||||
"error": "Recipe-Reparatur fehlgeschlagen: {message}"
|
||||
}
|
||||
},
|
||||
"header": {
|
||||
@@ -163,14 +199,35 @@
|
||||
"creator": "Ersteller",
|
||||
"title": "Rezept-Titel",
|
||||
"loraName": "LoRA-Dateiname",
|
||||
"loraModel": "LoRA-Modellname"
|
||||
"loraModel": "LoRA-Modellname",
|
||||
"prompt": "Prompt"
|
||||
}
|
||||
},
|
||||
"filter": {
|
||||
"title": "Modelle filtern",
|
||||
"presets": "Voreinstellungen",
|
||||
"savePreset": "Aktive Filter als neue Voreinstellung speichern.",
|
||||
"savePresetDisabledActive": "Speichern nicht möglich: Eine Voreinstellung ist bereits aktiv. Ändern Sie die Filter, um eine neue Voreinstellung zu speichern",
|
||||
"savePresetDisabledNoFilters": "Wählen Sie zuerst Filter aus, um als Voreinstellung zu speichern",
|
||||
"savePresetPrompt": "Voreinstellungsname eingeben:",
|
||||
"presetClickTooltip": "Voreinstellung \"{name}\" anwenden",
|
||||
"presetDeleteTooltip": "Voreinstellung löschen",
|
||||
"presetDeleteConfirm": "Voreinstellung \"{name}\" löschen?",
|
||||
"presetDeleteConfirmClick": "Zum Bestätigen erneut klicken",
|
||||
"presetOverwriteConfirm": "Voreinstellung \"{name}\" existiert bereits. Überschreiben?",
|
||||
"presetNamePlaceholder": "Voreinstellungsname...",
|
||||
"baseModel": "Basis-Modell",
|
||||
"modelTags": "Tags (Top 20)",
|
||||
"clearAll": "Alle Filter löschen"
|
||||
"modelTypes": "Model Types",
|
||||
"license": "Lizenz",
|
||||
"noCreditRequired": "Kein Credit erforderlich",
|
||||
"allowSellingGeneratedContent": "Verkauf erlaubt",
|
||||
"noTags": "Keine Tags",
|
||||
"clearAll": "Alle Filter löschen",
|
||||
"any": "Beliebig",
|
||||
"all": "Alle",
|
||||
"tagLogicAny": "Jedes Tag abgleichen (ODER)",
|
||||
"tagLogicAll": "Alle Tags abgleichen (UND)"
|
||||
},
|
||||
"theme": {
|
||||
"toggle": "Theme wechseln",
|
||||
@@ -180,6 +237,7 @@
|
||||
},
|
||||
"actions": {
|
||||
"checkUpdates": "Updates prüfen",
|
||||
"notifications": "Benachrichtigungen",
|
||||
"support": "Unterstützung"
|
||||
}
|
||||
},
|
||||
@@ -187,17 +245,33 @@
|
||||
"civitaiApiKey": "Civitai API Key",
|
||||
"civitaiApiKeyPlaceholder": "Geben Sie Ihren Civitai API Key ein",
|
||||
"civitaiApiKeyHelp": "Wird für die Authentifizierung beim Herunterladen von Modellen von Civitai verwendet",
|
||||
"openSettingsFileLocation": {
|
||||
"label": "Einstellungsordner öffnen",
|
||||
"tooltip": "Den Ordner mit der settings.json öffnen",
|
||||
"success": "Einstellungsordner geöffnet",
|
||||
"failed": "Einstellungsordner konnte nicht geöffnet werden",
|
||||
"copied": "Einstellungspfad in die Zwischenablage kopiert: {{path}}",
|
||||
"clipboardFallback": "Einstellungspfad: {{path}}"
|
||||
},
|
||||
"sections": {
|
||||
"contentFiltering": "Inhaltsfilterung",
|
||||
"videoSettings": "Video-Einstellungen",
|
||||
"layoutSettings": "Layout-Einstellungen",
|
||||
"folderSettings": "Ordner-Einstellungen",
|
||||
"priorityTags": "Prioritäts-Tags",
|
||||
"downloadPathTemplates": "Download-Pfad-Vorlagen",
|
||||
"exampleImages": "Beispielbilder",
|
||||
"updateFlags": "Update-Markierungen",
|
||||
"autoOrganize": "Auto-organize",
|
||||
"misc": "Verschiedenes",
|
||||
"metadataArchive": "Metadaten-Archiv-Datenbank",
|
||||
"storageLocation": "Einstellungsort",
|
||||
"proxySettings": "Proxy-Einstellungen"
|
||||
},
|
||||
"storage": {
|
||||
"locationLabel": "Portabler Modus",
|
||||
"locationHelp": "Aktiviere, um settings.json im Repository zu belassen; deaktiviere, um es im Benutzerkonfigurationsordner zu speichern."
|
||||
},
|
||||
"contentFiltering": {
|
||||
"blurNsfwContent": "NSFW-Inhalte unscharf stellen",
|
||||
"blurNsfwContentHelp": "Nicht jugendfreie (NSFW) Vorschaubilder unscharf stellen",
|
||||
@@ -208,6 +282,15 @@
|
||||
"autoplayOnHover": "Videos bei Hover automatisch abspielen",
|
||||
"autoplayOnHoverHelp": "Video-Vorschauen nur beim Darüberfahren mit der Maus abspielen"
|
||||
},
|
||||
"autoOrganizeExclusions": {
|
||||
"label": "Auto-Organisierungs-Ausnahmen",
|
||||
"placeholder": "Beispiel: curated/*, */backups/*; *_temp.safetensors",
|
||||
"help": "Dateien überspringen, die mit diesen Wildcard-Mustern übereinstimmen. Mehrere Muster mit Kommas oder Semikolons trennen.",
|
||||
"validation": {
|
||||
"noPatterns": "Geben Sie mindestens ein Muster ein, getrennt durch Kommas oder Semikolons.",
|
||||
"saveFailed": "Fehler beim Speichern der Ausschlüsse: {message}"
|
||||
}
|
||||
},
|
||||
"layoutSettings": {
|
||||
"displayDensity": "Anzeige-Dichte",
|
||||
"displayDensityOptions": {
|
||||
@@ -217,31 +300,67 @@
|
||||
},
|
||||
"displayDensityHelp": "Wählen Sie, wie viele Karten pro Zeile angezeigt werden sollen:",
|
||||
"displayDensityDetails": {
|
||||
"default": "Standard: 5 (1080p), 6 (2K), 8 (4K)",
|
||||
"medium": "Mittel: 6 (1080p), 7 (2K), 9 (4K)",
|
||||
"compact": "Kompakt: 7 (1080p), 8 (2K), 10 (4K)"
|
||||
"default": "5 (1080p), 6 (2K), 8 (4K)",
|
||||
"medium": "6 (1080p), 7 (2K), 9 (4K)",
|
||||
"compact": "7 (1080p), 8 (2K), 10 (4K)"
|
||||
},
|
||||
"displayDensityWarning": "Warnung: Höhere Dichten können bei Systemen mit begrenzten Ressourcen zu Performance-Problemen führen.",
|
||||
"showFolderSidebar": "Ordner-Seitenleiste anzeigen",
|
||||
"showFolderSidebarHelp": "Blenden Sie die Ordner-Navigationsleiste auf den Modellseiten ein oder aus. Wenn deaktiviert, bleiben Seitenleiste und Hoverbereich verborgen.",
|
||||
"cardInfoDisplay": "Karten-Info-Anzeige",
|
||||
"cardInfoDisplayOptions": {
|
||||
"always": "Immer sichtbar",
|
||||
"hover": "Bei Hover anzeigen"
|
||||
},
|
||||
"cardInfoDisplayHelp": "Wählen Sie, wann Modellinformationen und Aktionsschaltflächen angezeigt werden sollen:",
|
||||
"cardInfoDisplayDetails": {
|
||||
"always": "Immer sichtbar: Kopf- und Fußzeilen sind immer sichtbar",
|
||||
"hover": "Bei Hover anzeigen: Kopf- und Fußzeilen erscheinen nur beim Darüberfahren mit der Maus"
|
||||
}
|
||||
"cardInfoDisplayHelp": "Wählen Sie, wann Modellinformationen und Aktionsschaltflächen angezeigt werden sollen",
|
||||
"modelCardFooterAction": "Aktion der Modellkarten-Schaltfläche",
|
||||
"modelCardFooterActionOptions": {
|
||||
"exampleImages": "Beispielbilder öffnen",
|
||||
"replacePreview": "Vorschau ersetzen"
|
||||
},
|
||||
"modelCardFooterActionHelp": "Wähle aus, was die Schaltfläche unten rechts auf der Karte ausführt",
|
||||
"modelNameDisplay": "Anzeige des Modellnamens",
|
||||
"modelNameDisplayOptions": {
|
||||
"modelName": "Modellname",
|
||||
"fileName": "Dateiname"
|
||||
},
|
||||
"modelNameDisplayHelp": "Wählen Sie aus, was in der Fußzeile der Modellkarte angezeigt werden soll"
|
||||
},
|
||||
"folderSettings": {
|
||||
"activeLibrary": "Aktive Bibliothek",
|
||||
"activeLibraryHelp": "Zwischen den konfigurierten Bibliotheken wechseln, um die Standardordner zu aktualisieren. Eine Änderung der Auswahl lädt die Seite neu.",
|
||||
"loadingLibraries": "Bibliotheken werden geladen...",
|
||||
"noLibraries": "Keine Bibliotheken konfiguriert",
|
||||
"defaultLoraRoot": "Standard-LoRA-Stammordner",
|
||||
"defaultLoraRootHelp": "Legen Sie den Standard-LoRA-Stammordner für Downloads, Importe und Verschiebungen fest",
|
||||
"defaultCheckpointRoot": "Standard-Checkpoint-Stammordner",
|
||||
"defaultCheckpointRootHelp": "Legen Sie den Standard-Checkpoint-Stammordner für Downloads, Importe und Verschiebungen fest",
|
||||
"defaultUnetRoot": "Standard-Diffusion-Modell-Stammordner",
|
||||
"defaultUnetRootHelp": "Legen Sie den Standard-Diffusion-Modell-(UNET)-Stammordner für Downloads, Importe und Verschiebungen fest",
|
||||
"defaultEmbeddingRoot": "Standard-Embedding-Stammordner",
|
||||
"defaultEmbeddingRootHelp": "Legen Sie den Standard-Embedding-Stammordner für Downloads, Importe und Verschiebungen fest",
|
||||
"noDefault": "Kein Standard"
|
||||
},
|
||||
"priorityTags": {
|
||||
"title": "Prioritäts-Tags",
|
||||
"description": "Passen Sie die Tag-Prioritätsreihenfolge für jeden Modelltyp an (z. B. character, concept, style(toon|toon_style))",
|
||||
"placeholder": "character, concept, style(toon|toon_style)",
|
||||
"helpLinkLabel": "Prioritäts-Tags-Hilfe öffnen",
|
||||
"modelTypes": {
|
||||
"lora": "LoRA",
|
||||
"checkpoint": "Checkpoint",
|
||||
"embedding": "Embedding"
|
||||
},
|
||||
"saveSuccess": "Prioritäts-Tags aktualisiert.",
|
||||
"saveError": "Prioritäts-Tags konnten nicht aktualisiert werden.",
|
||||
"loadingSuggestions": "Lade Vorschläge...",
|
||||
"validation": {
|
||||
"missingClosingParen": "Eintrag {index} fehlt eine schließende Klammer.",
|
||||
"missingCanonical": "Eintrag {index} muss einen kanonischen Tag-Namen enthalten.",
|
||||
"duplicateCanonical": "Der kanonische Tag \"{tag}\" kommt mehrfach vor.",
|
||||
"unknown": "Ungültige Prioritäts-Tag-Konfiguration."
|
||||
}
|
||||
},
|
||||
"downloadPathTemplates": {
|
||||
"title": "Download-Pfad-Vorlagen",
|
||||
"help": "Konfigurieren Sie Ordnerstrukturen für verschiedene Modelltypen beim Herunterladen von Civitai.",
|
||||
@@ -289,6 +408,14 @@
|
||||
"download": "Herunterladen",
|
||||
"restartRequired": "Neustart erforderlich"
|
||||
},
|
||||
"updateFlagStrategy": {
|
||||
"label": "Strategie für Update-Markierungen",
|
||||
"help": "Entscheide, ob Update-Badges nur dann erscheinen, wenn eine neue Version dasselbe Basismodell wie deine lokalen Dateien verwendet, oder sobald es irgendein neueres Release für dieses Modell gibt.",
|
||||
"options": {
|
||||
"sameBase": "Updates nach Basismodell abgleichen",
|
||||
"any": "Jede verfügbare Aktualisierung markieren"
|
||||
}
|
||||
},
|
||||
"misc": {
|
||||
"includeTriggerWords": "Trigger Words in LoRA-Syntax einschließen",
|
||||
"includeTriggerWordsHelp": "Trainierte Trigger Words beim Kopieren der LoRA-Syntax in die Zwischenablage einschließen"
|
||||
@@ -348,12 +475,17 @@
|
||||
"dateAsc": "Älteste",
|
||||
"size": "Dateigröße",
|
||||
"sizeDesc": "Größte",
|
||||
"sizeAsc": "Kleinste"
|
||||
"sizeAsc": "Kleinste",
|
||||
"usage": "Anzahl Nutzung",
|
||||
"usageDesc": "Meiste",
|
||||
"usageAsc": "Wenigste"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "Modelliste aktualisieren",
|
||||
"quick": "Schnelle Aktualisierung (inkrementell)",
|
||||
"full": "Vollständiger Neuaufbau (komplett)"
|
||||
"quick": "Änderungen synchronisieren",
|
||||
"quickTooltip": "Nach neuen oder fehlenden Modelldateien suchen, damit die Liste aktuell bleibt.",
|
||||
"full": "Cache neu aufbauen",
|
||||
"fullTooltip": "Alle Modelldetails aus Metadatendateien neu laden – nutzen, wenn die Bibliothek veraltet wirkt oder nach manuellen Änderungen."
|
||||
},
|
||||
"fetch": {
|
||||
"title": "Metadaten von Civitai abrufen",
|
||||
@@ -374,6 +506,13 @@
|
||||
"favorites": {
|
||||
"title": "Nur Favoriten anzeigen",
|
||||
"action": "Favoriten"
|
||||
},
|
||||
"updates": {
|
||||
"title": "Nur Modelle mit verfügbaren Updates anzeigen",
|
||||
"action": "Updates",
|
||||
"menuLabel": "Weitere Update-Optionen anzeigen",
|
||||
"check": "Updates prüfen",
|
||||
"checkTooltip": "Die Aktualisierungssuche kann einige Zeit dauern."
|
||||
}
|
||||
},
|
||||
"bulkOperations": {
|
||||
@@ -382,8 +521,10 @@
|
||||
"viewSelected": "Auswahl anzeigen",
|
||||
"addTags": "Allen Tags hinzufügen",
|
||||
"setBaseModel": "Basis-Modell für alle festlegen",
|
||||
"setContentRating": "Inhaltsbewertung für alle festlegen",
|
||||
"copyAll": "Alle Syntax kopieren",
|
||||
"refreshAll": "Alle Metadaten aktualisieren",
|
||||
"checkUpdates": "Auswahl auf Updates prüfen",
|
||||
"moveAll": "Alle in Ordner verschieben",
|
||||
"autoOrganize": "Automatisch organisieren",
|
||||
"deleteAll": "Alle Modelle löschen",
|
||||
@@ -400,6 +541,7 @@
|
||||
},
|
||||
"contextMenu": {
|
||||
"refreshMetadata": "Civitai-Daten aktualisieren",
|
||||
"checkUpdates": "Updates prüfen",
|
||||
"relinkCivitai": "Mit Civitai neu verknüpfen",
|
||||
"copySyntax": "LoRA-Syntax kopieren",
|
||||
"copyFilename": "Modell-Dateiname kopieren",
|
||||
@@ -411,6 +553,7 @@
|
||||
"replacePreview": "Vorschau ersetzen",
|
||||
"setContentRating": "Inhaltsbewertung festlegen",
|
||||
"moveToFolder": "In Ordner verschieben",
|
||||
"repairMetadata": "Metadaten reparieren",
|
||||
"excludeModel": "Modell ausschließen",
|
||||
"deleteModel": "Modell löschen",
|
||||
"shareRecipe": "Rezept teilen",
|
||||
@@ -421,6 +564,9 @@
|
||||
},
|
||||
"recipes": {
|
||||
"title": "LoRA-Rezepte",
|
||||
"actions": {
|
||||
"sendCheckpoint": "Send to ComfyUI"
|
||||
},
|
||||
"controls": {
|
||||
"import": {
|
||||
"action": "Importieren",
|
||||
@@ -478,10 +624,26 @@
|
||||
"selectLoraRoot": "Bitte wählen Sie ein LoRA-Stammverzeichnis aus"
|
||||
}
|
||||
},
|
||||
"sort": {
|
||||
"title": "Rezepte sortieren nach...",
|
||||
"name": "Name",
|
||||
"nameAsc": "A - Z",
|
||||
"nameDesc": "Z - A",
|
||||
"date": "Datum",
|
||||
"dateDesc": "Neueste",
|
||||
"dateAsc": "Älteste",
|
||||
"lorasCount": "LoRA-Anzahl",
|
||||
"lorasCountDesc": "Meiste",
|
||||
"lorasCountAsc": "Wenigste"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "Rezeptliste aktualisieren"
|
||||
},
|
||||
"filteredByLora": "Gefiltert nach LoRA"
|
||||
"filteredByLora": "Gefiltert nach LoRA",
|
||||
"favorites": {
|
||||
"title": "Nur Favoriten anzeigen",
|
||||
"action": "Favoriten"
|
||||
}
|
||||
},
|
||||
"duplicates": {
|
||||
"found": "{count} Duplikat-Gruppen gefunden",
|
||||
@@ -507,23 +669,44 @@
|
||||
"noMissingLoras": "Keine fehlenden LoRAs zum Herunterladen",
|
||||
"getInfoFailed": "Fehler beim Abrufen der Informationen für fehlende LoRAs",
|
||||
"prepareError": "Fehler beim Vorbereiten der LoRAs für den Download: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "Rezept-Metadaten werden repariert...",
|
||||
"success": "Rezept-Metadaten erfolgreich repariert",
|
||||
"skipped": "Rezept bereits in der neuesten Version, keine Reparatur erforderlich",
|
||||
"failed": "Rezept-Reparatur fehlgeschlagen: {message}",
|
||||
"missingId": "Rezept kann nicht repariert werden: Fehlende Rezept-ID"
|
||||
}
|
||||
}
|
||||
},
|
||||
"checkpoints": {
|
||||
"title": "Checkpoint-Modelle"
|
||||
"title": "Checkpoint-Modelle",
|
||||
"modelTypes": {
|
||||
"checkpoint": "Checkpoint",
|
||||
"diffusion_model": "Diffusion Model"
|
||||
},
|
||||
"contextMenu": {
|
||||
"moveToOtherTypeFolder": "In {otherType}-Ordner verschieben"
|
||||
}
|
||||
},
|
||||
"embeddings": {
|
||||
"title": "Embedding-Modelle"
|
||||
},
|
||||
"sidebar": {
|
||||
"modelRoot": "Modell-Stammverzeichnis",
|
||||
"modelRoot": "Stammverzeichnis",
|
||||
"collapseAll": "Alle Ordner einklappen",
|
||||
"pinSidebar": "Sidebar anheften",
|
||||
"unpinSidebar": "Sidebar lösen",
|
||||
"switchToListView": "Zur Listenansicht wechseln",
|
||||
"switchToTreeView": "Zur Baumansicht wechseln",
|
||||
"collapseAllDisabled": "Im Listenmodus nicht verfügbar"
|
||||
"recursiveOn": "Unterordner durchsuchen",
|
||||
"recursiveOff": "Nur aktuellen Ordner durchsuchen",
|
||||
"recursiveUnavailable": "Rekursive Suche ist nur in der Baumansicht verfügbar",
|
||||
"collapseAllDisabled": "Im Listenmodus nicht verfügbar",
|
||||
"dragDrop": {
|
||||
"unableToResolveRoot": "Zielpfad für das Verschieben konnte nicht ermittelt werden.",
|
||||
"moveUnsupported": "Move is not supported for this item."
|
||||
}
|
||||
},
|
||||
"statistics": {
|
||||
"title": "Statistiken",
|
||||
@@ -598,6 +781,14 @@
|
||||
"downloadedPreview": "Vorschaubild heruntergeladen",
|
||||
"downloadingFile": "{type}-Datei wird heruntergeladen",
|
||||
"finalizing": "Download wird abgeschlossen..."
|
||||
},
|
||||
"progress": {
|
||||
"currentFile": "Aktuelle Datei:",
|
||||
"downloading": "Wird heruntergeladen: {name}",
|
||||
"transferred": "Heruntergeladen: {downloaded} / {total}",
|
||||
"transferredSimple": "Heruntergeladen: {downloaded}",
|
||||
"transferredUnknown": "Heruntergeladen: --",
|
||||
"speed": "Geschwindigkeit: {speed}"
|
||||
}
|
||||
},
|
||||
"move": {
|
||||
@@ -606,6 +797,7 @@
|
||||
"contentRating": {
|
||||
"title": "Inhaltsbewertung festlegen",
|
||||
"current": "Aktuell",
|
||||
"multiple": "Mehrere Werte",
|
||||
"levels": {
|
||||
"pg": "PG",
|
||||
"pg13": "PG13",
|
||||
@@ -644,6 +836,12 @@
|
||||
"countMessage": "Modelle werden dauerhaft gelöscht.",
|
||||
"action": "Alle löschen"
|
||||
},
|
||||
"checkUpdates": {
|
||||
"title": "Alle {typePlural} auf Updates prüfen?",
|
||||
"message": "Damit werden alle {typePlural} in deiner Bibliothek auf Updates geprüft. Bei großen Sammlungen kann das etwas länger dauern.",
|
||||
"tip": "Du möchtest in Etappen prüfen? Wechsle in den Sammelmodus, wähle die benötigten Modelle aus und nutze anschließend \"Auswahl auf Updates prüfen\".",
|
||||
"action": "Alles prüfen"
|
||||
},
|
||||
"bulkAddTags": {
|
||||
"title": "Tags zu mehreren Modellen hinzufügen",
|
||||
"description": "Tags hinzufügen zu",
|
||||
@@ -717,7 +915,9 @@
|
||||
},
|
||||
"openFileLocation": {
|
||||
"success": "Dateispeicherort erfolgreich geöffnet",
|
||||
"failed": "Fehler beim Öffnen des Dateispeicherorts"
|
||||
"failed": "Fehler beim Öffnen des Dateispeicherorts",
|
||||
"copied": "Pfad in die Zwischenablage kopiert: {{path}}",
|
||||
"clipboardFallback": "Pfad: {{path}}"
|
||||
},
|
||||
"metadata": {
|
||||
"version": "Version",
|
||||
@@ -740,11 +940,13 @@
|
||||
"addPresetParameter": "Voreingestellten Parameter hinzufügen...",
|
||||
"strengthMin": "Stärke Min",
|
||||
"strengthMax": "Stärke Max",
|
||||
"strengthRange": "Stärkenbereich",
|
||||
"strength": "Stärke",
|
||||
"clipStrength": "Clip-Stärke",
|
||||
"clipSkip": "Clip Skip",
|
||||
"valuePlaceholder": "Wert",
|
||||
"add": "Hinzufügen"
|
||||
"add": "Hinzufügen",
|
||||
"invalidRange": "Ungültiges Bereichsformat. Verwenden Sie x.x-y.y"
|
||||
},
|
||||
"triggerWords": {
|
||||
"label": "Trigger Words",
|
||||
@@ -780,13 +982,84 @@
|
||||
"tabs": {
|
||||
"examples": "Beispiele",
|
||||
"description": "Modellbeschreibung",
|
||||
"recipes": "Rezepte"
|
||||
"recipes": "Rezepte",
|
||||
"versions": "Versionen"
|
||||
},
|
||||
"navigation": {
|
||||
"label": "Modellnavigation",
|
||||
"previousWithShortcut": "Vorheriges Modell (←)",
|
||||
"nextWithShortcut": "Nächstes Modell (→)",
|
||||
"noPrevious": "Kein vorheriges Modell verfügbar",
|
||||
"noNext": "Kein weiteres Modell verfügbar"
|
||||
},
|
||||
"license": {
|
||||
"noImageSell": "No selling generated content",
|
||||
"noRentCivit": "No Civitai generation",
|
||||
"noRent": "No generation services",
|
||||
"noSell": "No selling models",
|
||||
"creditRequired": "Ersteller-Angabe erforderlich",
|
||||
"noDerivatives": "Keine gemeinsamen Zusammenführungen",
|
||||
"noReLicense": "Gleiche Berechtigungen erforderlich",
|
||||
"restrictionsLabel": "Lizenzbeschränkungen"
|
||||
},
|
||||
"loading": {
|
||||
"exampleImages": "Beispielbilder werden geladen...",
|
||||
"description": "Modellbeschreibung wird geladen...",
|
||||
"recipes": "Rezepte werden geladen...",
|
||||
"examples": "Beispiele werden geladen..."
|
||||
"examples": "Beispiele werden geladen...",
|
||||
"versions": "Versionen werden geladen..."
|
||||
},
|
||||
"versions": {
|
||||
"heading": "Modellversionen",
|
||||
"copy": "Verwalten Sie alle Versionen dieses Modells an einem Ort.",
|
||||
"media": {
|
||||
"placeholder": "Keine Vorschau"
|
||||
},
|
||||
"labels": {
|
||||
"unnamed": "Unbenannte Version",
|
||||
"noDetails": "Keine zusätzlichen Details"
|
||||
},
|
||||
"badges": {
|
||||
"current": "Aktuelle Version",
|
||||
"inLibrary": "In der Bibliothek",
|
||||
"newer": "Neuere Version",
|
||||
"ignored": "Ignoriert"
|
||||
},
|
||||
"actions": {
|
||||
"download": "Herunterladen",
|
||||
"delete": "Löschen",
|
||||
"ignore": "Ignorieren",
|
||||
"unignore": "Ignorierung aufheben",
|
||||
"resumeModelUpdates": "Aktualisierungen für dieses Modell fortsetzen",
|
||||
"ignoreModelUpdates": "Aktualisierungen für dieses Modell ignorieren",
|
||||
"viewLocalVersions": "Alle lokalen Versionen anzeigen",
|
||||
"viewLocalTooltip": "Demnächst verfügbar"
|
||||
},
|
||||
"filters": {
|
||||
"label": "Basisfilter",
|
||||
"state": {
|
||||
"showAll": "Alle Versionen",
|
||||
"showSameBase": "Gleiches Basismodell"
|
||||
},
|
||||
"tooltip": {
|
||||
"showAllVersions": "Wechseln, um alle Versionen anzuzeigen",
|
||||
"showSameBaseVersions": "Wechseln, um nur Versionen mit demselben Basismodell anzuzeigen"
|
||||
},
|
||||
"empty": "Keine Versionen entsprechen dem Filter für das aktuelle Basismodell."
|
||||
},
|
||||
"empty": "Noch keine Versionshistorie für dieses Modell vorhanden.",
|
||||
"error": "Versionen konnten nicht geladen werden.",
|
||||
"missingModelId": "Für dieses Modell ist keine Civitai-Model-ID vorhanden.",
|
||||
"confirm": {
|
||||
"delete": "Diese Version aus Ihrer Bibliothek löschen?"
|
||||
},
|
||||
"toast": {
|
||||
"modelIgnored": "Aktualisierungen für dieses Modell werden ignoriert",
|
||||
"modelResumed": "Aktualisierungen für dieses Modell werden wieder geprüft",
|
||||
"versionIgnored": "Aktualisierungen für diese Version werden ignoriert",
|
||||
"versionUnignored": "Version wurde wieder aktiviert",
|
||||
"versionDeleted": "Version gelöscht"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -893,7 +1166,9 @@
|
||||
"loraFailedToSend": "Fehler beim Senden der LoRA an den Workflow",
|
||||
"recipeAdded": "Rezept zum Workflow hinzugefügt",
|
||||
"recipeReplaced": "Rezept im Workflow ersetzt",
|
||||
"recipeFailedToSend": "Fehler beim Senden des Rezepts an den Workflow"
|
||||
"recipeFailedToSend": "Fehler beim Senden des Rezepts an den Workflow",
|
||||
"noMatchingNodes": "Keine kompatiblen Knoten im aktuellen Workflow verfügbar",
|
||||
"noTargetNodeSelected": "Kein Zielknoten ausgewählt"
|
||||
},
|
||||
"nodeSelector": {
|
||||
"recipe": "Rezept",
|
||||
@@ -906,7 +1181,11 @@
|
||||
"exampleImages": {
|
||||
"opened": "Beispielbilder-Ordner geöffnet",
|
||||
"openingFolder": "Beispielbilder-Ordner wird geöffnet",
|
||||
"failedToOpen": "Fehler beim Öffnen des Beispielbilder-Ordners"
|
||||
"failedToOpen": "Fehler beim Öffnen des Beispielbilder-Ordners",
|
||||
"setupRequired": "Beispielbilder-Speicher",
|
||||
"setupDescription": "Um benutzerdefinierte Beispielbilder hinzuzufügen, müssen Sie zuerst einen Download-Speicherort festlegen.",
|
||||
"setupUsage": "Dieser Pfad wird sowohl für heruntergeladene als auch für benutzerdefinierte Beispielbilder verwendet.",
|
||||
"openSettings": "Einstellungen öffnen"
|
||||
}
|
||||
},
|
||||
"help": {
|
||||
@@ -938,6 +1217,11 @@
|
||||
},
|
||||
"update": {
|
||||
"title": "Nach Updates suchen",
|
||||
"notificationsTitle": "Benachrichtigungszentrum",
|
||||
"tabs": {
|
||||
"updates": "Aktualisierungen",
|
||||
"messages": "Mitteilungen"
|
||||
},
|
||||
"updateAvailable": "Update verfügbar",
|
||||
"noChangelogAvailable": "Kein detailliertes Changelog verfügbar. Weitere Informationen auf GitHub.",
|
||||
"currentVersion": "Aktuelle Version",
|
||||
@@ -950,6 +1234,7 @@
|
||||
"checkingUpdates": "Nach Updates wird gesucht...",
|
||||
"checkingMessage": "Bitte warten Sie, während wir nach der neuesten Version suchen.",
|
||||
"showNotifications": "Update-Benachrichtigungen anzeigen",
|
||||
"latestBadge": "Neueste",
|
||||
"updateProgress": {
|
||||
"preparing": "Update wird vorbereitet...",
|
||||
"installing": "Update wird installiert...",
|
||||
@@ -969,6 +1254,13 @@
|
||||
"nightly": {
|
||||
"warning": "Warnung: Nightly Builds können experimentelle Funktionen enthalten und könnten instabil sein.",
|
||||
"enable": "Nightly Updates aktivieren"
|
||||
},
|
||||
"banners": {
|
||||
"recent": "Neueste Mitteilungen",
|
||||
"empty": "Keine aktuellen Banner verfügbar.",
|
||||
"shown": "{time} angezeigt",
|
||||
"dismissed": "{time} geschlossen",
|
||||
"active": "Aktiv"
|
||||
}
|
||||
},
|
||||
"support": {
|
||||
@@ -1048,6 +1340,9 @@
|
||||
"cannotSend": "Kann Rezept nicht senden: Fehlende Rezept-ID",
|
||||
"sendFailed": "Fehler beim Senden des Rezepts an Workflow",
|
||||
"sendError": "Fehler beim Senden des Rezepts an Workflow",
|
||||
"missingCheckpointPath": "Checkpoint-Pfad nicht verfügbar",
|
||||
"missingCheckpointInfo": "Checkpoint-Informationen fehlen",
|
||||
"downloadCheckpointFailed": "Checkpoint-Download fehlgeschlagen: {message}",
|
||||
"cannotDelete": "Kann Rezept nicht löschen: Fehlende Rezept-ID",
|
||||
"deleteConfirmationError": "Fehler beim Anzeigen der Löschbestätigung",
|
||||
"deletedSuccessfully": "Rezept erfolgreich gelöscht",
|
||||
@@ -1084,6 +1379,16 @@
|
||||
"bulkBaseModelUpdateSuccess": "Basis-Modell erfolgreich für {count} Modell(e) aktualisiert",
|
||||
"bulkBaseModelUpdatePartial": "{success} Modelle aktualisiert, {failed} fehlgeschlagen",
|
||||
"bulkBaseModelUpdateFailed": "Aktualisierung des Basis-Modells für ausgewählte Modelle fehlgeschlagen",
|
||||
"bulkContentRatingUpdating": "Inhaltsbewertung wird für {count} Modell(e) aktualisiert...",
|
||||
"bulkContentRatingSet": "Inhaltsbewertung auf {level} für {count} Modell(e) gesetzt",
|
||||
"bulkContentRatingPartial": "Inhaltsbewertung auf {level} für {success} Modell(e) gesetzt, {failed} fehlgeschlagen",
|
||||
"bulkContentRatingFailed": "Inhaltsbewertung für ausgewählte Modelle konnte nicht aktualisiert werden",
|
||||
"bulkUpdatesChecking": "Ausgewählte {type}-Modelle werden auf Updates geprüft...",
|
||||
"bulkUpdatesSuccess": "Updates für {count} ausgewählte {type}-Modelle verfügbar",
|
||||
"bulkUpdatesNone": "Keine Updates für ausgewählte {type}-Modelle gefunden",
|
||||
"bulkUpdatesMissing": "Ausgewählte {type}-Modelle sind nicht mit Civitai-Updates verknüpft",
|
||||
"bulkUpdatesPartialMissing": "{missing} ausgewählte {type}-Modelle ohne Civitai-Verknüpfung übersprungen",
|
||||
"bulkUpdatesFailed": "Updates für ausgewählte {type}-Modelle konnten nicht geprüft werden: {message}",
|
||||
"invalidCharactersRemoved": "Ungültige Zeichen aus Dateiname entfernt",
|
||||
"filenameCannotBeEmpty": "Dateiname darf nicht leer sein",
|
||||
"renameFailed": "Fehler beim Umbenennen der Datei: {message}",
|
||||
@@ -1095,6 +1400,7 @@
|
||||
"verificationCompleteSuccess": "Verifikation abgeschlossen. Alle Dateien sind bestätigte Duplikate.",
|
||||
"verificationFailed": "Fehler beim Verifizieren der Hashes: {message}",
|
||||
"noTagsToAdd": "Keine Tags zum Hinzufügen",
|
||||
"bulkTagsUpdating": "Tags für {count} Modell(e) werden aktualisiert...",
|
||||
"tagsAddedSuccessfully": "Erfolgreich {tagCount} Tag(s) zu {count} {type}(s) hinzugefügt",
|
||||
"tagsReplacedSuccessfully": "Tags für {count} {type}(s) erfolgreich durch {tagCount} Tag(s) ersetzt",
|
||||
"tagsAddFailed": "Fehler beim Hinzufügen von Tags zu {count} Modell(en)",
|
||||
@@ -1108,6 +1414,7 @@
|
||||
"settings": {
|
||||
"loraRootsFailed": "Fehler beim Laden der LoRA-Stammverzeichnisse: {message}",
|
||||
"checkpointRootsFailed": "Fehler beim Laden der Checkpoint-Stammverzeichnisse: {message}",
|
||||
"unetRootsFailed": "Fehler beim Laden der Diffusion-Modell-Stammverzeichnisse: {message}",
|
||||
"embeddingRootsFailed": "Fehler beim Laden der Embedding-Stammverzeichnisse: {message}",
|
||||
"mappingsUpdated": "Basis-Modell-Pfad-Zuordnungen aktualisiert ({count} Zuordnung{plural})",
|
||||
"mappingsCleared": "Basis-Modell-Pfad-Zuordnungen gelöscht",
|
||||
@@ -1118,6 +1425,8 @@
|
||||
"compactModeToggled": "Kompakt-Modus {state}",
|
||||
"settingSaveFailed": "Fehler beim Speichern der Einstellung: {message}",
|
||||
"displayDensitySet": "Anzeige-Dichte auf {density} gesetzt",
|
||||
"libraryLoadFailed": "Failed to load libraries: {message}",
|
||||
"libraryActivateFailed": "Failed to activate library: {message}",
|
||||
"languageChangeFailed": "Fehler beim Ändern der Sprache: {message}",
|
||||
"cacheCleared": "Cache-Dateien wurden erfolgreich gelöscht. Cache wird bei der nächsten Aktion neu aufgebaut.",
|
||||
"cacheClearFailed": "Fehler beim Löschen des Caches: {error}",
|
||||
@@ -1126,7 +1435,26 @@
|
||||
"filters": {
|
||||
"applied": "{message}",
|
||||
"cleared": "Filter gelöscht",
|
||||
"noCustomFilterToClear": "Kein benutzerdefinierter Filter zum Löschen"
|
||||
"noCustomFilterToClear": "Kein benutzerdefinierter Filter zum Löschen",
|
||||
"noActiveFilters": "Keine aktiven Filter zum Speichern"
|
||||
},
|
||||
"presets": {
|
||||
"created": "Voreinstellung \"{name}\" erstellt",
|
||||
"deleted": "Voreinstellung \"{name}\" gelöscht",
|
||||
"applied": "Voreinstellung \"{name}\" angewendet",
|
||||
"overwritten": "Voreinstellung \"{name}\" überschrieben",
|
||||
"restored": "Standard-Voreinstellungen wiederhergestellt"
|
||||
},
|
||||
"error": {
|
||||
"presetNameEmpty": "Voreinstellungsname darf nicht leer sein",
|
||||
"presetNameTooLong": "Voreinstellungsname darf maximal {max} Zeichen haben",
|
||||
"presetNameInvalidChars": "Voreinstellungsname enthält ungültige Zeichen",
|
||||
"presetNameExists": "Eine Voreinstellung mit diesem Namen existiert bereits",
|
||||
"maxPresetsReached": "Maximal {max} Voreinstellungen erlaubt. Löschen Sie eine, um weitere hinzuzufügen.",
|
||||
"presetNotFound": "Voreinstellung nicht gefunden",
|
||||
"invalidPreset": "Ungültige Voreinstellungsdaten",
|
||||
"deletePresetFailed": "Fehler beim Löschen der Voreinstellung",
|
||||
"applyPresetFailed": "Fehler beim Anwenden der Voreinstellung"
|
||||
},
|
||||
"downloads": {
|
||||
"imagesCompleted": "Beispielbilder {action} abgeschlossen",
|
||||
@@ -1142,7 +1470,7 @@
|
||||
},
|
||||
"triggerWords": {
|
||||
"loadFailed": "Konnte trainierte Wörter nicht laden",
|
||||
"tooLong": "Trigger Word sollte 30 Wörter nicht überschreiten",
|
||||
"tooLong": "Trigger Word sollte 100 Wörter nicht überschreiten",
|
||||
"tooMany": "Maximal 30 Trigger Words erlaubt",
|
||||
"alreadyExists": "Dieses Trigger Word existiert bereits",
|
||||
"updateSuccess": "Trigger Words erfolgreich aktualisiert",
|
||||
@@ -1191,6 +1519,8 @@
|
||||
"pauseFailed": "Fehler beim Pausieren des Downloads: {error}",
|
||||
"downloadResumed": "Download fortgesetzt",
|
||||
"resumeFailed": "Fehler beim Fortsetzen des Downloads: {error}",
|
||||
"downloadStopped": "Download abgebrochen",
|
||||
"stopFailed": "Download konnte nicht abgebrochen werden: {error}",
|
||||
"deleted": "Beispielbild gelöscht",
|
||||
"deleteFailed": "Fehler beim Löschen des Beispielbilds",
|
||||
"setPreviewFailed": "Fehler beim Setzen des Vorschaubilds"
|
||||
@@ -1211,6 +1541,8 @@
|
||||
"metadataRefreshed": "Metadaten erfolgreich aktualisiert",
|
||||
"metadataRefreshFailed": "Fehler beim Aktualisieren der Metadaten: {message}",
|
||||
"metadataUpdateComplete": "Metadaten-Update abgeschlossen",
|
||||
"operationCancelled": "Vorgang vom Benutzer abgebrochen",
|
||||
"operationCancelledPartial": "Vorgang abgebrochen. {success} Elemente verarbeitet.",
|
||||
"metadataFetchFailed": "Fehler beim Abrufen der Metadaten: {message}",
|
||||
"bulkMetadataCompleteAll": "Alle {count} {type}s erfolgreich aktualisiert",
|
||||
"bulkMetadataCompletePartial": "{success} von {total} {type}s aktualisiert",
|
||||
@@ -1227,7 +1559,8 @@
|
||||
"bulkMoveFailures": "Fehlgeschlagene Verschiebungen:\n{failures}",
|
||||
"bulkMoveSuccess": "{successCount} {type}s erfolgreich verschoben",
|
||||
"exampleImagesDownloadSuccess": "Beispielbilder erfolgreich heruntergeladen!",
|
||||
"exampleImagesDownloadFailed": "Fehler beim Herunterladen der Beispielbilder: {message}"
|
||||
"exampleImagesDownloadFailed": "Fehler beim Herunterladen der Beispielbilder: {message}",
|
||||
"moveFailed": "Failed to move item: {message}"
|
||||
}
|
||||
},
|
||||
"banners": {
|
||||
@@ -1237,6 +1570,26 @@
|
||||
"refreshNow": "Jetzt aktualisieren",
|
||||
"refreshingIn": "Aktualisierung in",
|
||||
"seconds": "Sekunden"
|
||||
},
|
||||
"communitySupport": {
|
||||
"title": "Keep LoRA Manager Thriving with Your Support ❤️",
|
||||
"content": "LoRA Manager is a passion project maintained full-time by a solo developer. Your support on Ko-fi helps cover development costs, keeps new updates coming, and unlocks a license key for the LM Civitai Extension as a thank-you gift. Every contribution truly makes a difference.",
|
||||
"supportCta": "Support on Ko-fi",
|
||||
"learnMore": "LM Civitai Extension Tutorial"
|
||||
},
|
||||
"cacheHealth": {
|
||||
"corrupted": {
|
||||
"title": "Cache-Korruption erkannt"
|
||||
},
|
||||
"degraded": {
|
||||
"title": "Cache-Probleme erkannt"
|
||||
},
|
||||
"content": "{invalid} von {total} Cache-Einträgen sind ungültig ({rate}). Dies kann zu fehlenden Modellen oder Fehlern führen. Ein Neuaufbau des Caches wird empfohlen.",
|
||||
"rebuildCache": "Cache neu aufbauen",
|
||||
"dismiss": "Verwerfen",
|
||||
"rebuilding": "Cache wird neu aufgebaut...",
|
||||
"rebuildFailed": "Fehler beim Neuaufbau des Caches: {error}",
|
||||
"retry": "Wiederholen"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
489
locales/en.json
489
locales/en.json
@@ -10,7 +10,8 @@
|
||||
"next": "Next",
|
||||
"backToTop": "Back to top",
|
||||
"settings": "Settings",
|
||||
"help": "Help"
|
||||
"help": "Help",
|
||||
"add": "Add"
|
||||
},
|
||||
"status": {
|
||||
"loading": "Loading...",
|
||||
@@ -31,7 +32,8 @@
|
||||
"japanese": "日本語",
|
||||
"korean": "한국어",
|
||||
"french": "Français",
|
||||
"spanish": "Español"
|
||||
"spanish": "Español",
|
||||
"Hebrew": "עברית"
|
||||
},
|
||||
"fileSize": {
|
||||
"zero": "0 Bytes",
|
||||
@@ -100,7 +102,12 @@
|
||||
"checkpointNameCopied": "Checkpoint name copied",
|
||||
"toggleBlur": "Toggle blur",
|
||||
"show": "Show",
|
||||
"openExampleImages": "Open Example Images Folder"
|
||||
"openExampleImages": "Open Example Images Folder",
|
||||
"replacePreview": "Replace Preview",
|
||||
"copyCheckpointName": "Copy checkpoint name",
|
||||
"copyEmbeddingName": "Copy embedding name",
|
||||
"sendCheckpointToWorkflow": "Send to ComfyUI",
|
||||
"sendEmbeddingToWorkflow": "Send to ComfyUI"
|
||||
},
|
||||
"nsfw": {
|
||||
"matureContent": "Mature Content",
|
||||
@@ -114,12 +121,20 @@
|
||||
"updateFailed": "Failed to update favorite status"
|
||||
},
|
||||
"sendToWorkflow": {
|
||||
"checkpointNotImplemented": "Send checkpoint to workflow - feature to be implemented"
|
||||
"checkpointNotImplemented": "Send checkpoint to workflow - feature to be implemented",
|
||||
"missingPath": "Unable to determine model path for this card"
|
||||
},
|
||||
"exampleImages": {
|
||||
"checkError": "Error checking for example images",
|
||||
"missingHash": "Missing model hash information.",
|
||||
"noRemoteImagesAvailable": "No remote example images available for this model on Civitai"
|
||||
},
|
||||
"badges": {
|
||||
"update": "Update",
|
||||
"updateAvailable": "Update available"
|
||||
},
|
||||
"usage": {
|
||||
"timesUsed": "Times used"
|
||||
}
|
||||
},
|
||||
"globalContextMenu": {
|
||||
@@ -128,12 +143,33 @@
|
||||
"missingPath": "Set a download location before downloading example images.",
|
||||
"unavailable": "Example image downloads aren't available yet. Try again after the page finishes loading."
|
||||
},
|
||||
"checkModelUpdates": {
|
||||
"label": "Check for updates",
|
||||
"loading": "Checking for {type} updates...",
|
||||
"success": "Found {count} update(s) for {type}s",
|
||||
"none": "All {type}s are up to date",
|
||||
"error": "Failed to check for {type} updates: {message}"
|
||||
},
|
||||
"cleanupExampleImages": {
|
||||
"label": "Clean up example image folders",
|
||||
"success": "Moved {count} folder(s) to the deleted folder",
|
||||
"none": "No example image folders needed cleanup",
|
||||
"partial": "Cleanup completed with {failures} folder(s) skipped",
|
||||
"error": "Failed to clean example image folders: {message}"
|
||||
},
|
||||
"fetchMissingLicenses": {
|
||||
"label": "Refresh license metadata",
|
||||
"loading": "Refreshing license metadata for {typePlural}...",
|
||||
"success": "Updated license metadata for {count} {typePlural}",
|
||||
"none": "All {typePlural} already have license metadata",
|
||||
"error": "Failed to refresh license metadata for {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Repair recipes data",
|
||||
"loading": "Repairing recipe data...",
|
||||
"success": "Successfully repaired {count} recipes.",
|
||||
"cancelled": "Repair cancelled. {count} recipes were repaired.",
|
||||
"error": "Recipe repair failed: {message}"
|
||||
}
|
||||
},
|
||||
"header": {
|
||||
@@ -163,14 +199,35 @@
|
||||
"creator": "Creator",
|
||||
"title": "Recipe Title",
|
||||
"loraName": "LoRA Filename",
|
||||
"loraModel": "LoRA Model Name"
|
||||
"loraModel": "LoRA Model Name",
|
||||
"prompt": "Prompt"
|
||||
}
|
||||
},
|
||||
"filter": {
|
||||
"title": "Filter Models",
|
||||
"presets": "Presets",
|
||||
"savePreset": "Save current active filters as a new preset.",
|
||||
"savePresetDisabledActive": "Cannot save: A preset is already active. Modify filters to save new preset.",
|
||||
"savePresetDisabledNoFilters": "Select filters first to save as preset",
|
||||
"savePresetPrompt": "Enter preset name:",
|
||||
"presetClickTooltip": "Click to apply preset \"{name}\"",
|
||||
"presetDeleteTooltip": "Delete preset",
|
||||
"presetDeleteConfirm": "Delete preset \"{name}\"?",
|
||||
"presetDeleteConfirmClick": "Click again to confirm",
|
||||
"presetOverwriteConfirm": "Preset \"{name}\" already exists. Overwrite?",
|
||||
"presetNamePlaceholder": "Preset name...",
|
||||
"baseModel": "Base Model",
|
||||
"modelTags": "Tags (Top 20)",
|
||||
"clearAll": "Clear All Filters"
|
||||
"modelTypes": "Model Types",
|
||||
"license": "License",
|
||||
"noCreditRequired": "No Credit Required",
|
||||
"allowSellingGeneratedContent": "Allow Selling",
|
||||
"noTags": "No tags",
|
||||
"clearAll": "Clear All Filters",
|
||||
"any": "Any",
|
||||
"all": "All",
|
||||
"tagLogicAny": "Match any tag (OR)",
|
||||
"tagLogicAll": "Match all tags (AND)"
|
||||
},
|
||||
"theme": {
|
||||
"toggle": "Toggle theme",
|
||||
@@ -180,6 +237,7 @@
|
||||
},
|
||||
"actions": {
|
||||
"checkUpdates": "Check Updates",
|
||||
"notifications": "Notifications",
|
||||
"support": "Support"
|
||||
}
|
||||
},
|
||||
@@ -187,17 +245,33 @@
|
||||
"civitaiApiKey": "Civitai API Key",
|
||||
"civitaiApiKeyPlaceholder": "Enter your Civitai API key",
|
||||
"civitaiApiKeyHelp": "Used for authentication when downloading models from Civitai",
|
||||
"openSettingsFileLocation": {
|
||||
"label": "Open settings folder",
|
||||
"tooltip": "Open folder containing settings.json",
|
||||
"success": "Opened settings.json folder",
|
||||
"failed": "Failed to open settings.json folder",
|
||||
"copied": "Settings path copied to clipboard: {{path}}",
|
||||
"clipboardFallback": "Settings path: {{path}}"
|
||||
},
|
||||
"sections": {
|
||||
"contentFiltering": "Content Filtering",
|
||||
"videoSettings": "Video Settings",
|
||||
"layoutSettings": "Layout Settings",
|
||||
"folderSettings": "Folder Settings",
|
||||
"priorityTags": "Priority Tags",
|
||||
"downloadPathTemplates": "Download Path Templates",
|
||||
"exampleImages": "Example Images",
|
||||
"updateFlags": "Update Flags",
|
||||
"autoOrganize": "Auto-organize",
|
||||
"misc": "Misc.",
|
||||
"metadataArchive": "Metadata Archive Database",
|
||||
"storageLocation": "Settings Location",
|
||||
"proxySettings": "Proxy Settings"
|
||||
},
|
||||
"storage": {
|
||||
"locationLabel": "Portable mode",
|
||||
"locationHelp": "Enable to keep settings.json inside the repository; disable to store it in your user config directory."
|
||||
},
|
||||
"contentFiltering": {
|
||||
"blurNsfwContent": "Blur NSFW Content",
|
||||
"blurNsfwContentHelp": "Blur mature (NSFW) content preview images",
|
||||
@@ -208,40 +282,85 @@
|
||||
"autoplayOnHover": "Autoplay Videos on Hover",
|
||||
"autoplayOnHoverHelp": "Only play video previews when hovering over them"
|
||||
},
|
||||
"autoOrganizeExclusions": {
|
||||
"label": "Auto-organize exclusions",
|
||||
"placeholder": "Example: curated/*, */backups/*; *_temp.safetensors",
|
||||
"help": "Skip moving files that match these wildcard patterns. Separate multiple patterns with commas or semicolons.",
|
||||
"validation": {
|
||||
"noPatterns": "Enter at least one pattern separated by commas or semicolons.",
|
||||
"saveFailed": "Unable to save exclusions: {message}"
|
||||
}
|
||||
},
|
||||
"layoutSettings": {
|
||||
"displayDensity": "Display Density",
|
||||
"displayDensityOptions": {
|
||||
"default": "Default",
|
||||
"medium": "Medium",
|
||||
"medium": "Medium",
|
||||
"compact": "Compact"
|
||||
},
|
||||
"displayDensityHelp": "Choose how many cards to display per row:",
|
||||
"displayDensityDetails": {
|
||||
"default": "Default: 5 (1080p), 6 (2K), 8 (4K)",
|
||||
"medium": "Medium: 6 (1080p), 7 (2K), 9 (4K)",
|
||||
"compact": "Compact: 7 (1080p), 8 (2K), 10 (4K)"
|
||||
"default": "5 (1080p), 6 (2K), 8 (4K)",
|
||||
"medium": "6 (1080p), 7 (2K), 9 (4K)",
|
||||
"compact": "7 (1080p), 8 (2K), 10 (4K)"
|
||||
},
|
||||
"displayDensityWarning": "Warning: Higher densities may cause performance issues on systems with limited resources.",
|
||||
"showFolderSidebar": "Show Folder Sidebar",
|
||||
"showFolderSidebarHelp": "Toggle the folder navigation sidebar on model pages. When disabled, the sidebar and hover area stay hidden.",
|
||||
"cardInfoDisplay": "Card Info Display",
|
||||
"cardInfoDisplayOptions": {
|
||||
"always": "Always Visible",
|
||||
"hover": "Reveal on Hover"
|
||||
},
|
||||
"cardInfoDisplayHelp": "Choose when to display model information and action buttons:",
|
||||
"cardInfoDisplayDetails": {
|
||||
"always": "Always Visible: Headers and footers are always visible",
|
||||
"hover": "Reveal on Hover: Headers and footers only appear when hovering over a card"
|
||||
}
|
||||
"cardInfoDisplayHelp": "Choose when to display model information and action buttons",
|
||||
"modelCardFooterAction": "Model Card Button Action",
|
||||
"modelCardFooterActionOptions": {
|
||||
"exampleImages": "Open Example Images",
|
||||
"replacePreview": "Replace Preview"
|
||||
},
|
||||
"modelCardFooterActionHelp": "Choose what the bottom-right card button does",
|
||||
"modelNameDisplay": "Model Name Display",
|
||||
"modelNameDisplayOptions": {
|
||||
"modelName": "Model Name",
|
||||
"fileName": "File Name"
|
||||
},
|
||||
"modelNameDisplayHelp": "Choose what to display in the model card footer"
|
||||
},
|
||||
"folderSettings": {
|
||||
"activeLibrary": "Active Library",
|
||||
"activeLibraryHelp": "Switch between configured libraries to update default folders. Changing the selection reloads the page.",
|
||||
"loadingLibraries": "Loading libraries...",
|
||||
"noLibraries": "No libraries configured",
|
||||
"defaultLoraRoot": "Default LoRA Root",
|
||||
"defaultLoraRootHelp": "Set the default LoRA root directory for downloads, imports and moves",
|
||||
"defaultLoraRootHelp": "Set default LoRA root directory for downloads, imports and moves",
|
||||
"defaultCheckpointRoot": "Default Checkpoint Root",
|
||||
"defaultCheckpointRootHelp": "Set the default checkpoint root directory for downloads, imports and moves",
|
||||
"defaultCheckpointRootHelp": "Set default checkpoint root directory for downloads, imports and moves",
|
||||
"defaultUnetRoot": "Default Diffusion Model Root",
|
||||
"defaultUnetRootHelp": "Set default diffusion model (UNET) root directory for downloads, imports and moves",
|
||||
"defaultEmbeddingRoot": "Default Embedding Root",
|
||||
"defaultEmbeddingRootHelp": "Set the default embedding root directory for downloads, imports and moves",
|
||||
"defaultEmbeddingRootHelp": "Set default embedding root directory for downloads, imports and moves",
|
||||
"noDefault": "No Default"
|
||||
},
|
||||
"priorityTags": {
|
||||
"title": "Priority Tags",
|
||||
"description": "Customize the tag priority order for each model type (e.g., character, concept, style(toon|toon_style))",
|
||||
"placeholder": "character, concept, style(toon|toon_style)",
|
||||
"helpLinkLabel": "Open priority tags help",
|
||||
"modelTypes": {
|
||||
"lora": "LoRA",
|
||||
"checkpoint": "Checkpoint",
|
||||
"embedding": "Embedding"
|
||||
},
|
||||
"saveSuccess": "Priority tags updated.",
|
||||
"saveError": "Failed to update priority tags.",
|
||||
"loadingSuggestions": "Loading suggestions...",
|
||||
"validation": {
|
||||
"missingClosingParen": "Entry {index} is missing a closing parenthesis.",
|
||||
"missingCanonical": "Entry {index} must include a canonical tag name.",
|
||||
"duplicateCanonical": "The canonical tag \"{tag}\" appears more than once.",
|
||||
"unknown": "Invalid priority tag configuration."
|
||||
}
|
||||
},
|
||||
"downloadPathTemplates": {
|
||||
"title": "Download Path Templates",
|
||||
"help": "Configure folder structures for different model types when downloading from Civitai.",
|
||||
@@ -249,7 +368,7 @@
|
||||
"templateOptions": {
|
||||
"flatStructure": "Flat Structure",
|
||||
"byBaseModel": "By Base Model",
|
||||
"byAuthor": "By Author",
|
||||
"byAuthor": "By Author",
|
||||
"byFirstTag": "By First Tag",
|
||||
"baseModelFirstTag": "Base Model + First Tag",
|
||||
"baseModelAuthor": "Base Model + Author",
|
||||
@@ -260,7 +379,7 @@
|
||||
"customTemplatePlaceholder": "Enter custom template (e.g., {base_model}/{author}/{first_tag})",
|
||||
"modelTypes": {
|
||||
"lora": "LoRA",
|
||||
"checkpoint": "Checkpoint",
|
||||
"checkpoint": "Checkpoint",
|
||||
"embedding": "Embedding"
|
||||
},
|
||||
"baseModelPathMappings": "Base Model Path Mappings",
|
||||
@@ -289,6 +408,14 @@
|
||||
"download": "Download",
|
||||
"restartRequired": "Requires restart"
|
||||
},
|
||||
"updateFlagStrategy": {
|
||||
"label": "Update Flag Strategy",
|
||||
"help": "Decide whether update badges should only appear when a new release shares the same base model as your local files or whenever any newer version exists for that model.",
|
||||
"options": {
|
||||
"sameBase": "Match updates by base model",
|
||||
"any": "Flag any available update"
|
||||
}
|
||||
},
|
||||
"misc": {
|
||||
"includeTriggerWords": "Include Trigger Words in LoRA Syntax",
|
||||
"includeTriggerWordsHelp": "Include trained trigger words when copying LoRA syntax to clipboard"
|
||||
@@ -325,11 +452,11 @@
|
||||
"proxyHost": "Proxy Host",
|
||||
"proxyHostPlaceholder": "proxy.example.com",
|
||||
"proxyHostHelp": "The hostname or IP address of your proxy server",
|
||||
"proxyPort": "Proxy Port",
|
||||
"proxyPort": "Proxy Port",
|
||||
"proxyPortPlaceholder": "8080",
|
||||
"proxyPortHelp": "The port number of your proxy server",
|
||||
"proxyUsername": "Username (Optional)",
|
||||
"proxyUsernamePlaceholder": "username",
|
||||
"proxyUsernamePlaceholder": "username",
|
||||
"proxyUsernameHelp": "Username for proxy authentication (if required)",
|
||||
"proxyPassword": "Password (Optional)",
|
||||
"proxyPasswordPlaceholder": "password",
|
||||
@@ -348,12 +475,17 @@
|
||||
"dateAsc": "Oldest",
|
||||
"size": "File Size",
|
||||
"sizeDesc": "Largest",
|
||||
"sizeAsc": "Smallest"
|
||||
"sizeAsc": "Smallest",
|
||||
"usage": "Use Count",
|
||||
"usageDesc": "Most",
|
||||
"usageAsc": "Least"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "Refresh model list",
|
||||
"quick": "Quick Refresh (incremental)",
|
||||
"full": "Full Rebuild (complete)"
|
||||
"quick": "Sync Changes",
|
||||
"quickTooltip": "Scan for new or missing model files so the list stays current.",
|
||||
"full": "Rebuild Cache",
|
||||
"fullTooltip": "Reload all model details from metadata files—use if the library looks out of date or after manual edits."
|
||||
},
|
||||
"fetch": {
|
||||
"title": "Fetch metadata from Civitai",
|
||||
@@ -374,19 +506,28 @@
|
||||
"favorites": {
|
||||
"title": "Show Favorites Only",
|
||||
"action": "Favorites"
|
||||
},
|
||||
"updates": {
|
||||
"title": "Show models with updates available",
|
||||
"action": "Updates",
|
||||
"menuLabel": "Show update options",
|
||||
"check": "Check updates",
|
||||
"checkTooltip": "Checking updates may take a while."
|
||||
}
|
||||
},
|
||||
"bulkOperations": {
|
||||
"selected": "{count} selected",
|
||||
"selectedSuffix": "selected",
|
||||
"viewSelected": "View Selected",
|
||||
"addTags": "Add Tags to All",
|
||||
"setBaseModel": "Set Base Model for All",
|
||||
"copyAll": "Copy All Syntax",
|
||||
"refreshAll": "Refresh All Metadata",
|
||||
"moveAll": "Move All to Folder",
|
||||
"addTags": "Add Tags to Selected",
|
||||
"setBaseModel": "Set Base Model for Selected",
|
||||
"setContentRating": "Set Content Rating for Selected",
|
||||
"copyAll": "Copy Selected Syntax",
|
||||
"refreshAll": "Refresh Selected Metadata",
|
||||
"checkUpdates": "Check Updates for Selected",
|
||||
"moveAll": "Move Selected to Folder",
|
||||
"autoOrganize": "Auto-Organize Selected",
|
||||
"deleteAll": "Delete All Models",
|
||||
"deleteAll": "Delete Selected Models",
|
||||
"clear": "Clear Selection",
|
||||
"autoOrganizeProgress": {
|
||||
"initializing": "Initializing auto-organize...",
|
||||
@@ -400,6 +541,7 @@
|
||||
},
|
||||
"contextMenu": {
|
||||
"refreshMetadata": "Refresh Civitai Data",
|
||||
"checkUpdates": "Check Updates",
|
||||
"relinkCivitai": "Re-link to Civitai",
|
||||
"copySyntax": "Copy LoRA Syntax",
|
||||
"copyFilename": "Copy Model Filename",
|
||||
@@ -411,6 +553,7 @@
|
||||
"replacePreview": "Replace Preview",
|
||||
"setContentRating": "Set Content Rating",
|
||||
"moveToFolder": "Move to Folder",
|
||||
"repairMetadata": "Repair metadata",
|
||||
"excludeModel": "Exclude Model",
|
||||
"deleteModel": "Delete Model",
|
||||
"shareRecipe": "Share Recipe",
|
||||
@@ -421,6 +564,9 @@
|
||||
},
|
||||
"recipes": {
|
||||
"title": "LoRA Recipes",
|
||||
"actions": {
|
||||
"sendCheckpoint": "Send to ComfyUI"
|
||||
},
|
||||
"controls": {
|
||||
"import": {
|
||||
"action": "Import",
|
||||
@@ -478,10 +624,26 @@
|
||||
"selectLoraRoot": "Please select a LoRA root directory"
|
||||
}
|
||||
},
|
||||
"sort": {
|
||||
"title": "Sort recipes by...",
|
||||
"name": "Name",
|
||||
"nameAsc": "A - Z",
|
||||
"nameDesc": "Z - A",
|
||||
"date": "Date",
|
||||
"dateDesc": "Newest",
|
||||
"dateAsc": "Oldest",
|
||||
"lorasCount": "LoRA Count",
|
||||
"lorasCountDesc": "Most",
|
||||
"lorasCountAsc": "Least"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "Refresh recipe list"
|
||||
},
|
||||
"filteredByLora": "Filtered by LoRA"
|
||||
"filteredByLora": "Filtered by LoRA",
|
||||
"favorites": {
|
||||
"title": "Show Favorites Only",
|
||||
"action": "Favorites"
|
||||
}
|
||||
},
|
||||
"duplicates": {
|
||||
"found": "Found {count} duplicate groups",
|
||||
@@ -507,23 +669,44 @@
|
||||
"noMissingLoras": "No missing LoRAs to download",
|
||||
"getInfoFailed": "Failed to get information for missing LoRAs",
|
||||
"prepareError": "Error preparing LoRAs for download: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "Repairing recipe metadata...",
|
||||
"success": "Recipe metadata repaired successfully",
|
||||
"skipped": "Recipe already at latest version, no repair needed",
|
||||
"failed": "Failed to repair recipe: {message}",
|
||||
"missingId": "Cannot repair recipe: Missing recipe ID"
|
||||
}
|
||||
}
|
||||
},
|
||||
"checkpoints": {
|
||||
"title": "Checkpoint Models"
|
||||
"title": "Checkpoint Models",
|
||||
"modelTypes": {
|
||||
"checkpoint": "Checkpoint",
|
||||
"diffusion_model": "Diffusion Model"
|
||||
},
|
||||
"contextMenu": {
|
||||
"moveToOtherTypeFolder": "Move to {otherType} Folder"
|
||||
}
|
||||
},
|
||||
"embeddings": {
|
||||
"title": "Embedding Models"
|
||||
},
|
||||
"sidebar": {
|
||||
"modelRoot": "Model Root",
|
||||
"modelRoot": "Root",
|
||||
"collapseAll": "Collapse All Folders",
|
||||
"pinSidebar": "Pin Sidebar",
|
||||
"unpinSidebar": "Unpin Sidebar",
|
||||
"switchToListView": "Switch to List View",
|
||||
"switchToTreeView": "Switch to Tree View",
|
||||
"collapseAllDisabled": "Not available in list view"
|
||||
"recursiveOn": "Search subfolders",
|
||||
"recursiveOff": "Search current folder only",
|
||||
"recursiveUnavailable": "Recursive search is available in tree view only",
|
||||
"collapseAllDisabled": "Not available in list view",
|
||||
"dragDrop": {
|
||||
"unableToResolveRoot": "Unable to determine destination path for move.",
|
||||
"moveUnsupported": "Move is not supported for this item."
|
||||
}
|
||||
},
|
||||
"statistics": {
|
||||
"title": "Statistics",
|
||||
@@ -598,6 +781,14 @@
|
||||
"downloadedPreview": "Downloaded preview image",
|
||||
"downloadingFile": "Downloading {type} file",
|
||||
"finalizing": "Finalizing download..."
|
||||
},
|
||||
"progress": {
|
||||
"currentFile": "Current file:",
|
||||
"downloading": "Downloading: {name}",
|
||||
"transferred": "Transferred: {downloaded} / {total}",
|
||||
"transferredSimple": "Transferred: {downloaded}",
|
||||
"transferredUnknown": "Transferred: --",
|
||||
"speed": "Speed: {speed}"
|
||||
}
|
||||
},
|
||||
"move": {
|
||||
@@ -606,6 +797,7 @@
|
||||
"contentRating": {
|
||||
"title": "Set Content Rating",
|
||||
"current": "Current",
|
||||
"multiple": "Multiple values",
|
||||
"levels": {
|
||||
"pg": "PG",
|
||||
"pg13": "PG13",
|
||||
@@ -644,6 +836,12 @@
|
||||
"countMessage": "models will be permanently deleted.",
|
||||
"action": "Delete All"
|
||||
},
|
||||
"checkUpdates": {
|
||||
"title": "Check updates for all {typePlural}?",
|
||||
"message": "This checks every {typePlural} in your library for updates. Large collections may take a little longer.",
|
||||
"tip": "To work in smaller batches, switch to bulk mode, choose the ones you need, then use \"Check Updates for Selected\".",
|
||||
"action": "Check All"
|
||||
},
|
||||
"bulkAddTags": {
|
||||
"title": "Add Tags to Multiple Models",
|
||||
"description": "Add tags to",
|
||||
@@ -713,11 +911,18 @@
|
||||
"viewOnCivitai": "View on Civitai",
|
||||
"viewOnCivitaiText": "View on Civitai",
|
||||
"viewCreatorProfile": "View Creator Profile",
|
||||
"openFileLocation": "Open File Location"
|
||||
"openFileLocation": "Open File Location",
|
||||
"viewParams": "View parameters",
|
||||
"setPreview": "Set as preview",
|
||||
"previewSet": "Preview updated successfully",
|
||||
"previewFailed": "Failed to update preview",
|
||||
"delete": "Delete"
|
||||
},
|
||||
"openFileLocation": {
|
||||
"success": "File location opened successfully",
|
||||
"failed": "Failed to open file location"
|
||||
"failed": "Failed to open file location",
|
||||
"copied": "Path copied to clipboard: {{path}}",
|
||||
"clipboardFallback": "Path: {{path}}"
|
||||
},
|
||||
"metadata": {
|
||||
"version": "Version",
|
||||
@@ -730,30 +935,41 @@
|
||||
"additionalNotes": "Additional Notes",
|
||||
"notesHint": "Press Enter to save, Shift+Enter for new line",
|
||||
"addNotesPlaceholder": "Add your notes here...",
|
||||
"aboutThisVersion": "About this version"
|
||||
"aboutThisVersion": "About this version",
|
||||
"triggerWords": "Trigger Words"
|
||||
},
|
||||
"notes": {
|
||||
"saved": "Notes saved successfully",
|
||||
"saveFailed": "Failed to save notes"
|
||||
},
|
||||
"usageTips": {
|
||||
"add": "Add",
|
||||
"addPresetParameter": "Add preset parameter...",
|
||||
"strengthMin": "Strength Min",
|
||||
"strengthMax": "Strength Max",
|
||||
"strengthRange": "Strength Range",
|
||||
"strength": "Strength",
|
||||
"clipStrength": "Clip Strength",
|
||||
"clipSkip": "Clip Skip",
|
||||
"valuePlaceholder": "Value",
|
||||
"add": "Add"
|
||||
"invalidRange": "Invalid range format. Use x.x-y.y"
|
||||
},
|
||||
"params": {
|
||||
"title": "Generation Parameters",
|
||||
"prompt": "Prompt",
|
||||
"negativePrompt": "Negative Prompt",
|
||||
"noData": "No generation data available",
|
||||
"promptCopied": "Prompt copied to clipboard"
|
||||
},
|
||||
"triggerWords": {
|
||||
"label": "Trigger Words",
|
||||
"noTriggerWordsNeeded": "No trigger word needed",
|
||||
"noTriggerWordsNeeded": "No trigger words needed",
|
||||
"edit": "Edit trigger words",
|
||||
"cancel": "Cancel editing",
|
||||
"save": "Save changes",
|
||||
"addPlaceholder": "Type to add or click suggestions below",
|
||||
"addPlaceholder": "Type to add trigger word...",
|
||||
"copyWord": "Copy trigger word",
|
||||
"copyAll": "Copy all trigger words",
|
||||
"deleteWord": "Delete trigger word",
|
||||
"suggestions": {
|
||||
"noSuggestions": "No suggestions available",
|
||||
@@ -763,6 +979,9 @@
|
||||
"wordSuggestions": "Word Suggestions",
|
||||
"wordsFound": "{count} words found",
|
||||
"loading": "Loading suggestions..."
|
||||
},
|
||||
"validation": {
|
||||
"duplicate": "This trigger word already exists"
|
||||
}
|
||||
},
|
||||
"description": {
|
||||
@@ -780,13 +999,105 @@
|
||||
"tabs": {
|
||||
"examples": "Examples",
|
||||
"description": "Model Description",
|
||||
"recipes": "Recipes"
|
||||
"recipes": "Recipes",
|
||||
"versions": "Versions"
|
||||
},
|
||||
"navigation": {
|
||||
"label": "Model navigation",
|
||||
"previousWithShortcut": "Previous model (←)",
|
||||
"nextWithShortcut": "Next model (→)",
|
||||
"noPrevious": "No previous model available",
|
||||
"noNext": "No next model available",
|
||||
"previous": "Previous",
|
||||
"next": "Next",
|
||||
"switchModel": "Switch model",
|
||||
"browseExamples": "Browse examples"
|
||||
},
|
||||
"license": {
|
||||
"noImageSell": "No selling generated content",
|
||||
"noRentCivit": "No Civitai generation",
|
||||
"noRent": "No generation services",
|
||||
"noSell": "No selling models",
|
||||
"creditRequired": "Creator credit required",
|
||||
"noDerivatives": "No sharing merges",
|
||||
"noReLicense": "Same permissions required",
|
||||
"restrictionsLabel": "License restrictions"
|
||||
},
|
||||
"examples": {
|
||||
"add": "Add",
|
||||
"addFirst": "Add your first example",
|
||||
"dropFiles": "Drop files here or click to browse",
|
||||
"supportedFormats": "Supports: JPG, PNG, WEBP, MP4, WEBM",
|
||||
"uploading": "Uploading...",
|
||||
"uploadSuccess": "Example uploaded successfully",
|
||||
"uploadFailed": "Failed to upload example",
|
||||
"confirmDelete": "Delete this example image?",
|
||||
"deleted": "Example deleted successfully",
|
||||
"deleteFailed": "Failed to delete example",
|
||||
"title": "Example",
|
||||
"empty": "No example images available"
|
||||
},
|
||||
"accordion": {
|
||||
"modelDescription": "Model Description"
|
||||
},
|
||||
"loading": {
|
||||
"exampleImages": "Loading example images...",
|
||||
"description": "Loading model description...",
|
||||
"recipes": "Loading recipes...",
|
||||
"examples": "Loading examples..."
|
||||
"examples": "Loading examples...",
|
||||
"versions": "Loading versions..."
|
||||
},
|
||||
"versions": {
|
||||
"heading": "Model versions",
|
||||
"copy": "Track and manage every version of this model in one place.",
|
||||
"media": {
|
||||
"placeholder": "No preview"
|
||||
},
|
||||
"labels": {
|
||||
"unnamed": "Untitled Version",
|
||||
"noDetails": "No additional details"
|
||||
},
|
||||
"badges": {
|
||||
"current": "Current Version",
|
||||
"inLibrary": "In Library",
|
||||
"newer": "Newer Version",
|
||||
"ignored": "Ignored"
|
||||
},
|
||||
"actions": {
|
||||
"download": "Download",
|
||||
"delete": "Delete",
|
||||
"ignore": "Ignore",
|
||||
"unignore": "Unignore",
|
||||
"resumeModelUpdates": "Resume updates for this model",
|
||||
"ignoreModelUpdates": "Ignore updates for this model",
|
||||
"viewLocalVersions": "View all local versions",
|
||||
"viewLocalTooltip": "Coming soon"
|
||||
},
|
||||
"filters": {
|
||||
"label": "Base filter",
|
||||
"state": {
|
||||
"showAll": "All versions",
|
||||
"showSameBase": "Same base"
|
||||
},
|
||||
"tooltip": {
|
||||
"showAllVersions": "Switch to showing all versions",
|
||||
"showSameBaseVersions": "Switch to showing only versions that match the current base model"
|
||||
},
|
||||
"empty": "No versions match the current base model filter."
|
||||
},
|
||||
"empty": "No version history available for this model yet.",
|
||||
"error": "Failed to load versions.",
|
||||
"missingModelId": "This model is missing a Civitai model id.",
|
||||
"confirm": {
|
||||
"delete": "Delete this version from your library?"
|
||||
},
|
||||
"toast": {
|
||||
"modelIgnored": "Updates ignored for this model",
|
||||
"modelResumed": "Update tracking resumed",
|
||||
"versionIgnored": "Updates ignored for this version",
|
||||
"versionUnignored": "Version re-enabled",
|
||||
"versionDeleted": "Version deleted"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -893,7 +1204,9 @@
|
||||
"loraFailedToSend": "Failed to send LoRA to workflow",
|
||||
"recipeAdded": "Recipe appended to workflow",
|
||||
"recipeReplaced": "Recipe replaced in workflow",
|
||||
"recipeFailedToSend": "Failed to send recipe to workflow"
|
||||
"recipeFailedToSend": "Failed to send recipe to workflow",
|
||||
"noMatchingNodes": "No compatible nodes available in the current workflow",
|
||||
"noTargetNodeSelected": "No target node selected"
|
||||
},
|
||||
"nodeSelector": {
|
||||
"recipe": "Recipe",
|
||||
@@ -906,7 +1219,11 @@
|
||||
"exampleImages": {
|
||||
"opened": "Example images folder opened",
|
||||
"openingFolder": "Opening example images folder",
|
||||
"failedToOpen": "Failed to open example images folder"
|
||||
"failedToOpen": "Failed to open example images folder",
|
||||
"setupRequired": "Example Images Storage",
|
||||
"setupDescription": "To add custom example images, you need to set a download location first.",
|
||||
"setupUsage": "This path is used for both downloaded and custom example images.",
|
||||
"openSettings": "Open Settings"
|
||||
}
|
||||
},
|
||||
"help": {
|
||||
@@ -938,6 +1255,11 @@
|
||||
},
|
||||
"update": {
|
||||
"title": "Check for Updates",
|
||||
"notificationsTitle": "Notifications",
|
||||
"tabs": {
|
||||
"updates": "Updates",
|
||||
"messages": "Messages"
|
||||
},
|
||||
"updateAvailable": "Update Available",
|
||||
"noChangelogAvailable": "No detailed changelog available. Check GitHub for more information.",
|
||||
"currentVersion": "Current Version",
|
||||
@@ -950,6 +1272,7 @@
|
||||
"checkingUpdates": "Checking for updates...",
|
||||
"checkingMessage": "Please wait while we check for the latest version.",
|
||||
"showNotifications": "Show update notifications",
|
||||
"latestBadge": "Latest",
|
||||
"updateProgress": {
|
||||
"preparing": "Preparing update...",
|
||||
"installing": "Installing update...",
|
||||
@@ -969,6 +1292,13 @@
|
||||
"nightly": {
|
||||
"warning": "Warning: Nightly builds may contain experimental features and could be unstable.",
|
||||
"enable": "Enable Nightly Updates"
|
||||
},
|
||||
"banners": {
|
||||
"recent": "Recent messages",
|
||||
"empty": "No recent banners yet.",
|
||||
"shown": "Shown {time}",
|
||||
"dismissed": "Dismissed {time}",
|
||||
"active": "Active"
|
||||
}
|
||||
},
|
||||
"support": {
|
||||
@@ -1048,6 +1378,9 @@
|
||||
"cannotSend": "Cannot send recipe: Missing recipe ID",
|
||||
"sendFailed": "Failed to send recipe to workflow",
|
||||
"sendError": "Error sending recipe to workflow",
|
||||
"missingCheckpointPath": "Checkpoint path not available",
|
||||
"missingCheckpointInfo": "Missing checkpoint information",
|
||||
"downloadCheckpointFailed": "Failed to download checkpoint: {message}",
|
||||
"cannotDelete": "Cannot delete recipe: Missing recipe ID",
|
||||
"deleteConfirmationError": "Error showing delete confirmation",
|
||||
"deletedSuccessfully": "Recipe deleted successfully",
|
||||
@@ -1084,6 +1417,16 @@
|
||||
"bulkBaseModelUpdateSuccess": "Successfully updated base model for {count} model(s)",
|
||||
"bulkBaseModelUpdatePartial": "Updated {success} model(s), failed {failed} model(s)",
|
||||
"bulkBaseModelUpdateFailed": "Failed to update base model for selected models",
|
||||
"bulkContentRatingUpdating": "Updating content rating for {count} model(s)...",
|
||||
"bulkContentRatingSet": "Set content rating to {level} for {count} model(s)",
|
||||
"bulkContentRatingPartial": "Set content rating to {level} for {success} model(s), {failed} failed",
|
||||
"bulkContentRatingFailed": "Failed to update content rating for selected models",
|
||||
"bulkUpdatesChecking": "Checking selected {type}(s) for updates...",
|
||||
"bulkUpdatesSuccess": "Updates available for {count} selected {type}(s)",
|
||||
"bulkUpdatesNone": "No updates found for selected {type}(s)",
|
||||
"bulkUpdatesMissing": "Selected {type}(s) are not linked to Civitai updates",
|
||||
"bulkUpdatesPartialMissing": "Skipped {missing} selected {type}(s) without Civitai links",
|
||||
"bulkUpdatesFailed": "Failed to check updates for selected {type}(s): {message}",
|
||||
"invalidCharactersRemoved": "Invalid characters removed from filename",
|
||||
"filenameCannotBeEmpty": "File name cannot be empty",
|
||||
"renameFailed": "Failed to rename file: {message}",
|
||||
@@ -1095,6 +1438,7 @@
|
||||
"verificationCompleteSuccess": "Verification complete. All files are confirmed duplicates.",
|
||||
"verificationFailed": "Failed to verify hashes: {message}",
|
||||
"noTagsToAdd": "No tags to add",
|
||||
"bulkTagsUpdating": "Updating tags for {count} model(s)...",
|
||||
"tagsAddedSuccessfully": "Successfully added {tagCount} tag(s) to {count} {type}(s)",
|
||||
"tagsReplacedSuccessfully": "Successfully replaced tags for {count} {type}(s) with {tagCount} tag(s)",
|
||||
"tagsAddFailed": "Failed to add tags to {count} model(s)",
|
||||
@@ -1108,6 +1452,7 @@
|
||||
"settings": {
|
||||
"loraRootsFailed": "Failed to load LoRA roots: {message}",
|
||||
"checkpointRootsFailed": "Failed to load checkpoint roots: {message}",
|
||||
"unetRootsFailed": "Failed to load diffusion model roots: {message}",
|
||||
"embeddingRootsFailed": "Failed to load embedding roots: {message}",
|
||||
"mappingsUpdated": "Base model path mappings updated ({count} mapping{plural})",
|
||||
"mappingsCleared": "Base model path mappings cleared",
|
||||
@@ -1118,6 +1463,8 @@
|
||||
"compactModeToggled": "Compact Mode {state}",
|
||||
"settingSaveFailed": "Failed to save setting: {message}",
|
||||
"displayDensitySet": "Display Density set to {density}",
|
||||
"libraryLoadFailed": "Failed to load libraries: {message}",
|
||||
"libraryActivateFailed": "Failed to activate library: {message}",
|
||||
"languageChangeFailed": "Failed to change language: {message}",
|
||||
"cacheCleared": "Cache files have been cleared successfully. Cache will rebuild on next action.",
|
||||
"cacheClearFailed": "Failed to clear cache: {error}",
|
||||
@@ -1126,7 +1473,26 @@
|
||||
"filters": {
|
||||
"applied": "{message}",
|
||||
"cleared": "Filters cleared",
|
||||
"noCustomFilterToClear": "No custom filter to clear"
|
||||
"noCustomFilterToClear": "No custom filter to clear",
|
||||
"noActiveFilters": "No active filters to save"
|
||||
},
|
||||
"presets": {
|
||||
"created": "Preset \"{name}\" created",
|
||||
"deleted": "Preset \"{name}\" deleted",
|
||||
"applied": "Preset \"{name}\" applied",
|
||||
"overwritten": "Preset \"{name}\" overwritten",
|
||||
"restored": "Default presets restored"
|
||||
},
|
||||
"error": {
|
||||
"presetNameEmpty": "Preset name cannot be empty",
|
||||
"presetNameTooLong": "Preset name must be {max} characters or less",
|
||||
"presetNameInvalidChars": "Preset name contains invalid characters",
|
||||
"presetNameExists": "A preset with this name already exists",
|
||||
"maxPresetsReached": "Maximum {max} presets allowed. Delete one to add more.",
|
||||
"presetNotFound": "Preset not found",
|
||||
"invalidPreset": "Invalid preset data",
|
||||
"deletePresetFailed": "Failed to delete preset",
|
||||
"applyPresetFailed": "Failed to apply preset"
|
||||
},
|
||||
"downloads": {
|
||||
"imagesCompleted": "Example images {action} completed",
|
||||
@@ -1142,7 +1508,7 @@
|
||||
},
|
||||
"triggerWords": {
|
||||
"loadFailed": "Could not load trained words",
|
||||
"tooLong": "Trigger word should not exceed 30 words",
|
||||
"tooLong": "Trigger word should not exceed 100 words",
|
||||
"tooMany": "Maximum 30 trigger words allowed",
|
||||
"alreadyExists": "This trigger word already exists",
|
||||
"updateSuccess": "Trigger words updated successfully",
|
||||
@@ -1191,6 +1557,8 @@
|
||||
"pauseFailed": "Failed to pause download: {error}",
|
||||
"downloadResumed": "Download resumed",
|
||||
"resumeFailed": "Failed to resume download: {error}",
|
||||
"downloadStopped": "Download cancelled",
|
||||
"stopFailed": "Failed to cancel download: {error}",
|
||||
"deleted": "Example image deleted",
|
||||
"deleteFailed": "Failed to delete example image",
|
||||
"setPreviewFailed": "Failed to set preview image"
|
||||
@@ -1211,6 +1579,8 @@
|
||||
"metadataRefreshed": "Metadata refreshed successfully",
|
||||
"metadataRefreshFailed": "Failed to refresh metadata: {message}",
|
||||
"metadataUpdateComplete": "Metadata update complete",
|
||||
"operationCancelled": "Operation cancelled by user",
|
||||
"operationCancelledPartial": "Operation cancelled. {success} items processed.",
|
||||
"metadataFetchFailed": "Failed to fetch metadata: {message}",
|
||||
"bulkMetadataCompleteAll": "Successfully refreshed all {count} {type}s",
|
||||
"bulkMetadataCompletePartial": "Refreshed {success} of {total} {type}s",
|
||||
@@ -1227,7 +1597,8 @@
|
||||
"bulkMoveFailures": "Failed moves:\n{failures}",
|
||||
"bulkMoveSuccess": "Successfully moved {successCount} {type}s",
|
||||
"exampleImagesDownloadSuccess": "Successfully downloaded example images!",
|
||||
"exampleImagesDownloadFailed": "Failed to download example images: {message}"
|
||||
"exampleImagesDownloadFailed": "Failed to download example images: {message}",
|
||||
"moveFailed": "Failed to move item: {message}"
|
||||
}
|
||||
},
|
||||
"banners": {
|
||||
@@ -1237,6 +1608,26 @@
|
||||
"refreshNow": "Refresh Now",
|
||||
"refreshingIn": "Refreshing in",
|
||||
"seconds": "seconds"
|
||||
},
|
||||
"communitySupport": {
|
||||
"title": "Keep LoRA Manager Thriving with Your Support ❤️",
|
||||
"content": "LoRA Manager is a passion project maintained full-time by a solo developer. Your support on Ko-fi helps cover development costs, keeps new updates coming, and unlocks a license key for the LM Civitai Extension as a thank-you gift. Every contribution truly makes a difference.",
|
||||
"supportCta": "Support on Ko-fi",
|
||||
"learnMore": "LM Civitai Extension Tutorial"
|
||||
},
|
||||
"cacheHealth": {
|
||||
"corrupted": {
|
||||
"title": "Cache Corruption Detected"
|
||||
},
|
||||
"degraded": {
|
||||
"title": "Cache Issues Detected"
|
||||
},
|
||||
"content": "{invalid} of {total} cache entries are invalid ({rate}). This may cause missing models or errors. Rebuilding the cache is recommended.",
|
||||
"rebuildCache": "Rebuild Cache",
|
||||
"dismiss": "Dismiss",
|
||||
"rebuilding": "Rebuilding cache...",
|
||||
"rebuildFailed": "Failed to rebuild cache: {error}",
|
||||
"retry": "Retry"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
413
locales/es.json
413
locales/es.json
@@ -10,7 +10,8 @@
|
||||
"next": "Siguiente",
|
||||
"backToTop": "Volver arriba",
|
||||
"settings": "Configuración",
|
||||
"help": "Ayuda"
|
||||
"help": "Ayuda",
|
||||
"add": "Añadir"
|
||||
},
|
||||
"status": {
|
||||
"loading": "Cargando...",
|
||||
@@ -31,7 +32,8 @@
|
||||
"japanese": "日本語",
|
||||
"korean": "한국어",
|
||||
"french": "Français",
|
||||
"spanish": "Español"
|
||||
"spanish": "Español",
|
||||
"Hebrew": "עברית"
|
||||
},
|
||||
"fileSize": {
|
||||
"zero": "0 Bytes",
|
||||
@@ -100,7 +102,12 @@
|
||||
"checkpointNameCopied": "Nombre del checkpoint copiado",
|
||||
"toggleBlur": "Alternar difuminado",
|
||||
"show": "Mostrar",
|
||||
"openExampleImages": "Abrir carpeta de imágenes de ejemplo"
|
||||
"openExampleImages": "Abrir carpeta de imágenes de ejemplo",
|
||||
"replacePreview": "Reemplazar vista previa",
|
||||
"copyCheckpointName": "Copiar nombre del checkpoint",
|
||||
"copyEmbeddingName": "Copiar nombre del embedding",
|
||||
"sendCheckpointToWorkflow": "Enviar a ComfyUI",
|
||||
"sendEmbeddingToWorkflow": "Enviar a ComfyUI"
|
||||
},
|
||||
"nsfw": {
|
||||
"matureContent": "Contenido para adultos",
|
||||
@@ -114,12 +121,20 @@
|
||||
"updateFailed": "Error al actualizar estado de favoritos"
|
||||
},
|
||||
"sendToWorkflow": {
|
||||
"checkpointNotImplemented": "Enviar checkpoint al flujo de trabajo - función por implementar"
|
||||
"checkpointNotImplemented": "Enviar checkpoint al flujo de trabajo - función por implementar",
|
||||
"missingPath": "No se puede determinar la ruta del modelo para esta tarjeta"
|
||||
},
|
||||
"exampleImages": {
|
||||
"checkError": "Error al verificar imágenes de ejemplo",
|
||||
"missingHash": "Falta información del hash del modelo.",
|
||||
"noRemoteImagesAvailable": "No hay imágenes de ejemplo remotas disponibles para este modelo en Civitai"
|
||||
},
|
||||
"badges": {
|
||||
"update": "Actualización",
|
||||
"updateAvailable": "Actualización disponible"
|
||||
},
|
||||
"usage": {
|
||||
"timesUsed": "Veces usado"
|
||||
}
|
||||
},
|
||||
"globalContextMenu": {
|
||||
@@ -128,12 +143,33 @@
|
||||
"missingPath": "Establece una ubicación de descarga antes de descargar imágenes de ejemplo.",
|
||||
"unavailable": "Las descargas de imágenes de ejemplo aún no están disponibles. Intenta de nuevo después de que la página termine de cargar."
|
||||
},
|
||||
"checkModelUpdates": {
|
||||
"label": "Buscar actualizaciones",
|
||||
"loading": "Buscando actualizaciones de {type}...",
|
||||
"success": "Se encontraron {count} actualización(es) para {type}",
|
||||
"none": "Todos los {type} están actualizados",
|
||||
"error": "Error al buscar actualizaciones de {type}: {message}"
|
||||
},
|
||||
"cleanupExampleImages": {
|
||||
"label": "Limpiar carpetas de imágenes de ejemplo",
|
||||
"success": "Se movieron {count} carpeta(s) a la carpeta de eliminados",
|
||||
"none": "No hay carpetas de imágenes de ejemplo que necesiten limpieza",
|
||||
"partial": "Limpieza completada con {failures} carpeta(s) omitidas",
|
||||
"error": "No se pudieron limpiar las carpetas de imágenes de ejemplo: {message}"
|
||||
},
|
||||
"fetchMissingLicenses": {
|
||||
"label": "Refresh license metadata",
|
||||
"loading": "Refreshing license metadata for {typePlural}...",
|
||||
"success": "Updated license metadata for {count} {typePlural}",
|
||||
"none": "All {typePlural} already have license metadata",
|
||||
"error": "Failed to refresh license metadata for {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Reparar datos de recetas",
|
||||
"loading": "Reparando datos de recetas...",
|
||||
"success": "Se repararon con éxito {count} recetas.",
|
||||
"cancelled": "Reparación cancelada. {count} recetas fueron reparadas.",
|
||||
"error": "Error al reparar recetas: {message}"
|
||||
}
|
||||
},
|
||||
"header": {
|
||||
@@ -163,14 +199,35 @@
|
||||
"creator": "Creador",
|
||||
"title": "Título de la receta",
|
||||
"loraName": "Nombre de archivo LoRA",
|
||||
"loraModel": "Nombre del modelo LoRA"
|
||||
"loraModel": "Nombre del modelo LoRA",
|
||||
"prompt": "Prompt"
|
||||
}
|
||||
},
|
||||
"filter": {
|
||||
"title": "Filtrar modelos",
|
||||
"presets": "Preajustes",
|
||||
"savePreset": "Guardar filtros activos como nuevo preajuste.",
|
||||
"savePresetDisabledActive": "No se puede guardar: Ya hay un preajuste activo. Modifique los filtros para guardar un nuevo preajuste",
|
||||
"savePresetDisabledNoFilters": "Seleccione filtros primero para guardar como preajuste",
|
||||
"savePresetPrompt": "Ingrese el nombre del preajuste:",
|
||||
"presetClickTooltip": "Hacer clic para aplicar preajuste \"{name}\"",
|
||||
"presetDeleteTooltip": "Eliminar preajuste",
|
||||
"presetDeleteConfirm": "¿Eliminar preajuste \"{name}\"?",
|
||||
"presetDeleteConfirmClick": "Haga clic de nuevo para confirmar",
|
||||
"presetOverwriteConfirm": "El preset \"{name}\" ya existe. ¿Sobrescribir?",
|
||||
"presetNamePlaceholder": "Nombre del preajuste...",
|
||||
"baseModel": "Modelo base",
|
||||
"modelTags": "Etiquetas (Top 20)",
|
||||
"clearAll": "Limpiar todos los filtros"
|
||||
"modelTypes": "Model Types",
|
||||
"license": "Licencia",
|
||||
"noCreditRequired": "Sin crédito requerido",
|
||||
"allowSellingGeneratedContent": "Venta permitida",
|
||||
"noTags": "Sin etiquetas",
|
||||
"clearAll": "Limpiar todos los filtros",
|
||||
"any": "Cualquiera",
|
||||
"all": "Todos",
|
||||
"tagLogicAny": "Coincidir con cualquier etiqueta (O)",
|
||||
"tagLogicAll": "Coincidir con todas las etiquetas (Y)"
|
||||
},
|
||||
"theme": {
|
||||
"toggle": "Cambiar tema",
|
||||
@@ -180,6 +237,7 @@
|
||||
},
|
||||
"actions": {
|
||||
"checkUpdates": "Comprobar actualizaciones",
|
||||
"notifications": "Notificaciones",
|
||||
"support": "Soporte"
|
||||
}
|
||||
},
|
||||
@@ -187,17 +245,33 @@
|
||||
"civitaiApiKey": "Clave API de Civitai",
|
||||
"civitaiApiKeyPlaceholder": "Introduce tu clave API de Civitai",
|
||||
"civitaiApiKeyHelp": "Utilizada para autenticación al descargar modelos de Civitai",
|
||||
"openSettingsFileLocation": {
|
||||
"label": "Abrir carpeta de ajustes",
|
||||
"tooltip": "Abrir la carpeta que contiene settings.json",
|
||||
"success": "Carpeta de settings.json abierta",
|
||||
"failed": "No se pudo abrir la carpeta de settings.json",
|
||||
"copied": "Ruta de configuración copiada al portapapeles: {{path}}",
|
||||
"clipboardFallback": "Ruta de configuración: {{path}}"
|
||||
},
|
||||
"sections": {
|
||||
"contentFiltering": "Filtrado de contenido",
|
||||
"videoSettings": "Configuración de video",
|
||||
"layoutSettings": "Configuración de diseño",
|
||||
"folderSettings": "Configuración de carpetas",
|
||||
"priorityTags": "Etiquetas prioritarias",
|
||||
"downloadPathTemplates": "Plantillas de rutas de descarga",
|
||||
"exampleImages": "Imágenes de ejemplo",
|
||||
"updateFlags": "Indicadores de actualización",
|
||||
"autoOrganize": "Auto-organize",
|
||||
"misc": "Varios",
|
||||
"metadataArchive": "Base de datos de archivo de metadatos",
|
||||
"storageLocation": "Ubicación de ajustes",
|
||||
"proxySettings": "Configuración de proxy"
|
||||
},
|
||||
"storage": {
|
||||
"locationLabel": "Modo portátil",
|
||||
"locationHelp": "Activa para mantener settings.json dentro del repositorio; desactívalo para guardarlo en tu directorio de configuración de usuario."
|
||||
},
|
||||
"contentFiltering": {
|
||||
"blurNsfwContent": "Difuminar contenido NSFW",
|
||||
"blurNsfwContentHelp": "Difuminar imágenes de vista previa de contenido para adultos (NSFW)",
|
||||
@@ -208,6 +282,15 @@
|
||||
"autoplayOnHover": "Reproducir videos automáticamente al pasar el ratón",
|
||||
"autoplayOnHoverHelp": "Solo reproducir vistas previas de video al pasar el ratón sobre ellas"
|
||||
},
|
||||
"autoOrganizeExclusions": {
|
||||
"label": "Exclusiones de auto-organización",
|
||||
"placeholder": "Ejemplo: curated/*, */backups/*; *_temp.safetensors",
|
||||
"help": "Omitir archivos que coincidan con estos patrones comodín. Separe múltiples patrones con comas o puntos y comas.",
|
||||
"validation": {
|
||||
"noPatterns": "Ingrese al menos un patrón separado por comas o puntos y comas.",
|
||||
"saveFailed": "No se pudieron guardar las exclusiones: {message}"
|
||||
}
|
||||
},
|
||||
"layoutSettings": {
|
||||
"displayDensity": "Densidad de visualización",
|
||||
"displayDensityOptions": {
|
||||
@@ -217,31 +300,67 @@
|
||||
},
|
||||
"displayDensityHelp": "Elige cuántas tarjetas mostrar por fila:",
|
||||
"displayDensityDetails": {
|
||||
"default": "Predeterminado: 5 (1080p), 6 (2K), 8 (4K)",
|
||||
"medium": "Medio: 6 (1080p), 7 (2K), 9 (4K)",
|
||||
"compact": "Compacto: 7 (1080p), 8 (2K), 10 (4K)"
|
||||
"default": "5 (1080p), 6 (2K), 8 (4K)",
|
||||
"medium": "6 (1080p), 7 (2K), 9 (4K)",
|
||||
"compact": "7 (1080p), 8 (2K), 10 (4K)"
|
||||
},
|
||||
"displayDensityWarning": "Advertencia: Densidades más altas pueden causar problemas de rendimiento en sistemas con recursos limitados.",
|
||||
"showFolderSidebar": "Mostrar barra lateral de carpetas",
|
||||
"showFolderSidebarHelp": "Activa o desactiva la barra lateral de navegación de carpetas en las páginas de modelos. Cuando está desactivada, la barra lateral y el área de desplazamiento permanecen ocultas.",
|
||||
"cardInfoDisplay": "Visualización de información de tarjeta",
|
||||
"cardInfoDisplayOptions": {
|
||||
"always": "Siempre visible",
|
||||
"hover": "Mostrar al pasar el ratón"
|
||||
},
|
||||
"cardInfoDisplayHelp": "Elige cuándo mostrar información del modelo y botones de acción:",
|
||||
"cardInfoDisplayDetails": {
|
||||
"always": "Siempre visible: Los encabezados y pies de página siempre son visibles",
|
||||
"hover": "Mostrar al pasar el ratón: Los encabezados y pies de página solo aparecen al pasar el ratón sobre una tarjeta"
|
||||
}
|
||||
"cardInfoDisplayHelp": "Elige cuándo mostrar información del modelo y botones de acción",
|
||||
"modelCardFooterAction": "Acción del botón de tarjeta de modelo",
|
||||
"modelCardFooterActionOptions": {
|
||||
"exampleImages": "Abrir imágenes de ejemplo",
|
||||
"replacePreview": "Reemplazar vista previa"
|
||||
},
|
||||
"modelCardFooterActionHelp": "Elige qué hace el botón en la esquina inferior derecha de la tarjeta",
|
||||
"modelNameDisplay": "Visualización del nombre del modelo",
|
||||
"modelNameDisplayOptions": {
|
||||
"modelName": "Nombre del modelo",
|
||||
"fileName": "Nombre del archivo"
|
||||
},
|
||||
"modelNameDisplayHelp": "Elige qué mostrar en el pie de la tarjeta del modelo"
|
||||
},
|
||||
"folderSettings": {
|
||||
"activeLibrary": "Biblioteca activa",
|
||||
"activeLibraryHelp": "Alterna entre las bibliotecas configuradas para actualizar las carpetas predeterminadas. Cambiar la selección recarga la página.",
|
||||
"loadingLibraries": "Cargando bibliotecas...",
|
||||
"noLibraries": "No hay bibliotecas configuradas",
|
||||
"defaultLoraRoot": "Raíz predeterminada de LoRA",
|
||||
"defaultLoraRootHelp": "Establecer el directorio raíz predeterminado de LoRA para descargas, importaciones y movimientos",
|
||||
"defaultCheckpointRoot": "Raíz predeterminada de checkpoint",
|
||||
"defaultCheckpointRootHelp": "Establecer el directorio raíz predeterminado de checkpoint para descargas, importaciones y movimientos",
|
||||
"defaultUnetRoot": "Raíz predeterminada de Diffusion Model",
|
||||
"defaultUnetRootHelp": "Establecer el directorio raíz predeterminado de Diffusion Model (UNET) para descargas, importaciones y movimientos",
|
||||
"defaultEmbeddingRoot": "Raíz predeterminada de embedding",
|
||||
"defaultEmbeddingRootHelp": "Establecer el directorio raíz predeterminado de embedding para descargas, importaciones y movimientos",
|
||||
"noDefault": "Sin predeterminado"
|
||||
},
|
||||
"priorityTags": {
|
||||
"title": "Etiquetas prioritarias",
|
||||
"description": "Personaliza el orden de prioridad de etiquetas para cada tipo de modelo (p. ej., character, concept, style(toon|toon_style))",
|
||||
"placeholder": "character, concept, style(toon|toon_style)",
|
||||
"helpLinkLabel": "Abrir ayuda de etiquetas prioritarias",
|
||||
"modelTypes": {
|
||||
"lora": "LoRA",
|
||||
"checkpoint": "Checkpoint",
|
||||
"embedding": "Embedding"
|
||||
},
|
||||
"saveSuccess": "Etiquetas prioritarias actualizadas.",
|
||||
"saveError": "Error al actualizar las etiquetas prioritarias.",
|
||||
"loadingSuggestions": "Cargando sugerencias...",
|
||||
"validation": {
|
||||
"missingClosingParen": "A la entrada {index} le falta un paréntesis de cierre.",
|
||||
"missingCanonical": "La entrada {index} debe incluir un nombre de etiqueta canónica.",
|
||||
"duplicateCanonical": "La etiqueta canónica \"{tag}\" aparece más de una vez.",
|
||||
"unknown": "Configuración de etiquetas prioritarias no válida."
|
||||
}
|
||||
},
|
||||
"downloadPathTemplates": {
|
||||
"title": "Plantillas de rutas de descarga",
|
||||
"help": "Configurar estructuras de carpetas para diferentes tipos de modelos al descargar de Civitai.",
|
||||
@@ -289,6 +408,14 @@
|
||||
"download": "Descargar",
|
||||
"restartRequired": "Requiere reinicio"
|
||||
},
|
||||
"updateFlagStrategy": {
|
||||
"label": "Estrategia de indicadores de actualización",
|
||||
"help": "Decide si las insignias de actualización deben mostrarse solo cuando una nueva versión comparte el mismo modelo base que tus archivos locales o siempre que exista cualquier versión más reciente de ese modelo.",
|
||||
"options": {
|
||||
"sameBase": "Coincidir actualizaciones por modelo base",
|
||||
"any": "Marcar cualquier actualización disponible"
|
||||
}
|
||||
},
|
||||
"misc": {
|
||||
"includeTriggerWords": "Incluir palabras clave en la sintaxis de LoRA",
|
||||
"includeTriggerWordsHelp": "Incluir palabras clave entrenadas al copiar la sintaxis de LoRA al portapapeles"
|
||||
@@ -348,12 +475,17 @@
|
||||
"dateAsc": "Más antiguo",
|
||||
"size": "Tamaño de archivo",
|
||||
"sizeDesc": "Mayor",
|
||||
"sizeAsc": "Menor"
|
||||
"sizeAsc": "Menor",
|
||||
"usage": "Número de usos",
|
||||
"usageDesc": "Más",
|
||||
"usageAsc": "Menos"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "Actualizar lista de modelos",
|
||||
"quick": "Actualización rápida (incremental)",
|
||||
"full": "Reconstrucción completa"
|
||||
"quick": "Sincronizar cambios",
|
||||
"quickTooltip": "Busca archivos de modelo nuevos o faltantes para mantener la lista al día.",
|
||||
"full": "Reconstruir caché",
|
||||
"fullTooltip": "Vuelve a cargar todos los detalles desde los archivos de metadatos; úsalo si la biblioteca parece desactualizada o tras ediciones manuales."
|
||||
},
|
||||
"fetch": {
|
||||
"title": "Obtener metadatos de Civitai",
|
||||
@@ -374,6 +506,13 @@
|
||||
"favorites": {
|
||||
"title": "Mostrar solo favoritos",
|
||||
"action": "Favoritos"
|
||||
},
|
||||
"updates": {
|
||||
"title": "Mostrar solo modelos con actualizaciones disponibles",
|
||||
"action": "Actualizaciones",
|
||||
"menuLabel": "Mostrar opciones de actualización",
|
||||
"check": "Buscar actualizaciones",
|
||||
"checkTooltip": "Comprobar actualizaciones puede tardar."
|
||||
}
|
||||
},
|
||||
"bulkOperations": {
|
||||
@@ -382,8 +521,10 @@
|
||||
"viewSelected": "Ver seleccionados",
|
||||
"addTags": "Añadir etiquetas a todos",
|
||||
"setBaseModel": "Establecer modelo base para todos",
|
||||
"setContentRating": "Establecer clasificación de contenido para todos",
|
||||
"copyAll": "Copiar toda la sintaxis",
|
||||
"refreshAll": "Actualizar todos los metadatos",
|
||||
"checkUpdates": "Comprobar actualizaciones para la selección",
|
||||
"moveAll": "Mover todos a carpeta",
|
||||
"autoOrganize": "Auto-organizar seleccionados",
|
||||
"deleteAll": "Eliminar todos los modelos",
|
||||
@@ -400,6 +541,7 @@
|
||||
},
|
||||
"contextMenu": {
|
||||
"refreshMetadata": "Actualizar datos de Civitai",
|
||||
"checkUpdates": "Comprobar actualizaciones",
|
||||
"relinkCivitai": "Re-vincular a Civitai",
|
||||
"copySyntax": "Copiar sintaxis de LoRA",
|
||||
"copyFilename": "Copiar nombre de archivo del modelo",
|
||||
@@ -411,6 +553,7 @@
|
||||
"replacePreview": "Reemplazar vista previa",
|
||||
"setContentRating": "Establecer clasificación de contenido",
|
||||
"moveToFolder": "Mover a carpeta",
|
||||
"repairMetadata": "Reparar metadatos",
|
||||
"excludeModel": "Excluir modelo",
|
||||
"deleteModel": "Eliminar modelo",
|
||||
"shareRecipe": "Compartir receta",
|
||||
@@ -421,6 +564,9 @@
|
||||
},
|
||||
"recipes": {
|
||||
"title": "Recetas de LoRA",
|
||||
"actions": {
|
||||
"sendCheckpoint": "Enviar a ComfyUI"
|
||||
},
|
||||
"controls": {
|
||||
"import": {
|
||||
"action": "Importar",
|
||||
@@ -478,10 +624,26 @@
|
||||
"selectLoraRoot": "Por favor selecciona un directorio raíz de LoRA"
|
||||
}
|
||||
},
|
||||
"sort": {
|
||||
"title": "Ordenar recetas por...",
|
||||
"name": "Nombre",
|
||||
"nameAsc": "A - Z",
|
||||
"nameDesc": "Z - A",
|
||||
"date": "Fecha",
|
||||
"dateDesc": "Más reciente",
|
||||
"dateAsc": "Más antiguo",
|
||||
"lorasCount": "Cant. de LoRAs",
|
||||
"lorasCountDesc": "Más",
|
||||
"lorasCountAsc": "Menos"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "Actualizar lista de recetas"
|
||||
},
|
||||
"filteredByLora": "Filtrado por LoRA"
|
||||
"filteredByLora": "Filtrado por LoRA",
|
||||
"favorites": {
|
||||
"title": "Mostrar solo favoritos",
|
||||
"action": "Favoritos"
|
||||
}
|
||||
},
|
||||
"duplicates": {
|
||||
"found": "Se encontraron {count} grupos de duplicados",
|
||||
@@ -507,23 +669,44 @@
|
||||
"noMissingLoras": "No hay LoRAs faltantes para descargar",
|
||||
"getInfoFailed": "Error al obtener información de LoRAs faltantes",
|
||||
"prepareError": "Error preparando LoRAs para descarga: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "Reparando metadatos de la receta...",
|
||||
"success": "Metadatos de la receta reparados con éxito",
|
||||
"skipped": "La receta ya está en la última versión, no se necesita reparación",
|
||||
"failed": "Error al reparar la receta: {message}",
|
||||
"missingId": "No se puede reparar la receta: falta el ID de la receta"
|
||||
}
|
||||
}
|
||||
},
|
||||
"checkpoints": {
|
||||
"title": "Modelos checkpoint"
|
||||
"title": "Modelos checkpoint",
|
||||
"modelTypes": {
|
||||
"checkpoint": "Checkpoint",
|
||||
"diffusion_model": "Diffusion Model"
|
||||
},
|
||||
"contextMenu": {
|
||||
"moveToOtherTypeFolder": "Mover a la carpeta {otherType}"
|
||||
}
|
||||
},
|
||||
"embeddings": {
|
||||
"title": "Modelos embedding"
|
||||
},
|
||||
"sidebar": {
|
||||
"modelRoot": "Raíz del modelo",
|
||||
"modelRoot": "Raíz",
|
||||
"collapseAll": "Colapsar todas las carpetas",
|
||||
"pinSidebar": "Fijar barra lateral",
|
||||
"unpinSidebar": "Desfijar barra lateral",
|
||||
"switchToListView": "Cambiar a vista de lista",
|
||||
"switchToTreeView": "Cambiar a vista de árbol",
|
||||
"collapseAllDisabled": "No disponible en vista de lista"
|
||||
"recursiveOn": "Buscar en subcarpetas",
|
||||
"recursiveOff": "Buscar solo en la carpeta actual",
|
||||
"recursiveUnavailable": "La búsqueda recursiva solo está disponible en la vista en árbol",
|
||||
"collapseAllDisabled": "No disponible en vista de lista",
|
||||
"dragDrop": {
|
||||
"unableToResolveRoot": "No se puede determinar la ruta de destino para el movimiento.",
|
||||
"moveUnsupported": "Move is not supported for this item."
|
||||
}
|
||||
},
|
||||
"statistics": {
|
||||
"title": "Estadísticas",
|
||||
@@ -598,6 +781,14 @@
|
||||
"downloadedPreview": "Imagen de vista previa descargada",
|
||||
"downloadingFile": "Descargando archivo de {type}",
|
||||
"finalizing": "Finalizando descarga..."
|
||||
},
|
||||
"progress": {
|
||||
"currentFile": "Archivo actual:",
|
||||
"downloading": "Descargando: {name}",
|
||||
"transferred": "Descargado: {downloaded} / {total}",
|
||||
"transferredSimple": "Descargado: {downloaded}",
|
||||
"transferredUnknown": "Descargado: --",
|
||||
"speed": "Velocidad: {speed}"
|
||||
}
|
||||
},
|
||||
"move": {
|
||||
@@ -606,6 +797,7 @@
|
||||
"contentRating": {
|
||||
"title": "Establecer clasificación de contenido",
|
||||
"current": "Actual",
|
||||
"multiple": "Valores múltiples",
|
||||
"levels": {
|
||||
"pg": "PG",
|
||||
"pg13": "PG13",
|
||||
@@ -644,6 +836,12 @@
|
||||
"countMessage": "modelos serán eliminados permanentemente.",
|
||||
"action": "Eliminar todo"
|
||||
},
|
||||
"checkUpdates": {
|
||||
"title": "¿Comprobar actualizaciones para todos los {typePlural}?",
|
||||
"message": "Esto comprobará las actualizaciones de todos los {typePlural} de tu biblioteca. En colecciones grandes puede tardar un poco más.",
|
||||
"tip": "¿Quieres hacerlo por partes? Activa el modo por lotes, selecciona los modelos que necesites y usa \"Comprobar actualizaciones para la selección\".",
|
||||
"action": "Comprobar todo"
|
||||
},
|
||||
"bulkAddTags": {
|
||||
"title": "Añadir etiquetas a múltiples modelos",
|
||||
"description": "Añadir etiquetas a",
|
||||
@@ -717,7 +915,9 @@
|
||||
},
|
||||
"openFileLocation": {
|
||||
"success": "Ubicación del archivo abierta exitosamente",
|
||||
"failed": "Error al abrir la ubicación del archivo"
|
||||
"failed": "Error al abrir la ubicación del archivo",
|
||||
"copied": "Ruta copiada al portapapeles: {{path}}",
|
||||
"clipboardFallback": "Ruta: {{path}}"
|
||||
},
|
||||
"metadata": {
|
||||
"version": "Versión",
|
||||
@@ -740,11 +940,13 @@
|
||||
"addPresetParameter": "Añadir parámetro preestablecido...",
|
||||
"strengthMin": "Fuerza mínima",
|
||||
"strengthMax": "Fuerza máxima",
|
||||
"strengthRange": "Rango de fuerza",
|
||||
"strength": "Fuerza",
|
||||
"clipStrength": "Fuerza de Clip",
|
||||
"clipSkip": "Clip Skip",
|
||||
"valuePlaceholder": "Valor",
|
||||
"add": "Añadir"
|
||||
"add": "Añadir",
|
||||
"invalidRange": "Formato de rango inválido. Use x.x-y.y"
|
||||
},
|
||||
"triggerWords": {
|
||||
"label": "Palabras clave",
|
||||
@@ -780,13 +982,84 @@
|
||||
"tabs": {
|
||||
"examples": "Ejemplos",
|
||||
"description": "Descripción del modelo",
|
||||
"recipes": "Recetas"
|
||||
"recipes": "Recetas",
|
||||
"versions": "Versiones"
|
||||
},
|
||||
"navigation": {
|
||||
"label": "Navegación de modelos",
|
||||
"previousWithShortcut": "Modelo anterior (←)",
|
||||
"nextWithShortcut": "Siguiente modelo (→)",
|
||||
"noPrevious": "No hay modelo anterior disponible",
|
||||
"noNext": "No hay siguiente modelo disponible"
|
||||
},
|
||||
"license": {
|
||||
"noImageSell": "No selling generated content",
|
||||
"noRentCivit": "No Civitai generation",
|
||||
"noRent": "No generation services",
|
||||
"noSell": "No selling models",
|
||||
"creditRequired": "Crédito del creador requerido",
|
||||
"noDerivatives": "No se permiten fusiones",
|
||||
"noReLicense": "Se requieren mismos permisos",
|
||||
"restrictionsLabel": "Restricciones de licencia"
|
||||
},
|
||||
"loading": {
|
||||
"exampleImages": "Cargando imágenes de ejemplo...",
|
||||
"description": "Cargando descripción del modelo...",
|
||||
"recipes": "Cargando recetas...",
|
||||
"examples": "Cargando ejemplos..."
|
||||
"examples": "Cargando ejemplos...",
|
||||
"versions": "Cargando versiones..."
|
||||
},
|
||||
"versions": {
|
||||
"heading": "Versiones del modelo",
|
||||
"copy": "Administra todas las versiones de este modelo en un solo lugar.",
|
||||
"media": {
|
||||
"placeholder": "Sin vista previa"
|
||||
},
|
||||
"labels": {
|
||||
"unnamed": "Versión sin nombre",
|
||||
"noDetails": "Sin detalles adicionales"
|
||||
},
|
||||
"badges": {
|
||||
"current": "Versión actual",
|
||||
"inLibrary": "En la biblioteca",
|
||||
"newer": "Versión más reciente",
|
||||
"ignored": "Ignorada"
|
||||
},
|
||||
"actions": {
|
||||
"download": "Descargar",
|
||||
"delete": "Eliminar",
|
||||
"ignore": "Ignorar",
|
||||
"unignore": "Dejar de ignorar",
|
||||
"resumeModelUpdates": "Reanudar actualizaciones para este modelo",
|
||||
"ignoreModelUpdates": "Ignorar actualizaciones para este modelo",
|
||||
"viewLocalVersions": "Ver todas las versiones locales",
|
||||
"viewLocalTooltip": "Disponible pronto"
|
||||
},
|
||||
"filters": {
|
||||
"label": "Filtro base",
|
||||
"state": {
|
||||
"showAll": "Todas las versiones",
|
||||
"showSameBase": "Mismo modelo base"
|
||||
},
|
||||
"tooltip": {
|
||||
"showAllVersions": "Cambiar para mostrar todas las versiones",
|
||||
"showSameBaseVersions": "Cambiar para mostrar solo versiones del mismo modelo base"
|
||||
},
|
||||
"empty": "Ninguna versión coincide con el filtro del modelo base actual."
|
||||
},
|
||||
"empty": "Aún no hay historial de versiones para este modelo.",
|
||||
"error": "No se pudieron cargar las versiones.",
|
||||
"missingModelId": "Este modelo no tiene un ID de modelo de Civitai.",
|
||||
"confirm": {
|
||||
"delete": "¿Eliminar esta versión de tu biblioteca?"
|
||||
},
|
||||
"toast": {
|
||||
"modelIgnored": "Se ignoran las actualizaciones de este modelo",
|
||||
"modelResumed": "Seguimiento de actualizaciones reanudado",
|
||||
"versionIgnored": "Se ignoran las actualizaciones de esta versión",
|
||||
"versionUnignored": "Versión habilitada nuevamente",
|
||||
"versionDeleted": "Versión eliminada"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -893,7 +1166,9 @@
|
||||
"loraFailedToSend": "Error al enviar LoRA al flujo de trabajo",
|
||||
"recipeAdded": "Receta añadida al flujo de trabajo",
|
||||
"recipeReplaced": "Receta reemplazada en el flujo de trabajo",
|
||||
"recipeFailedToSend": "Error al enviar receta al flujo de trabajo"
|
||||
"recipeFailedToSend": "Error al enviar receta al flujo de trabajo",
|
||||
"noMatchingNodes": "No hay nodos compatibles disponibles en el flujo de trabajo actual",
|
||||
"noTargetNodeSelected": "No se ha seleccionado ningún nodo de destino"
|
||||
},
|
||||
"nodeSelector": {
|
||||
"recipe": "Receta",
|
||||
@@ -906,7 +1181,11 @@
|
||||
"exampleImages": {
|
||||
"opened": "Carpeta de imágenes de ejemplo abierta",
|
||||
"openingFolder": "Abriendo carpeta de imágenes de ejemplo",
|
||||
"failedToOpen": "Error al abrir carpeta de imágenes de ejemplo"
|
||||
"failedToOpen": "Error al abrir carpeta de imágenes de ejemplo",
|
||||
"setupRequired": "Almacenamiento de imágenes de ejemplo",
|
||||
"setupDescription": "Para agregar imágenes de ejemplo personalizadas, primero necesita establecer una ubicación de descarga.",
|
||||
"setupUsage": "Esta ruta se utiliza tanto para imágenes de ejemplo descargadas como personalizadas.",
|
||||
"openSettings": "Abrir configuración"
|
||||
}
|
||||
},
|
||||
"help": {
|
||||
@@ -938,6 +1217,11 @@
|
||||
},
|
||||
"update": {
|
||||
"title": "Comprobar actualizaciones",
|
||||
"notificationsTitle": "Centro de notificaciones",
|
||||
"tabs": {
|
||||
"updates": "Actualizaciones",
|
||||
"messages": "Mensajes"
|
||||
},
|
||||
"updateAvailable": "Actualización disponible",
|
||||
"noChangelogAvailable": "No hay registro de cambios detallado disponible. Revisa GitHub para más información.",
|
||||
"currentVersion": "Versión actual",
|
||||
@@ -950,6 +1234,7 @@
|
||||
"checkingUpdates": "Comprobando actualizaciones...",
|
||||
"checkingMessage": "Por favor espera mientras comprobamos la última versión.",
|
||||
"showNotifications": "Mostrar notificaciones de actualización",
|
||||
"latestBadge": "Último",
|
||||
"updateProgress": {
|
||||
"preparing": "Preparando actualización...",
|
||||
"installing": "Instalando actualización...",
|
||||
@@ -969,6 +1254,13 @@
|
||||
"nightly": {
|
||||
"warning": "Advertencia: Las compilaciones nocturnas pueden contener características experimentales y podrían ser inestables.",
|
||||
"enable": "Habilitar actualizaciones nocturnas"
|
||||
},
|
||||
"banners": {
|
||||
"recent": "Notificaciones recientes",
|
||||
"empty": "No hay banners recientes.",
|
||||
"shown": "Mostrado {time}",
|
||||
"dismissed": "Descartado {time}",
|
||||
"active": "Activo"
|
||||
}
|
||||
},
|
||||
"support": {
|
||||
@@ -1048,6 +1340,9 @@
|
||||
"cannotSend": "No se puede enviar receta: Falta ID de receta",
|
||||
"sendFailed": "Error al enviar receta al flujo de trabajo",
|
||||
"sendError": "Error enviando receta al flujo de trabajo",
|
||||
"missingCheckpointPath": "Ruta del checkpoint no disponible",
|
||||
"missingCheckpointInfo": "Falta información del checkpoint",
|
||||
"downloadCheckpointFailed": "Error al descargar el checkpoint: {message}",
|
||||
"cannotDelete": "No se puede eliminar receta: Falta ID de receta",
|
||||
"deleteConfirmationError": "Error mostrando confirmación de eliminación",
|
||||
"deletedSuccessfully": "Receta eliminada exitosamente",
|
||||
@@ -1084,6 +1379,16 @@
|
||||
"bulkBaseModelUpdateSuccess": "Modelo base actualizado exitosamente para {count} modelo(s)",
|
||||
"bulkBaseModelUpdatePartial": "Actualizados {success} modelo(s), fallaron {failed} modelo(s)",
|
||||
"bulkBaseModelUpdateFailed": "Error al actualizar el modelo base para los modelos seleccionados",
|
||||
"bulkContentRatingUpdating": "Actualizando la clasificación de contenido para {count} modelo(s)...",
|
||||
"bulkContentRatingSet": "Clasificación de contenido establecida en {level} para {count} modelo(s)",
|
||||
"bulkContentRatingPartial": "Clasificación de contenido establecida en {level} para {success} modelo(s), {failed} fallaron",
|
||||
"bulkContentRatingFailed": "No se pudo actualizar la clasificación de contenido para los modelos seleccionados",
|
||||
"bulkUpdatesChecking": "Comprobando actualizaciones para {type} seleccionados...",
|
||||
"bulkUpdatesSuccess": "Actualizaciones disponibles para {count} {type} seleccionados",
|
||||
"bulkUpdatesNone": "No se encontraron actualizaciones para los {type} seleccionados",
|
||||
"bulkUpdatesMissing": "Los {type} seleccionados no están vinculados a actualizaciones de Civitai",
|
||||
"bulkUpdatesPartialMissing": "Se omitieron {missing} {type} seleccionados sin enlace de Civitai",
|
||||
"bulkUpdatesFailed": "Error al comprobar actualizaciones para los {type} seleccionados: {message}",
|
||||
"invalidCharactersRemoved": "Caracteres inválidos eliminados del nombre de archivo",
|
||||
"filenameCannotBeEmpty": "El nombre de archivo no puede estar vacío",
|
||||
"renameFailed": "Error al renombrar archivo: {message}",
|
||||
@@ -1095,6 +1400,7 @@
|
||||
"verificationCompleteSuccess": "Verificación completa. Todos los archivos son confirmados duplicados.",
|
||||
"verificationFailed": "Error al verificar hashes: {message}",
|
||||
"noTagsToAdd": "No hay etiquetas para añadir",
|
||||
"bulkTagsUpdating": "Actualizando etiquetas para {count} modelo(s)...",
|
||||
"tagsAddedSuccessfully": "Se añadieron exitosamente {tagCount} etiqueta(s) a {count} {type}(s)",
|
||||
"tagsReplacedSuccessfully": "Se reemplazaron exitosamente las etiquetas de {count} {type}(s) con {tagCount} etiqueta(s)",
|
||||
"tagsAddFailed": "Error al añadir etiquetas a {count} modelo(s)",
|
||||
@@ -1108,6 +1414,7 @@
|
||||
"settings": {
|
||||
"loraRootsFailed": "Error al cargar raíces de LoRA: {message}",
|
||||
"checkpointRootsFailed": "Error al cargar raíces de checkpoint: {message}",
|
||||
"unetRootsFailed": "Error al cargar raíces de Diffusion Model: {message}",
|
||||
"embeddingRootsFailed": "Error al cargar raíces de embedding: {message}",
|
||||
"mappingsUpdated": "Mapeos de rutas de modelo base actualizados ({count} mapeo{plural})",
|
||||
"mappingsCleared": "Mapeos de rutas de modelo base limpiados",
|
||||
@@ -1118,6 +1425,8 @@
|
||||
"compactModeToggled": "Modo compacto {state}",
|
||||
"settingSaveFailed": "Error al guardar configuración: {message}",
|
||||
"displayDensitySet": "Densidad de visualización establecida a {density}",
|
||||
"libraryLoadFailed": "Failed to load libraries: {message}",
|
||||
"libraryActivateFailed": "Failed to activate library: {message}",
|
||||
"languageChangeFailed": "Error al cambiar idioma: {message}",
|
||||
"cacheCleared": "Archivos de caché limpiados exitosamente. La caché se reconstruirá en la próxima acción.",
|
||||
"cacheClearFailed": "Error al limpiar caché: {error}",
|
||||
@@ -1126,7 +1435,26 @@
|
||||
"filters": {
|
||||
"applied": "{message}",
|
||||
"cleared": "Filtros limpiados",
|
||||
"noCustomFilterToClear": "No hay filtro personalizado para limpiar"
|
||||
"noCustomFilterToClear": "No hay filtro personalizado para limpiar",
|
||||
"noActiveFilters": "No hay filtros activos para guardar"
|
||||
},
|
||||
"presets": {
|
||||
"created": "Preajuste \"{name}\" creado",
|
||||
"deleted": "Preajuste \"{name}\" eliminado",
|
||||
"applied": "Preajuste \"{name}\" aplicado",
|
||||
"overwritten": "Preset \"{name}\" sobrescrito",
|
||||
"restored": "Presets predeterminados restaurados"
|
||||
},
|
||||
"error": {
|
||||
"presetNameEmpty": "El nombre del preajuste no puede estar vacío",
|
||||
"presetNameTooLong": "El nombre del preajuste debe tener {max} caracteres o menos",
|
||||
"presetNameInvalidChars": "El nombre del preajuste contiene caracteres inválidos",
|
||||
"presetNameExists": "Ya existe un preajuste con este nombre",
|
||||
"maxPresetsReached": "Máximo {max} preajustes permitidos. Elimine uno para agregar más.",
|
||||
"presetNotFound": "Preajuste no encontrado",
|
||||
"invalidPreset": "Datos de preajuste inválidos",
|
||||
"deletePresetFailed": "Error al eliminar el preajuste",
|
||||
"applyPresetFailed": "Error al aplicar el preajuste"
|
||||
},
|
||||
"downloads": {
|
||||
"imagesCompleted": "Imágenes de ejemplo {action} completadas",
|
||||
@@ -1142,7 +1470,7 @@
|
||||
},
|
||||
"triggerWords": {
|
||||
"loadFailed": "No se pudieron cargar palabras entrenadas",
|
||||
"tooLong": "La palabra clave no debe exceder 30 palabras",
|
||||
"tooLong": "La palabra clave no debe exceder 100 palabras",
|
||||
"tooMany": "Máximo 30 palabras clave permitidas",
|
||||
"alreadyExists": "Esta palabra clave ya existe",
|
||||
"updateSuccess": "Palabras clave actualizadas exitosamente",
|
||||
@@ -1191,6 +1519,8 @@
|
||||
"pauseFailed": "Error al pausar descarga: {error}",
|
||||
"downloadResumed": "Descarga reanudada",
|
||||
"resumeFailed": "Error al reanudar descarga: {error}",
|
||||
"downloadStopped": "Descarga cancelada",
|
||||
"stopFailed": "Error al cancelar descarga: {error}",
|
||||
"deleted": "Imagen de ejemplo eliminada",
|
||||
"deleteFailed": "Error al eliminar imagen de ejemplo",
|
||||
"setPreviewFailed": "Error al establecer imagen de vista previa"
|
||||
@@ -1211,6 +1541,8 @@
|
||||
"metadataRefreshed": "Metadatos actualizados exitosamente",
|
||||
"metadataRefreshFailed": "Error al actualizar metadatos: {message}",
|
||||
"metadataUpdateComplete": "Actualización de metadatos completada",
|
||||
"operationCancelled": "Operación cancelada por el usuario",
|
||||
"operationCancelledPartial": "Operación cancelada. {success} elementos procesados.",
|
||||
"metadataFetchFailed": "Error al obtener metadatos: {message}",
|
||||
"bulkMetadataCompleteAll": "Actualizados exitosamente todos los {count} {type}s",
|
||||
"bulkMetadataCompletePartial": "Actualizados {success} de {total} {type}s",
|
||||
@@ -1227,7 +1559,8 @@
|
||||
"bulkMoveFailures": "Movimientos fallidos:\n{failures}",
|
||||
"bulkMoveSuccess": "Movidos exitosamente {successCount} {type}s",
|
||||
"exampleImagesDownloadSuccess": "¡Imágenes de ejemplo descargadas exitosamente!",
|
||||
"exampleImagesDownloadFailed": "Error al descargar imágenes de ejemplo: {message}"
|
||||
"exampleImagesDownloadFailed": "Error al descargar imágenes de ejemplo: {message}",
|
||||
"moveFailed": "Failed to move item: {message}"
|
||||
}
|
||||
},
|
||||
"banners": {
|
||||
@@ -1237,6 +1570,26 @@
|
||||
"refreshNow": "Actualizar ahora",
|
||||
"refreshingIn": "Actualizando en",
|
||||
"seconds": "segundos"
|
||||
},
|
||||
"communitySupport": {
|
||||
"title": "Keep LoRA Manager Thriving with Your Support ❤️",
|
||||
"content": "LoRA Manager is a passion project maintained full-time by a solo developer. Your support on Ko-fi helps cover development costs, keeps new updates coming, and unlocks a license key for the LM Civitai Extension as a thank-you gift. Every contribution truly makes a difference.",
|
||||
"supportCta": "Support on Ko-fi",
|
||||
"learnMore": "LM Civitai Extension Tutorial"
|
||||
},
|
||||
"cacheHealth": {
|
||||
"corrupted": {
|
||||
"title": "Corrupción de caché detectada"
|
||||
},
|
||||
"degraded": {
|
||||
"title": "Problemas de caché detectados"
|
||||
},
|
||||
"content": "{invalid} de {total} entradas de caché son inválidas ({rate}). Esto puede causar modelos faltantes o errores. Se recomienda reconstruir la caché.",
|
||||
"rebuildCache": "Reconstruir caché",
|
||||
"dismiss": "Descartar",
|
||||
"rebuilding": "Reconstruyendo caché...",
|
||||
"rebuildFailed": "Error al reconstruir la caché: {error}",
|
||||
"retry": "Reintentar"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
415
locales/fr.json
415
locales/fr.json
@@ -10,7 +10,8 @@
|
||||
"next": "Suivant",
|
||||
"backToTop": "Retour en haut",
|
||||
"settings": "Paramètres",
|
||||
"help": "Aide"
|
||||
"help": "Aide",
|
||||
"add": "Ajouter"
|
||||
},
|
||||
"status": {
|
||||
"loading": "Chargement...",
|
||||
@@ -31,7 +32,8 @@
|
||||
"japanese": "日本語",
|
||||
"korean": "한국어",
|
||||
"french": "Français",
|
||||
"spanish": "Español"
|
||||
"spanish": "Español",
|
||||
"Hebrew": "עברית"
|
||||
},
|
||||
"fileSize": {
|
||||
"zero": "0 Octets",
|
||||
@@ -100,7 +102,12 @@
|
||||
"checkpointNameCopied": "Nom du checkpoint copié",
|
||||
"toggleBlur": "Basculer le flou",
|
||||
"show": "Afficher",
|
||||
"openExampleImages": "Ouvrir le dossier d'images d'exemple"
|
||||
"openExampleImages": "Ouvrir le dossier d'images d'exemple",
|
||||
"replacePreview": "Remplacer l'aperçu",
|
||||
"copyCheckpointName": "Copier le nom du checkpoint",
|
||||
"copyEmbeddingName": "Copier le nom de l'embedding",
|
||||
"sendCheckpointToWorkflow": "Envoyer vers ComfyUI",
|
||||
"sendEmbeddingToWorkflow": "Envoyer vers ComfyUI"
|
||||
},
|
||||
"nsfw": {
|
||||
"matureContent": "Contenu pour adultes",
|
||||
@@ -114,12 +121,20 @@
|
||||
"updateFailed": "Échec de la mise à jour du statut des favoris"
|
||||
},
|
||||
"sendToWorkflow": {
|
||||
"checkpointNotImplemented": "Envoyer le checkpoint vers le workflow - fonctionnalité à implémenter"
|
||||
"checkpointNotImplemented": "Envoyer le checkpoint vers le workflow - fonctionnalité à implémenter",
|
||||
"missingPath": "Impossible de déterminer le chemin du modèle pour cette carte"
|
||||
},
|
||||
"exampleImages": {
|
||||
"checkError": "Erreur lors de la vérification des images d'exemple",
|
||||
"missingHash": "Informations de hachage du modèle manquantes.",
|
||||
"noRemoteImagesAvailable": "Aucune image d'exemple distante disponible pour ce modèle sur Civitai"
|
||||
},
|
||||
"badges": {
|
||||
"update": "Mise à jour",
|
||||
"updateAvailable": "Mise à jour disponible"
|
||||
},
|
||||
"usage": {
|
||||
"timesUsed": "Nombre d'utilisations"
|
||||
}
|
||||
},
|
||||
"globalContextMenu": {
|
||||
@@ -128,12 +143,33 @@
|
||||
"missingPath": "Définissez un emplacement de téléchargement avant de télécharger les images d'exemple.",
|
||||
"unavailable": "Le téléchargement des images d'exemple n'est pas encore disponible. Réessayez après le chargement complet de la page."
|
||||
},
|
||||
"checkModelUpdates": {
|
||||
"label": "Vérifier les mises à jour",
|
||||
"loading": "Recherche de mises à jour pour {type}...",
|
||||
"success": "{count} mise(s) à jour trouvée(s) pour {type}",
|
||||
"none": "Tous les {type} sont à jour",
|
||||
"error": "Échec de la vérification des mises à jour pour {type} : {message}"
|
||||
},
|
||||
"cleanupExampleImages": {
|
||||
"label": "Nettoyer les dossiers d'images d'exemple",
|
||||
"label": "Supprimer les dossiers d'exemples orphelins",
|
||||
"success": "{count} dossier(s) déplacé(s) vers le dossier supprimé",
|
||||
"none": "Aucun dossier d'images d'exemple à nettoyer",
|
||||
"partial": "Nettoyage terminé avec {failures} dossier(s) ignoré(s)",
|
||||
"error": "Échec du nettoyage des dossiers d'images d'exemple : {message}"
|
||||
},
|
||||
"fetchMissingLicenses": {
|
||||
"label": "Refresh license metadata",
|
||||
"loading": "Refreshing license metadata for {typePlural}...",
|
||||
"success": "Updated license metadata for {count} {typePlural}",
|
||||
"none": "All {typePlural} already have license metadata",
|
||||
"error": "Failed to refresh license metadata for {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Réparer les données de recettes",
|
||||
"loading": "Réparation des données de recettes...",
|
||||
"success": "{count} recettes réparées avec succès.",
|
||||
"cancelled": "Réparation annulée. {count} recettes ont été réparées.",
|
||||
"error": "Échec de la réparation des recettes : {message}"
|
||||
}
|
||||
},
|
||||
"header": {
|
||||
@@ -163,14 +199,35 @@
|
||||
"creator": "Créateur",
|
||||
"title": "Titre de la recipe",
|
||||
"loraName": "Nom de fichier LoRA",
|
||||
"loraModel": "Nom du modèle LoRA"
|
||||
"loraModel": "Nom du modèle LoRA",
|
||||
"prompt": "Prompt"
|
||||
}
|
||||
},
|
||||
"filter": {
|
||||
"title": "Filtrer les modèles",
|
||||
"presets": "Préréglages",
|
||||
"savePreset": "Enregistrer les filtres actifs comme nouveau préréglage.",
|
||||
"savePresetDisabledActive": "Impossible d'enregistrer : Un préréglage est déjà actif. Modifiez les filtres pour enregistrer un nouveau préréglage",
|
||||
"savePresetDisabledNoFilters": "Sélectionnez d'abord des filtres à enregistrer comme préréglage",
|
||||
"savePresetPrompt": "Entrez le nom du préréglage :",
|
||||
"presetClickTooltip": "Cliquer pour appliquer le préréglage \"{name}\"",
|
||||
"presetDeleteTooltip": "Supprimer le préréglage",
|
||||
"presetDeleteConfirm": "Supprimer le préréglage \"{name}\" ?",
|
||||
"presetDeleteConfirmClick": "Cliquez à nouveau pour confirmer",
|
||||
"presetOverwriteConfirm": "Le préréglage \"{name}\" existe déjà. Remplacer?",
|
||||
"presetNamePlaceholder": "Nom du préréglage...",
|
||||
"baseModel": "Modèle de base",
|
||||
"modelTags": "Tags (Top 20)",
|
||||
"clearAll": "Effacer tous les filtres"
|
||||
"modelTypes": "Model Types",
|
||||
"license": "Licence",
|
||||
"noCreditRequired": "Crédit non requis",
|
||||
"allowSellingGeneratedContent": "Vente autorisée",
|
||||
"noTags": "Aucun tag",
|
||||
"clearAll": "Effacer tous les filtres",
|
||||
"any": "N'importe quel",
|
||||
"all": "Tous",
|
||||
"tagLogicAny": "Correspondre à n'importe quel tag (OU)",
|
||||
"tagLogicAll": "Correspondre à tous les tags (ET)"
|
||||
},
|
||||
"theme": {
|
||||
"toggle": "Basculer le thème",
|
||||
@@ -180,6 +237,7 @@
|
||||
},
|
||||
"actions": {
|
||||
"checkUpdates": "Vérifier les mises à jour",
|
||||
"notifications": "Notifications",
|
||||
"support": "Support"
|
||||
}
|
||||
},
|
||||
@@ -187,17 +245,33 @@
|
||||
"civitaiApiKey": "Clé API Civitai",
|
||||
"civitaiApiKeyPlaceholder": "Entrez votre clé API Civitai",
|
||||
"civitaiApiKeyHelp": "Utilisée pour l'authentification lors du téléchargement de modèles depuis Civitai",
|
||||
"openSettingsFileLocation": {
|
||||
"label": "Ouvrir le dossier des paramètres",
|
||||
"tooltip": "Ouvrir le dossier contenant settings.json",
|
||||
"success": "Dossier settings.json ouvert",
|
||||
"failed": "Impossible d'ouvrir le dossier settings.json",
|
||||
"copied": "Chemin des paramètres copié dans le presse-papiers: {{path}}",
|
||||
"clipboardFallback": "Chemin des paramètres: {{path}}"
|
||||
},
|
||||
"sections": {
|
||||
"contentFiltering": "Filtrage du contenu",
|
||||
"videoSettings": "Paramètres vidéo",
|
||||
"layoutSettings": "Paramètres d'affichage",
|
||||
"folderSettings": "Paramètres des dossiers",
|
||||
"priorityTags": "Étiquettes prioritaires",
|
||||
"downloadPathTemplates": "Modèles de chemin de téléchargement",
|
||||
"exampleImages": "Images d'exemple",
|
||||
"updateFlags": "Indicateurs de mise à jour",
|
||||
"autoOrganize": "Auto-organize",
|
||||
"misc": "Divers",
|
||||
"metadataArchive": "Base de données d'archive des métadonnées",
|
||||
"storageLocation": "Emplacement des paramètres",
|
||||
"proxySettings": "Paramètres du proxy"
|
||||
},
|
||||
"storage": {
|
||||
"locationLabel": "Mode portable",
|
||||
"locationHelp": "Activez pour garder settings.json dans le dépôt ; désactivez pour le placer dans votre dossier de configuration utilisateur."
|
||||
},
|
||||
"contentFiltering": {
|
||||
"blurNsfwContent": "Flouter le contenu NSFW",
|
||||
"blurNsfwContentHelp": "Flouter les images d'aperçu de contenu pour adultes (NSFW)",
|
||||
@@ -208,6 +282,15 @@
|
||||
"autoplayOnHover": "Lecture automatique vidéo au survol",
|
||||
"autoplayOnHoverHelp": "Lire les aperçus vidéo uniquement lors du survol"
|
||||
},
|
||||
"autoOrganizeExclusions": {
|
||||
"label": "Exclusions de l'auto-organisation",
|
||||
"placeholder": "Exemple : curated/*, */backups/*; *_temp.safetensors",
|
||||
"help": "Ignorer les fichiers correspondant à ces motifs génériques. Séparez plusieurs motifs par des virgules ou des points-virgules.",
|
||||
"validation": {
|
||||
"noPatterns": "Entrez au moins un motif séparé par des virgules ou des points-virgules.",
|
||||
"saveFailed": "Impossible d'enregistrer les exclusions : {message}"
|
||||
}
|
||||
},
|
||||
"layoutSettings": {
|
||||
"displayDensity": "Densité d'affichage",
|
||||
"displayDensityOptions": {
|
||||
@@ -217,31 +300,67 @@
|
||||
},
|
||||
"displayDensityHelp": "Choisissez combien de cartes afficher par ligne :",
|
||||
"displayDensityDetails": {
|
||||
"default": "Par défaut : 5 (1080p), 6 (2K), 8 (4K)",
|
||||
"medium": "Moyen : 6 (1080p), 7 (2K), 9 (4K)",
|
||||
"compact": "Compact : 7 (1080p), 8 (2K), 10 (4K)"
|
||||
"default": "5 (1080p), 6 (2K), 8 (4K)",
|
||||
"medium": "6 (1080p), 7 (2K), 9 (4K)",
|
||||
"compact": "7 (1080p), 8 (2K), 10 (4K)"
|
||||
},
|
||||
"displayDensityWarning": "Attention : Des densités plus élevées peuvent causer des problèmes de performance sur les systèmes avec des ressources limitées.",
|
||||
"showFolderSidebar": "Afficher la barre latérale des dossiers",
|
||||
"showFolderSidebarHelp": "Activez ou désactivez la barre latérale de navigation des dossiers sur les pages de modèles. Lorsqu'elle est désactivée, la barre latérale et la zone de survol restent masquées.",
|
||||
"cardInfoDisplay": "Affichage des informations de carte",
|
||||
"cardInfoDisplayOptions": {
|
||||
"always": "Toujours visible",
|
||||
"hover": "Révéler au survol"
|
||||
},
|
||||
"cardInfoDisplayHelp": "Choisissez quand afficher les informations du modèle et les boutons d'action :",
|
||||
"cardInfoDisplayDetails": {
|
||||
"always": "Toujours visible : Les en-têtes et pieds de page sont toujours visibles",
|
||||
"hover": "Révéler au survol : Les en-têtes et pieds de page n'apparaissent qu'au survol d'une carte"
|
||||
}
|
||||
"cardInfoDisplayHelp": "Choisissez quand afficher les informations du modèle et les boutons d'action",
|
||||
"modelCardFooterAction": "Action du bouton de carte de modèle",
|
||||
"modelCardFooterActionOptions": {
|
||||
"exampleImages": "Ouvrir les images d'exemple",
|
||||
"replacePreview": "Remplacer l'aperçu"
|
||||
},
|
||||
"modelCardFooterActionHelp": "Choisissez ce que fait le bouton en bas à droite de la carte",
|
||||
"modelNameDisplay": "Affichage du nom du modèle",
|
||||
"modelNameDisplayOptions": {
|
||||
"modelName": "Nom du modèle",
|
||||
"fileName": "Nom du fichier"
|
||||
},
|
||||
"modelNameDisplayHelp": "Choisissez ce qui doit être affiché dans le pied de page de la carte du modèle"
|
||||
},
|
||||
"folderSettings": {
|
||||
"activeLibrary": "Bibliothèque active",
|
||||
"activeLibraryHelp": "Basculer entre les bibliothèques configurées pour mettre à jour les dossiers par défaut. Changer la sélection recharge la page.",
|
||||
"loadingLibraries": "Chargement des bibliothèques...",
|
||||
"noLibraries": "Aucune bibliothèque configurée",
|
||||
"defaultLoraRoot": "Racine LoRA par défaut",
|
||||
"defaultLoraRootHelp": "Définir le répertoire racine LoRA par défaut pour les téléchargements, imports et déplacements",
|
||||
"defaultCheckpointRoot": "Racine Checkpoint par défaut",
|
||||
"defaultCheckpointRootHelp": "Définir le répertoire racine checkpoint par défaut pour les téléchargements, imports et déplacements",
|
||||
"defaultUnetRoot": "Racine Diffusion Model par défaut",
|
||||
"defaultUnetRootHelp": "Définir le répertoire racine Diffusion Model (UNET) par défaut pour les téléchargements, imports et déplacements",
|
||||
"defaultEmbeddingRoot": "Racine Embedding par défaut",
|
||||
"defaultEmbeddingRootHelp": "Définir le répertoire racine embedding par défaut pour les téléchargements, imports et déplacements",
|
||||
"noDefault": "Aucun par défaut"
|
||||
},
|
||||
"priorityTags": {
|
||||
"title": "Étiquettes prioritaires",
|
||||
"description": "Personnalisez l'ordre de priorité des étiquettes pour chaque type de modèle (par ex. : character, concept, style(toon|toon_style))",
|
||||
"placeholder": "character, concept, style(toon|toon_style)",
|
||||
"helpLinkLabel": "Ouvrir l'aide sur les étiquettes prioritaires",
|
||||
"modelTypes": {
|
||||
"lora": "LoRA",
|
||||
"checkpoint": "Checkpoint",
|
||||
"embedding": "Embedding"
|
||||
},
|
||||
"saveSuccess": "Étiquettes prioritaires mises à jour.",
|
||||
"saveError": "Échec de la mise à jour des étiquettes prioritaires.",
|
||||
"loadingSuggestions": "Chargement des suggestions...",
|
||||
"validation": {
|
||||
"missingClosingParen": "L'entrée {index} n'a pas de parenthèse fermante.",
|
||||
"missingCanonical": "L'entrée {index} doit inclure un nom d'étiquette canonique.",
|
||||
"duplicateCanonical": "L'étiquette canonique \"{tag}\" apparaît plusieurs fois.",
|
||||
"unknown": "Configuration d'étiquettes prioritaires invalide."
|
||||
}
|
||||
},
|
||||
"downloadPathTemplates": {
|
||||
"title": "Modèles de chemin de téléchargement",
|
||||
"help": "Configurer les structures de dossiers pour différents types de modèles lors du téléchargement depuis Civitai.",
|
||||
@@ -289,6 +408,14 @@
|
||||
"download": "Télécharger",
|
||||
"restartRequired": "Redémarrage requis"
|
||||
},
|
||||
"updateFlagStrategy": {
|
||||
"label": "Stratégie des indicateurs de mise à jour",
|
||||
"help": "Choisissez si les badges de mise à jour doivent apparaître uniquement lorsqu’une nouvelle version partage le même modèle de base que vos fichiers locaux, ou dès qu’il existe une version plus récente pour ce modèle.",
|
||||
"options": {
|
||||
"sameBase": "Faire correspondre les mises à jour par modèle de base",
|
||||
"any": "Signaler n’importe quelle mise à jour disponible"
|
||||
}
|
||||
},
|
||||
"misc": {
|
||||
"includeTriggerWords": "Inclure les mots-clés dans la syntaxe LoRA",
|
||||
"includeTriggerWordsHelp": "Inclure les mots-clés d'entraînement lors de la copie de la syntaxe LoRA dans le presse-papiers"
|
||||
@@ -348,12 +475,17 @@
|
||||
"dateAsc": "Plus ancien",
|
||||
"size": "Taille du fichier",
|
||||
"sizeDesc": "Plus grand",
|
||||
"sizeAsc": "Plus petit"
|
||||
"sizeAsc": "Plus petit",
|
||||
"usage": "Nombre d'utilisations",
|
||||
"usageDesc": "Plus",
|
||||
"usageAsc": "Moins"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "Actualiser la liste des modèles",
|
||||
"quick": "Actualisation rapide (incrémentale)",
|
||||
"full": "Reconstruction complète"
|
||||
"quick": "Synchroniser les changements",
|
||||
"quickTooltip": "Analyse les nouveaux fichiers de modèle ou les fichiers manquants pour garder la liste à jour.",
|
||||
"full": "Reconstruire le cache",
|
||||
"fullTooltip": "Recharge tous les détails des modèles depuis les fichiers metadata — à utiliser si la bibliothèque paraît obsolète ou après des modifications manuelles."
|
||||
},
|
||||
"fetch": {
|
||||
"title": "Récupérer les métadonnées depuis Civitai",
|
||||
@@ -374,6 +506,13 @@
|
||||
"favorites": {
|
||||
"title": "Afficher uniquement les favoris",
|
||||
"action": "Favoris"
|
||||
},
|
||||
"updates": {
|
||||
"title": "Afficher uniquement les modèles avec des mises à jour disponibles",
|
||||
"action": "Mises à jour",
|
||||
"menuLabel": "Afficher les options de mise à jour",
|
||||
"check": "Rechercher des mises à jour",
|
||||
"checkTooltip": "La vérification peut prendre du temps."
|
||||
}
|
||||
},
|
||||
"bulkOperations": {
|
||||
@@ -382,8 +521,10 @@
|
||||
"viewSelected": "Voir la sélection",
|
||||
"addTags": "Ajouter des tags à tous",
|
||||
"setBaseModel": "Définir le modèle de base pour tous",
|
||||
"setContentRating": "Définir la classification du contenu pour tous",
|
||||
"copyAll": "Copier toute la syntaxe",
|
||||
"refreshAll": "Actualiser toutes les métadonnées",
|
||||
"checkUpdates": "Vérifier les mises à jour pour la sélection",
|
||||
"moveAll": "Déplacer tout vers un dossier",
|
||||
"autoOrganize": "Auto-organiser la sélection",
|
||||
"deleteAll": "Supprimer tous les modèles",
|
||||
@@ -400,6 +541,7 @@
|
||||
},
|
||||
"contextMenu": {
|
||||
"refreshMetadata": "Actualiser les données Civitai",
|
||||
"checkUpdates": "Vérifier les mises à jour",
|
||||
"relinkCivitai": "Relier à nouveau à Civitai",
|
||||
"copySyntax": "Copier la syntaxe LoRA",
|
||||
"copyFilename": "Copier le nom de fichier du modèle",
|
||||
@@ -411,6 +553,7 @@
|
||||
"replacePreview": "Remplacer l'aperçu",
|
||||
"setContentRating": "Définir la classification du contenu",
|
||||
"moveToFolder": "Déplacer vers un dossier",
|
||||
"repairMetadata": "Réparer les métadonnées",
|
||||
"excludeModel": "Exclure le modèle",
|
||||
"deleteModel": "Supprimer le modèle",
|
||||
"shareRecipe": "Partager la recipe",
|
||||
@@ -421,6 +564,9 @@
|
||||
},
|
||||
"recipes": {
|
||||
"title": "LoRA Recipes",
|
||||
"actions": {
|
||||
"sendCheckpoint": "Envoyer vers ComfyUI"
|
||||
},
|
||||
"controls": {
|
||||
"import": {
|
||||
"action": "Importer",
|
||||
@@ -478,10 +624,26 @@
|
||||
"selectLoraRoot": "Veuillez sélectionner un répertoire racine LoRA"
|
||||
}
|
||||
},
|
||||
"sort": {
|
||||
"title": "Trier les recettes par...",
|
||||
"name": "Nom",
|
||||
"nameAsc": "A - Z",
|
||||
"nameDesc": "Z - A",
|
||||
"date": "Date",
|
||||
"dateDesc": "Plus récent",
|
||||
"dateAsc": "Plus ancien",
|
||||
"lorasCount": "Nombre de LoRAs",
|
||||
"lorasCountDesc": "Plus",
|
||||
"lorasCountAsc": "Moins"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "Actualiser la liste des recipes"
|
||||
},
|
||||
"filteredByLora": "Filtré par LoRA"
|
||||
"filteredByLora": "Filtré par LoRA",
|
||||
"favorites": {
|
||||
"title": "Afficher uniquement les favoris",
|
||||
"action": "Favoris"
|
||||
}
|
||||
},
|
||||
"duplicates": {
|
||||
"found": "Trouvé {count} groupes de doublons",
|
||||
@@ -507,23 +669,44 @@
|
||||
"noMissingLoras": "Aucun LoRA manquant à télécharger",
|
||||
"getInfoFailed": "Échec de l'obtention des informations pour les LoRAs manquants",
|
||||
"prepareError": "Erreur lors de la préparation des LoRAs pour le téléchargement : {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "Réparation des métadonnées de la recette...",
|
||||
"success": "Métadonnées de la recette réparées avec succès",
|
||||
"skipped": "Recette déjà à la version la plus récente, aucune réparation nécessaire",
|
||||
"failed": "Échec de la réparation de la recette : {message}",
|
||||
"missingId": "Impossible de réparer la recette : ID de recette manquant"
|
||||
}
|
||||
}
|
||||
},
|
||||
"checkpoints": {
|
||||
"title": "Modèles Checkpoint"
|
||||
"title": "Modèles Checkpoint",
|
||||
"modelTypes": {
|
||||
"checkpoint": "Checkpoint",
|
||||
"diffusion_model": "Diffusion Model"
|
||||
},
|
||||
"contextMenu": {
|
||||
"moveToOtherTypeFolder": "Déplacer vers le dossier {otherType}"
|
||||
}
|
||||
},
|
||||
"embeddings": {
|
||||
"title": "Modèles Embedding"
|
||||
},
|
||||
"sidebar": {
|
||||
"modelRoot": "Racine du modèle",
|
||||
"modelRoot": "Racine",
|
||||
"collapseAll": "Réduire tous les dossiers",
|
||||
"pinSidebar": "Épingler la barre latérale",
|
||||
"unpinSidebar": "Désépingler la barre latérale",
|
||||
"switchToListView": "Passer en vue liste",
|
||||
"switchToTreeView": "Passer en vue arborescence",
|
||||
"collapseAllDisabled": "Non disponible en vue liste"
|
||||
"recursiveOn": "Rechercher dans les sous-dossiers",
|
||||
"recursiveOff": "Rechercher uniquement dans le dossier actuel",
|
||||
"recursiveUnavailable": "La recherche récursive n'est disponible qu'en vue arborescente",
|
||||
"collapseAllDisabled": "Non disponible en vue liste",
|
||||
"dragDrop": {
|
||||
"unableToResolveRoot": "Impossible de déterminer le chemin de destination pour le déplacement.",
|
||||
"moveUnsupported": "Move is not supported for this item."
|
||||
}
|
||||
},
|
||||
"statistics": {
|
||||
"title": "Statistiques",
|
||||
@@ -598,6 +781,14 @@
|
||||
"downloadedPreview": "Image d'aperçu téléchargée",
|
||||
"downloadingFile": "Téléchargement du fichier {type}",
|
||||
"finalizing": "Finalisation du téléchargement..."
|
||||
},
|
||||
"progress": {
|
||||
"currentFile": "Fichier actuel :",
|
||||
"downloading": "Téléchargement : {name}",
|
||||
"transferred": "Téléchargé : {downloaded} / {total}",
|
||||
"transferredSimple": "Téléchargé : {downloaded}",
|
||||
"transferredUnknown": "Téléchargé : --",
|
||||
"speed": "Vitesse : {speed}"
|
||||
}
|
||||
},
|
||||
"move": {
|
||||
@@ -606,6 +797,7 @@
|
||||
"contentRating": {
|
||||
"title": "Définir la classification du contenu",
|
||||
"current": "Actuel",
|
||||
"multiple": "Valeurs multiples",
|
||||
"levels": {
|
||||
"pg": "PG",
|
||||
"pg13": "PG13",
|
||||
@@ -644,6 +836,12 @@
|
||||
"countMessage": "modèles seront définitivement supprimés.",
|
||||
"action": "Tout supprimer"
|
||||
},
|
||||
"checkUpdates": {
|
||||
"title": "Vérifier les mises à jour pour tous les {typePlural} ?",
|
||||
"message": "Cette action vérifie les mises à jour pour tous les {typePlural} de votre bibliothèque. Les grandes collections peuvent prendre un peu plus de temps.",
|
||||
"tip": "Besoin de procéder par étapes ? Passez en mode lot, sélectionnez les modèles souhaités puis utilisez \"Vérifier les mises à jour pour la sélection\".",
|
||||
"action": "Tout vérifier"
|
||||
},
|
||||
"bulkAddTags": {
|
||||
"title": "Ajouter des tags à plusieurs modèles",
|
||||
"description": "Ajouter des tags à",
|
||||
@@ -717,7 +915,9 @@
|
||||
},
|
||||
"openFileLocation": {
|
||||
"success": "Emplacement du fichier ouvert avec succès",
|
||||
"failed": "Échec de l'ouverture de l'emplacement du fichier"
|
||||
"failed": "Échec de l'ouverture de l'emplacement du fichier",
|
||||
"copied": "Chemin copié dans le presse-papiers: {{path}}",
|
||||
"clipboardFallback": "Chemin: {{path}}"
|
||||
},
|
||||
"metadata": {
|
||||
"version": "Version",
|
||||
@@ -740,11 +940,13 @@
|
||||
"addPresetParameter": "Ajouter un paramètre prédéfini...",
|
||||
"strengthMin": "Force Min",
|
||||
"strengthMax": "Force Max",
|
||||
"strengthRange": "Gamme de force",
|
||||
"strength": "Force",
|
||||
"clipStrength": "Force Clip",
|
||||
"clipSkip": "Clip Skip",
|
||||
"valuePlaceholder": "Valeur",
|
||||
"add": "Ajouter"
|
||||
"add": "Ajouter",
|
||||
"invalidRange": "Format de plage invalide. Utilisez x.x-y.y"
|
||||
},
|
||||
"triggerWords": {
|
||||
"label": "Mots-clés",
|
||||
@@ -780,13 +982,84 @@
|
||||
"tabs": {
|
||||
"examples": "Exemples",
|
||||
"description": "Description du modèle",
|
||||
"recipes": "Recipes"
|
||||
"recipes": "Recipes",
|
||||
"versions": "Versions"
|
||||
},
|
||||
"navigation": {
|
||||
"label": "Navigation des modèles",
|
||||
"previousWithShortcut": "Modèle précédent (←)",
|
||||
"nextWithShortcut": "Modèle suivant (→)",
|
||||
"noPrevious": "Aucun modèle précédent",
|
||||
"noNext": "Aucun modèle suivant"
|
||||
},
|
||||
"license": {
|
||||
"noImageSell": "No selling generated content",
|
||||
"noRentCivit": "No Civitai generation",
|
||||
"noRent": "No generation services",
|
||||
"noSell": "No selling models",
|
||||
"creditRequired": "Crédit du créateur requis",
|
||||
"noDerivatives": "Pas de fusion de partage",
|
||||
"noReLicense": "Mêmes autorisations requises",
|
||||
"restrictionsLabel": "Restrictions de licence"
|
||||
},
|
||||
"loading": {
|
||||
"exampleImages": "Chargement des images d'exemple...",
|
||||
"description": "Chargement de la description du modèle...",
|
||||
"recipes": "Chargement des recipes...",
|
||||
"examples": "Chargement des exemples..."
|
||||
"examples": "Chargement des exemples...",
|
||||
"versions": "Chargement des versions..."
|
||||
},
|
||||
"versions": {
|
||||
"heading": "Versions du modèle",
|
||||
"copy": "Gérez toutes les versions de ce modèle en un seul endroit.",
|
||||
"media": {
|
||||
"placeholder": "Aucune prévisualisation"
|
||||
},
|
||||
"labels": {
|
||||
"unnamed": "Version sans nom",
|
||||
"noDetails": "Aucun détail supplémentaire"
|
||||
},
|
||||
"badges": {
|
||||
"current": "Version actuelle",
|
||||
"inLibrary": "Dans la bibliothèque",
|
||||
"newer": "Version plus récente",
|
||||
"ignored": "Ignorée"
|
||||
},
|
||||
"actions": {
|
||||
"download": "Télécharger",
|
||||
"delete": "Supprimer",
|
||||
"ignore": "Ignorer",
|
||||
"unignore": "Ne plus ignorer",
|
||||
"resumeModelUpdates": "Reprendre les mises à jour pour ce modèle",
|
||||
"ignoreModelUpdates": "Ignorer les mises à jour pour ce modèle",
|
||||
"viewLocalVersions": "Voir toutes les versions locales",
|
||||
"viewLocalTooltip": "Bientôt disponible"
|
||||
},
|
||||
"filters": {
|
||||
"label": "Filtre de base",
|
||||
"state": {
|
||||
"showAll": "Toutes les versions",
|
||||
"showSameBase": "Même modèle de base"
|
||||
},
|
||||
"tooltip": {
|
||||
"showAllVersions": "Passer à l'affichage de toutes les versions",
|
||||
"showSameBaseVersions": "Passer à l'affichage des versions du même modèle de base"
|
||||
},
|
||||
"empty": "Aucune version ne correspond au filtre du modèle de base actuel."
|
||||
},
|
||||
"empty": "Aucun historique de versions n'est disponible pour ce modèle pour le moment.",
|
||||
"error": "Échec du chargement des versions.",
|
||||
"missingModelId": "Ce modèle ne possède pas d'identifiant de modèle Civitai.",
|
||||
"confirm": {
|
||||
"delete": "Supprimer cette version de votre bibliothèque ?"
|
||||
},
|
||||
"toast": {
|
||||
"modelIgnored": "Les mises à jour de ce modèle sont ignorées",
|
||||
"modelResumed": "Suivi des mises à jour repris",
|
||||
"versionIgnored": "Les mises à jour de cette version sont ignorées",
|
||||
"versionUnignored": "Version réactivée",
|
||||
"versionDeleted": "Version supprimée"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -893,7 +1166,9 @@
|
||||
"loraFailedToSend": "Échec de l'envoi du LoRA au workflow",
|
||||
"recipeAdded": "Recipe ajoutée au workflow",
|
||||
"recipeReplaced": "Recipe remplacée dans le workflow",
|
||||
"recipeFailedToSend": "Échec de l'envoi de la recipe au workflow"
|
||||
"recipeFailedToSend": "Échec de l'envoi de la recipe au workflow",
|
||||
"noMatchingNodes": "Aucun nœud compatible disponible dans le workflow actuel",
|
||||
"noTargetNodeSelected": "Aucun nœud cible sélectionné"
|
||||
},
|
||||
"nodeSelector": {
|
||||
"recipe": "Recipe",
|
||||
@@ -906,7 +1181,11 @@
|
||||
"exampleImages": {
|
||||
"opened": "Dossier d'images d'exemple ouvert",
|
||||
"openingFolder": "Ouverture du dossier d'images d'exemple",
|
||||
"failedToOpen": "Échec de l'ouverture du dossier d'images d'exemple"
|
||||
"failedToOpen": "Échec de l'ouverture du dossier d'images d'exemple",
|
||||
"setupRequired": "Stockage d'images d'exemple",
|
||||
"setupDescription": "Pour ajouter des images d'exemple personnalisées, vous devez d'abord définir un emplacement de téléchargement.",
|
||||
"setupUsage": "Ce chemin est utilisé pour les images d'exemple téléchargées et personnalisées.",
|
||||
"openSettings": "Ouvrir les paramètres"
|
||||
}
|
||||
},
|
||||
"help": {
|
||||
@@ -938,6 +1217,11 @@
|
||||
},
|
||||
"update": {
|
||||
"title": "Vérifier les mises à jour",
|
||||
"notificationsTitle": "Notifications",
|
||||
"tabs": {
|
||||
"updates": "Mises à jour",
|
||||
"messages": "Messages"
|
||||
},
|
||||
"updateAvailable": "Mise à jour disponible",
|
||||
"noChangelogAvailable": "Aucun journal des modifications détaillé disponible. Consultez GitHub pour plus d'informations.",
|
||||
"currentVersion": "Version actuelle",
|
||||
@@ -950,6 +1234,7 @@
|
||||
"checkingUpdates": "Vérification des mises à jour...",
|
||||
"checkingMessage": "Veuillez patienter pendant la vérification de la dernière version.",
|
||||
"showNotifications": "Afficher les notifications de mise à jour",
|
||||
"latestBadge": "Dernier",
|
||||
"updateProgress": {
|
||||
"preparing": "Préparation de la mise à jour...",
|
||||
"installing": "Installation de la mise à jour...",
|
||||
@@ -969,6 +1254,13 @@
|
||||
"nightly": {
|
||||
"warning": "Attention : Les versions nightly peuvent contenir des fonctionnalités expérimentales et être instables.",
|
||||
"enable": "Activer les mises à jour nightly"
|
||||
},
|
||||
"banners": {
|
||||
"recent": "Messages récents",
|
||||
"empty": "Aucune bannière récente.",
|
||||
"shown": "Affiché {time}",
|
||||
"dismissed": "Ignoré {time}",
|
||||
"active": "Actif"
|
||||
}
|
||||
},
|
||||
"support": {
|
||||
@@ -1048,6 +1340,9 @@
|
||||
"cannotSend": "Impossible d'envoyer la recipe : ID de recipe manquant",
|
||||
"sendFailed": "Échec de l'envoi de la recipe vers le workflow",
|
||||
"sendError": "Erreur lors de l'envoi de la recipe vers le workflow",
|
||||
"missingCheckpointPath": "Chemin du checkpoint indisponible",
|
||||
"missingCheckpointInfo": "Informations sur le checkpoint manquantes",
|
||||
"downloadCheckpointFailed": "Échec du téléchargement du checkpoint : {message}",
|
||||
"cannotDelete": "Impossible de supprimer la recipe : ID de recipe manquant",
|
||||
"deleteConfirmationError": "Erreur lors de l'affichage de la confirmation de suppression",
|
||||
"deletedSuccessfully": "Recipe supprimée avec succès",
|
||||
@@ -1084,6 +1379,16 @@
|
||||
"bulkBaseModelUpdateSuccess": "Modèle de base mis à jour avec succès pour {count} modèle(s)",
|
||||
"bulkBaseModelUpdatePartial": "{success} modèle(s) mis à jour, {failed} modèle(s) en échec",
|
||||
"bulkBaseModelUpdateFailed": "Échec de la mise à jour du modèle de base pour les modèles sélectionnés",
|
||||
"bulkContentRatingUpdating": "Mise à jour de la classification du contenu pour {count} modèle(s)...",
|
||||
"bulkContentRatingSet": "Classification du contenu définie sur {level} pour {count} modèle(s)",
|
||||
"bulkContentRatingPartial": "Classification du contenu définie sur {level} pour {success} modèle(s), {failed} échec(s)",
|
||||
"bulkContentRatingFailed": "Impossible de mettre à jour la classification du contenu pour les modèles sélectionnés",
|
||||
"bulkUpdatesChecking": "Vérification des mises à jour pour les {type} sélectionnés...",
|
||||
"bulkUpdatesSuccess": "Mises à jour disponibles pour {count} {type} sélectionnés",
|
||||
"bulkUpdatesNone": "Aucune mise à jour trouvée pour les {type} sélectionnés",
|
||||
"bulkUpdatesMissing": "Les {type} sélectionnés ne sont pas liés aux mises à jour Civitai",
|
||||
"bulkUpdatesPartialMissing": "{missing} {type} sélectionnés sans lien Civitai ignorés",
|
||||
"bulkUpdatesFailed": "Échec de la vérification des mises à jour pour les {type} sélectionnés : {message}",
|
||||
"invalidCharactersRemoved": "Caractères invalides supprimés du nom de fichier",
|
||||
"filenameCannotBeEmpty": "Le nom de fichier ne peut pas être vide",
|
||||
"renameFailed": "Échec du renommage du fichier : {message}",
|
||||
@@ -1095,6 +1400,7 @@
|
||||
"verificationCompleteSuccess": "Vérification terminée. Tous les fichiers sont confirmés comme doublons.",
|
||||
"verificationFailed": "Échec de la vérification des hash : {message}",
|
||||
"noTagsToAdd": "Aucun tag à ajouter",
|
||||
"bulkTagsUpdating": "Mise à jour des tags pour {count} modèle(s)...",
|
||||
"tagsAddedSuccessfully": "{tagCount} tag(s) ajouté(s) avec succès à {count} {type}(s)",
|
||||
"tagsReplacedSuccessfully": "Tags remplacés avec succès pour {count} {type}(s) avec {tagCount} tag(s)",
|
||||
"tagsAddFailed": "Échec de l'ajout des tags à {count} modèle(s)",
|
||||
@@ -1108,6 +1414,7 @@
|
||||
"settings": {
|
||||
"loraRootsFailed": "Échec du chargement des racines LoRA : {message}",
|
||||
"checkpointRootsFailed": "Échec du chargement des racines checkpoint : {message}",
|
||||
"unetRootsFailed": "Échec du chargement des racines Diffusion Model : {message}",
|
||||
"embeddingRootsFailed": "Échec du chargement des racines embedding : {message}",
|
||||
"mappingsUpdated": "Mappages de chemin de modèle de base mis à jour ({count} mappage{plural})",
|
||||
"mappingsCleared": "Mappages de chemin de modèle de base effacés",
|
||||
@@ -1118,6 +1425,8 @@
|
||||
"compactModeToggled": "Mode compact {state}",
|
||||
"settingSaveFailed": "Échec de la sauvegarde du paramètre : {message}",
|
||||
"displayDensitySet": "Densité d'affichage définie sur {density}",
|
||||
"libraryLoadFailed": "Failed to load libraries: {message}",
|
||||
"libraryActivateFailed": "Failed to activate library: {message}",
|
||||
"languageChangeFailed": "Échec du changement de langue : {message}",
|
||||
"cacheCleared": "Les fichiers de cache ont été vidés avec succès. Le cache sera reconstruit à la prochaine action.",
|
||||
"cacheClearFailed": "Échec du vidage du cache : {error}",
|
||||
@@ -1126,7 +1435,26 @@
|
||||
"filters": {
|
||||
"applied": "{message}",
|
||||
"cleared": "Filtres effacés",
|
||||
"noCustomFilterToClear": "Aucun filtre personnalisé à effacer"
|
||||
"noCustomFilterToClear": "Aucun filtre personnalisé à effacer",
|
||||
"noActiveFilters": "Aucun filtre actif à enregistrer"
|
||||
},
|
||||
"presets": {
|
||||
"created": "Préréglage \"{name}\" créé",
|
||||
"deleted": "Préréglage \"{name}\" supprimé",
|
||||
"applied": "Préréglage \"{name}\" appliqué",
|
||||
"overwritten": "Préréglage \"{name}\" remplacé",
|
||||
"restored": "Paramètres par défaut restaurés"
|
||||
},
|
||||
"error": {
|
||||
"presetNameEmpty": "Le nom du préréglage ne peut pas être vide",
|
||||
"presetNameTooLong": "Le nom du préréglage doit contenir au maximum {max} caractères",
|
||||
"presetNameInvalidChars": "Le nom du préréglage contient des caractères invalides",
|
||||
"presetNameExists": "Un préréglage avec ce nom existe déjà",
|
||||
"maxPresetsReached": "Maximum {max} préréglages autorisés. Supprimez-en un pour en ajouter plus.",
|
||||
"presetNotFound": "Préréglage non trouvé",
|
||||
"invalidPreset": "Données de préréglage invalides",
|
||||
"deletePresetFailed": "Échec de la suppression du préréglage",
|
||||
"applyPresetFailed": "Échec de l'application du préréglage"
|
||||
},
|
||||
"downloads": {
|
||||
"imagesCompleted": "Images d'exemple {action} terminées",
|
||||
@@ -1142,7 +1470,7 @@
|
||||
},
|
||||
"triggerWords": {
|
||||
"loadFailed": "Impossible de charger les mots entraînés",
|
||||
"tooLong": "Le mot-clé ne doit pas dépasser 30 mots",
|
||||
"tooLong": "Le mot-clé ne doit pas dépasser 100 mots",
|
||||
"tooMany": "Maximum 30 mots-clés autorisés",
|
||||
"alreadyExists": "Ce mot-clé existe déjà",
|
||||
"updateSuccess": "Mots-clés mis à jour avec succès",
|
||||
@@ -1191,6 +1519,8 @@
|
||||
"pauseFailed": "Échec de la mise en pause du téléchargement : {error}",
|
||||
"downloadResumed": "Téléchargement repris",
|
||||
"resumeFailed": "Échec de la reprise du téléchargement : {error}",
|
||||
"downloadStopped": "Téléchargement annulé",
|
||||
"stopFailed": "Échec de l'annulation du téléchargement : {error}",
|
||||
"deleted": "Image d'exemple supprimée",
|
||||
"deleteFailed": "Échec de la suppression de l'image d'exemple",
|
||||
"setPreviewFailed": "Échec de la définition de l'image d'aperçu"
|
||||
@@ -1211,6 +1541,8 @@
|
||||
"metadataRefreshed": "Métadonnées actualisées avec succès",
|
||||
"metadataRefreshFailed": "Échec de l'actualisation des métadonnées : {message}",
|
||||
"metadataUpdateComplete": "Mise à jour des métadonnées terminée",
|
||||
"operationCancelled": "Opération annulée par l'utilisateur",
|
||||
"operationCancelledPartial": "Opération annulée. {success} éléments traités.",
|
||||
"metadataFetchFailed": "Échec de la récupération des métadonnées : {message}",
|
||||
"bulkMetadataCompleteAll": "Actualisation réussie de tous les {count} {type}s",
|
||||
"bulkMetadataCompletePartial": "{success} sur {total} {type}s actualisés",
|
||||
@@ -1227,7 +1559,8 @@
|
||||
"bulkMoveFailures": "Échecs de déplacement :\n{failures}",
|
||||
"bulkMoveSuccess": "{successCount} {type}s déplacés avec succès",
|
||||
"exampleImagesDownloadSuccess": "Images d'exemple téléchargées avec succès !",
|
||||
"exampleImagesDownloadFailed": "Échec du téléchargement des images d'exemple : {message}"
|
||||
"exampleImagesDownloadFailed": "Échec du téléchargement des images d'exemple : {message}",
|
||||
"moveFailed": "Failed to move item: {message}"
|
||||
}
|
||||
},
|
||||
"banners": {
|
||||
@@ -1237,6 +1570,26 @@
|
||||
"refreshNow": "Actualiser maintenant",
|
||||
"refreshingIn": "Actualisation dans",
|
||||
"seconds": "secondes"
|
||||
},
|
||||
"communitySupport": {
|
||||
"title": "Keep LoRA Manager Thriving with Your Support ❤️",
|
||||
"content": "LoRA Manager is a passion project maintained full-time by a solo developer. Your support on Ko-fi helps cover development costs, keeps new updates coming, and unlocks a license key for the LM Civitai Extension as a thank-you gift. Every contribution truly makes a difference.",
|
||||
"supportCta": "Support on Ko-fi",
|
||||
"learnMore": "LM Civitai Extension Tutorial"
|
||||
},
|
||||
"cacheHealth": {
|
||||
"corrupted": {
|
||||
"title": "Corruption du cache détectée"
|
||||
},
|
||||
"degraded": {
|
||||
"title": "Problèmes de cache détectés"
|
||||
},
|
||||
"content": "{invalid} des {total} entrées de cache sont invalides ({rate}). Cela peut provoquer des modèles manquants ou des erreurs. Il est recommandé de reconstruire le cache.",
|
||||
"rebuildCache": "Reconstruire le cache",
|
||||
"dismiss": "Ignorer",
|
||||
"rebuilding": "Reconstruction du cache...",
|
||||
"rebuildFailed": "Échec de la reconstruction du cache : {error}",
|
||||
"retry": "Réessayer"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
1595
locales/he.json
Normal file
1595
locales/he.json
Normal file
File diff suppressed because it is too large
Load Diff
415
locales/ja.json
415
locales/ja.json
@@ -10,7 +10,8 @@
|
||||
"next": "次へ",
|
||||
"backToTop": "トップに戻る",
|
||||
"settings": "設定",
|
||||
"help": "ヘルプ"
|
||||
"help": "ヘルプ",
|
||||
"add": "追加"
|
||||
},
|
||||
"status": {
|
||||
"loading": "読み込み中...",
|
||||
@@ -31,7 +32,8 @@
|
||||
"japanese": "日本語",
|
||||
"korean": "한국어",
|
||||
"french": "Français",
|
||||
"spanish": "Español"
|
||||
"spanish": "Español",
|
||||
"Hebrew": "עברית"
|
||||
},
|
||||
"fileSize": {
|
||||
"zero": "0バイト",
|
||||
@@ -100,7 +102,12 @@
|
||||
"checkpointNameCopied": "checkpointの名前をコピーしました",
|
||||
"toggleBlur": "ぼかしの切り替え",
|
||||
"show": "表示",
|
||||
"openExampleImages": "例画像フォルダを開く"
|
||||
"openExampleImages": "例画像フォルダを開く",
|
||||
"replacePreview": "プレビューを置換",
|
||||
"copyCheckpointName": "checkpoint名をコピー",
|
||||
"copyEmbeddingName": "embedding名をコピー",
|
||||
"sendCheckpointToWorkflow": "ComfyUIに送信",
|
||||
"sendEmbeddingToWorkflow": "ComfyUIに送信"
|
||||
},
|
||||
"nsfw": {
|
||||
"matureContent": "成人向けコンテンツ",
|
||||
@@ -114,12 +121,20 @@
|
||||
"updateFailed": "お気に入り状態の更新に失敗しました"
|
||||
},
|
||||
"sendToWorkflow": {
|
||||
"checkpointNotImplemented": "checkpointをワークフローに送信 - 実装予定の機能"
|
||||
"checkpointNotImplemented": "checkpointをワークフローに送信 - 実装予定の機能",
|
||||
"missingPath": "このカードのモデルパスを特定できません"
|
||||
},
|
||||
"exampleImages": {
|
||||
"checkError": "例画像の確認中にエラーが発生しました",
|
||||
"missingHash": "モデルハッシュ情報がありません。",
|
||||
"noRemoteImagesAvailable": "このモデルのCivitaiでのリモート例画像は利用できません"
|
||||
},
|
||||
"badges": {
|
||||
"update": "アップデート",
|
||||
"updateAvailable": "アップデートがあります"
|
||||
},
|
||||
"usage": {
|
||||
"timesUsed": "使用回数"
|
||||
}
|
||||
},
|
||||
"globalContextMenu": {
|
||||
@@ -128,12 +143,33 @@
|
||||
"missingPath": "例画像をダウンロードする前にダウンロード場所を設定してください。",
|
||||
"unavailable": "例画像のダウンロードはまだ利用できません。ページの読み込みが完了してから再度お試しください。"
|
||||
},
|
||||
"checkModelUpdates": {
|
||||
"label": "アップデートを確認",
|
||||
"loading": "{type} のアップデートを確認中…",
|
||||
"success": "{type} のアップデートが {count} 件見つかりました",
|
||||
"none": "すべての {type} は最新です",
|
||||
"error": "{type} のアップデート確認に失敗しました: {message}"
|
||||
},
|
||||
"cleanupExampleImages": {
|
||||
"label": "例画像フォルダをクリーンアップ",
|
||||
"success": "{count} 個のフォルダを削除フォルダに移動しました",
|
||||
"none": "クリーンアップが必要な例画像フォルダはありません",
|
||||
"partial": "クリーンアップが完了しましたが、{failures} 個のフォルダはスキップされました",
|
||||
"error": "例画像フォルダのクリーンアップに失敗しました:{message}"
|
||||
},
|
||||
"fetchMissingLicenses": {
|
||||
"label": "Refresh license metadata",
|
||||
"loading": "Refreshing license metadata for {typePlural}...",
|
||||
"success": "Updated license metadata for {count} {typePlural}",
|
||||
"none": "All {typePlural} already have license metadata",
|
||||
"error": "Failed to refresh license metadata for {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "レシピデータの修復",
|
||||
"loading": "レシピデータを修復中...",
|
||||
"success": "{count} 件のレシピを正常に修復しました。",
|
||||
"cancelled": "修復がキャンセルされました。{count}個のレシピが修復されました。",
|
||||
"error": "レシピの修復に失敗しました: {message}"
|
||||
}
|
||||
},
|
||||
"header": {
|
||||
@@ -163,14 +199,35 @@
|
||||
"creator": "作成者",
|
||||
"title": "レシピタイトル",
|
||||
"loraName": "LoRAファイル名",
|
||||
"loraModel": "LoRAモデル名"
|
||||
"loraModel": "LoRAモデル名",
|
||||
"prompt": "プロンプト"
|
||||
}
|
||||
},
|
||||
"filter": {
|
||||
"title": "モデルをフィルタ",
|
||||
"presets": "プリセット",
|
||||
"savePreset": "現在のアクティブフィルタを新しいプリセットとして保存。",
|
||||
"savePresetDisabledActive": "保存できません:プリセットがすでにアクティブです。フィルタを変更して新しいプリセットを保存してください",
|
||||
"savePresetDisabledNoFilters": "先にフィルタを選択してからプリセットとして保存",
|
||||
"savePresetPrompt": "プリセット名を入力:",
|
||||
"presetClickTooltip": "プリセット \"{name}\" を適用するにはクリック",
|
||||
"presetDeleteTooltip": "プリセットを削除",
|
||||
"presetDeleteConfirm": "プリセット \"{name}\" を削除しますか?",
|
||||
"presetDeleteConfirmClick": "もう一度クリックして確認",
|
||||
"presetOverwriteConfirm": "プリセット「{name}」は既に存在します。上書きしますか?",
|
||||
"presetNamePlaceholder": "プリセット名...",
|
||||
"baseModel": "ベースモデル",
|
||||
"modelTags": "タグ(上位20)",
|
||||
"clearAll": "すべてのフィルタをクリア"
|
||||
"modelTypes": "Model Types",
|
||||
"license": "ライセンス",
|
||||
"noCreditRequired": "クレジット不要",
|
||||
"allowSellingGeneratedContent": "販売許可",
|
||||
"noTags": "タグなし",
|
||||
"clearAll": "すべてのフィルタをクリア",
|
||||
"any": "いずれか",
|
||||
"all": "すべて",
|
||||
"tagLogicAny": "いずれかのタグに一致 (OR)",
|
||||
"tagLogicAll": "すべてのタグに一致 (AND)"
|
||||
},
|
||||
"theme": {
|
||||
"toggle": "テーマの切り替え",
|
||||
@@ -180,6 +237,7 @@
|
||||
},
|
||||
"actions": {
|
||||
"checkUpdates": "更新確認",
|
||||
"notifications": "通知",
|
||||
"support": "サポート"
|
||||
}
|
||||
},
|
||||
@@ -187,17 +245,33 @@
|
||||
"civitaiApiKey": "Civitai APIキー",
|
||||
"civitaiApiKeyPlaceholder": "Civitai APIキーを入力してください",
|
||||
"civitaiApiKeyHelp": "Civitaiからモデルをダウンロードするときの認証に使用されます",
|
||||
"openSettingsFileLocation": {
|
||||
"label": "設定フォルダーを開く",
|
||||
"tooltip": "settings.json を含むフォルダーを開きます",
|
||||
"success": "settings.json フォルダーを開きました",
|
||||
"failed": "settings.json フォルダーを開けませんでした",
|
||||
"copied": "設定パスをクリップボードにコピーしました: {{path}}",
|
||||
"clipboardFallback": "設定パス: {{path}}"
|
||||
},
|
||||
"sections": {
|
||||
"contentFiltering": "コンテンツフィルタリング",
|
||||
"videoSettings": "動画設定",
|
||||
"layoutSettings": "レイアウト設定",
|
||||
"folderSettings": "フォルダ設定",
|
||||
"priorityTags": "優先タグ",
|
||||
"downloadPathTemplates": "ダウンロードパステンプレート",
|
||||
"exampleImages": "例画像",
|
||||
"updateFlags": "アップデートフラグ",
|
||||
"autoOrganize": "Auto-organize",
|
||||
"misc": "その他",
|
||||
"metadataArchive": "メタデータアーカイブデータベース",
|
||||
"storageLocation": "設定の場所",
|
||||
"proxySettings": "プロキシ設定"
|
||||
},
|
||||
"storage": {
|
||||
"locationLabel": "ポータブルモード",
|
||||
"locationHelp": "有効にすると settings.json をリポジトリ内に保持し、無効にするとユーザー設定ディレクトリに格納します。"
|
||||
},
|
||||
"contentFiltering": {
|
||||
"blurNsfwContent": "NSFWコンテンツをぼかす",
|
||||
"blurNsfwContentHelp": "成人向け(NSFW)コンテンツのプレビュー画像をぼかします",
|
||||
@@ -208,6 +282,15 @@
|
||||
"autoplayOnHover": "ホバー時に動画を自動再生",
|
||||
"autoplayOnHoverHelp": "動画プレビューはホバー時にのみ再生されます"
|
||||
},
|
||||
"autoOrganizeExclusions": {
|
||||
"label": "自動整理除外設定",
|
||||
"placeholder": "例: curated/*, */backups/*; *_temp.safetensors",
|
||||
"help": "これらのワイルドカードパターンに一致するファイルの移動をスキップします。複数のパターンはカンマまたはセミコロンで区切ってください。",
|
||||
"validation": {
|
||||
"noPatterns": "カンマまたはセミコロンで区切られた少なくとも1つのパターンを入力してください。",
|
||||
"saveFailed": "除外設定を保存できませんでした: {message}"
|
||||
}
|
||||
},
|
||||
"layoutSettings": {
|
||||
"displayDensity": "表示密度",
|
||||
"displayDensityOptions": {
|
||||
@@ -217,31 +300,67 @@
|
||||
},
|
||||
"displayDensityHelp": "1行に表示するカード数を選択:",
|
||||
"displayDensityDetails": {
|
||||
"default": "デフォルト:5(1080p)、6(2K)、8(4K)",
|
||||
"medium": "中:6(1080p)、7(2K)、9(4K)",
|
||||
"compact": "コンパクト:7(1080p)、8(2K)、10(4K)"
|
||||
"default": "5(1080p)、6(2K)、8(4K)",
|
||||
"medium": "6(1080p)、7(2K)、9(4K)",
|
||||
"compact": "7(1080p)、8(2K)、10(4K)"
|
||||
},
|
||||
"displayDensityWarning": "警告:高密度設定は、リソースが限られたシステムでパフォーマンスの問題を引き起こす可能性があります。",
|
||||
"showFolderSidebar": "フォルダサイドバーを表示",
|
||||
"showFolderSidebarHelp": "モデルページのフォルダナビゲーションサイドバーを表示/非表示にします。無効にするとサイドバーとホバーエリアは表示されません。",
|
||||
"cardInfoDisplay": "カード情報表示",
|
||||
"cardInfoDisplayOptions": {
|
||||
"always": "常に表示",
|
||||
"hover": "ホバー時に表示"
|
||||
},
|
||||
"cardInfoDisplayHelp": "モデル情報とアクションボタンの表示タイミングを選択:",
|
||||
"cardInfoDisplayDetails": {
|
||||
"always": "常に表示:ヘッダーとフッターが常に表示されます",
|
||||
"hover": "ホバー時に表示:カードにホバーしたときのみヘッダーとフッターが表示されます"
|
||||
}
|
||||
"cardInfoDisplayHelp": "モデル情報とアクションボタンの表示タイミングを選択",
|
||||
"modelCardFooterAction": "モデルカードボタンのアクション",
|
||||
"modelCardFooterActionOptions": {
|
||||
"exampleImages": "例画像を開く",
|
||||
"replacePreview": "プレビューを置換"
|
||||
},
|
||||
"modelCardFooterActionHelp": "カード右下のボタンが何をするかを選択します",
|
||||
"modelNameDisplay": "モデル名表示",
|
||||
"modelNameDisplayOptions": {
|
||||
"modelName": "モデル名",
|
||||
"fileName": "ファイル名"
|
||||
},
|
||||
"modelNameDisplayHelp": "モデルカードのフッターに表示する内容を選択"
|
||||
},
|
||||
"folderSettings": {
|
||||
"activeLibrary": "アクティブライブラリ",
|
||||
"activeLibraryHelp": "設定済みのライブラリを切り替えてデフォルトのフォルダを更新します。選択を変更するとページが再読み込みされます。",
|
||||
"loadingLibraries": "ライブラリを読み込み中...",
|
||||
"noLibraries": "ライブラリが設定されていません",
|
||||
"defaultLoraRoot": "デフォルトLoRAルート",
|
||||
"defaultLoraRootHelp": "ダウンロード、インポート、移動用のデフォルトLoRAルートディレクトリを設定",
|
||||
"defaultCheckpointRoot": "デフォルトCheckpointルート",
|
||||
"defaultCheckpointRootHelp": "ダウンロード、インポート、移動用のデフォルトcheckpointルートディレクトリを設定",
|
||||
"defaultUnetRoot": "デフォルトDiffusion Modelルート",
|
||||
"defaultUnetRootHelp": "ダウンロード、インポート、移動用のデフォルトDiffusion Model (UNET)ルートディレクトリを設定",
|
||||
"defaultEmbeddingRoot": "デフォルトEmbeddingルート",
|
||||
"defaultEmbeddingRootHelp": "ダウンロード、インポート、移動用のデフォルトembeddingルートディレクトリを設定",
|
||||
"noDefault": "デフォルトなし"
|
||||
},
|
||||
"priorityTags": {
|
||||
"title": "優先タグ",
|
||||
"description": "各モデルタイプのタグ優先順位をカスタマイズします (例: character, concept, style(toon|toon_style))",
|
||||
"placeholder": "character, concept, style(toon|toon_style)",
|
||||
"helpLinkLabel": "優先タグのヘルプを開く",
|
||||
"modelTypes": {
|
||||
"lora": "LoRA",
|
||||
"checkpoint": "チェックポイント",
|
||||
"embedding": "埋め込み"
|
||||
},
|
||||
"saveSuccess": "優先タグを更新しました。",
|
||||
"saveError": "優先タグの更新に失敗しました。",
|
||||
"loadingSuggestions": "候補を読み込み中...",
|
||||
"validation": {
|
||||
"missingClosingParen": "エントリ {index} に閉じ括弧がありません。",
|
||||
"missingCanonical": "エントリ {index} には正規タグ名を含める必要があります。",
|
||||
"duplicateCanonical": "正規タグ \"{tag}\" が複数回登場しています。",
|
||||
"unknown": "無効な優先タグ設定です。"
|
||||
}
|
||||
},
|
||||
"downloadPathTemplates": {
|
||||
"title": "ダウンロードパステンプレート",
|
||||
"help": "Civitaiからダウンロードする際の異なるモデルタイプのフォルダ構造を設定します。",
|
||||
@@ -289,6 +408,14 @@
|
||||
"download": "ダウンロード",
|
||||
"restartRequired": "再起動が必要"
|
||||
},
|
||||
"updateFlagStrategy": {
|
||||
"label": "アップデートフラグの表示戦略",
|
||||
"help": "新リリースがローカルファイルと同じベースモデルを共有する場合にのみ更新バッジを表示するか、そのモデルに新しいバージョンがあれば常に表示するかを決めます。",
|
||||
"options": {
|
||||
"sameBase": "ベースモデルで更新をマッチ",
|
||||
"any": "利用可能な更新すべてを表示"
|
||||
}
|
||||
},
|
||||
"misc": {
|
||||
"includeTriggerWords": "LoRA構文にトリガーワードを含める",
|
||||
"includeTriggerWordsHelp": "LoRA構文をクリップボードにコピーする際、学習済みトリガーワードを含めます"
|
||||
@@ -348,12 +475,17 @@
|
||||
"dateAsc": "古い順",
|
||||
"size": "ファイルサイズ",
|
||||
"sizeDesc": "大きい順",
|
||||
"sizeAsc": "小さい順"
|
||||
"sizeAsc": "小さい順",
|
||||
"usage": "使用回数",
|
||||
"usageDesc": "多い",
|
||||
"usageAsc": "少ない"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "モデルリストを更新",
|
||||
"quick": "クイック更新(増分)",
|
||||
"full": "完全再構築(完全)"
|
||||
"quick": "変更を同期",
|
||||
"quickTooltip": "新しいモデルファイルや欠けているファイルをスキャンして一覧を最新に保ちます。",
|
||||
"full": "キャッシュを再構築",
|
||||
"fullTooltip": "メタデータファイルから全モデル情報を再読み込みします。リストが古いと感じるときや手動編集後に使用してください。"
|
||||
},
|
||||
"fetch": {
|
||||
"title": "Civitaiからメタデータを取得",
|
||||
@@ -374,6 +506,13 @@
|
||||
"favorites": {
|
||||
"title": "お気に入りのみ表示",
|
||||
"action": "お気に入り"
|
||||
},
|
||||
"updates": {
|
||||
"title": "アップデート可能なモデルのみ表示",
|
||||
"action": "アップデート",
|
||||
"menuLabel": "更新オプションを表示",
|
||||
"check": "アップデートを確認",
|
||||
"checkTooltip": "確認には時間がかかる場合があります。"
|
||||
}
|
||||
},
|
||||
"bulkOperations": {
|
||||
@@ -382,8 +521,10 @@
|
||||
"viewSelected": "選択中を表示",
|
||||
"addTags": "すべてにタグを追加",
|
||||
"setBaseModel": "すべてにベースモデルを設定",
|
||||
"setContentRating": "すべてのモデルのコンテンツレーティングを設定",
|
||||
"copyAll": "すべての構文をコピー",
|
||||
"refreshAll": "すべてのメタデータを更新",
|
||||
"checkUpdates": "選択項目の更新を確認",
|
||||
"moveAll": "すべてをフォルダに移動",
|
||||
"autoOrganize": "自動整理を実行",
|
||||
"deleteAll": "すべてのモデルを削除",
|
||||
@@ -400,6 +541,7 @@
|
||||
},
|
||||
"contextMenu": {
|
||||
"refreshMetadata": "Civitaiデータを更新",
|
||||
"checkUpdates": "更新確認",
|
||||
"relinkCivitai": "Civitaiに再リンク",
|
||||
"copySyntax": "LoRA構文をコピー",
|
||||
"copyFilename": "モデルファイル名をコピー",
|
||||
@@ -411,6 +553,7 @@
|
||||
"replacePreview": "プレビューを置換",
|
||||
"setContentRating": "コンテンツレーティングを設定",
|
||||
"moveToFolder": "フォルダに移動",
|
||||
"repairMetadata": "メタデータを修復",
|
||||
"excludeModel": "モデルを除外",
|
||||
"deleteModel": "モデルを削除",
|
||||
"shareRecipe": "レシピを共有",
|
||||
@@ -421,6 +564,9 @@
|
||||
},
|
||||
"recipes": {
|
||||
"title": "LoRAレシピ",
|
||||
"actions": {
|
||||
"sendCheckpoint": "ComfyUIへ送信"
|
||||
},
|
||||
"controls": {
|
||||
"import": {
|
||||
"action": "インポート",
|
||||
@@ -478,10 +624,26 @@
|
||||
"selectLoraRoot": "LoRAルートディレクトリを選択してください"
|
||||
}
|
||||
},
|
||||
"sort": {
|
||||
"title": "レシピの並び替え...",
|
||||
"name": "名前",
|
||||
"nameAsc": "A - Z",
|
||||
"nameDesc": "Z - A",
|
||||
"date": "日付",
|
||||
"dateDesc": "新しい順",
|
||||
"dateAsc": "古い順",
|
||||
"lorasCount": "LoRA数",
|
||||
"lorasCountDesc": "多い順",
|
||||
"lorasCountAsc": "少ない順"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "レシピリストを更新"
|
||||
},
|
||||
"filteredByLora": "LoRAでフィルタ済み"
|
||||
"filteredByLora": "LoRAでフィルタ済み",
|
||||
"favorites": {
|
||||
"title": "お気に入りのみ表示",
|
||||
"action": "お気に入り"
|
||||
}
|
||||
},
|
||||
"duplicates": {
|
||||
"found": "{count} 個の重複グループが見つかりました",
|
||||
@@ -507,23 +669,44 @@
|
||||
"noMissingLoras": "ダウンロードする不足LoRAがありません",
|
||||
"getInfoFailed": "不足LoRAの情報取得に失敗しました",
|
||||
"prepareError": "ダウンロード用LoRAの準備中にエラー:{message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "レシピのメタデータを修復中...",
|
||||
"success": "レシピのメタデータが正常に修復されました",
|
||||
"skipped": "レシピはすでに最新バージョンです。修復は不要です",
|
||||
"failed": "レシピの修復に失敗しました: {message}",
|
||||
"missingId": "レシピを修復できません: レシピIDがありません"
|
||||
}
|
||||
}
|
||||
},
|
||||
"checkpoints": {
|
||||
"title": "Checkpointモデル"
|
||||
"title": "Checkpointモデル",
|
||||
"modelTypes": {
|
||||
"checkpoint": "Checkpoint",
|
||||
"diffusion_model": "Diffusion Model"
|
||||
},
|
||||
"contextMenu": {
|
||||
"moveToOtherTypeFolder": "{otherType} フォルダに移動"
|
||||
}
|
||||
},
|
||||
"embeddings": {
|
||||
"title": "Embeddingモデル"
|
||||
},
|
||||
"sidebar": {
|
||||
"modelRoot": "モデルルート",
|
||||
"modelRoot": "ルート",
|
||||
"collapseAll": "すべてのフォルダを折りたたむ",
|
||||
"pinSidebar": "サイドバーを固定",
|
||||
"unpinSidebar": "サイドバーの固定を解除",
|
||||
"switchToListView": "リストビューに切り替え",
|
||||
"switchToTreeView": "ツリービューに切り替え",
|
||||
"collapseAllDisabled": "リストビューでは利用できません"
|
||||
"switchToTreeView": "ツリー表示に切り替え",
|
||||
"recursiveOn": "サブフォルダーを検索",
|
||||
"recursiveOff": "現在のフォルダーのみを検索",
|
||||
"recursiveUnavailable": "再帰検索はツリービューでのみ利用できます",
|
||||
"collapseAllDisabled": "リストビューでは利用できません",
|
||||
"dragDrop": {
|
||||
"unableToResolveRoot": "移動先のパスを特定できません。",
|
||||
"moveUnsupported": "Move is not supported for this item."
|
||||
}
|
||||
},
|
||||
"statistics": {
|
||||
"title": "統計",
|
||||
@@ -598,6 +781,14 @@
|
||||
"downloadedPreview": "プレビュー画像をダウンロードしました",
|
||||
"downloadingFile": "{type}ファイルをダウンロード中",
|
||||
"finalizing": "ダウンロードを完了中..."
|
||||
},
|
||||
"progress": {
|
||||
"currentFile": "現在のファイル:",
|
||||
"downloading": "ダウンロード中: {name}",
|
||||
"transferred": "ダウンロード済み: {downloaded} / {total}",
|
||||
"transferredSimple": "ダウンロード済み: {downloaded}",
|
||||
"transferredUnknown": "ダウンロード済み: --",
|
||||
"speed": "速度: {speed}"
|
||||
}
|
||||
},
|
||||
"move": {
|
||||
@@ -606,6 +797,7 @@
|
||||
"contentRating": {
|
||||
"title": "コンテンツレーティングを設定",
|
||||
"current": "現在",
|
||||
"multiple": "複数の値",
|
||||
"levels": {
|
||||
"pg": "PG",
|
||||
"pg13": "PG13",
|
||||
@@ -644,6 +836,12 @@
|
||||
"countMessage": "モデルが完全に削除されます。",
|
||||
"action": "すべて削除"
|
||||
},
|
||||
"checkUpdates": {
|
||||
"title": "すべての{type}の更新を確認しますか?",
|
||||
"message": "ライブラリ内のすべての{type}で更新を確認します。コレクションが大きい場合は時間がかかることがあります。",
|
||||
"tip": "少しずつ確認したい場合はバルクモードに切り替え、必要なモデルを選んで「選択項目の更新を確認」を使ってください。",
|
||||
"action": "すべて確認"
|
||||
},
|
||||
"bulkAddTags": {
|
||||
"title": "複数モデルにタグを追加",
|
||||
"description": "タグを追加するモデル:",
|
||||
@@ -717,7 +915,9 @@
|
||||
},
|
||||
"openFileLocation": {
|
||||
"success": "ファイルの場所を正常に開きました",
|
||||
"failed": "ファイルの場所を開くのに失敗しました"
|
||||
"failed": "ファイルの場所を開くのに失敗しました",
|
||||
"copied": "パスをクリップボードにコピーしました: {{path}}",
|
||||
"clipboardFallback": "パス: {{path}}"
|
||||
},
|
||||
"metadata": {
|
||||
"version": "バージョン",
|
||||
@@ -740,11 +940,13 @@
|
||||
"addPresetParameter": "プリセットパラメータを追加...",
|
||||
"strengthMin": "強度最小",
|
||||
"strengthMax": "強度最大",
|
||||
"strengthRange": "強度範囲",
|
||||
"strength": "強度",
|
||||
"clipStrength": "クリップ強度",
|
||||
"clipSkip": "Clip Skip",
|
||||
"valuePlaceholder": "値",
|
||||
"add": "追加"
|
||||
"add": "追加",
|
||||
"invalidRange": "無効な範囲形式です。x.x-y.y を使用してください"
|
||||
},
|
||||
"triggerWords": {
|
||||
"label": "トリガーワード",
|
||||
@@ -780,13 +982,84 @@
|
||||
"tabs": {
|
||||
"examples": "例",
|
||||
"description": "モデル説明",
|
||||
"recipes": "レシピ"
|
||||
"recipes": "レシピ",
|
||||
"versions": "バージョン"
|
||||
},
|
||||
"navigation": {
|
||||
"label": "モデルナビゲーション",
|
||||
"previousWithShortcut": "前のモデル(←)",
|
||||
"nextWithShortcut": "次のモデル(→)",
|
||||
"noPrevious": "前のモデルがありません",
|
||||
"noNext": "次のモデルがありません"
|
||||
},
|
||||
"license": {
|
||||
"noImageSell": "No selling generated content",
|
||||
"noRentCivit": "No Civitai generation",
|
||||
"noRent": "No generation services",
|
||||
"noSell": "No selling models",
|
||||
"creditRequired": "作成者のクレジットが必要",
|
||||
"noDerivatives": "共有マージ不可",
|
||||
"noReLicense": "同じ権限が必要",
|
||||
"restrictionsLabel": "ライセンス制限"
|
||||
},
|
||||
"loading": {
|
||||
"exampleImages": "例画像を読み込み中...",
|
||||
"description": "モデル説明を読み込み中...",
|
||||
"recipes": "レシピを読み込み中...",
|
||||
"examples": "例を読み込み中..."
|
||||
"examples": "例を読み込み中...",
|
||||
"versions": "バージョンを読み込み中..."
|
||||
},
|
||||
"versions": {
|
||||
"heading": "モデルバージョン",
|
||||
"copy": "このモデルのすべてのバージョンを一か所で管理します。",
|
||||
"media": {
|
||||
"placeholder": "プレビューなし"
|
||||
},
|
||||
"labels": {
|
||||
"unnamed": "名前のないバージョン",
|
||||
"noDetails": "追加情報なし"
|
||||
},
|
||||
"badges": {
|
||||
"current": "現在のバージョン",
|
||||
"inLibrary": "ライブラリにあります",
|
||||
"newer": "新しいバージョン",
|
||||
"ignored": "無視中"
|
||||
},
|
||||
"actions": {
|
||||
"download": "ダウンロード",
|
||||
"delete": "削除",
|
||||
"ignore": "無視",
|
||||
"unignore": "無視を解除",
|
||||
"resumeModelUpdates": "このモデルの更新を再開",
|
||||
"ignoreModelUpdates": "このモデルの更新を無視",
|
||||
"viewLocalVersions": "ローカルの全バージョンを表示",
|
||||
"viewLocalTooltip": "近日対応予定"
|
||||
},
|
||||
"filters": {
|
||||
"label": "ベースフィルター",
|
||||
"state": {
|
||||
"showAll": "すべてのバージョン",
|
||||
"showSameBase": "同じベース"
|
||||
},
|
||||
"tooltip": {
|
||||
"showAllVersions": "すべてのバージョンを表示する",
|
||||
"showSameBaseVersions": "同じベースモデルのバージョンのみ表示する"
|
||||
},
|
||||
"empty": "現在のベースモデルフィルターに一致するバージョンがありません。"
|
||||
},
|
||||
"empty": "このモデルにはまだバージョン履歴がありません。",
|
||||
"error": "バージョンの読み込みに失敗しました。",
|
||||
"missingModelId": "このモデルにはCivitaiのモデルIDがありません。",
|
||||
"confirm": {
|
||||
"delete": "このバージョンをライブラリから削除しますか?"
|
||||
},
|
||||
"toast": {
|
||||
"modelIgnored": "このモデルの更新は無視されます",
|
||||
"modelResumed": "更新の監視を再開しました",
|
||||
"versionIgnored": "このバージョンの更新は無視されます",
|
||||
"versionUnignored": "バージョンを再度有効にしました",
|
||||
"versionDeleted": "バージョンを削除しました"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -893,7 +1166,9 @@
|
||||
"loraFailedToSend": "LoRAをワークフローに送信できませんでした",
|
||||
"recipeAdded": "レシピがワークフローに追加されました",
|
||||
"recipeReplaced": "レシピがワークフローで置換されました",
|
||||
"recipeFailedToSend": "レシピをワークフローに送信できませんでした"
|
||||
"recipeFailedToSend": "レシピをワークフローに送信できませんでした",
|
||||
"noMatchingNodes": "現在のワークフローには互換性のあるノードがありません",
|
||||
"noTargetNodeSelected": "ターゲットノードが選択されていません"
|
||||
},
|
||||
"nodeSelector": {
|
||||
"recipe": "レシピ",
|
||||
@@ -906,7 +1181,11 @@
|
||||
"exampleImages": {
|
||||
"opened": "例画像フォルダが開かれました",
|
||||
"openingFolder": "例画像フォルダを開いています",
|
||||
"failedToOpen": "例画像フォルダを開くのに失敗しました"
|
||||
"failedToOpen": "例画像フォルダを開くのに失敗しました",
|
||||
"setupRequired": "例画像ストレージ",
|
||||
"setupDescription": "カスタム例画像を追加するには、まずダウンロード場所を設定する必要があります。",
|
||||
"setupUsage": "このパスは、ダウンロードした例画像とカスタム画像の両方に使用されます。",
|
||||
"openSettings": "設定を開く"
|
||||
}
|
||||
},
|
||||
"help": {
|
||||
@@ -938,6 +1217,11 @@
|
||||
},
|
||||
"update": {
|
||||
"title": "更新確認",
|
||||
"notificationsTitle": "通知センター",
|
||||
"tabs": {
|
||||
"updates": "更新",
|
||||
"messages": "メッセージ"
|
||||
},
|
||||
"updateAvailable": "更新が利用可能",
|
||||
"noChangelogAvailable": "詳細な変更ログは利用できません。詳細はGitHubでご確認ください。",
|
||||
"currentVersion": "現在のバージョン",
|
||||
@@ -950,6 +1234,7 @@
|
||||
"checkingUpdates": "更新を確認中...",
|
||||
"checkingMessage": "最新バージョンを確認しています。お待ちください。",
|
||||
"showNotifications": "更新通知を表示",
|
||||
"latestBadge": "最新",
|
||||
"updateProgress": {
|
||||
"preparing": "更新を準備中...",
|
||||
"installing": "更新をインストール中...",
|
||||
@@ -969,6 +1254,13 @@
|
||||
"nightly": {
|
||||
"warning": "警告:ナイトリービルドには実験的機能が含まれており、不安定な場合があります。",
|
||||
"enable": "ナイトリー更新を有効にする"
|
||||
},
|
||||
"banners": {
|
||||
"recent": "最近の通知",
|
||||
"empty": "最近のバナーはありません。",
|
||||
"shown": "{time} に表示",
|
||||
"dismissed": "{time} に非表示",
|
||||
"active": "アクティブ"
|
||||
}
|
||||
},
|
||||
"support": {
|
||||
@@ -1048,6 +1340,9 @@
|
||||
"cannotSend": "レシピを送信できません:レシピIDがありません",
|
||||
"sendFailed": "レシピのワークフローへの送信に失敗しました",
|
||||
"sendError": "レシピのワークフロー送信エラー",
|
||||
"missingCheckpointPath": "チェックポイントのパスがありません",
|
||||
"missingCheckpointInfo": "チェックポイント情報が不足しています",
|
||||
"downloadCheckpointFailed": "チェックポイントのダウンロードに失敗しました: {message}",
|
||||
"cannotDelete": "レシピを削除できません:レシピIDがありません",
|
||||
"deleteConfirmationError": "削除確認の表示中にエラーが発生しました",
|
||||
"deletedSuccessfully": "レシピが正常に削除されました",
|
||||
@@ -1084,6 +1379,16 @@
|
||||
"bulkBaseModelUpdateSuccess": "{count} モデルのベースモデルが正常に更新されました",
|
||||
"bulkBaseModelUpdatePartial": "{success} モデルを更新、{failed} モデルは失敗しました",
|
||||
"bulkBaseModelUpdateFailed": "選択したモデルのベースモデルの更新に失敗しました",
|
||||
"bulkContentRatingUpdating": "{count} 件のモデルのコンテンツレーティングを更新中...",
|
||||
"bulkContentRatingSet": "{count} 件のモデルのコンテンツレーティングを {level} に設定しました",
|
||||
"bulkContentRatingPartial": "{success} 件のモデルのコンテンツレーティングを {level} に設定、{failed} 件は失敗しました",
|
||||
"bulkContentRatingFailed": "選択したモデルのコンテンツレーティングを更新できませんでした",
|
||||
"bulkUpdatesChecking": "選択された{type}の更新を確認しています...",
|
||||
"bulkUpdatesSuccess": "{count} 件の選択された{type}に利用可能な更新があります",
|
||||
"bulkUpdatesNone": "選択された{type}には更新が見つかりませんでした",
|
||||
"bulkUpdatesMissing": "選択された{type}はCivitaiの更新にリンクされていません",
|
||||
"bulkUpdatesPartialMissing": "Civitaiリンクがない{missing} 件の{type}をスキップしました",
|
||||
"bulkUpdatesFailed": "選択された{type}の更新確認に失敗しました: {message}",
|
||||
"invalidCharactersRemoved": "ファイル名から無効な文字が削除されました",
|
||||
"filenameCannotBeEmpty": "ファイル名を空にすることはできません",
|
||||
"renameFailed": "ファイル名の変更に失敗しました:{message}",
|
||||
@@ -1095,6 +1400,7 @@
|
||||
"verificationCompleteSuccess": "検証完了。すべてのファイルが重複であることが確認されました。",
|
||||
"verificationFailed": "ハッシュの検証に失敗しました:{message}",
|
||||
"noTagsToAdd": "追加するタグがありません",
|
||||
"bulkTagsUpdating": "{count} 個のモデルのタグを更新しています...",
|
||||
"tagsAddedSuccessfully": "{count} {type} に {tagCount} 個のタグを追加しました",
|
||||
"tagsReplacedSuccessfully": "{count} {type} のタグを {tagCount} 個に置換しました",
|
||||
"tagsAddFailed": "{count} モデルへのタグ追加に失敗しました",
|
||||
@@ -1108,6 +1414,7 @@
|
||||
"settings": {
|
||||
"loraRootsFailed": "LoRAルートの読み込みに失敗しました:{message}",
|
||||
"checkpointRootsFailed": "checkpointルートの読み込みに失敗しました:{message}",
|
||||
"unetRootsFailed": "Diffusion Modelルートの読み込みに失敗しました:{message}",
|
||||
"embeddingRootsFailed": "embeddingルートの読み込みに失敗しました:{message}",
|
||||
"mappingsUpdated": "ベースモデルパスマッピングが更新されました({count} マッピング{plural})",
|
||||
"mappingsCleared": "ベースモデルパスマッピングがクリアされました",
|
||||
@@ -1118,6 +1425,8 @@
|
||||
"compactModeToggled": "コンパクトモード {state}",
|
||||
"settingSaveFailed": "設定の保存に失敗しました:{message}",
|
||||
"displayDensitySet": "表示密度が {density} に設定されました",
|
||||
"libraryLoadFailed": "Failed to load libraries: {message}",
|
||||
"libraryActivateFailed": "Failed to activate library: {message}",
|
||||
"languageChangeFailed": "言語の変更に失敗しました:{message}",
|
||||
"cacheCleared": "キャッシュファイルが正常にクリアされました。次回のアクションでキャッシュが再構築されます。",
|
||||
"cacheClearFailed": "キャッシュのクリアに失敗しました:{error}",
|
||||
@@ -1126,7 +1435,26 @@
|
||||
"filters": {
|
||||
"applied": "{message}",
|
||||
"cleared": "フィルタがクリアされました",
|
||||
"noCustomFilterToClear": "クリアするカスタムフィルタがありません"
|
||||
"noCustomFilterToClear": "クリアするカスタムフィルタがありません",
|
||||
"noActiveFilters": "保存するアクティブフィルタがありません"
|
||||
},
|
||||
"presets": {
|
||||
"created": "プリセット \"{name}\" が作成されました",
|
||||
"deleted": "プリセット \"{name}\" が削除されました",
|
||||
"applied": "プリセット \"{name}\" が適用されました",
|
||||
"overwritten": "プリセット「{name}」を上書きしました",
|
||||
"restored": "デフォルトのプリセットを復元しました"
|
||||
},
|
||||
"error": {
|
||||
"presetNameEmpty": "プリセット名を入力してください",
|
||||
"presetNameTooLong": "プリセット名は{max}文字以内にしてください",
|
||||
"presetNameInvalidChars": "プリセット名に使用できない文字が含まれています",
|
||||
"presetNameExists": "同じ名前のプリセットが既に存在します",
|
||||
"maxPresetsReached": "プリセットは最大{max}個までです。追加するには既存のものを削除してください。",
|
||||
"presetNotFound": "プリセットが見つかりません",
|
||||
"invalidPreset": "無効なプリセットデータです",
|
||||
"deletePresetFailed": "プリセットの削除に失敗しました",
|
||||
"applyPresetFailed": "プリセットの適用に失敗しました"
|
||||
},
|
||||
"downloads": {
|
||||
"imagesCompleted": "例画像 {action} が完了しました",
|
||||
@@ -1142,7 +1470,7 @@
|
||||
},
|
||||
"triggerWords": {
|
||||
"loadFailed": "学習済みワードを読み込めませんでした",
|
||||
"tooLong": "トリガーワードは30ワードを超えてはいけません",
|
||||
"tooLong": "トリガーワードは100ワードを超えてはいけません",
|
||||
"tooMany": "最大30トリガーワードまで許可されています",
|
||||
"alreadyExists": "このトリガーワードは既に存在します",
|
||||
"updateSuccess": "トリガーワードが正常に更新されました",
|
||||
@@ -1191,6 +1519,8 @@
|
||||
"pauseFailed": "ダウンロードの一時停止に失敗しました:{error}",
|
||||
"downloadResumed": "ダウンロードが再開されました",
|
||||
"resumeFailed": "ダウンロードの再開に失敗しました:{error}",
|
||||
"downloadStopped": "ダウンロードをキャンセルしました",
|
||||
"stopFailed": "ダウンロードのキャンセルに失敗しました:{error}",
|
||||
"deleted": "例画像が削除されました",
|
||||
"deleteFailed": "例画像の削除に失敗しました",
|
||||
"setPreviewFailed": "プレビュー画像の設定に失敗しました"
|
||||
@@ -1211,6 +1541,8 @@
|
||||
"metadataRefreshed": "メタデータが正常に更新されました",
|
||||
"metadataRefreshFailed": "メタデータの更新に失敗しました:{message}",
|
||||
"metadataUpdateComplete": "メタデータ更新完了",
|
||||
"operationCancelled": "ユーザーによって操作がキャンセルされました",
|
||||
"operationCancelledPartial": "操作がキャンセルされました。{success} 個の項目が処理されました。",
|
||||
"metadataFetchFailed": "メタデータの取得に失敗しました:{message}",
|
||||
"bulkMetadataCompleteAll": "{count} {type}すべてが正常に更新されました",
|
||||
"bulkMetadataCompletePartial": "{total} {type}のうち {success} が更新されました",
|
||||
@@ -1227,7 +1559,8 @@
|
||||
"bulkMoveFailures": "失敗した移動:\n{failures}",
|
||||
"bulkMoveSuccess": "{successCount} {type}が正常に移動されました",
|
||||
"exampleImagesDownloadSuccess": "例画像が正常にダウンロードされました!",
|
||||
"exampleImagesDownloadFailed": "例画像のダウンロードに失敗しました:{message}"
|
||||
"exampleImagesDownloadFailed": "例画像のダウンロードに失敗しました:{message}",
|
||||
"moveFailed": "Failed to move item: {message}"
|
||||
}
|
||||
},
|
||||
"banners": {
|
||||
@@ -1237,6 +1570,26 @@
|
||||
"refreshNow": "今すぐ更新",
|
||||
"refreshingIn": "更新まで",
|
||||
"seconds": "秒"
|
||||
},
|
||||
"communitySupport": {
|
||||
"title": "Keep LoRA Manager Thriving with Your Support ❤️",
|
||||
"content": "LoRA Manager is a passion project maintained full-time by a solo developer. Your support on Ko-fi helps cover development costs, keeps new updates coming, and unlocks a license key for the LM Civitai Extension as a thank-you gift. Every contribution truly makes a difference.",
|
||||
"supportCta": "Support on Ko-fi",
|
||||
"learnMore": "LM Civitai Extension Tutorial"
|
||||
},
|
||||
"cacheHealth": {
|
||||
"corrupted": {
|
||||
"title": "キャッシュの破損が検出されました"
|
||||
},
|
||||
"degraded": {
|
||||
"title": "キャッシュの問題が検出されました"
|
||||
},
|
||||
"content": "{total}個のキャッシュエントリのうち{invalid}個が無効です({rate})。モデルが見つからない原因になったり、エラーが発生する可能性があります。キャッシュの再構築を推奨します。",
|
||||
"rebuildCache": "キャッシュを再構築",
|
||||
"dismiss": "閉じる",
|
||||
"rebuilding": "キャッシュを再構築中...",
|
||||
"rebuildFailed": "キャッシュの再構築に失敗しました: {error}",
|
||||
"retry": "再試行"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
413
locales/ko.json
413
locales/ko.json
@@ -10,7 +10,8 @@
|
||||
"next": "다음",
|
||||
"backToTop": "맨 위로",
|
||||
"settings": "설정",
|
||||
"help": "도움말"
|
||||
"help": "도움말",
|
||||
"add": "추가"
|
||||
},
|
||||
"status": {
|
||||
"loading": "로딩 중...",
|
||||
@@ -31,7 +32,8 @@
|
||||
"japanese": "日本語",
|
||||
"korean": "한국어",
|
||||
"french": "Français",
|
||||
"spanish": "Español"
|
||||
"spanish": "Español",
|
||||
"Hebrew": "עברית"
|
||||
},
|
||||
"fileSize": {
|
||||
"zero": "0 바이트",
|
||||
@@ -100,7 +102,12 @@
|
||||
"checkpointNameCopied": "Checkpoint 이름 복사됨",
|
||||
"toggleBlur": "블러 토글",
|
||||
"show": "보기",
|
||||
"openExampleImages": "예시 이미지 폴더 열기"
|
||||
"openExampleImages": "예시 이미지 폴더 열기",
|
||||
"replacePreview": "미리보기 교체",
|
||||
"copyCheckpointName": "Checkpoint 이름 복사",
|
||||
"copyEmbeddingName": "Embedding 이름 복사",
|
||||
"sendCheckpointToWorkflow": "ComfyUI로 전송",
|
||||
"sendEmbeddingToWorkflow": "ComfyUI로 전송"
|
||||
},
|
||||
"nsfw": {
|
||||
"matureContent": "성인 콘텐츠",
|
||||
@@ -114,12 +121,20 @@
|
||||
"updateFailed": "즐겨찾기 상태 업데이트 실패"
|
||||
},
|
||||
"sendToWorkflow": {
|
||||
"checkpointNotImplemented": "Checkpoint을 워크플로로 전송 - 구현 예정 기능"
|
||||
"checkpointNotImplemented": "Checkpoint을 워크플로로 전송 - 구현 예정 기능",
|
||||
"missingPath": "이 카드의 모델 경로를 확인할 수 없습니다"
|
||||
},
|
||||
"exampleImages": {
|
||||
"checkError": "예시 이미지 확인 중 오류",
|
||||
"missingHash": "모델 해시 정보가 없습니다.",
|
||||
"noRemoteImagesAvailable": "Civitai에서 이 모델의 원격 예시 이미지를 사용할 수 없습니다"
|
||||
},
|
||||
"badges": {
|
||||
"update": "업데이트",
|
||||
"updateAvailable": "업데이트 가능"
|
||||
},
|
||||
"usage": {
|
||||
"timesUsed": "사용 횟수"
|
||||
}
|
||||
},
|
||||
"globalContextMenu": {
|
||||
@@ -128,12 +143,33 @@
|
||||
"missingPath": "예시 이미지를 다운로드하기 전에 다운로드 위치를 설정하세요.",
|
||||
"unavailable": "예시 이미지 다운로드는 아직 사용할 수 없습니다. 페이지 로딩이 완료된 후 다시 시도하세요."
|
||||
},
|
||||
"checkModelUpdates": {
|
||||
"label": "업데이트 확인",
|
||||
"loading": "{type} 업데이트를 확인 중...",
|
||||
"success": "{type} 업데이트 {count}개를 찾았습니다",
|
||||
"none": "모든 {type}가 최신 상태입니다",
|
||||
"error": "{type} 업데이트 확인 실패: {message}"
|
||||
},
|
||||
"cleanupExampleImages": {
|
||||
"label": "예시 이미지 폴더 정리",
|
||||
"success": "{count}개의 폴더가 삭제 폴더로 이동되었습니다",
|
||||
"none": "정리가 필요한 예시 이미지 폴더가 없습니다",
|
||||
"partial": "정리가 완료되었으나 {failures}개의 폴더가 건너뛰어졌습니다",
|
||||
"error": "예시 이미지 폴더 정리에 실패했습니다: {message}"
|
||||
},
|
||||
"fetchMissingLicenses": {
|
||||
"label": "Refresh license metadata",
|
||||
"loading": "Refreshing license metadata for {typePlural}...",
|
||||
"success": "Updated license metadata for {count} {typePlural}",
|
||||
"none": "All {typePlural} already have license metadata",
|
||||
"error": "Failed to refresh license metadata for {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "레시피 데이터 복구",
|
||||
"loading": "레시피 데이터 복구 중...",
|
||||
"success": "{count}개의 레시피가 성공적으로 복구되었습니다.",
|
||||
"cancelled": "수리가 취소되었습니다. {count}개의 레시피가 수리되었습니다.",
|
||||
"error": "레시피 복구 실패: {message}"
|
||||
}
|
||||
},
|
||||
"header": {
|
||||
@@ -163,14 +199,35 @@
|
||||
"creator": "제작자",
|
||||
"title": "레시피 제목",
|
||||
"loraName": "LoRA 파일명",
|
||||
"loraModel": "LoRA 모델명"
|
||||
"loraModel": "LoRA 모델명",
|
||||
"prompt": "프롬프트"
|
||||
}
|
||||
},
|
||||
"filter": {
|
||||
"title": "모델 필터",
|
||||
"presets": "프리셋",
|
||||
"savePreset": "현재 활성 필터를 새 프리셋으로 저장.",
|
||||
"savePresetDisabledActive": "저장할 수 없음: 프리셋이 이미 활성화되어 있습니다. 필터를 수정한 후 새 프리셋을 저장하세요",
|
||||
"savePresetDisabledNoFilters": "먼저 필터를 선택한 후 프리셋으로 저장",
|
||||
"savePresetPrompt": "프리셋 이름 입력:",
|
||||
"presetClickTooltip": "프리셋 \"{name}\" 적용하려면 클릭",
|
||||
"presetDeleteTooltip": "프리셋 삭제",
|
||||
"presetDeleteConfirm": "프리셋 \"{name}\" 삭제하시겠습니까?",
|
||||
"presetDeleteConfirmClick": "다시 클릭하여 확인",
|
||||
"presetOverwriteConfirm": "프리셋 \"{name}\"이(가) 이미 존재합니다. 덮어쓰시겠습니까?",
|
||||
"presetNamePlaceholder": "프리셋 이름...",
|
||||
"baseModel": "베이스 모델",
|
||||
"modelTags": "태그 (상위 20개)",
|
||||
"clearAll": "모든 필터 지우기"
|
||||
"modelTypes": "Model Types",
|
||||
"license": "라이선스",
|
||||
"noCreditRequired": "크레딧 표기 없음",
|
||||
"allowSellingGeneratedContent": "판매 허용",
|
||||
"noTags": "태그 없음",
|
||||
"clearAll": "모든 필터 지우기",
|
||||
"any": "아무",
|
||||
"all": "모두",
|
||||
"tagLogicAny": "모든 태그 일치 (OR)",
|
||||
"tagLogicAll": "모든 태그 일치 (AND)"
|
||||
},
|
||||
"theme": {
|
||||
"toggle": "테마 토글",
|
||||
@@ -180,6 +237,7 @@
|
||||
},
|
||||
"actions": {
|
||||
"checkUpdates": "업데이트 확인",
|
||||
"notifications": "알림",
|
||||
"support": "지원"
|
||||
}
|
||||
},
|
||||
@@ -187,17 +245,33 @@
|
||||
"civitaiApiKey": "Civitai API 키",
|
||||
"civitaiApiKeyPlaceholder": "Civitai API 키를 입력하세요",
|
||||
"civitaiApiKeyHelp": "Civitai에서 모델을 다운로드할 때 인증에 사용됩니다",
|
||||
"openSettingsFileLocation": {
|
||||
"label": "설정 폴더 열기",
|
||||
"tooltip": "settings.json이 있는 폴더를 엽니다",
|
||||
"success": "settings.json 폴더를 열었습니다",
|
||||
"failed": "settings.json 폴더를 열지 못했습니다",
|
||||
"copied": "설정 경로가 클립보드에 복사되었습니다: {{path}}",
|
||||
"clipboardFallback": "설정 경로: {{path}}"
|
||||
},
|
||||
"sections": {
|
||||
"contentFiltering": "콘텐츠 필터링",
|
||||
"videoSettings": "비디오 설정",
|
||||
"layoutSettings": "레이아웃 설정",
|
||||
"folderSettings": "폴더 설정",
|
||||
"priorityTags": "우선순위 태그",
|
||||
"downloadPathTemplates": "다운로드 경로 템플릿",
|
||||
"exampleImages": "예시 이미지",
|
||||
"updateFlags": "업데이트 표시",
|
||||
"autoOrganize": "Auto-organize",
|
||||
"misc": "기타",
|
||||
"metadataArchive": "메타데이터 아카이브 데이터베이스",
|
||||
"storageLocation": "설정 위치",
|
||||
"proxySettings": "프록시 설정"
|
||||
},
|
||||
"storage": {
|
||||
"locationLabel": "휴대용 모드",
|
||||
"locationHelp": "활성화하면 settings.json을 리포지토리에 유지하고, 비활성화하면 사용자 구성 디렉터리에 저장합니다."
|
||||
},
|
||||
"contentFiltering": {
|
||||
"blurNsfwContent": "NSFW 콘텐츠 블러 처리",
|
||||
"blurNsfwContentHelp": "성인(NSFW) 콘텐츠 미리보기 이미지를 블러 처리합니다",
|
||||
@@ -208,6 +282,15 @@
|
||||
"autoplayOnHover": "호버 시 비디오 자동 재생",
|
||||
"autoplayOnHoverHelp": "마우스를 올렸을 때만 비디오 미리보기를 재생합니다"
|
||||
},
|
||||
"autoOrganizeExclusions": {
|
||||
"label": "자동 정리 제외 항목",
|
||||
"placeholder": "예: curated/*, */backups/*; *_temp.safetensors",
|
||||
"help": "이 와일드카드 패턴과 일치하는 파일 이동을 건너뜁니다. 여러 패턴은 쉼표 또는 세미콜론으로 구분하십시오.",
|
||||
"validation": {
|
||||
"noPatterns": "쉼표 또는 세미콜론으로 구분된 최소한 하나의 패턴을 입력하십시오.",
|
||||
"saveFailed": "제외 항목을 저장할 수 없습니다: {message}"
|
||||
}
|
||||
},
|
||||
"layoutSettings": {
|
||||
"displayDensity": "표시 밀도",
|
||||
"displayDensityOptions": {
|
||||
@@ -217,31 +300,67 @@
|
||||
},
|
||||
"displayDensityHelp": "한 줄에 표시할 카드 수를 선택하세요:",
|
||||
"displayDensityDetails": {
|
||||
"default": "기본: 5개 (1080p), 6개 (2K), 8개 (4K)",
|
||||
"medium": "중간: 6개 (1080p), 7개 (2K), 9개 (4K)",
|
||||
"compact": "조밀: 7개 (1080p), 8개 (2K), 10개 (4K)"
|
||||
"default": "5개 (1080p), 6개 (2K), 8개 (4K)",
|
||||
"medium": "6개 (1080p), 7개 (2K), 9개 (4K)",
|
||||
"compact": "7개 (1080p), 8개 (2K), 10개 (4K)"
|
||||
},
|
||||
"displayDensityWarning": "경고: 높은 밀도는 리소스가 제한된 시스템에서 성능 문제를 일으킬 수 있습니다.",
|
||||
"showFolderSidebar": "폴더 사이드바 표시",
|
||||
"showFolderSidebarHelp": "모델 페이지에서 폴더 탐색 사이드바를 켜거나 끕니다. 비활성화하면 사이드바와 호버 영역이 표시되지 않습니다.",
|
||||
"cardInfoDisplay": "카드 정보 표시",
|
||||
"cardInfoDisplayOptions": {
|
||||
"always": "항상 표시",
|
||||
"hover": "호버 시 표시"
|
||||
},
|
||||
"cardInfoDisplayHelp": "모델 정보 및 액션 버튼을 언제 표시할지 선택하세요:",
|
||||
"cardInfoDisplayDetails": {
|
||||
"always": "항상 표시: 헤더와 푸터가 항상 보입니다",
|
||||
"hover": "호버 시 표시: 카드에 마우스를 올렸을 때만 헤더와 푸터가 나타납니다"
|
||||
}
|
||||
"cardInfoDisplayHelp": "모델 정보 및 액션 버튼을 언제 표시할지 선택하세요",
|
||||
"modelCardFooterAction": "모델 카드 버튼 동작",
|
||||
"modelCardFooterActionOptions": {
|
||||
"exampleImages": "예시 이미지 열기",
|
||||
"replacePreview": "미리보기 교체"
|
||||
},
|
||||
"modelCardFooterActionHelp": "카드 우측 하단 버튼이 수행할 작업을 선택하세요",
|
||||
"modelNameDisplay": "모델명 표시",
|
||||
"modelNameDisplayOptions": {
|
||||
"modelName": "모델명",
|
||||
"fileName": "파일명"
|
||||
},
|
||||
"modelNameDisplayHelp": "모델 카드 하단에 표시할 내용을 선택하세요"
|
||||
},
|
||||
"folderSettings": {
|
||||
"activeLibrary": "활성 라이브러리",
|
||||
"activeLibraryHelp": "구성된 라이브러리를 전환하여 기본 폴더를 업데이트합니다. 선택을 변경하면 페이지가 다시 로드됩니다.",
|
||||
"loadingLibraries": "라이브러리를 불러오는 중...",
|
||||
"noLibraries": "구성된 라이브러리가 없습니다",
|
||||
"defaultLoraRoot": "기본 LoRA 루트",
|
||||
"defaultLoraRootHelp": "다운로드, 가져오기 및 이동을 위한 기본 LoRA 루트 디렉토리를 설정합니다",
|
||||
"defaultCheckpointRoot": "기본 Checkpoint 루트",
|
||||
"defaultCheckpointRootHelp": "다운로드, 가져오기 및 이동을 위한 기본 Checkpoint 루트 디렉토리를 설정합니다",
|
||||
"defaultUnetRoot": "기본 Diffusion Model 루트",
|
||||
"defaultUnetRootHelp": "다운로드, 가져오기 및 이동을 위한 기본 Diffusion Model (UNET) 루트 디렉토리를 설정합니다",
|
||||
"defaultEmbeddingRoot": "기본 Embedding 루트",
|
||||
"defaultEmbeddingRootHelp": "다운로드, 가져오기 및 이동을 위한 기본 Embedding 루트 디렉토리를 설정합니다",
|
||||
"noDefault": "기본값 없음"
|
||||
},
|
||||
"priorityTags": {
|
||||
"title": "우선순위 태그",
|
||||
"description": "모델 유형별 태그 우선순위를 사용자 지정합니다(예: character, concept, style(toon|toon_style)).",
|
||||
"placeholder": "character, concept, style(toon|toon_style)",
|
||||
"helpLinkLabel": "우선순위 태그 도움말 열기",
|
||||
"modelTypes": {
|
||||
"lora": "LoRA",
|
||||
"checkpoint": "체크포인트",
|
||||
"embedding": "임베딩"
|
||||
},
|
||||
"saveSuccess": "우선순위 태그가 업데이트되었습니다.",
|
||||
"saveError": "우선순위 태그를 업데이트하지 못했습니다.",
|
||||
"loadingSuggestions": "추천을 불러오는 중...",
|
||||
"validation": {
|
||||
"missingClosingParen": "{index}번째 항목에 닫는 괄호가 없습니다.",
|
||||
"missingCanonical": "{index}번째 항목에는 정식 태그 이름이 포함되어야 합니다.",
|
||||
"duplicateCanonical": "정식 태그 \"{tag}\"가 여러 번 나타납니다.",
|
||||
"unknown": "잘못된 우선순위 태그 구성입니다."
|
||||
}
|
||||
},
|
||||
"downloadPathTemplates": {
|
||||
"title": "다운로드 경로 템플릿",
|
||||
"help": "Civitai에서 다운로드할 때 다양한 모델 유형의 폴더 구조를 구성합니다.",
|
||||
@@ -289,6 +408,14 @@
|
||||
"download": "다운로드",
|
||||
"restartRequired": "재시작 필요"
|
||||
},
|
||||
"updateFlagStrategy": {
|
||||
"label": "업데이트 표시 전략",
|
||||
"help": "새 릴리스가 로컬 파일과 동일한 베이스 모델을 공유할 때만 업데이트 배지를 표시할지, 또는 해당 모델에 사용 가능한 새 버전이 있으면 항상 표시할지 결정합니다.",
|
||||
"options": {
|
||||
"sameBase": "베이스 모델로 업데이트 일치",
|
||||
"any": "사용 가능한 모든 업데이트 표시"
|
||||
}
|
||||
},
|
||||
"misc": {
|
||||
"includeTriggerWords": "LoRA 문법에 트리거 단어 포함",
|
||||
"includeTriggerWordsHelp": "LoRA 문법을 클립보드에 복사할 때 학습된 트리거 단어를 포함합니다"
|
||||
@@ -348,12 +475,17 @@
|
||||
"dateAsc": "오래된순",
|
||||
"size": "파일 크기",
|
||||
"sizeDesc": "큰 순서",
|
||||
"sizeAsc": "작은 순서"
|
||||
"sizeAsc": "작은 순서",
|
||||
"usage": "사용 횟수",
|
||||
"usageDesc": "많은 순",
|
||||
"usageAsc": "적은 순"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "모델 목록 새로고침",
|
||||
"quick": "빠른 새로고침 (증분)",
|
||||
"full": "전체 재구성 (완전)"
|
||||
"quick": "변경 사항 동기화",
|
||||
"quickTooltip": "새로운 모델 파일이나 누락된 파일을 찾아 목록을 최신 상태로 유지합니다.",
|
||||
"full": "캐시 재구성",
|
||||
"fullTooltip": "메타데이터 파일에서 모든 모델 정보를 다시 불러옵니다. 라이브러리가 오래되어 보이거나 수동 수정 후에 사용하세요."
|
||||
},
|
||||
"fetch": {
|
||||
"title": "Civitai에서 메타데이터 가져오기",
|
||||
@@ -374,6 +506,13 @@
|
||||
"favorites": {
|
||||
"title": "즐겨찾기만 보기",
|
||||
"action": "즐겨찾기"
|
||||
},
|
||||
"updates": {
|
||||
"title": "업데이트 가능한 모델만 표시",
|
||||
"action": "업데이트",
|
||||
"menuLabel": "업데이트 옵션 표시",
|
||||
"check": "업데이트 확인",
|
||||
"checkTooltip": "업데이트 확인에는 시간이 걸릴 수 있습니다."
|
||||
}
|
||||
},
|
||||
"bulkOperations": {
|
||||
@@ -382,8 +521,10 @@
|
||||
"viewSelected": "선택 항목 보기",
|
||||
"addTags": "모두에 태그 추가",
|
||||
"setBaseModel": "모두에 베이스 모델 설정",
|
||||
"setContentRating": "모든 모델에 콘텐츠 등급 설정",
|
||||
"copyAll": "모든 문법 복사",
|
||||
"refreshAll": "모든 메타데이터 새로고침",
|
||||
"checkUpdates": "선택 항목 업데이트 확인",
|
||||
"moveAll": "모두 폴더로 이동",
|
||||
"autoOrganize": "자동 정리 선택",
|
||||
"deleteAll": "모든 모델 삭제",
|
||||
@@ -400,6 +541,7 @@
|
||||
},
|
||||
"contextMenu": {
|
||||
"refreshMetadata": "Civitai 데이터 새로고침",
|
||||
"checkUpdates": "업데이트 확인",
|
||||
"relinkCivitai": "Civitai에 다시 연결",
|
||||
"copySyntax": "LoRA 문법 복사",
|
||||
"copyFilename": "모델 파일명 복사",
|
||||
@@ -411,6 +553,7 @@
|
||||
"replacePreview": "미리보기 교체",
|
||||
"setContentRating": "콘텐츠 등급 설정",
|
||||
"moveToFolder": "폴더로 이동",
|
||||
"repairMetadata": "메타데이터 복구",
|
||||
"excludeModel": "모델 제외",
|
||||
"deleteModel": "모델 삭제",
|
||||
"shareRecipe": "레시피 공유",
|
||||
@@ -421,6 +564,9 @@
|
||||
},
|
||||
"recipes": {
|
||||
"title": "LoRA 레시피",
|
||||
"actions": {
|
||||
"sendCheckpoint": "ComfyUI로 보내기"
|
||||
},
|
||||
"controls": {
|
||||
"import": {
|
||||
"action": "가져오기",
|
||||
@@ -478,10 +624,26 @@
|
||||
"selectLoraRoot": "LoRA 루트 디렉토리를 선택해주세요"
|
||||
}
|
||||
},
|
||||
"sort": {
|
||||
"title": "레시피 정렬...",
|
||||
"name": "이름",
|
||||
"nameAsc": "A - Z",
|
||||
"nameDesc": "Z - A",
|
||||
"date": "날짜",
|
||||
"dateDesc": "최신순",
|
||||
"dateAsc": "오래된순",
|
||||
"lorasCount": "LoRA 수",
|
||||
"lorasCountDesc": "많은순",
|
||||
"lorasCountAsc": "적은순"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "레시피 목록 새로고침"
|
||||
},
|
||||
"filteredByLora": "LoRA로 필터링됨"
|
||||
"filteredByLora": "LoRA로 필터링됨",
|
||||
"favorites": {
|
||||
"title": "즐겨찾기만 표시",
|
||||
"action": "즐겨찾기"
|
||||
}
|
||||
},
|
||||
"duplicates": {
|
||||
"found": "{count}개의 중복 그룹 발견",
|
||||
@@ -507,23 +669,44 @@
|
||||
"noMissingLoras": "다운로드할 누락된 LoRA가 없습니다",
|
||||
"getInfoFailed": "누락된 LoRA 정보를 가져오는데 실패했습니다",
|
||||
"prepareError": "LoRA 다운로드 준비 중 오류: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "레시피 메타데이터 복구 중...",
|
||||
"success": "레시피 메타데이터가 성공적으로 복구되었습니다",
|
||||
"skipped": "레시피가 이미 최신 버전입니다. 복구가 필요하지 않습니다",
|
||||
"failed": "레시피 복구 실패: {message}",
|
||||
"missingId": "레시피를 복구할 수 없음: 레시피 ID 누락"
|
||||
}
|
||||
}
|
||||
},
|
||||
"checkpoints": {
|
||||
"title": "Checkpoint 모델"
|
||||
"title": "Checkpoint 모델",
|
||||
"modelTypes": {
|
||||
"checkpoint": "Checkpoint",
|
||||
"diffusion_model": "Diffusion Model"
|
||||
},
|
||||
"contextMenu": {
|
||||
"moveToOtherTypeFolder": "{otherType} 폴더로 이동"
|
||||
}
|
||||
},
|
||||
"embeddings": {
|
||||
"title": "Embedding 모델"
|
||||
},
|
||||
"sidebar": {
|
||||
"modelRoot": "모델 루트",
|
||||
"modelRoot": "루트",
|
||||
"collapseAll": "모든 폴더 접기",
|
||||
"pinSidebar": "사이드바 고정",
|
||||
"unpinSidebar": "사이드바 고정 해제",
|
||||
"switchToListView": "목록 보기로 전환",
|
||||
"switchToTreeView": "트리 보기로 전환",
|
||||
"collapseAllDisabled": "목록 보기에서는 사용할 수 없습니다"
|
||||
"recursiveOn": "하위 폴더 검색",
|
||||
"recursiveOff": "현재 폴더만 검색",
|
||||
"recursiveUnavailable": "재귀 검색은 트리 보기에서만 사용할 수 있습니다",
|
||||
"collapseAllDisabled": "목록 보기에서는 사용할 수 없습니다",
|
||||
"dragDrop": {
|
||||
"unableToResolveRoot": "이동할 대상 경로를 확인할 수 없습니다.",
|
||||
"moveUnsupported": "Move is not supported for this item."
|
||||
}
|
||||
},
|
||||
"statistics": {
|
||||
"title": "통계",
|
||||
@@ -598,6 +781,14 @@
|
||||
"downloadedPreview": "미리보기 이미지 다운로드됨",
|
||||
"downloadingFile": "{type} 파일 다운로드 중",
|
||||
"finalizing": "다운로드 완료 중..."
|
||||
},
|
||||
"progress": {
|
||||
"currentFile": "현재 파일:",
|
||||
"downloading": "다운로드 중: {name}",
|
||||
"transferred": "다운로드됨: {downloaded} / {total}",
|
||||
"transferredSimple": "다운로드됨: {downloaded}",
|
||||
"transferredUnknown": "다운로드됨: --",
|
||||
"speed": "속도: {speed}"
|
||||
}
|
||||
},
|
||||
"move": {
|
||||
@@ -606,6 +797,7 @@
|
||||
"contentRating": {
|
||||
"title": "콘텐츠 등급 설정",
|
||||
"current": "현재",
|
||||
"multiple": "여러 값",
|
||||
"levels": {
|
||||
"pg": "PG",
|
||||
"pg13": "PG13",
|
||||
@@ -644,6 +836,12 @@
|
||||
"countMessage": "개의 모델이 영구적으로 삭제됩니다.",
|
||||
"action": "모두 삭제"
|
||||
},
|
||||
"checkUpdates": {
|
||||
"title": "{type} 전체 업데이트를 확인할까요?",
|
||||
"message": "라이브러리에 있는 모든 {type}의 업데이트를 확인합니다. 컬렉션이 클수록 시간이 조금 더 걸릴 수 있습니다.",
|
||||
"tip": "나눠서 진행하고 싶다면 벌크 모드로 전환해 필요한 모델만 선택한 뒤 \"선택 항목 업데이트 확인\"을 사용하세요.",
|
||||
"action": "전체 확인"
|
||||
},
|
||||
"bulkAddTags": {
|
||||
"title": "여러 모델에 태그 추가",
|
||||
"description": "다음에 태그를 추가합니다:",
|
||||
@@ -717,7 +915,9 @@
|
||||
},
|
||||
"openFileLocation": {
|
||||
"success": "파일 위치가 성공적으로 열렸습니다",
|
||||
"failed": "파일 위치 열기에 실패했습니다"
|
||||
"failed": "파일 위치 열기에 실패했습니다",
|
||||
"copied": "경로가 클립보드에 복사되었습니다: {{path}}",
|
||||
"clipboardFallback": "경로: {{path}}"
|
||||
},
|
||||
"metadata": {
|
||||
"version": "버전",
|
||||
@@ -740,11 +940,13 @@
|
||||
"addPresetParameter": "프리셋 매개변수 추가...",
|
||||
"strengthMin": "최소 강도",
|
||||
"strengthMax": "최대 강도",
|
||||
"strengthRange": "강도 범위",
|
||||
"strength": "강도",
|
||||
"clipStrength": "클립 강도",
|
||||
"clipSkip": "클립 스킵",
|
||||
"valuePlaceholder": "값",
|
||||
"add": "추가"
|
||||
"add": "추가",
|
||||
"invalidRange": "잘못된 범위 형식입니다. x.x-y.y를 사용하세요"
|
||||
},
|
||||
"triggerWords": {
|
||||
"label": "트리거 단어",
|
||||
@@ -780,13 +982,84 @@
|
||||
"tabs": {
|
||||
"examples": "예시",
|
||||
"description": "모델 설명",
|
||||
"recipes": "레시피"
|
||||
"recipes": "레시피",
|
||||
"versions": "버전"
|
||||
},
|
||||
"navigation": {
|
||||
"label": "모델 탐색",
|
||||
"previousWithShortcut": "이전 모델(←)",
|
||||
"nextWithShortcut": "다음 모델(→)",
|
||||
"noPrevious": "이전 모델이 없습니다",
|
||||
"noNext": "다음 모델이 없습니다"
|
||||
},
|
||||
"license": {
|
||||
"noImageSell": "No selling generated content",
|
||||
"noRentCivit": "No Civitai generation",
|
||||
"noRent": "No generation services",
|
||||
"noSell": "No selling models",
|
||||
"creditRequired": "제작자 크레딧 필요",
|
||||
"noDerivatives": "공유 병합 불가",
|
||||
"noReLicense": "동일한 권한 필요",
|
||||
"restrictionsLabel": "라이선스 제한"
|
||||
},
|
||||
"loading": {
|
||||
"exampleImages": "예시 이미지 로딩 중...",
|
||||
"description": "모델 설명 로딩 중...",
|
||||
"recipes": "레시피 로딩 중...",
|
||||
"examples": "예시 로딩 중..."
|
||||
"examples": "예시 로딩 중...",
|
||||
"versions": "버전 로딩 중..."
|
||||
},
|
||||
"versions": {
|
||||
"heading": "모델 버전",
|
||||
"copy": "이 모델의 모든 버전을 한 곳에서 관리하세요.",
|
||||
"media": {
|
||||
"placeholder": "미리보기 없음"
|
||||
},
|
||||
"labels": {
|
||||
"unnamed": "이름 없는 버전",
|
||||
"noDetails": "추가 정보 없음"
|
||||
},
|
||||
"badges": {
|
||||
"current": "현재 버전",
|
||||
"inLibrary": "라이브러리에 있음",
|
||||
"newer": "최신 버전",
|
||||
"ignored": "무시됨"
|
||||
},
|
||||
"actions": {
|
||||
"download": "다운로드",
|
||||
"delete": "삭제",
|
||||
"ignore": "무시",
|
||||
"unignore": "무시 해제",
|
||||
"resumeModelUpdates": "이 모델 업데이트 재개",
|
||||
"ignoreModelUpdates": "이 모델 업데이트 무시",
|
||||
"viewLocalVersions": "로컬 버전 모두 보기",
|
||||
"viewLocalTooltip": "곧 제공 예정"
|
||||
},
|
||||
"filters": {
|
||||
"label": "기본 필터",
|
||||
"state": {
|
||||
"showAll": "모든 버전",
|
||||
"showSameBase": "같은 베이스"
|
||||
},
|
||||
"tooltip": {
|
||||
"showAllVersions": "모든 버전을 표시하도록 전환",
|
||||
"showSameBaseVersions": "같은 베이스 모델 버전만 표시하도록 전환"
|
||||
},
|
||||
"empty": "현재 베이스 모델 필터와 일치하는 버전이 없습니다."
|
||||
},
|
||||
"empty": "이 모델에는 아직 버전 기록이 없습니다.",
|
||||
"error": "버전을 불러오지 못했습니다.",
|
||||
"missingModelId": "이 모델에는 Civitai 모델 ID가 없습니다.",
|
||||
"confirm": {
|
||||
"delete": "이 버전을 라이브러리에서 삭제하시겠습니까?"
|
||||
},
|
||||
"toast": {
|
||||
"modelIgnored": "이 모델의 업데이트가 무시됩니다",
|
||||
"modelResumed": "업데이트 추적이 재개되었습니다",
|
||||
"versionIgnored": "이 버전의 업데이트가 무시됩니다",
|
||||
"versionUnignored": "버전이 다시 활성화되었습니다",
|
||||
"versionDeleted": "버전이 삭제되었습니다"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -893,7 +1166,9 @@
|
||||
"loraFailedToSend": "LoRA를 워크플로로 전송하지 못했습니다",
|
||||
"recipeAdded": "레시피가 워크플로에 추가되었습니다",
|
||||
"recipeReplaced": "레시피가 워크플로에서 교체되었습니다",
|
||||
"recipeFailedToSend": "레시피를 워크플로로 전송하지 못했습니다"
|
||||
"recipeFailedToSend": "레시피를 워크플로로 전송하지 못했습니다",
|
||||
"noMatchingNodes": "현재 워크플로에서 호환되는 노드가 없습니다",
|
||||
"noTargetNodeSelected": "대상 노드가 선택되지 않았습니다"
|
||||
},
|
||||
"nodeSelector": {
|
||||
"recipe": "레시피",
|
||||
@@ -906,7 +1181,11 @@
|
||||
"exampleImages": {
|
||||
"opened": "예시 이미지 폴더가 열렸습니다",
|
||||
"openingFolder": "예시 이미지 폴더를 여는 중",
|
||||
"failedToOpen": "예시 이미지 폴더 열기 실패"
|
||||
"failedToOpen": "예시 이미지 폴더 열기 실패",
|
||||
"setupRequired": "예시 이미지 저장소",
|
||||
"setupDescription": "사용자 지정 예시 이미지를 추가하려면 먼저 다운로드 위치를 설정해야 합니다.",
|
||||
"setupUsage": "이 경로는 다운로드한 예시 이미지와 사용자 지정 이미지 모두에 사용됩니다.",
|
||||
"openSettings": "설정 열기"
|
||||
}
|
||||
},
|
||||
"help": {
|
||||
@@ -938,6 +1217,11 @@
|
||||
},
|
||||
"update": {
|
||||
"title": "업데이트 확인",
|
||||
"notificationsTitle": "알림 센터",
|
||||
"tabs": {
|
||||
"updates": "업데이트",
|
||||
"messages": "메시지"
|
||||
},
|
||||
"updateAvailable": "업데이트 사용 가능",
|
||||
"noChangelogAvailable": "상세한 변경 로그가 없습니다. 더 많은 정보는 GitHub를 확인하세요.",
|
||||
"currentVersion": "현재 버전",
|
||||
@@ -950,6 +1234,7 @@
|
||||
"checkingUpdates": "업데이트 확인 중...",
|
||||
"checkingMessage": "최신 버전을 확인하는 동안 잠시 기다려주세요.",
|
||||
"showNotifications": "업데이트 알림 표시",
|
||||
"latestBadge": "최신",
|
||||
"updateProgress": {
|
||||
"preparing": "업데이트 준비 중...",
|
||||
"installing": "업데이트 설치 중...",
|
||||
@@ -969,6 +1254,13 @@
|
||||
"nightly": {
|
||||
"warning": "경고: 나이틀리 빌드는 실험적 기능을 포함할 수 있으며 불안정할 수 있습니다.",
|
||||
"enable": "나이틀리 업데이트 활성화"
|
||||
},
|
||||
"banners": {
|
||||
"recent": "최근 알림",
|
||||
"empty": "최근 배너가 없습니다.",
|
||||
"shown": "{time}에 표시",
|
||||
"dismissed": "{time}에 닫힘",
|
||||
"active": "활성"
|
||||
}
|
||||
},
|
||||
"support": {
|
||||
@@ -1048,6 +1340,9 @@
|
||||
"cannotSend": "레시피를 전송할 수 없습니다: 레시피 ID 누락",
|
||||
"sendFailed": "레시피를 워크플로로 전송하는데 실패했습니다",
|
||||
"sendError": "레시피를 워크플로로 전송하는 중 오류",
|
||||
"missingCheckpointPath": "체크포인트 경로를 사용할 수 없습니다",
|
||||
"missingCheckpointInfo": "체크포인트 정보가 부족합니다",
|
||||
"downloadCheckpointFailed": "체크포인트 다운로드 실패: {message}",
|
||||
"cannotDelete": "레시피를 삭제할 수 없습니다: 레시피 ID 누락",
|
||||
"deleteConfirmationError": "삭제 확인 표시 오류",
|
||||
"deletedSuccessfully": "레시피가 성공적으로 삭제되었습니다",
|
||||
@@ -1084,6 +1379,16 @@
|
||||
"bulkBaseModelUpdateSuccess": "{count}개의 모델에 베이스 모델이 성공적으로 업데이트되었습니다",
|
||||
"bulkBaseModelUpdatePartial": "{success}개의 모델이 업데이트되었고, {failed}개의 모델이 실패했습니다",
|
||||
"bulkBaseModelUpdateFailed": "선택한 모델의 베이스 모델 업데이트에 실패했습니다",
|
||||
"bulkContentRatingUpdating": "{count}개 모델의 콘텐츠 등급을 업데이트하는 중...",
|
||||
"bulkContentRatingSet": "{count}개 모델의 콘텐츠 등급을 {level}(으)로 설정했습니다",
|
||||
"bulkContentRatingPartial": "{success}개 모델의 콘텐츠 등급을 {level}(으)로 설정했고, {failed}개는 실패했습니다",
|
||||
"bulkContentRatingFailed": "선택한 모델의 콘텐츠 등급을 업데이트하지 못했습니다",
|
||||
"bulkUpdatesChecking": "선택한 {type}의 업데이트를 확인하는 중...",
|
||||
"bulkUpdatesSuccess": "선택한 {count}개의 {type}에 사용할 수 있는 업데이트가 있습니다",
|
||||
"bulkUpdatesNone": "선택한 {type}에 대한 업데이트가 없습니다",
|
||||
"bulkUpdatesMissing": "선택한 {type}이 Civitai 업데이트에 연결되어 있지 않습니다",
|
||||
"bulkUpdatesPartialMissing": "Civitai 링크가 없는 {missing}개의 {type}을 건너뛰었습니다",
|
||||
"bulkUpdatesFailed": "선택한 {type}의 업데이트 확인에 실패했습니다: {message}",
|
||||
"invalidCharactersRemoved": "파일명에서 잘못된 문자가 제거되었습니다",
|
||||
"filenameCannotBeEmpty": "파일 이름은 비어있을 수 없습니다",
|
||||
"renameFailed": "파일 이름 변경 실패: {message}",
|
||||
@@ -1095,6 +1400,7 @@
|
||||
"verificationCompleteSuccess": "검증 완료. 모든 파일이 중복임을 확인했습니다.",
|
||||
"verificationFailed": "해시 검증 실패: {message}",
|
||||
"noTagsToAdd": "추가할 태그가 없습니다",
|
||||
"bulkTagsUpdating": "{count}개 모델의 태그를 업데이트 중입니다...",
|
||||
"tagsAddedSuccessfully": "{count}개의 {type}에 {tagCount}개의 태그가 성공적으로 추가되었습니다",
|
||||
"tagsReplacedSuccessfully": "{count}개의 {type}의 태그가 {tagCount}개의 태그로 성공적으로 교체되었습니다",
|
||||
"tagsAddFailed": "{count}개의 모델에 태그 추가에 실패했습니다",
|
||||
@@ -1108,6 +1414,7 @@
|
||||
"settings": {
|
||||
"loraRootsFailed": "LoRA 루트 로딩 실패: {message}",
|
||||
"checkpointRootsFailed": "Checkpoint 루트 로딩 실패: {message}",
|
||||
"unetRootsFailed": "Diffusion Model 루트 로딩 실패: {message}",
|
||||
"embeddingRootsFailed": "Embedding 루트 로딩 실패: {message}",
|
||||
"mappingsUpdated": "베이스 모델 경로 매핑이 업데이트되었습니다 ({count}개 매핑)",
|
||||
"mappingsCleared": "베이스 모델 경로 매핑이 지워졌습니다",
|
||||
@@ -1118,6 +1425,8 @@
|
||||
"compactModeToggled": "컴팩트 모드 {state}",
|
||||
"settingSaveFailed": "설정 저장 실패: {message}",
|
||||
"displayDensitySet": "표시 밀도가 {density}로 설정되었습니다",
|
||||
"libraryLoadFailed": "Failed to load libraries: {message}",
|
||||
"libraryActivateFailed": "Failed to activate library: {message}",
|
||||
"languageChangeFailed": "언어 변경 실패: {message}",
|
||||
"cacheCleared": "캐시 파일이 성공적으로 지워졌습니다. 다음 작업 시 캐시가 재구축됩니다.",
|
||||
"cacheClearFailed": "캐시 지우기 실패: {error}",
|
||||
@@ -1126,7 +1435,26 @@
|
||||
"filters": {
|
||||
"applied": "{message}",
|
||||
"cleared": "필터가 지워졌습니다",
|
||||
"noCustomFilterToClear": "지울 사용자 정의 필터가 없습니다"
|
||||
"noCustomFilterToClear": "지울 사용자 정의 필터가 없습니다",
|
||||
"noActiveFilters": "저장할 활성 필터가 없습니다"
|
||||
},
|
||||
"presets": {
|
||||
"created": "프리셋 \"{name}\" 생성됨",
|
||||
"deleted": "프리셋 \"{name}\" 삭제됨",
|
||||
"applied": "프리셋 \"{name}\" 적용됨",
|
||||
"overwritten": "프리셋 \"{name}\" 덮어쓰기 완료",
|
||||
"restored": "기본 프리셋 복원 완료"
|
||||
},
|
||||
"error": {
|
||||
"presetNameEmpty": "프리셋 이름을 입력하세요",
|
||||
"presetNameTooLong": "프리셋 이름은 {max}자 이하여야 합니다",
|
||||
"presetNameInvalidChars": "프리셋 이름에 유효하지 않은 문자가 포함되어 있습니다",
|
||||
"presetNameExists": "동일한 이름의 프리셋이 이미 존재합니다",
|
||||
"maxPresetsReached": "최대 {max}개의 프리셋만 허용됩니다. 더 추가하려면 기존 것을 삭제하세요.",
|
||||
"presetNotFound": "프리셋을 찾을 수 없습니다",
|
||||
"invalidPreset": "잘못된 프리셋 데이터입니다",
|
||||
"deletePresetFailed": "프리셋 삭제에 실패했습니다",
|
||||
"applyPresetFailed": "프리셋 적용에 실패했습니다"
|
||||
},
|
||||
"downloads": {
|
||||
"imagesCompleted": "예시 이미지 {action}이(가) 완료되었습니다",
|
||||
@@ -1142,7 +1470,7 @@
|
||||
},
|
||||
"triggerWords": {
|
||||
"loadFailed": "학습된 단어를 로딩할 수 없습니다",
|
||||
"tooLong": "트리거 단어는 30단어를 초과할 수 없습니다",
|
||||
"tooLong": "트리거 단어는 100단어를 초과할 수 없습니다",
|
||||
"tooMany": "최대 30개의 트리거 단어만 허용됩니다",
|
||||
"alreadyExists": "이 트리거 단어는 이미 존재합니다",
|
||||
"updateSuccess": "트리거 단어가 성공적으로 업데이트되었습니다",
|
||||
@@ -1191,6 +1519,8 @@
|
||||
"pauseFailed": "다운로드 일시정지 실패: {error}",
|
||||
"downloadResumed": "다운로드가 재개되었습니다",
|
||||
"resumeFailed": "다운로드 재개 실패: {error}",
|
||||
"downloadStopped": "다운로드가 취소되었습니다",
|
||||
"stopFailed": "다운로드 취소 실패: {error}",
|
||||
"deleted": "예시 이미지가 삭제되었습니다",
|
||||
"deleteFailed": "예시 이미지 삭제 실패",
|
||||
"setPreviewFailed": "미리보기 이미지 설정 실패"
|
||||
@@ -1211,6 +1541,8 @@
|
||||
"metadataRefreshed": "메타데이터가 성공적으로 새로고침되었습니다",
|
||||
"metadataRefreshFailed": "메타데이터 새로고침 실패: {message}",
|
||||
"metadataUpdateComplete": "메타데이터 업데이트 완료",
|
||||
"operationCancelled": "사용자에 의해 작업이 취소되었습니다",
|
||||
"operationCancelledPartial": "작업이 취소되었습니다. {success}개 항목이 처리되었습니다.",
|
||||
"metadataFetchFailed": "메타데이터 가져오기 실패: {message}",
|
||||
"bulkMetadataCompleteAll": "모든 {count}개 {type}이(가) 성공적으로 새로고침되었습니다",
|
||||
"bulkMetadataCompletePartial": "{total}개 중 {success}개 {type}이(가) 새로고침되었습니다",
|
||||
@@ -1227,7 +1559,8 @@
|
||||
"bulkMoveFailures": "실패한 이동:\n{failures}",
|
||||
"bulkMoveSuccess": "{successCount}개 {type}이(가) 성공적으로 이동되었습니다",
|
||||
"exampleImagesDownloadSuccess": "예시 이미지가 성공적으로 다운로드되었습니다!",
|
||||
"exampleImagesDownloadFailed": "예시 이미지 다운로드 실패: {message}"
|
||||
"exampleImagesDownloadFailed": "예시 이미지 다운로드 실패: {message}",
|
||||
"moveFailed": "Failed to move item: {message}"
|
||||
}
|
||||
},
|
||||
"banners": {
|
||||
@@ -1237,6 +1570,26 @@
|
||||
"refreshNow": "지금 새로고침",
|
||||
"refreshingIn": "새로고침까지",
|
||||
"seconds": "초"
|
||||
},
|
||||
"communitySupport": {
|
||||
"title": "Keep LoRA Manager Thriving with Your Support ❤️",
|
||||
"content": "LoRA Manager is a passion project maintained full-time by a solo developer. Your support on Ko-fi helps cover development costs, keeps new updates coming, and unlocks a license key for the LM Civitai Extension as a thank-you gift. Every contribution truly makes a difference.",
|
||||
"supportCta": "Support on Ko-fi",
|
||||
"learnMore": "LM Civitai Extension Tutorial"
|
||||
},
|
||||
"cacheHealth": {
|
||||
"corrupted": {
|
||||
"title": "캐시 손상이 감지되었습니다"
|
||||
},
|
||||
"degraded": {
|
||||
"title": "캐시 문제가 감지되었습니다"
|
||||
},
|
||||
"content": "{total}개의 캐시 항목 중 {invalid}개가 유효하지 않습니다 ({rate}). 모델 누락이나 오류가 발생할 수 있습니다. 캐시를 재구축하는 것이 좋습니다.",
|
||||
"rebuildCache": "캐시 재구축",
|
||||
"dismiss": "무시",
|
||||
"rebuilding": "캐시 재구축 중...",
|
||||
"rebuildFailed": "캐시 재구축 실패: {error}",
|
||||
"retry": "다시 시도"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
413
locales/ru.json
413
locales/ru.json
@@ -10,7 +10,8 @@
|
||||
"next": "Далее",
|
||||
"backToTop": "Наверх",
|
||||
"settings": "Настройки",
|
||||
"help": "Справка"
|
||||
"help": "Справка",
|
||||
"add": "Добавить"
|
||||
},
|
||||
"status": {
|
||||
"loading": "Загрузка...",
|
||||
@@ -31,7 +32,8 @@
|
||||
"japanese": "日本語",
|
||||
"korean": "한국어",
|
||||
"french": "Français",
|
||||
"spanish": "Español"
|
||||
"spanish": "Español",
|
||||
"Hebrew": "עברית"
|
||||
},
|
||||
"fileSize": {
|
||||
"zero": "0 Байт",
|
||||
@@ -100,7 +102,12 @@
|
||||
"checkpointNameCopied": "Имя checkpoint скопировано",
|
||||
"toggleBlur": "Переключить размытие",
|
||||
"show": "Показать",
|
||||
"openExampleImages": "Открыть папку с примерами"
|
||||
"openExampleImages": "Открыть папку с примерами",
|
||||
"replacePreview": "Заменить превью",
|
||||
"copyCheckpointName": "Копировать имя checkpoint",
|
||||
"copyEmbeddingName": "Копировать имя embedding",
|
||||
"sendCheckpointToWorkflow": "Отправить в ComfyUI",
|
||||
"sendEmbeddingToWorkflow": "Отправить в ComfyUI"
|
||||
},
|
||||
"nsfw": {
|
||||
"matureContent": "Контент для взрослых",
|
||||
@@ -114,12 +121,20 @@
|
||||
"updateFailed": "Не удалось обновить статус избранного"
|
||||
},
|
||||
"sendToWorkflow": {
|
||||
"checkpointNotImplemented": "Отправка checkpoint в workflow - функция будет реализована"
|
||||
"checkpointNotImplemented": "Отправка checkpoint в workflow - функция будет реализована",
|
||||
"missingPath": "Невозможно определить путь модели для этой карточки"
|
||||
},
|
||||
"exampleImages": {
|
||||
"checkError": "Ошибка проверки примеров изображений",
|
||||
"missingHash": "Отсутствует хеш модели.",
|
||||
"noRemoteImagesAvailable": "Нет удаленных примеров изображений для этой модели на Civitai"
|
||||
},
|
||||
"badges": {
|
||||
"update": "Обновление",
|
||||
"updateAvailable": "Доступно обновление"
|
||||
},
|
||||
"usage": {
|
||||
"timesUsed": "Количество использований"
|
||||
}
|
||||
},
|
||||
"globalContextMenu": {
|
||||
@@ -128,12 +143,33 @@
|
||||
"missingPath": "Укажите место загрузки перед загрузкой примеров изображений.",
|
||||
"unavailable": "Загрузка примеров изображений пока недоступна. Попробуйте снова после полной загрузки страницы."
|
||||
},
|
||||
"checkModelUpdates": {
|
||||
"label": "Проверить обновления",
|
||||
"loading": "Проверка обновлений для {type}...",
|
||||
"success": "Найдено {count} обновлений для {type}",
|
||||
"none": "Все {type} актуальны",
|
||||
"error": "Не удалось проверить обновления для {type}: {message}"
|
||||
},
|
||||
"cleanupExampleImages": {
|
||||
"label": "Очистить папки с примерами изображений",
|
||||
"success": "Перемещено {count} папок в папку удалённых",
|
||||
"none": "Нет папок с примерами изображений, требующих очистки",
|
||||
"partial": "Очистка завершена, пропущено {failures} папок",
|
||||
"error": "Не удалось очистить папки с примерами изображений: {message}"
|
||||
},
|
||||
"fetchMissingLicenses": {
|
||||
"label": "Refresh license metadata",
|
||||
"loading": "Refreshing license metadata for {typePlural}...",
|
||||
"success": "Updated license metadata for {count} {typePlural}",
|
||||
"none": "All {typePlural} already have license metadata",
|
||||
"error": "Failed to refresh license metadata for {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Восстановить данные рецептов",
|
||||
"loading": "Восстановление данных рецептов...",
|
||||
"success": "Успешно восстановлено {count} рецептов.",
|
||||
"cancelled": "Восстановление отменено. {count} рецептов было восстановлено.",
|
||||
"error": "Ошибка восстановления рецептов: {message}"
|
||||
}
|
||||
},
|
||||
"header": {
|
||||
@@ -163,14 +199,35 @@
|
||||
"creator": "Автор",
|
||||
"title": "Название рецепта",
|
||||
"loraName": "Имя файла LoRA",
|
||||
"loraModel": "Название модели LoRA"
|
||||
"loraModel": "Название модели LoRA",
|
||||
"prompt": "Запрос"
|
||||
}
|
||||
},
|
||||
"filter": {
|
||||
"title": "Фильтр моделей",
|
||||
"presets": "Пресеты",
|
||||
"savePreset": "Сохранить текущие активные фильтры как новый пресет.",
|
||||
"savePresetDisabledActive": "Невозможно сохранить: Пресет уже активен. Измените фильтры, чтобы сохранить новый пресет",
|
||||
"savePresetDisabledNoFilters": "Сначала выберите фильтры для сохранения как пресет",
|
||||
"savePresetPrompt": "Введите имя пресета:",
|
||||
"presetClickTooltip": "Нажмите чтобы применить пресет \"{name}\"",
|
||||
"presetDeleteTooltip": "Удалить пресет",
|
||||
"presetDeleteConfirm": "Удалить пресет \"{name}\"?",
|
||||
"presetDeleteConfirmClick": "Нажмите еще раз для подтверждения",
|
||||
"presetOverwriteConfirm": "Пресет \"{name}\" уже существует. Перезаписать?",
|
||||
"presetNamePlaceholder": "Имя пресета...",
|
||||
"baseModel": "Базовая модель",
|
||||
"modelTags": "Теги (Топ 20)",
|
||||
"clearAll": "Очистить все фильтры"
|
||||
"modelTypes": "Model Types",
|
||||
"license": "Лицензия",
|
||||
"noCreditRequired": "Без указания авторства",
|
||||
"allowSellingGeneratedContent": "Продажа разрешена",
|
||||
"noTags": "Без тегов",
|
||||
"clearAll": "Очистить все фильтры",
|
||||
"any": "Любой",
|
||||
"all": "Все",
|
||||
"tagLogicAny": "Совпадение с любым тегом (ИЛИ)",
|
||||
"tagLogicAll": "Совпадение со всеми тегами (И)"
|
||||
},
|
||||
"theme": {
|
||||
"toggle": "Переключить тему",
|
||||
@@ -180,6 +237,7 @@
|
||||
},
|
||||
"actions": {
|
||||
"checkUpdates": "Проверить обновления",
|
||||
"notifications": "Уведомления",
|
||||
"support": "Поддержка"
|
||||
}
|
||||
},
|
||||
@@ -187,17 +245,33 @@
|
||||
"civitaiApiKey": "Ключ API Civitai",
|
||||
"civitaiApiKeyPlaceholder": "Введите ваш ключ API Civitai",
|
||||
"civitaiApiKeyHelp": "Используется для аутентификации при загрузке моделей с Civitai",
|
||||
"openSettingsFileLocation": {
|
||||
"label": "Открыть папку настроек",
|
||||
"tooltip": "Открыть папку, содержащую settings.json",
|
||||
"success": "Папка settings.json открыта",
|
||||
"failed": "Не удалось открыть папку settings.json",
|
||||
"copied": "Путь настроек скопирован в буфер обмена: {{path}}",
|
||||
"clipboardFallback": "Путь настроек: {{path}}"
|
||||
},
|
||||
"sections": {
|
||||
"contentFiltering": "Фильтрация контента",
|
||||
"videoSettings": "Настройки видео",
|
||||
"layoutSettings": "Настройки макета",
|
||||
"folderSettings": "Настройки папок",
|
||||
"priorityTags": "Приоритетные теги",
|
||||
"downloadPathTemplates": "Шаблоны путей загрузки",
|
||||
"exampleImages": "Примеры изображений",
|
||||
"updateFlags": "Метки обновлений",
|
||||
"autoOrganize": "Auto-organize",
|
||||
"misc": "Разное",
|
||||
"metadataArchive": "Архив метаданных",
|
||||
"storageLocation": "Расположение настроек",
|
||||
"proxySettings": "Настройки прокси"
|
||||
},
|
||||
"storage": {
|
||||
"locationLabel": "Портативный режим",
|
||||
"locationHelp": "Включите, чтобы хранить settings.json в репозитории; выключите, чтобы сохранить его в папке конфигурации пользователя."
|
||||
},
|
||||
"contentFiltering": {
|
||||
"blurNsfwContent": "Размывать NSFW контент",
|
||||
"blurNsfwContentHelp": "Размывать превью изображений контента для взрослых (NSFW)",
|
||||
@@ -208,6 +282,15 @@
|
||||
"autoplayOnHover": "Автовоспроизведение видео при наведении",
|
||||
"autoplayOnHoverHelp": "Воспроизводить превью видео только при наведении курсора"
|
||||
},
|
||||
"autoOrganizeExclusions": {
|
||||
"label": "Исключения автосортировки",
|
||||
"placeholder": "Пример: curated/*, */backups/*; *_temp.safetensors",
|
||||
"help": "Пропускать перемещение файлов, соответствующих этим шаблонам. Разделяйте несколько шаблонов запятыми или точками с запятой.",
|
||||
"validation": {
|
||||
"noPatterns": "Введите хотя бы один шаблон, разделенный запятыми или точками с запятой.",
|
||||
"saveFailed": "Не удалось сохранить исключения: {message}"
|
||||
}
|
||||
},
|
||||
"layoutSettings": {
|
||||
"displayDensity": "Плотность отображения",
|
||||
"displayDensityOptions": {
|
||||
@@ -217,31 +300,67 @@
|
||||
},
|
||||
"displayDensityHelp": "Выберите количество карточек для отображения в ряду:",
|
||||
"displayDensityDetails": {
|
||||
"default": "По умолчанию: 5 (1080p), 6 (2K), 8 (4K)",
|
||||
"medium": "Средняя: 6 (1080p), 7 (2K), 9 (4K)",
|
||||
"compact": "Компактная: 7 (1080p), 8 (2K), 10 (4K)"
|
||||
"default": "5 (1080p), 6 (2K), 8 (4K)",
|
||||
"medium": "6 (1080p), 7 (2K), 9 (4K)",
|
||||
"compact": "7 (1080p), 8 (2K), 10 (4K)"
|
||||
},
|
||||
"displayDensityWarning": "Предупреждение: Высокая плотность может вызвать проблемы с производительностью на системах с ограниченными ресурсами.",
|
||||
"showFolderSidebar": "Показывать боковую панель папок",
|
||||
"showFolderSidebarHelp": "Включает или выключает боковую панель навигации по папкам на страницах моделей. При отключении панель и область наведения скрыты.",
|
||||
"cardInfoDisplay": "Отображение информации карточки",
|
||||
"cardInfoDisplayOptions": {
|
||||
"always": "Всегда видимо",
|
||||
"hover": "Показать при наведении"
|
||||
},
|
||||
"cardInfoDisplayHelp": "Выберите когда отображать информацию о модели и кнопки действий:",
|
||||
"cardInfoDisplayDetails": {
|
||||
"always": "Всегда видимо: Заголовки и подписи всегда видны",
|
||||
"hover": "Показать при наведении: Заголовки и подписи появляются только при наведении на карточку"
|
||||
}
|
||||
"cardInfoDisplayHelp": "Выберите когда отображать информацию о модели и кнопки действий",
|
||||
"modelCardFooterAction": "Действие кнопки карточки модели",
|
||||
"modelCardFooterActionOptions": {
|
||||
"exampleImages": "Открыть примеры изображений",
|
||||
"replacePreview": "Заменить превью"
|
||||
},
|
||||
"modelCardFooterActionHelp": "Выберите, что делает кнопка в правом нижнем углу карточки",
|
||||
"modelNameDisplay": "Отображение названия модели",
|
||||
"modelNameDisplayOptions": {
|
||||
"modelName": "Название модели",
|
||||
"fileName": "Имя файла"
|
||||
},
|
||||
"modelNameDisplayHelp": "Выберите, что отображать в нижней части карточки модели"
|
||||
},
|
||||
"folderSettings": {
|
||||
"activeLibrary": "Активная библиотека",
|
||||
"activeLibraryHelp": "Переключайтесь между настроенными библиотеками, чтобы обновить папки по умолчанию. Изменение выбора перезагружает страницу.",
|
||||
"loadingLibraries": "Загрузка библиотек...",
|
||||
"noLibraries": "Библиотеки не настроены",
|
||||
"defaultLoraRoot": "Корневая папка LoRA по умолчанию",
|
||||
"defaultLoraRootHelp": "Установить корневую папку LoRA по умолчанию для загрузок, импорта и перемещений",
|
||||
"defaultCheckpointRoot": "Корневая папка Checkpoint по умолчанию",
|
||||
"defaultCheckpointRootHelp": "Установить корневую папку checkpoint по умолчанию для загрузок, импорта и перемещений",
|
||||
"defaultUnetRoot": "Корневая папка Diffusion Model по умолчанию",
|
||||
"defaultUnetRootHelp": "Установить корневую папку Diffusion Model (UNET) по умолчанию для загрузок, импорта и перемещений",
|
||||
"defaultEmbeddingRoot": "Корневая папка Embedding по умолчанию",
|
||||
"defaultEmbeddingRootHelp": "Установить корневую папку embedding по умолчанию для загрузок, импорта и перемещений",
|
||||
"noDefault": "Не задано"
|
||||
},
|
||||
"priorityTags": {
|
||||
"title": "Приоритетные теги",
|
||||
"description": "Настройте порядок приоритетов тегов для каждого типа моделей (например, character, concept, style(toon|toon_style)).",
|
||||
"placeholder": "character, concept, style(toon|toon_style)",
|
||||
"helpLinkLabel": "Открыть справку по приоритетным тегам",
|
||||
"modelTypes": {
|
||||
"lora": "LoRA",
|
||||
"checkpoint": "Чекпойнт",
|
||||
"embedding": "Эмбеддинг"
|
||||
},
|
||||
"saveSuccess": "Приоритетные теги обновлены.",
|
||||
"saveError": "Не удалось обновить приоритетные теги.",
|
||||
"loadingSuggestions": "Загрузка подсказок...",
|
||||
"validation": {
|
||||
"missingClosingParen": "В записи {index} отсутствует закрывающая скобка.",
|
||||
"missingCanonical": "Запись {index} должна содержать каноническое имя тега.",
|
||||
"duplicateCanonical": "Канонический тег \"{tag}\" встречается более одного раза.",
|
||||
"unknown": "Недопустимая конфигурация приоритетных тегов."
|
||||
}
|
||||
},
|
||||
"downloadPathTemplates": {
|
||||
"title": "Шаблоны путей загрузки",
|
||||
"help": "Настройте структуру папок для разных типов моделей при загрузке с Civitai.",
|
||||
@@ -289,6 +408,14 @@
|
||||
"download": "Загрузить",
|
||||
"restartRequired": "Требует перезапуска"
|
||||
},
|
||||
"updateFlagStrategy": {
|
||||
"label": "Стратегия меток обновлений",
|
||||
"help": "Выберите, отображать ли значки обновления только когда новая версия имеет тот же базовый модель, что и локальные файлы, или всегда при наличии любого нового релиза для этой модели.",
|
||||
"options": {
|
||||
"sameBase": "Совпадение обновлений по базовой модели",
|
||||
"any": "Отмечать любые доступные обновления"
|
||||
}
|
||||
},
|
||||
"misc": {
|
||||
"includeTriggerWords": "Включать триггерные слова в синтаксис LoRA",
|
||||
"includeTriggerWordsHelp": "Включать обученные триггерные слова при копировании синтаксиса LoRA в буфер обмена"
|
||||
@@ -348,12 +475,17 @@
|
||||
"dateAsc": "Старейшим",
|
||||
"size": "Размеру файла",
|
||||
"sizeDesc": "Наибольшим",
|
||||
"sizeAsc": "Наименьшим"
|
||||
"sizeAsc": "Наименьшим",
|
||||
"usage": "Число использований",
|
||||
"usageDesc": "Больше",
|
||||
"usageAsc": "Меньше"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "Обновить список моделей",
|
||||
"quick": "Быстрое обновление (инкрементальное)",
|
||||
"full": "Полная перестройка (полное)"
|
||||
"quick": "Синхронизировать изменения",
|
||||
"quickTooltip": "Находит новые или отсутствующие файлы моделей, чтобы список оставался актуальным.",
|
||||
"full": "Перестроить кэш",
|
||||
"fullTooltip": "Перечитывает все данные моделей из файлов метаданных — используйте, если библиотека выглядит устаревшей или после ручных правок."
|
||||
},
|
||||
"fetch": {
|
||||
"title": "Получить метаданные с Civitai",
|
||||
@@ -374,6 +506,13 @@
|
||||
"favorites": {
|
||||
"title": "Показать только избранное",
|
||||
"action": "Избранное"
|
||||
},
|
||||
"updates": {
|
||||
"title": "Показывать только модели с доступными обновлениями",
|
||||
"action": "Обновления",
|
||||
"menuLabel": "Показать параметры обновления",
|
||||
"check": "Проверить обновления",
|
||||
"checkTooltip": "Проверка может занять время."
|
||||
}
|
||||
},
|
||||
"bulkOperations": {
|
||||
@@ -382,8 +521,10 @@
|
||||
"viewSelected": "Просмотреть выбранные",
|
||||
"addTags": "Добавить теги ко всем",
|
||||
"setBaseModel": "Установить базовую модель для всех",
|
||||
"setContentRating": "Установить рейтинг контента для всех",
|
||||
"copyAll": "Копировать весь синтаксис",
|
||||
"refreshAll": "Обновить все метаданные",
|
||||
"checkUpdates": "Проверить обновления для выбранных",
|
||||
"moveAll": "Переместить все в папку",
|
||||
"autoOrganize": "Автоматически организовать выбранные",
|
||||
"deleteAll": "Удалить все модели",
|
||||
@@ -400,6 +541,7 @@
|
||||
},
|
||||
"contextMenu": {
|
||||
"refreshMetadata": "Обновить данные Civitai",
|
||||
"checkUpdates": "Проверить обновления",
|
||||
"relinkCivitai": "Пересвязать с Civitai",
|
||||
"copySyntax": "Копировать синтаксис LoRA",
|
||||
"copyFilename": "Копировать имя файла модели",
|
||||
@@ -411,6 +553,7 @@
|
||||
"replacePreview": "Заменить превью",
|
||||
"setContentRating": "Установить рейтинг контента",
|
||||
"moveToFolder": "Переместить в папку",
|
||||
"repairMetadata": "Восстановить метаданные",
|
||||
"excludeModel": "Исключить модель",
|
||||
"deleteModel": "Удалить модель",
|
||||
"shareRecipe": "Поделиться рецептом",
|
||||
@@ -421,6 +564,9 @@
|
||||
},
|
||||
"recipes": {
|
||||
"title": "Рецепты LoRA",
|
||||
"actions": {
|
||||
"sendCheckpoint": "Отправить в ComfyUI"
|
||||
},
|
||||
"controls": {
|
||||
"import": {
|
||||
"action": "Импортировать",
|
||||
@@ -478,10 +624,26 @@
|
||||
"selectLoraRoot": "Пожалуйста, выберите корневую папку LoRA"
|
||||
}
|
||||
},
|
||||
"sort": {
|
||||
"title": "Сортировка рецептов...",
|
||||
"name": "Имя",
|
||||
"nameAsc": "А - Я",
|
||||
"nameDesc": "Я - А",
|
||||
"date": "Дата",
|
||||
"dateDesc": "Сначала новые",
|
||||
"dateAsc": "Сначала старые",
|
||||
"lorasCount": "Кол-во LoRA",
|
||||
"lorasCountDesc": "Больше всего",
|
||||
"lorasCountAsc": "Меньше всего"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "Обновить список рецептов"
|
||||
},
|
||||
"filteredByLora": "Фильтр по LoRA"
|
||||
"filteredByLora": "Фильтр по LoRA",
|
||||
"favorites": {
|
||||
"title": "Только избранные",
|
||||
"action": "Избранное"
|
||||
}
|
||||
},
|
||||
"duplicates": {
|
||||
"found": "Найдено {count} групп дубликатов",
|
||||
@@ -507,23 +669,44 @@
|
||||
"noMissingLoras": "Нет отсутствующих LoRAs для загрузки",
|
||||
"getInfoFailed": "Не удалось получить информацию для отсутствующих LoRAs",
|
||||
"prepareError": "Ошибка подготовки LoRAs для загрузки: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "Восстановление метаданных рецепта...",
|
||||
"success": "Метаданные рецепта успешно восстановлены",
|
||||
"skipped": "Рецепт уже последней версии, восстановление не требуется",
|
||||
"failed": "Не удалось восстановить рецепт: {message}",
|
||||
"missingId": "Не удалось восстановить рецепт: отсутствует ID рецепта"
|
||||
}
|
||||
}
|
||||
},
|
||||
"checkpoints": {
|
||||
"title": "Модели Checkpoint"
|
||||
"title": "Модели Checkpoint",
|
||||
"modelTypes": {
|
||||
"checkpoint": "Checkpoint",
|
||||
"diffusion_model": "Diffusion Model"
|
||||
},
|
||||
"contextMenu": {
|
||||
"moveToOtherTypeFolder": "Переместить в папку {otherType}"
|
||||
}
|
||||
},
|
||||
"embeddings": {
|
||||
"title": "Модели Embedding"
|
||||
},
|
||||
"sidebar": {
|
||||
"modelRoot": "Корень моделей",
|
||||
"modelRoot": "Корень",
|
||||
"collapseAll": "Свернуть все папки",
|
||||
"pinSidebar": "Закрепить боковую панель",
|
||||
"unpinSidebar": "Открепить боковую панель",
|
||||
"switchToListView": "Переключить на вид списка",
|
||||
"switchToTreeView": "Переключить на древовидный вид",
|
||||
"collapseAllDisabled": "Недоступно в виде списка"
|
||||
"recursiveOn": "Искать во вложенных папках",
|
||||
"recursiveOff": "Искать только в текущей папке",
|
||||
"recursiveUnavailable": "Рекурсивный поиск доступен только в режиме дерева",
|
||||
"collapseAllDisabled": "Недоступно в виде списка",
|
||||
"dragDrop": {
|
||||
"unableToResolveRoot": "Не удалось определить путь назначения для перемещения.",
|
||||
"moveUnsupported": "Move is not supported for this item."
|
||||
}
|
||||
},
|
||||
"statistics": {
|
||||
"title": "Статистика",
|
||||
@@ -598,6 +781,14 @@
|
||||
"downloadedPreview": "Превью изображение загружено",
|
||||
"downloadingFile": "Загрузка файла {type}",
|
||||
"finalizing": "Завершение загрузки..."
|
||||
},
|
||||
"progress": {
|
||||
"currentFile": "Текущий файл:",
|
||||
"downloading": "Скачивается: {name}",
|
||||
"transferred": "Скачано: {downloaded} / {total}",
|
||||
"transferredSimple": "Скачано: {downloaded}",
|
||||
"transferredUnknown": "Скачано: --",
|
||||
"speed": "Скорость: {speed}"
|
||||
}
|
||||
},
|
||||
"move": {
|
||||
@@ -606,6 +797,7 @@
|
||||
"contentRating": {
|
||||
"title": "Установить рейтинг контента",
|
||||
"current": "Текущий",
|
||||
"multiple": "Несколько значений",
|
||||
"levels": {
|
||||
"pg": "PG",
|
||||
"pg13": "PG13",
|
||||
@@ -644,6 +836,12 @@
|
||||
"countMessage": "моделей будут удалены навсегда.",
|
||||
"action": "Удалить все"
|
||||
},
|
||||
"checkUpdates": {
|
||||
"title": "Проверить обновления для всех {typePlural}?",
|
||||
"message": "Будут проверены обновления для всех {typePlural} в вашей библиотеке. Для больших коллекций это может занять немного больше времени.",
|
||||
"tip": "Хотите проверять по частям? Переключитесь в массовый режим, выберите нужные модели и используйте \"Проверить обновления для выбранных\".",
|
||||
"action": "Проверить всё"
|
||||
},
|
||||
"bulkAddTags": {
|
||||
"title": "Добавить теги к нескольким моделям",
|
||||
"description": "Добавить теги к",
|
||||
@@ -717,7 +915,9 @@
|
||||
},
|
||||
"openFileLocation": {
|
||||
"success": "Расположение файла успешно открыто",
|
||||
"failed": "Не удалось открыть расположение файла"
|
||||
"failed": "Не удалось открыть расположение файла",
|
||||
"copied": "Путь скопирован в буфер обмена: {{path}}",
|
||||
"clipboardFallback": "Путь: {{path}}"
|
||||
},
|
||||
"metadata": {
|
||||
"version": "Версия",
|
||||
@@ -740,11 +940,13 @@
|
||||
"addPresetParameter": "Добавить предустановленный параметр...",
|
||||
"strengthMin": "Мин. сила",
|
||||
"strengthMax": "Макс. сила",
|
||||
"strengthRange": "Диапазон силы",
|
||||
"strength": "Сила",
|
||||
"clipStrength": "Сила клипа",
|
||||
"clipSkip": "Clip Skip",
|
||||
"valuePlaceholder": "Значение",
|
||||
"add": "Добавить"
|
||||
"add": "Добавить",
|
||||
"invalidRange": "Неверный формат диапазона. Используйте x.x-y.y"
|
||||
},
|
||||
"triggerWords": {
|
||||
"label": "Триггерные слова",
|
||||
@@ -780,13 +982,84 @@
|
||||
"tabs": {
|
||||
"examples": "Примеры",
|
||||
"description": "Описание модели",
|
||||
"recipes": "Рецепты"
|
||||
"recipes": "Рецепты",
|
||||
"versions": "Версии"
|
||||
},
|
||||
"navigation": {
|
||||
"label": "Навигация по моделям",
|
||||
"previousWithShortcut": "Предыдущая модель (←)",
|
||||
"nextWithShortcut": "Следующая модель (→)",
|
||||
"noPrevious": "Предыдущая модель отсутствует",
|
||||
"noNext": "Следующая модель отсутствует"
|
||||
},
|
||||
"license": {
|
||||
"noImageSell": "No selling generated content",
|
||||
"noRentCivit": "No Civitai generation",
|
||||
"noRent": "No generation services",
|
||||
"noSell": "No selling models",
|
||||
"creditRequired": "Требуется указание авторства",
|
||||
"noDerivatives": "Запрет на совместное использование производных работ",
|
||||
"noReLicense": "Требуются те же права",
|
||||
"restrictionsLabel": "Лицензионные ограничения"
|
||||
},
|
||||
"loading": {
|
||||
"exampleImages": "Загрузка примеров изображений...",
|
||||
"description": "Загрузка описания модели...",
|
||||
"recipes": "Загрузка рецептов...",
|
||||
"examples": "Загрузка примеров..."
|
||||
"examples": "Загрузка примеров...",
|
||||
"versions": "Загрузка версий..."
|
||||
},
|
||||
"versions": {
|
||||
"heading": "Версии модели",
|
||||
"copy": "Управляйте всеми версиями этой модели в одном месте.",
|
||||
"media": {
|
||||
"placeholder": "Нет превью"
|
||||
},
|
||||
"labels": {
|
||||
"unnamed": "Версия без названия",
|
||||
"noDetails": "Дополнительная информация отсутствует"
|
||||
},
|
||||
"badges": {
|
||||
"current": "Текущая версия",
|
||||
"inLibrary": "В библиотеке",
|
||||
"newer": "Более новая версия",
|
||||
"ignored": "Игнорируется"
|
||||
},
|
||||
"actions": {
|
||||
"download": "Скачать",
|
||||
"delete": "Удалить",
|
||||
"ignore": "Игнорировать",
|
||||
"unignore": "Перестать игнорировать",
|
||||
"resumeModelUpdates": "Возобновить обновления для этой модели",
|
||||
"ignoreModelUpdates": "Игнорировать обновления для этой модели",
|
||||
"viewLocalVersions": "Показать все локальные версии",
|
||||
"viewLocalTooltip": "Скоро появится"
|
||||
},
|
||||
"filters": {
|
||||
"label": "Фильтр по базе",
|
||||
"state": {
|
||||
"showAll": "Все версии",
|
||||
"showSameBase": "Тот же базовый"
|
||||
},
|
||||
"tooltip": {
|
||||
"showAllVersions": "Переключиться на отображение всех версий",
|
||||
"showSameBaseVersions": "Переключиться на отображение только версий с тем же базовым"
|
||||
},
|
||||
"empty": "Нет версий, соответствующих текущему фильтру базовой модели."
|
||||
},
|
||||
"empty": "Для этой модели пока нет истории версий.",
|
||||
"error": "Не удалось загрузить версии.",
|
||||
"missingModelId": "У этой модели отсутствует идентификатор модели Civitai.",
|
||||
"confirm": {
|
||||
"delete": "Удалить эту версию из библиотеки?"
|
||||
},
|
||||
"toast": {
|
||||
"modelIgnored": "Обновления для этой модели игнорируются",
|
||||
"modelResumed": "Отслеживание обновлений возобновлено",
|
||||
"versionIgnored": "Обновления для этой версии игнорируются",
|
||||
"versionUnignored": "Версия снова активна",
|
||||
"versionDeleted": "Версия удалена"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -893,7 +1166,9 @@
|
||||
"loraFailedToSend": "Не удалось отправить LoRA в workflow",
|
||||
"recipeAdded": "Рецепт добавлен в workflow",
|
||||
"recipeReplaced": "Рецепт заменён в workflow",
|
||||
"recipeFailedToSend": "Не удалось отправить рецепт в workflow"
|
||||
"recipeFailedToSend": "Не удалось отправить рецепт в workflow",
|
||||
"noMatchingNodes": "В текущем workflow нет совместимых узлов",
|
||||
"noTargetNodeSelected": "Целевой узел не выбран"
|
||||
},
|
||||
"nodeSelector": {
|
||||
"recipe": "Рецепт",
|
||||
@@ -906,7 +1181,11 @@
|
||||
"exampleImages": {
|
||||
"opened": "Папка с примерами изображений открыта",
|
||||
"openingFolder": "Открытие папки с примерами изображений",
|
||||
"failedToOpen": "Не удалось открыть папку с примерами изображений"
|
||||
"failedToOpen": "Не удалось открыть папку с примерами изображений",
|
||||
"setupRequired": "Хранилище примеров изображений",
|
||||
"setupDescription": "Чтобы добавить собственные примеры изображений, сначала нужно установить место загрузки.",
|
||||
"setupUsage": "Этот путь используется как для загруженных, так и для пользовательских примеров изображений.",
|
||||
"openSettings": "Открыть настройки"
|
||||
}
|
||||
},
|
||||
"help": {
|
||||
@@ -938,6 +1217,11 @@
|
||||
},
|
||||
"update": {
|
||||
"title": "Проверить обновления",
|
||||
"notificationsTitle": "Центр уведомлений",
|
||||
"tabs": {
|
||||
"updates": "Обновления",
|
||||
"messages": "Сообщения"
|
||||
},
|
||||
"updateAvailable": "Доступно обновление",
|
||||
"noChangelogAvailable": "Подробный список изменений недоступен. Проверьте GitHub для получения дополнительной информации.",
|
||||
"currentVersion": "Текущая версия",
|
||||
@@ -950,6 +1234,7 @@
|
||||
"checkingUpdates": "Проверка обновлений...",
|
||||
"checkingMessage": "Пожалуйста, подождите, пока мы проверяем последнюю версию.",
|
||||
"showNotifications": "Показывать уведомления об обновлениях",
|
||||
"latestBadge": "Последний",
|
||||
"updateProgress": {
|
||||
"preparing": "Подготовка обновления...",
|
||||
"installing": "Установка обновления...",
|
||||
@@ -969,6 +1254,13 @@
|
||||
"nightly": {
|
||||
"warning": "Предупреждение: Ночные сборки могут содержать экспериментальные функции и могут быть нестабильными.",
|
||||
"enable": "Включить ночные обновления"
|
||||
},
|
||||
"banners": {
|
||||
"recent": "Недавние уведомления",
|
||||
"empty": "Недавних баннеров нет.",
|
||||
"shown": "Показано {time}",
|
||||
"dismissed": "Закрыто {time}",
|
||||
"active": "Активно"
|
||||
}
|
||||
},
|
||||
"support": {
|
||||
@@ -1048,6 +1340,9 @@
|
||||
"cannotSend": "Невозможно отправить рецепт: отсутствует ID рецепта",
|
||||
"sendFailed": "Не удалось отправить рецепт в workflow",
|
||||
"sendError": "Ошибка отправки рецепта в workflow",
|
||||
"missingCheckpointPath": "Путь к чекпойнту недоступен",
|
||||
"missingCheckpointInfo": "Отсутствуют данные о чекпойнте",
|
||||
"downloadCheckpointFailed": "Не удалось скачать чекпойнт: {message}",
|
||||
"cannotDelete": "Невозможно удалить рецепт: отсутствует ID рецепта",
|
||||
"deleteConfirmationError": "Ошибка отображения подтверждения удаления",
|
||||
"deletedSuccessfully": "Рецепт успешно удален",
|
||||
@@ -1084,6 +1379,16 @@
|
||||
"bulkBaseModelUpdateSuccess": "Базовая модель успешно обновлена для {count} моделей",
|
||||
"bulkBaseModelUpdatePartial": "Обновлено {success} моделей, не удалось обновить {failed} моделей",
|
||||
"bulkBaseModelUpdateFailed": "Не удалось обновить базовую модель для выбранных моделей",
|
||||
"bulkContentRatingUpdating": "Обновление рейтинга контента для {count} модель(ей)...",
|
||||
"bulkContentRatingSet": "Рейтинг контента установлен на {level} для {count} модель(ей)",
|
||||
"bulkContentRatingPartial": "Рейтинг контента {level} установлен для {success} модель(ей), {failed} не удалось",
|
||||
"bulkContentRatingFailed": "Не удалось обновить рейтинг контента для выбранных моделей",
|
||||
"bulkUpdatesChecking": "Проверка обновлений для выбранных {type}...",
|
||||
"bulkUpdatesSuccess": "Доступны обновления для {count} выбранных {type}",
|
||||
"bulkUpdatesNone": "Обновления для выбранных {type} не найдены",
|
||||
"bulkUpdatesMissing": "Выбранные {type} не привязаны к обновлениям Civitai",
|
||||
"bulkUpdatesPartialMissing": "Пропущено {missing} выбранных {type} без привязки Civitai",
|
||||
"bulkUpdatesFailed": "Не удалось проверить обновления для выбранных {type}: {message}",
|
||||
"invalidCharactersRemoved": "Недопустимые символы удалены из имени файла",
|
||||
"filenameCannotBeEmpty": "Имя файла не может быть пустым",
|
||||
"renameFailed": "Не удалось переименовать файл: {message}",
|
||||
@@ -1095,6 +1400,7 @@
|
||||
"verificationCompleteSuccess": "Проверка завершена. Все файлы подтверждены как дубликаты.",
|
||||
"verificationFailed": "Не удалось проверить хеши: {message}",
|
||||
"noTagsToAdd": "Нет тегов для добавления",
|
||||
"bulkTagsUpdating": "Обновление тегов для {count} модел(ей)...",
|
||||
"tagsAddedSuccessfully": "Успешно добавлено {tagCount} тег(ов) к {count} {type}(ам)",
|
||||
"tagsReplacedSuccessfully": "Успешно заменены теги для {count} {type}(ов) на {tagCount} тег(ов)",
|
||||
"tagsAddFailed": "Не удалось добавить теги к {count} модель(ям)",
|
||||
@@ -1108,6 +1414,7 @@
|
||||
"settings": {
|
||||
"loraRootsFailed": "Не удалось загрузить корни LoRA: {message}",
|
||||
"checkpointRootsFailed": "Не удалось загрузить корни checkpoint: {message}",
|
||||
"unetRootsFailed": "Не удалось загрузить корни Diffusion Model: {message}",
|
||||
"embeddingRootsFailed": "Не удалось загрузить корни embedding: {message}",
|
||||
"mappingsUpdated": "Сопоставления путей базовых моделей обновлены ({count} сопоставлени{plural})",
|
||||
"mappingsCleared": "Сопоставления путей базовых моделей очищены",
|
||||
@@ -1118,6 +1425,8 @@
|
||||
"compactModeToggled": "Компактный режим {state}",
|
||||
"settingSaveFailed": "Не удалось сохранить настройку: {message}",
|
||||
"displayDensitySet": "Плотность отображения установлена на {density}",
|
||||
"libraryLoadFailed": "Failed to load libraries: {message}",
|
||||
"libraryActivateFailed": "Failed to activate library: {message}",
|
||||
"languageChangeFailed": "Не удалось изменить язык: {message}",
|
||||
"cacheCleared": "Файлы кэша успешно очищены. Кэш будет пересобран при следующем действии.",
|
||||
"cacheClearFailed": "Не удалось очистить кэш: {error}",
|
||||
@@ -1126,7 +1435,26 @@
|
||||
"filters": {
|
||||
"applied": "{message}",
|
||||
"cleared": "Фильтры очищены",
|
||||
"noCustomFilterToClear": "Нет пользовательского фильтра для очистки"
|
||||
"noCustomFilterToClear": "Нет пользовательского фильтра для очистки",
|
||||
"noActiveFilters": "Нет активных фильтров для сохранения"
|
||||
},
|
||||
"presets": {
|
||||
"created": "Пресет \"{name}\" создан",
|
||||
"deleted": "Пресет \"{name}\" удален",
|
||||
"applied": "Пресет \"{name}\" применен",
|
||||
"overwritten": "Пресет \"{name}\" перезаписан",
|
||||
"restored": "Пресеты по умолчанию восстановлены"
|
||||
},
|
||||
"error": {
|
||||
"presetNameEmpty": "Имя пресета не может быть пустым",
|
||||
"presetNameTooLong": "Имя пресета должно содержать не более {max} символов",
|
||||
"presetNameInvalidChars": "Имя пресета содержит недопустимые символы",
|
||||
"presetNameExists": "Пресет с таким именем уже существует",
|
||||
"maxPresetsReached": "Допустимо максимум {max} пресетов. Удалите один, чтобы добавить больше.",
|
||||
"presetNotFound": "Пресет не найден",
|
||||
"invalidPreset": "Недопустимые данные пресета",
|
||||
"deletePresetFailed": "Не удалось удалить пресет",
|
||||
"applyPresetFailed": "Не удалось применить пресет"
|
||||
},
|
||||
"downloads": {
|
||||
"imagesCompleted": "Примеры изображений {action} завершены",
|
||||
@@ -1142,7 +1470,7 @@
|
||||
},
|
||||
"triggerWords": {
|
||||
"loadFailed": "Не удалось загрузить обученные слова",
|
||||
"tooLong": "Триггерное слово не должно превышать 30 слов",
|
||||
"tooLong": "Триггерное слово не должно превышать 100 слов",
|
||||
"tooMany": "Максимум 30 триггерных слов разрешено",
|
||||
"alreadyExists": "Это триггерное слово уже существует",
|
||||
"updateSuccess": "Триггерные слова успешно обновлены",
|
||||
@@ -1191,6 +1519,8 @@
|
||||
"pauseFailed": "Не удалось приостановить загрузку: {error}",
|
||||
"downloadResumed": "Загрузка возобновлена",
|
||||
"resumeFailed": "Не удалось возобновить загрузку: {error}",
|
||||
"downloadStopped": "Загрузка отменена",
|
||||
"stopFailed": "Не удалось отменить загрузку: {error}",
|
||||
"deleted": "Пример изображения удален",
|
||||
"deleteFailed": "Не удалось удалить пример изображения",
|
||||
"setPreviewFailed": "Не удалось установить превью изображение"
|
||||
@@ -1211,6 +1541,8 @@
|
||||
"metadataRefreshed": "Метаданные успешно обновлены",
|
||||
"metadataRefreshFailed": "Не удалось обновить метаданные: {message}",
|
||||
"metadataUpdateComplete": "Обновление метаданных завершено",
|
||||
"operationCancelled": "Операция отменена пользователем",
|
||||
"operationCancelledPartial": "Операция отменена. Обработано {success} элементов.",
|
||||
"metadataFetchFailed": "Не удалось получить метаданные: {message}",
|
||||
"bulkMetadataCompleteAll": "Успешно обновлены все {count} {type}s",
|
||||
"bulkMetadataCompletePartial": "Обновлено {success} из {total} {type}s",
|
||||
@@ -1227,7 +1559,8 @@
|
||||
"bulkMoveFailures": "Неудачные перемещения:\n{failures}",
|
||||
"bulkMoveSuccess": "Успешно перемещено {successCount} {type}s",
|
||||
"exampleImagesDownloadSuccess": "Примеры изображений успешно загружены!",
|
||||
"exampleImagesDownloadFailed": "Не удалось загрузить примеры изображений: {message}"
|
||||
"exampleImagesDownloadFailed": "Не удалось загрузить примеры изображений: {message}",
|
||||
"moveFailed": "Failed to move item: {message}"
|
||||
}
|
||||
},
|
||||
"banners": {
|
||||
@@ -1237,6 +1570,26 @@
|
||||
"refreshNow": "Обновить сейчас",
|
||||
"refreshingIn": "Обновление через",
|
||||
"seconds": "секунд"
|
||||
},
|
||||
"communitySupport": {
|
||||
"title": "Keep LoRA Manager Thriving with Your Support ❤️",
|
||||
"content": "LoRA Manager is a passion project maintained full-time by a solo developer. Your support on Ko-fi helps cover development costs, keeps new updates coming, and unlocks a license key for the LM Civitai Extension as a thank-you gift. Every contribution truly makes a difference.",
|
||||
"supportCta": "Support on Ko-fi",
|
||||
"learnMore": "LM Civitai Extension Tutorial"
|
||||
},
|
||||
"cacheHealth": {
|
||||
"corrupted": {
|
||||
"title": "Обнаружено повреждение кэша"
|
||||
},
|
||||
"degraded": {
|
||||
"title": "Обнаружены проблемы с кэшем"
|
||||
},
|
||||
"content": "{invalid} из {total} записей кэша недействительны ({rate}). Это может привести к отсутствию моделей или ошибкам. Рекомендуется перестроить кэш.",
|
||||
"rebuildCache": "Перестроить кэш",
|
||||
"dismiss": "Отклонить",
|
||||
"rebuilding": "Перестроение кэша...",
|
||||
"rebuildFailed": "Не удалось перестроить кэш: {error}",
|
||||
"retry": "Повторить"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -10,7 +10,8 @@
|
||||
"next": "下一步",
|
||||
"backToTop": "返回顶部",
|
||||
"settings": "设置",
|
||||
"help": "帮助"
|
||||
"help": "帮助",
|
||||
"add": "添加"
|
||||
},
|
||||
"status": {
|
||||
"loading": "加载中...",
|
||||
@@ -21,8 +22,8 @@
|
||||
"disabled": "已禁用"
|
||||
},
|
||||
"language": {
|
||||
"select": "Language",
|
||||
"select_help": "Choose your preferred language for the interface",
|
||||
"select": "选择语言",
|
||||
"select_help": "选择你喜欢的界面语言",
|
||||
"english": "English",
|
||||
"chinese_simplified": "中文(简体)",
|
||||
"chinese_traditional": "中文(繁体)",
|
||||
@@ -31,7 +32,8 @@
|
||||
"japanese": "日本語",
|
||||
"korean": "한국어",
|
||||
"french": "Français",
|
||||
"spanish": "Español"
|
||||
"spanish": "Español",
|
||||
"Hebrew": "עברית"
|
||||
},
|
||||
"fileSize": {
|
||||
"zero": "0 字节",
|
||||
@@ -100,7 +102,12 @@
|
||||
"checkpointNameCopied": "检查点名称已复制",
|
||||
"toggleBlur": "切换模糊",
|
||||
"show": "显示",
|
||||
"openExampleImages": "打开示例图片文件夹"
|
||||
"openExampleImages": "打开示例图片文件夹",
|
||||
"replacePreview": "替换预览",
|
||||
"copyCheckpointName": "复制 Checkpoint 名称",
|
||||
"copyEmbeddingName": "复制 Embedding 名称",
|
||||
"sendCheckpointToWorkflow": "发送到 ComfyUI",
|
||||
"sendEmbeddingToWorkflow": "发送到 ComfyUI"
|
||||
},
|
||||
"nsfw": {
|
||||
"matureContent": "成熟内容",
|
||||
@@ -114,12 +121,20 @@
|
||||
"updateFailed": "收藏状态更新失败"
|
||||
},
|
||||
"sendToWorkflow": {
|
||||
"checkpointNotImplemented": "发送检查点到工作流 - 功能待实现"
|
||||
"checkpointNotImplemented": "发送检查点到工作流 - 功能待实现",
|
||||
"missingPath": "无法确定此卡片的模型路径"
|
||||
},
|
||||
"exampleImages": {
|
||||
"checkError": "检查示例图片时出错",
|
||||
"missingHash": "缺少模型哈希信息。",
|
||||
"noRemoteImagesAvailable": "此模型在 Civitai 上没有远程示例图片"
|
||||
},
|
||||
"badges": {
|
||||
"update": "更新",
|
||||
"updateAvailable": "有可用更新"
|
||||
},
|
||||
"usage": {
|
||||
"timesUsed": "使用次数"
|
||||
}
|
||||
},
|
||||
"globalContextMenu": {
|
||||
@@ -128,12 +143,33 @@
|
||||
"missingPath": "请先设置下载位置后再下载示例图片。",
|
||||
"unavailable": "示例图片下载当前不可用。请在页面加载完成后重试。"
|
||||
},
|
||||
"checkModelUpdates": {
|
||||
"label": "检查更新",
|
||||
"loading": "正在检查 {type} 更新...",
|
||||
"success": "找到 {count} 条 {type} 更新",
|
||||
"none": "所有 {type} 均已是最新版本",
|
||||
"error": "检查 {type} 更新失败:{message}"
|
||||
},
|
||||
"cleanupExampleImages": {
|
||||
"label": "清理示例图片文件夹",
|
||||
"success": "已将 {count} 个文件夹移动到已删除文件夹",
|
||||
"none": "没有需要清理的示例图片文件夹",
|
||||
"partial": "清理完成,有 {failures} 个文件夹跳过",
|
||||
"error": "清理示例图片文件夹失败:{message}"
|
||||
},
|
||||
"fetchMissingLicenses": {
|
||||
"label": "Refresh license metadata",
|
||||
"loading": "Refreshing license metadata for {typePlural}...",
|
||||
"success": "Updated license metadata for {count} {typePlural}",
|
||||
"none": "All {typePlural} already have license metadata",
|
||||
"error": "Failed to refresh license metadata for {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "修复配方数据",
|
||||
"loading": "正在修复配方数据...",
|
||||
"success": "成功修复了 {count} 个配方。",
|
||||
"cancelled": "修复已取消。已修复 {count} 个配方。",
|
||||
"error": "配方修复失败:{message}"
|
||||
}
|
||||
},
|
||||
"header": {
|
||||
@@ -163,14 +199,35 @@
|
||||
"creator": "创作者",
|
||||
"title": "配方标题",
|
||||
"loraName": "LoRA 文件名",
|
||||
"loraModel": "LoRA 模型名称"
|
||||
"loraModel": "LoRA 模型名称",
|
||||
"prompt": "提示词"
|
||||
}
|
||||
},
|
||||
"filter": {
|
||||
"title": "筛选模型",
|
||||
"presets": "预设",
|
||||
"savePreset": "将当前激活的筛选器保存为新预设。",
|
||||
"savePresetDisabledActive": "无法保存:已有预设处于激活状态。修改筛选器后可保存新预设",
|
||||
"savePresetDisabledNoFilters": "先选择筛选器,然后保存为预设",
|
||||
"savePresetPrompt": "输入预设名称:",
|
||||
"presetClickTooltip": "点击应用预设 \"{name}\"",
|
||||
"presetDeleteTooltip": "删除预设",
|
||||
"presetDeleteConfirm": "删除预设 \"{name}\"?",
|
||||
"presetDeleteConfirmClick": "再次点击确认",
|
||||
"presetOverwriteConfirm": "预设 \"{name}\" 已存在。是否覆盖?",
|
||||
"presetNamePlaceholder": "预设名称...",
|
||||
"baseModel": "基础模型",
|
||||
"modelTags": "标签(前20)",
|
||||
"clearAll": "清除所有筛选"
|
||||
"modelTypes": "Model Types",
|
||||
"license": "许可证",
|
||||
"noCreditRequired": "无需署名",
|
||||
"allowSellingGeneratedContent": "允许销售",
|
||||
"noTags": "无标签",
|
||||
"clearAll": "清除所有筛选",
|
||||
"any": "任一",
|
||||
"all": "全部",
|
||||
"tagLogicAny": "匹配任一标签 (或)",
|
||||
"tagLogicAll": "匹配所有标签 (与)"
|
||||
},
|
||||
"theme": {
|
||||
"toggle": "切换主题",
|
||||
@@ -180,6 +237,7 @@
|
||||
},
|
||||
"actions": {
|
||||
"checkUpdates": "检查更新",
|
||||
"notifications": "通知",
|
||||
"support": "支持"
|
||||
}
|
||||
},
|
||||
@@ -187,17 +245,33 @@
|
||||
"civitaiApiKey": "Civitai API 密钥",
|
||||
"civitaiApiKeyPlaceholder": "请输入你的 Civitai API 密钥",
|
||||
"civitaiApiKeyHelp": "用于从 Civitai 下载模型时的身份验证",
|
||||
"openSettingsFileLocation": {
|
||||
"label": "打开设置文件夹",
|
||||
"tooltip": "打开包含 settings.json 的文件夹",
|
||||
"success": "已打开 settings.json 文件夹",
|
||||
"failed": "无法打开 settings.json 文件夹",
|
||||
"copied": "设置路径已复制到剪贴板:{{path}}",
|
||||
"clipboardFallback": "设置路径:{{path}}"
|
||||
},
|
||||
"sections": {
|
||||
"contentFiltering": "内容过滤",
|
||||
"videoSettings": "视频设置",
|
||||
"layoutSettings": "布局设置",
|
||||
"folderSettings": "文件夹设置",
|
||||
"priorityTags": "优先标签",
|
||||
"downloadPathTemplates": "下载路径模板",
|
||||
"exampleImages": "示例图片",
|
||||
"updateFlags": "更新标记",
|
||||
"autoOrganize": "Auto-organize",
|
||||
"misc": "其他",
|
||||
"metadataArchive": "元数据归档数据库",
|
||||
"storageLocation": "设置位置",
|
||||
"proxySettings": "代理设置"
|
||||
},
|
||||
"storage": {
|
||||
"locationLabel": "便携模式",
|
||||
"locationHelp": "开启可将 settings.json 保存在仓库中;关闭则保存在用户配置目录。"
|
||||
},
|
||||
"contentFiltering": {
|
||||
"blurNsfwContent": "模糊 NSFW 内容",
|
||||
"blurNsfwContentHelp": "模糊成熟(NSFW)内容预览图片",
|
||||
@@ -208,6 +282,15 @@
|
||||
"autoplayOnHover": "悬停时自动播放视频",
|
||||
"autoplayOnHoverHelp": "仅在悬停时播放视频预览"
|
||||
},
|
||||
"autoOrganizeExclusions": {
|
||||
"label": "自动整理排除项",
|
||||
"placeholder": "示例: curated/*, */backups/*; *_temp.safetensors",
|
||||
"help": "跳过与这些通配符模式匹配的文件。多个模式用逗号或分号分隔。",
|
||||
"validation": {
|
||||
"noPatterns": "请输入至少一个用逗号或分号分隔的模式。",
|
||||
"saveFailed": "无法保存排除项:{message}"
|
||||
}
|
||||
},
|
||||
"layoutSettings": {
|
||||
"displayDensity": "显示密度",
|
||||
"displayDensityOptions": {
|
||||
@@ -217,31 +300,67 @@
|
||||
},
|
||||
"displayDensityHelp": "选择每行显示卡片数量:",
|
||||
"displayDensityDetails": {
|
||||
"default": "默认:5(1080p),6(2K),8(4K)",
|
||||
"medium": "中等:6(1080p),7(2K),9(4K)",
|
||||
"compact": "紧凑:7(1080p),8(2K),10(4K)"
|
||||
"default": "5(1080p),6(2K),8(4K)",
|
||||
"medium": "6(1080p),7(2K),9(4K)",
|
||||
"compact": "7(1080p),8(2K),10(4K)"
|
||||
},
|
||||
"displayDensityWarning": "警告:高密度可能导致资源有限的系统性能下降。",
|
||||
"showFolderSidebar": "显示文件夹侧边栏",
|
||||
"showFolderSidebarHelp": "在模型页面启用或禁用文件夹导航侧边栏。关闭后,侧边栏和悬停区域将保持隐藏。",
|
||||
"cardInfoDisplay": "卡片信息显示",
|
||||
"cardInfoDisplayOptions": {
|
||||
"always": "始终可见",
|
||||
"hover": "悬停时显示"
|
||||
},
|
||||
"cardInfoDisplayHelp": "选择何时显示模型信息和操作按钮:",
|
||||
"cardInfoDisplayDetails": {
|
||||
"always": "始终可见:标题和底部始终显示",
|
||||
"hover": "悬停时显示:仅在悬停卡片时显示标题和底部"
|
||||
}
|
||||
"cardInfoDisplayHelp": "选择何时显示模型信息和操作按钮",
|
||||
"modelCardFooterAction": "模型卡片按钮操作",
|
||||
"modelCardFooterActionOptions": {
|
||||
"exampleImages": "打开示例图片",
|
||||
"replacePreview": "替换预览"
|
||||
},
|
||||
"modelCardFooterActionHelp": "选择右下角卡片按钮的功能",
|
||||
"modelNameDisplay": "模型名称显示",
|
||||
"modelNameDisplayOptions": {
|
||||
"modelName": "模型名称",
|
||||
"fileName": "文件名"
|
||||
},
|
||||
"modelNameDisplayHelp": "选择在模型卡片底部显示的内容"
|
||||
},
|
||||
"folderSettings": {
|
||||
"activeLibrary": "活动库",
|
||||
"activeLibraryHelp": "在已配置的库之间切换以更新默认文件夹。更改选择将重新加载页面。",
|
||||
"loadingLibraries": "正在加载库...",
|
||||
"noLibraries": "尚未配置库",
|
||||
"defaultLoraRoot": "默认 LoRA 根目录",
|
||||
"defaultLoraRootHelp": "设置下载、导入和移动时的默认 LoRA 根目录",
|
||||
"defaultCheckpointRoot": "默认 Checkpoint 根目录",
|
||||
"defaultCheckpointRootHelp": "设置下载、导入和移动时的默认 Checkpoint 根目录",
|
||||
"defaultUnetRoot": "默认 Diffusion Model 根目录",
|
||||
"defaultUnetRootHelp": "设置下载、导入和移动时的默认 Diffusion Model (UNET) 根目录",
|
||||
"defaultEmbeddingRoot": "默认 Embedding 根目录",
|
||||
"defaultEmbeddingRootHelp": "设置下载、导入和移动时的默认 Embedding 根目录",
|
||||
"noDefault": "无默认"
|
||||
},
|
||||
"priorityTags": {
|
||||
"title": "优先标签",
|
||||
"description": "为每种模型类型自定义标签优先级顺序 (例如: character, concept, style(toon|toon_style))",
|
||||
"placeholder": "character, concept, style(toon|toon_style)",
|
||||
"helpLinkLabel": "打开优先标签帮助",
|
||||
"modelTypes": {
|
||||
"lora": "LoRA",
|
||||
"checkpoint": "Checkpoint",
|
||||
"embedding": "Embedding"
|
||||
},
|
||||
"saveSuccess": "优先标签已更新。",
|
||||
"saveError": "优先标签更新失败。",
|
||||
"loadingSuggestions": "正在加载建议...",
|
||||
"validation": {
|
||||
"missingClosingParen": "条目 {index} 缺少右括号。",
|
||||
"missingCanonical": "条目 {index} 必须包含规范标签名称。",
|
||||
"duplicateCanonical": "规范标签 \"{tag}\" 出现多次。",
|
||||
"unknown": "优先标签配置无效。"
|
||||
}
|
||||
},
|
||||
"downloadPathTemplates": {
|
||||
"title": "下载路径模板",
|
||||
"help": "配置从 Civitai 下载不同模型类型的文件夹结构。",
|
||||
@@ -289,6 +408,14 @@
|
||||
"download": "下载",
|
||||
"restartRequired": "需要重启"
|
||||
},
|
||||
"updateFlagStrategy": {
|
||||
"label": "更新标记策略",
|
||||
"help": "决定更新徽章是否仅在新版本与本地文件共享相同基础模型时显示,或只要该模型有任何更新版本就显示。",
|
||||
"options": {
|
||||
"sameBase": "按基础模型匹配更新",
|
||||
"any": "显示任何可用更新"
|
||||
}
|
||||
},
|
||||
"misc": {
|
||||
"includeTriggerWords": "复制 LoRA 语法时包含触发词",
|
||||
"includeTriggerWordsHelp": "复制 LoRA 语法到剪贴板时包含训练触发词"
|
||||
@@ -348,12 +475,17 @@
|
||||
"dateAsc": "最旧",
|
||||
"size": "文件大小",
|
||||
"sizeDesc": "最大",
|
||||
"sizeAsc": "最小"
|
||||
"sizeAsc": "最小",
|
||||
"usage": "使用次数",
|
||||
"usageDesc": "最多",
|
||||
"usageAsc": "最少"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "刷新模型列表",
|
||||
"quick": "快速刷新(增量)",
|
||||
"full": "完全重建(完整)"
|
||||
"quick": "同步变更",
|
||||
"quickTooltip": "扫描新的或缺失的模型文件,保持列表最新。",
|
||||
"full": "重建缓存",
|
||||
"fullTooltip": "从元数据文件重新加载所有模型信息;用于列表过时或手动编辑后。"
|
||||
},
|
||||
"fetch": {
|
||||
"title": "从 Civitai 获取元数据",
|
||||
@@ -374,19 +506,28 @@
|
||||
"favorites": {
|
||||
"title": "仅显示收藏",
|
||||
"action": "收藏"
|
||||
},
|
||||
"updates": {
|
||||
"title": "仅显示可用更新的模型",
|
||||
"action": "更新",
|
||||
"menuLabel": "显示更新选项",
|
||||
"check": "检查更新",
|
||||
"checkTooltip": "检查更新可能耗时。"
|
||||
}
|
||||
},
|
||||
"bulkOperations": {
|
||||
"selected": "已选中 {count} 项",
|
||||
"selectedSuffix": "已选中",
|
||||
"viewSelected": "查看已选中",
|
||||
"addTags": "为所有添加标签",
|
||||
"setBaseModel": "为所有设置基础模型",
|
||||
"copyAll": "复制全部语法",
|
||||
"refreshAll": "刷新全部元数据",
|
||||
"moveAll": "全部移动到文件夹",
|
||||
"addTags": "为所选中添加标签",
|
||||
"setBaseModel": "为所选中设置基础模型",
|
||||
"setContentRating": "为所选中设置内容评级",
|
||||
"copyAll": "复制所选中语法",
|
||||
"refreshAll": "刷新所选中元数据",
|
||||
"checkUpdates": "检查所选更新",
|
||||
"moveAll": "移动所选中到文件夹",
|
||||
"autoOrganize": "自动整理所选模型",
|
||||
"deleteAll": "删除所有模型",
|
||||
"deleteAll": "删除选中模型",
|
||||
"clear": "清除选择",
|
||||
"autoOrganizeProgress": {
|
||||
"initializing": "正在初始化自动整理...",
|
||||
@@ -400,6 +541,7 @@
|
||||
},
|
||||
"contextMenu": {
|
||||
"refreshMetadata": "刷新 Civitai 数据",
|
||||
"checkUpdates": "检查更新",
|
||||
"relinkCivitai": "重新关联到 Civitai",
|
||||
"copySyntax": "复制 LoRA 语法",
|
||||
"copyFilename": "复制模型文件名",
|
||||
@@ -411,6 +553,7 @@
|
||||
"replacePreview": "替换预览",
|
||||
"setContentRating": "设置内容评级",
|
||||
"moveToFolder": "移动到文件夹",
|
||||
"repairMetadata": "修复元数据",
|
||||
"excludeModel": "排除模型",
|
||||
"deleteModel": "删除模型",
|
||||
"shareRecipe": "分享配方",
|
||||
@@ -421,6 +564,9 @@
|
||||
},
|
||||
"recipes": {
|
||||
"title": "LoRA 配方",
|
||||
"actions": {
|
||||
"sendCheckpoint": "发送到 ComfyUI"
|
||||
},
|
||||
"controls": {
|
||||
"import": {
|
||||
"action": "导入",
|
||||
@@ -478,10 +624,26 @@
|
||||
"selectLoraRoot": "请选择 LoRA 根目录"
|
||||
}
|
||||
},
|
||||
"sort": {
|
||||
"title": "配方排序...",
|
||||
"name": "名称",
|
||||
"nameAsc": "A - Z",
|
||||
"nameDesc": "Z - A",
|
||||
"date": "时间",
|
||||
"dateDesc": "最新",
|
||||
"dateAsc": "最早",
|
||||
"lorasCount": "LoRA 数量",
|
||||
"lorasCountDesc": "最多",
|
||||
"lorasCountAsc": "最少"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "刷新配方列表"
|
||||
},
|
||||
"filteredByLora": "按 LoRA 筛选"
|
||||
"filteredByLora": "按 LoRA 筛选",
|
||||
"favorites": {
|
||||
"title": "仅显示收藏",
|
||||
"action": "收藏"
|
||||
}
|
||||
},
|
||||
"duplicates": {
|
||||
"found": "发现 {count} 个重复组",
|
||||
@@ -507,23 +669,44 @@
|
||||
"noMissingLoras": "没有缺失的 LoRA 可下载",
|
||||
"getInfoFailed": "获取缺失 LoRA 信息失败",
|
||||
"prepareError": "准备下载 LoRA 时出错:{message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "正在修复配方元数据...",
|
||||
"success": "配方元数据修复成功",
|
||||
"skipped": "配方已是最新版本,无需修复",
|
||||
"failed": "修复配方失败:{message}",
|
||||
"missingId": "无法修复配方:缺少配方 ID"
|
||||
}
|
||||
}
|
||||
},
|
||||
"checkpoints": {
|
||||
"title": "Checkpoint 模型"
|
||||
"title": "Checkpoint 模型",
|
||||
"modelTypes": {
|
||||
"checkpoint": "Checkpoint",
|
||||
"diffusion_model": "Diffusion Model"
|
||||
},
|
||||
"contextMenu": {
|
||||
"moveToOtherTypeFolder": "移动到 {otherType} 文件夹"
|
||||
}
|
||||
},
|
||||
"embeddings": {
|
||||
"title": "Embedding 模型"
|
||||
},
|
||||
"sidebar": {
|
||||
"modelRoot": "模型根目录",
|
||||
"modelRoot": "根目录",
|
||||
"collapseAll": "折叠所有文件夹",
|
||||
"pinSidebar": "固定侧边栏",
|
||||
"unpinSidebar": "取消固定侧边栏",
|
||||
"switchToListView": "切换到列表视图",
|
||||
"switchToTreeView": "切换到树状视图",
|
||||
"collapseAllDisabled": "列表视图下不可用"
|
||||
"recursiveOn": "搜索子文件夹",
|
||||
"recursiveOff": "仅搜索当前文件夹",
|
||||
"recursiveUnavailable": "仅在树形视图中可使用递归搜索",
|
||||
"collapseAllDisabled": "列表视图下不可用",
|
||||
"dragDrop": {
|
||||
"unableToResolveRoot": "无法确定移动的目标路径。",
|
||||
"moveUnsupported": "Move is not supported for this item."
|
||||
}
|
||||
},
|
||||
"statistics": {
|
||||
"title": "统计",
|
||||
@@ -598,6 +781,14 @@
|
||||
"downloadedPreview": "预览图片已下载",
|
||||
"downloadingFile": "正在下载 {type} 文件",
|
||||
"finalizing": "正在完成下载..."
|
||||
},
|
||||
"progress": {
|
||||
"currentFile": "当前文件:",
|
||||
"downloading": "下载中:{name}",
|
||||
"transferred": "已下载:{downloaded} / {total}",
|
||||
"transferredSimple": "已下载:{downloaded}",
|
||||
"transferredUnknown": "已下载:--",
|
||||
"speed": "速度:{speed}"
|
||||
}
|
||||
},
|
||||
"move": {
|
||||
@@ -606,6 +797,7 @@
|
||||
"contentRating": {
|
||||
"title": "设置内容评级",
|
||||
"current": "当前",
|
||||
"multiple": "多个值",
|
||||
"levels": {
|
||||
"pg": "PG",
|
||||
"pg13": "PG13",
|
||||
@@ -644,6 +836,12 @@
|
||||
"countMessage": "模型将被永久删除。",
|
||||
"action": "全部删除"
|
||||
},
|
||||
"checkUpdates": {
|
||||
"title": "检查所有 {type} 的更新?",
|
||||
"message": "这会为库中的每个 {type} 检查更新,大型集合可能需要一些时间。",
|
||||
"tip": "想分批进行?切换到批量模式,选中需要的模型,然后使用“检查所选更新”。",
|
||||
"action": "检查全部"
|
||||
},
|
||||
"bulkAddTags": {
|
||||
"title": "批量添加标签",
|
||||
"description": "为多个模型添加标签",
|
||||
@@ -717,7 +915,9 @@
|
||||
},
|
||||
"openFileLocation": {
|
||||
"success": "文件位置已成功打开",
|
||||
"failed": "打开文件位置失败"
|
||||
"failed": "打开文件位置失败",
|
||||
"copied": "路径已复制到剪贴板:{{path}}",
|
||||
"clipboardFallback": "路径:{{path}}"
|
||||
},
|
||||
"metadata": {
|
||||
"version": "版本",
|
||||
@@ -740,11 +940,13 @@
|
||||
"addPresetParameter": "添加预设参数...",
|
||||
"strengthMin": "最小强度",
|
||||
"strengthMax": "最大强度",
|
||||
"strengthRange": "强度范围",
|
||||
"strength": "强度",
|
||||
"clipStrength": "Clip 强度",
|
||||
"clipSkip": "Clip Skip",
|
||||
"valuePlaceholder": "数值",
|
||||
"add": "添加"
|
||||
"add": "添加",
|
||||
"invalidRange": "无效的范围格式。请使用 x.x-y.y"
|
||||
},
|
||||
"triggerWords": {
|
||||
"label": "触发词",
|
||||
@@ -780,13 +982,84 @@
|
||||
"tabs": {
|
||||
"examples": "示例",
|
||||
"description": "模型描述",
|
||||
"recipes": "配方"
|
||||
"recipes": "配方",
|
||||
"versions": "版本"
|
||||
},
|
||||
"navigation": {
|
||||
"label": "模型导航",
|
||||
"previousWithShortcut": "上一个模型(←)",
|
||||
"nextWithShortcut": "下一个模型(→)",
|
||||
"noPrevious": "没有上一个模型",
|
||||
"noNext": "没有下一个模型"
|
||||
},
|
||||
"license": {
|
||||
"noImageSell": "No selling generated content",
|
||||
"noRentCivit": "No Civitai generation",
|
||||
"noRent": "No generation services",
|
||||
"noSell": "No selling models",
|
||||
"creditRequired": "需要创作者署名",
|
||||
"noDerivatives": "禁止分享合并作品",
|
||||
"noReLicense": "需要相同权限",
|
||||
"restrictionsLabel": "许可证限制"
|
||||
},
|
||||
"loading": {
|
||||
"exampleImages": "正在加载示例图片...",
|
||||
"description": "正在加载模型描述...",
|
||||
"recipes": "正在加载配方...",
|
||||
"examples": "正在加载示例..."
|
||||
"examples": "正在加载示例...",
|
||||
"versions": "正在加载版本..."
|
||||
},
|
||||
"versions": {
|
||||
"heading": "模型版本",
|
||||
"copy": "在一个位置管理该模型的所有版本。",
|
||||
"media": {
|
||||
"placeholder": "无预览"
|
||||
},
|
||||
"labels": {
|
||||
"unnamed": "未命名版本",
|
||||
"noDetails": "暂无更多信息"
|
||||
},
|
||||
"badges": {
|
||||
"current": "当前版本",
|
||||
"inLibrary": "已在库中",
|
||||
"newer": "较新的版本",
|
||||
"ignored": "已忽略"
|
||||
},
|
||||
"actions": {
|
||||
"download": "下载",
|
||||
"delete": "删除",
|
||||
"ignore": "忽略",
|
||||
"unignore": "取消忽略",
|
||||
"resumeModelUpdates": "继续跟踪该模型的更新",
|
||||
"ignoreModelUpdates": "忽略该模型的更新",
|
||||
"viewLocalVersions": "查看所有本地版本",
|
||||
"viewLocalTooltip": "敬请期待"
|
||||
},
|
||||
"filters": {
|
||||
"label": "基础筛选",
|
||||
"state": {
|
||||
"showAll": "全部版本",
|
||||
"showSameBase": "相同基模型"
|
||||
},
|
||||
"tooltip": {
|
||||
"showAllVersions": "切换为显示所有版本",
|
||||
"showSameBaseVersions": "仅显示与当前基模型匹配的版本"
|
||||
},
|
||||
"empty": "没有与当前基模型筛选匹配的版本。"
|
||||
},
|
||||
"empty": "该模型还没有版本历史。",
|
||||
"error": "加载版本失败。",
|
||||
"missingModelId": "该模型缺少 Civitai 模型 ID。",
|
||||
"confirm": {
|
||||
"delete": "从库中删除此版本?"
|
||||
},
|
||||
"toast": {
|
||||
"modelIgnored": "已忽略该模型的更新",
|
||||
"modelResumed": "已恢复更新跟踪",
|
||||
"versionIgnored": "已忽略该版本的更新",
|
||||
"versionUnignored": "已重新启用该版本",
|
||||
"versionDeleted": "版本已删除"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -893,7 +1166,9 @@
|
||||
"loraFailedToSend": "发送 LoRA 到工作流失败",
|
||||
"recipeAdded": "配方已追加到工作流",
|
||||
"recipeReplaced": "配方已替换到工作流",
|
||||
"recipeFailedToSend": "发送配方到工作流失败"
|
||||
"recipeFailedToSend": "发送配方到工作流失败",
|
||||
"noMatchingNodes": "当前工作流中没有兼容的节点",
|
||||
"noTargetNodeSelected": "未选择目标节点"
|
||||
},
|
||||
"nodeSelector": {
|
||||
"recipe": "配方",
|
||||
@@ -906,7 +1181,11 @@
|
||||
"exampleImages": {
|
||||
"opened": "示例图片文件夹已打开",
|
||||
"openingFolder": "正在打开示例图片文件夹",
|
||||
"failedToOpen": "打开示例图片文件夹失败"
|
||||
"failedToOpen": "打开示例图片文件夹失败",
|
||||
"setupRequired": "示例图片存储",
|
||||
"setupDescription": "要添加自定义示例图片,您需要先设置下载位置。",
|
||||
"setupUsage": "此路径用于存储下载的示例图片和自定义图片。",
|
||||
"openSettings": "打开设置"
|
||||
}
|
||||
},
|
||||
"help": {
|
||||
@@ -938,6 +1217,11 @@
|
||||
},
|
||||
"update": {
|
||||
"title": "检查更新",
|
||||
"notificationsTitle": "通知中心",
|
||||
"tabs": {
|
||||
"updates": "更新",
|
||||
"messages": "消息"
|
||||
},
|
||||
"updateAvailable": "更新可用",
|
||||
"noChangelogAvailable": "没有详细的更新日志可用。请查看 GitHub 以获取更多信息。",
|
||||
"currentVersion": "当前版本",
|
||||
@@ -950,6 +1234,7 @@
|
||||
"checkingUpdates": "正在检查更新...",
|
||||
"checkingMessage": "请稍候,正在检查最新版本。",
|
||||
"showNotifications": "显示更新通知",
|
||||
"latestBadge": "最新",
|
||||
"updateProgress": {
|
||||
"preparing": "正在准备更新...",
|
||||
"installing": "正在安装更新...",
|
||||
@@ -969,6 +1254,13 @@
|
||||
"nightly": {
|
||||
"warning": "警告:Nightly 版本可能包含实验性功能,可能不稳定。",
|
||||
"enable": "启用 Nightly 更新"
|
||||
},
|
||||
"banners": {
|
||||
"recent": "最近的通知",
|
||||
"empty": "暂无最近的横幅通知。",
|
||||
"shown": "{time} 显示",
|
||||
"dismissed": "{time} 关闭",
|
||||
"active": "仍在显示"
|
||||
}
|
||||
},
|
||||
"support": {
|
||||
@@ -1048,6 +1340,9 @@
|
||||
"cannotSend": "无法发送配方:缺少配方 ID",
|
||||
"sendFailed": "发送配方到工作流失败",
|
||||
"sendError": "发送配方到工作流出错",
|
||||
"missingCheckpointPath": "缺少检查点路径",
|
||||
"missingCheckpointInfo": "缺少检查点信息",
|
||||
"downloadCheckpointFailed": "下载检查点失败:{message}",
|
||||
"cannotDelete": "无法删除配方:缺少配方 ID",
|
||||
"deleteConfirmationError": "显示删除确认出错",
|
||||
"deletedSuccessfully": "配方删除成功",
|
||||
@@ -1084,6 +1379,16 @@
|
||||
"bulkBaseModelUpdateSuccess": "成功为 {count} 个模型更新基础模型",
|
||||
"bulkBaseModelUpdatePartial": "更新了 {success} 个模型,{failed} 个失败",
|
||||
"bulkBaseModelUpdateFailed": "为选中模型更新基础模型失败",
|
||||
"bulkContentRatingUpdating": "正在为 {count} 个模型更新内容评级...",
|
||||
"bulkContentRatingSet": "已将 {count} 个模型的内容评级设置为 {level}",
|
||||
"bulkContentRatingPartial": "已将 {success} 个模型的内容评级设置为 {level},{failed} 个失败",
|
||||
"bulkContentRatingFailed": "未能更新所选模型的内容评级",
|
||||
"bulkUpdatesChecking": "正在检查所选 {type} 的更新...",
|
||||
"bulkUpdatesSuccess": "{count} 个所选 {type} 有可用更新",
|
||||
"bulkUpdatesNone": "所选 {type} 未发现更新",
|
||||
"bulkUpdatesMissing": "所选 {type} 未关联 Civitai 更新",
|
||||
"bulkUpdatesPartialMissing": "已跳过 {missing} 个未关联 Civitai 的所选 {type}",
|
||||
"bulkUpdatesFailed": "检查所选 {type} 的更新失败:{message}",
|
||||
"invalidCharactersRemoved": "文件名中的无效字符已移除",
|
||||
"filenameCannotBeEmpty": "文件名不能为空",
|
||||
"renameFailed": "重命名文件失败:{message}",
|
||||
@@ -1095,6 +1400,7 @@
|
||||
"verificationCompleteSuccess": "验证完成。所有文件均为重复项。",
|
||||
"verificationFailed": "验证哈希失败:{message}",
|
||||
"noTagsToAdd": "没有可添加的标签",
|
||||
"bulkTagsUpdating": "正在更新 {count} 个模型的标签...",
|
||||
"tagsAddedSuccessfully": "已成功为 {count} 个 {type} 添加 {tagCount} 个标签",
|
||||
"tagsReplacedSuccessfully": "已成功为 {count} 个 {type} 替换为 {tagCount} 个标签",
|
||||
"tagsAddFailed": "为 {count} 个模型添加标签失败",
|
||||
@@ -1108,6 +1414,7 @@
|
||||
"settings": {
|
||||
"loraRootsFailed": "加载 LoRA 根目录失败:{message}",
|
||||
"checkpointRootsFailed": "加载 Checkpoint 根目录失败:{message}",
|
||||
"unetRootsFailed": "加载 Diffusion Model 根目录失败:{message}",
|
||||
"embeddingRootsFailed": "加载 Embedding 根目录失败:{message}",
|
||||
"mappingsUpdated": "基础模型路径映射已更新({count} 条映射{plural})",
|
||||
"mappingsCleared": "基础模型路径映射已清除",
|
||||
@@ -1118,6 +1425,8 @@
|
||||
"compactModeToggled": "紧凑模式 {state}",
|
||||
"settingSaveFailed": "保存设置失败:{message}",
|
||||
"displayDensitySet": "显示密度已设置为 {density}",
|
||||
"libraryLoadFailed": "Failed to load libraries: {message}",
|
||||
"libraryActivateFailed": "Failed to activate library: {message}",
|
||||
"languageChangeFailed": "切换语言失败:{message}",
|
||||
"cacheCleared": "缓存文件已成功清除。下次操作将重建缓存。",
|
||||
"cacheClearFailed": "清除缓存失败:{error}",
|
||||
@@ -1126,7 +1435,26 @@
|
||||
"filters": {
|
||||
"applied": "{message}",
|
||||
"cleared": "筛选已清除",
|
||||
"noCustomFilterToClear": "没有自定义筛选可清除"
|
||||
"noCustomFilterToClear": "没有自定义筛选可清除",
|
||||
"noActiveFilters": "没有可保存的激活筛选"
|
||||
},
|
||||
"presets": {
|
||||
"created": "预设 \"{name}\" 已创建",
|
||||
"deleted": "预设 \"{name}\" 已删除",
|
||||
"applied": "预设 \"{name}\" 已应用",
|
||||
"overwritten": "预设 \"{name}\" 已覆盖",
|
||||
"restored": "默认预设已恢复"
|
||||
},
|
||||
"error": {
|
||||
"presetNameEmpty": "预设名称不能为空",
|
||||
"presetNameTooLong": "预设名称不能超过 {max} 个字符",
|
||||
"presetNameInvalidChars": "预设名称包含无效字符",
|
||||
"presetNameExists": "已存在同名预设",
|
||||
"maxPresetsReached": "最多允许 {max} 个预设。删除一个以添加更多。",
|
||||
"presetNotFound": "预设未找到",
|
||||
"invalidPreset": "无效的预设数据",
|
||||
"deletePresetFailed": "删除预设失败",
|
||||
"applyPresetFailed": "应用预设失败"
|
||||
},
|
||||
"downloads": {
|
||||
"imagesCompleted": "示例图片{action}完成",
|
||||
@@ -1142,7 +1470,7 @@
|
||||
},
|
||||
"triggerWords": {
|
||||
"loadFailed": "无法加载训练词",
|
||||
"tooLong": "触发词不能超过30个词",
|
||||
"tooLong": "触发词不能超过100个词",
|
||||
"tooMany": "最多允许30个触发词",
|
||||
"alreadyExists": "该触发词已存在",
|
||||
"updateSuccess": "触发词更新成功",
|
||||
@@ -1191,6 +1519,8 @@
|
||||
"pauseFailed": "暂停下载失败:{error}",
|
||||
"downloadResumed": "下载已恢复",
|
||||
"resumeFailed": "恢复下载失败:{error}",
|
||||
"downloadStopped": "下载已取消",
|
||||
"stopFailed": "取消下载失败:{error}",
|
||||
"deleted": "示例图片已删除",
|
||||
"deleteFailed": "删除示例图片失败",
|
||||
"setPreviewFailed": "设置预览图片失败"
|
||||
@@ -1211,6 +1541,8 @@
|
||||
"metadataRefreshed": "元数据刷新成功",
|
||||
"metadataRefreshFailed": "刷新元数据失败:{message}",
|
||||
"metadataUpdateComplete": "元数据更新完成",
|
||||
"operationCancelled": "操作已由用户取消",
|
||||
"operationCancelledPartial": "操作已取消。已处理 {success} 个项目。",
|
||||
"metadataFetchFailed": "获取元数据失败:{message}",
|
||||
"bulkMetadataCompleteAll": "全部 {count} 个 {type} 元数据刷新成功",
|
||||
"bulkMetadataCompletePartial": "已刷新 {success}/{total} 个 {type} 元数据",
|
||||
@@ -1227,7 +1559,8 @@
|
||||
"bulkMoveFailures": "移动失败:\n{failures}",
|
||||
"bulkMoveSuccess": "成功移动 {successCount} 个 {type}",
|
||||
"exampleImagesDownloadSuccess": "示例图片下载成功!",
|
||||
"exampleImagesDownloadFailed": "示例图片下载失败:{message}"
|
||||
"exampleImagesDownloadFailed": "示例图片下载失败:{message}",
|
||||
"moveFailed": "Failed to move item: {message}"
|
||||
}
|
||||
},
|
||||
"banners": {
|
||||
@@ -1237,6 +1570,26 @@
|
||||
"refreshNow": "立即刷新",
|
||||
"refreshingIn": "将在",
|
||||
"seconds": "秒后刷新"
|
||||
},
|
||||
"communitySupport": {
|
||||
"title": "LM 浏览器插件限时优惠 ⚡",
|
||||
"content": "来爱发电为Lora Manager项目发电,支持项目持续开发的同时,获取浏览器插件验证码,按季支付更优惠!支付宝/微信方便支付。感谢支持!🚀",
|
||||
"supportCta": "为LM发电",
|
||||
"learnMore": "浏览器插件教程"
|
||||
},
|
||||
"cacheHealth": {
|
||||
"corrupted": {
|
||||
"title": "检测到缓存损坏"
|
||||
},
|
||||
"degraded": {
|
||||
"title": "检测到缓存问题"
|
||||
},
|
||||
"content": "{total} 个缓存条目中有 {invalid} 个无效({rate})。这可能导致模型丢失或错误。建议重建缓存。",
|
||||
"rebuildCache": "重建缓存",
|
||||
"dismiss": "忽略",
|
||||
"rebuilding": "正在重建缓存...",
|
||||
"rebuildFailed": "重建缓存失败:{error}",
|
||||
"retry": "重试"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -10,7 +10,8 @@
|
||||
"next": "下一步",
|
||||
"backToTop": "回到頂部",
|
||||
"settings": "設定",
|
||||
"help": "說明"
|
||||
"help": "說明",
|
||||
"add": "新增"
|
||||
},
|
||||
"status": {
|
||||
"loading": "載入中...",
|
||||
@@ -31,7 +32,8 @@
|
||||
"japanese": "日本語",
|
||||
"korean": "한국어",
|
||||
"french": "Français",
|
||||
"spanish": "Español"
|
||||
"spanish": "Español",
|
||||
"Hebrew": "עברית"
|
||||
},
|
||||
"fileSize": {
|
||||
"zero": "0 位元組",
|
||||
@@ -100,7 +102,12 @@
|
||||
"checkpointNameCopied": "Checkpoint 名稱已複製",
|
||||
"toggleBlur": "切換模糊",
|
||||
"show": "顯示",
|
||||
"openExampleImages": "開啟範例圖片資料夾"
|
||||
"openExampleImages": "開啟範例圖片資料夾",
|
||||
"replacePreview": "更換預覽圖",
|
||||
"copyCheckpointName": "複製檢查點名稱",
|
||||
"copyEmbeddingName": "複製嵌入名稱",
|
||||
"sendCheckpointToWorkflow": "傳送到 ComfyUI",
|
||||
"sendEmbeddingToWorkflow": "傳送到 ComfyUI"
|
||||
},
|
||||
"nsfw": {
|
||||
"matureContent": "成熟內容",
|
||||
@@ -114,12 +121,20 @@
|
||||
"updateFailed": "更新收藏狀態失敗"
|
||||
},
|
||||
"sendToWorkflow": {
|
||||
"checkpointNotImplemented": "傳送 checkpoint 到工作流 - 功能尚未實現"
|
||||
"checkpointNotImplemented": "傳送 checkpoint 到工作流 - 功能尚未實現",
|
||||
"missingPath": "無法確定此卡片的模型路徑"
|
||||
},
|
||||
"exampleImages": {
|
||||
"checkError": "檢查範例圖片時發生錯誤",
|
||||
"missingHash": "缺少模型雜湊資訊。",
|
||||
"noRemoteImagesAvailable": "此模型在 Civitai 上無遠端範例圖片"
|
||||
},
|
||||
"badges": {
|
||||
"update": "更新",
|
||||
"updateAvailable": "有可用更新"
|
||||
},
|
||||
"usage": {
|
||||
"timesUsed": "使用次數"
|
||||
}
|
||||
},
|
||||
"globalContextMenu": {
|
||||
@@ -128,12 +143,33 @@
|
||||
"missingPath": "請先設定下載位置再下載範例圖片。",
|
||||
"unavailable": "範例圖片下載目前尚不可用。請在頁面載入完成後再試一次。"
|
||||
},
|
||||
"checkModelUpdates": {
|
||||
"label": "檢查更新",
|
||||
"loading": "正在檢查 {type} 更新...",
|
||||
"success": "找到 {count} 個 {type} 更新",
|
||||
"none": "所有 {type} 都是最新版本",
|
||||
"error": "檢查 {type} 更新失敗:{message}"
|
||||
},
|
||||
"cleanupExampleImages": {
|
||||
"label": "清理範例圖片資料夾",
|
||||
"success": "已將 {count} 個資料夾移至已刪除資料夾",
|
||||
"none": "沒有需要清理的範例圖片資料夾",
|
||||
"partial": "清理完成,有 {failures} 個資料夾略過",
|
||||
"error": "清理範例圖片資料夾失敗:{message}"
|
||||
},
|
||||
"fetchMissingLicenses": {
|
||||
"label": "重新整理授權中繼資料",
|
||||
"loading": "正在重新整理 {typePlural} 的授權中繼資料...",
|
||||
"success": "已更新 {count} 個 {typePlural} 的授權中繼資料",
|
||||
"none": "所有 {typePlural} 已具備授權中繼資料",
|
||||
"error": "重新整理 {typePlural} 授權中繼資料失敗:{message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "修復配方資料",
|
||||
"loading": "正在修復配方資料...",
|
||||
"success": "成功修復 {count} 個配方。",
|
||||
"cancelled": "修復已取消。已修復 {count} 個配方。",
|
||||
"error": "配方修復失敗:{message}"
|
||||
}
|
||||
},
|
||||
"header": {
|
||||
@@ -163,14 +199,35 @@
|
||||
"creator": "創作者",
|
||||
"title": "配方標題",
|
||||
"loraName": "LoRA 檔案名稱",
|
||||
"loraModel": "LoRA 模型名稱"
|
||||
"loraModel": "LoRA 模型名稱",
|
||||
"prompt": "提示詞"
|
||||
}
|
||||
},
|
||||
"filter": {
|
||||
"title": "篩選模型",
|
||||
"presets": "預設",
|
||||
"savePreset": "將目前啟用的篩選器儲存為新預設。",
|
||||
"savePresetDisabledActive": "無法儲存:已有預設處於啟用狀態。修改篩選器後可儲存新預設",
|
||||
"savePresetDisabledNoFilters": "先選擇篩選器,然後儲存為預設",
|
||||
"savePresetPrompt": "輸入預設名稱:",
|
||||
"presetClickTooltip": "點擊套用預設 \"{name}\"",
|
||||
"presetDeleteTooltip": "刪除預設",
|
||||
"presetDeleteConfirm": "刪除預設 \"{name}\"?",
|
||||
"presetDeleteConfirmClick": "再次點擊確認",
|
||||
"presetOverwriteConfirm": "預設 \"{name}\" 已存在。是否覆蓋?",
|
||||
"presetNamePlaceholder": "預設名稱...",
|
||||
"baseModel": "基礎模型",
|
||||
"modelTags": "標籤(前 20)",
|
||||
"clearAll": "清除所有篩選"
|
||||
"modelTypes": "Model Types",
|
||||
"license": "授權",
|
||||
"noCreditRequired": "無需署名",
|
||||
"allowSellingGeneratedContent": "允許銷售",
|
||||
"noTags": "無標籤",
|
||||
"clearAll": "清除所有篩選",
|
||||
"any": "任一",
|
||||
"all": "全部",
|
||||
"tagLogicAny": "符合任一票籤 (或)",
|
||||
"tagLogicAll": "符合所有標籤 (與)"
|
||||
},
|
||||
"theme": {
|
||||
"toggle": "切換主題",
|
||||
@@ -180,6 +237,7 @@
|
||||
},
|
||||
"actions": {
|
||||
"checkUpdates": "檢查更新",
|
||||
"notifications": "通知",
|
||||
"support": "支援"
|
||||
}
|
||||
},
|
||||
@@ -187,17 +245,33 @@
|
||||
"civitaiApiKey": "Civitai API 金鑰",
|
||||
"civitaiApiKeyPlaceholder": "請輸入您的 Civitai API 金鑰",
|
||||
"civitaiApiKeyHelp": "用於從 Civitai 下載模型時的身份驗證",
|
||||
"openSettingsFileLocation": {
|
||||
"label": "開啟設定資料夾",
|
||||
"tooltip": "開啟包含 settings.json 的資料夾",
|
||||
"success": "已開啟 settings.json 資料夾",
|
||||
"failed": "無法開啟 settings.json 資料夾",
|
||||
"copied": "設定路徑已複製到剪貼簿:{{path}}",
|
||||
"clipboardFallback": "設定路徑:{{path}}"
|
||||
},
|
||||
"sections": {
|
||||
"contentFiltering": "內容過濾",
|
||||
"videoSettings": "影片設定",
|
||||
"layoutSettings": "版面設定",
|
||||
"folderSettings": "資料夾設定",
|
||||
"priorityTags": "優先標籤",
|
||||
"downloadPathTemplates": "下載路徑範本",
|
||||
"exampleImages": "範例圖片",
|
||||
"updateFlags": "更新標記",
|
||||
"autoOrganize": "Auto-organize",
|
||||
"misc": "其他",
|
||||
"metadataArchive": "中繼資料封存資料庫",
|
||||
"storageLocation": "設定位置",
|
||||
"proxySettings": "代理設定"
|
||||
},
|
||||
"storage": {
|
||||
"locationLabel": "可攜式模式",
|
||||
"locationHelp": "啟用可將 settings.json 保存在儲存庫中;停用則保存在使用者設定目錄。"
|
||||
},
|
||||
"contentFiltering": {
|
||||
"blurNsfwContent": "模糊 NSFW 內容",
|
||||
"blurNsfwContentHelp": "模糊成熟(NSFW)內容預覽圖片",
|
||||
@@ -208,6 +282,15 @@
|
||||
"autoplayOnHover": "滑鼠懸停自動播放影片",
|
||||
"autoplayOnHoverHelp": "僅在滑鼠懸停時播放影片預覽"
|
||||
},
|
||||
"autoOrganizeExclusions": {
|
||||
"label": "自動整理排除項目",
|
||||
"placeholder": "範例: curated/*, */backups/*; *_temp.safetensors",
|
||||
"help": "跳過符合這些萬用字元模式的檔案。多個模式請用逗號或分號分隔。",
|
||||
"validation": {
|
||||
"noPatterns": "請輸入至少一個以逗號或分號分隔的模式。",
|
||||
"saveFailed": "無法儲存排除項目:{message}"
|
||||
}
|
||||
},
|
||||
"layoutSettings": {
|
||||
"displayDensity": "顯示密度",
|
||||
"displayDensityOptions": {
|
||||
@@ -217,31 +300,67 @@
|
||||
},
|
||||
"displayDensityHelp": "選擇每行顯示卡片數量:",
|
||||
"displayDensityDetails": {
|
||||
"default": "預設:5(1080p)、6(2K)、8(4K)",
|
||||
"medium": "中等:6(1080p)、7(2K)、9(4K)",
|
||||
"compact": "緊湊:7(1080p)、8(2K)、10(4K)"
|
||||
"default": "5(1080p)、6(2K)、8(4K)",
|
||||
"medium": "6(1080p)、7(2K)、9(4K)",
|
||||
"compact": "7(1080p)、8(2K)、10(4K)"
|
||||
},
|
||||
"displayDensityWarning": "警告:較高密度可能導致資源有限的系統效能下降。",
|
||||
"showFolderSidebar": "顯示資料夾側邊欄",
|
||||
"showFolderSidebarHelp": "在模型頁面啟用或停用資料夾導覽側邊欄。停用後,側邊欄與滑鼠懸停區域將保持隱藏。",
|
||||
"cardInfoDisplay": "卡片資訊顯示",
|
||||
"cardInfoDisplayOptions": {
|
||||
"always": "永遠顯示",
|
||||
"hover": "滑鼠懸停顯示"
|
||||
},
|
||||
"cardInfoDisplayHelp": "選擇何時顯示模型資訊與操作按鈕:",
|
||||
"cardInfoDisplayDetails": {
|
||||
"always": "永遠顯示:標題與頁腳始終可見",
|
||||
"hover": "滑鼠懸停顯示:標題與頁腳僅在滑鼠懸停時顯示"
|
||||
}
|
||||
"cardInfoDisplayHelp": "選擇何時顯示模型資訊與操作按鈕",
|
||||
"modelCardFooterAction": "模型卡片按鈕操作",
|
||||
"modelCardFooterActionOptions": {
|
||||
"exampleImages": "開啟範例圖片",
|
||||
"replacePreview": "更換預覽圖"
|
||||
},
|
||||
"modelCardFooterActionHelp": "選擇右下角卡片按鈕的功能",
|
||||
"modelNameDisplay": "模型名稱顯示",
|
||||
"modelNameDisplayOptions": {
|
||||
"modelName": "模型名稱",
|
||||
"fileName": "檔案名稱"
|
||||
},
|
||||
"modelNameDisplayHelp": "選擇在模型卡片底部顯示的內容"
|
||||
},
|
||||
"folderSettings": {
|
||||
"activeLibrary": "使用中的資料庫",
|
||||
"activeLibraryHelp": "在已設定的資料庫之間切換以更新預設資料夾。變更選項會重新載入頁面。",
|
||||
"loadingLibraries": "正在載入資料庫...",
|
||||
"noLibraries": "尚未設定任何資料庫",
|
||||
"defaultLoraRoot": "預設 LoRA 根目錄",
|
||||
"defaultLoraRootHelp": "設定下載、匯入和移動時的預設 LoRA 根目錄",
|
||||
"defaultCheckpointRoot": "預設 Checkpoint 根目錄",
|
||||
"defaultCheckpointRootHelp": "設定下載、匯入和移動時的預設 Checkpoint 根目錄",
|
||||
"defaultUnetRoot": "預設 Diffusion Model 根目錄",
|
||||
"defaultUnetRootHelp": "設定下載、匯入和移動時的預設 Diffusion Model (UNET) 根目錄",
|
||||
"defaultEmbeddingRoot": "預設 Embedding 根目錄",
|
||||
"defaultEmbeddingRootHelp": "設定下載、匯入和移動時的預設 Embedding 根目錄",
|
||||
"noDefault": "未設定預設"
|
||||
},
|
||||
"priorityTags": {
|
||||
"title": "優先標籤",
|
||||
"description": "為每種模型類型自訂標籤的優先順序 (例如: character, concept, style(toon|toon_style))",
|
||||
"placeholder": "character, concept, style(toon|toon_style)",
|
||||
"helpLinkLabel": "開啟優先標籤說明",
|
||||
"modelTypes": {
|
||||
"lora": "LoRA",
|
||||
"checkpoint": "Checkpoint",
|
||||
"embedding": "Embedding"
|
||||
},
|
||||
"saveSuccess": "優先標籤已更新。",
|
||||
"saveError": "更新優先標籤失敗。",
|
||||
"loadingSuggestions": "正在載入建議...",
|
||||
"validation": {
|
||||
"missingClosingParen": "項目 {index} 缺少右括號。",
|
||||
"missingCanonical": "項目 {index} 必須包含正規標籤名稱。",
|
||||
"duplicateCanonical": "正規標籤 \"{tag}\" 出現多於一次。",
|
||||
"unknown": "優先標籤設定無效。"
|
||||
}
|
||||
},
|
||||
"downloadPathTemplates": {
|
||||
"title": "下載路徑範本",
|
||||
"help": "設定從 Civitai 下載時不同模型類型的資料夾結構。",
|
||||
@@ -289,6 +408,14 @@
|
||||
"download": "下載",
|
||||
"restartRequired": "需要重新啟動"
|
||||
},
|
||||
"updateFlagStrategy": {
|
||||
"label": "更新標記策略",
|
||||
"help": "決定更新徽章是否僅在新版本與本地檔案共享相同基礎模型時顯示,或只要該模型有任何更新版本就顯示。",
|
||||
"options": {
|
||||
"sameBase": "依基礎模型匹配更新",
|
||||
"any": "顯示任何可用更新"
|
||||
}
|
||||
},
|
||||
"misc": {
|
||||
"includeTriggerWords": "在 LoRA 語法中包含觸發詞",
|
||||
"includeTriggerWordsHelp": "複製 LoRA 語法到剪貼簿時包含訓練觸發詞"
|
||||
@@ -348,12 +475,17 @@
|
||||
"dateAsc": "最舊",
|
||||
"size": "檔案大小",
|
||||
"sizeDesc": "最大",
|
||||
"sizeAsc": "最小"
|
||||
"sizeAsc": "最小",
|
||||
"usage": "使用次數",
|
||||
"usageDesc": "最多",
|
||||
"usageAsc": "最少"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "重新整理模型列表",
|
||||
"quick": "快速刷新(增量)",
|
||||
"full": "完整重建(全部)"
|
||||
"quick": "同步變更",
|
||||
"quickTooltip": "掃描新的或缺少的模型檔案,讓清單保持最新。",
|
||||
"full": "重建快取",
|
||||
"fullTooltip": "從中繼資料檔重新載入所有模型資訊;適用於清單過時或手動編輯後。"
|
||||
},
|
||||
"fetch": {
|
||||
"title": "從 Civitai 取得 metadata",
|
||||
@@ -374,6 +506,13 @@
|
||||
"favorites": {
|
||||
"title": "僅顯示收藏",
|
||||
"action": "收藏"
|
||||
},
|
||||
"updates": {
|
||||
"title": "僅顯示可用更新的模型",
|
||||
"action": "更新",
|
||||
"menuLabel": "顯示更新選項",
|
||||
"check": "檢查更新",
|
||||
"checkTooltip": "檢查更新可能耗時。"
|
||||
}
|
||||
},
|
||||
"bulkOperations": {
|
||||
@@ -382,8 +521,10 @@
|
||||
"viewSelected": "檢視已選取",
|
||||
"addTags": "新增標籤到全部",
|
||||
"setBaseModel": "設定全部基礎模型",
|
||||
"setContentRating": "為全部設定內容分級",
|
||||
"copyAll": "複製全部語法",
|
||||
"refreshAll": "刷新全部 metadata",
|
||||
"checkUpdates": "檢查所選更新",
|
||||
"moveAll": "全部移動到資料夾",
|
||||
"autoOrganize": "自動整理所選模型",
|
||||
"deleteAll": "刪除全部模型",
|
||||
@@ -400,6 +541,7 @@
|
||||
},
|
||||
"contextMenu": {
|
||||
"refreshMetadata": "刷新 Civitai 資料",
|
||||
"checkUpdates": "檢查更新",
|
||||
"relinkCivitai": "重新連結 Civitai",
|
||||
"copySyntax": "複製 LoRA 語法",
|
||||
"copyFilename": "複製模型檔名",
|
||||
@@ -411,6 +553,7 @@
|
||||
"replacePreview": "更換預覽圖",
|
||||
"setContentRating": "設定內容分級",
|
||||
"moveToFolder": "移動到資料夾",
|
||||
"repairMetadata": "修復元數據",
|
||||
"excludeModel": "排除模型",
|
||||
"deleteModel": "刪除模型",
|
||||
"shareRecipe": "分享配方",
|
||||
@@ -421,6 +564,9 @@
|
||||
},
|
||||
"recipes": {
|
||||
"title": "LoRA 配方",
|
||||
"actions": {
|
||||
"sendCheckpoint": "傳送到 ComfyUI"
|
||||
},
|
||||
"controls": {
|
||||
"import": {
|
||||
"action": "匯入",
|
||||
@@ -478,10 +624,26 @@
|
||||
"selectLoraRoot": "請選擇 LoRA 根目錄"
|
||||
}
|
||||
},
|
||||
"sort": {
|
||||
"title": "配方排序...",
|
||||
"name": "名稱",
|
||||
"nameAsc": "A - Z",
|
||||
"nameDesc": "Z - A",
|
||||
"date": "時間",
|
||||
"dateDesc": "最新",
|
||||
"dateAsc": "最舊",
|
||||
"lorasCount": "LoRA 數量",
|
||||
"lorasCountDesc": "最多",
|
||||
"lorasCountAsc": "最少"
|
||||
},
|
||||
"refresh": {
|
||||
"title": "重新整理配方列表"
|
||||
},
|
||||
"filteredByLora": "已依 LoRA 篩選"
|
||||
"filteredByLora": "已依 LoRA 篩選",
|
||||
"favorites": {
|
||||
"title": "僅顯示收藏",
|
||||
"action": "收藏"
|
||||
}
|
||||
},
|
||||
"duplicates": {
|
||||
"found": "發現 {count} 組重複項",
|
||||
@@ -507,23 +669,44 @@
|
||||
"noMissingLoras": "無缺少的 LoRA 可下載",
|
||||
"getInfoFailed": "取得缺少 LoRA 資訊失敗",
|
||||
"prepareError": "準備下載 LoRA 時發生錯誤:{message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "正在修復配方元數據...",
|
||||
"success": "配方元數據修復成功",
|
||||
"skipped": "配方已是最新版本,無需修復",
|
||||
"failed": "修復配方失敗:{message}",
|
||||
"missingId": "無法修復配方:缺少配方 ID"
|
||||
}
|
||||
}
|
||||
},
|
||||
"checkpoints": {
|
||||
"title": "Checkpoint 模型"
|
||||
"title": "Checkpoint 模型",
|
||||
"modelTypes": {
|
||||
"checkpoint": "Checkpoint",
|
||||
"diffusion_model": "Diffusion Model"
|
||||
},
|
||||
"contextMenu": {
|
||||
"moveToOtherTypeFolder": "移動到 {otherType} 資料夾"
|
||||
}
|
||||
},
|
||||
"embeddings": {
|
||||
"title": "Embedding 模型"
|
||||
},
|
||||
"sidebar": {
|
||||
"modelRoot": "模型根目錄",
|
||||
"modelRoot": "根目錄",
|
||||
"collapseAll": "全部摺疊資料夾",
|
||||
"pinSidebar": "固定側邊欄",
|
||||
"unpinSidebar": "取消固定側邊欄",
|
||||
"switchToListView": "切換至列表檢視",
|
||||
"switchToTreeView": "切換至樹狀檢視",
|
||||
"collapseAllDisabled": "列表檢視下不可用"
|
||||
"switchToTreeView": "切換到樹狀檢視",
|
||||
"recursiveOn": "搜尋子資料夾",
|
||||
"recursiveOff": "僅搜尋目前資料夾",
|
||||
"recursiveUnavailable": "遞迴搜尋僅能在樹狀檢視中使用",
|
||||
"collapseAllDisabled": "列表檢視下不可用",
|
||||
"dragDrop": {
|
||||
"unableToResolveRoot": "無法確定移動的目標路徑。",
|
||||
"moveUnsupported": "Move is not supported for this item."
|
||||
}
|
||||
},
|
||||
"statistics": {
|
||||
"title": "統計",
|
||||
@@ -598,6 +781,14 @@
|
||||
"downloadedPreview": "已下載預覽圖片",
|
||||
"downloadingFile": "正在下載 {type} 檔案",
|
||||
"finalizing": "完成下載中..."
|
||||
},
|
||||
"progress": {
|
||||
"currentFile": "目前檔案:",
|
||||
"downloading": "下載中:{name}",
|
||||
"transferred": "已下載:{downloaded} / {total}",
|
||||
"transferredSimple": "已下載:{downloaded}",
|
||||
"transferredUnknown": "已下載:--",
|
||||
"speed": "速度:{speed}"
|
||||
}
|
||||
},
|
||||
"move": {
|
||||
@@ -606,6 +797,7 @@
|
||||
"contentRating": {
|
||||
"title": "設定內容分級",
|
||||
"current": "目前",
|
||||
"multiple": "多個值",
|
||||
"levels": {
|
||||
"pg": "PG",
|
||||
"pg13": "PG13",
|
||||
@@ -644,6 +836,12 @@
|
||||
"countMessage": "模型將被永久刪除。",
|
||||
"action": "全部刪除"
|
||||
},
|
||||
"checkUpdates": {
|
||||
"title": "要檢查所有 {type} 的更新嗎?",
|
||||
"message": "這會為資料庫中的每個 {type} 檢查更新,大型收藏可能會花上一些時間。",
|
||||
"tip": "想分批處理?切換到批次模式,選擇需要的模型,然後使用「檢查所選更新」。",
|
||||
"action": "全部檢查"
|
||||
},
|
||||
"bulkAddTags": {
|
||||
"title": "新增標籤到多個模型",
|
||||
"description": "新增標籤到",
|
||||
@@ -717,7 +915,9 @@
|
||||
},
|
||||
"openFileLocation": {
|
||||
"success": "檔案位置已成功開啟",
|
||||
"failed": "開啟檔案位置失敗"
|
||||
"failed": "開啟檔案位置失敗",
|
||||
"copied": "路徑已複製到剪貼簿:{{path}}",
|
||||
"clipboardFallback": "路徑:{{path}}"
|
||||
},
|
||||
"metadata": {
|
||||
"version": "版本",
|
||||
@@ -740,11 +940,13 @@
|
||||
"addPresetParameter": "新增預設參數...",
|
||||
"strengthMin": "最小強度",
|
||||
"strengthMax": "最大強度",
|
||||
"strengthRange": "強度範圍",
|
||||
"strength": "強度",
|
||||
"clipStrength": "Clip 強度",
|
||||
"clipSkip": "Clip Skip",
|
||||
"valuePlaceholder": "數值",
|
||||
"add": "新增"
|
||||
"add": "新增",
|
||||
"invalidRange": "無效的範圍格式。請使用 x.x-y.y"
|
||||
},
|
||||
"triggerWords": {
|
||||
"label": "觸發詞",
|
||||
@@ -780,13 +982,84 @@
|
||||
"tabs": {
|
||||
"examples": "範例圖片",
|
||||
"description": "模型描述",
|
||||
"recipes": "配方"
|
||||
"recipes": "配方",
|
||||
"versions": "版本"
|
||||
},
|
||||
"navigation": {
|
||||
"label": "模型導覽",
|
||||
"previousWithShortcut": "上一個模型(←)",
|
||||
"nextWithShortcut": "下一個模型(→)",
|
||||
"noPrevious": "沒有上一個模型",
|
||||
"noNext": "沒有下一個模型"
|
||||
},
|
||||
"license": {
|
||||
"noImageSell": "No selling generated content",
|
||||
"noRentCivit": "No Civitai generation",
|
||||
"noRent": "No generation services",
|
||||
"noSell": "No selling models",
|
||||
"creditRequired": "需要創作者標示",
|
||||
"noDerivatives": "禁止分享合併作品",
|
||||
"noReLicense": "需要相同授權",
|
||||
"restrictionsLabel": "授權限制"
|
||||
},
|
||||
"loading": {
|
||||
"exampleImages": "載入範例圖片中...",
|
||||
"description": "載入模型描述中...",
|
||||
"recipes": "載入配方中...",
|
||||
"examples": "載入範例中..."
|
||||
"examples": "載入範例中...",
|
||||
"versions": "載入版本中..."
|
||||
},
|
||||
"versions": {
|
||||
"heading": "模型版本",
|
||||
"copy": "在同一位置追蹤並管理此模型的所有版本。",
|
||||
"media": {
|
||||
"placeholder": "無預覽"
|
||||
},
|
||||
"labels": {
|
||||
"unnamed": "未命名版本",
|
||||
"noDetails": "沒有其他資訊"
|
||||
},
|
||||
"badges": {
|
||||
"current": "目前版本",
|
||||
"inLibrary": "已在庫中",
|
||||
"newer": "較新版本",
|
||||
"ignored": "已忽略"
|
||||
},
|
||||
"actions": {
|
||||
"download": "下載",
|
||||
"delete": "刪除",
|
||||
"ignore": "忽略",
|
||||
"unignore": "取消忽略",
|
||||
"resumeModelUpdates": "恢復追蹤此模型的更新",
|
||||
"ignoreModelUpdates": "忽略此模型的更新",
|
||||
"viewLocalVersions": "檢視所有本地版本",
|
||||
"viewLocalTooltip": "敬請期待"
|
||||
},
|
||||
"filters": {
|
||||
"label": "基礎篩選",
|
||||
"state": {
|
||||
"showAll": "所有版本",
|
||||
"showSameBase": "相同基礎模型"
|
||||
},
|
||||
"tooltip": {
|
||||
"showAllVersions": "切換為顯示所有版本",
|
||||
"showSameBaseVersions": "僅顯示與目前基礎模型相符的版本"
|
||||
},
|
||||
"empty": "沒有符合目前基礎模型篩選的版本。"
|
||||
},
|
||||
"empty": "此模型尚無版本歷史。",
|
||||
"error": "載入版本失敗。",
|
||||
"missingModelId": "此模型缺少 Civitai 模型 ID。",
|
||||
"confirm": {
|
||||
"delete": "要從庫中刪除此版本嗎?"
|
||||
},
|
||||
"toast": {
|
||||
"modelIgnored": "已忽略此模型的更新",
|
||||
"modelResumed": "已恢復更新追蹤",
|
||||
"versionIgnored": "已忽略此版本的更新",
|
||||
"versionUnignored": "已重新啟用此版本",
|
||||
"versionDeleted": "已刪除此版本"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -893,7 +1166,9 @@
|
||||
"loraFailedToSend": "傳送 LoRA 到工作流失敗",
|
||||
"recipeAdded": "配方已附加到工作流",
|
||||
"recipeReplaced": "配方已取代於工作流",
|
||||
"recipeFailedToSend": "傳送配方到工作流失敗"
|
||||
"recipeFailedToSend": "傳送配方到工作流失敗",
|
||||
"noMatchingNodes": "目前工作流程中沒有相容的節點",
|
||||
"noTargetNodeSelected": "未選擇目標節點"
|
||||
},
|
||||
"nodeSelector": {
|
||||
"recipe": "配方",
|
||||
@@ -906,7 +1181,11 @@
|
||||
"exampleImages": {
|
||||
"opened": "範例圖片資料夾已開啟",
|
||||
"openingFolder": "正在開啟範例圖片資料夾",
|
||||
"failedToOpen": "開啟範例圖片資料夾失敗"
|
||||
"failedToOpen": "開啟範例圖片資料夾失敗",
|
||||
"setupRequired": "範例圖片儲存",
|
||||
"setupDescription": "要新增自訂範例圖片,您需要先設定下載位置。",
|
||||
"setupUsage": "此路徑用於儲存下載的範例圖片和自訂圖片。",
|
||||
"openSettings": "開啟設定"
|
||||
}
|
||||
},
|
||||
"help": {
|
||||
@@ -938,6 +1217,11 @@
|
||||
},
|
||||
"update": {
|
||||
"title": "檢查更新",
|
||||
"notificationsTitle": "通知中心",
|
||||
"tabs": {
|
||||
"updates": "更新",
|
||||
"messages": "訊息"
|
||||
},
|
||||
"updateAvailable": "有新版本可用",
|
||||
"noChangelogAvailable": "無詳細更新日誌。請至 GitHub 查看更多資訊。",
|
||||
"currentVersion": "目前版本",
|
||||
@@ -950,6 +1234,7 @@
|
||||
"checkingUpdates": "正在檢查更新...",
|
||||
"checkingMessage": "請稍候,正在檢查最新版本。",
|
||||
"showNotifications": "顯示更新通知",
|
||||
"latestBadge": "最新",
|
||||
"updateProgress": {
|
||||
"preparing": "正在準備更新...",
|
||||
"installing": "正在安裝更新...",
|
||||
@@ -969,6 +1254,13 @@
|
||||
"nightly": {
|
||||
"warning": "警告:Nightly 版本可能包含實驗性功能且可能不穩定。",
|
||||
"enable": "啟用 Nightly 更新"
|
||||
},
|
||||
"banners": {
|
||||
"recent": "最新通知",
|
||||
"empty": "目前沒有最近的橫幅通知。",
|
||||
"shown": "{time} 顯示",
|
||||
"dismissed": "{time} 關閉",
|
||||
"active": "仍在顯示"
|
||||
}
|
||||
},
|
||||
"support": {
|
||||
@@ -1048,6 +1340,9 @@
|
||||
"cannotSend": "無法傳送配方:缺少配方 ID",
|
||||
"sendFailed": "傳送配方到工作流失敗",
|
||||
"sendError": "傳送配方到工作流錯誤",
|
||||
"missingCheckpointPath": "缺少檢查點路徑",
|
||||
"missingCheckpointInfo": "缺少檢查點資訊",
|
||||
"downloadCheckpointFailed": "下載檢查點失敗:{message}",
|
||||
"cannotDelete": "無法刪除配方:缺少配方 ID",
|
||||
"deleteConfirmationError": "顯示刪除確認時發生錯誤",
|
||||
"deletedSuccessfully": "配方已成功刪除",
|
||||
@@ -1084,6 +1379,16 @@
|
||||
"bulkBaseModelUpdateSuccess": "已成功為 {count} 個模型更新基礎模型",
|
||||
"bulkBaseModelUpdatePartial": "已更新 {success} 個模型,{failed} 個模型失敗",
|
||||
"bulkBaseModelUpdateFailed": "更新所選模型的基礎模型失敗",
|
||||
"bulkContentRatingUpdating": "正在為 {count} 個模型更新內容分級...",
|
||||
"bulkContentRatingSet": "已將 {count} 個模型的內容分級設定為 {level}",
|
||||
"bulkContentRatingPartial": "已將 {success} 個模型的內容分級設定為 {level},{failed} 個失敗",
|
||||
"bulkContentRatingFailed": "無法更新所選模型的內容分級",
|
||||
"bulkUpdatesChecking": "正在檢查所選 {type} 的更新...",
|
||||
"bulkUpdatesSuccess": "{count} 個所選 {type} 有可用更新",
|
||||
"bulkUpdatesNone": "所選 {type} 未找到更新",
|
||||
"bulkUpdatesMissing": "所選 {type} 未連結 Civitai 更新",
|
||||
"bulkUpdatesPartialMissing": "已略過 {missing} 個未連結 Civitai 的所選 {type}",
|
||||
"bulkUpdatesFailed": "檢查所選 {type} 更新失敗:{message}",
|
||||
"invalidCharactersRemoved": "已移除檔名中的無效字元",
|
||||
"filenameCannotBeEmpty": "檔案名稱不可為空",
|
||||
"renameFailed": "重新命名檔案失敗:{message}",
|
||||
@@ -1095,6 +1400,7 @@
|
||||
"verificationCompleteSuccess": "驗證完成。所有檔案均確認為重複項。",
|
||||
"verificationFailed": "驗證雜湊失敗:{message}",
|
||||
"noTagsToAdd": "沒有可新增的標籤",
|
||||
"bulkTagsUpdating": "正在更新 {count} 個模型的標籤...",
|
||||
"tagsAddedSuccessfully": "已成功將 {tagCount} 個標籤新增到 {count} 個 {type}",
|
||||
"tagsReplacedSuccessfully": "已成功以 {tagCount} 個標籤取代 {count} 個 {type} 的標籤",
|
||||
"tagsAddFailed": "新增標籤到 {count} 個模型失敗",
|
||||
@@ -1108,6 +1414,7 @@
|
||||
"settings": {
|
||||
"loraRootsFailed": "載入 LoRA 根目錄失敗:{message}",
|
||||
"checkpointRootsFailed": "載入 checkpoint 根目錄失敗:{message}",
|
||||
"unetRootsFailed": "載入 Diffusion Model 根目錄失敗:{message}",
|
||||
"embeddingRootsFailed": "載入 embedding 根目錄失敗:{message}",
|
||||
"mappingsUpdated": "基礎模型路徑對應已更新({count} 個對應)",
|
||||
"mappingsCleared": "基礎模型路徑對應已清除",
|
||||
@@ -1118,6 +1425,8 @@
|
||||
"compactModeToggled": "緊湊模式已{state}",
|
||||
"settingSaveFailed": "儲存設定失敗:{message}",
|
||||
"displayDensitySet": "顯示密度已設為 {density}",
|
||||
"libraryLoadFailed": "Failed to load libraries: {message}",
|
||||
"libraryActivateFailed": "Failed to activate library: {message}",
|
||||
"languageChangeFailed": "切換語言失敗:{message}",
|
||||
"cacheCleared": "快取檔案已成功清除。快取將於下次操作時重建。",
|
||||
"cacheClearFailed": "清除快取失敗:{error}",
|
||||
@@ -1126,7 +1435,26 @@
|
||||
"filters": {
|
||||
"applied": "{message}",
|
||||
"cleared": "篩選已清除",
|
||||
"noCustomFilterToClear": "無自訂篩選可清除"
|
||||
"noCustomFilterToClear": "無自訂篩選可清除",
|
||||
"noActiveFilters": "沒有可儲存的啟用篩選"
|
||||
},
|
||||
"presets": {
|
||||
"created": "預設 \"{name}\" 已建立",
|
||||
"deleted": "預設 \"{name}\" 已刪除",
|
||||
"applied": "預設 \"{name}\" 已套用",
|
||||
"overwritten": "預設 \"{name}\" 已覆蓋",
|
||||
"restored": "預設設定已恢復"
|
||||
},
|
||||
"error": {
|
||||
"presetNameEmpty": "預設名稱不能為空",
|
||||
"presetNameTooLong": "預設名稱不能超過 {max} 個字元",
|
||||
"presetNameInvalidChars": "預設名稱包含無效字元",
|
||||
"presetNameExists": "已存在同名預設",
|
||||
"maxPresetsReached": "最多允許 {max} 個預設。刪除一個以新增更多。",
|
||||
"presetNotFound": "預設未找到",
|
||||
"invalidPreset": "無效的預設資料",
|
||||
"deletePresetFailed": "刪除預設失敗",
|
||||
"applyPresetFailed": "套用預設失敗"
|
||||
},
|
||||
"downloads": {
|
||||
"imagesCompleted": "範例圖片{action}完成",
|
||||
@@ -1142,7 +1470,7 @@
|
||||
},
|
||||
"triggerWords": {
|
||||
"loadFailed": "無法載入訓練詞",
|
||||
"tooLong": "觸發詞不可超過 30 個字",
|
||||
"tooLong": "觸發詞不可超過 100 個字",
|
||||
"tooMany": "最多允許 30 個觸發詞",
|
||||
"alreadyExists": "此觸發詞已存在",
|
||||
"updateSuccess": "觸發詞已更新",
|
||||
@@ -1191,6 +1519,8 @@
|
||||
"pauseFailed": "暫停下載失敗:{error}",
|
||||
"downloadResumed": "下載已恢復",
|
||||
"resumeFailed": "恢復下載失敗:{error}",
|
||||
"downloadStopped": "下載已取消",
|
||||
"stopFailed": "取消下載失敗:{error}",
|
||||
"deleted": "範例圖片已刪除",
|
||||
"deleteFailed": "刪除範例圖片失敗",
|
||||
"setPreviewFailed": "設定預覽圖片失敗"
|
||||
@@ -1211,6 +1541,8 @@
|
||||
"metadataRefreshed": "metadata 已成功刷新",
|
||||
"metadataRefreshFailed": "刷新 metadata 失敗:{message}",
|
||||
"metadataUpdateComplete": "metadata 更新完成",
|
||||
"operationCancelled": "操作已由用戶取消",
|
||||
"operationCancelledPartial": "操作已取消。已處理 {success} 個項目。",
|
||||
"metadataFetchFailed": "取得 metadata 失敗:{message}",
|
||||
"bulkMetadataCompleteAll": "已成功刷新全部 {count} 個 {type}",
|
||||
"bulkMetadataCompletePartial": "已刷新 {success} / {total} 個 {type}",
|
||||
@@ -1227,7 +1559,8 @@
|
||||
"bulkMoveFailures": "移動失敗:\n{failures}",
|
||||
"bulkMoveSuccess": "已成功移動 {successCount} 個 {type}",
|
||||
"exampleImagesDownloadSuccess": "範例圖片下載成功!",
|
||||
"exampleImagesDownloadFailed": "下載範例圖片失敗:{message}"
|
||||
"exampleImagesDownloadFailed": "下載範例圖片失敗:{message}",
|
||||
"moveFailed": "Failed to move item: {message}"
|
||||
}
|
||||
},
|
||||
"banners": {
|
||||
@@ -1237,6 +1570,26 @@
|
||||
"refreshNow": "立即重新整理",
|
||||
"refreshingIn": "將於",
|
||||
"seconds": "秒後重新整理"
|
||||
},
|
||||
"communitySupport": {
|
||||
"title": "Keep LoRA Manager Thriving with Your Support ❤️",
|
||||
"content": "LoRA Manager is a passion project maintained full-time by a solo developer. Your support on Ko-fi helps cover development costs, keeps new updates coming, and unlocks a license key for the LM Civitai Extension as a thank-you gift. Every contribution truly makes a difference.",
|
||||
"supportCta": "Support on Ko-fi",
|
||||
"learnMore": "LM Civitai Extension Tutorial"
|
||||
},
|
||||
"cacheHealth": {
|
||||
"corrupted": {
|
||||
"title": "檢測到快取損壞"
|
||||
},
|
||||
"degraded": {
|
||||
"title": "檢測到快取問題"
|
||||
},
|
||||
"content": "{total} 個快取項目中有 {invalid} 個無效({rate})。這可能會導致模型遺失或錯誤。建議重建快取。",
|
||||
"rebuildCache": "重建快取",
|
||||
"dismiss": "關閉",
|
||||
"rebuilding": "重建快取中...",
|
||||
"rebuildFailed": "重建快取失敗:{error}",
|
||||
"retry": "重試"
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
3
package-lock.json
generated
3
package-lock.json
generated
@@ -114,6 +114,7 @@
|
||||
}
|
||||
],
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"engines": {
|
||||
"node": ">=18"
|
||||
},
|
||||
@@ -137,6 +138,7 @@
|
||||
}
|
||||
],
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"engines": {
|
||||
"node": ">=18"
|
||||
}
|
||||
@@ -1611,6 +1613,7 @@
|
||||
"integrity": "sha512-MyL55p3Ut3cXbeBEG7Hcv0mVM8pp8PBNWxRqchZnSfAiES1v1mRnMeFfaHWIPULpwsYfvO+ZmMZz5tGCnjzDUQ==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"dependencies": {
|
||||
"cssstyle": "^4.0.1",
|
||||
"data-urls": "^5.0.0",
|
||||
|
||||
@@ -4,8 +4,11 @@
|
||||
"private": true,
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"test": "vitest run",
|
||||
"test:watch": "vitest"
|
||||
"test": "npm run test:js && npm run test:vue",
|
||||
"test:js": "vitest run",
|
||||
"test:vue": "cd vue-widgets && npx vitest run",
|
||||
"test:watch": "vitest",
|
||||
"test:coverage": "node scripts/run_frontend_coverage.js"
|
||||
},
|
||||
"devDependencies": {
|
||||
"jsdom": "^24.0.0",
|
||||
|
||||
927
py/config.py
927
py/config.py
File diff suppressed because it is too large
Load Diff
@@ -2,7 +2,15 @@ import asyncio
|
||||
import sys
|
||||
import os
|
||||
import logging
|
||||
from pathlib import Path
|
||||
from .utils.logging_config import setup_logging
|
||||
|
||||
# Check if we're in standalone mode
|
||||
standalone_mode = os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1" or os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
|
||||
|
||||
# Only setup logging prefix if not in standalone mode
|
||||
if not standalone_mode:
|
||||
setup_logging()
|
||||
|
||||
from server import PromptServer # type: ignore
|
||||
|
||||
from .config import config
|
||||
@@ -11,17 +19,47 @@ from .routes.recipe_routes import RecipeRoutes
|
||||
from .routes.stats_routes import StatsRoutes
|
||||
from .routes.update_routes import UpdateRoutes
|
||||
from .routes.misc_routes import MiscRoutes
|
||||
from .routes.preview_routes import PreviewRoutes
|
||||
from .routes.example_images_routes import ExampleImagesRoutes
|
||||
from .services.service_registry import ServiceRegistry
|
||||
from .services.settings_manager import settings
|
||||
from .services.settings_manager import get_settings_manager
|
||||
from .utils.example_images_migration import ExampleImagesMigration
|
||||
from .services.websocket_manager import ws_manager
|
||||
from .services.example_images_cleanup_service import ExampleImagesCleanupService
|
||||
from .middleware.csp_middleware import relax_csp_for_remote_media
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Check if we're in standalone mode
|
||||
STANDALONE_MODE = 'nodes' not in sys.modules
|
||||
HEADER_SIZE_LIMIT = 16384
|
||||
|
||||
|
||||
def _sanitize_size_limit(value):
|
||||
"""Return a non-negative integer size for ``handler_args`` comparisons."""
|
||||
|
||||
try:
|
||||
coerced = int(value)
|
||||
except (TypeError, ValueError):
|
||||
return 0
|
||||
return coerced if coerced >= 0 else 0
|
||||
|
||||
|
||||
class _SettingsProxy:
|
||||
def __init__(self):
|
||||
self._manager = None
|
||||
|
||||
def _resolve(self):
|
||||
if self._manager is None:
|
||||
self._manager = get_settings_manager()
|
||||
return self._manager
|
||||
|
||||
def get(self, *args, **kwargs):
|
||||
return self._resolve().get(*args, **kwargs)
|
||||
|
||||
def __getattr__(self, item):
|
||||
return getattr(self._resolve(), item)
|
||||
|
||||
|
||||
settings = _SettingsProxy()
|
||||
|
||||
class LoraManager:
|
||||
"""Main entry point for LoRA Manager plugin"""
|
||||
@@ -31,6 +69,41 @@ class LoraManager:
|
||||
"""Initialize and register all routes using the new refactored architecture"""
|
||||
app = PromptServer.instance.app
|
||||
|
||||
if relax_csp_for_remote_media not in app.middlewares:
|
||||
# Ensure CSP relaxer executes after ComfyUI's block_external_middleware so it can
|
||||
# see and extend the restrictive header instead of being overwritten by it.
|
||||
block_middleware_index = next(
|
||||
(
|
||||
idx
|
||||
for idx, middleware in enumerate(app.middlewares)
|
||||
if getattr(middleware, "__name__", "") == "block_external_middleware"
|
||||
),
|
||||
None,
|
||||
)
|
||||
|
||||
if block_middleware_index is None:
|
||||
app.middlewares.append(relax_csp_for_remote_media)
|
||||
else:
|
||||
app.middlewares.insert(block_middleware_index, relax_csp_for_remote_media)
|
||||
|
||||
# Increase allowed header sizes so browsers with large localhost cookie
|
||||
# jars (multiple UIs on 127.0.0.1) don't trip aiohttp's 8KB default
|
||||
# limits. Cookies for unrelated apps are still sent to the plugin and
|
||||
# may otherwise raise LineTooLong errors when the request parser reads
|
||||
# them. Preserve any previously configured handler arguments while
|
||||
# ensuring our minimum sizes are applied.
|
||||
handler_args = getattr(app, "_handler_args", {}) or {}
|
||||
updated_handler_args = dict(handler_args)
|
||||
updated_handler_args["max_field_size"] = max(
|
||||
_sanitize_size_limit(handler_args.get("max_field_size", 0)),
|
||||
HEADER_SIZE_LIMIT,
|
||||
)
|
||||
updated_handler_args["max_line_size"] = max(
|
||||
_sanitize_size_limit(handler_args.get("max_line_size", 0)),
|
||||
HEADER_SIZE_LIMIT,
|
||||
)
|
||||
app._handler_args = updated_handler_args
|
||||
|
||||
# Configure aiohttp access logger to be less verbose
|
||||
logging.getLogger('aiohttp.access').setLevel(logging.WARNING)
|
||||
|
||||
@@ -50,102 +123,12 @@ class LoraManager:
|
||||
asyncio_logger = logging.getLogger("asyncio")
|
||||
asyncio_logger.addFilter(ConnectionResetFilter())
|
||||
|
||||
added_targets = set() # Track already added target paths
|
||||
|
||||
# Add static route for example images if the path exists in settings
|
||||
example_images_path = settings.get('example_images_path')
|
||||
logger.info(f"Example images path: {example_images_path}")
|
||||
if example_images_path and os.path.exists(example_images_path):
|
||||
app.router.add_static('/example_images_static', example_images_path)
|
||||
logger.info(f"Added static route for example images: /example_images_static -> {example_images_path}")
|
||||
|
||||
# Add static routes for each lora root
|
||||
for idx, root in enumerate(config.loras_roots, start=1):
|
||||
preview_path = f'/loras_static/root{idx}/preview'
|
||||
|
||||
real_root = root
|
||||
if root in config._path_mappings.values():
|
||||
for target, link in config._path_mappings.items():
|
||||
if link == root:
|
||||
real_root = target
|
||||
break
|
||||
# Add static route for original path
|
||||
app.router.add_static(preview_path, real_root)
|
||||
logger.info(f"Added static route {preview_path} -> {real_root}")
|
||||
|
||||
# Record route mapping
|
||||
config.add_route_mapping(real_root, preview_path)
|
||||
added_targets.add(real_root)
|
||||
|
||||
# Add static routes for each checkpoint root
|
||||
for idx, root in enumerate(config.base_models_roots, start=1):
|
||||
preview_path = f'/checkpoints_static/root{idx}/preview'
|
||||
|
||||
real_root = root
|
||||
if root in config._path_mappings.values():
|
||||
for target, link in config._path_mappings.items():
|
||||
if link == root:
|
||||
real_root = target
|
||||
break
|
||||
# Add static route for original path
|
||||
app.router.add_static(preview_path, real_root)
|
||||
logger.info(f"Added static route {preview_path} -> {real_root}")
|
||||
|
||||
# Record route mapping
|
||||
config.add_route_mapping(real_root, preview_path)
|
||||
added_targets.add(real_root)
|
||||
|
||||
# Add static routes for each embedding root
|
||||
for idx, root in enumerate(config.embeddings_roots, start=1):
|
||||
preview_path = f'/embeddings_static/root{idx}/preview'
|
||||
|
||||
real_root = root
|
||||
if root in config._path_mappings.values():
|
||||
for target, link in config._path_mappings.items():
|
||||
if link == root:
|
||||
real_root = target
|
||||
break
|
||||
# Add static route for original path
|
||||
app.router.add_static(preview_path, real_root)
|
||||
logger.info(f"Added static route {preview_path} -> {real_root}")
|
||||
|
||||
# Record route mapping
|
||||
config.add_route_mapping(real_root, preview_path)
|
||||
added_targets.add(real_root)
|
||||
|
||||
# Add static routes for symlink target paths
|
||||
link_idx = {
|
||||
'lora': 1,
|
||||
'checkpoint': 1,
|
||||
'embedding': 1
|
||||
}
|
||||
|
||||
for target_path, link_path in config._path_mappings.items():
|
||||
if target_path not in added_targets:
|
||||
# Determine if this is a checkpoint, lora, or embedding link based on path
|
||||
is_checkpoint = any(cp_root in link_path for cp_root in config.base_models_roots)
|
||||
is_checkpoint = is_checkpoint or any(cp_root in target_path for cp_root in config.base_models_roots)
|
||||
is_embedding = any(emb_root in link_path for emb_root in config.embeddings_roots)
|
||||
is_embedding = is_embedding or any(emb_root in target_path for emb_root in config.embeddings_roots)
|
||||
|
||||
if is_checkpoint:
|
||||
route_path = f'/checkpoints_static/link_{link_idx["checkpoint"]}/preview'
|
||||
link_idx["checkpoint"] += 1
|
||||
elif is_embedding:
|
||||
route_path = f'/embeddings_static/link_{link_idx["embedding"]}/preview'
|
||||
link_idx["embedding"] += 1
|
||||
else:
|
||||
route_path = f'/loras_static/link_{link_idx["lora"]}/preview'
|
||||
link_idx["lora"] += 1
|
||||
|
||||
try:
|
||||
app.router.add_static(route_path, Path(target_path).resolve(strict=False))
|
||||
logger.info(f"Added static route for link target {route_path} -> {target_path}")
|
||||
config.add_route_mapping(target_path, route_path)
|
||||
added_targets.add(target_path)
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to add static route on initialization for {target_path}: {e}")
|
||||
continue
|
||||
|
||||
# Add static route for locales JSON files
|
||||
if os.path.exists(config.i18n_path):
|
||||
@@ -168,6 +151,7 @@ class LoraManager:
|
||||
UpdateRoutes.setup_routes(app)
|
||||
MiscRoutes.setup_routes(app)
|
||||
ExampleImagesRoutes.setup_routes(app, ws_manager=ws_manager)
|
||||
PreviewRoutes.setup_routes(app)
|
||||
|
||||
# Setup WebSocket routes that are shared across all model types
|
||||
app.router.add_get('/ws/fetch-progress', ws_manager.handle_connection)
|
||||
@@ -180,8 +164,6 @@ class LoraManager:
|
||||
# Add cleanup
|
||||
app.on_shutdown.append(cls._cleanup)
|
||||
|
||||
logger.info(f"LoRA Manager: Set up routes for {len(ModelServiceFactory.get_registered_types())} model types: {', '.join(ModelServiceFactory.get_registered_types())}")
|
||||
|
||||
@classmethod
|
||||
async def _initialize_services(cls):
|
||||
"""Initialize all services using the ServiceRegistry"""
|
||||
|
||||
@@ -1,7 +1,10 @@
|
||||
import os
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Check if running in standalone mode
|
||||
standalone_mode = os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
|
||||
standalone_mode = os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1" or os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
|
||||
|
||||
if not standalone_mode:
|
||||
from .metadata_hook import MetadataHook
|
||||
@@ -14,7 +17,7 @@ if not standalone_mode:
|
||||
# Initialize registry
|
||||
registry = MetadataRegistry()
|
||||
|
||||
print("ComfyUI Metadata Collector initialized")
|
||||
logger.info("ComfyUI Metadata Collector initialized")
|
||||
|
||||
def get_metadata(prompt_id=None):
|
||||
"""Helper function to get metadata from the registry"""
|
||||
@@ -23,7 +26,7 @@ if not standalone_mode:
|
||||
else:
|
||||
# Standalone mode - provide dummy implementations
|
||||
def init():
|
||||
print("ComfyUI Metadata Collector disabled in standalone mode")
|
||||
logger.info("ComfyUI Metadata Collector disabled in standalone mode")
|
||||
|
||||
def get_metadata(prompt_id=None):
|
||||
"""Dummy implementation for standalone mode"""
|
||||
|
||||
@@ -1,7 +1,10 @@
|
||||
import sys
|
||||
import inspect
|
||||
import logging
|
||||
from .metadata_registry import MetadataRegistry
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class MetadataHook:
|
||||
"""Install hooks for metadata collection"""
|
||||
|
||||
@@ -23,7 +26,7 @@ class MetadataHook:
|
||||
|
||||
# If we can't find the execution module, we can't install hooks
|
||||
if execution is None:
|
||||
print("Could not locate ComfyUI execution module, metadata collection disabled")
|
||||
logger.warning("Could not locate ComfyUI execution module, metadata collection disabled")
|
||||
return
|
||||
|
||||
# Detect whether we're using the new async version of ComfyUI
|
||||
@@ -37,16 +40,16 @@ class MetadataHook:
|
||||
is_async = inspect.iscoroutinefunction(execution._map_node_over_list)
|
||||
|
||||
if is_async:
|
||||
print("Detected async ComfyUI execution, installing async metadata hooks")
|
||||
logger.info("Detected async ComfyUI execution, installing async metadata hooks")
|
||||
MetadataHook._install_async_hooks(execution, map_node_func_name)
|
||||
else:
|
||||
print("Detected sync ComfyUI execution, installing sync metadata hooks")
|
||||
logger.info("Detected sync ComfyUI execution, installing sync metadata hooks")
|
||||
MetadataHook._install_sync_hooks(execution)
|
||||
|
||||
print("Metadata collection hooks installed for runtime values")
|
||||
logger.info("Metadata collection hooks installed for runtime values")
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error installing metadata hooks: {str(e)}")
|
||||
logger.error(f"Error installing metadata hooks: {str(e)}")
|
||||
|
||||
@staticmethod
|
||||
def _install_sync_hooks(execution):
|
||||
@@ -82,7 +85,7 @@ class MetadataHook:
|
||||
if node_id is not None:
|
||||
registry.record_node_execution(node_id, class_type, input_data_all, None)
|
||||
except Exception as e:
|
||||
print(f"Error collecting metadata (pre-execution): {str(e)}")
|
||||
logger.error(f"Error collecting metadata (pre-execution): {str(e)}")
|
||||
|
||||
# Execute the original function
|
||||
results = original_map_node_over_list(obj, input_data_all, func, allow_interrupt, execution_block_cb, pre_execute_cb)
|
||||
@@ -113,7 +116,7 @@ class MetadataHook:
|
||||
if node_id is not None:
|
||||
registry.update_node_execution(node_id, class_type, results)
|
||||
except Exception as e:
|
||||
print(f"Error collecting metadata (post-execution): {str(e)}")
|
||||
logger.error(f"Error collecting metadata (post-execution): {str(e)}")
|
||||
|
||||
return results
|
||||
|
||||
@@ -159,7 +162,7 @@ class MetadataHook:
|
||||
if node_id is not None:
|
||||
registry.record_node_execution(node_id, class_type, input_data_all, None)
|
||||
except Exception as e:
|
||||
print(f"Error collecting metadata (pre-execution): {str(e)}")
|
||||
logger.error(f"Error collecting metadata (pre-execution): {str(e)}")
|
||||
|
||||
# Call original function with all args/kwargs
|
||||
results = await original_map_node_over_list(
|
||||
@@ -176,7 +179,7 @@ class MetadataHook:
|
||||
if node_id is not None:
|
||||
registry.update_node_execution(node_id, class_type, results)
|
||||
except Exception as e:
|
||||
print(f"Error collecting metadata (post-execution): {str(e)}")
|
||||
logger.error(f"Error collecting metadata (post-execution): {str(e)}")
|
||||
|
||||
return results
|
||||
|
||||
|
||||
@@ -3,7 +3,7 @@ import os
|
||||
from .constants import IMAGES
|
||||
|
||||
# Check if running in standalone mode
|
||||
standalone_mode = os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
|
||||
standalone_mode = os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1" or os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
|
||||
|
||||
from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IS_SAMPLER
|
||||
|
||||
@@ -39,8 +39,39 @@ class MetadataProcessor:
|
||||
if node_id in metadata.get(SAMPLING, {}) and metadata[SAMPLING][node_id].get(IS_SAMPLER, False):
|
||||
candidate_samplers[node_id] = metadata[SAMPLING][node_id]
|
||||
|
||||
# If we found candidate samplers, apply primary sampler logic to these candidates only
|
||||
if candidate_samplers:
|
||||
# If we found candidate samplers, apply primary sampler logic to these candidates only
|
||||
|
||||
# PRE-PROCESS: Ensure all candidate samplers have their parameters populated
|
||||
# This is especially important for SamplerCustomAdvanced which needs tracing
|
||||
prompt = metadata.get("current_prompt")
|
||||
for node_id in candidate_samplers:
|
||||
# If a sampler is missing common parameters like steps or denoise,
|
||||
# try to populate them using tracing before ranking
|
||||
sampler_info = candidate_samplers[node_id]
|
||||
params = sampler_info.get("parameters", {})
|
||||
|
||||
if prompt and (params.get("steps") is None or params.get("denoise") is None):
|
||||
# Create a temporary params dict to use the handler
|
||||
temp_params = {
|
||||
"steps": params.get("steps"),
|
||||
"denoise": params.get("denoise"),
|
||||
"sampler": params.get("sampler_name"),
|
||||
"scheduler": params.get("scheduler")
|
||||
}
|
||||
|
||||
# Check if it's SamplerCustomAdvanced
|
||||
if prompt.original_prompt and node_id in prompt.original_prompt:
|
||||
if prompt.original_prompt[node_id].get("class_type") == "SamplerCustomAdvanced":
|
||||
MetadataProcessor.handle_custom_advanced_sampler(metadata, prompt, node_id, temp_params)
|
||||
|
||||
# Update the actual parameters with found values
|
||||
params["steps"] = temp_params.get("steps")
|
||||
params["denoise"] = temp_params.get("denoise")
|
||||
if temp_params.get("sampler"):
|
||||
params["sampler_name"] = temp_params.get("sampler")
|
||||
if temp_params.get("scheduler"):
|
||||
params["scheduler"] = temp_params.get("scheduler")
|
||||
|
||||
# Collect potential primary samplers based on different criteria
|
||||
custom_advanced_samplers = []
|
||||
advanced_add_noise_samplers = []
|
||||
@@ -49,7 +80,6 @@ class MetadataProcessor:
|
||||
high_denoise_id = None
|
||||
|
||||
# First, check for SamplerCustomAdvanced among candidates
|
||||
prompt = metadata.get("current_prompt")
|
||||
if prompt and prompt.original_prompt:
|
||||
for node_id in candidate_samplers:
|
||||
node_info = prompt.original_prompt.get(node_id, {})
|
||||
@@ -77,15 +107,16 @@ class MetadataProcessor:
|
||||
# Combine all potential primary samplers
|
||||
potential_samplers = custom_advanced_samplers + advanced_add_noise_samplers + high_denoise_samplers
|
||||
|
||||
# Find the most recent potential primary sampler (closest to downstream node)
|
||||
for i in range(downstream_index - 1, -1, -1):
|
||||
# Find the first potential primary sampler (prefer base sampler over refine)
|
||||
# Use forward search to prioritize the first one in execution order
|
||||
for i in range(downstream_index):
|
||||
node_id = execution_order[i]
|
||||
if node_id in potential_samplers:
|
||||
return node_id, candidate_samplers[node_id]
|
||||
|
||||
# If no potential sampler found from our criteria, return the most recent sampler
|
||||
# If no potential sampler found from our criteria, return the first sampler
|
||||
if candidate_samplers:
|
||||
for i in range(downstream_index - 1, -1, -1):
|
||||
for i in range(downstream_index):
|
||||
node_id = execution_order[i]
|
||||
if node_id in candidate_samplers:
|
||||
return node_id, candidate_samplers[node_id]
|
||||
@@ -176,8 +207,11 @@ class MetadataProcessor:
|
||||
found_node_id = input_value[0] # Connected node_id
|
||||
|
||||
# If we're looking for a specific node class
|
||||
if target_class and prompt.original_prompt[found_node_id].get("class_type") == target_class:
|
||||
return found_node_id
|
||||
if target_class:
|
||||
if found_node_id not in prompt.original_prompt:
|
||||
return None
|
||||
if prompt.original_prompt[found_node_id].get("class_type") == target_class:
|
||||
return found_node_id
|
||||
|
||||
# If we're not looking for a specific class, update the last valid node
|
||||
if not target_class:
|
||||
@@ -185,11 +219,19 @@ class MetadataProcessor:
|
||||
|
||||
# Continue tracing through intermediate nodes
|
||||
current_node_id = found_node_id
|
||||
# For most conditioning nodes, the input we want to follow is named "conditioning"
|
||||
if "conditioning" in prompt.original_prompt[current_node_id].get("inputs", {}):
|
||||
|
||||
# Check if current source node exists
|
||||
if current_node_id not in prompt.original_prompt:
|
||||
return found_node_id if not target_class else None
|
||||
|
||||
# Determine which input to follow next on the source node
|
||||
source_node_inputs = prompt.original_prompt[current_node_id].get("inputs", {})
|
||||
if input_name in source_node_inputs:
|
||||
current_input = input_name
|
||||
elif "conditioning" in source_node_inputs:
|
||||
current_input = "conditioning"
|
||||
else:
|
||||
# If there's no "conditioning" input, return the current node
|
||||
# If there's no suitable input to follow, return the current node
|
||||
# if we're not looking for a specific target_class
|
||||
return found_node_id if not target_class else None
|
||||
else:
|
||||
@@ -202,12 +244,89 @@ class MetadataProcessor:
|
||||
return last_valid_node if not target_class else None
|
||||
|
||||
@staticmethod
|
||||
def find_primary_checkpoint(metadata):
|
||||
"""Find the primary checkpoint model in the workflow"""
|
||||
if not metadata.get(MODELS):
|
||||
def trace_model_path(metadata, prompt, start_node_id):
|
||||
"""
|
||||
Trace the model connection path upstream to find the checkpoint
|
||||
"""
|
||||
if not prompt or not prompt.original_prompt:
|
||||
return None
|
||||
|
||||
# In most workflows, there's only one checkpoint, so we can just take the first one
|
||||
current_node_id = start_node_id
|
||||
depth = 0
|
||||
max_depth = 50
|
||||
|
||||
while depth < max_depth:
|
||||
# Check if current node is a registered checkpoint in our metadata
|
||||
# This handles cached nodes correctly because metadata contains info for all nodes in the graph
|
||||
if current_node_id in metadata.get(MODELS, {}):
|
||||
if metadata[MODELS][current_node_id].get("type") == "checkpoint":
|
||||
return current_node_id
|
||||
|
||||
if current_node_id not in prompt.original_prompt:
|
||||
return None
|
||||
|
||||
node = prompt.original_prompt[current_node_id]
|
||||
inputs = node.get("inputs", {})
|
||||
class_type = node.get("class_type", "")
|
||||
|
||||
# Determine which input to follow next
|
||||
next_input_name = "model"
|
||||
|
||||
# Special handling for initial node
|
||||
if depth == 0:
|
||||
if class_type == "SamplerCustomAdvanced":
|
||||
next_input_name = "guider"
|
||||
|
||||
# If the specific input doesn't exist, try generic 'model'
|
||||
if next_input_name not in inputs:
|
||||
if "model" in inputs:
|
||||
next_input_name = "model"
|
||||
elif "basic_pipe" in inputs:
|
||||
# Handle pipe nodes like FromBasicPipe by following the pipeline
|
||||
next_input_name = "basic_pipe"
|
||||
else:
|
||||
# Dead end - no model input to follow
|
||||
return None
|
||||
|
||||
# Get connected node
|
||||
input_val = inputs[next_input_name]
|
||||
if isinstance(input_val, list) and len(input_val) > 0:
|
||||
current_node_id = input_val[0]
|
||||
else:
|
||||
return None
|
||||
|
||||
depth += 1
|
||||
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def find_primary_checkpoint(metadata, downstream_id=None, primary_sampler_id=None):
|
||||
"""
|
||||
Find the primary checkpoint model in the workflow
|
||||
|
||||
Parameters:
|
||||
- metadata: The workflow metadata
|
||||
- downstream_id: Optional ID of a downstream node to help identify the specific primary sampler
|
||||
- primary_sampler_id: Optional ID of the primary sampler if already known
|
||||
"""
|
||||
if not metadata.get(MODELS):
|
||||
return None
|
||||
|
||||
# Method 1: Topology-based tracing (More accurate for complex workflows)
|
||||
# First, find the primary sampler if not provided
|
||||
if not primary_sampler_id:
|
||||
primary_sampler_id, _ = MetadataProcessor.find_primary_sampler(metadata, downstream_id)
|
||||
|
||||
if primary_sampler_id:
|
||||
prompt = metadata.get("current_prompt")
|
||||
if prompt:
|
||||
# Trace back from the sampler to find the checkpoint
|
||||
checkpoint_id = MetadataProcessor.trace_model_path(metadata, prompt, primary_sampler_id)
|
||||
if checkpoint_id and checkpoint_id in metadata.get(MODELS, {}):
|
||||
return metadata[MODELS][checkpoint_id].get("name")
|
||||
|
||||
# Method 2: Fallback to the first available checkpoint (Original behavior)
|
||||
# In most simple workflows, there's only one checkpoint, so we can just take the first one
|
||||
for node_id, model_info in metadata.get(MODELS, {}).items():
|
||||
if model_info.get("type") == "checkpoint":
|
||||
return model_info.get("name")
|
||||
@@ -311,7 +430,8 @@ class MetadataProcessor:
|
||||
primary_sampler_id, primary_sampler = MetadataProcessor.find_primary_sampler(metadata, id)
|
||||
|
||||
# Directly get checkpoint from metadata instead of tracing
|
||||
checkpoint = MetadataProcessor.find_primary_checkpoint(metadata)
|
||||
# Pass primary_sampler_id to avoid redundant calculation
|
||||
checkpoint = MetadataProcessor.find_primary_checkpoint(metadata, id, primary_sampler_id)
|
||||
if checkpoint:
|
||||
params["checkpoint"] = checkpoint
|
||||
|
||||
@@ -445,6 +565,7 @@ class MetadataProcessor:
|
||||
scheduler_params = metadata[SAMPLING][scheduler_node_id].get("parameters", {})
|
||||
params["steps"] = scheduler_params.get("steps")
|
||||
params["scheduler"] = scheduler_params.get("scheduler")
|
||||
params["denoise"] = scheduler_params.get("denoise")
|
||||
|
||||
# 2. Trace sampler input to find KSamplerSelect (only if sampler input exists)
|
||||
if "sampler" in sampler_inputs:
|
||||
|
||||
@@ -196,9 +196,11 @@ class MetadataRegistry:
|
||||
node_metadata[category] = {}
|
||||
node_metadata[category][node_id] = current_metadata[category][node_id]
|
||||
|
||||
# Save to cache if we have any metadata for this node
|
||||
# Save new metadata or clear stale cache entries when metadata is empty
|
||||
if any(node_metadata.values()):
|
||||
self.node_cache[cache_key] = node_metadata
|
||||
else:
|
||||
self.node_cache.pop(cache_key, None)
|
||||
|
||||
def clear_unused_cache(self):
|
||||
"""Clean up node_cache entries that are no longer in use"""
|
||||
|
||||
@@ -3,6 +3,18 @@ import os
|
||||
from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES, IS_SAMPLER
|
||||
|
||||
|
||||
def _store_checkpoint_metadata(metadata, node_id, model_name):
|
||||
"""Store checkpoint model information when available."""
|
||||
if not model_name:
|
||||
return
|
||||
metadata.setdefault(MODELS, {})
|
||||
metadata[MODELS][node_id] = {
|
||||
"name": model_name,
|
||||
"type": "checkpoint",
|
||||
"node_id": node_id
|
||||
}
|
||||
|
||||
|
||||
class NodeMetadataExtractor:
|
||||
"""Base class for node-specific metadata extraction"""
|
||||
|
||||
@@ -29,12 +41,48 @@ class CheckpointLoaderExtractor(NodeMetadataExtractor):
|
||||
return
|
||||
|
||||
model_name = inputs.get("ckpt_name")
|
||||
if model_name:
|
||||
metadata[MODELS][node_id] = {
|
||||
"name": model_name,
|
||||
"type": "checkpoint",
|
||||
"node_id": node_id
|
||||
}
|
||||
_store_checkpoint_metadata(metadata, node_id, model_name)
|
||||
|
||||
|
||||
class NunchakuFluxDiTLoaderExtractor(NodeMetadataExtractor):
|
||||
@staticmethod
|
||||
def extract(node_id, inputs, outputs, metadata):
|
||||
if not inputs or "model_path" not in inputs:
|
||||
return
|
||||
|
||||
model_name = inputs.get("model_path")
|
||||
_store_checkpoint_metadata(metadata, node_id, model_name)
|
||||
|
||||
|
||||
class NunchakuQwenImageDiTLoaderExtractor(NodeMetadataExtractor):
|
||||
@staticmethod
|
||||
def extract(node_id, inputs, outputs, metadata):
|
||||
if not inputs or "model_name" not in inputs:
|
||||
return
|
||||
|
||||
model_name = inputs.get("model_name")
|
||||
_store_checkpoint_metadata(metadata, node_id, model_name)
|
||||
|
||||
class GGUFLoaderExtractor(NodeMetadataExtractor):
|
||||
@staticmethod
|
||||
def extract(node_id, inputs, outputs, metadata):
|
||||
if not inputs or "gguf_name" not in inputs:
|
||||
return
|
||||
|
||||
model_name = inputs.get("gguf_name")
|
||||
_store_checkpoint_metadata(metadata, node_id, model_name)
|
||||
|
||||
|
||||
class KJNodesModelLoaderExtractor(NodeMetadataExtractor):
|
||||
"""Extract metadata from KJNodes loaders that expose `model_name`."""
|
||||
|
||||
@staticmethod
|
||||
def extract(node_id, inputs, outputs, metadata):
|
||||
if not inputs or "model_name" not in inputs:
|
||||
return
|
||||
|
||||
model_name = inputs.get("model_name")
|
||||
_store_checkpoint_metadata(metadata, node_id, model_name)
|
||||
|
||||
class TSCCheckpointLoaderExtractor(NodeMetadataExtractor):
|
||||
@staticmethod
|
||||
@@ -43,12 +91,7 @@ class TSCCheckpointLoaderExtractor(NodeMetadataExtractor):
|
||||
return
|
||||
|
||||
model_name = inputs.get("ckpt_name")
|
||||
if model_name:
|
||||
metadata[MODELS][node_id] = {
|
||||
"name": model_name,
|
||||
"type": "checkpoint",
|
||||
"node_id": node_id
|
||||
}
|
||||
_store_checkpoint_metadata(metadata, node_id, model_name)
|
||||
|
||||
# For loader node has lora_stack input, like Efficient Loader from Efficient Nodes
|
||||
active_loras = []
|
||||
@@ -651,6 +694,7 @@ NODE_EXTRACTORS = {
|
||||
"KSamplerAdvancedBasicPipe": KSamplerAdvancedBasicPipeExtractor, # comfyui-impact-pack
|
||||
"KSampler_inspire_pipe": KSamplerBasicPipeExtractor, # comfyui-inspire-pack
|
||||
"KSamplerAdvanced_inspire_pipe": KSamplerAdvancedBasicPipeExtractor, # comfyui-inspire-pack
|
||||
"KSampler_inspire": SamplerExtractor, # comfyui-inspire-pack
|
||||
# Sampling Selectors
|
||||
"KSamplerSelect": KSamplerSelectExtractor, # Add KSamplerSelect
|
||||
"BasicScheduler": BasicSchedulerExtractor, # Add BasicScheduler
|
||||
@@ -660,12 +704,20 @@ NODE_EXTRACTORS = {
|
||||
"comfyLoader": CheckpointLoaderExtractor, # easy comfyLoader
|
||||
"CheckpointLoaderSimpleWithImages": CheckpointLoaderExtractor, # CheckpointLoader|pysssss
|
||||
"TSC_EfficientLoader": TSCCheckpointLoaderExtractor, # Efficient Nodes
|
||||
"NunchakuFluxDiTLoader": NunchakuFluxDiTLoaderExtractor, # ComfyUI-Nunchaku
|
||||
"NunchakuQwenImageDiTLoader": NunchakuQwenImageDiTLoaderExtractor, # ComfyUI-Nunchaku
|
||||
"LoaderGGUF": GGUFLoaderExtractor, # calcuis gguf
|
||||
"LoaderGGUFAdvanced": GGUFLoaderExtractor, # calcuis gguf
|
||||
"GGUFLoaderKJ": KJNodesModelLoaderExtractor, # KJNodes
|
||||
"DiffusionModelLoaderKJ": KJNodesModelLoaderExtractor, # KJNodes
|
||||
"CheckpointLoaderKJ": CheckpointLoaderExtractor, # KJNodes
|
||||
"UNETLoader": UNETLoaderExtractor, # Updated to use dedicated extractor
|
||||
"UnetLoaderGGUF": UNETLoaderExtractor, # Updated to use dedicated extractor
|
||||
"LoraLoader": LoraLoaderExtractor,
|
||||
"LoraManagerLoader": LoraLoaderManagerExtractor,
|
||||
"LoraLoaderLM": LoraLoaderManagerExtractor,
|
||||
# Conditioning
|
||||
"CLIPTextEncode": CLIPTextEncodeExtractor,
|
||||
"PromptLM": CLIPTextEncodeExtractor,
|
||||
"CLIPTextEncodeFlux": CLIPTextEncodeFluxExtractor, # Add CLIPTextEncodeFlux
|
||||
"WAS_Text_to_Conditioning": CLIPTextEncodeExtractor,
|
||||
"AdvancedCLIPTextEncode": CLIPTextEncodeExtractor, # From https://github.com/BlenderNeko/ComfyUI_ADV_CLIP_emb
|
||||
|
||||
65
py/middleware/csp_middleware.py
Normal file
65
py/middleware/csp_middleware.py
Normal file
@@ -0,0 +1,65 @@
|
||||
"""Middleware helpers for adjusting Content Security Policy headers."""
|
||||
|
||||
from typing import Awaitable, Callable, Dict, List
|
||||
|
||||
from aiohttp import web
|
||||
|
||||
REMOTE_MEDIA_SOURCES = (
|
||||
"https://image.civitai.com",
|
||||
"https://img.genur.art",
|
||||
)
|
||||
|
||||
|
||||
@web.middleware
|
||||
async def relax_csp_for_remote_media(
|
||||
request: web.Request, handler: Callable[[web.Request], Awaitable[web.StreamResponse]]
|
||||
) -> web.StreamResponse:
|
||||
"""Allow LoRA Manager media previews to load from trusted remote domains.
|
||||
|
||||
When ComfyUI is started with ``--disable-api-nodes`` it injects a restrictive
|
||||
``Content-Security-Policy`` header that blocks remote images and videos. The
|
||||
LoRA Manager UI legitimately needs to fetch previews from Civitai and Genur,
|
||||
so this middleware augments the existing CSP to whitelist those hosts while
|
||||
preserving all other directives.
|
||||
"""
|
||||
|
||||
response: web.StreamResponse = await handler(request)
|
||||
header_value = response.headers.get("Content-Security-Policy")
|
||||
|
||||
if not header_value:
|
||||
return response
|
||||
|
||||
directive_order: List[str] = []
|
||||
directives: Dict[str, List[str]] = {}
|
||||
|
||||
for raw_directive in header_value.split(";"):
|
||||
directive = raw_directive.strip()
|
||||
if not directive:
|
||||
continue
|
||||
|
||||
parts = directive.split()
|
||||
name, values = parts[0], parts[1:]
|
||||
if name not in directive_order:
|
||||
directive_order.append(name)
|
||||
directives[name] = values
|
||||
|
||||
def merge_sources(name: str, sources: List[str], defaults: List[str] | None = None) -> None:
|
||||
existing = directives.get(name, list(defaults or []))
|
||||
|
||||
for source in sources:
|
||||
if source not in existing:
|
||||
existing.append(source)
|
||||
|
||||
directives[name] = existing
|
||||
if name not in directive_order:
|
||||
directive_order.append(name)
|
||||
|
||||
merge_sources("img-src", list(REMOTE_MEDIA_SOURCES))
|
||||
merge_sources("media-src", ["'self'", *REMOTE_MEDIA_SOURCES], defaults=["'self'"])
|
||||
|
||||
updated_header = "; ".join(
|
||||
f"{name} {' '.join(directives[name])}".rstrip() for name in directive_order
|
||||
)
|
||||
|
||||
response.headers["Content-Security-Policy"] = f"{updated_header};"
|
||||
return response
|
||||
@@ -1,15 +1,15 @@
|
||||
import logging
|
||||
from server import PromptServer # type: ignore
|
||||
from ..metadata_collector.metadata_processor import MetadataProcessor
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class DebugMetadata:
|
||||
|
||||
class DebugMetadataLM:
|
||||
NAME = "Debug Metadata (LoraManager)"
|
||||
CATEGORY = "Lora Manager/utils"
|
||||
DESCRIPTION = "Debug node to verify metadata_processor functionality"
|
||||
OUTPUT_NODE = True
|
||||
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
@@ -25,21 +25,37 @@ class DebugMetadata:
|
||||
FUNCTION = "process_metadata"
|
||||
|
||||
def process_metadata(self, images, id):
|
||||
"""
|
||||
Process metadata from the execution context and return it for UI display.
|
||||
|
||||
The metadata is returned via the 'ui' key in the return dict, which triggers
|
||||
node.onExecuted on the frontend to update the JsonDisplayWidget.
|
||||
|
||||
Args:
|
||||
images: Input images (required for execution flow)
|
||||
id: Node's unique ID (hidden)
|
||||
|
||||
Returns:
|
||||
Dict with 'result' (empty tuple) and 'ui' (metadata dict for widget display)
|
||||
"""
|
||||
try:
|
||||
# Get the current execution context's metadata
|
||||
from ..metadata_collector import get_metadata
|
||||
|
||||
metadata = get_metadata()
|
||||
|
||||
# Use the MetadataProcessor to convert it to JSON string
|
||||
metadata_json = MetadataProcessor.to_json(metadata, id)
|
||||
|
||||
# Send metadata to frontend for display
|
||||
PromptServer.instance.send_sync("metadata_update", {
|
||||
"id": id,
|
||||
"metadata": metadata_json
|
||||
})
|
||||
|
||||
|
||||
# Use the MetadataProcessor to convert it to dict
|
||||
metadata_dict = MetadataProcessor.to_dict(metadata, id)
|
||||
|
||||
return {
|
||||
"result": (),
|
||||
# ComfyUI expects ui values to be lists, wrap the dict in a list
|
||||
"ui": {"metadata": [metadata_dict]},
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error processing metadata: {e}")
|
||||
|
||||
return ()
|
||||
return {
|
||||
"result": (),
|
||||
"ui": {"metadata": [{"error": str(e)}]},
|
||||
}
|
||||
|
||||
134
py/nodes/lora_cycler.py
Normal file
134
py/nodes/lora_cycler.py
Normal file
@@ -0,0 +1,134 @@
|
||||
"""
|
||||
Lora Cycler Node - Sequentially cycles through LoRAs from a pool.
|
||||
|
||||
This node accepts optional pool_config input to filter available LoRAs, and outputs
|
||||
a LORA_STACK with one LoRA at a time. Returns UI updates with current/next LoRA info
|
||||
and tracks the cycle progress which persists across workflow save/load.
|
||||
"""
|
||||
|
||||
import logging
|
||||
import os
|
||||
from ..utils.utils import get_lora_info
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class LoraCyclerLM:
|
||||
"""Node that sequentially cycles through LoRAs from a pool"""
|
||||
|
||||
NAME = "Lora Cycler (LoraManager)"
|
||||
CATEGORY = "Lora Manager/randomizer"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"cycler_config": ("CYCLER_CONFIG", {}),
|
||||
},
|
||||
"optional": {
|
||||
"pool_config": ("POOL_CONFIG", {}),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("LORA_STACK",)
|
||||
RETURN_NAMES = ("LORA_STACK",)
|
||||
|
||||
FUNCTION = "cycle"
|
||||
OUTPUT_NODE = False
|
||||
|
||||
async def cycle(self, cycler_config, pool_config=None):
|
||||
"""
|
||||
Cycle through LoRAs based on configuration and pool filters.
|
||||
|
||||
Args:
|
||||
cycler_config: Dict with cycler settings (current_index, model_strength, clip_strength, sort_by)
|
||||
pool_config: Optional config from LoRA Pool node for filtering
|
||||
|
||||
Returns:
|
||||
Dictionary with 'result' (LORA_STACK tuple) and 'ui' (for widget display)
|
||||
"""
|
||||
from ..services.service_registry import ServiceRegistry
|
||||
from ..services.lora_service import LoraService
|
||||
|
||||
# Extract settings from cycler_config
|
||||
current_index = cycler_config.get("current_index", 1) # 1-based
|
||||
model_strength = float(cycler_config.get("model_strength", 1.0))
|
||||
clip_strength = float(cycler_config.get("clip_strength", 1.0))
|
||||
sort_by = "filename"
|
||||
|
||||
# Dual-index mechanism for batch queue synchronization
|
||||
execution_index = cycler_config.get("execution_index") # Can be None
|
||||
# next_index_from_config = cycler_config.get("next_index") # Not used on backend
|
||||
|
||||
# Get scanner and service
|
||||
scanner = await ServiceRegistry.get_lora_scanner()
|
||||
lora_service = LoraService(scanner)
|
||||
|
||||
# Get filtered and sorted LoRA list
|
||||
lora_list = await lora_service.get_cycler_list(
|
||||
pool_config=pool_config, sort_by=sort_by
|
||||
)
|
||||
|
||||
total_count = len(lora_list)
|
||||
|
||||
if total_count == 0:
|
||||
logger.warning("[LoraCyclerLM] No LoRAs available in pool")
|
||||
return {
|
||||
"result": ([],),
|
||||
"ui": {
|
||||
"current_index": [1],
|
||||
"next_index": [1],
|
||||
"total_count": [0],
|
||||
"current_lora_name": [""],
|
||||
"current_lora_filename": [""],
|
||||
"error": ["No LoRAs available in pool"],
|
||||
},
|
||||
}
|
||||
|
||||
# Determine which index to use for this execution
|
||||
# If execution_index is provided (batch queue case), use it
|
||||
# Otherwise use current_index (first execution or non-batch case)
|
||||
if execution_index is not None:
|
||||
actual_index = execution_index
|
||||
else:
|
||||
actual_index = current_index
|
||||
|
||||
# Clamp index to valid range (1-based)
|
||||
clamped_index = max(1, min(actual_index, total_count))
|
||||
|
||||
# Get LoRA at current index (convert to 0-based for list access)
|
||||
current_lora = lora_list[clamped_index - 1]
|
||||
|
||||
# Build LORA_STACK with single LoRA
|
||||
lora_path, _ = get_lora_info(current_lora["file_name"])
|
||||
if not lora_path:
|
||||
logger.warning(
|
||||
f"[LoraCyclerLM] Could not find path for LoRA: {current_lora['file_name']}"
|
||||
)
|
||||
lora_stack = []
|
||||
else:
|
||||
# Normalize path separators
|
||||
lora_path = lora_path.replace("/", os.sep)
|
||||
lora_stack = [(lora_path, model_strength, clip_strength)]
|
||||
|
||||
# Calculate next index (wrap to 1 if at end)
|
||||
next_index = clamped_index + 1
|
||||
if next_index > total_count:
|
||||
next_index = 1
|
||||
|
||||
# Get next LoRA for UI display (what will be used next generation)
|
||||
next_lora = lora_list[next_index - 1]
|
||||
next_display_name = next_lora["file_name"]
|
||||
|
||||
return {
|
||||
"result": (lora_stack,),
|
||||
"ui": {
|
||||
"current_index": [clamped_index],
|
||||
"next_index": [next_index],
|
||||
"total_count": [total_count],
|
||||
"current_lora_name": [current_lora["file_name"]],
|
||||
"current_lora_filename": [current_lora["file_name"]],
|
||||
"next_lora_name": [next_display_name],
|
||||
"next_lora_filename": [next_lora["file_name"]],
|
||||
},
|
||||
}
|
||||
@@ -1,13 +1,12 @@
|
||||
import logging
|
||||
import re
|
||||
from nodes import LoraLoader
|
||||
from comfy.comfy_types import IO # type: ignore
|
||||
from ..utils.utils import get_lora_info
|
||||
from .utils import FlexibleOptionalInputType, any_type, extract_lora_name, get_loras_list, nunchaku_load_lora
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class LoraManagerLoader:
|
||||
class LoraLoaderLM:
|
||||
NAME = "Lora Loader (LoraManager)"
|
||||
CATEGORY = "Lora Manager/loaders"
|
||||
|
||||
@@ -17,18 +16,15 @@ class LoraManagerLoader:
|
||||
"required": {
|
||||
"model": ("MODEL",),
|
||||
# "clip": ("CLIP",),
|
||||
"text": (IO.STRING, {
|
||||
"multiline": True,
|
||||
"pysssss.autocomplete": False,
|
||||
"dynamicPrompts": True,
|
||||
"text": ("AUTOCOMPLETE_TEXT_LORAS", {
|
||||
"placeholder": "Search LoRAs to add...",
|
||||
"tooltip": "Format: <lora:lora_name:strength> separated by spaces or punctuation",
|
||||
"placeholder": "LoRA syntax input: <lora:name:strength>"
|
||||
}),
|
||||
},
|
||||
"optional": FlexibleOptionalInputType(any_type),
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("MODEL", "CLIP", IO.STRING, IO.STRING)
|
||||
RETURN_TYPES = ("MODEL", "CLIP", "STRING", "STRING")
|
||||
RETURN_NAMES = ("MODEL", "CLIP", "trigger_words", "loaded_loras")
|
||||
FUNCTION = "load_loras"
|
||||
|
||||
@@ -132,7 +128,7 @@ class LoraManagerLoader:
|
||||
|
||||
return (model, clip, trigger_words_text, formatted_loras_text)
|
||||
|
||||
class LoraManagerTextLoader:
|
||||
class LoraTextLoaderLM:
|
||||
NAME = "LoRA Text Loader (LoraManager)"
|
||||
CATEGORY = "Lora Manager/loaders"
|
||||
|
||||
@@ -141,8 +137,7 @@ class LoraManagerTextLoader:
|
||||
return {
|
||||
"required": {
|
||||
"model": ("MODEL",),
|
||||
"lora_syntax": (IO.STRING, {
|
||||
"defaultInput": True,
|
||||
"lora_syntax": ("STRING", {
|
||||
"forceInput": True,
|
||||
"tooltip": "Format: <lora:lora_name:strength> separated by spaces or punctuation"
|
||||
}),
|
||||
@@ -153,7 +148,7 @@ class LoraManagerTextLoader:
|
||||
}
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("MODEL", "CLIP", IO.STRING, IO.STRING)
|
||||
RETURN_TYPES = ("MODEL", "CLIP", "STRING", "STRING")
|
||||
RETURN_NAMES = ("MODEL", "CLIP", "trigger_words", "loaded_loras")
|
||||
FUNCTION = "load_loras_from_text"
|
||||
|
||||
|
||||
87
py/nodes/lora_pool.py
Normal file
87
py/nodes/lora_pool.py
Normal file
@@ -0,0 +1,87 @@
|
||||
"""
|
||||
LoRA Pool Node - Defines filter configuration for LoRA selection.
|
||||
|
||||
This node provides a visual filter editor that generates a LORA_POOL_CONFIG
|
||||
object for use by downstream nodes (like LoRA Randomizer).
|
||||
"""
|
||||
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class LoraPoolLM:
|
||||
"""
|
||||
A node that defines LoRA filter criteria through a Vue-based widget.
|
||||
|
||||
Outputs a LORA_POOL_CONFIG that can be consumed by:
|
||||
- Frontend: LoRA Randomizer widget reads connected pool's widget value
|
||||
- Backend: LoRA Randomizer receives config during workflow execution
|
||||
"""
|
||||
|
||||
NAME = "Lora Pool (LoraManager)"
|
||||
CATEGORY = "Lora Manager/randomizer"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"pool_config": ("LORA_POOL_CONFIG", {}),
|
||||
},
|
||||
"hidden": {
|
||||
# Hidden input to pass through unique node ID for frontend
|
||||
"unique_id": "UNIQUE_ID",
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("POOL_CONFIG",)
|
||||
RETURN_NAMES = ("POOL_CONFIG",)
|
||||
|
||||
FUNCTION = "process"
|
||||
OUTPUT_NODE = False
|
||||
|
||||
def process(self, pool_config, unique_id=None):
|
||||
"""
|
||||
Pass through the pool configuration filters.
|
||||
|
||||
The config is generated entirely by the frontend widget.
|
||||
This function validates and returns only the filters field.
|
||||
|
||||
Args:
|
||||
pool_config: Dict containing filter criteria from widget
|
||||
unique_id: Node's unique ID (hidden)
|
||||
|
||||
Returns:
|
||||
Tuple containing the filters dict from pool_config
|
||||
"""
|
||||
# Validate required structure
|
||||
if not isinstance(pool_config, dict):
|
||||
logger.warning("Invalid pool_config type, using empty config")
|
||||
pool_config = self._default_config()
|
||||
|
||||
# Ensure version field exists
|
||||
if "version" not in pool_config:
|
||||
pool_config["version"] = 1
|
||||
|
||||
# Extract filters field
|
||||
filters = pool_config.get("filters", self._default_config()["filters"])
|
||||
|
||||
# Log for debugging
|
||||
logger.debug(f"[LoraPoolLM] Processing filters: {filters}")
|
||||
|
||||
return (filters,)
|
||||
|
||||
@staticmethod
|
||||
def _default_config():
|
||||
"""Return default empty configuration."""
|
||||
return {
|
||||
"version": 1,
|
||||
"filters": {
|
||||
"baseModels": [],
|
||||
"tags": {"include": [], "exclude": []},
|
||||
"folders": {"include": [], "exclude": []},
|
||||
"favoritesOnly": False,
|
||||
"license": {"noCreditRequired": False, "allowSelling": False},
|
||||
},
|
||||
"preview": {"matchCount": 0, "lastUpdated": 0},
|
||||
}
|
||||
206
py/nodes/lora_randomizer.py
Normal file
206
py/nodes/lora_randomizer.py
Normal file
@@ -0,0 +1,206 @@
|
||||
"""
|
||||
Lora Randomizer Node - Randomly selects LoRAs from a pool with configurable settings.
|
||||
|
||||
This node accepts optional pool_config input to filter available LoRAs, and outputs
|
||||
a LORA_STACK with randomly selected LoRAs. Returns UI updates with new random LoRAs
|
||||
and tracks the last used combination for reuse.
|
||||
"""
|
||||
|
||||
import logging
|
||||
import random
|
||||
import os
|
||||
from ..utils.utils import get_lora_info
|
||||
from .utils import extract_lora_name
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class LoraRandomizerLM:
|
||||
"""Node that randomly selects LoRAs from a pool"""
|
||||
|
||||
NAME = "Lora Randomizer (LoraManager)"
|
||||
CATEGORY = "Lora Manager/randomizer"
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"randomizer_config": ("RANDOMIZER_CONFIG", {}),
|
||||
"loras": ("LORAS", {}),
|
||||
},
|
||||
"optional": {
|
||||
"pool_config": ("POOL_CONFIG", {}),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("LORA_STACK",)
|
||||
RETURN_NAMES = ("LORA_STACK",)
|
||||
|
||||
FUNCTION = "randomize"
|
||||
OUTPUT_NODE = False
|
||||
|
||||
def _preprocess_loras_input(self, loras):
|
||||
"""
|
||||
Preprocess loras input to handle different widget formats.
|
||||
|
||||
Args:
|
||||
loras: Input from widget, either:
|
||||
- List of LoRA dicts (expected format)
|
||||
- Dict with '__value__' key containing the list
|
||||
|
||||
Returns:
|
||||
List of LoRA dicts
|
||||
"""
|
||||
if isinstance(loras, dict) and "__value__" in loras:
|
||||
return loras["__value__"]
|
||||
return loras
|
||||
|
||||
async def randomize(self, randomizer_config, loras, pool_config=None):
|
||||
"""
|
||||
Randomize LoRAs based on configuration and pool filters.
|
||||
|
||||
Args:
|
||||
randomizer_config: Dict with randomizer settings (count, strength ranges, roll_mode)
|
||||
loras: List of LoRA dicts from LORAS widget (includes locked state)
|
||||
pool_config: Optional config from LoRA Pool node for filtering
|
||||
|
||||
Returns:
|
||||
Dictionary with 'result' (LORA_STACK tuple) and 'ui' (for widget display)
|
||||
"""
|
||||
from ..services.service_registry import ServiceRegistry
|
||||
|
||||
loras = self._preprocess_loras_input(loras)
|
||||
|
||||
roll_mode = randomizer_config.get("roll_mode", "always")
|
||||
logger.debug(f"[LoraRandomizerLM] roll_mode: {roll_mode}")
|
||||
|
||||
# Dual seed mechanism for batch queue synchronization
|
||||
# execution_seed: seed for generating execution_stack (= previous next_seed)
|
||||
# next_seed: seed for generating ui_loras (= what will be displayed after execution)
|
||||
execution_seed = randomizer_config.get("execution_seed", None)
|
||||
next_seed = randomizer_config.get("next_seed", None)
|
||||
|
||||
if roll_mode == "fixed":
|
||||
ui_loras = loras
|
||||
execution_loras = loras
|
||||
else:
|
||||
scanner = await ServiceRegistry.get_lora_scanner()
|
||||
|
||||
# Generate execution_loras from execution_seed (if available)
|
||||
if execution_seed is not None:
|
||||
# Use execution_seed to regenerate the same loras that were shown to user
|
||||
execution_loras = await self._generate_random_loras_for_ui(
|
||||
scanner, randomizer_config, loras, pool_config, seed=execution_seed
|
||||
)
|
||||
else:
|
||||
# First execution: use loras input (what user sees in the widget)
|
||||
execution_loras = loras
|
||||
|
||||
# Generate ui_loras from next_seed (for display after execution)
|
||||
ui_loras = await self._generate_random_loras_for_ui(
|
||||
scanner, randomizer_config, loras, pool_config, seed=next_seed
|
||||
)
|
||||
|
||||
execution_stack = self._build_execution_stack_from_input(execution_loras)
|
||||
|
||||
return {
|
||||
"result": (execution_stack,),
|
||||
"ui": {"loras": ui_loras, "last_used": execution_loras},
|
||||
}
|
||||
|
||||
def _build_execution_stack_from_input(self, loras):
|
||||
"""
|
||||
Build LORA_STACK tuple from input loras list for execution.
|
||||
|
||||
Args:
|
||||
loras: List of LoRA dicts with name, strength, clipStrength, active
|
||||
|
||||
Returns:
|
||||
List of tuples (lora_path, model_strength, clip_strength)
|
||||
"""
|
||||
lora_stack = []
|
||||
for lora in loras:
|
||||
if not lora.get("active", False):
|
||||
continue
|
||||
|
||||
# Get file path
|
||||
lora_path, trigger_words = get_lora_info(lora["name"])
|
||||
if not lora_path:
|
||||
logger.warning(
|
||||
f"[LoraRandomizerLM] Could not find path for LoRA: {lora['name']}"
|
||||
)
|
||||
continue
|
||||
|
||||
# Normalize path separators
|
||||
lora_path = lora_path.replace("/", os.sep)
|
||||
|
||||
# Extract strengths (convert to float to prevent string subtraction errors)
|
||||
model_strength = float(lora.get("strength", 1.0))
|
||||
clip_strength = float(lora.get("clipStrength", model_strength))
|
||||
|
||||
lora_stack.append((lora_path, model_strength, clip_strength))
|
||||
|
||||
return lora_stack
|
||||
|
||||
async def _generate_random_loras_for_ui(
|
||||
self, scanner, randomizer_config, input_loras, pool_config=None, seed=None
|
||||
):
|
||||
"""
|
||||
Generate new random loras for UI display.
|
||||
|
||||
Args:
|
||||
scanner: LoraScanner instance
|
||||
randomizer_config: Dict with randomizer settings
|
||||
input_loras: Current input loras (for extracting locked loras)
|
||||
pool_config: Optional pool filters
|
||||
seed: Optional seed for deterministic randomization
|
||||
|
||||
Returns:
|
||||
List of LoRA dicts for UI display
|
||||
"""
|
||||
from ..services.lora_service import LoraService
|
||||
|
||||
# Parse randomizer settings (convert numeric values to float to prevent type errors)
|
||||
count_mode = randomizer_config.get("count_mode", "range")
|
||||
count_fixed = int(randomizer_config.get("count_fixed", 5))
|
||||
count_min = int(randomizer_config.get("count_min", 3))
|
||||
count_max = int(randomizer_config.get("count_max", 7))
|
||||
model_strength_min = float(randomizer_config.get("model_strength_min", 0.0))
|
||||
model_strength_max = float(randomizer_config.get("model_strength_max", 1.0))
|
||||
use_same_clip_strength = randomizer_config.get("use_same_clip_strength", True)
|
||||
clip_strength_min = float(randomizer_config.get("clip_strength_min", 0.0))
|
||||
clip_strength_max = float(randomizer_config.get("clip_strength_max", 1.0))
|
||||
use_recommended_strength = randomizer_config.get(
|
||||
"use_recommended_strength", False
|
||||
)
|
||||
recommended_strength_scale_min = float(
|
||||
randomizer_config.get("recommended_strength_scale_min", 0.5)
|
||||
)
|
||||
recommended_strength_scale_max = float(
|
||||
randomizer_config.get("recommended_strength_scale_max", 1.0)
|
||||
)
|
||||
|
||||
# Extract locked LoRAs from input
|
||||
locked_loras = [lora for lora in input_loras if lora.get("locked", False)]
|
||||
|
||||
# Use LoraService to generate random LoRAs
|
||||
lora_service = LoraService(scanner)
|
||||
result_loras = await lora_service.get_random_loras(
|
||||
count=count_fixed,
|
||||
model_strength_min=model_strength_min,
|
||||
model_strength_max=model_strength_max,
|
||||
use_same_clip_strength=use_same_clip_strength,
|
||||
clip_strength_min=clip_strength_min,
|
||||
clip_strength_max=clip_strength_max,
|
||||
locked_loras=locked_loras,
|
||||
pool_config=pool_config,
|
||||
count_mode=count_mode,
|
||||
count_min=count_min,
|
||||
count_max=count_max,
|
||||
use_recommended_strength=use_recommended_strength,
|
||||
recommended_strength_scale_min=recommended_strength_scale_min,
|
||||
recommended_strength_scale_max=recommended_strength_scale_max,
|
||||
seed=seed,
|
||||
)
|
||||
|
||||
return result_loras
|
||||
@@ -1,4 +1,3 @@
|
||||
from comfy.comfy_types import IO # type: ignore
|
||||
import os
|
||||
from ..utils.utils import get_lora_info
|
||||
from .utils import FlexibleOptionalInputType, any_type, extract_lora_name, get_loras_list
|
||||
@@ -7,7 +6,7 @@ import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class LoraStacker:
|
||||
class LoraStackerLM:
|
||||
NAME = "Lora Stacker (LoraManager)"
|
||||
CATEGORY = "Lora Manager/stackers"
|
||||
|
||||
@@ -15,18 +14,15 @@ class LoraStacker:
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"text": (IO.STRING, {
|
||||
"multiline": True,
|
||||
"pysssss.autocomplete": False,
|
||||
"dynamicPrompts": True,
|
||||
"text": ("AUTOCOMPLETE_TEXT_LORAS", {
|
||||
"placeholder": "Search LoRAs to add...",
|
||||
"tooltip": "Format: <lora:lora_name:strength> separated by spaces or punctuation",
|
||||
"placeholder": "LoRA syntax input: <lora:name:strength>"
|
||||
}),
|
||||
},
|
||||
"optional": FlexibleOptionalInputType(any_type),
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("LORA_STACK", IO.STRING, IO.STRING)
|
||||
RETURN_TYPES = ("LORA_STACK", "STRING", "STRING")
|
||||
RETURN_NAMES = ("LORA_STACK", "trigger_words", "active_loras")
|
||||
FUNCTION = "stack_loras"
|
||||
|
||||
|
||||
58
py/nodes/prompt.py
Normal file
58
py/nodes/prompt.py
Normal file
@@ -0,0 +1,58 @@
|
||||
from typing import Any, Optional
|
||||
|
||||
class PromptLM:
|
||||
"""Encodes text (and optional trigger words) into CLIP conditioning."""
|
||||
|
||||
NAME = "Prompt (LoraManager)"
|
||||
CATEGORY = "Lora Manager/conditioning"
|
||||
DESCRIPTION = (
|
||||
"Encodes a text prompt using a CLIP model into an embedding that can be used "
|
||||
"to guide the diffusion model towards generating specific images."
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"text": (
|
||||
"AUTOCOMPLETE_TEXT_PROMPT,STRING",
|
||||
{
|
||||
"widgetType": "AUTOCOMPLETE_TEXT_PROMPT",
|
||||
"placeholder": "Enter prompt... /char, /artist for quick tag search",
|
||||
"tooltip": "The text to be encoded.",
|
||||
},
|
||||
),
|
||||
"clip": (
|
||||
'CLIP',
|
||||
{"tooltip": "The CLIP model used for encoding the text."},
|
||||
),
|
||||
},
|
||||
"optional": {
|
||||
"trigger_words": (
|
||||
'STRING',
|
||||
{
|
||||
"forceInput": True,
|
||||
"tooltip": (
|
||||
"Optional trigger words to prepend to the text before "
|
||||
"encoding."
|
||||
)
|
||||
},
|
||||
)
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ('CONDITIONING', 'STRING',)
|
||||
RETURN_NAMES = ('CONDITIONING', 'PROMPT',)
|
||||
OUTPUT_TOOLTIPS = (
|
||||
"A conditioning containing the embedded text used to guide the diffusion model.",
|
||||
)
|
||||
FUNCTION = "encode"
|
||||
|
||||
def encode(self, text: str, clip: Any, trigger_words: Optional[str] = None):
|
||||
prompt = text
|
||||
if trigger_words:
|
||||
prompt = ", ".join([trigger_words, text])
|
||||
|
||||
from nodes import CLIPTextEncode # type: ignore
|
||||
conditioning = CLIPTextEncode().encode(clip, prompt)[0]
|
||||
return (conditioning, prompt,)
|
||||
@@ -8,8 +8,11 @@ from ..metadata_collector.metadata_processor import MetadataProcessor
|
||||
from ..metadata_collector import get_metadata
|
||||
from PIL import Image, PngImagePlugin
|
||||
import piexif
|
||||
import logging
|
||||
|
||||
class SaveImage:
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class SaveImageLM:
|
||||
NAME = "Save Image (LoraManager)"
|
||||
CATEGORY = "Lora Manager/utils"
|
||||
DESCRIPTION = "Save images with embedded generation metadata in compatible format"
|
||||
@@ -273,9 +276,15 @@ class SaveImage:
|
||||
length = int(parts[1])
|
||||
prompt = prompt[:length]
|
||||
filename = filename.replace(segment, prompt.strip())
|
||||
elif key == "model" and 'checkpoint' in metadata_dict:
|
||||
model = metadata_dict.get('checkpoint', '')
|
||||
model = os.path.splitext(os.path.basename(model))[0]
|
||||
elif key == "model":
|
||||
model_value = metadata_dict.get('checkpoint')
|
||||
if isinstance(model_value, (bytes, os.PathLike)):
|
||||
model_value = str(model_value)
|
||||
|
||||
if not isinstance(model_value, str) or not model_value:
|
||||
model = "model_unavailable"
|
||||
else:
|
||||
model = os.path.splitext(os.path.basename(model_value))[0]
|
||||
if len(parts) >= 2:
|
||||
length = int(parts[1])
|
||||
model = model[:length]
|
||||
@@ -379,7 +388,7 @@ class SaveImage:
|
||||
exif_bytes = piexif.dump(exif_dict)
|
||||
save_kwargs["exif"] = exif_bytes
|
||||
except Exception as e:
|
||||
print(f"Error adding EXIF data: {e}")
|
||||
logger.error(f"Error adding EXIF data: {e}")
|
||||
img.save(file_path, format="JPEG", **save_kwargs)
|
||||
elif file_format == "webp":
|
||||
try:
|
||||
@@ -397,7 +406,7 @@ class SaveImage:
|
||||
exif_bytes = piexif.dump(exif_dict)
|
||||
save_kwargs["exif"] = exif_bytes
|
||||
except Exception as e:
|
||||
print(f"Error adding EXIF data: {e}")
|
||||
logger.error(f"Error adding EXIF data: {e}")
|
||||
|
||||
img.save(file_path, format="WEBP", **save_kwargs)
|
||||
|
||||
@@ -408,7 +417,7 @@ class SaveImage:
|
||||
})
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error saving image: {e}")
|
||||
logger.error(f"Error saving image: {e}")
|
||||
|
||||
return results
|
||||
|
||||
@@ -442,4 +451,4 @@ class SaveImage:
|
||||
add_counter_to_filename
|
||||
)
|
||||
|
||||
return (images,)
|
||||
return (images,)
|
||||
|
||||
33
py/nodes/text.py
Normal file
33
py/nodes/text.py
Normal file
@@ -0,0 +1,33 @@
|
||||
class TextLM:
|
||||
"""A simple text node with autocomplete support."""
|
||||
|
||||
NAME = "Text (LoraManager)"
|
||||
CATEGORY = "Lora Manager/utils"
|
||||
DESCRIPTION = (
|
||||
"A simple text input node with autocomplete support for tags and styles."
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"text": (
|
||||
"AUTOCOMPLETE_TEXT_PROMPT,STRING",
|
||||
{
|
||||
"widgetType": "AUTOCOMPLETE_TEXT_PROMPT",
|
||||
"placeholder": "Enter text... /char, /artist for quick tag search",
|
||||
"tooltip": "The text output.",
|
||||
},
|
||||
),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("STRING",)
|
||||
RETURN_NAMES = ("STRING",)
|
||||
OUTPUT_TOOLTIPS = (
|
||||
"The text output.",
|
||||
)
|
||||
FUNCTION = "process"
|
||||
|
||||
def process(self, text: str):
|
||||
return (text,)
|
||||
@@ -1,29 +1,41 @@
|
||||
import json
|
||||
import re
|
||||
from server import PromptServer # type: ignore
|
||||
from .utils import FlexibleOptionalInputType, any_type
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class TriggerWordToggle:
|
||||
class TriggerWordToggleLM:
|
||||
NAME = "TriggerWord Toggle (LoraManager)"
|
||||
CATEGORY = "Lora Manager/utils"
|
||||
DESCRIPTION = "Toggle trigger words on/off"
|
||||
|
||||
|
||||
@classmethod
|
||||
def INPUT_TYPES(cls):
|
||||
return {
|
||||
"required": {
|
||||
"group_mode": ("BOOLEAN", {
|
||||
"default": True,
|
||||
"tooltip": "When enabled, treats each group of trigger words as a single toggleable unit."
|
||||
}),
|
||||
"default_active": ("BOOLEAN", {
|
||||
"default": True,
|
||||
"tooltip": "Sets the default initial state (active or inactive) when trigger words are added."
|
||||
}),
|
||||
"group_mode": (
|
||||
"BOOLEAN",
|
||||
{
|
||||
"default": True,
|
||||
"tooltip": "When enabled, treats each group of trigger words as a single toggleable unit.",
|
||||
},
|
||||
),
|
||||
"default_active": (
|
||||
"BOOLEAN",
|
||||
{
|
||||
"default": True,
|
||||
"tooltip": "Sets the default initial state (active or inactive) when trigger words are added.",
|
||||
},
|
||||
),
|
||||
"allow_strength_adjustment": (
|
||||
"BOOLEAN",
|
||||
{
|
||||
"default": False,
|
||||
"tooltip": "Enable mouse wheel adjustment of each trigger word's strength.",
|
||||
},
|
||||
),
|
||||
},
|
||||
"optional": FlexibleOptionalInputType(any_type),
|
||||
"hidden": {
|
||||
@@ -35,63 +47,154 @@ class TriggerWordToggle:
|
||||
RETURN_NAMES = ("filtered_trigger_words",)
|
||||
FUNCTION = "process_trigger_words"
|
||||
|
||||
def _get_toggle_data(self, kwargs, key='toggle_trigger_words'):
|
||||
def _get_toggle_data(self, kwargs, key="toggle_trigger_words"):
|
||||
"""Helper to extract data from either old or new kwargs format"""
|
||||
if key not in kwargs:
|
||||
return None
|
||||
|
||||
|
||||
data = kwargs[key]
|
||||
# Handle new format: {'key': {'__value__': ...}}
|
||||
if isinstance(data, dict) and '__value__' in data:
|
||||
return data['__value__']
|
||||
if isinstance(data, dict) and "__value__" in data:
|
||||
return data["__value__"]
|
||||
# Handle old format: {'key': ...}
|
||||
else:
|
||||
return data
|
||||
|
||||
def process_trigger_words(self, id, group_mode, default_active, **kwargs):
|
||||
def _normalize_trigger_words(self, trigger_words):
|
||||
"""Normalize trigger words by splitting by both single and double commas, stripping whitespace, and filtering empty strings"""
|
||||
if not trigger_words or not isinstance(trigger_words, str):
|
||||
return set()
|
||||
|
||||
# Split by double commas first to preserve groups, then by single commas
|
||||
groups = re.split(r",{2,}", trigger_words)
|
||||
words = []
|
||||
for group in groups:
|
||||
# Split each group by single comma
|
||||
group_words = [word.strip() for word in group.split(",")]
|
||||
words.extend(group_words)
|
||||
|
||||
# Filter out empty strings and return as set
|
||||
return set(word for word in words if word)
|
||||
|
||||
def process_trigger_words(
|
||||
self,
|
||||
id,
|
||||
group_mode,
|
||||
default_active,
|
||||
allow_strength_adjustment=False,
|
||||
**kwargs,
|
||||
):
|
||||
# Handle both old and new formats for trigger_words
|
||||
trigger_words_data = self._get_toggle_data(kwargs, 'orinalMessage')
|
||||
trigger_words = trigger_words_data if isinstance(trigger_words_data, str) else ""
|
||||
|
||||
trigger_words_data = self._get_toggle_data(kwargs, "orinalMessage")
|
||||
trigger_words = (
|
||||
trigger_words_data if isinstance(trigger_words_data, str) else ""
|
||||
)
|
||||
|
||||
filtered_triggers = trigger_words
|
||||
|
||||
|
||||
# Check if trigger_words is provided and different from orinalMessage
|
||||
trigger_words_override = self._get_toggle_data(kwargs, "trigger_words")
|
||||
if (
|
||||
trigger_words_override
|
||||
and isinstance(trigger_words_override, str)
|
||||
and self._normalize_trigger_words(trigger_words_override) != self._normalize_trigger_words(trigger_words)
|
||||
):
|
||||
filtered_triggers = trigger_words_override
|
||||
return (filtered_triggers,)
|
||||
|
||||
# Get toggle data with support for both formats
|
||||
trigger_data = self._get_toggle_data(kwargs, 'toggle_trigger_words')
|
||||
trigger_data = self._get_toggle_data(kwargs, "toggle_trigger_words")
|
||||
if trigger_data:
|
||||
try:
|
||||
# Convert to list if it's a JSON string
|
||||
if isinstance(trigger_data, str):
|
||||
trigger_data = json.loads(trigger_data)
|
||||
|
||||
# Create dictionaries to track active state of words or groups
|
||||
active_state = {item['text']: item.get('active', False) for item in trigger_data}
|
||||
|
||||
if group_mode:
|
||||
# Split by two or more consecutive commas to get groups
|
||||
groups = re.split(r',{2,}', trigger_words)
|
||||
# Remove leading/trailing whitespace from each group
|
||||
groups = [group.strip() for group in groups]
|
||||
|
||||
# Filter groups: keep those not in toggle_trigger_words or those that are active
|
||||
filtered_groups = [group for group in groups if group not in active_state or active_state[group]]
|
||||
|
||||
if filtered_groups:
|
||||
filtered_triggers = ', '.join(filtered_groups)
|
||||
|
||||
if isinstance(trigger_data, list):
|
||||
if group_mode:
|
||||
if allow_strength_adjustment:
|
||||
parsed_items = [
|
||||
self._parse_trigger_item(
|
||||
item, allow_strength_adjustment
|
||||
)
|
||||
for item in trigger_data
|
||||
]
|
||||
filtered_groups = [
|
||||
self._format_word_output(
|
||||
item["text"],
|
||||
item["strength"],
|
||||
allow_strength_adjustment,
|
||||
)
|
||||
for item in parsed_items
|
||||
if item["text"] and item["active"]
|
||||
]
|
||||
else:
|
||||
filtered_groups = [
|
||||
(item.get("text") or "").strip()
|
||||
for item in trigger_data
|
||||
if (item.get("text") or "").strip()
|
||||
and item.get("active", False)
|
||||
]
|
||||
filtered_triggers = (
|
||||
", ".join(filtered_groups) if filtered_groups else ""
|
||||
)
|
||||
else:
|
||||
filtered_triggers = ""
|
||||
parsed_items = [
|
||||
self._parse_trigger_item(item, allow_strength_adjustment)
|
||||
for item in trigger_data
|
||||
]
|
||||
filtered_words = [
|
||||
self._format_word_output(
|
||||
item["text"],
|
||||
item["strength"],
|
||||
allow_strength_adjustment,
|
||||
)
|
||||
for item in parsed_items
|
||||
if item["text"] and item["active"]
|
||||
]
|
||||
filtered_triggers = (
|
||||
", ".join(filtered_words) if filtered_words else ""
|
||||
)
|
||||
else:
|
||||
# Original behavior for individual words mode
|
||||
original_words = [word.strip() for word in trigger_words.split(',')]
|
||||
# Filter out empty strings
|
||||
original_words = [word for word in original_words if word]
|
||||
filtered_words = [word for word in original_words if word not in active_state or active_state[word]]
|
||||
|
||||
if filtered_words:
|
||||
filtered_triggers = ', '.join(filtered_words)
|
||||
# Fallback to original message parsing if data is not in the expected list format
|
||||
if group_mode:
|
||||
groups = re.split(r",{2,}", trigger_words)
|
||||
groups = [group.strip() for group in groups if group.strip()]
|
||||
filtered_triggers = ", ".join(groups)
|
||||
else:
|
||||
filtered_triggers = ""
|
||||
|
||||
words = [
|
||||
word.strip()
|
||||
for word in trigger_words.split(",")
|
||||
if word.strip()
|
||||
]
|
||||
filtered_triggers = ", ".join(words)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error processing trigger words: {e}")
|
||||
|
||||
return (filtered_triggers,)
|
||||
|
||||
return (filtered_triggers,)
|
||||
|
||||
def _parse_trigger_item(self, item, allow_strength_adjustment):
|
||||
text = (item.get("text") or "").strip()
|
||||
active = bool(item.get("active", False))
|
||||
strength = item.get("strength")
|
||||
|
||||
strength_match = re.match(r"^\((.+):([\d.]+)\)$", text)
|
||||
if strength_match:
|
||||
text = strength_match.group(1).strip()
|
||||
if strength is None:
|
||||
try:
|
||||
strength = float(strength_match.group(2))
|
||||
except ValueError:
|
||||
strength = None
|
||||
|
||||
return {
|
||||
"text": text,
|
||||
"active": active,
|
||||
"strength": strength if allow_strength_adjustment else None,
|
||||
}
|
||||
|
||||
def _format_word_output(self, base_word, strength, allow_strength_adjustment):
|
||||
if allow_strength_adjustment and strength is not None:
|
||||
return f"({base_word}:{strength:.2f})"
|
||||
return base_word
|
||||
|
||||
@@ -36,6 +36,7 @@ any_type = AnyType("*")
|
||||
import os
|
||||
import logging
|
||||
import copy
|
||||
import sys
|
||||
import folder_paths
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -98,22 +99,38 @@ def to_diffusers(input_lora):
|
||||
|
||||
def nunchaku_load_lora(model, lora_name, lora_strength):
|
||||
"""Load a Flux LoRA for Nunchaku model"""
|
||||
# Get full path to the LoRA file. Allow both direct paths and registered LoRA names.
|
||||
lora_path = lora_name if os.path.isfile(lora_name) else folder_paths.get_full_path("loras", lora_name)
|
||||
if not lora_path or not os.path.isfile(lora_path):
|
||||
logger.warning("Skipping LoRA '%s' because it could not be found", lora_name)
|
||||
return model
|
||||
|
||||
model_wrapper = model.model.diffusion_model
|
||||
transformer = model_wrapper.model
|
||||
|
||||
# Save the transformer temporarily
|
||||
model_wrapper.model = None
|
||||
ret_model = copy.deepcopy(model) # copy everything except the model
|
||||
ret_model_wrapper = ret_model.model.diffusion_model
|
||||
|
||||
# Restore the model and set it for the copy
|
||||
model_wrapper.model = transformer
|
||||
ret_model_wrapper.model = transformer
|
||||
|
||||
# Get full path to the LoRA file
|
||||
lora_path = folder_paths.get_full_path("loras", lora_name)
|
||||
ret_model_wrapper.loras.append((lora_path, lora_strength))
|
||||
|
||||
# Try to find copy_with_ctx in the same module as ComfyFluxWrapper
|
||||
module_name = model_wrapper.__class__.__module__
|
||||
module = sys.modules.get(module_name)
|
||||
copy_with_ctx = getattr(module, "copy_with_ctx", None)
|
||||
|
||||
if copy_with_ctx is not None:
|
||||
# New logic using copy_with_ctx from ComfyUI-nunchaku 1.1.0+
|
||||
ret_model_wrapper, ret_model = copy_with_ctx(model_wrapper)
|
||||
ret_model_wrapper.loras = [*model_wrapper.loras, (lora_path, lora_strength)]
|
||||
else:
|
||||
# Fallback to legacy logic
|
||||
logger.warning("Please upgrade ComfyUI-nunchaku to 1.1.0 or above for better LoRA support. Falling back to legacy loading logic.")
|
||||
transformer = model_wrapper.model
|
||||
|
||||
# Save the transformer temporarily
|
||||
model_wrapper.model = None
|
||||
ret_model = copy.deepcopy(model) # copy everything except the model
|
||||
ret_model_wrapper = ret_model.model.diffusion_model
|
||||
|
||||
# Restore the model and set it for the copy
|
||||
model_wrapper.model = transformer
|
||||
ret_model_wrapper.model = transformer
|
||||
ret_model_wrapper.loras.append((lora_path, lora_strength))
|
||||
|
||||
# Convert the LoRA to diffusers format
|
||||
sd = to_diffusers(lora_path)
|
||||
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
from comfy.comfy_types import IO # type: ignore
|
||||
import folder_paths # type: ignore
|
||||
from ..utils.utils import get_lora_info
|
||||
from .utils import FlexibleOptionalInputType, any_type, get_loras_list
|
||||
@@ -6,7 +5,7 @@ import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class WanVideoLoraSelect:
|
||||
class WanVideoLoraSelectLM:
|
||||
NAME = "WanVideo Lora Select (LoraManager)"
|
||||
CATEGORY = "Lora Manager/stackers"
|
||||
|
||||
@@ -16,18 +15,15 @@ class WanVideoLoraSelect:
|
||||
"required": {
|
||||
"low_mem_load": ("BOOLEAN", {"default": False, "tooltip": "Load LORA models with less VRAM usage, slower loading. This affects ALL LoRAs, not just the current ones. No effect if merge_loras is False"}),
|
||||
"merge_loras": ("BOOLEAN", {"default": True, "tooltip": "Merge LoRAs into the model, otherwise they are loaded on the fly. Always disabled for GGUF and scaled fp8 models. This affects ALL LoRAs, not just the current one"}),
|
||||
"text": (IO.STRING, {
|
||||
"multiline": True,
|
||||
"pysssss.autocomplete": False,
|
||||
"dynamicPrompts": True,
|
||||
"text": ("AUTOCOMPLETE_TEXT_LORAS", {
|
||||
"placeholder": "Search LoRAs to add...",
|
||||
"tooltip": "Format: <lora:lora_name:strength> separated by spaces or punctuation",
|
||||
"placeholder": "LoRA syntax input: <lora:name:strength>"
|
||||
}),
|
||||
},
|
||||
"optional": FlexibleOptionalInputType(any_type),
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("WANVIDLORA", IO.STRING, IO.STRING)
|
||||
RETURN_TYPES = ("WANVIDLORA", "STRING", "STRING")
|
||||
RETURN_NAMES = ("lora", "trigger_words", "active_loras")
|
||||
FUNCTION = "process_loras"
|
||||
|
||||
|
||||
@@ -1,5 +1,4 @@
|
||||
from comfy.comfy_types import IO
|
||||
import folder_paths
|
||||
import folder_paths # type: ignore
|
||||
from ..utils.utils import get_lora_info
|
||||
from .utils import any_type
|
||||
import logging
|
||||
@@ -8,7 +7,7 @@ import logging
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 定义新节点的类
|
||||
class WanVideoLoraSelectFromText:
|
||||
class WanVideoLoraTextSelectLM:
|
||||
# 节点在UI中显示的名称
|
||||
NAME = "WanVideo Lora Select From Text (LoraManager)"
|
||||
# 节点所属的分类
|
||||
@@ -20,9 +19,8 @@ class WanVideoLoraSelectFromText:
|
||||
"required": {
|
||||
"low_mem_load": ("BOOLEAN", {"default": False, "tooltip": "Load LORA models with less VRAM usage, slower loading. This affects ALL LoRAs, not just the current ones. No effect if merge_loras is False"}),
|
||||
"merge_lora": ("BOOLEAN", {"default": True, "tooltip": "Merge LoRAs into the model, otherwise they are loaded on the fly. Always disabled for GGUF and scaled fp8 models. This affects ALL LoRAs, not just the current one"}),
|
||||
"lora_syntax": (IO.STRING, {
|
||||
"lora_syntax": ("STRING", {
|
||||
"multiline": True,
|
||||
"defaultInput": True,
|
||||
"forceInput": True,
|
||||
"tooltip": "Connect a TEXT output for LoRA syntax: <lora:name:strength>"
|
||||
}),
|
||||
@@ -34,7 +32,7 @@ class WanVideoLoraSelectFromText:
|
||||
}
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("WANVIDLORA", IO.STRING, IO.STRING)
|
||||
RETURN_TYPES = ("WANVIDLORA", "STRING", "STRING")
|
||||
RETURN_NAMES = ("lora", "trigger_words", "active_loras")
|
||||
|
||||
FUNCTION = "process_loras_from_syntax"
|
||||
@@ -117,11 +115,3 @@ class WanVideoLoraSelectFromText:
|
||||
active_loras_text = " ".join(formatted_loras)
|
||||
|
||||
return (loras_list, trigger_words_text, active_loras_text)
|
||||
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"WanVideoLoraSelectFromText": WanVideoLoraSelectFromText
|
||||
}
|
||||
|
||||
NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"WanVideoLoraSelectFromText": "WanVideo Lora Select From Text (LoraManager)"
|
||||
}
|
||||
|
||||
@@ -8,6 +8,7 @@ from typing import Dict, List, Any, Optional, Tuple
|
||||
from abc import ABC, abstractmethod
|
||||
from ..config import config
|
||||
from ..utils.constants import VALID_LORA_TYPES
|
||||
from ..utils.civitai_utils import rewrite_preview_url
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@@ -36,7 +37,8 @@ class RecipeMetadataParser(ABC):
|
||||
"""
|
||||
pass
|
||||
|
||||
async def populate_lora_from_civitai(self, lora_entry: Dict[str, Any], civitai_info_tuple: Tuple[Dict[str, Any], Optional[str]],
|
||||
@staticmethod
|
||||
async def populate_lora_from_civitai(lora_entry: Dict[str, Any], civitai_info_tuple: Tuple[Dict[str, Any], Optional[str]],
|
||||
recipe_scanner=None, base_model_counts=None, hash_value=None) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
Populate a lora entry with information from Civitai API response
|
||||
@@ -78,7 +80,7 @@ class RecipeMetadataParser(ABC):
|
||||
# Update model name if available
|
||||
if 'model' in civitai_info and 'name' in civitai_info['model']:
|
||||
lora_entry['name'] = civitai_info['model']['name']
|
||||
|
||||
|
||||
lora_entry['id'] = civitai_info.get('id')
|
||||
lora_entry['modelId'] = civitai_info.get('modelId')
|
||||
|
||||
@@ -88,7 +90,10 @@ class RecipeMetadataParser(ABC):
|
||||
|
||||
# Get thumbnail URL from first image
|
||||
if 'images' in civitai_info and civitai_info['images']:
|
||||
lora_entry['thumbnailUrl'] = civitai_info['images'][0].get('url', '')
|
||||
image_url = civitai_info['images'][0].get('url')
|
||||
if image_url:
|
||||
rewritten_image_url, _ = rewrite_preview_url(image_url, media_type='image')
|
||||
lora_entry['thumbnailUrl'] = rewritten_image_url or image_url
|
||||
|
||||
# Get base model
|
||||
current_base_model = civitai_info.get('baseModel', '')
|
||||
@@ -144,40 +149,68 @@ class RecipeMetadataParser(ABC):
|
||||
logger.error(f"Error populating lora from Civitai info: {e}")
|
||||
|
||||
return lora_entry
|
||||
|
||||
async def populate_checkpoint_from_civitai(self, checkpoint: Dict[str, Any], civitai_info: Dict[str, Any]) -> Dict[str, Any]:
|
||||
|
||||
@staticmethod
|
||||
async def populate_checkpoint_from_civitai(checkpoint: Dict[str, Any], civitai_info: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""
|
||||
Populate checkpoint information from Civitai API response
|
||||
|
||||
Args:
|
||||
checkpoint: The checkpoint entry to populate
|
||||
civitai_info: The response from Civitai API
|
||||
civitai_info: The response from Civitai API or a (data, error_msg) tuple
|
||||
|
||||
Returns:
|
||||
The populated checkpoint dict
|
||||
"""
|
||||
try:
|
||||
if civitai_info and civitai_info.get("error") != "Model not found":
|
||||
# Update model name if available
|
||||
if 'model' in civitai_info and 'name' in civitai_info['model']:
|
||||
checkpoint['name'] = civitai_info['model']['name']
|
||||
|
||||
# Update version if available
|
||||
if 'name' in civitai_info:
|
||||
checkpoint['version'] = civitai_info.get('name', '')
|
||||
|
||||
# Get thumbnail URL from first image
|
||||
if 'images' in civitai_info and civitai_info['images']:
|
||||
checkpoint['thumbnailUrl'] = civitai_info['images'][0].get('url', '')
|
||||
|
||||
# Get base model
|
||||
checkpoint['baseModel'] = civitai_info.get('baseModel', '')
|
||||
|
||||
# Get download URL
|
||||
checkpoint['downloadUrl'] = civitai_info.get('downloadUrl', '')
|
||||
else:
|
||||
# Model not found or deleted
|
||||
civitai_data, error_msg = (
|
||||
(civitai_info, None)
|
||||
if not isinstance(civitai_info, tuple)
|
||||
else civitai_info
|
||||
)
|
||||
|
||||
if not civitai_data or error_msg == "Model not found":
|
||||
checkpoint['isDeleted'] = True
|
||||
return checkpoint
|
||||
|
||||
if 'model' in civitai_data and 'name' in civitai_data['model']:
|
||||
checkpoint['name'] = civitai_data['model']['name']
|
||||
|
||||
if 'name' in civitai_data:
|
||||
checkpoint['version'] = civitai_data.get('name', '')
|
||||
|
||||
if 'images' in civitai_data and civitai_data['images']:
|
||||
image_url = civitai_data['images'][0].get('url')
|
||||
if image_url:
|
||||
rewritten_image_url, _ = rewrite_preview_url(image_url, media_type='image')
|
||||
checkpoint['thumbnailUrl'] = rewritten_image_url or image_url
|
||||
|
||||
checkpoint['baseModel'] = civitai_data.get('baseModel', '')
|
||||
checkpoint['downloadUrl'] = civitai_data.get('downloadUrl', '')
|
||||
|
||||
checkpoint['modelId'] = civitai_data.get('modelId', checkpoint.get('modelId', 0))
|
||||
checkpoint['id'] = civitai_data.get('id', 0)
|
||||
|
||||
if 'files' in civitai_data:
|
||||
model_file = next(
|
||||
(
|
||||
file
|
||||
for file in civitai_data.get('files', [])
|
||||
if file.get('type') == 'Model'
|
||||
),
|
||||
None,
|
||||
)
|
||||
|
||||
if model_file:
|
||||
checkpoint['size'] = model_file.get('sizeKB', 0) * 1024
|
||||
|
||||
sha256 = model_file.get('hashes', {}).get('SHA256')
|
||||
if sha256:
|
||||
checkpoint['hash'] = sha256.lower()
|
||||
|
||||
file_name = model_file.get('name', '')
|
||||
if file_name:
|
||||
checkpoint['file_name'] = os.path.splitext(file_name)[0]
|
||||
except Exception as e:
|
||||
logger.error(f"Error populating checkpoint from Civitai info: {e}")
|
||||
|
||||
|
||||
216
py/recipes/enrichment.py
Normal file
216
py/recipes/enrichment.py
Normal file
@@ -0,0 +1,216 @@
|
||||
import logging
|
||||
import json
|
||||
import re
|
||||
import os
|
||||
from typing import Any, Dict, Optional
|
||||
from .merger import GenParamsMerger
|
||||
from .base import RecipeMetadataParser
|
||||
from ..services.metadata_service import get_default_metadata_provider
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class RecipeEnricher:
|
||||
"""Service to enrich recipe metadata from multiple sources (Civitai, Embedded, User)."""
|
||||
|
||||
@staticmethod
|
||||
async def enrich_recipe(
|
||||
recipe: Dict[str, Any],
|
||||
civitai_client: Any,
|
||||
request_params: Optional[Dict[str, Any]] = None
|
||||
) -> bool:
|
||||
"""
|
||||
Enrich a recipe dictionary in-place with metadata from Civitai and embedded params.
|
||||
|
||||
Args:
|
||||
recipe: The recipe dictionary to enrich. Must have 'gen_params' initialized.
|
||||
civitai_client: Authenticated Civitai client instance.
|
||||
request_params: (Optional) Parameters from a user request (e.g. import).
|
||||
|
||||
Returns:
|
||||
bool: True if the recipe was modified, False otherwise.
|
||||
"""
|
||||
updated = False
|
||||
gen_params = recipe.get("gen_params", {})
|
||||
|
||||
# 1. Fetch Civitai Info if available
|
||||
civitai_meta = None
|
||||
model_version_id = None
|
||||
|
||||
source_url = recipe.get("source_url") or recipe.get("source_path", "")
|
||||
|
||||
# Check if it's a Civitai image URL
|
||||
image_id_match = re.search(r'civitai\.com/images/(\d+)', str(source_url))
|
||||
if image_id_match:
|
||||
image_id = image_id_match.group(1)
|
||||
try:
|
||||
image_info = await civitai_client.get_image_info(image_id)
|
||||
if image_info:
|
||||
# Handle nested meta often found in Civitai API responses
|
||||
raw_meta = image_info.get("meta")
|
||||
if isinstance(raw_meta, dict):
|
||||
if "meta" in raw_meta and isinstance(raw_meta["meta"], dict):
|
||||
civitai_meta = raw_meta["meta"]
|
||||
else:
|
||||
civitai_meta = raw_meta
|
||||
|
||||
model_version_id = image_info.get("modelVersionId")
|
||||
|
||||
# If not at top level, check resources in meta
|
||||
if not model_version_id and civitai_meta:
|
||||
resources = civitai_meta.get("civitaiResources", [])
|
||||
for res in resources:
|
||||
if res.get("type") == "checkpoint":
|
||||
model_version_id = res.get("modelVersionId")
|
||||
break
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to fetch Civitai image info: {e}")
|
||||
|
||||
# 2. Merge Parameters
|
||||
# Priority: request_params > civitai_meta > embedded (existing gen_params)
|
||||
new_gen_params = GenParamsMerger.merge(
|
||||
request_params=request_params,
|
||||
civitai_meta=civitai_meta,
|
||||
embedded_metadata=gen_params
|
||||
)
|
||||
|
||||
if new_gen_params != gen_params:
|
||||
recipe["gen_params"] = new_gen_params
|
||||
updated = True
|
||||
|
||||
# 3. Checkpoint Enrichment
|
||||
# If we have a checkpoint entry, or we can find one
|
||||
# Use 'id' (from Civitai version) as a marker that it's been enriched
|
||||
checkpoint_entry = recipe.get("checkpoint")
|
||||
has_full_checkpoint = checkpoint_entry and checkpoint_entry.get("name") and checkpoint_entry.get("id")
|
||||
|
||||
if not has_full_checkpoint:
|
||||
# Helper to look up values in priority order
|
||||
def start_lookup(keys):
|
||||
for source in [request_params, civitai_meta, gen_params]:
|
||||
if source:
|
||||
if isinstance(keys, list):
|
||||
for k in keys:
|
||||
if k in source: return source[k]
|
||||
else:
|
||||
if keys in source: return source[keys]
|
||||
return None
|
||||
|
||||
target_version_id = model_version_id or start_lookup("modelVersionId")
|
||||
|
||||
# Also check existing checkpoint entry
|
||||
if not target_version_id and checkpoint_entry:
|
||||
target_version_id = checkpoint_entry.get("modelVersionId") or checkpoint_entry.get("id")
|
||||
|
||||
# Check for version ID in resources (which might be a string in gen_params)
|
||||
if not target_version_id:
|
||||
# Look in all sources for "Civitai resources"
|
||||
resources_val = start_lookup(["Civitai resources", "civitai_resources", "resources"])
|
||||
if resources_val:
|
||||
target_version_id = RecipeEnricher._extract_version_id_from_resources({"Civitai resources": resources_val})
|
||||
|
||||
target_hash = start_lookup(["Model hash", "checkpoint_hash", "hashes"])
|
||||
if not target_hash and checkpoint_entry:
|
||||
target_hash = checkpoint_entry.get("hash") or checkpoint_entry.get("model_hash")
|
||||
|
||||
# Look for 'Model' which sometimes is the hash or name
|
||||
model_val = start_lookup("Model")
|
||||
|
||||
# Look for Checkpoint name fallback
|
||||
checkpoint_val = checkpoint_entry.get("name") if checkpoint_entry else None
|
||||
if not checkpoint_val:
|
||||
checkpoint_val = start_lookup(["Checkpoint", "checkpoint"])
|
||||
|
||||
checkpoint_updated = await RecipeEnricher._resolve_and_populate_checkpoint(
|
||||
recipe, target_version_id, target_hash, model_val, checkpoint_val
|
||||
)
|
||||
if checkpoint_updated:
|
||||
updated = True
|
||||
else:
|
||||
# Checkpoint exists, no need to sync to gen_params anymore.
|
||||
pass
|
||||
# base_model resolution moved to _resolve_and_populate_checkpoint to support strict formatting
|
||||
return updated
|
||||
|
||||
@staticmethod
|
||||
def _extract_version_id_from_resources(gen_params: Dict[str, Any]) -> Optional[Any]:
|
||||
"""Try to find modelVersionId in Civitai resources parameter."""
|
||||
civitai_resources_raw = gen_params.get("Civitai resources")
|
||||
if not civitai_resources_raw:
|
||||
return None
|
||||
|
||||
resources_list = None
|
||||
if isinstance(civitai_resources_raw, str):
|
||||
try:
|
||||
resources_list = json.loads(civitai_resources_raw)
|
||||
except Exception:
|
||||
pass
|
||||
elif isinstance(civitai_resources_raw, list):
|
||||
resources_list = civitai_resources_raw
|
||||
|
||||
if isinstance(resources_list, list):
|
||||
for res in resources_list:
|
||||
if res.get("type") == "checkpoint":
|
||||
return res.get("modelVersionId")
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
async def _resolve_and_populate_checkpoint(
|
||||
recipe: Dict[str, Any],
|
||||
target_version_id: Optional[Any],
|
||||
target_hash: Optional[str],
|
||||
model_val: Optional[str],
|
||||
checkpoint_val: Optional[str]
|
||||
) -> bool:
|
||||
"""Find checkpoint metadata and populate it in the recipe."""
|
||||
metadata_provider = await get_default_metadata_provider()
|
||||
civitai_info = None
|
||||
|
||||
if target_version_id:
|
||||
civitai_info = await metadata_provider.get_model_version_info(str(target_version_id))
|
||||
elif target_hash:
|
||||
civitai_info = await metadata_provider.get_model_by_hash(target_hash)
|
||||
else:
|
||||
# Look for 'Model' which sometimes is the hash or name
|
||||
if model_val and len(model_val) == 10: # Likely a short hash
|
||||
civitai_info = await metadata_provider.get_model_by_hash(model_val)
|
||||
|
||||
if civitai_info and not (isinstance(civitai_info, tuple) and civitai_info[1] == "Model not found"):
|
||||
# If we already have a partial checkpoint, use it as base
|
||||
existing_cp = recipe.get("checkpoint")
|
||||
if existing_cp is None:
|
||||
existing_cp = {}
|
||||
checkpoint_data = await RecipeMetadataParser.populate_checkpoint_from_civitai(existing_cp, civitai_info)
|
||||
# 1. First, resolve base_model using full data before we format it away
|
||||
current_base_model = recipe.get("base_model")
|
||||
resolved_base_model = checkpoint_data.get("baseModel")
|
||||
if resolved_base_model:
|
||||
# Update if empty OR if it matches our generic prefix but is less specific
|
||||
is_generic = not current_base_model or current_base_model.lower() in ["flux", "sdxl", "sd15"]
|
||||
if is_generic and resolved_base_model != current_base_model:
|
||||
recipe["base_model"] = resolved_base_model
|
||||
|
||||
# 2. Format according to requirements: type, modelId, modelVersionId, modelName, modelVersionName
|
||||
formatted_checkpoint = {
|
||||
"type": "checkpoint",
|
||||
"modelId": checkpoint_data.get("modelId"),
|
||||
"modelVersionId": checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
|
||||
"modelName": checkpoint_data.get("name"), # In base.py, 'name' is populated from civitai_data['model']['name']
|
||||
"modelVersionName": checkpoint_data.get("version") # In base.py, 'version' is populated from civitai_data['name']
|
||||
}
|
||||
# Remove None values
|
||||
recipe["checkpoint"] = {k: v for k, v in formatted_checkpoint.items() if v is not None}
|
||||
|
||||
return True
|
||||
else:
|
||||
# Fallback to name extraction if we don't already have one
|
||||
existing_cp = recipe.get("checkpoint")
|
||||
if not existing_cp or not existing_cp.get("modelName"):
|
||||
cp_name = checkpoint_val
|
||||
if cp_name:
|
||||
recipe["checkpoint"] = {
|
||||
"type": "checkpoint",
|
||||
"modelName": cp_name
|
||||
}
|
||||
return True
|
||||
|
||||
return False
|
||||
98
py/recipes/merger.py
Normal file
98
py/recipes/merger.py
Normal file
@@ -0,0 +1,98 @@
|
||||
from typing import Any, Dict, Optional
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
class GenParamsMerger:
|
||||
"""Utility to merge generation parameters from multiple sources with priority."""
|
||||
|
||||
BLACKLISTED_KEYS = {
|
||||
"id", "url", "userId", "username", "createdAt", "updatedAt", "hash", "meta",
|
||||
"draft", "extra", "width", "height", "process", "quantity", "workflow",
|
||||
"baseModel", "resources", "disablePoi", "aspectRatio", "Created Date",
|
||||
"experimental", "civitaiResources", "civitai_resources", "Civitai resources",
|
||||
"modelVersionId", "modelId", "hashes", "Model", "Model hash", "checkpoint_hash",
|
||||
"checkpoint", "checksum", "model_checksum"
|
||||
}
|
||||
|
||||
NORMALIZATION_MAPPING = {
|
||||
# Civitai specific
|
||||
"cfgScale": "cfg_scale",
|
||||
"clipSkip": "clip_skip",
|
||||
"negativePrompt": "negative_prompt",
|
||||
# Case variations
|
||||
"Sampler": "sampler",
|
||||
"Steps": "steps",
|
||||
"Seed": "seed",
|
||||
"Size": "size",
|
||||
"Prompt": "prompt",
|
||||
"Negative prompt": "negative_prompt",
|
||||
"Cfg scale": "cfg_scale",
|
||||
"Clip skip": "clip_skip",
|
||||
"Denoising strength": "denoising_strength",
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def merge(
|
||||
request_params: Optional[Dict[str, Any]] = None,
|
||||
civitai_meta: Optional[Dict[str, Any]] = None,
|
||||
embedded_metadata: Optional[Dict[str, Any]] = None
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Merge generation parameters from three sources.
|
||||
|
||||
Priority: request_params > civitai_meta > embedded_metadata
|
||||
|
||||
Args:
|
||||
request_params: Params provided directly in the import request
|
||||
civitai_meta: Params from Civitai Image API 'meta' field
|
||||
embedded_metadata: Params extracted from image EXIF/embedded metadata
|
||||
|
||||
Returns:
|
||||
Merged parameters dictionary
|
||||
"""
|
||||
result = {}
|
||||
|
||||
# 1. Start with embedded metadata (lowest priority)
|
||||
if embedded_metadata:
|
||||
# If it's a full recipe metadata, we use its gen_params
|
||||
if "gen_params" in embedded_metadata and isinstance(embedded_metadata["gen_params"], dict):
|
||||
GenParamsMerger._update_normalized(result, embedded_metadata["gen_params"])
|
||||
else:
|
||||
# Otherwise assume the dict itself contains gen_params
|
||||
GenParamsMerger._update_normalized(result, embedded_metadata)
|
||||
|
||||
# 2. Layer Civitai meta (medium priority)
|
||||
if civitai_meta:
|
||||
GenParamsMerger._update_normalized(result, civitai_meta)
|
||||
|
||||
# 3. Layer request params (highest priority)
|
||||
if request_params:
|
||||
GenParamsMerger._update_normalized(result, request_params)
|
||||
|
||||
# Filter out blacklisted keys and also the original camelCase keys if they were normalized
|
||||
final_result = {}
|
||||
for k, v in result.items():
|
||||
if k in GenParamsMerger.BLACKLISTED_KEYS:
|
||||
continue
|
||||
if k in GenParamsMerger.NORMALIZATION_MAPPING:
|
||||
continue
|
||||
final_result[k] = v
|
||||
|
||||
return final_result
|
||||
|
||||
@staticmethod
|
||||
def _update_normalized(target: Dict[str, Any], source: Dict[str, Any]) -> None:
|
||||
"""Update target dict with normalized keys from source."""
|
||||
for k, v in source.items():
|
||||
normalized_key = GenParamsMerger.NORMALIZATION_MAPPING.get(k, k)
|
||||
target[normalized_key] = v
|
||||
# Also keep the original key for now if it's not the same,
|
||||
# so we can filter at the end or avoid losing it if it wasn't supposed to be renamed?
|
||||
# Actually, if we rename it, we should probably NOT keep both in 'target'
|
||||
# because we want to filter them out at the end anyway.
|
||||
if normalized_key != k:
|
||||
# If we are overwriting an existing snake_case key with a camelCase one's value,
|
||||
# that's fine because of the priority order of calls to _update_normalized.
|
||||
pass
|
||||
target[k] = v
|
||||
@@ -1,6 +1,7 @@
|
||||
"""Parser for Automatic1111 metadata format."""
|
||||
|
||||
import re
|
||||
import os
|
||||
import json
|
||||
import logging
|
||||
from typing import Dict, Any
|
||||
@@ -22,6 +23,7 @@ class AutomaticMetadataParser(RecipeMetadataParser):
|
||||
CIVITAI_METADATA_REGEX = r', Civitai metadata:\s*(\{.*?\})'
|
||||
EXTRANETS_REGEX = r'<(lora|hypernet):([^:]+):(-?[0-9.]+)>'
|
||||
MODEL_HASH_PATTERN = r'Model hash: ([a-zA-Z0-9]+)'
|
||||
MODEL_NAME_PATTERN = r'Model: ([^,]+)'
|
||||
VAE_HASH_PATTERN = r'VAE hash: ([a-zA-Z0-9]+)'
|
||||
|
||||
def is_metadata_matching(self, user_comment: str) -> bool:
|
||||
@@ -115,6 +117,12 @@ class AutomaticMetadataParser(RecipeMetadataParser):
|
||||
except json.JSONDecodeError:
|
||||
logger.error("Error parsing hashes JSON")
|
||||
|
||||
# Pick up model hash from parsed hashes if available
|
||||
if "hashes" in metadata and not metadata.get("model_hash"):
|
||||
model_hash_from_hashes = metadata["hashes"].get("model")
|
||||
if model_hash_from_hashes:
|
||||
metadata["model_hash"] = model_hash_from_hashes
|
||||
|
||||
# Extract Lora hashes in alternative format
|
||||
lora_hashes_match = re.search(self.LORA_HASHES_REGEX, params_section)
|
||||
if not hashes_match and lora_hashes_match:
|
||||
@@ -137,6 +145,17 @@ class AutomaticMetadataParser(RecipeMetadataParser):
|
||||
params_section = params_section.replace(lora_hashes_match.group(0), '')
|
||||
except Exception as e:
|
||||
logger.error(f"Error parsing Lora hashes: {e}")
|
||||
|
||||
# Extract checkpoint model hash/name when provided outside Civitai resources
|
||||
model_hash_match = re.search(self.MODEL_HASH_PATTERN, params_section)
|
||||
if model_hash_match:
|
||||
metadata["model_hash"] = model_hash_match.group(1).strip()
|
||||
params_section = params_section.replace(model_hash_match.group(0), '')
|
||||
|
||||
model_name_match = re.search(self.MODEL_NAME_PATTERN, params_section)
|
||||
if model_name_match:
|
||||
metadata["model_name"] = model_name_match.group(1).strip()
|
||||
params_section = params_section.replace(model_name_match.group(0), '')
|
||||
|
||||
# Extract basic parameters
|
||||
param_pattern = r'([A-Za-z\s]+): ([^,]+)'
|
||||
@@ -178,9 +197,10 @@ class AutomaticMetadataParser(RecipeMetadataParser):
|
||||
|
||||
metadata["gen_params"] = gen_params
|
||||
|
||||
# Extract LoRA information
|
||||
# Extract LoRA and checkpoint information
|
||||
loras = []
|
||||
base_model_counts = {}
|
||||
checkpoint = None
|
||||
|
||||
# First use Civitai resources if available (more reliable source)
|
||||
if metadata.get("civitai_resources"):
|
||||
@@ -202,6 +222,50 @@ class AutomaticMetadataParser(RecipeMetadataParser):
|
||||
resource["modelVersionId"] = air_modelVersionId
|
||||
# --- End added ---
|
||||
|
||||
if resource.get("type") == "checkpoint" and resource.get("modelVersionId"):
|
||||
version_id = resource.get("modelVersionId")
|
||||
version_id_str = str(version_id)
|
||||
checkpoint_entry = {
|
||||
'id': version_id,
|
||||
'modelId': resource.get("modelId", 0),
|
||||
'name': resource.get("modelName", "Unknown Checkpoint"),
|
||||
'version': resource.get("modelVersionName", resource.get("versionName", "")),
|
||||
'type': resource.get("type", "checkpoint"),
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': resource.get("modelName", ""),
|
||||
'hash': resource.get("hash", "") or "",
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
}
|
||||
|
||||
if metadata_provider:
|
||||
try:
|
||||
civitai_info = await metadata_provider.get_model_version_info(version_id_str)
|
||||
checkpoint_entry = await self.populate_checkpoint_from_civitai(
|
||||
checkpoint_entry,
|
||||
civitai_info
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
"Error fetching Civitai info for checkpoint version %s: %s",
|
||||
version_id,
|
||||
e,
|
||||
)
|
||||
|
||||
# Prefer the first checkpoint found
|
||||
if checkpoint_entry.get("baseModel"):
|
||||
base_model_value = checkpoint_entry["baseModel"]
|
||||
base_model_counts[base_model_value] = base_model_counts.get(base_model_value, 0) + 1
|
||||
|
||||
if checkpoint is None:
|
||||
checkpoint = checkpoint_entry
|
||||
|
||||
continue
|
||||
|
||||
if resource.get("type") in ["lora", "lycoris", "hypernet"] and resource.get("modelVersionId"):
|
||||
# Initialize lora entry
|
||||
lora_entry = {
|
||||
@@ -237,6 +301,52 @@ class AutomaticMetadataParser(RecipeMetadataParser):
|
||||
|
||||
loras.append(lora_entry)
|
||||
|
||||
# Fallback checkpoint parsing from generic "Model" and "Model hash" fields
|
||||
if checkpoint is None:
|
||||
model_hash = metadata.get("model_hash")
|
||||
if not model_hash and metadata.get("hashes"):
|
||||
model_hash = metadata["hashes"].get("model")
|
||||
|
||||
model_name = metadata.get("model_name")
|
||||
file_name = ""
|
||||
if model_name:
|
||||
cleaned_name = re.split(r"[\\\\/]", model_name)[-1]
|
||||
file_name = os.path.splitext(cleaned_name)[0]
|
||||
|
||||
if model_hash or model_name:
|
||||
checkpoint_entry = {
|
||||
'id': 0,
|
||||
'modelId': 0,
|
||||
'name': model_name or "Unknown Checkpoint",
|
||||
'version': '',
|
||||
'type': 'checkpoint',
|
||||
'hash': model_hash or "",
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': file_name,
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
}
|
||||
|
||||
if metadata_provider and model_hash:
|
||||
try:
|
||||
civitai_info = await metadata_provider.get_model_by_hash(model_hash)
|
||||
checkpoint_entry = await self.populate_checkpoint_from_civitai(
|
||||
checkpoint_entry,
|
||||
civitai_info
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for checkpoint hash {model_hash}: {e}")
|
||||
|
||||
if checkpoint_entry.get("baseModel"):
|
||||
base_model_value = checkpoint_entry["baseModel"]
|
||||
base_model_counts[base_model_value] = base_model_counts.get(base_model_value, 0) + 1
|
||||
|
||||
checkpoint = checkpoint_entry
|
||||
|
||||
# If no LoRAs from Civitai resources or to supplement, extract from metadata["hashes"]
|
||||
if not loras or len(loras) == 0:
|
||||
# Extract lora weights from extranet tags in prompt (for later use)
|
||||
@@ -300,7 +410,9 @@ class AutomaticMetadataParser(RecipeMetadataParser):
|
||||
|
||||
# Try to get base model from resources or make educated guess
|
||||
base_model = None
|
||||
if base_model_counts:
|
||||
if checkpoint and checkpoint.get("baseModel"):
|
||||
base_model = checkpoint.get("baseModel")
|
||||
elif base_model_counts:
|
||||
# Use the most common base model from the loras
|
||||
base_model = max(base_model_counts.items(), key=lambda x: x[1])[0]
|
||||
|
||||
@@ -317,6 +429,10 @@ class AutomaticMetadataParser(RecipeMetadataParser):
|
||||
'gen_params': filtered_gen_params,
|
||||
'from_automatic_metadata': True
|
||||
}
|
||||
|
||||
if checkpoint:
|
||||
result['checkpoint'] = checkpoint
|
||||
result['model'] = checkpoint
|
||||
|
||||
return result
|
||||
|
||||
|
||||
@@ -23,13 +23,48 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
"""
|
||||
if not metadata or not isinstance(metadata, dict):
|
||||
return False
|
||||
|
||||
# Check for key markers specific to Civitai image metadata
|
||||
return any([
|
||||
"resources" in metadata,
|
||||
"civitaiResources" in metadata,
|
||||
"additionalResources" in metadata
|
||||
])
|
||||
|
||||
def has_markers(payload: Dict[str, Any]) -> bool:
|
||||
# Check for common CivitAI image metadata fields
|
||||
civitai_image_fields = (
|
||||
"resources",
|
||||
"civitaiResources",
|
||||
"additionalResources",
|
||||
"hashes",
|
||||
"prompt",
|
||||
"negativePrompt",
|
||||
"steps",
|
||||
"sampler",
|
||||
"cfgScale",
|
||||
"seed",
|
||||
"width",
|
||||
"height",
|
||||
"Model",
|
||||
"Model hash"
|
||||
)
|
||||
return any(key in payload for key in civitai_image_fields)
|
||||
|
||||
# Check the main metadata object
|
||||
if has_markers(metadata):
|
||||
return True
|
||||
|
||||
# Check for LoRA hash patterns
|
||||
hashes = metadata.get("hashes")
|
||||
if isinstance(hashes, dict) and any(str(key).lower().startswith("lora:") for key in hashes):
|
||||
return True
|
||||
|
||||
# Check nested meta object (common in CivitAI image responses)
|
||||
nested_meta = metadata.get("meta")
|
||||
if isinstance(nested_meta, dict):
|
||||
if has_markers(nested_meta):
|
||||
return True
|
||||
|
||||
# Also check for LoRA hash patterns in nested meta
|
||||
hashes = nested_meta.get("hashes")
|
||||
if isinstance(hashes, dict) and any(str(key).lower().startswith("lora:") for key in hashes):
|
||||
return True
|
||||
|
||||
return False
|
||||
|
||||
async def parse_metadata(self, metadata, recipe_scanner=None, civitai_client=None) -> Dict[str, Any]:
|
||||
"""Parse metadata from Civitai image format
|
||||
@@ -45,11 +80,32 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
try:
|
||||
# Get metadata provider instead of using civitai_client directly
|
||||
metadata_provider = await get_default_metadata_provider()
|
||||
|
||||
# Civitai image responses may wrap the actual metadata inside a "meta" key
|
||||
if (
|
||||
isinstance(metadata, dict)
|
||||
and "meta" in metadata
|
||||
and isinstance(metadata["meta"], dict)
|
||||
):
|
||||
inner_meta = metadata["meta"]
|
||||
if any(
|
||||
key in inner_meta
|
||||
for key in (
|
||||
"resources",
|
||||
"civitaiResources",
|
||||
"additionalResources",
|
||||
"hashes",
|
||||
"prompt",
|
||||
"negativePrompt",
|
||||
)
|
||||
):
|
||||
metadata = inner_meta
|
||||
|
||||
# Initialize result structure
|
||||
result = {
|
||||
'base_model': None,
|
||||
'loras': [],
|
||||
'model': None,
|
||||
'gen_params': {},
|
||||
'from_civitai_image': True
|
||||
}
|
||||
@@ -61,8 +117,9 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
lora_hashes = {}
|
||||
if "hashes" in metadata and isinstance(metadata["hashes"], dict):
|
||||
for key, hash_value in metadata["hashes"].items():
|
||||
if key.startswith("LORA:"):
|
||||
lora_name = key.replace("LORA:", "")
|
||||
key_str = str(key)
|
||||
if key_str.lower().startswith("lora:"):
|
||||
lora_name = key_str.split(":", 1)[1]
|
||||
lora_hashes[lora_name] = hash_value
|
||||
|
||||
# Extract prompt and negative prompt
|
||||
@@ -174,13 +231,48 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
# Process civitaiResources array
|
||||
if "civitaiResources" in metadata and isinstance(metadata["civitaiResources"], list):
|
||||
for resource in metadata["civitaiResources"]:
|
||||
# Get unique identifier for deduplication
|
||||
# Get resource type and identifier
|
||||
resource_type = str(resource.get("type") or "").lower()
|
||||
version_id = str(resource.get("modelVersionId", ""))
|
||||
|
||||
|
||||
if resource_type == "checkpoint":
|
||||
checkpoint_entry = {
|
||||
'id': resource.get("modelVersionId", 0),
|
||||
'modelId': resource.get("modelId", 0),
|
||||
'name': resource.get("modelName", "Unknown Checkpoint"),
|
||||
'version': resource.get("modelVersionName", ""),
|
||||
'type': resource.get("type", "checkpoint"),
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': resource.get("modelName", ""),
|
||||
'hash': resource.get("hash", "") or "",
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
}
|
||||
|
||||
if version_id and metadata_provider:
|
||||
try:
|
||||
civitai_info = await metadata_provider.get_model_version_info(version_id)
|
||||
|
||||
checkpoint_entry = await self.populate_checkpoint_from_civitai(
|
||||
checkpoint_entry,
|
||||
civitai_info
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for checkpoint version {version_id}: {e}")
|
||||
|
||||
if result["model"] is None:
|
||||
result["model"] = checkpoint_entry
|
||||
|
||||
continue
|
||||
|
||||
# Skip if we've already added this LoRA
|
||||
if version_id and version_id in added_loras:
|
||||
continue
|
||||
|
||||
|
||||
# Initialize lora entry
|
||||
lora_entry = {
|
||||
'id': resource.get("modelVersionId", 0),
|
||||
@@ -196,31 +288,31 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
}
|
||||
|
||||
|
||||
# Try to get info from Civitai if modelVersionId is available
|
||||
if version_id and metadata_provider:
|
||||
try:
|
||||
# Use get_model_version_info instead of get_model_version
|
||||
civitai_info = await metadata_provider.get_model_version_info(version_id)
|
||||
|
||||
|
||||
populated_entry = await self.populate_lora_from_civitai(
|
||||
lora_entry,
|
||||
civitai_info,
|
||||
recipe_scanner,
|
||||
base_model_counts
|
||||
)
|
||||
|
||||
|
||||
if populated_entry is None:
|
||||
continue # Skip invalid LoRA types
|
||||
|
||||
|
||||
lora_entry = populated_entry
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for model version {version_id}: {e}")
|
||||
|
||||
|
||||
# Track this LoRA in our deduplication dict
|
||||
if version_id:
|
||||
added_loras[version_id] = len(result["loras"])
|
||||
|
||||
|
||||
result["loras"].append(lora_entry)
|
||||
|
||||
# Process additionalResources array
|
||||
@@ -284,7 +376,59 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
logger.error(f"Error fetching Civitai info for model ID {version_id}: {e}")
|
||||
|
||||
result["loras"].append(lora_entry)
|
||||
|
||||
|
||||
# If we found LoRA hashes in the metadata but haven't already
|
||||
# populated entries for them, fall back to creating LoRAs from
|
||||
# the hashes section. Some Civitai image responses only include
|
||||
# LoRA information here without explicit resources entries.
|
||||
for lora_name, lora_hash in lora_hashes.items():
|
||||
if not lora_hash:
|
||||
continue
|
||||
|
||||
# Skip LoRAs we've already added via resources or other fields
|
||||
if lora_hash in added_loras:
|
||||
continue
|
||||
|
||||
lora_entry = {
|
||||
'name': lora_name,
|
||||
'type': "lora",
|
||||
'weight': 1.0,
|
||||
'hash': lora_hash,
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': lora_name,
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
}
|
||||
|
||||
if metadata_provider:
|
||||
try:
|
||||
civitai_info = await metadata_provider.get_model_by_hash(lora_hash)
|
||||
|
||||
populated_entry = await self.populate_lora_from_civitai(
|
||||
lora_entry,
|
||||
civitai_info,
|
||||
recipe_scanner,
|
||||
base_model_counts,
|
||||
lora_hash
|
||||
)
|
||||
|
||||
if populated_entry is None:
|
||||
continue
|
||||
|
||||
lora_entry = populated_entry
|
||||
|
||||
if 'id' in lora_entry and lora_entry['id']:
|
||||
added_loras[str(lora_entry['id'])] = len(result["loras"])
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for LoRA hash {lora_hash}: {e}")
|
||||
|
||||
added_loras[lora_hash] = len(result["loras"])
|
||||
result["loras"].append(lora_entry)
|
||||
|
||||
# Check for LoRA info in the format "Lora_0 Model hash", "Lora_0 Model name", etc.
|
||||
lora_index = 0
|
||||
while f"Lora_{lora_index} Model hash" in metadata and f"Lora_{lora_index} Model name" in metadata:
|
||||
|
||||
@@ -36,9 +36,6 @@ class ComfyMetadataParser(RecipeMetadataParser):
|
||||
# Find all LoraLoader nodes
|
||||
lora_nodes = {k: v for k, v in data.items() if isinstance(v, dict) and v.get('class_type') == 'LoraLoader'}
|
||||
|
||||
if not lora_nodes:
|
||||
return {"error": "No LoRA information found in this ComfyUI workflow", "loras": []}
|
||||
|
||||
# Process each LoraLoader node
|
||||
for node_id, node in lora_nodes.items():
|
||||
if 'inputs' not in node or 'lora_name' not in node['inputs']:
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
"""Parser for meta format (Lora_N Model hash) metadata."""
|
||||
|
||||
import os
|
||||
import re
|
||||
import logging
|
||||
from typing import Dict, Any
|
||||
@@ -145,14 +146,53 @@ class MetaFormatParser(RecipeMetadataParser):
|
||||
|
||||
loras.append(lora_entry)
|
||||
|
||||
# Extract model information
|
||||
model = None
|
||||
if 'model' in metadata:
|
||||
model = metadata['model']
|
||||
# Extract checkpoint information from generic Model/Model hash fields
|
||||
checkpoint = None
|
||||
model_hash = metadata.get("model_hash")
|
||||
model_name = metadata.get("model")
|
||||
|
||||
if model_hash or model_name:
|
||||
cleaned_name = None
|
||||
if model_name:
|
||||
cleaned_name = re.split(r"[\\\\/]", model_name)[-1]
|
||||
cleaned_name = os.path.splitext(cleaned_name)[0]
|
||||
|
||||
checkpoint_entry = {
|
||||
'id': 0,
|
||||
'modelId': 0,
|
||||
'name': model_name or "Unknown Checkpoint",
|
||||
'version': '',
|
||||
'type': 'checkpoint',
|
||||
'hash': model_hash or "",
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': cleaned_name or (model_name or ""),
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
}
|
||||
|
||||
if metadata_provider and model_hash:
|
||||
try:
|
||||
civitai_info = await metadata_provider.get_model_by_hash(model_hash)
|
||||
checkpoint_entry = await self.populate_checkpoint_from_civitai(
|
||||
checkpoint_entry,
|
||||
civitai_info
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for checkpoint hash {model_hash}: {e}")
|
||||
|
||||
if checkpoint_entry.get("baseModel"):
|
||||
base_model_value = checkpoint_entry["baseModel"]
|
||||
base_model_counts[base_model_value] = base_model_counts.get(base_model_value, 0) + 1
|
||||
|
||||
checkpoint = checkpoint_entry
|
||||
|
||||
# Set base_model to the most common one from civitai_info
|
||||
base_model = None
|
||||
if base_model_counts:
|
||||
# Set base_model to the most common one from civitai_info or checkpoint
|
||||
base_model = checkpoint["baseModel"] if checkpoint and checkpoint.get("baseModel") else None
|
||||
if not base_model and base_model_counts:
|
||||
base_model = max(base_model_counts.items(), key=lambda x: x[1])[0]
|
||||
|
||||
# Extract generation parameters for recipe metadata
|
||||
@@ -170,7 +210,8 @@ class MetaFormatParser(RecipeMetadataParser):
|
||||
'loras': loras,
|
||||
'gen_params': gen_params,
|
||||
'raw_metadata': metadata,
|
||||
'from_meta_format': True
|
||||
'from_meta_format': True,
|
||||
**({'checkpoint': checkpoint, 'model': checkpoint} if checkpoint else {})
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
|
||||
@@ -3,7 +3,7 @@
|
||||
import re
|
||||
import json
|
||||
import logging
|
||||
from typing import Dict, Any
|
||||
from typing import Dict, Any, Optional
|
||||
from ...config import config
|
||||
from ..base import RecipeMetadataParser
|
||||
from ..constants import GEN_PARAM_KEYS
|
||||
@@ -16,6 +16,28 @@ class RecipeFormatParser(RecipeMetadataParser):
|
||||
|
||||
# Regular expression pattern for extracting recipe metadata
|
||||
METADATA_MARKER = r'Recipe metadata: (\{.*\})'
|
||||
|
||||
async def _get_lora_from_version_index(self, recipe_scanner, model_version_id: Any) -> Optional[Dict[str, Any]]:
|
||||
"""Return a cached LoRA entry by modelVersionId if available."""
|
||||
|
||||
if not recipe_scanner or not getattr(recipe_scanner, "_lora_scanner", None):
|
||||
return None
|
||||
|
||||
try:
|
||||
normalized_id = int(model_version_id)
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
|
||||
try:
|
||||
cache = await recipe_scanner._lora_scanner.get_cached_data()
|
||||
except Exception as exc: # pragma: no cover - defensive logging
|
||||
logger.debug("Unable to load lora cache for version lookup: %s", exc)
|
||||
return None
|
||||
|
||||
if not cache or not getattr(cache, "version_index", None):
|
||||
return None
|
||||
|
||||
return cache.version_index.get(normalized_id)
|
||||
|
||||
def is_metadata_matching(self, user_comment: str) -> bool:
|
||||
"""Check if the user comment matches the metadata format"""
|
||||
@@ -53,49 +75,110 @@ class RecipeFormatParser(RecipeMetadataParser):
|
||||
'type': 'lora',
|
||||
'weight': lora.get('strength', 1.0),
|
||||
'file_name': lora.get('file_name', ''),
|
||||
'hash': lora.get('hash', '')
|
||||
'hash': lora.get('hash', ''),
|
||||
'existsLocally': False,
|
||||
'inLibrary': False,
|
||||
'localPath': None,
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'size': 0
|
||||
}
|
||||
|
||||
# Check if this LoRA exists locally by SHA256 hash
|
||||
if lora.get('hash') and recipe_scanner:
|
||||
if recipe_scanner:
|
||||
lora_scanner = recipe_scanner._lora_scanner
|
||||
exists_locally = lora_scanner.has_hash(lora['hash'])
|
||||
if exists_locally:
|
||||
lora_cache = await lora_scanner.get_cached_data()
|
||||
lora_item = next((item for item in lora_cache.raw_data if item['sha256'].lower() == lora['hash'].lower()), None)
|
||||
if lora_item:
|
||||
|
||||
if lora.get('hash'):
|
||||
exists_locally = lora_scanner.has_hash(lora['hash'])
|
||||
if exists_locally:
|
||||
lora_cache = await lora_scanner.get_cached_data()
|
||||
lora_item = next((item for item in lora_cache.raw_data if item['sha256'].lower() == lora['hash'].lower()), None)
|
||||
if lora_item:
|
||||
lora_entry['existsLocally'] = True
|
||||
lora_entry['inLibrary'] = True
|
||||
lora_entry['localPath'] = lora_item['file_path']
|
||||
lora_entry['file_name'] = lora_item['file_name']
|
||||
lora_entry['size'] = lora_item['size']
|
||||
lora_entry['thumbnailUrl'] = config.get_preview_static_url(lora_item['preview_url'])
|
||||
|
||||
else:
|
||||
lora_entry['existsLocally'] = False
|
||||
lora_entry['inLibrary'] = False
|
||||
lora_entry['localPath'] = None
|
||||
|
||||
# If we still don't have a local match, try matching by modelVersionId
|
||||
if not lora_entry['existsLocally'] and lora.get('modelVersionId') is not None:
|
||||
cached_lora = await self._get_lora_from_version_index(recipe_scanner, lora.get('modelVersionId'))
|
||||
if cached_lora:
|
||||
lora_entry['existsLocally'] = True
|
||||
lora_entry['localPath'] = lora_item['file_path']
|
||||
lora_entry['file_name'] = lora_item['file_name']
|
||||
lora_entry['size'] = lora_item['size']
|
||||
lora_entry['thumbnailUrl'] = config.get_preview_static_url(lora_item['preview_url'])
|
||||
|
||||
else:
|
||||
lora_entry['existsLocally'] = False
|
||||
lora_entry['localPath'] = None
|
||||
|
||||
# Try to get additional info from Civitai if we have a model version ID
|
||||
if lora.get('modelVersionId') and metadata_provider:
|
||||
try:
|
||||
civitai_info_tuple = await metadata_provider.get_model_version_info(lora['modelVersionId'])
|
||||
# Populate lora entry with Civitai info
|
||||
populated_entry = await self.populate_lora_from_civitai(
|
||||
lora_entry,
|
||||
civitai_info_tuple,
|
||||
recipe_scanner,
|
||||
None, # No need to track base model counts
|
||||
lora['hash']
|
||||
)
|
||||
if populated_entry is None:
|
||||
continue # Skip invalid LoRA types
|
||||
lora_entry = populated_entry
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for LoRA: {e}")
|
||||
lora_entry['thumbnailUrl'] = '/loras_static/images/no-preview.png'
|
||||
lora_entry['inLibrary'] = True
|
||||
lora_entry['localPath'] = cached_lora.get('file_path')
|
||||
lora_entry['file_name'] = cached_lora.get('file_name') or lora_entry['file_name']
|
||||
lora_entry['size'] = cached_lora.get('size', lora_entry['size'])
|
||||
if cached_lora.get('sha256'):
|
||||
lora_entry['hash'] = cached_lora['sha256']
|
||||
preview_url = cached_lora.get('preview_url')
|
||||
if preview_url:
|
||||
lora_entry['thumbnailUrl'] = config.get_preview_static_url(preview_url)
|
||||
|
||||
# Try to get additional info from Civitai if we have a model version ID and still missing locally
|
||||
if not lora_entry['existsLocally'] and lora.get('modelVersionId') and metadata_provider:
|
||||
try:
|
||||
civitai_info_tuple = await metadata_provider.get_model_version_info(lora['modelVersionId'])
|
||||
# Populate lora entry with Civitai info
|
||||
populated_entry = await self.populate_lora_from_civitai(
|
||||
lora_entry,
|
||||
civitai_info_tuple,
|
||||
recipe_scanner,
|
||||
None, # No need to track base model counts
|
||||
lora_entry.get('hash', '')
|
||||
)
|
||||
if populated_entry is None:
|
||||
continue # Skip invalid LoRA types
|
||||
lora_entry = populated_entry
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for LoRA: {e}")
|
||||
lora_entry['thumbnailUrl'] = '/loras_static/images/no-preview.png'
|
||||
|
||||
loras.append(lora_entry)
|
||||
|
||||
|
||||
logger.info(f"Found {len(loras)} loras in recipe metadata")
|
||||
|
||||
# Process checkpoint information if present
|
||||
checkpoint = None
|
||||
checkpoint_data = recipe_metadata.get('checkpoint') or {}
|
||||
if isinstance(checkpoint_data, dict) and checkpoint_data:
|
||||
version_id = checkpoint_data.get('modelVersionId') or checkpoint_data.get('id')
|
||||
checkpoint_entry = {
|
||||
'id': version_id or 0,
|
||||
'modelId': checkpoint_data.get('modelId', 0),
|
||||
'name': checkpoint_data.get('name', 'Unknown Checkpoint'),
|
||||
'version': checkpoint_data.get('version', ''),
|
||||
'type': checkpoint_data.get('type', 'checkpoint'),
|
||||
'hash': checkpoint_data.get('hash', ''),
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': checkpoint_data.get('file_name', ''),
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
}
|
||||
|
||||
if metadata_provider:
|
||||
try:
|
||||
civitai_info = None
|
||||
if version_id:
|
||||
civitai_info = await metadata_provider.get_model_version_info(str(version_id))
|
||||
elif checkpoint_entry.get('hash'):
|
||||
civitai_info = await metadata_provider.get_model_by_hash(checkpoint_entry['hash'])
|
||||
|
||||
if civitai_info:
|
||||
checkpoint_entry = await self.populate_checkpoint_from_civitai(checkpoint_entry, civitai_info)
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for checkpoint in recipe metadata: {e}")
|
||||
|
||||
checkpoint = checkpoint_entry
|
||||
|
||||
# Filter gen_params to only include recognized keys
|
||||
filtered_gen_params = {}
|
||||
@@ -105,12 +188,13 @@ class RecipeFormatParser(RecipeMetadataParser):
|
||||
filtered_gen_params[key] = value
|
||||
|
||||
return {
|
||||
'base_model': recipe_metadata.get('base_model', ''),
|
||||
'base_model': checkpoint['baseModel'] if checkpoint and checkpoint.get('baseModel') else recipe_metadata.get('base_model', ''),
|
||||
'loras': loras,
|
||||
'gen_params': filtered_gen_params,
|
||||
'tags': recipe_metadata.get('tags', []),
|
||||
'title': recipe_metadata.get('title', ''),
|
||||
'from_recipe_metadata': True
|
||||
'from_recipe_metadata': True,
|
||||
**({'checkpoint': checkpoint, 'model': checkpoint} if checkpoint else {})
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
|
||||
@@ -2,7 +2,7 @@ from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from abc import ABC, abstractmethod
|
||||
from typing import Callable, Dict, Mapping
|
||||
from typing import TYPE_CHECKING, Callable, Dict, Mapping
|
||||
|
||||
import jinja2
|
||||
from aiohttp import web
|
||||
@@ -17,7 +17,7 @@ from ..services.model_lifecycle_service import ModelLifecycleService
|
||||
from ..services.preview_asset_service import PreviewAssetService
|
||||
from ..services.server_i18n import server_i18n as default_server_i18n
|
||||
from ..services.service_registry import ServiceRegistry
|
||||
from ..services.settings_manager import settings as default_settings
|
||||
from ..services.settings_manager import get_settings_manager
|
||||
from ..services.tag_update_service import TagUpdateService
|
||||
from ..services.websocket_manager import ws_manager as default_ws_manager
|
||||
from ..services.use_cases import (
|
||||
@@ -42,8 +42,12 @@ from .handlers.model_handlers import (
|
||||
ModelMoveHandler,
|
||||
ModelPageView,
|
||||
ModelQueryHandler,
|
||||
ModelUpdateHandler,
|
||||
)
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from ..services.model_update_service import ModelUpdateService
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@@ -56,14 +60,14 @@ class BaseModelRoutes(ABC):
|
||||
self,
|
||||
service=None,
|
||||
*,
|
||||
settings_service=default_settings,
|
||||
settings_service=None,
|
||||
ws_manager=default_ws_manager,
|
||||
server_i18n=default_server_i18n,
|
||||
metadata_provider_factory=get_default_metadata_provider,
|
||||
) -> None:
|
||||
self.service = None
|
||||
self.model_type = ""
|
||||
self._settings = settings_service
|
||||
self._settings = settings_service or get_settings_manager()
|
||||
self._ws_manager = ws_manager
|
||||
self._server_i18n = server_i18n
|
||||
self._metadata_provider_factory = metadata_provider_factory
|
||||
@@ -90,7 +94,7 @@ class BaseModelRoutes(ABC):
|
||||
self._metadata_sync_service = MetadataSyncService(
|
||||
metadata_manager=MetadataManager,
|
||||
preview_service=self._preview_service,
|
||||
settings=settings_service,
|
||||
settings=self._settings,
|
||||
default_metadata_provider_factory=metadata_provider_factory,
|
||||
metadata_provider_selector=get_metadata_provider,
|
||||
)
|
||||
@@ -99,21 +103,30 @@ class BaseModelRoutes(ABC):
|
||||
ws_manager=self._ws_manager,
|
||||
download_manager_factory=ServiceRegistry.get_download_manager,
|
||||
)
|
||||
self._model_update_service: ModelUpdateService | None = None
|
||||
|
||||
if service is not None:
|
||||
self.attach_service(service)
|
||||
|
||||
def set_model_update_service(self, service: "ModelUpdateService") -> None:
|
||||
"""Attach the model update tracking service."""
|
||||
|
||||
self._model_update_service = service
|
||||
self._handler_set = None
|
||||
self._handler_mapping = None
|
||||
|
||||
def attach_service(self, service) -> None:
|
||||
"""Attach a model service and rebuild handler dependencies."""
|
||||
self.service = service
|
||||
self.model_type = service.model_type
|
||||
self.model_file_service = ModelFileService(service.scanner, service.model_type)
|
||||
self.model_move_service = ModelMoveService(service.scanner)
|
||||
self.model_move_service = ModelMoveService(service.scanner, service.model_type)
|
||||
self.model_lifecycle_service = ModelLifecycleService(
|
||||
scanner=service.scanner,
|
||||
metadata_manager=MetadataManager,
|
||||
metadata_loader=self._metadata_sync_service.load_local_metadata,
|
||||
recipe_scanner_factory=ServiceRegistry.get_recipe_scanner,
|
||||
update_service=self._model_update_service,
|
||||
)
|
||||
self._handler_set = None
|
||||
self._handler_mapping = None
|
||||
@@ -127,6 +140,7 @@ class BaseModelRoutes(ABC):
|
||||
|
||||
def _create_handler_set(self) -> ModelHandlerSet:
|
||||
service = self._ensure_service()
|
||||
update_service = self._ensure_model_update_service()
|
||||
page_view = ModelPageView(
|
||||
template_env=self.template_env,
|
||||
template_name=self.template_name or "",
|
||||
@@ -186,6 +200,12 @@ class BaseModelRoutes(ABC):
|
||||
ws_manager=self._ws_manager,
|
||||
logger=logger,
|
||||
)
|
||||
updates = ModelUpdateHandler(
|
||||
service=service,
|
||||
update_service=update_service,
|
||||
metadata_provider_selector=get_metadata_provider,
|
||||
logger=logger,
|
||||
)
|
||||
return ModelHandlerSet(
|
||||
page_view=page_view,
|
||||
listing=listing,
|
||||
@@ -195,6 +215,7 @@ class BaseModelRoutes(ABC):
|
||||
civitai=civitai,
|
||||
move=move,
|
||||
auto_organize=auto_organize,
|
||||
updates=updates,
|
||||
)
|
||||
|
||||
@property
|
||||
@@ -249,7 +270,7 @@ class BaseModelRoutes(ABC):
|
||||
def _ensure_move_service(self) -> ModelMoveService:
|
||||
if self.model_move_service is None:
|
||||
service = self._ensure_service()
|
||||
self.model_move_service = ModelMoveService(service.scanner)
|
||||
self.model_move_service = ModelMoveService(service.scanner, service.model_type)
|
||||
return self.model_move_service
|
||||
|
||||
def _ensure_lifecycle_service(self) -> ModelLifecycleService:
|
||||
@@ -273,3 +294,7 @@ class BaseModelRoutes(ABC):
|
||||
|
||||
return proxy
|
||||
|
||||
def _ensure_model_update_service(self) -> "ModelUpdateService":
|
||||
if self._model_update_service is None:
|
||||
raise RuntimeError("Model update service has not been attached")
|
||||
return self._model_update_service
|
||||
|
||||
@@ -18,7 +18,7 @@ from ..services.recipes import (
|
||||
)
|
||||
from ..services.server_i18n import server_i18n
|
||||
from ..services.service_registry import ServiceRegistry
|
||||
from ..services.settings_manager import settings
|
||||
from ..services.settings_manager import get_settings_manager
|
||||
from ..utils.constants import CARD_PREVIEW_WIDTH
|
||||
from ..utils.exif_utils import ExifUtils
|
||||
from .handlers.recipe_handlers import (
|
||||
@@ -48,7 +48,7 @@ class BaseRecipeRoutes:
|
||||
self.recipe_scanner = None
|
||||
self.lora_scanner = None
|
||||
self.civitai_client = None
|
||||
self.settings = settings
|
||||
self.settings = get_settings_manager()
|
||||
self.server_i18n = server_i18n
|
||||
self.template_env = jinja2.Environment(
|
||||
loader=jinja2.FileSystemLoader(config.templates_path),
|
||||
@@ -79,26 +79,8 @@ class BaseRecipeRoutes:
|
||||
return
|
||||
|
||||
app.on_startup.append(self.attach_dependencies)
|
||||
app.on_startup.append(self.prewarm_cache)
|
||||
self._startup_hooks_registered = True
|
||||
|
||||
async def prewarm_cache(self, app: web.Application | None = None) -> None:
|
||||
"""Pre-load recipe and LoRA caches on startup."""
|
||||
|
||||
try:
|
||||
await self.attach_dependencies(app)
|
||||
|
||||
if self.lora_scanner is not None:
|
||||
await self.lora_scanner.get_cached_data()
|
||||
hash_index = getattr(self.lora_scanner, "_hash_index", None)
|
||||
if hash_index is not None and hasattr(hash_index, "_hash_to_path"):
|
||||
_ = len(hash_index._hash_to_path)
|
||||
|
||||
if self.recipe_scanner is not None:
|
||||
await self.recipe_scanner.get_cached_data(force_refresh=True)
|
||||
except Exception as exc:
|
||||
logger.error("Error pre-warming recipe cache: %s", exc, exc_info=True)
|
||||
|
||||
def to_route_mapping(self) -> Mapping[str, Callable]:
|
||||
"""Return a mapping of handler name to coroutine for registrar binding."""
|
||||
|
||||
@@ -134,7 +116,7 @@ class BaseRecipeRoutes:
|
||||
recipe_scanner_getter = lambda: self.recipe_scanner
|
||||
civitai_client_getter = lambda: self.civitai_client
|
||||
|
||||
standalone_mode = os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
|
||||
standalone_mode = os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1" or os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
|
||||
if not standalone_mode:
|
||||
from ..metadata_collector import get_metadata # type: ignore[import-not-found]
|
||||
from ..metadata_collector.metadata_processor import ( # type: ignore[import-not-found]
|
||||
@@ -191,6 +173,8 @@ class BaseRecipeRoutes:
|
||||
logger=logger,
|
||||
persistence_service=persistence_service,
|
||||
analysis_service=analysis_service,
|
||||
downloader_factory=get_downloader,
|
||||
civitai_client_getter=civitai_client_getter,
|
||||
)
|
||||
analysis = RecipeAnalysisHandler(
|
||||
ensure_dependencies_ready=self.ensure_dependencies_ready,
|
||||
@@ -214,4 +198,3 @@ class BaseRecipeRoutes:
|
||||
analysis=analysis,
|
||||
sharing=sharing,
|
||||
)
|
||||
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
import logging
|
||||
from typing import Dict
|
||||
from aiohttp import web
|
||||
|
||||
from .base_model_routes import BaseModelRoutes
|
||||
@@ -20,8 +21,10 @@ class CheckpointRoutes(BaseModelRoutes):
|
||||
async def initialize_services(self):
|
||||
"""Initialize services from ServiceRegistry"""
|
||||
checkpoint_scanner = await ServiceRegistry.get_checkpoint_scanner()
|
||||
self.service = CheckpointService(checkpoint_scanner)
|
||||
|
||||
update_service = await ServiceRegistry.get_model_update_service()
|
||||
self.service = CheckpointService(checkpoint_scanner, update_service=update_service)
|
||||
self.set_model_update_service(update_service)
|
||||
|
||||
# Attach service dependencies
|
||||
self.attach_service(self.service)
|
||||
|
||||
@@ -49,6 +52,19 @@ class CheckpointRoutes(BaseModelRoutes):
|
||||
def _get_expected_model_types(self) -> str:
|
||||
"""Get expected model types string for error messages"""
|
||||
return "Checkpoint"
|
||||
|
||||
def _parse_specific_params(self, request: web.Request) -> Dict:
|
||||
"""Parse Checkpoint-specific parameters"""
|
||||
params: Dict = {}
|
||||
|
||||
if 'checkpoint_hash' in request.query:
|
||||
params['hash_filters'] = {'single_hash': request.query['checkpoint_hash'].lower()}
|
||||
elif 'checkpoint_hashes' in request.query:
|
||||
params['hash_filters'] = {
|
||||
'multiple_hashes': [h.lower() for h in request.query['checkpoint_hashes'].split(',')]
|
||||
}
|
||||
|
||||
return params
|
||||
|
||||
async def get_checkpoint_info(self, request: web.Request) -> web.Response:
|
||||
"""Get detailed information for a specific checkpoint by name"""
|
||||
@@ -93,4 +109,4 @@ class CheckpointRoutes(BaseModelRoutes):
|
||||
return web.json_response({
|
||||
"success": False,
|
||||
"error": str(e)
|
||||
}, status=500)
|
||||
}, status=500)
|
||||
|
||||
@@ -19,8 +19,10 @@ class EmbeddingRoutes(BaseModelRoutes):
|
||||
async def initialize_services(self):
|
||||
"""Initialize services from ServiceRegistry"""
|
||||
embedding_scanner = await ServiceRegistry.get_embedding_scanner()
|
||||
self.service = EmbeddingService(embedding_scanner)
|
||||
|
||||
update_service = await ServiceRegistry.get_model_update_service()
|
||||
self.service = EmbeddingService(embedding_scanner, update_service=update_service)
|
||||
self.set_model_update_service(update_service)
|
||||
|
||||
# Attach service dependencies
|
||||
self.attach_service(self.service)
|
||||
|
||||
|
||||
@@ -22,12 +22,15 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
|
||||
RouteDefinition("GET", "/api/lm/example-images-status", "get_example_images_status"),
|
||||
RouteDefinition("POST", "/api/lm/pause-example-images", "pause_example_images"),
|
||||
RouteDefinition("POST", "/api/lm/resume-example-images", "resume_example_images"),
|
||||
RouteDefinition("POST", "/api/lm/stop-example-images", "stop_example_images"),
|
||||
RouteDefinition("POST", "/api/lm/open-example-images-folder", "open_example_images_folder"),
|
||||
RouteDefinition("GET", "/api/lm/example-image-files", "get_example_image_files"),
|
||||
RouteDefinition("GET", "/api/lm/has-example-images", "has_example_images"),
|
||||
RouteDefinition("POST", "/api/lm/delete-example-image", "delete_example_image"),
|
||||
RouteDefinition("POST", "/api/lm/force-download-example-images", "force_download_example_images"),
|
||||
RouteDefinition("POST", "/api/lm/cleanup-example-image-folders", "cleanup_example_image_folders"),
|
||||
RouteDefinition("POST", "/api/lm/example-images/set-nsfw-level", "set_example_image_nsfw_level"),
|
||||
RouteDefinition("POST", "/api/lm/check-example-images-needed", "check_example_images_needed"),
|
||||
)
|
||||
|
||||
|
||||
|
||||
@@ -68,6 +68,13 @@ class ExampleImagesDownloadHandler:
|
||||
except DownloadNotRunningError as exc:
|
||||
return web.json_response({'success': False, 'error': str(exc)}, status=400)
|
||||
|
||||
async def stop_example_images(self, request: web.Request) -> web.StreamResponse:
|
||||
try:
|
||||
result = await self._download_manager.stop_download(request)
|
||||
return web.json_response(result)
|
||||
except DownloadNotRunningError as exc:
|
||||
return web.json_response({'success': False, 'error': str(exc)}, status=400)
|
||||
|
||||
async def force_download_example_images(self, request: web.Request) -> web.StreamResponse:
|
||||
try:
|
||||
payload = await request.json()
|
||||
@@ -85,6 +92,19 @@ class ExampleImagesDownloadHandler:
|
||||
except ExampleImagesDownloadError as exc:
|
||||
return web.json_response({'success': False, 'error': str(exc)}, status=500)
|
||||
|
||||
async def check_example_images_needed(self, request: web.Request) -> web.StreamResponse:
|
||||
"""Lightweight check to see if any models need example images downloaded."""
|
||||
try:
|
||||
payload = await request.json()
|
||||
model_types = payload.get('model_types', ['lora', 'checkpoint', 'embedding'])
|
||||
result = await self._download_manager.check_pending_models(model_types)
|
||||
return web.json_response(result)
|
||||
except Exception as exc:
|
||||
return web.json_response(
|
||||
{'success': False, 'error': str(exc)},
|
||||
status=500
|
||||
)
|
||||
|
||||
|
||||
class ExampleImagesManagementHandler:
|
||||
"""HTTP adapters for import/delete endpoints."""
|
||||
@@ -106,6 +126,9 @@ class ExampleImagesManagementHandler:
|
||||
async def delete_example_image(self, request: web.Request) -> web.StreamResponse:
|
||||
return await self._processor.delete_custom_image(request)
|
||||
|
||||
async def set_example_image_nsfw_level(self, request: web.Request) -> web.StreamResponse:
|
||||
return await self._processor.set_example_image_nsfw_level(request)
|
||||
|
||||
async def cleanup_example_image_folders(self, request: web.Request) -> web.StreamResponse:
|
||||
result = await self._cleanup_service.cleanup_example_image_folders()
|
||||
|
||||
@@ -149,9 +172,12 @@ class ExampleImagesHandlerSet:
|
||||
"get_example_images_status": self.download.get_example_images_status,
|
||||
"pause_example_images": self.download.pause_example_images,
|
||||
"resume_example_images": self.download.resume_example_images,
|
||||
"stop_example_images": self.download.stop_example_images,
|
||||
"force_download_example_images": self.download.force_download_example_images,
|
||||
"check_example_images_needed": self.download.check_example_images_needed,
|
||||
"import_example_images": self.management.import_example_images,
|
||||
"delete_example_image": self.management.delete_example_image,
|
||||
"set_example_image_nsfw_level": self.management.set_example_image_nsfw_level,
|
||||
"cleanup_example_image_folders": self.management.cleanup_example_image_folders,
|
||||
"open_example_images_folder": self.files.open_example_images_folder,
|
||||
"get_example_image_files": self.files.get_example_image_files,
|
||||
|
||||
1556
py/routes/handlers/misc_handlers.py
Normal file
1556
py/routes/handlers/misc_handlers.py
Normal file
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
55
py/routes/handlers/preview_handlers.py
Normal file
55
py/routes/handlers/preview_handlers.py
Normal file
@@ -0,0 +1,55 @@
|
||||
"""Handlers responsible for serving preview assets dynamically."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import urllib.parse
|
||||
from pathlib import Path
|
||||
|
||||
from aiohttp import web
|
||||
|
||||
from ...config import config as global_config
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class PreviewHandler:
|
||||
"""Serve preview assets for the active library at request time."""
|
||||
|
||||
def __init__(self, *, config=global_config) -> None:
|
||||
self._config = config
|
||||
|
||||
async def serve_preview(self, request: web.Request) -> web.StreamResponse:
|
||||
"""Return the preview file referenced by the encoded ``path`` query."""
|
||||
|
||||
raw_path = request.query.get("path", "")
|
||||
if not raw_path:
|
||||
raise web.HTTPBadRequest(text="Missing 'path' query parameter")
|
||||
|
||||
try:
|
||||
decoded_path = urllib.parse.unquote(raw_path)
|
||||
except Exception as exc: # pragma: no cover - defensive guard
|
||||
logger.debug("Failed to decode preview path %s: %s", raw_path, exc)
|
||||
raise web.HTTPBadRequest(text="Invalid preview path encoding") from exc
|
||||
|
||||
normalized = decoded_path.replace("\\", "/")
|
||||
|
||||
if not self._config.is_preview_path_allowed(normalized):
|
||||
raise web.HTTPForbidden(text="Preview path is not within an allowed directory")
|
||||
|
||||
candidate = Path(normalized)
|
||||
try:
|
||||
resolved = candidate.expanduser().resolve(strict=False)
|
||||
except Exception as exc:
|
||||
logger.debug("Failed to resolve preview path %s: %s", normalized, exc)
|
||||
raise web.HTTPBadRequest(text="Unable to resolve preview path") from exc
|
||||
|
||||
if not resolved.is_file():
|
||||
logger.debug("Preview file not found at %s", str(resolved))
|
||||
raise web.HTTPNotFound(text="Preview file not found")
|
||||
|
||||
# aiohttp's FileResponse handles range requests and content headers for us.
|
||||
return web.FileResponse(path=resolved, chunk_size=256 * 1024)
|
||||
|
||||
|
||||
__all__ = ["PreviewHandler"]
|
||||
@@ -4,8 +4,11 @@ from __future__ import annotations
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import re
|
||||
import asyncio
|
||||
import tempfile
|
||||
from dataclasses import dataclass
|
||||
from typing import Any, Awaitable, Callable, Dict, Mapping, Optional
|
||||
from typing import Any, Awaitable, Callable, Dict, List, Mapping, Optional
|
||||
|
||||
from aiohttp import web
|
||||
|
||||
@@ -20,6 +23,12 @@ from ...services.recipes import (
|
||||
RecipeSharingService,
|
||||
RecipeValidationError,
|
||||
)
|
||||
from ...services.metadata_service import get_default_metadata_provider
|
||||
from ...utils.civitai_utils import rewrite_preview_url
|
||||
from ...utils.exif_utils import ExifUtils
|
||||
from ...recipes.merger import GenParamsMerger
|
||||
from ...recipes.enrichment import RecipeEnricher
|
||||
from ...services.websocket_manager import ws_manager as default_ws_manager
|
||||
|
||||
Logger = logging.Logger
|
||||
EnsureDependenciesCallable = Callable[[], Awaitable[None]]
|
||||
@@ -45,22 +54,33 @@ class RecipeHandlerSet:
|
||||
"render_page": self.page_view.render_page,
|
||||
"list_recipes": self.listing.list_recipes,
|
||||
"get_recipe": self.listing.get_recipe,
|
||||
"import_remote_recipe": self.management.import_remote_recipe,
|
||||
"analyze_uploaded_image": self.analysis.analyze_uploaded_image,
|
||||
"analyze_local_image": self.analysis.analyze_local_image,
|
||||
"save_recipe": self.management.save_recipe,
|
||||
"delete_recipe": self.management.delete_recipe,
|
||||
"get_top_tags": self.query.get_top_tags,
|
||||
"get_base_models": self.query.get_base_models,
|
||||
"get_roots": self.query.get_roots,
|
||||
"get_folders": self.query.get_folders,
|
||||
"get_folder_tree": self.query.get_folder_tree,
|
||||
"get_unified_folder_tree": self.query.get_unified_folder_tree,
|
||||
"share_recipe": self.sharing.share_recipe,
|
||||
"download_shared_recipe": self.sharing.download_shared_recipe,
|
||||
"get_recipe_syntax": self.query.get_recipe_syntax,
|
||||
"update_recipe": self.management.update_recipe,
|
||||
"reconnect_lora": self.management.reconnect_lora,
|
||||
"find_duplicates": self.query.find_duplicates,
|
||||
"move_recipes_bulk": self.management.move_recipes_bulk,
|
||||
"bulk_delete": self.management.bulk_delete,
|
||||
"save_recipe_from_widget": self.management.save_recipe_from_widget,
|
||||
"get_recipes_for_lora": self.query.get_recipes_for_lora,
|
||||
"scan_recipes": self.query.scan_recipes,
|
||||
"move_recipe": self.management.move_recipe,
|
||||
"repair_recipes": self.management.repair_recipes,
|
||||
"cancel_repair": self.management.cancel_repair,
|
||||
"repair_recipe": self.management.repair_recipe,
|
||||
"get_repair_progress": self.management.get_repair_progress,
|
||||
}
|
||||
|
||||
|
||||
@@ -144,22 +164,45 @@ class RecipeListingHandler:
|
||||
page_size = int(request.query.get("page_size", "20"))
|
||||
sort_by = request.query.get("sort_by", "date")
|
||||
search = request.query.get("search")
|
||||
folder = request.query.get("folder")
|
||||
recursive = request.query.get("recursive", "true").lower() == "true"
|
||||
|
||||
search_options = {
|
||||
"title": request.query.get("search_title", "true").lower() == "true",
|
||||
"tags": request.query.get("search_tags", "true").lower() == "true",
|
||||
"lora_name": request.query.get("search_lora_name", "true").lower() == "true",
|
||||
"lora_model": request.query.get("search_lora_model", "true").lower() == "true",
|
||||
"prompt": request.query.get("search_prompt", "true").lower() == "true",
|
||||
}
|
||||
|
||||
filters: Dict[str, list[str]] = {}
|
||||
filters: Dict[str, Any] = {}
|
||||
base_models = request.query.get("base_models")
|
||||
if base_models:
|
||||
filters["base_model"] = base_models.split(",")
|
||||
|
||||
tags = request.query.get("tags")
|
||||
if tags:
|
||||
filters["tags"] = tags.split(",")
|
||||
if request.query.get("favorite", "false").lower() == "true":
|
||||
filters["favorite"] = True
|
||||
|
||||
tag_filters: Dict[str, str] = {}
|
||||
legacy_tags = request.query.get("tags")
|
||||
if legacy_tags:
|
||||
for tag in legacy_tags.split(","):
|
||||
tag = tag.strip()
|
||||
if tag:
|
||||
tag_filters[tag] = "include"
|
||||
|
||||
include_tags = request.query.getall("tag_include", [])
|
||||
for tag in include_tags:
|
||||
if tag:
|
||||
tag_filters[tag] = "include"
|
||||
|
||||
exclude_tags = request.query.getall("tag_exclude", [])
|
||||
for tag in exclude_tags:
|
||||
if tag:
|
||||
tag_filters[tag] = "exclude"
|
||||
|
||||
if tag_filters:
|
||||
filters["tags"] = tag_filters
|
||||
|
||||
lora_hash = request.query.get("lora_hash")
|
||||
|
||||
@@ -171,6 +214,8 @@ class RecipeListingHandler:
|
||||
filters=filters,
|
||||
search_options=search_options,
|
||||
lora_hash=lora_hash,
|
||||
folder=folder,
|
||||
recursive=recursive,
|
||||
)
|
||||
|
||||
for item in result.get("items", []):
|
||||
@@ -206,18 +251,16 @@ class RecipeListingHandler:
|
||||
|
||||
def format_recipe_file_url(self, file_path: str) -> str:
|
||||
try:
|
||||
recipes_dir = os.path.join(config.loras_roots[0], "recipes").replace(os.sep, "/")
|
||||
normalized_path = file_path.replace(os.sep, "/")
|
||||
if normalized_path.startswith(recipes_dir):
|
||||
relative_path = os.path.relpath(file_path, config.loras_roots[0]).replace(os.sep, "/")
|
||||
return f"/loras_static/root1/preview/{relative_path}"
|
||||
|
||||
file_name = os.path.basename(file_path)
|
||||
return f"/loras_static/root1/preview/recipes/{file_name}"
|
||||
normalized_path = os.path.normpath(file_path)
|
||||
static_url = config.get_preview_static_url(normalized_path)
|
||||
if static_url:
|
||||
return static_url
|
||||
except Exception as exc: # pragma: no cover - logging path
|
||||
self._logger.error("Error formatting recipe file URL: %s", exc, exc_info=True)
|
||||
return "/loras_static/images/no-preview.png"
|
||||
|
||||
return "/loras_static/images/no-preview.png"
|
||||
|
||||
|
||||
class RecipeQueryHandler:
|
||||
"""Provide read-only insights on recipe data."""
|
||||
@@ -279,6 +322,58 @@ class RecipeQueryHandler:
|
||||
self._logger.error("Error retrieving base models: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def get_roots(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
raise RuntimeError("Recipe scanner unavailable")
|
||||
|
||||
roots = [recipe_scanner.recipes_dir] if recipe_scanner.recipes_dir else []
|
||||
return web.json_response({"success": True, "roots": roots})
|
||||
except Exception as exc:
|
||||
self._logger.error("Error retrieving recipe roots: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def get_folders(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
raise RuntimeError("Recipe scanner unavailable")
|
||||
|
||||
folders = await recipe_scanner.get_folders()
|
||||
return web.json_response({"success": True, "folders": folders})
|
||||
except Exception as exc:
|
||||
self._logger.error("Error retrieving recipe folders: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def get_folder_tree(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
raise RuntimeError("Recipe scanner unavailable")
|
||||
|
||||
folder_tree = await recipe_scanner.get_folder_tree()
|
||||
return web.json_response({"success": True, "tree": folder_tree})
|
||||
except Exception as exc:
|
||||
self._logger.error("Error retrieving recipe folder tree: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def get_unified_folder_tree(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
raise RuntimeError("Recipe scanner unavailable")
|
||||
|
||||
folder_tree = await recipe_scanner.get_folder_tree()
|
||||
return web.json_response({"success": True, "tree": folder_tree})
|
||||
except Exception as exc:
|
||||
self._logger.error("Error retrieving unified recipe folder tree: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def get_recipes_for_lora(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
@@ -317,10 +412,11 @@ class RecipeQueryHandler:
|
||||
if recipe_scanner is None:
|
||||
raise RuntimeError("Recipe scanner unavailable")
|
||||
|
||||
duplicate_groups = await recipe_scanner.find_all_duplicate_recipes()
|
||||
fingerprint_groups = await recipe_scanner.find_all_duplicate_recipes()
|
||||
url_groups = await recipe_scanner.find_duplicate_recipes_by_source()
|
||||
response_data = []
|
||||
|
||||
for fingerprint, recipe_ids in duplicate_groups.items():
|
||||
for fingerprint, recipe_ids in fingerprint_groups.items():
|
||||
if len(recipe_ids) <= 1:
|
||||
continue
|
||||
|
||||
@@ -344,12 +440,44 @@ class RecipeQueryHandler:
|
||||
recipes.sort(key=lambda entry: entry.get("modified", 0), reverse=True)
|
||||
response_data.append(
|
||||
{
|
||||
"type": "fingerprint",
|
||||
"fingerprint": fingerprint,
|
||||
"count": len(recipes),
|
||||
"recipes": recipes,
|
||||
}
|
||||
)
|
||||
|
||||
for url, recipe_ids in url_groups.items():
|
||||
if len(recipe_ids) <= 1:
|
||||
continue
|
||||
|
||||
recipes = []
|
||||
for recipe_id in recipe_ids:
|
||||
recipe = await recipe_scanner.get_recipe_by_id(recipe_id)
|
||||
if recipe:
|
||||
recipes.append(
|
||||
{
|
||||
"id": recipe.get("id"),
|
||||
"title": recipe.get("title"),
|
||||
"file_url": recipe.get("file_url")
|
||||
or self._format_recipe_file_url(recipe.get("file_path", "")),
|
||||
"modified": recipe.get("modified"),
|
||||
"created_date": recipe.get("created_date"),
|
||||
"lora_count": len(recipe.get("loras", [])),
|
||||
}
|
||||
)
|
||||
|
||||
if len(recipes) >= 2:
|
||||
recipes.sort(key=lambda entry: entry.get("modified", 0), reverse=True)
|
||||
response_data.append(
|
||||
{
|
||||
"type": "source_url",
|
||||
"fingerprint": url,
|
||||
"count": len(recipes),
|
||||
"recipes": recipes,
|
||||
}
|
||||
)
|
||||
|
||||
response_data.sort(key=lambda entry: entry["count"], reverse=True)
|
||||
return web.json_response({"success": True, "duplicate_groups": response_data})
|
||||
except Exception as exc:
|
||||
@@ -389,12 +517,18 @@ class RecipeManagementHandler:
|
||||
logger: Logger,
|
||||
persistence_service: RecipePersistenceService,
|
||||
analysis_service: RecipeAnalysisService,
|
||||
downloader_factory,
|
||||
civitai_client_getter: CivitaiClientGetter,
|
||||
ws_manager=default_ws_manager,
|
||||
) -> None:
|
||||
self._ensure_dependencies_ready = ensure_dependencies_ready
|
||||
self._recipe_scanner_getter = recipe_scanner_getter
|
||||
self._logger = logger
|
||||
self._persistence_service = persistence_service
|
||||
self._analysis_service = analysis_service
|
||||
self._downloader_factory = downloader_factory
|
||||
self._civitai_client_getter = civitai_client_getter
|
||||
self._ws_manager = ws_manager
|
||||
|
||||
async def save_recipe(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
@@ -413,6 +547,7 @@ class RecipeManagementHandler:
|
||||
name=payload["name"],
|
||||
tags=payload["tags"],
|
||||
metadata=payload["metadata"],
|
||||
extension=payload.get("extension"),
|
||||
)
|
||||
return web.json_response(result.payload, status=result.status)
|
||||
except RecipeValidationError as exc:
|
||||
@@ -421,6 +556,215 @@ class RecipeManagementHandler:
|
||||
self._logger.error("Error saving recipe: %s", exc, exc_info=True)
|
||||
return web.json_response({"error": str(exc)}, status=500)
|
||||
|
||||
async def repair_recipes(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
return web.json_response({"success": False, "error": "Recipe scanner unavailable"}, status=503)
|
||||
|
||||
# Check if already running
|
||||
if self._ws_manager.is_recipe_repair_running():
|
||||
return web.json_response({"success": False, "error": "Recipe repair already in progress"}, status=409)
|
||||
|
||||
recipe_scanner.reset_cancellation()
|
||||
|
||||
async def progress_callback(data):
|
||||
await self._ws_manager.broadcast_recipe_repair_progress(data)
|
||||
|
||||
# Run in background to avoid timeout
|
||||
async def run_repair():
|
||||
try:
|
||||
await recipe_scanner.repair_all_recipes(
|
||||
progress_callback=progress_callback
|
||||
)
|
||||
except Exception as e:
|
||||
self._logger.error(f"Error in recipe repair task: {e}", exc_info=True)
|
||||
await self._ws_manager.broadcast_recipe_repair_progress({
|
||||
"status": "error",
|
||||
"error": str(e)
|
||||
})
|
||||
finally:
|
||||
# Keep the final status for a while so the UI can see it
|
||||
await asyncio.sleep(5)
|
||||
# Don't cleanup if it was cancelled, let the UI see the cancelled state for a bit?
|
||||
# Actually cleanup_recipe_repair_progress is fine as long as we waited enough.
|
||||
self._ws_manager.cleanup_recipe_repair_progress()
|
||||
|
||||
asyncio.create_task(run_repair())
|
||||
|
||||
return web.json_response({"success": True, "message": "Recipe repair started"})
|
||||
except Exception as exc:
|
||||
self._logger.error("Error starting recipe repair: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def cancel_repair(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
return web.json_response({"success": False, "error": "Recipe scanner unavailable"}, status=503)
|
||||
|
||||
recipe_scanner.cancel_task()
|
||||
return web.json_response({"success": True, "message": "Cancellation requested"})
|
||||
except Exception as exc:
|
||||
self._logger.error("Error cancelling recipe repair: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def repair_recipe(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
return web.json_response({"success": False, "error": "Recipe scanner unavailable"}, status=503)
|
||||
|
||||
recipe_id = request.match_info["recipe_id"]
|
||||
result = await recipe_scanner.repair_recipe_by_id(recipe_id)
|
||||
return web.json_response(result)
|
||||
except RecipeNotFoundError as exc:
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=404)
|
||||
except Exception as exc:
|
||||
self._logger.error("Error repairing single recipe: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def get_repair_progress(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
progress = self._ws_manager.get_recipe_repair_progress()
|
||||
if progress:
|
||||
return web.json_response({"success": True, "progress": progress})
|
||||
return web.json_response({"success": False, "message": "No repair in progress"}, status=404)
|
||||
except Exception as exc:
|
||||
self._logger.error("Error getting repair progress: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
|
||||
async def import_remote_recipe(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
raise RuntimeError("Recipe scanner unavailable")
|
||||
|
||||
# 1. Parse Parameters
|
||||
params = request.rel_url.query
|
||||
image_url = params.get("image_url")
|
||||
name = params.get("name")
|
||||
resources_raw = params.get("resources")
|
||||
|
||||
if not image_url:
|
||||
raise RecipeValidationError("Missing required field: image_url")
|
||||
if not name:
|
||||
raise RecipeValidationError("Missing required field: name")
|
||||
if not resources_raw:
|
||||
raise RecipeValidationError("Missing required field: resources")
|
||||
|
||||
checkpoint_entry, lora_entries = self._parse_resources_payload(resources_raw)
|
||||
gen_params_request = self._parse_gen_params(params.get("gen_params"))
|
||||
|
||||
# 2. Initial Metadata Construction
|
||||
metadata: Dict[str, Any] = {
|
||||
"base_model": params.get("base_model", "") or "",
|
||||
"loras": lora_entries,
|
||||
"gen_params": gen_params_request or {},
|
||||
"source_url": image_url
|
||||
}
|
||||
|
||||
source_path = params.get("source_path")
|
||||
if source_path:
|
||||
metadata["source_path"] = source_path
|
||||
|
||||
# Checkpoint handling
|
||||
if checkpoint_entry:
|
||||
metadata["checkpoint"] = checkpoint_entry
|
||||
# Ensure checkpoint is also in gen_params for consistency if needed by enricher?
|
||||
# Actually enricher looks at metadata['checkpoint'], so this is fine.
|
||||
|
||||
# Try to resolve base model from checkpoint if not explicitly provided
|
||||
if not metadata["base_model"]:
|
||||
base_model_from_metadata = await self._resolve_base_model_from_checkpoint(checkpoint_entry)
|
||||
if base_model_from_metadata:
|
||||
metadata["base_model"] = base_model_from_metadata
|
||||
|
||||
tags = self._parse_tags(params.get("tags"))
|
||||
|
||||
# 3. Download Image
|
||||
image_bytes, extension, civitai_meta_from_download = await self._download_remote_media(image_url)
|
||||
|
||||
# 4. Extract Embedded Metadata
|
||||
# Note: We still extract this here because Enricher currently expects 'gen_params' to already be populated
|
||||
# with embedded data if we want it to merge it.
|
||||
# However, logic in Enricher merges: request > civitai > embedded.
|
||||
# So we should gather embedded params and put them into the recipe's gen_params (as initial state)
|
||||
# OR pass them to enricher to handle?
|
||||
# The interface of Enricher.enrich_recipe takes `recipe` (with gen_params) and `request_params`.
|
||||
# So let's extract embedded and put it into recipe['gen_params'] but careful not to overwrite request params.
|
||||
# Actually, `GenParamsMerger` which `Enricher` uses handles 3 layers.
|
||||
# But `Enricher` interface is: recipe['gen_params'] (as embedded) + request_params + civitai (fetched internally).
|
||||
# Wait, `Enricher` fetches Civitai info internally based on URL.
|
||||
# `civitai_meta_from_download` is returned by `_download_remote_media` which might be useful if URL didn't have ID.
|
||||
|
||||
# Let's extract embedded metadata first
|
||||
embedded_gen_params = {}
|
||||
try:
|
||||
with tempfile.NamedTemporaryFile(suffix=extension, delete=False) as temp_img:
|
||||
temp_img.write(image_bytes)
|
||||
temp_img_path = temp_img.name
|
||||
|
||||
try:
|
||||
raw_embedded = ExifUtils.extract_image_metadata(temp_img_path)
|
||||
if raw_embedded:
|
||||
parser = self._analysis_service._recipe_parser_factory.create_parser(raw_embedded)
|
||||
if parser:
|
||||
parsed_embedded = await parser.parse_metadata(raw_embedded, recipe_scanner=recipe_scanner)
|
||||
if parsed_embedded and "gen_params" in parsed_embedded:
|
||||
embedded_gen_params = parsed_embedded["gen_params"]
|
||||
else:
|
||||
embedded_gen_params = {"raw_metadata": raw_embedded}
|
||||
finally:
|
||||
if os.path.exists(temp_img_path):
|
||||
os.unlink(temp_img_path)
|
||||
except Exception as exc:
|
||||
self._logger.warning("Failed to extract embedded metadata during import: %s", exc)
|
||||
|
||||
# Pre-populate gen_params with embedded data so Enricher treats it as the "base" layer
|
||||
if embedded_gen_params:
|
||||
# Merge embedded into existing gen_params (which currently only has request params if any)
|
||||
# But wait, we want request params to override everything.
|
||||
# So we should set recipe['gen_params'] = embedded, and pass request params to enricher.
|
||||
metadata["gen_params"] = embedded_gen_params
|
||||
|
||||
# 5. Enrich with unified logic
|
||||
# This will fetch Civitai info (if URL matches) and merge: request > civitai > embedded
|
||||
civitai_client = self._civitai_client_getter()
|
||||
await RecipeEnricher.enrich_recipe(
|
||||
recipe=metadata,
|
||||
civitai_client=civitai_client,
|
||||
request_params=gen_params_request # Pass explicit request params here to override
|
||||
)
|
||||
|
||||
# If we got civitai_meta from download but Enricher didn't fetch it (e.g. not a civitai URL or failed),
|
||||
# we might want to manually merge it?
|
||||
# But usually `import_remote_recipe` is used with Civitai URLs.
|
||||
# For now, relying on Enricher's internal fetch is consistent with repair.
|
||||
|
||||
result = await self._persistence_service.save_recipe(
|
||||
recipe_scanner=recipe_scanner,
|
||||
image_bytes=image_bytes,
|
||||
image_base64=None,
|
||||
name=name,
|
||||
tags=tags,
|
||||
metadata=metadata,
|
||||
extension=extension,
|
||||
)
|
||||
return web.json_response(result.payload, status=result.status)
|
||||
except RecipeValidationError as exc:
|
||||
return web.json_response({"error": str(exc)}, status=400)
|
||||
except RecipeDownloadError as exc:
|
||||
return web.json_response({"error": str(exc)}, status=400)
|
||||
except Exception as exc:
|
||||
self._logger.error("Error importing recipe from remote source: %s", exc, exc_info=True)
|
||||
return web.json_response({"error": str(exc)}, status=500)
|
||||
|
||||
async def delete_recipe(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
@@ -460,6 +804,64 @@ class RecipeManagementHandler:
|
||||
self._logger.error("Error updating recipe: %s", exc, exc_info=True)
|
||||
return web.json_response({"error": str(exc)}, status=500)
|
||||
|
||||
async def move_recipe(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
raise RuntimeError("Recipe scanner unavailable")
|
||||
|
||||
data = await request.json()
|
||||
recipe_id = data.get("recipe_id")
|
||||
target_path = data.get("target_path")
|
||||
if not recipe_id or not target_path:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "recipe_id and target_path are required"}, status=400
|
||||
)
|
||||
|
||||
result = await self._persistence_service.move_recipe(
|
||||
recipe_scanner=recipe_scanner,
|
||||
recipe_id=str(recipe_id),
|
||||
target_path=str(target_path),
|
||||
)
|
||||
return web.json_response(result.payload, status=result.status)
|
||||
except RecipeValidationError as exc:
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=400)
|
||||
except RecipeNotFoundError as exc:
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=404)
|
||||
except Exception as exc:
|
||||
self._logger.error("Error moving recipe: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def move_recipes_bulk(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
recipe_scanner = self._recipe_scanner_getter()
|
||||
if recipe_scanner is None:
|
||||
raise RuntimeError("Recipe scanner unavailable")
|
||||
|
||||
data = await request.json()
|
||||
recipe_ids = data.get("recipe_ids") or []
|
||||
target_path = data.get("target_path")
|
||||
if not recipe_ids or not target_path:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "recipe_ids and target_path are required"}, status=400
|
||||
)
|
||||
|
||||
result = await self._persistence_service.move_recipes_bulk(
|
||||
recipe_scanner=recipe_scanner,
|
||||
recipe_ids=recipe_ids,
|
||||
target_path=str(target_path),
|
||||
)
|
||||
return web.json_response(result.payload, status=result.status)
|
||||
except RecipeValidationError as exc:
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=400)
|
||||
except RecipeNotFoundError as exc:
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=404)
|
||||
except Exception as exc:
|
||||
self._logger.error("Error moving recipes in bulk: %s", exc, exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(exc)}, status=500)
|
||||
|
||||
async def reconnect_lora(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
@@ -541,6 +943,7 @@ class RecipeManagementHandler:
|
||||
name: Optional[str] = None
|
||||
tags: list[str] = []
|
||||
metadata: Optional[Dict[str, Any]] = None
|
||||
extension: Optional[str] = None
|
||||
|
||||
while True:
|
||||
field = await reader.next()
|
||||
@@ -571,6 +974,8 @@ class RecipeManagementHandler:
|
||||
metadata = json.loads(metadata_text)
|
||||
except Exception:
|
||||
metadata = {}
|
||||
elif field.name == "extension":
|
||||
extension = await field.text()
|
||||
|
||||
return {
|
||||
"image_bytes": image_bytes,
|
||||
@@ -578,8 +983,161 @@ class RecipeManagementHandler:
|
||||
"name": name,
|
||||
"tags": tags,
|
||||
"metadata": metadata,
|
||||
"extension": extension,
|
||||
}
|
||||
|
||||
def _parse_tags(self, tag_text: Optional[str]) -> list[str]:
|
||||
if not tag_text:
|
||||
return []
|
||||
return [tag.strip() for tag in tag_text.split(",") if tag.strip()]
|
||||
|
||||
def _parse_gen_params(self, payload: Optional[str]) -> Optional[Dict[str, Any]]:
|
||||
if payload is None:
|
||||
return None
|
||||
if payload == "":
|
||||
return {}
|
||||
try:
|
||||
parsed = json.loads(payload)
|
||||
except json.JSONDecodeError as exc:
|
||||
raise RecipeValidationError(f"Invalid gen_params payload: {exc}") from exc
|
||||
if parsed is None:
|
||||
return {}
|
||||
if not isinstance(parsed, dict):
|
||||
raise RecipeValidationError("gen_params payload must be an object")
|
||||
return parsed
|
||||
|
||||
def _parse_resources_payload(self, payload_raw: str) -> tuple[Optional[Dict[str, Any]], List[Dict[str, Any]]]:
|
||||
try:
|
||||
payload = json.loads(payload_raw)
|
||||
except json.JSONDecodeError as exc:
|
||||
raise RecipeValidationError(f"Invalid resources payload: {exc}") from exc
|
||||
|
||||
if not isinstance(payload, list):
|
||||
raise RecipeValidationError("Resources payload must be a list")
|
||||
|
||||
checkpoint_entry: Optional[Dict[str, Any]] = None
|
||||
lora_entries: List[Dict[str, Any]] = []
|
||||
|
||||
for resource in payload:
|
||||
if not isinstance(resource, dict):
|
||||
continue
|
||||
resource_type = str(resource.get("type") or "").lower()
|
||||
if resource_type == "checkpoint":
|
||||
checkpoint_entry = self._build_checkpoint_entry(resource)
|
||||
elif resource_type in {"lora", "lycoris"}:
|
||||
lora_entries.append(self._build_lora_entry(resource))
|
||||
|
||||
return checkpoint_entry, lora_entries
|
||||
|
||||
def _build_checkpoint_entry(self, resource: Dict[str, Any]) -> Dict[str, Any]:
|
||||
return {
|
||||
"type": resource.get("type", "checkpoint"),
|
||||
"modelId": self._safe_int(resource.get("modelId")),
|
||||
"modelVersionId": self._safe_int(resource.get("modelVersionId")),
|
||||
"modelName": resource.get("modelName", ""),
|
||||
"modelVersionName": resource.get("modelVersionName", ""),
|
||||
}
|
||||
|
||||
def _build_lora_entry(self, resource: Dict[str, Any]) -> Dict[str, Any]:
|
||||
weight_raw = resource.get("weight", 1.0)
|
||||
try:
|
||||
weight = float(weight_raw)
|
||||
except (TypeError, ValueError):
|
||||
weight = 1.0
|
||||
return {
|
||||
"file_name": resource.get("modelName", ""),
|
||||
"weight": weight,
|
||||
"id": self._safe_int(resource.get("modelVersionId")),
|
||||
"name": resource.get("modelName", ""),
|
||||
"version": resource.get("modelVersionName", ""),
|
||||
"isDeleted": False,
|
||||
"exclude": False,
|
||||
}
|
||||
|
||||
async def _download_remote_media(self, image_url: str) -> tuple[bytes, str, Any]:
|
||||
civitai_client = self._civitai_client_getter()
|
||||
downloader = await self._downloader_factory()
|
||||
temp_path = None
|
||||
try:
|
||||
with tempfile.NamedTemporaryFile(delete=False) as temp_file:
|
||||
temp_path = temp_file.name
|
||||
download_url = image_url
|
||||
image_info = None
|
||||
civitai_match = re.match(r"https://civitai\.com/images/(\d+)", image_url)
|
||||
if civitai_match:
|
||||
if civitai_client is None:
|
||||
raise RecipeDownloadError("Civitai client unavailable for image download")
|
||||
image_info = await civitai_client.get_image_info(civitai_match.group(1))
|
||||
if not image_info:
|
||||
raise RecipeDownloadError("Failed to fetch image information from Civitai")
|
||||
|
||||
media_url = image_info.get("url")
|
||||
if not media_url:
|
||||
raise RecipeDownloadError("No image URL found in Civitai response")
|
||||
|
||||
# Use optimized preview URLs if possible
|
||||
media_type = image_info.get("type")
|
||||
rewritten_url, _ = rewrite_preview_url(media_url, media_type=media_type)
|
||||
if rewritten_url:
|
||||
download_url = rewritten_url
|
||||
else:
|
||||
download_url = media_url
|
||||
|
||||
success, result = await downloader.download_file(download_url, temp_path, use_auth=False)
|
||||
if not success:
|
||||
raise RecipeDownloadError(f"Failed to download image: {result}")
|
||||
|
||||
# Extract extension from URL
|
||||
url_path = download_url.split('?')[0].split('#')[0]
|
||||
extension = os.path.splitext(url_path)[1].lower()
|
||||
if not extension:
|
||||
extension = ".webp" # Default to webp if unknown
|
||||
|
||||
with open(temp_path, "rb") as file_obj:
|
||||
return file_obj.read(), extension, image_info.get("meta") if civitai_match and image_info else None
|
||||
except RecipeDownloadError:
|
||||
raise
|
||||
except RecipeValidationError:
|
||||
raise
|
||||
except Exception as exc: # pragma: no cover - defensive guard
|
||||
raise RecipeValidationError(f"Unable to download image: {exc}") from exc
|
||||
finally:
|
||||
if temp_path:
|
||||
try:
|
||||
os.unlink(temp_path)
|
||||
except FileNotFoundError:
|
||||
pass
|
||||
|
||||
|
||||
def _safe_int(self, value: Any) -> int:
|
||||
try:
|
||||
return int(value)
|
||||
except (TypeError, ValueError):
|
||||
return 0
|
||||
|
||||
async def _resolve_base_model_from_checkpoint(self, checkpoint_entry: Dict[str, Any]) -> str:
|
||||
version_id = self._safe_int(checkpoint_entry.get("modelVersionId"))
|
||||
|
||||
if not version_id:
|
||||
return ""
|
||||
|
||||
try:
|
||||
provider = await get_default_metadata_provider()
|
||||
if not provider:
|
||||
return ""
|
||||
|
||||
version_info = await provider.get_model_version_info(version_id)
|
||||
if isinstance(version_info, tuple):
|
||||
version_info = version_info[0]
|
||||
|
||||
if isinstance(version_info, dict):
|
||||
base_model = version_info.get("baseModel") or ""
|
||||
return str(base_model) if base_model is not None else ""
|
||||
except Exception as exc: # pragma: no cover - defensive logging
|
||||
self._logger.warning("Failed to resolve base model from checkpoint metadata: %s", exc)
|
||||
|
||||
return ""
|
||||
|
||||
|
||||
class RecipeAnalysisHandler:
|
||||
"""Analyze images to extract recipe metadata."""
|
||||
|
||||
@@ -12,234 +12,344 @@ from ..utils.utils import get_lora_info
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class LoraRoutes(BaseModelRoutes):
|
||||
"""LoRA-specific route controller"""
|
||||
|
||||
|
||||
def __init__(self):
|
||||
"""Initialize LoRA routes with LoRA service"""
|
||||
super().__init__()
|
||||
self.template_name = "loras.html"
|
||||
|
||||
|
||||
async def initialize_services(self):
|
||||
"""Initialize services from ServiceRegistry"""
|
||||
lora_scanner = await ServiceRegistry.get_lora_scanner()
|
||||
self.service = LoraService(lora_scanner)
|
||||
|
||||
update_service = await ServiceRegistry.get_model_update_service()
|
||||
self.service = LoraService(lora_scanner, update_service=update_service)
|
||||
self.set_model_update_service(update_service)
|
||||
|
||||
# Attach service dependencies
|
||||
self.attach_service(self.service)
|
||||
|
||||
|
||||
def setup_routes(self, app: web.Application):
|
||||
"""Setup LoRA routes"""
|
||||
# Schedule service initialization on app startup
|
||||
app.on_startup.append(lambda _: self.initialize_services())
|
||||
|
||||
# Setup common routes with 'loras' prefix (includes page route)
|
||||
super().setup_routes(app, 'loras')
|
||||
super().setup_routes(app, "loras")
|
||||
|
||||
def setup_specific_routes(self, registrar: ModelRouteRegistrar, prefix: str):
|
||||
"""Setup LoRA-specific routes"""
|
||||
# LoRA-specific query routes
|
||||
registrar.add_prefixed_route('GET', '/api/lm/{prefix}/letter-counts', prefix, self.get_letter_counts)
|
||||
registrar.add_prefixed_route('GET', '/api/lm/{prefix}/get-trigger-words', prefix, self.get_lora_trigger_words)
|
||||
registrar.add_prefixed_route('GET', '/api/lm/{prefix}/usage-tips-by-path', prefix, self.get_lora_usage_tips_by_path)
|
||||
registrar.add_prefixed_route(
|
||||
"GET", "/api/lm/{prefix}/letter-counts", prefix, self.get_letter_counts
|
||||
)
|
||||
registrar.add_prefixed_route(
|
||||
"GET",
|
||||
"/api/lm/{prefix}/get-trigger-words",
|
||||
prefix,
|
||||
self.get_lora_trigger_words,
|
||||
)
|
||||
registrar.add_prefixed_route(
|
||||
"GET",
|
||||
"/api/lm/{prefix}/usage-tips-by-path",
|
||||
prefix,
|
||||
self.get_lora_usage_tips_by_path,
|
||||
)
|
||||
|
||||
# Randomizer routes
|
||||
registrar.add_prefixed_route(
|
||||
"POST", "/api/lm/{prefix}/random-sample", prefix, self.get_random_loras
|
||||
)
|
||||
|
||||
# Cycler routes
|
||||
registrar.add_prefixed_route(
|
||||
"POST", "/api/lm/{prefix}/cycler-list", prefix, self.get_cycler_list
|
||||
)
|
||||
|
||||
# ComfyUI integration
|
||||
registrar.add_prefixed_route('POST', '/api/lm/{prefix}/get_trigger_words', prefix, self.get_trigger_words)
|
||||
|
||||
registrar.add_prefixed_route(
|
||||
"POST", "/api/lm/{prefix}/get_trigger_words", prefix, self.get_trigger_words
|
||||
)
|
||||
|
||||
def _parse_specific_params(self, request: web.Request) -> Dict:
|
||||
"""Parse LoRA-specific parameters"""
|
||||
params = {}
|
||||
|
||||
|
||||
# LoRA-specific parameters
|
||||
if 'first_letter' in request.query:
|
||||
params['first_letter'] = request.query.get('first_letter')
|
||||
|
||||
if "first_letter" in request.query:
|
||||
params["first_letter"] = request.query.get("first_letter")
|
||||
|
||||
# Handle fuzzy search parameter name variation
|
||||
if request.query.get('fuzzy') == 'true':
|
||||
params['fuzzy_search'] = True
|
||||
|
||||
if request.query.get("fuzzy") == "true":
|
||||
params["fuzzy_search"] = True
|
||||
|
||||
# Handle additional filter parameters for LoRAs
|
||||
if 'lora_hash' in request.query:
|
||||
if not params.get('hash_filters'):
|
||||
params['hash_filters'] = {}
|
||||
params['hash_filters']['single_hash'] = request.query['lora_hash'].lower()
|
||||
elif 'lora_hashes' in request.query:
|
||||
if not params.get('hash_filters'):
|
||||
params['hash_filters'] = {}
|
||||
params['hash_filters']['multiple_hashes'] = [h.lower() for h in request.query['lora_hashes'].split(',')]
|
||||
|
||||
if "lora_hash" in request.query:
|
||||
if not params.get("hash_filters"):
|
||||
params["hash_filters"] = {}
|
||||
params["hash_filters"]["single_hash"] = request.query["lora_hash"].lower()
|
||||
elif "lora_hashes" in request.query:
|
||||
if not params.get("hash_filters"):
|
||||
params["hash_filters"] = {}
|
||||
params["hash_filters"]["multiple_hashes"] = [
|
||||
h.lower() for h in request.query["lora_hashes"].split(",")
|
||||
]
|
||||
|
||||
return params
|
||||
|
||||
|
||||
def _validate_civitai_model_type(self, model_type: str) -> bool:
|
||||
"""Validate CivitAI model type for LoRA"""
|
||||
from ..utils.constants import VALID_LORA_TYPES
|
||||
|
||||
return model_type.lower() in VALID_LORA_TYPES
|
||||
|
||||
|
||||
def _get_expected_model_types(self) -> str:
|
||||
"""Get expected model types string for error messages"""
|
||||
return "LORA, LoCon, or DORA"
|
||||
|
||||
|
||||
# LoRA-specific route handlers
|
||||
async def get_letter_counts(self, request: web.Request) -> web.Response:
|
||||
"""Get count of LoRAs for each letter of the alphabet"""
|
||||
try:
|
||||
letter_counts = await self.service.get_letter_counts()
|
||||
return web.json_response({
|
||||
'success': True,
|
||||
'letter_counts': letter_counts
|
||||
})
|
||||
return web.json_response({"success": True, "letter_counts": letter_counts})
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting letter counts: {e}")
|
||||
return web.json_response({
|
||||
'success': False,
|
||||
'error': str(e)
|
||||
}, status=500)
|
||||
|
||||
return web.json_response({"success": False, "error": str(e)}, status=500)
|
||||
|
||||
async def get_lora_notes(self, request: web.Request) -> web.Response:
|
||||
"""Get notes for a specific LoRA file"""
|
||||
try:
|
||||
lora_name = request.query.get('name')
|
||||
lora_name = request.query.get("name")
|
||||
if not lora_name:
|
||||
return web.Response(text='Lora file name is required', status=400)
|
||||
|
||||
return web.Response(text="Lora file name is required", status=400)
|
||||
|
||||
notes = await self.service.get_lora_notes(lora_name)
|
||||
if notes is not None:
|
||||
return web.json_response({
|
||||
'success': True,
|
||||
'notes': notes
|
||||
})
|
||||
return web.json_response({"success": True, "notes": notes})
|
||||
else:
|
||||
return web.json_response({
|
||||
'success': False,
|
||||
'error': 'LoRA not found in cache'
|
||||
}, status=404)
|
||||
|
||||
return web.json_response(
|
||||
{"success": False, "error": "LoRA not found in cache"}, status=404
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting lora notes: {e}", exc_info=True)
|
||||
return web.json_response({
|
||||
'success': False,
|
||||
'error': str(e)
|
||||
}, status=500)
|
||||
|
||||
return web.json_response({"success": False, "error": str(e)}, status=500)
|
||||
|
||||
async def get_lora_trigger_words(self, request: web.Request) -> web.Response:
|
||||
"""Get trigger words for a specific LoRA file"""
|
||||
try:
|
||||
lora_name = request.query.get('name')
|
||||
lora_name = request.query.get("name")
|
||||
if not lora_name:
|
||||
return web.Response(text='Lora file name is required', status=400)
|
||||
|
||||
return web.Response(text="Lora file name is required", status=400)
|
||||
|
||||
trigger_words = await self.service.get_lora_trigger_words(lora_name)
|
||||
return web.json_response({
|
||||
'success': True,
|
||||
'trigger_words': trigger_words
|
||||
})
|
||||
|
||||
return web.json_response({"success": True, "trigger_words": trigger_words})
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting lora trigger words: {e}", exc_info=True)
|
||||
return web.json_response({
|
||||
'success': False,
|
||||
'error': str(e)
|
||||
}, status=500)
|
||||
|
||||
return web.json_response({"success": False, "error": str(e)}, status=500)
|
||||
|
||||
async def get_lora_usage_tips_by_path(self, request: web.Request) -> web.Response:
|
||||
"""Get usage tips for a LoRA by its relative path"""
|
||||
try:
|
||||
relative_path = request.query.get('relative_path')
|
||||
relative_path = request.query.get("relative_path")
|
||||
if not relative_path:
|
||||
return web.Response(text='Relative path is required', status=400)
|
||||
|
||||
usage_tips = await self.service.get_lora_usage_tips_by_relative_path(relative_path)
|
||||
return web.json_response({
|
||||
'success': True,
|
||||
'usage_tips': usage_tips or ''
|
||||
})
|
||||
|
||||
return web.Response(text="Relative path is required", status=400)
|
||||
|
||||
usage_tips = await self.service.get_lora_usage_tips_by_relative_path(
|
||||
relative_path
|
||||
)
|
||||
return web.json_response({"success": True, "usage_tips": usage_tips or ""})
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting lora usage tips by path: {e}", exc_info=True)
|
||||
return web.json_response({
|
||||
'success': False,
|
||||
'error': str(e)
|
||||
}, status=500)
|
||||
|
||||
return web.json_response({"success": False, "error": str(e)}, status=500)
|
||||
|
||||
async def get_lora_preview_url(self, request: web.Request) -> web.Response:
|
||||
"""Get the static preview URL for a LoRA file"""
|
||||
try:
|
||||
lora_name = request.query.get('name')
|
||||
lora_name = request.query.get("name")
|
||||
if not lora_name:
|
||||
return web.Response(text='Lora file name is required', status=400)
|
||||
|
||||
return web.Response(text="Lora file name is required", status=400)
|
||||
|
||||
preview_url = await self.service.get_lora_preview_url(lora_name)
|
||||
if preview_url:
|
||||
return web.json_response({
|
||||
'success': True,
|
||||
'preview_url': preview_url
|
||||
})
|
||||
return web.json_response({"success": True, "preview_url": preview_url})
|
||||
else:
|
||||
return web.json_response({
|
||||
'success': False,
|
||||
'error': 'No preview URL found for the specified lora'
|
||||
}, status=404)
|
||||
|
||||
return web.json_response(
|
||||
{
|
||||
"success": False,
|
||||
"error": "No preview URL found for the specified lora",
|
||||
},
|
||||
status=404,
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting lora preview URL: {e}", exc_info=True)
|
||||
return web.json_response({
|
||||
'success': False,
|
||||
'error': str(e)
|
||||
}, status=500)
|
||||
|
||||
return web.json_response({"success": False, "error": str(e)}, status=500)
|
||||
|
||||
async def get_lora_civitai_url(self, request: web.Request) -> web.Response:
|
||||
"""Get the Civitai URL for a LoRA file"""
|
||||
try:
|
||||
lora_name = request.query.get('name')
|
||||
lora_name = request.query.get("name")
|
||||
if not lora_name:
|
||||
return web.Response(text='Lora file name is required', status=400)
|
||||
|
||||
return web.Response(text="Lora file name is required", status=400)
|
||||
|
||||
result = await self.service.get_lora_civitai_url(lora_name)
|
||||
if result['civitai_url']:
|
||||
return web.json_response({
|
||||
'success': True,
|
||||
**result
|
||||
})
|
||||
if result["civitai_url"]:
|
||||
return web.json_response({"success": True, **result})
|
||||
else:
|
||||
return web.json_response({
|
||||
'success': False,
|
||||
'error': 'No Civitai data found for the specified lora'
|
||||
}, status=404)
|
||||
|
||||
return web.json_response(
|
||||
{
|
||||
"success": False,
|
||||
"error": "No Civitai data found for the specified lora",
|
||||
},
|
||||
status=404,
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting lora Civitai URL: {e}", exc_info=True)
|
||||
return web.json_response({
|
||||
'success': False,
|
||||
'error': str(e)
|
||||
}, status=500)
|
||||
|
||||
return web.json_response({"success": False, "error": str(e)}, status=500)
|
||||
|
||||
async def get_random_loras(self, request: web.Request) -> web.Response:
|
||||
"""Get random LoRAs based on filters and strength ranges"""
|
||||
try:
|
||||
json_data = await request.json()
|
||||
|
||||
# Parse parameters
|
||||
count = json_data.get("count", 5)
|
||||
count_min = json_data.get("count_min")
|
||||
count_max = json_data.get("count_max")
|
||||
model_strength_min = float(json_data.get("model_strength_min", 0.0))
|
||||
model_strength_max = float(json_data.get("model_strength_max", 1.0))
|
||||
use_same_clip_strength = json_data.get("use_same_clip_strength", True)
|
||||
clip_strength_min = float(json_data.get("clip_strength_min", 0.0))
|
||||
clip_strength_max = float(json_data.get("clip_strength_max", 1.0))
|
||||
locked_loras = json_data.get("locked_loras", [])
|
||||
pool_config = json_data.get("pool_config")
|
||||
use_recommended_strength = json_data.get("use_recommended_strength", False)
|
||||
recommended_strength_scale_min = float(
|
||||
json_data.get("recommended_strength_scale_min", 0.5)
|
||||
)
|
||||
recommended_strength_scale_max = float(
|
||||
json_data.get("recommended_strength_scale_max", 1.0)
|
||||
)
|
||||
|
||||
# Determine target count
|
||||
if count_min is not None and count_max is not None:
|
||||
import random
|
||||
|
||||
target_count = random.randint(count_min, count_max)
|
||||
else:
|
||||
target_count = count
|
||||
|
||||
# Validate parameters
|
||||
if target_count < 1 or target_count > 100:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "Count must be between 1 and 100"},
|
||||
status=400,
|
||||
)
|
||||
|
||||
if model_strength_min < -10 or model_strength_max > 10:
|
||||
return web.json_response(
|
||||
{
|
||||
"success": False,
|
||||
"error": "Model strength must be between -10 and 10",
|
||||
},
|
||||
status=400,
|
||||
)
|
||||
|
||||
# Get random LoRAs from service
|
||||
result_loras = await self.service.get_random_loras(
|
||||
count=target_count,
|
||||
model_strength_min=model_strength_min,
|
||||
model_strength_max=model_strength_max,
|
||||
use_same_clip_strength=use_same_clip_strength,
|
||||
clip_strength_min=clip_strength_min,
|
||||
clip_strength_max=clip_strength_max,
|
||||
locked_loras=locked_loras,
|
||||
pool_config=pool_config,
|
||||
use_recommended_strength=use_recommended_strength,
|
||||
recommended_strength_scale_min=recommended_strength_scale_min,
|
||||
recommended_strength_scale_max=recommended_strength_scale_max,
|
||||
)
|
||||
|
||||
return web.json_response(
|
||||
{"success": True, "loras": result_loras, "count": len(result_loras)}
|
||||
)
|
||||
|
||||
except ValueError as e:
|
||||
logger.error(f"Invalid parameter for random LoRAs: {e}")
|
||||
return web.json_response({"success": False, "error": str(e)}, status=400)
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting random LoRAs: {e}", exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(e)}, status=500)
|
||||
|
||||
async def get_cycler_list(self, request: web.Request) -> web.Response:
|
||||
"""Get filtered and sorted LoRA list for cycler widget"""
|
||||
try:
|
||||
json_data = await request.json()
|
||||
|
||||
# Parse parameters
|
||||
pool_config = json_data.get("pool_config")
|
||||
sort_by = json_data.get("sort_by", "filename")
|
||||
|
||||
# Get cycler list from service
|
||||
lora_list = await self.service.get_cycler_list(
|
||||
pool_config=pool_config,
|
||||
sort_by=sort_by
|
||||
)
|
||||
|
||||
return web.json_response(
|
||||
{"success": True, "loras": lora_list, "count": len(lora_list)}
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting cycler list: {e}", exc_info=True)
|
||||
return web.json_response({"success": False, "error": str(e)}, status=500)
|
||||
|
||||
async def get_trigger_words(self, request: web.Request) -> web.Response:
|
||||
"""Get trigger words for specified LoRA models"""
|
||||
try:
|
||||
json_data = await request.json()
|
||||
lora_names = json_data.get("lora_names", [])
|
||||
node_ids = json_data.get("node_ids", [])
|
||||
|
||||
|
||||
all_trigger_words = []
|
||||
for lora_name in lora_names:
|
||||
_, trigger_words = get_lora_info(lora_name)
|
||||
all_trigger_words.extend(trigger_words)
|
||||
|
||||
|
||||
# Format the trigger words
|
||||
trigger_words_text = ",, ".join(all_trigger_words) if all_trigger_words else ""
|
||||
|
||||
trigger_words_text = (
|
||||
",, ".join(all_trigger_words) if all_trigger_words else ""
|
||||
)
|
||||
|
||||
# Send update to all connected trigger word toggle nodes
|
||||
for node_id in node_ids:
|
||||
PromptServer.instance.send_sync("trigger_word_update", {
|
||||
"id": node_id,
|
||||
"message": trigger_words_text
|
||||
})
|
||||
|
||||
for entry in node_ids:
|
||||
node_identifier = entry
|
||||
graph_identifier = None
|
||||
if isinstance(entry, dict):
|
||||
node_identifier = entry.get("node_id")
|
||||
graph_identifier = entry.get("graph_id")
|
||||
|
||||
try:
|
||||
parsed_node_id = int(node_identifier)
|
||||
except (TypeError, ValueError):
|
||||
parsed_node_id = node_identifier
|
||||
|
||||
payload = {"id": parsed_node_id, "message": trigger_words_text}
|
||||
|
||||
if graph_identifier is not None:
|
||||
payload["graph_id"] = str(graph_identifier)
|
||||
|
||||
PromptServer.instance.send_sync("trigger_word_update", payload)
|
||||
|
||||
return web.json_response({"success": True})
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error getting trigger words: {e}")
|
||||
return web.json_response({
|
||||
"success": False,
|
||||
"error": str(e)
|
||||
}, status=500)
|
||||
return web.json_response({"success": False, "error": str(e)}, status=500)
|
||||
|
||||
74
py/routes/misc_route_registrar.py
Normal file
74
py/routes/misc_route_registrar.py
Normal file
@@ -0,0 +1,74 @@
|
||||
"""Route registrar for miscellaneous endpoints.
|
||||
|
||||
This module mirrors the model route registrar architecture so that
|
||||
miscellaneous endpoints share a consistent registration flow.
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass
|
||||
from typing import Callable, Iterable, Mapping
|
||||
|
||||
from aiohttp import web
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class RouteDefinition:
|
||||
"""Declarative definition for a HTTP route."""
|
||||
|
||||
method: str
|
||||
path: str
|
||||
handler_name: str
|
||||
|
||||
|
||||
MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
|
||||
RouteDefinition("GET", "/api/lm/settings", "get_settings"),
|
||||
RouteDefinition("POST", "/api/lm/settings", "update_settings"),
|
||||
RouteDefinition("GET", "/api/lm/priority-tags", "get_priority_tags"),
|
||||
RouteDefinition("GET", "/api/lm/settings/libraries", "get_settings_libraries"),
|
||||
RouteDefinition("POST", "/api/lm/settings/libraries/activate", "activate_library"),
|
||||
RouteDefinition("GET", "/api/lm/health-check", "health_check"),
|
||||
RouteDefinition("POST", "/api/lm/open-file-location", "open_file_location"),
|
||||
RouteDefinition("POST", "/api/lm/update-usage-stats", "update_usage_stats"),
|
||||
RouteDefinition("GET", "/api/lm/get-usage-stats", "get_usage_stats"),
|
||||
RouteDefinition("POST", "/api/lm/update-lora-code", "update_lora_code"),
|
||||
RouteDefinition("GET", "/api/lm/trained-words", "get_trained_words"),
|
||||
RouteDefinition("GET", "/api/lm/model-example-files", "get_model_example_files"),
|
||||
RouteDefinition("POST", "/api/lm/register-nodes", "register_nodes"),
|
||||
RouteDefinition("POST", "/api/lm/update-node-widget", "update_node_widget"),
|
||||
RouteDefinition("GET", "/api/lm/get-registry", "get_registry"),
|
||||
RouteDefinition("GET", "/api/lm/check-model-exists", "check_model_exists"),
|
||||
RouteDefinition("GET", "/api/lm/civitai/user-models", "get_civitai_user_models"),
|
||||
RouteDefinition("POST", "/api/lm/download-metadata-archive", "download_metadata_archive"),
|
||||
RouteDefinition("POST", "/api/lm/remove-metadata-archive", "remove_metadata_archive"),
|
||||
RouteDefinition("GET", "/api/lm/metadata-archive-status", "get_metadata_archive_status"),
|
||||
RouteDefinition("GET", "/api/lm/model-versions-status", "get_model_versions_status"),
|
||||
RouteDefinition("POST", "/api/lm/settings/open-location", "open_settings_location"),
|
||||
RouteDefinition("GET", "/api/lm/custom-words/search", "search_custom_words"),
|
||||
)
|
||||
|
||||
|
||||
class MiscRouteRegistrar:
|
||||
"""Bind miscellaneous route definitions to an aiohttp router."""
|
||||
|
||||
_METHOD_MAP = {
|
||||
"GET": "add_get",
|
||||
"POST": "add_post",
|
||||
"PUT": "add_put",
|
||||
"DELETE": "add_delete",
|
||||
}
|
||||
|
||||
def __init__(self, app: web.Application) -> None:
|
||||
self._app = app
|
||||
|
||||
def register_routes(
|
||||
self,
|
||||
handler_lookup: Mapping[str, Callable[[web.Request], object]],
|
||||
*,
|
||||
definitions: Iterable[RouteDefinition] = MISC_ROUTE_DEFINITIONS,
|
||||
) -> None:
|
||||
for definition in definitions:
|
||||
self._bind(definition.method, definition.path, handler_lookup[definition.handler_name])
|
||||
|
||||
def _bind(self, method: str, path: str, handler: Callable) -> None:
|
||||
add_method_name = self._METHOD_MAP[method.upper()]
|
||||
add_method = getattr(self._app.router, add_method_name)
|
||||
add_method(path, handler)
|
||||
File diff suppressed because it is too large
Load Diff
@@ -39,6 +39,7 @@ COMMON_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/auto-organize-progress", "get_auto_organize_progress"),
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/top-tags", "get_top_tags"),
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/base-models", "get_base_models"),
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/model-types", "get_model_types"),
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/scan", "scan_models"),
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/roots", "get_model_roots"),
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/folders", "get_folders"),
|
||||
@@ -55,10 +56,19 @@ COMMON_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/civitai/versions/{model_id}", "get_civitai_versions"),
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/civitai/model/version/{modelVersionId}", "get_civitai_model_by_version"),
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/civitai/model/hash/{hash}", "get_civitai_model_by_hash"),
|
||||
RouteDefinition("POST", "/api/lm/{prefix}/updates/refresh", "refresh_model_updates"),
|
||||
RouteDefinition("POST", "/api/lm/{prefix}/updates/fetch-missing-license", "fetch_missing_civitai_license_data"),
|
||||
RouteDefinition("POST", "/api/lm/{prefix}/updates/ignore", "set_model_update_ignore"),
|
||||
RouteDefinition("POST", "/api/lm/{prefix}/updates/ignore-version", "set_version_update_ignore"),
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/updates/status/{model_id}", "get_model_update_status"),
|
||||
RouteDefinition("GET", "/api/lm/{prefix}/updates/versions/{model_id}", "get_model_versions"),
|
||||
RouteDefinition("POST", "/api/lm/download-model", "download_model"),
|
||||
RouteDefinition("GET", "/api/lm/download-model-get", "download_model_get"),
|
||||
RouteDefinition("GET", "/api/lm/cancel-download-get", "cancel_download_get"),
|
||||
RouteDefinition("GET", "/api/lm/pause-download", "pause_download_get"),
|
||||
RouteDefinition("GET", "/api/lm/resume-download", "resume_download_get"),
|
||||
RouteDefinition("GET", "/api/lm/download-progress/{download_id}", "get_download_progress"),
|
||||
RouteDefinition("POST", "/api/lm/{prefix}/cancel-task", "cancel_task"),
|
||||
RouteDefinition("GET", "/{prefix}", "handle_models_page"),
|
||||
)
|
||||
|
||||
@@ -96,4 +106,3 @@ class ModelRouteRegistrar:
|
||||
add_method_name = self._METHOD_MAP[method.upper()]
|
||||
add_method = getattr(self._app.router, add_method_name)
|
||||
add_method(path, handler)
|
||||
|
||||
|
||||
25
py/routes/preview_routes.py
Normal file
25
py/routes/preview_routes.py
Normal file
@@ -0,0 +1,25 @@
|
||||
"""Route controller for preview asset delivery."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from aiohttp import web
|
||||
|
||||
from .handlers.preview_handlers import PreviewHandler
|
||||
|
||||
|
||||
class PreviewRoutes:
|
||||
"""Register routes that expose preview assets."""
|
||||
|
||||
def __init__(self, *, handler: PreviewHandler | None = None) -> None:
|
||||
self._handler = handler or PreviewHandler()
|
||||
|
||||
@classmethod
|
||||
def setup_routes(cls, app: web.Application) -> None:
|
||||
controller = cls()
|
||||
controller.register(app)
|
||||
|
||||
def register(self, app: web.Application) -> None:
|
||||
app.router.add_get('/api/lm/previews', self._handler.serve_preview)
|
||||
|
||||
|
||||
__all__ = ["PreviewRoutes"]
|
||||
@@ -20,22 +20,33 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
|
||||
RouteDefinition("GET", "/loras/recipes", "render_page"),
|
||||
RouteDefinition("GET", "/api/lm/recipes", "list_recipes"),
|
||||
RouteDefinition("GET", "/api/lm/recipe/{recipe_id}", "get_recipe"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/import-remote", "import_remote_recipe"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/analyze-image", "analyze_uploaded_image"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/analyze-local-image", "analyze_local_image"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/save", "save_recipe"),
|
||||
RouteDefinition("DELETE", "/api/lm/recipe/{recipe_id}", "delete_recipe"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/top-tags", "get_top_tags"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/base-models", "get_base_models"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/roots", "get_roots"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/folders", "get_folders"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/folder-tree", "get_folder_tree"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/unified-folder-tree", "get_unified_folder_tree"),
|
||||
RouteDefinition("GET", "/api/lm/recipe/{recipe_id}/share", "share_recipe"),
|
||||
RouteDefinition("GET", "/api/lm/recipe/{recipe_id}/share/download", "download_shared_recipe"),
|
||||
RouteDefinition("GET", "/api/lm/recipe/{recipe_id}/syntax", "get_recipe_syntax"),
|
||||
RouteDefinition("PUT", "/api/lm/recipe/{recipe_id}/update", "update_recipe"),
|
||||
RouteDefinition("POST", "/api/lm/recipe/move", "move_recipe"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/move-bulk", "move_recipes_bulk"),
|
||||
RouteDefinition("POST", "/api/lm/recipe/lora/reconnect", "reconnect_lora"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/find-duplicates", "find_duplicates"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/bulk-delete", "bulk_delete"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/save-from-widget", "save_recipe_from_widget"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/for-lora", "get_recipes_for_lora"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/scan", "scan_recipes"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/repair", "repair_recipes"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/cancel-repair", "cancel_repair"),
|
||||
RouteDefinition("POST", "/api/lm/recipe/{recipe_id}/repair", "repair_recipe"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/repair-progress", "get_repair_progress"),
|
||||
)
|
||||
|
||||
|
||||
@@ -61,4 +72,3 @@ class RecipeRouteRegistrar:
|
||||
add_method_name = self._METHOD_MAP[method.upper()]
|
||||
add_method = getattr(self._app.router, add_method_name)
|
||||
add_method(path, handler)
|
||||
|
||||
|
||||
@@ -8,13 +8,32 @@ from collections import defaultdict, Counter
|
||||
from typing import Dict, List, Any
|
||||
|
||||
from ..config import config
|
||||
from ..services.settings_manager import settings
|
||||
from ..services.settings_manager import get_settings_manager
|
||||
from ..services.server_i18n import server_i18n
|
||||
from ..services.service_registry import ServiceRegistry
|
||||
from ..utils.usage_stats import UsageStats
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class _SettingsProxy:
|
||||
def __init__(self):
|
||||
self._manager = None
|
||||
|
||||
def _resolve(self):
|
||||
if self._manager is None:
|
||||
self._manager = get_settings_manager()
|
||||
return self._manager
|
||||
|
||||
def get(self, *args, **kwargs):
|
||||
return self._resolve().get(*args, **kwargs)
|
||||
|
||||
def __getattr__(self, item):
|
||||
return getattr(self._resolve(), item)
|
||||
|
||||
|
||||
settings = _SettingsProxy()
|
||||
|
||||
class StatsRoutes:
|
||||
"""Route handlers for Statistics page and API endpoints"""
|
||||
|
||||
@@ -66,7 +85,9 @@ class StatsRoutes:
|
||||
is_initializing = lora_initializing or checkpoint_initializing or embedding_initializing
|
||||
|
||||
# 获取用户语言设置
|
||||
user_language = settings.get('language', 'en')
|
||||
settings_object = settings
|
||||
user_language = settings_object.get('language', 'en')
|
||||
settings_manager = settings_object if not isinstance(settings_object, _SettingsProxy) else settings_object._resolve()
|
||||
|
||||
# 设置服务端i18n语言
|
||||
server_i18n.set_locale(user_language)
|
||||
@@ -79,7 +100,7 @@ class StatsRoutes:
|
||||
template = self.template_env.get_template('statistics.html')
|
||||
rendered = template.render(
|
||||
is_initializing=is_initializing,
|
||||
settings=settings,
|
||||
settings=settings_manager,
|
||||
request=request,
|
||||
t=server_i18n.get_translation,
|
||||
)
|
||||
|
||||
@@ -5,12 +5,18 @@ import git
|
||||
import zipfile
|
||||
import shutil
|
||||
import tempfile
|
||||
from aiohttp import web
|
||||
import asyncio
|
||||
from aiohttp import web, ClientError
|
||||
from typing import Dict, List
|
||||
|
||||
from ..utils.settings_paths import ensure_settings_file
|
||||
from ..services.downloader import get_downloader
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
NETWORK_EXCEPTIONS = (ClientError, OSError, asyncio.TimeoutError)
|
||||
|
||||
|
||||
class UpdateRoutes:
|
||||
"""Routes for handling plugin update checks"""
|
||||
|
||||
@@ -39,8 +45,9 @@ class UpdateRoutes:
|
||||
# Fetch remote version from GitHub
|
||||
if nightly:
|
||||
remote_version, changelog = await UpdateRoutes._get_nightly_version()
|
||||
releases = None
|
||||
else:
|
||||
remote_version, changelog = await UpdateRoutes._get_remote_version()
|
||||
remote_version, changelog, releases = await UpdateRoutes._get_remote_version()
|
||||
|
||||
# Compare versions
|
||||
if nightly:
|
||||
@@ -53,7 +60,7 @@ class UpdateRoutes:
|
||||
remote_version.replace('v', '')
|
||||
)
|
||||
|
||||
return web.json_response({
|
||||
response_data = {
|
||||
'success': True,
|
||||
'current_version': local_version,
|
||||
'latest_version': remote_version,
|
||||
@@ -61,8 +68,20 @@ class UpdateRoutes:
|
||||
'changelog': changelog,
|
||||
'git_info': git_info,
|
||||
'nightly': nightly
|
||||
})
|
||||
}
|
||||
|
||||
# Include releases list for stable mode
|
||||
if releases is not None:
|
||||
response_data['releases'] = releases
|
||||
|
||||
return web.json_response(response_data)
|
||||
|
||||
except NETWORK_EXCEPTIONS as e:
|
||||
logger.warning("Network unavailable during update check: %s", e)
|
||||
return web.json_response({
|
||||
'success': False,
|
||||
'error': 'Network unavailable for update check'
|
||||
})
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to check for updates: {e}", exc_info=True)
|
||||
return web.json_response({
|
||||
@@ -111,7 +130,7 @@ class UpdateRoutes:
|
||||
current_dir = os.path.dirname(os.path.abspath(__file__))
|
||||
plugin_root = os.path.dirname(os.path.dirname(current_dir))
|
||||
|
||||
settings_path = os.path.join(plugin_root, 'settings.json')
|
||||
settings_path = ensure_settings_file(logger)
|
||||
settings_backup = None
|
||||
if os.path.exists(settings_path):
|
||||
with open(settings_path, 'r', encoding='utf-8') as f:
|
||||
@@ -193,8 +212,8 @@ class UpdateRoutes:
|
||||
|
||||
zip_path = tmp_zip_path
|
||||
|
||||
# Skip both settings.json and civitai folder
|
||||
UpdateRoutes._clean_plugin_folder(plugin_root, skip_files=['settings.json', 'civitai'])
|
||||
# Skip both settings.json, civitai and model cache folder
|
||||
UpdateRoutes._clean_plugin_folder(plugin_root, skip_files=['settings.json', 'civitai', 'model_cache'])
|
||||
|
||||
# Extract ZIP to temp dir
|
||||
with tempfile.TemporaryDirectory() as tmp_dir:
|
||||
@@ -283,6 +302,9 @@ class UpdateRoutes:
|
||||
|
||||
return version, changelog
|
||||
|
||||
except NETWORK_EXCEPTIONS as e:
|
||||
logger.warning("Unable to reach GitHub for nightly version: %s", e)
|
||||
return "main", []
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching nightly version: {e}", exc_info=True)
|
||||
return "main", []
|
||||
@@ -329,6 +351,11 @@ class UpdateRoutes:
|
||||
origin.fetch()
|
||||
|
||||
if nightly:
|
||||
# Reset to discard any local changes
|
||||
repo.git.reset('--hard')
|
||||
# Clean untracked files
|
||||
repo.git.clean('-fd')
|
||||
|
||||
# Switch to main branch and pull latest
|
||||
main_branch = 'main'
|
||||
if main_branch not in [branch.name for branch in repo.branches]:
|
||||
@@ -342,6 +369,11 @@ class UpdateRoutes:
|
||||
new_version = f"main-{repo.head.commit.hexsha[:7]}"
|
||||
|
||||
else:
|
||||
# Reset to discard any local changes
|
||||
repo.git.reset('--hard')
|
||||
# Clean untracked files
|
||||
repo.git.clean('-fd')
|
||||
|
||||
# Get latest release tag
|
||||
tags = sorted(repo.tags, key=lambda t: t.commit.committed_datetime, reverse=True)
|
||||
if not tags:
|
||||
@@ -418,39 +450,58 @@ class UpdateRoutes:
|
||||
return git_info
|
||||
|
||||
@staticmethod
|
||||
async def _get_remote_version() -> tuple[str, List[str]]:
|
||||
async def _get_remote_version() -> tuple[str, List[str], List[Dict]]:
|
||||
"""
|
||||
Fetch remote version from GitHub
|
||||
Returns:
|
||||
tuple: (version string, changelog list)
|
||||
tuple: (version string, changelog list, releases list)
|
||||
"""
|
||||
repo_owner = "willmiao"
|
||||
repo_name = "ComfyUI-Lora-Manager"
|
||||
|
||||
# Use GitHub API to fetch the latest release
|
||||
github_url = f"https://api.github.com/repos/{repo_owner}/{repo_name}/releases/latest"
|
||||
# Use GitHub API to fetch the last 5 releases
|
||||
github_url = f"https://api.github.com/repos/{repo_owner}/{repo_name}/releases?per_page=5"
|
||||
|
||||
try:
|
||||
downloader = await get_downloader()
|
||||
success, data = await downloader.make_request('GET', github_url, custom_headers={'Accept': 'application/vnd.github+json'})
|
||||
|
||||
if not success:
|
||||
logger.warning(f"Failed to fetch GitHub release: {data}")
|
||||
return "v0.0.0", []
|
||||
logger.warning(f"Failed to fetch GitHub releases: {data}")
|
||||
return "v0.0.0", [], []
|
||||
|
||||
version = data.get('tag_name', '')
|
||||
if not version.startswith('v'):
|
||||
version = f"v{version}"
|
||||
# Parse releases
|
||||
releases = []
|
||||
for i, release in enumerate(data):
|
||||
version = release.get('tag_name', '')
|
||||
if not version.startswith('v'):
|
||||
version = f"v{version}"
|
||||
|
||||
# Extract changelog from release notes
|
||||
body = release.get('body', '')
|
||||
changelog = UpdateRoutes._parse_changelog(body)
|
||||
|
||||
releases.append({
|
||||
'version': version,
|
||||
'changelog': changelog,
|
||||
'published_at': release.get('published_at', ''),
|
||||
'is_latest': i == 0
|
||||
})
|
||||
|
||||
# Extract changelog from release notes
|
||||
body = data.get('body', '')
|
||||
changelog = UpdateRoutes._parse_changelog(body)
|
||||
# Get latest version and its changelog
|
||||
if releases:
|
||||
latest_version = releases[0]['version']
|
||||
latest_changelog = releases[0]['changelog']
|
||||
return latest_version, latest_changelog, releases
|
||||
|
||||
return version, changelog
|
||||
return "v0.0.0", [], []
|
||||
|
||||
except NETWORK_EXCEPTIONS as e:
|
||||
logger.warning("Unable to reach GitHub for release info: %s", e)
|
||||
return "v0.0.0", [], []
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching remote version: {e}", exc_info=True)
|
||||
return "v0.0.0", []
|
||||
return "v0.0.0", [], []
|
||||
|
||||
@staticmethod
|
||||
def _parse_changelog(release_notes: str) -> List[str]:
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
259
py/services/cache_entry_validator.py
Normal file
259
py/services/cache_entry_validator.py
Normal file
@@ -0,0 +1,259 @@
|
||||
"""
|
||||
Cache Entry Validator
|
||||
|
||||
Validates and repairs cache entries to prevent runtime errors from
|
||||
missing or invalid critical fields.
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Any, Dict, List, Optional, Tuple
|
||||
import logging
|
||||
import os
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@dataclass
|
||||
class ValidationResult:
|
||||
"""Result of validating a single cache entry."""
|
||||
is_valid: bool
|
||||
repaired: bool
|
||||
errors: List[str] = field(default_factory=list)
|
||||
entry: Optional[Dict[str, Any]] = None
|
||||
|
||||
|
||||
class CacheEntryValidator:
|
||||
"""
|
||||
Validates and repairs cache entry core fields.
|
||||
|
||||
Critical fields that cause runtime errors when missing:
|
||||
- file_path: KeyError in multiple locations
|
||||
- sha256: KeyError/AttributeError in hash operations
|
||||
|
||||
Medium severity fields that may cause sorting/display issues:
|
||||
- size: KeyError during sorting
|
||||
- modified: KeyError during sorting
|
||||
- model_name: AttributeError on .lower() calls
|
||||
|
||||
Low severity fields:
|
||||
- tags: KeyError/TypeError in recipe operations
|
||||
"""
|
||||
|
||||
# Field definitions: (default_value, is_required)
|
||||
CORE_FIELDS: Dict[str, Tuple[Any, bool]] = {
|
||||
'file_path': ('', True),
|
||||
'sha256': ('', True),
|
||||
'file_name': ('', False),
|
||||
'model_name': ('', False),
|
||||
'folder': ('', False),
|
||||
'size': (0, False),
|
||||
'modified': (0.0, False),
|
||||
'tags': ([], False),
|
||||
'preview_url': ('', False),
|
||||
'base_model': ('', False),
|
||||
'from_civitai': (True, False),
|
||||
'favorite': (False, False),
|
||||
'exclude': (False, False),
|
||||
'db_checked': (False, False),
|
||||
'preview_nsfw_level': (0, False),
|
||||
'notes': ('', False),
|
||||
'usage_tips': ('', False),
|
||||
}
|
||||
|
||||
@classmethod
|
||||
def validate(cls, entry: Dict[str, Any], *, auto_repair: bool = True) -> ValidationResult:
|
||||
"""
|
||||
Validate a single cache entry.
|
||||
|
||||
Args:
|
||||
entry: The cache entry dictionary to validate
|
||||
auto_repair: If True, attempt to repair missing/invalid fields
|
||||
|
||||
Returns:
|
||||
ValidationResult with validation status and optionally repaired entry
|
||||
"""
|
||||
if entry is None:
|
||||
return ValidationResult(
|
||||
is_valid=False,
|
||||
repaired=False,
|
||||
errors=['Entry is None'],
|
||||
entry=None
|
||||
)
|
||||
|
||||
if not isinstance(entry, dict):
|
||||
return ValidationResult(
|
||||
is_valid=False,
|
||||
repaired=False,
|
||||
errors=[f'Entry is not a dict: {type(entry).__name__}'],
|
||||
entry=None
|
||||
)
|
||||
|
||||
errors: List[str] = []
|
||||
repaired = False
|
||||
working_entry = dict(entry) if auto_repair else entry
|
||||
|
||||
for field_name, (default_value, is_required) in cls.CORE_FIELDS.items():
|
||||
value = working_entry.get(field_name)
|
||||
|
||||
# Check if field is missing or None
|
||||
if value is None:
|
||||
if is_required:
|
||||
errors.append(f"Required field '{field_name}' is missing or None")
|
||||
if auto_repair:
|
||||
working_entry[field_name] = cls._get_default_copy(default_value)
|
||||
repaired = True
|
||||
continue
|
||||
|
||||
# Validate field type and value
|
||||
field_error = cls._validate_field(field_name, value, default_value)
|
||||
if field_error:
|
||||
errors.append(field_error)
|
||||
if auto_repair:
|
||||
working_entry[field_name] = cls._get_default_copy(default_value)
|
||||
repaired = True
|
||||
|
||||
# Special validation: file_path must not be empty for required field
|
||||
file_path = working_entry.get('file_path', '')
|
||||
if not file_path or (isinstance(file_path, str) and not file_path.strip()):
|
||||
errors.append("Required field 'file_path' is empty")
|
||||
# Cannot repair empty file_path - entry is invalid
|
||||
return ValidationResult(
|
||||
is_valid=False,
|
||||
repaired=repaired,
|
||||
errors=errors,
|
||||
entry=working_entry if auto_repair else None
|
||||
)
|
||||
|
||||
# Special validation: sha256 must not be empty for required field
|
||||
sha256 = working_entry.get('sha256', '')
|
||||
if not sha256 or (isinstance(sha256, str) and not sha256.strip()):
|
||||
errors.append("Required field 'sha256' is empty")
|
||||
# Cannot repair empty sha256 - entry is invalid
|
||||
return ValidationResult(
|
||||
is_valid=False,
|
||||
repaired=repaired,
|
||||
errors=errors,
|
||||
entry=working_entry if auto_repair else None
|
||||
)
|
||||
|
||||
# Normalize sha256 to lowercase if needed
|
||||
if isinstance(sha256, str):
|
||||
normalized_sha = sha256.lower().strip()
|
||||
if normalized_sha != sha256:
|
||||
working_entry['sha256'] = normalized_sha
|
||||
repaired = True
|
||||
|
||||
# Determine if entry is valid
|
||||
# Entry is valid if no critical required field errors remain after repair
|
||||
# Critical fields are file_path and sha256
|
||||
CRITICAL_REQUIRED_FIELDS = {'file_path', 'sha256'}
|
||||
has_critical_errors = any(
|
||||
"Required field" in error and
|
||||
any(f"'{field}'" in error for field in CRITICAL_REQUIRED_FIELDS)
|
||||
for error in errors
|
||||
)
|
||||
|
||||
is_valid = not has_critical_errors
|
||||
|
||||
return ValidationResult(
|
||||
is_valid=is_valid,
|
||||
repaired=repaired,
|
||||
errors=errors,
|
||||
entry=working_entry if auto_repair else entry
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def validate_batch(
|
||||
cls,
|
||||
entries: List[Dict[str, Any]],
|
||||
*,
|
||||
auto_repair: bool = True
|
||||
) -> Tuple[List[Dict[str, Any]], List[Dict[str, Any]]]:
|
||||
"""
|
||||
Validate a batch of cache entries.
|
||||
|
||||
Args:
|
||||
entries: List of cache entry dictionaries to validate
|
||||
auto_repair: If True, attempt to repair missing/invalid fields
|
||||
|
||||
Returns:
|
||||
Tuple of (valid_entries, invalid_entries)
|
||||
"""
|
||||
if not entries:
|
||||
return [], []
|
||||
|
||||
valid_entries: List[Dict[str, Any]] = []
|
||||
invalid_entries: List[Dict[str, Any]] = []
|
||||
|
||||
for entry in entries:
|
||||
result = cls.validate(entry, auto_repair=auto_repair)
|
||||
|
||||
if result.is_valid:
|
||||
# Use repaired entry if available, otherwise original
|
||||
valid_entries.append(result.entry if result.entry else entry)
|
||||
else:
|
||||
invalid_entries.append(entry)
|
||||
# Log invalid entries for debugging
|
||||
file_path = entry.get('file_path', '<unknown>') if isinstance(entry, dict) else '<not a dict>'
|
||||
logger.warning(
|
||||
f"Invalid cache entry for '{file_path}': {', '.join(result.errors)}"
|
||||
)
|
||||
|
||||
return valid_entries, invalid_entries
|
||||
|
||||
@classmethod
|
||||
def _validate_field(cls, field_name: str, value: Any, default_value: Any) -> Optional[str]:
|
||||
"""
|
||||
Validate a specific field value.
|
||||
|
||||
Returns an error message if invalid, None if valid.
|
||||
"""
|
||||
expected_type = type(default_value)
|
||||
|
||||
# Special handling for numeric types
|
||||
if expected_type == int:
|
||||
if not isinstance(value, (int, float)):
|
||||
return f"Field '{field_name}' should be numeric, got {type(value).__name__}"
|
||||
elif expected_type == float:
|
||||
if not isinstance(value, (int, float)):
|
||||
return f"Field '{field_name}' should be numeric, got {type(value).__name__}"
|
||||
elif expected_type == bool:
|
||||
# Be lenient with boolean fields - accept truthy/falsy values
|
||||
pass
|
||||
elif expected_type == str:
|
||||
if not isinstance(value, str):
|
||||
return f"Field '{field_name}' should be string, got {type(value).__name__}"
|
||||
elif expected_type == list:
|
||||
if not isinstance(value, (list, tuple)):
|
||||
return f"Field '{field_name}' should be list, got {type(value).__name__}"
|
||||
|
||||
return None
|
||||
|
||||
@classmethod
|
||||
def _get_default_copy(cls, default_value: Any) -> Any:
|
||||
"""Get a copy of the default value to avoid shared mutable state."""
|
||||
if isinstance(default_value, list):
|
||||
return list(default_value)
|
||||
if isinstance(default_value, dict):
|
||||
return dict(default_value)
|
||||
return default_value
|
||||
|
||||
@classmethod
|
||||
def get_file_path_safe(cls, entry: Dict[str, Any], default: str = '') -> str:
|
||||
"""Safely get file_path from an entry."""
|
||||
if not isinstance(entry, dict):
|
||||
return default
|
||||
value = entry.get('file_path')
|
||||
if isinstance(value, str):
|
||||
return value
|
||||
return default
|
||||
|
||||
@classmethod
|
||||
def get_sha256_safe(cls, entry: Dict[str, Any], default: str = '') -> str:
|
||||
"""Safely get sha256 from an entry."""
|
||||
if not isinstance(entry, dict):
|
||||
return default
|
||||
value = entry.get('sha256')
|
||||
if isinstance(value, str):
|
||||
return value.lower()
|
||||
return default
|
||||
201
py/services/cache_health_monitor.py
Normal file
201
py/services/cache_health_monitor.py
Normal file
@@ -0,0 +1,201 @@
|
||||
"""
|
||||
Cache Health Monitor
|
||||
|
||||
Monitors cache health status and determines when user intervention is needed.
|
||||
"""
|
||||
|
||||
from dataclasses import dataclass, field
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, List, Optional
|
||||
import logging
|
||||
|
||||
from .cache_entry_validator import CacheEntryValidator, ValidationResult
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class CacheHealthStatus(Enum):
|
||||
"""Health status of the cache."""
|
||||
HEALTHY = "healthy"
|
||||
DEGRADED = "degraded"
|
||||
CORRUPTED = "corrupted"
|
||||
|
||||
|
||||
@dataclass
|
||||
class HealthReport:
|
||||
"""Report of cache health check."""
|
||||
status: CacheHealthStatus
|
||||
total_entries: int
|
||||
valid_entries: int
|
||||
invalid_entries: int
|
||||
repaired_entries: int
|
||||
invalid_paths: List[str] = field(default_factory=list)
|
||||
message: str = ""
|
||||
|
||||
@property
|
||||
def corruption_rate(self) -> float:
|
||||
"""Calculate the percentage of invalid entries."""
|
||||
if self.total_entries <= 0:
|
||||
return 0.0
|
||||
return self.invalid_entries / self.total_entries
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
"""Convert to dictionary for JSON serialization."""
|
||||
return {
|
||||
'status': self.status.value,
|
||||
'total_entries': self.total_entries,
|
||||
'valid_entries': self.valid_entries,
|
||||
'invalid_entries': self.invalid_entries,
|
||||
'repaired_entries': self.repaired_entries,
|
||||
'corruption_rate': f"{self.corruption_rate:.1%}",
|
||||
'invalid_paths': self.invalid_paths[:10], # Limit to first 10
|
||||
'message': self.message,
|
||||
}
|
||||
|
||||
|
||||
class CacheHealthMonitor:
|
||||
"""
|
||||
Monitors cache health and determines appropriate status.
|
||||
|
||||
Thresholds:
|
||||
- HEALTHY: 0% invalid entries
|
||||
- DEGRADED: 0-5% invalid entries (auto-repaired, user should rebuild)
|
||||
- CORRUPTED: >5% invalid entries (significant data loss likely)
|
||||
"""
|
||||
|
||||
# Threshold percentages
|
||||
DEGRADED_THRESHOLD = 0.01 # 1% - show warning
|
||||
CORRUPTED_THRESHOLD = 0.05 # 5% - critical warning
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
degraded_threshold: float = DEGRADED_THRESHOLD,
|
||||
corrupted_threshold: float = CORRUPTED_THRESHOLD
|
||||
):
|
||||
"""
|
||||
Initialize the health monitor.
|
||||
|
||||
Args:
|
||||
degraded_threshold: Corruption rate threshold for DEGRADED status
|
||||
corrupted_threshold: Corruption rate threshold for CORRUPTED status
|
||||
"""
|
||||
self.degraded_threshold = degraded_threshold
|
||||
self.corrupted_threshold = corrupted_threshold
|
||||
|
||||
def check_health(
|
||||
self,
|
||||
entries: List[Dict[str, Any]],
|
||||
*,
|
||||
auto_repair: bool = True
|
||||
) -> HealthReport:
|
||||
"""
|
||||
Check the health of cache entries.
|
||||
|
||||
Args:
|
||||
entries: List of cache entry dictionaries to check
|
||||
auto_repair: If True, attempt to repair entries during validation
|
||||
|
||||
Returns:
|
||||
HealthReport with status and statistics
|
||||
"""
|
||||
if not entries:
|
||||
return HealthReport(
|
||||
status=CacheHealthStatus.HEALTHY,
|
||||
total_entries=0,
|
||||
valid_entries=0,
|
||||
invalid_entries=0,
|
||||
repaired_entries=0,
|
||||
message="Cache is empty"
|
||||
)
|
||||
|
||||
total_entries = len(entries)
|
||||
valid_entries: List[Dict[str, Any]] = []
|
||||
invalid_entries: List[Dict[str, Any]] = []
|
||||
repaired_count = 0
|
||||
invalid_paths: List[str] = []
|
||||
|
||||
for entry in entries:
|
||||
result = CacheEntryValidator.validate(entry, auto_repair=auto_repair)
|
||||
|
||||
if result.is_valid:
|
||||
valid_entries.append(result.entry if result.entry else entry)
|
||||
if result.repaired:
|
||||
repaired_count += 1
|
||||
else:
|
||||
invalid_entries.append(entry)
|
||||
# Extract file path for reporting
|
||||
file_path = CacheEntryValidator.get_file_path_safe(entry, '<unknown>')
|
||||
invalid_paths.append(file_path)
|
||||
|
||||
invalid_count = len(invalid_entries)
|
||||
valid_count = len(valid_entries)
|
||||
|
||||
# Determine status based on corruption rate
|
||||
corruption_rate = invalid_count / total_entries if total_entries > 0 else 0.0
|
||||
|
||||
if invalid_count == 0:
|
||||
status = CacheHealthStatus.HEALTHY
|
||||
message = "Cache is healthy"
|
||||
elif corruption_rate >= self.corrupted_threshold:
|
||||
status = CacheHealthStatus.CORRUPTED
|
||||
message = (
|
||||
f"Cache is corrupted: {invalid_count} invalid entries "
|
||||
f"({corruption_rate:.1%}). Rebuild recommended."
|
||||
)
|
||||
elif corruption_rate >= self.degraded_threshold or invalid_count > 0:
|
||||
status = CacheHealthStatus.DEGRADED
|
||||
message = (
|
||||
f"Cache has {invalid_count} invalid entries "
|
||||
f"({corruption_rate:.1%}). Consider rebuilding cache."
|
||||
)
|
||||
else:
|
||||
# This shouldn't happen, but handle gracefully
|
||||
status = CacheHealthStatus.HEALTHY
|
||||
message = "Cache is healthy"
|
||||
|
||||
# Log the health check result
|
||||
if status != CacheHealthStatus.HEALTHY:
|
||||
logger.warning(
|
||||
f"Cache health check: {status.value} - "
|
||||
f"{invalid_count}/{total_entries} invalid, "
|
||||
f"{repaired_count} repaired"
|
||||
)
|
||||
if invalid_paths:
|
||||
logger.debug(f"Invalid entry paths: {invalid_paths[:5]}")
|
||||
|
||||
return HealthReport(
|
||||
status=status,
|
||||
total_entries=total_entries,
|
||||
valid_entries=valid_count,
|
||||
invalid_entries=invalid_count,
|
||||
repaired_entries=repaired_count,
|
||||
invalid_paths=invalid_paths,
|
||||
message=message
|
||||
)
|
||||
|
||||
def should_notify_user(self, report: HealthReport) -> bool:
|
||||
"""
|
||||
Determine if the user should be notified about cache health.
|
||||
|
||||
Args:
|
||||
report: The health report to evaluate
|
||||
|
||||
Returns:
|
||||
True if user should be notified
|
||||
"""
|
||||
return report.status != CacheHealthStatus.HEALTHY
|
||||
|
||||
def get_notification_severity(self, report: HealthReport) -> str:
|
||||
"""
|
||||
Get the severity level for user notification.
|
||||
|
||||
Args:
|
||||
report: The health report to evaluate
|
||||
|
||||
Returns:
|
||||
Severity string: 'warning' or 'error'
|
||||
"""
|
||||
if report.status == CacheHealthStatus.CORRUPTED:
|
||||
return 'error'
|
||||
return 'warning'
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user