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1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
 Will Miao
|
ed7cf418b4 |
@@ -0,0 +1,146 @@
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---
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name: lora-manager-e2e
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description: "End-to-end testing and validation for LoRa Manager features. Use ONLY for sandboxed E2E validation of LoRa Manager standalone mode: start the standalone server on a free port with --settings-path, drive the web UI (http://127.0.0.1:{PORT}/loras) via Chrome DevTools MCP, and verify frontend-to-backend integration. NOT for UI behavior checks that unit tests (Vitest/jsdom) can cover. Trigger keywords: E2E, standalone, Chrome DevTools MCP, lora-manager-e2e, sandbox."
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---
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# LoRa Manager E2E Testing
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End-to-end testing of LoRa Manager standalone mode using Chrome DevTools MCP.
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## When to Use — and When NOT To
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E2E runs are slow and token-heavy. Reach for them only when the question genuinely
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spans server + browser (routing, scan persistence, websocket updates, EXIF writes).
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- **Default to unit/component tests first**: `npm run test:js` (Vitest/jsdom) covers
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DOM rendering, modal behavior, event handling and API-client calls deterministically
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in seconds. Backend logic goes through `pytest`. A UI-behavior question answered by
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jsdom MUST NOT be escalated to E2E.
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- **Use E2E only when** the behavior cannot be observed without a live server and a
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real browser, e.g. template rendering through the aiohttp server, scanner → SQLite
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persistence → API → DOM round-trips, or real EXIF/image writes.
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- If you start an E2E and realize a unit test would answer the question, stop and
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switch.
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**Browser driver is fixed: Chrome DevTools MCP.** Do not substitute kimi-webbridge —
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it operates on the user's real browser (real tabs, real sessions, synthetic
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`isTrusted=false` events), which breaks the isolation this skill requires and lacks
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the console/network inspection E2E debugging relies on. kimi-webbridge is for
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interactive browsing with the user's real login sessions, not for sandboxed E2E.
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## Conventions
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- **`{PORT}`**: default candidate `8188`, but it is **commonly occupied by a live
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ComfyUI** — always check first (`ss -tlnp | grep ':{PORT}'`) and use a free port
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(e.g. `8199`). Substitute the chosen port everywhere below. Never kill a process
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you did not start for this E2E.
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- **`<repo-root>`**: the repository/worktree root; run all commands from there.
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- **`<sandbox>`**: a throwaway dir, e.g. `/tmp/opencode/<plan>-e2e`.
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## SANDBOX (MANDATORY)
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> Every E2E run MUST target a throwaway sandbox, never real user data.
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1. **Explicit settings directory**: always launch with `--settings-path <sandbox>/settings`.
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This pins ALL runtime data (`settings.json`, `cache/`, `backups/`, `logs/`, `stats/`,
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`wildcards/`) under the sandbox. **Never** create `<repo-root>/settings.json` — the repo
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folder is usually the real ComfyUI plugin folder and a portable settings file there is
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read by the real instance.
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2. **Sandboxed library paths**: point `folder_paths` / `recipes_path` /
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`example_images_path` at disposable dirs under `<sandbox>` — never the real library,
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real recipe dir, or real settings:
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```json
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{
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"folder_paths": {
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"loras": ["<sandbox>/models/loras"],
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"checkpoints": ["<sandbox>/models/checkpoints"],
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"unet": ["<sandbox>/models/checkpoints"],
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"diffusers": []
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},
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"recipes_path": "<sandbox>/recipes",
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"example_images_path": "<sandbox>/example_images"
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}
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```
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3. **Real-data protection proof**: before starting and after finishing, snapshot the real
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config and recipe library and confirm they are byte-identical; also confirm
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`<repo-root>` gained no `settings.json` or `cache/`:
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```bash
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sha256sum ~/.config/ComfyUI-LoRA-Manager/settings.json > <sandbox>/settings.before.sha256
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ls ~/models/recipes/*.recipe.json 2>/dev/null | wc -l > <sandbox>/recipes-count.before.txt
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# AFTER the run: record again and diff. Any change = the run leaked into real data.
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```
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## Quick Start
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```bash
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cd <repo-root>
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# 1. Sandbox
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mkdir -p <sandbox>/settings <sandbox>/models/{loras,checkpoints} <sandbox>/{recipes,example_images}
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# write <sandbox>/settings/settings.json per the SANDBOX example
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# 2. Port
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ss -tlnp | grep ':{PORT}' || echo "port {PORT} is free"
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# 3. Server — MUST be fully detached (a plain background & dies with the shell);
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# the helper enforces this and manages its own pidfile
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python .agents/skills/lora-manager-e2e/scripts/start_server.py \
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--port {PORT} --settings-path <sandbox>/settings --wait --timeout 30 --detach
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ss -tlnp | grep ':{PORT}' # verify listening BEFORE proceeding
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# 4. Chrome with remote debugging, then connect Chrome DevTools MCP (verify via list_pages)
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google-chrome --remote-debugging-port=9222 --user-data-dir=/tmp/chrome-lora-manager http://127.0.0.1:{PORT}/loras
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```
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Then drive the UI with the MCP tools (`take_snapshot`, `click`, `fill`, `fill_form`,
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`evaluate_script`, `wait_for`, `list_network_requests`, `list_console_messages`) —
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see [references/mcp-cheatsheet.md](references/mcp-cheatsheet.md) for patterns.
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Server restart after config/fixture changes:
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```bash
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python .agents/skills/lora-manager-e2e/scripts/start_server.py \
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--port {PORT} --settings-path <sandbox>/settings --restart --wait --detach
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# then reload the browser page (ignoreCache=True)
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```
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`--restart` only kills the E2E server the script itself started (via its pidfile) and
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aborts instead of killing unrelated processes on the port.
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## Abort Rule
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A sandboxed E2E should finish in well under 30 minutes. If any phase exceeds ~2x its
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expected duration (server readiness > 60 s, MCP connect > 2 min, a single scenario >
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10 min), or any single tool call fails 3+ times in a row, **STOP** — do not retry
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blindly. Report `BLOCKED` with the phase, last observed state (server PID,
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`ss -tlnp` output, page snapshot, last API response) and suspected cause. A clean
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BLOCKED report beats an hour of retries.
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## Troubleshooting
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- **"browser is already running" / `list_pages` fails**: a stale Chrome holds the
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profile dir. Find it (`ps -ef | grep -i '[c]hrome.*user-data-dir'`), confirm it is a
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leftover QA Chrome (not the live ComfyUI, not your current MCP browser), kill only
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that PID, then retry `list_pages`.
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- **MCP refuses to write screenshots into the worktree**: save to `/tmp` via
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`take_screenshot(filePath="/tmp/...")` and copy into the evidence dir from the shell.
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## Cleanup
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1. Stop the standalone server: `kill <recorded-pid>` (only the PID you started), then
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confirm `ss -tlnp | grep ':{PORT}'` is empty.
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2. Close browser pages (keep at least one open).
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3. `rm -rf <sandbox>`; verify `<repo-root>` gained no `settings.json` or `cache/`.
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4. Re-run the real-data protection check from the SANDBOX section and record the result.
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## References & Scripts
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- [references/mcp-cheatsheet.md](references/mcp-cheatsheet.md) — Chrome DevTools MCP
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command patterns (navigation, waiting, snapshots, forms, network, console, performance).
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- [references/test-scenarios.md](references/test-scenarios.md) — detailed test scenarios
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(list display, metadata editing, recipes, settings, import/export).
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- [references/recipe-rematch-fixtures.md](references/recipe-rematch-fixtures.md) —
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fixture format, fresh-state reset and known gaps for recipe rematch/repair E2E runs.
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- `scripts/start_server.py` — start/restart the standalone server
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(`--port --settings-path --restart --wait --timeout --detach`); refuses to touch
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unrelated processes on the port.
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- `scripts/wait_for_server.py` — poll readiness (`--port --timeout`).
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@@ -0,0 +1,360 @@
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# Chrome DevTools MCP Cheatsheet for LoRa Manager
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Quick reference for common MCP commands used in LoRa Manager E2E testing.
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> **Port convention**: `{PORT}` is the port chosen for the E2E run (default candidate `8188`, but only if actually free — see the SKILL.md Port Selection section; use e.g. `8199` when `8188` is occupied by a live ComfyUI). Always run against the **sandboxed** standalone server, never a live instance.
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## Navigation
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```python
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# Navigate to LoRA list page
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navigate_page(type="url", url="http://127.0.0.1:{PORT}/loras")
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# Reload page with cache clear
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navigate_page(type="reload", ignoreCache=True)
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# Go back/forward
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navigate_page(type="back")
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navigate_page(type="forward")
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```
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## Waiting
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```python
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# Wait for text to appear
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wait_for(text="LoRAs", timeout=10000)
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# Wait for specific element (via evaluate_script)
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evaluate_script(function="""
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() => {
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return new Promise((resolve) => {
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const check = () => {
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if (document.querySelector('.lora-card')) {
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resolve(true);
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} else {
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setTimeout(check, 100);
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}
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};
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check();
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});
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}
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""")
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```
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## Taking Snapshots
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```python
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# Full page snapshot
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snapshot = take_snapshot()
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# Verbose snapshot (more details)
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snapshot = take_snapshot(verbose=True)
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# Save to file
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take_snapshot(filePath="test-snapshots/page-load.json")
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```
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## Element Interaction
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```python
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# Click element
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click(uid="element-uid-from-snapshot")
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# Double click
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click(uid="element-uid", dblClick=True)
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# Fill input
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fill(uid="search-input", value="test query")
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# Fill multiple inputs
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fill_form(elements=[
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{"uid": "input-1", "value": "value 1"},
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{"uid": "input-2", "value": "value 2"},
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])
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# Hover
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hover(uid="lora-card-1")
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# Upload file
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upload_file(uid="file-input", filePath="/path/to/file.safetensors")
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```
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## Keyboard Input
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```python
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# Press key
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press_key(key="Enter")
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press_key(key="Escape")
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press_key(key="Tab")
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# Keyboard shortcuts
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||||
press_key(key="Control+A") # Select all
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press_key(key="Control+F") # Find
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```
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||||
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## JavaScript Evaluation
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```python
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# Simple evaluation
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result = evaluate_script(function="() => document.title")
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# Async evaluation
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result = evaluate_script(function="""
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async () => {
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const response = await fetch('/loras/api/list');
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return await response.json();
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}
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""")
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# Check element existence
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exists = evaluate_script(function="""
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() => document.querySelector('.lora-card') !== null
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""")
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# Get element count
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count = evaluate_script(function="""
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() => document.querySelectorAll('.lora-card').length
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""")
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```
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## Network Monitoring
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```python
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# List all network requests
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requests = list_network_requests()
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|
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# Filter by resource type
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xhr_requests = list_network_requests(resourceTypes=["xhr", "fetch"])
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# Get specific request details
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details = get_network_request(reqid=123)
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# Include preserved requests from previous navigations
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all_requests = list_network_requests(includePreservedRequests=True)
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```
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|
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## Console Monitoring
|
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|
||||
```python
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# List all console messages
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messages = list_console_messages()
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# Filter by type
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errors = list_console_messages(types=["error", "warn"])
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|
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# Include preserved messages
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all_messages = list_console_messages(includePreservedMessages=True)
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# Get specific message
|
||||
details = get_console_message(msgid=1)
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```
|
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|
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## Performance Testing
|
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|
||||
```python
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# Start trace with page reload
|
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performance_start_trace(reload=True, autoStop=False)
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|
||||
# Start trace without reload
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performance_start_trace(reload=False, autoStop=True, filePath="trace.json.gz")
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|
||||
# Stop trace
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results = performance_stop_trace()
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|
||||
# Stop and save
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||||
performance_stop_trace(filePath="trace-results.json.gz")
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|
||||
# Analyze specific insight
|
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insight = performance_analyze_insight(
|
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insightSetId="results.insightSets[0].id",
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insightName="LCPBreakdown"
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||||
)
|
||||
```
|
||||
|
||||
## Page Management
|
||||
|
||||
```python
|
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# List open pages
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pages = list_pages()
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|
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# Select a page
|
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select_page(pageId=0, bringToFront=True)
|
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|
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# Create new page
|
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new_page(url="http://127.0.0.1:{PORT}/loras")
|
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|
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# Close page (keep at least one open!)
|
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close_page(pageId=1)
|
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|
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# Resize page
|
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resize_page(width=1920, height=1080)
|
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```
|
||||
|
||||
## Screenshots
|
||||
|
||||
```python
|
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# Full page screenshot
|
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take_screenshot(fullPage=True)
|
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|
||||
# Viewport screenshot
|
||||
take_screenshot()
|
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|
||||
# Element screenshot
|
||||
take_screenshot(uid="lora-card-1")
|
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|
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# Save to file
|
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take_screenshot(filePath="screenshots/page.png", format="png")
|
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|
||||
# 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:{PORT}/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}"
|
||||
```
|
||||
|
||||
## Troubleshooting
|
||||
|
||||
### Stale profile lock ("browser is already running" / `list_pages` fails)
|
||||
|
||||
A Chrome profile held by a stale Chrome from a prior MCP session makes `list_pages`
|
||||
fail with "browser is already running". Fix:
|
||||
|
||||
1. Find the stale Chrome that owns the profile dir (e.g. `~/.config/chrome-dev-profile`):
|
||||
```bash
|
||||
ps -ef | grep -i '[c]hrome.*user-data-dir'
|
||||
```
|
||||
2. Confirm it is a QA Chrome from a completed task (NOT the live ComfyUI server, NOT
|
||||
your current MCP instance).
|
||||
3. Kill ONLY that stale Chrome (`kill <stale-pid>`), then retry `list_pages`.
|
||||
|
||||
### Screenshot-write restrictions
|
||||
|
||||
The MCP may refuse to write into paths outside its configured workspace roots
|
||||
(e.g. `.omo/evidence/screenshots/` under a worktree that canonicalizes to an unmapped
|
||||
path). Save the screenshot to `/tmp` via the MCP, then copy it into the evidence dir:
|
||||
|
||||
```bash
|
||||
# MCP: take_screenshot(filePath="/tmp/<plan>-e2e/recipe-b-after.png", format="png")
|
||||
# Shell:
|
||||
mkdir -p <repo-root>/.omo/evidence/screenshots
|
||||
cp /tmp/<plan>-e2e/recipe-b-after.png <repo-root>/.omo/evidence/screenshots/
|
||||
```
|
||||
|
||||
### Time budgets & abort rule
|
||||
|
||||
See SKILL.md "Time Budgets & Abort Guidance": if a phase exceeds ~2x its budget or a
|
||||
tool call retries 3+ times in a row, STOP and report BLOCKED with the last observed
|
||||
state (server PID + `ss -tlnp`, page snapshot, last API response). Do not loop.
|
||||
@@ -0,0 +1,72 @@
|
||||
# Recipe Rematch/Repair E2E — Fixtures, Fresh State, Known Gaps
|
||||
|
||||
Specialized guidance for recipe rematch/repair E2E runs, extracted from the SKILL.md
|
||||
main flow. Read the SKILL.md SANDBOX section first — everything here assumes a
|
||||
sandboxed run.
|
||||
|
||||
## Fixture Rules (validated by the task-8 E2E)
|
||||
|
||||
Seed the **sandboxed** `recipes_path` with hand-written fixture recipes:
|
||||
|
||||
1. **Filename constraint**: each file MUST be named `f"{id}.recipe.json"` **and** the
|
||||
in-JSON `id` field MUST equal the filename. Discovery accepts any `*.recipe.json`,
|
||||
but persistence resolves the path via `get_recipe_json_path` and
|
||||
`_save_recipe_persistently` returns `False` on a mismatch → the fixture would be
|
||||
counted as an error.
|
||||
- `recipe-a.recipe.json` → in-JSON `"id": "recipe-a"`
|
||||
2. **File format**: mirror an existing recipe JSON — top-level `id`, `file_path`,
|
||||
`title`, `loras`, `fingerprint`, `gen_params`; lora entries per the persistence
|
||||
conventions (`hash`, `file_name`, `modelVersionId`, `isDeleted`, ...).
|
||||
3. **Companion image**: each recipe needs an image (e.g. a `.webp` generated with PIL)
|
||||
referenced by `file_path`, used for EXIF verification
|
||||
(`ExifUtils.append_recipe_metadata` writes a `"Recipe metadata: ..."` marker; a
|
||||
freshly generated `.webp` with no marker is the clean "untouched" control).
|
||||
4. **autov3 three-state contract**: for L3 (autov3-only, renamed-file) fixtures the
|
||||
local model's `.metadata.json` sidecar MUST have the `autov3` key **ABSENT** (the
|
||||
"unchecked" state), NOT `""` — `""` is the TERMINAL "checked but unavailable" state
|
||||
that L3 deliberately skips. The scanner computes + persists `autov3` from the file
|
||||
header during the normal library scan (`model_scanner.py` `_process_model_file`), so
|
||||
the live L3 match resolves through the local autov3/hash cache; the
|
||||
computed-autov3 branch for unchecked items is covered by the unit suite.
|
||||
5. **Fixture design for a rematch run** (mirrors the task-8 E2E):
|
||||
- `recipe-a`: lora entry `isDeleted=True`, `hash` = 12-char autov3 computed from the
|
||||
local model (`calculate_autov3`, `py/utils/file_utils.py`), whose local model file
|
||||
was RENAMED after the recipe was written so `file_name` differs (proves L3 match
|
||||
without filename).
|
||||
- `recipe-b`: parser-convention checkpoint entry (uses `id`, no `modelVersionId`)
|
||||
matching a local checkpoint via L2 — the local checkpoint's `.metadata.json` MUST
|
||||
carry civitai version data with that `id` so `version_index` contains it (L2
|
||||
cannot match otherwise).
|
||||
- `recipe-c`: healthy recipe (no deleted entries) → must remain untouched.
|
||||
|
||||
The scanner computes and persists model hashes during the library scan, so the sandbox
|
||||
model dirs just need the model files + `.metadata.json` sidecars. With
|
||||
`--settings-path`, all derived data lands under the sandbox settings dir (`cache/`,
|
||||
`backups/`, `logs/`, `stats/`, `wildcards/`), and NO `cache/` appears in the repo root.
|
||||
|
||||
## Fresh State Between Entry-Point Runs
|
||||
|
||||
Each entry point (global / per-recipe / selection-bulk) must start from the same
|
||||
deleted state. Between runs (keep a pristine copy in `<sandbox>/recipes-before/`):
|
||||
|
||||
```bash
|
||||
# 1. Reset fixtures to the before-state snapshot
|
||||
cp <sandbox>/recipes-before/*.recipe.json <sandbox>/recipes/
|
||||
# 2. Clear the recipe/FTS caches (with --settings-path these live under the sandbox
|
||||
# settings dir, NOT <repo-root>/cache)
|
||||
rm -f <sandbox>/settings/cache/recipe/*.sqlite
|
||||
rm -rf <sandbox>/settings/cache/fts/*
|
||||
# 3. Restart the server (fresh process, fresh scan)
|
||||
python .agents/skills/lora-manager-e2e/scripts/start_server.py \
|
||||
--port {PORT} --settings-path <sandbox>/settings --restart --wait --timeout 30 --detach
|
||||
# 4. Re-verify the server is listening + reload the browser page
|
||||
```
|
||||
|
||||
## Cancellation Testing (KNOWN GAP)
|
||||
|
||||
Testing the rematch-cancel path E2E requires a run long enough to cancel mid-flight. A
|
||||
tiny 3-recipe fixture set completes in **seconds** — too fast to reliably cancel. The
|
||||
cancel path is currently **unit-covered only** (`rematch_all_recipes` cancellation
|
||||
tests); do not block an E2E run on cancel-path verification. If you must attempt it,
|
||||
you would need an artificially large/deferred fixture set to create a cancellable
|
||||
window — treat this as a research task, not part of the standard E2E.
|
||||
@@ -0,0 +1,280 @@
|
||||
# LoRa Manager E2E Test Scenarios
|
||||
|
||||
This document provides detailed test scenarios for end-to-end validation of LoRa Manager features.
|
||||
|
||||
> **Run preconditions (from SKILL.md)**: every run uses the **sandboxed** standalone
|
||||
> server on a free port `{PORT}` (default candidate `8188`, only if actually free — pick
|
||||
> e.g. `8199` when `8188` is occupied by a live ComfyUI). Fixtures live in the sandboxed
|
||||
> `recipes_path` as `f"{id}.recipe.json"` files with matching in-JSON `id`; the real user
|
||||
> config and real library are never touched (record protection proof before/after).
|
||||
> Abort if a phase exceeds ~2x its budget or a tool call retries 3+ times (SKILL.md
|
||||
> "Time Budgets & Abort Guidance").
|
||||
|
||||
## 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:{PORT}/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:{PORT}/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:{PORT}/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 --port {PORT} --restart --wait --timeout 30 --detach`
|
||||
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"
|
||||
```
|
||||
+215
@@ -0,0 +1,215 @@
|
||||
#!/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.
|
||||
|
||||
Port: pick a FREE port for the run — 8188 is commonly occupied by a live
|
||||
ComfyUI (see the skill's Port Selection section). Set PORT below to e.g. 8199
|
||||
when 8188 is taken. Always run against a SANDBOXED standalone server.
|
||||
"""
|
||||
|
||||
import subprocess
|
||||
import sys
|
||||
|
||||
# Choose the E2E port. 8188 is only the default candidate; use 8199 (or any
|
||||
# free port checked with `ss -tlnp`) when 8188 is occupied by a live ComfyUI.
|
||||
PORT = "8188"
|
||||
|
||||
|
||||
def run_test():
|
||||
"""Run example E2E test flow."""
|
||||
|
||||
print("=" * 60)
|
||||
print("LoRa Manager E2E Test Example")
|
||||
print("=" * 60)
|
||||
|
||||
# Step 1: Start server (detached so it survives the shell)
|
||||
print("\n[1/5] Starting LoRa Manager standalone server...")
|
||||
result = subprocess.run(
|
||||
[sys.executable, "start_server.py", "--port", PORT, "--wait", "--timeout", "30", "--detach"],
|
||||
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(
|
||||
f"google-chrome --remote-debugging-port=9222 "
|
||||
f"--user-data-dir=/tmp/chrome-lora-manager http://127.0.0.1:{PORT}/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(
|
||||
f"""
|
||||
MCP Commands to execute:
|
||||
1. navigate_page(type="url", url="http://127.0.0.1:{PORT}/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(
|
||||
f"""
|
||||
Scenario: Change setting and verify after restart
|
||||
|
||||
Steps:
|
||||
1. Navigate to settings page
|
||||
- navigate_page(type="url", url="http://127.0.0.1:{PORT}/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", "--port", "{PORT}", "--restart", "--wait", "--detach"])
|
||||
|
||||
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:{PORT}/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(
|
||||
f"""
|
||||
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:{PORT}/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)
|
||||
@@ -215,26 +215,6 @@ The system runs in two modes:
|
||||
- Vanilla JS tests: `tests/frontend/**/*.test.js` with jsdom; setup in `tests/frontend/setup.js`
|
||||
- Vue widget tests: `vue-widgets/tests/**/*.test.ts` with jsdom + `@vue/test-utils`
|
||||
|
||||
### UI Verification (manual default)
|
||||
|
||||
UI/layout changes are verified by the user by eye — do NOT spin up a sandbox,
|
||||
standalone server, or browser automation to "prove" a visual fix. Ask the user to
|
||||
look instead. The full browser E2E ceremony (server + Chrome DevTools MCP +
|
||||
screenshots) is slow, token-heavy, and fragile; reserve it for genuine
|
||||
server+browser integration bugs, and only when the user explicitly agrees.
|
||||
|
||||
If a cross-layer issue ever needs a live server, the sandboxed helpers live in
|
||||
`scripts/e2e/` (`start_server.py`, `wait_for_server.py`). Non-negotiable rules:
|
||||
|
||||
- Always launch with `--settings-path <sandbox>/settings` and sandboxed
|
||||
`folder_paths` under `/tmp` — the repo folder is the real plugin folder and a
|
||||
`settings.json` there is read by the live instance. Never touch real config or
|
||||
real model libraries.
|
||||
- Never kill a process you did not start; `start_server.py` tracks its own PIDs
|
||||
via pidfile and refuses to touch unrelated processes on the port.
|
||||
- Abort after ~30 minutes or 3 consecutive tool failures; report `BLOCKED` with
|
||||
observed state instead of retrying blindly. Clean up sandbox and server after.
|
||||
|
||||
## Key Integration Points
|
||||
|
||||
- **Settings:** Stored in the user config directory (via `platformdirs`) or portable mode (`"use_portable_settings": true`)
|
||||
|
||||
@@ -137,7 +137,7 @@ and must be normalized. `en` = keep the English word as-is.
|
||||
|
||||
| Term | Use | Fix |
|
||||
|---|---|---|
|
||||
| recipe | Rezept/Rezepte | leftover English "Recipe" keys → Rezept (e.g. `toast.recipes.recipeSaved`) |
|
||||
| recipe | Rezept/Rezepte | 5 leftover English "Recipe" keys → Rezept (e.g. `globalContextMenu.repairRecipes.label`, `toast.recipes.recipeSaved`) |
|
||||
| base model | pick Basis-Modell or Basismodell | currently 27× hyphenated vs 15× closed |
|
||||
| metadata | Metadaten | 4 keys use "Modelldaten" (`onboarding.steps.fetch.title/content`) → Metadaten |
|
||||
| bulk | pick Massen- or Sammelmodus | `loras.controls.bulk.action` = "Massen" reads as "crowds" — use "Massenbearbeitung"/"Mehrfachauswahl" |
|
||||
@@ -193,7 +193,7 @@ and must be normalized. `en` = keep the English word as-is.
|
||||
| Checkpoint | Checkpoint or チェックポイント (pick one) | 3 variants: Checkpoint (~14), checkpoint lowercase (4), チェックポイント (4, e.g. `settings.priorityTags.modelTypes.checkpoint`) |
|
||||
| Embedding | Embedding | 4 keys lowercase "embedding" mid-sentence |
|
||||
| bulk | 一括 | `modals.checkUpdates.tip` "バルクモード" → 一括モード |
|
||||
| recipe counter | 件 or 個 | `globalContextMenu.rematchRecipes.success` uses 件, `.cancelled` uses 個 — unify |
|
||||
| recipe counter | 件 or 個 | `repairRecipes.success` uses 件, `.cancelled` uses 個 — unify |
|
||||
|
||||
### ko
|
||||
|
||||
|
||||
+19
-2
@@ -212,6 +212,13 @@
|
||||
"none": "Alle {typePlural} verfügen bereits über Lizenzmetadaten",
|
||||
"error": "Lizenzmetadaten für {typePlural} konnten nicht aktualisiert werden: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Rezept-Daten reparieren",
|
||||
"loading": "Rezept-Daten werden repariert...",
|
||||
"success": "{count} Rezepte erfolgreich repariert.",
|
||||
"cancelled": "Reparatur abgebrochen. {count} Rezepte wurden repariert.",
|
||||
"error": "Rezept-Reparatur fehlgeschlagen: {message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "Rezepte lokalen Modellen neu zuordnen",
|
||||
"loading": "Rezepte werden lokalen Modellen neu zugeordnet...",
|
||||
@@ -477,8 +484,6 @@
|
||||
"layoutSettings": {
|
||||
"groupByModel": "Nach Modell gruppieren",
|
||||
"groupByModelHelp": "Wenn aktiviert, wird nur die neueste Version jedes CivitAI-Modells als einzelne Karte angezeigt. Ältere Versionen werden ausgeblendet.",
|
||||
"stickyControls": "Aktionsleiste sichtbar halten",
|
||||
"stickyControlsHelp": "Wenn aktiviert, bleibt die Aktionsleiste (Aktualisieren, Herunterladen usw.) beim Scrollen zusammen mit der Breadcrumb-Navigation oben angeheftet.",
|
||||
"displayDensity": "Anzeige-Dichte",
|
||||
"displayDensityOptions": {
|
||||
"default": "Standard",
|
||||
@@ -814,6 +819,7 @@
|
||||
"setContentRating": "Inhaltsbewertung für alle festlegen",
|
||||
"copyAll": "Alle Syntax kopieren",
|
||||
"refreshAll": "Alle Metadaten aktualisieren",
|
||||
"repairMetadata": "Metadaten der Auswahl reparieren",
|
||||
"rematchMetadata": "Ausgewählte mit lokalen Modellen abgleichen",
|
||||
"reimportMetadata": "Aus Quelle neu importieren",
|
||||
"checkUpdates": "Auswahl auf Updates prüfen",
|
||||
@@ -869,6 +875,7 @@
|
||||
"replacePreview": "Vorschau ersetzen",
|
||||
"setContentRating": "Inhaltsbewertung festlegen",
|
||||
"moveToFolder": "In Ordner verschieben",
|
||||
"repairMetadata": "Metadaten reparieren",
|
||||
"rematchMetadata": "Mit lokalen Modellen abgleichen",
|
||||
"reimportMetadata": "Aus Quelle neu importieren",
|
||||
"excludeModel": "Modell ausschließen",
|
||||
@@ -1121,6 +1128,13 @@
|
||||
"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"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "Rezept wird aus Quelle neu importiert...",
|
||||
"success": "Rezept erfolgreich neu importiert",
|
||||
@@ -2222,6 +2236,9 @@
|
||||
"batchImportBrowseFailed": "Ordner konnte nicht durchsucht werden: {message}",
|
||||
"batchImportDirectorySelected": "Verzeichnis ausgewählt: {path}",
|
||||
"noRecipesSelected": "Keine Rezepte ausgewählt",
|
||||
"repairBulkComplete": "Reparatur abgeschlossen: {repaired} repariert, {skipped} übersprungen (von {total})",
|
||||
"repairBulkSkipped": "Keine Reparatur für die {total} ausgewählten Rezepte erforderlich",
|
||||
"repairBulkFailed": "Reparatur der ausgewählten Rezepte fehlgeschlagen: {message}",
|
||||
"rematchComplete": "{entries} Einträge in {recipes} Rezepten zugeordnet",
|
||||
"rematchCompleteErrors": "{entries} Einträge in {recipes} Rezepten zugeordnet, {failures} fehlgeschlagen",
|
||||
"rematchAllFailed": "Zuordnung fehlgeschlagen für {failures} von {total} ausgewählten Rezepten",
|
||||
|
||||
+19
-2
@@ -212,6 +212,13 @@
|
||||
"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}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "Rematch recipes to local models",
|
||||
"loading": "Rematching recipes to local models...",
|
||||
@@ -477,8 +484,6 @@
|
||||
"layoutSettings": {
|
||||
"groupByModel": "Group by Model",
|
||||
"groupByModelHelp": "When enabled, only the latest version of each CivitAI model is shown as a single card. Older versions are hidden.",
|
||||
"stickyControls": "Keep Action Bar Visible",
|
||||
"stickyControlsHelp": "When enabled, the action bar (Refresh, Download, etc.) stays pinned at the top while scrolling, together with the breadcrumb navigation.",
|
||||
"displayDensity": "Display Density",
|
||||
"displayDensityOptions": {
|
||||
"default": "Default",
|
||||
@@ -814,6 +819,7 @@
|
||||
"setContentRating": "Set Content Rating for Selected",
|
||||
"copyAll": "Copy Selected Syntax",
|
||||
"refreshAll": "Refresh Selected Metadata",
|
||||
"repairMetadata": "Repair Metadata for Selected",
|
||||
"rematchMetadata": "Rematch Selected to Local Models",
|
||||
"reimportMetadata": "Re-import from Source",
|
||||
"checkUpdates": "Check Updates for Selected",
|
||||
@@ -869,6 +875,7 @@
|
||||
"replacePreview": "Replace Preview",
|
||||
"setContentRating": "Set Content Rating",
|
||||
"moveToFolder": "Move to Folder",
|
||||
"repairMetadata": "Repair metadata",
|
||||
"rematchMetadata": "Rematch to local models",
|
||||
"reimportMetadata": "Re-import from Source",
|
||||
"excludeModel": "Exclude Model",
|
||||
@@ -1121,6 +1128,13 @@
|
||||
"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"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "Re-importing recipe from source...",
|
||||
"success": "Recipe re-imported successfully",
|
||||
@@ -2222,6 +2236,9 @@
|
||||
"batchImportBrowseFailed": "Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"noRecipesSelected": "No recipes selected",
|
||||
"repairBulkComplete": "Repair complete: {repaired} repaired, {skipped} skipped (of {total})",
|
||||
"repairBulkSkipped": "No repair needed for any of the {total} selected recipes",
|
||||
"repairBulkFailed": "Failed to repair selected recipes: {message}",
|
||||
"rematchComplete": "Matched {entries} entries across {recipes} recipes",
|
||||
"rematchCompleteErrors": "Matched {entries} entries across {recipes} recipes, {failures} failed",
|
||||
"rematchAllFailed": "Rematch failed for {failures} of {total} selected recipes",
|
||||
|
||||
+19
-2
@@ -212,6 +212,13 @@
|
||||
"none": "Todos los {typePlural} ya tienen metadatos de licencia",
|
||||
"error": "No se pudieron actualizar los metadatos de licencia de los {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}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "Reasociar recetas con modelos locales",
|
||||
"loading": "Reasociando recetas con modelos locales...",
|
||||
@@ -477,8 +484,6 @@
|
||||
"layoutSettings": {
|
||||
"groupByModel": "Agrupar por modelo",
|
||||
"groupByModelHelp": "Cuando está activado, solo se muestra la versión más reciente de cada modelo de CivitAI como una tarjeta única. Las versiones anteriores están ocultas.",
|
||||
"stickyControls": "Mantener visible la barra de acciones",
|
||||
"stickyControlsHelp": "Cuando está activado, la barra de acciones (Actualizar, Descargar, etc.) permanece fijada en la parte superior al desplazarse, junto con la navegación por rutas.",
|
||||
"displayDensity": "Densidad de visualización",
|
||||
"displayDensityOptions": {
|
||||
"default": "Predeterminado",
|
||||
@@ -814,6 +819,7 @@
|
||||
"setContentRating": "Establecer clasificación de contenido para todos",
|
||||
"copyAll": "Copiar toda la sintaxis",
|
||||
"refreshAll": "Actualizar todos los metadatos",
|
||||
"repairMetadata": "Reparar metadatos de la selección",
|
||||
"rematchMetadata": "Reasociar los seleccionados con modelos locales",
|
||||
"reimportMetadata": "Reimportar desde origen",
|
||||
"checkUpdates": "Comprobar actualizaciones para la selección",
|
||||
@@ -869,6 +875,7 @@
|
||||
"replacePreview": "Reemplazar vista previa",
|
||||
"setContentRating": "Establecer clasificación de contenido",
|
||||
"moveToFolder": "Mover a carpeta",
|
||||
"repairMetadata": "Reparar metadatos",
|
||||
"rematchMetadata": "Reasociar con modelos locales",
|
||||
"reimportMetadata": "Reimportar desde origen",
|
||||
"excludeModel": "Excluir modelo",
|
||||
@@ -1121,6 +1128,13 @@
|
||||
"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"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "Reimportando receta desde origen...",
|
||||
"success": "Receta reimportada exitosamente",
|
||||
@@ -2222,6 +2236,9 @@
|
||||
"batchImportBrowseFailed": "No se pudo examinar el directorio: {message}",
|
||||
"batchImportDirectorySelected": "Directorio seleccionado: {path}",
|
||||
"noRecipesSelected": "No se han seleccionado recetas",
|
||||
"repairBulkComplete": "Reparación completa: {repaired} reparadas, {skipped} omitidas (de {total})",
|
||||
"repairBulkSkipped": "No se necesita reparación para ninguna de las {total} recetas seleccionadas",
|
||||
"repairBulkFailed": "Error al reparar las recetas seleccionadas: {message}",
|
||||
"rematchComplete": "{entries} entradas asociadas en {recipes} recetas",
|
||||
"rematchCompleteErrors": "{entries} entradas asociadas en {recipes} recetas, {failures} fallidas",
|
||||
"rematchAllFailed": "Falló la reasociación de {failures} de {total} recetas seleccionadas",
|
||||
|
||||
+19
-2
@@ -212,6 +212,13 @@
|
||||
"none": "Tous les {typePlural} possèdent déjà des métadonnées de licence",
|
||||
"error": "Échec de l'actualisation des métadonnées de licence pour les {typePlural} : {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "Réparer les données de Recipes",
|
||||
"loading": "Réparation des données de Recipes...",
|
||||
"success": "{count} Recipes réparées avec succès.",
|
||||
"cancelled": "Réparation annulée. {count} Recipes ont été réparées.",
|
||||
"error": "Échec de la réparation des Recipes : {message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "Réassocier les Recipes aux modèles locaux",
|
||||
"loading": "Réassociation des Recipes aux modèles locaux...",
|
||||
@@ -477,8 +484,6 @@
|
||||
"layoutSettings": {
|
||||
"groupByModel": "Grouper par modèle",
|
||||
"groupByModelHelp": "Lorsque activé, seule la version la plus récente de chaque modèle CivitAI s'affiche sous forme de carte unique. Les versions plus anciennes sont masquées.",
|
||||
"stickyControls": "Garder la barre d'actions visible",
|
||||
"stickyControlsHelp": "Lorsque activé, la barre d'actions (Actualiser, Télécharger, etc.) reste épinglée en haut lors du défilement, avec la navigation par fil d'Ariane.",
|
||||
"displayDensity": "Densité d'affichage",
|
||||
"displayDensityOptions": {
|
||||
"default": "Par défaut",
|
||||
@@ -814,6 +819,7 @@
|
||||
"setContentRating": "Définir la classification du contenu pour tous",
|
||||
"copyAll": "Copier toute la syntaxe",
|
||||
"refreshAll": "Actualiser toutes les métadonnées",
|
||||
"repairMetadata": "Réparer les métadonnées de la sélection",
|
||||
"rematchMetadata": "Réassocier la sélection aux modèles locaux",
|
||||
"reimportMetadata": "Ré-importer depuis la source",
|
||||
"checkUpdates": "Vérifier les mises à jour pour la sélection",
|
||||
@@ -869,6 +875,7 @@
|
||||
"replacePreview": "Remplacer l'aperçu",
|
||||
"setContentRating": "Définir la classification du contenu",
|
||||
"moveToFolder": "Déplacer vers un dossier",
|
||||
"repairMetadata": "Réparer les métadonnées",
|
||||
"rematchMetadata": "Réassocier aux modèles locaux",
|
||||
"reimportMetadata": "Ré-importer depuis la source",
|
||||
"excludeModel": "Exclure le modèle",
|
||||
@@ -1121,6 +1128,13 @@
|
||||
"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 Recipe...",
|
||||
"success": "Métadonnées de la Recipe réparées avec succès",
|
||||
"skipped": "Recette déjà à la version la plus récente, aucune réparation nécessaire",
|
||||
"failed": "Échec de la réparation de la Recipe : {message}",
|
||||
"missingId": "Impossible de réparer la Recipe : ID de Recipe manquant"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "Ré-import de la Recipe depuis la source...",
|
||||
"success": "Recette ré-importée avec succès",
|
||||
@@ -2222,6 +2236,9 @@
|
||||
"batchImportBrowseFailed": "Échec de la navigation dans le dossier : {message}",
|
||||
"batchImportDirectorySelected": "Dossier sélectionné : {path}",
|
||||
"noRecipesSelected": "Aucune Recipe sélectionnée",
|
||||
"repairBulkComplete": "Réparation terminée : {repaired} réparée(s), {skipped} ignorée(s) (sur {total})",
|
||||
"repairBulkSkipped": "Aucune réparation nécessaire parmi les {total} Recipes sélectionnées",
|
||||
"repairBulkFailed": "Échec de la réparation des Recipes sélectionnées : {message}",
|
||||
"rematchComplete": "{entries} entrées associées dans {recipes} Recipes",
|
||||
"rematchCompleteErrors": "{entries} entrées associées dans {recipes} Recipes, {failures} échecs",
|
||||
"rematchAllFailed": "Échec de la réassociation de {failures} Recipes sélectionnées sur {total}",
|
||||
|
||||
+19
-2
@@ -212,6 +212,13 @@
|
||||
"none": "לכל ה-{typePlural} כבר יש מטא-נתוני רישיון",
|
||||
"error": "לא ניתן היה לרענן את מטא-נתוני הרישיון עבור {typePlural}: {message}"
|
||||
},
|
||||
"repairRecipes": {
|
||||
"label": "תיקון נתוני מתכונים",
|
||||
"loading": "מתקן נתוני מתכונים...",
|
||||
"success": "תוקנו בהצלחה {count} מתכונים.",
|
||||
"cancelled": "תיקון בוטל. {count} מתכונים תוקנו.",
|
||||
"error": "תיקון המתכונים נכשל: {message}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "התאמה מחדש של מתכונים למודלים מקומיים",
|
||||
"loading": "מתבצעת התאמה מחדש של מתכונים למודלים מקומיים...",
|
||||
@@ -477,8 +484,6 @@
|
||||
"layoutSettings": {
|
||||
"groupByModel": "קיבוץ לפי מודל",
|
||||
"groupByModelHelp": "כאשר מופעל, רק הגרסה העדכנית ביותר של כל מודל CivitAI מוצגת ככרטיס בודד. גרסאות ישנות יותר מוסתרות.",
|
||||
"stickyControls": "השארת סרגל הפעולות גלוי",
|
||||
"stickyControlsHelp": "כאשר מופעל, סרגל הפעולות (רענון, הורדה וכו') נשאר מוצמד לחלק העליון בעת גלילה, יחד עם ניווט פירורי הלחם.",
|
||||
"displayDensity": "צפיפות תצוגה",
|
||||
"displayDensityOptions": {
|
||||
"default": "ברירת מחדל",
|
||||
@@ -814,6 +819,7 @@
|
||||
"setContentRating": "הגדר דירוג תוכן לכל המודלים",
|
||||
"copyAll": "העתק את כל התחבירים",
|
||||
"refreshAll": "רענן את כל המטא-נתונים",
|
||||
"repairMetadata": "תקן מטא-נתונים עבור הנבחרים",
|
||||
"rematchMetadata": "התאמה מחדש של הנבחרים למודלים מקומיים",
|
||||
"reimportMetadata": "ייבא מחדש ממקור",
|
||||
"checkUpdates": "בדוק עדכונים לבחירה",
|
||||
@@ -869,6 +875,7 @@
|
||||
"replacePreview": "החלף תצוגה מקדימה",
|
||||
"setContentRating": "הגדר דירוג תוכן",
|
||||
"moveToFolder": "העבר לתיקייה",
|
||||
"repairMetadata": "תיקון מטא-נתונים",
|
||||
"rematchMetadata": "התאמה מחדש למודלים מקומיים",
|
||||
"reimportMetadata": "ייבא מחדש ממקור",
|
||||
"excludeModel": "החרג מודל",
|
||||
@@ -1121,6 +1128,13 @@
|
||||
"getInfoFailed": "קבלת מידע עבור LoRAs חסרים נכשלה",
|
||||
"prepareError": "שגיאה בהכנת LoRAs להורדה: {message}"
|
||||
},
|
||||
"repair": {
|
||||
"starting": "מתקן מטא-נתונים של מתכון...",
|
||||
"success": "מטא-נתונים של מתכון תוקן בהצלחה",
|
||||
"skipped": "המתכון כבר בגרסה העדכנית ביותר, אין צורך בתיקון",
|
||||
"failed": "תיקון המתכון נכשל: {message}",
|
||||
"missingId": "לא ניתן לתקן את המתכון: חסר מזהה מתכון"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "מייבא מתכון מחדש מהמקור...",
|
||||
"success": "המתכון יובא מחדש בהצלחה",
|
||||
@@ -2222,6 +2236,9 @@
|
||||
"batchImportBrowseFailed": "לא ניתן היה לעיין בתיקייה: {message}",
|
||||
"batchImportDirectorySelected": "נבחרה תיקייה: {path}",
|
||||
"noRecipesSelected": "לא נבחרו מתכונים",
|
||||
"repairBulkComplete": "התיקון הושלם: {repaired} תוקנו, {skipped} דולגו (מתוך {total})",
|
||||
"repairBulkSkipped": "אין צורך בתיקון עבור {total} המתכונים הנבחרים",
|
||||
"repairBulkFailed": "תיקון המתכונים הנבחרים נכשל: {message}",
|
||||
"rematchComplete": "הותאמו {entries} פריטים ב־{recipes} מתכונים",
|
||||
"rematchCompleteErrors": "הותאמו {entries} פריטים ב־{recipes} מתכונים, {failures} נכשלו",
|
||||
"rematchAllFailed": "ההתאמה נכשלה עבור {failures} מתוך {total} מתכונים שנבחרו",
|
||||
|
||||
+19
-2
@@ -212,6 +212,13 @@
|
||||
"none": "すべての{typePlural}には既にライセンスメタデータがあります",
|
||||
"error": "{typePlural}のライセンスメタデータを更新できませんでした: {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}件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}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "レシピをローカルモデルに再マッチング",
|
||||
"loading": "レシピをローカルモデルに再マッチングしています...",
|
||||
@@ -477,8 +484,6 @@
|
||||
"layoutSettings": {
|
||||
"groupByModel": "モデルでグループ化",
|
||||
"groupByModelHelp": "有効にすると、各CivitAIモデルの最新バージョンのみが1枚のカードとして表示され、古いバージョンは非表示になります。",
|
||||
"stickyControls": "アクションバーを常に表示",
|
||||
"stickyControlsHelp": "有効にすると、アクションバー（更新、ダウンロードなど）がスクロール時にパンくずナビゲーションと一緒に画面上部に固定されます。",
|
||||
"displayDensity": "表示密度",
|
||||
"displayDensityOptions": {
|
||||
"default": "デフォルト",
|
||||
@@ -814,6 +819,7 @@
|
||||
"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",
|
||||
"repairMetadata": "選択したレシピのメタデータを修復",
|
||||
"rematchMetadata": "選択したモデルをローカルモデルに再マッチング",
|
||||
"reimportMetadata": "ソースから再インポート",
|
||||
"checkUpdates": "選択項目の更新を確認",
|
||||
@@ -869,6 +875,7 @@
|
||||
"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",
|
||||
"rematchMetadata": "ローカルモデルに再マッチング",
|
||||
"reimportMetadata": "ソースから再インポート",
|
||||
"excludeModel": "モデルを除外",
|
||||
@@ -1121,6 +1128,13 @@
|
||||
"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"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "ソースからレシピを再インポート中...",
|
||||
"success": "レシピの再インポートが完了しました",
|
||||
@@ -2222,6 +2236,9 @@
|
||||
"batchImportBrowseFailed": "フォルダを参照できませんでした: {message}",
|
||||
"batchImportDirectorySelected": "選択されたフォルダ: {path}",
|
||||
"noRecipesSelected": "レシピが選択されていません",
|
||||
"repairBulkComplete": "修復完了：{repaired} 件修復、{skipped} 件スキップ（合計 {total} 件）",
|
||||
"repairBulkSkipped": "選択した {total} 件のレシピは修復不要です",
|
||||
"repairBulkFailed": "選択したレシピの修復に失敗しました：{message}",
|
||||
"rematchComplete": "{recipes} 件のレシピで {entries} エントリをマッチングしました",
|
||||
"rematchCompleteErrors": "{recipes} 件のレシピで {entries} エントリをマッチングしました（{failures} 件失敗）",
|
||||
"rematchAllFailed": "選択した {total} 件中 {failures} 件のレシピの再マッチングに失敗しました",
|
||||
|
||||
+19
-2
@@ -212,6 +212,13 @@
|
||||
"none": "모든 {typePlural}에 이미 라이선스 메타데이터가 있습니다",
|
||||
"error": "{typePlural}의 라이선스 메타데이터를 새로고침하지 못했습니다: {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}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "레시피를 로컬 모델에 다시 매칭",
|
||||
"loading": "레시피를 로컬 모델에 다시 매칭하는 중...",
|
||||
@@ -477,8 +484,6 @@
|
||||
"layoutSettings": {
|
||||
"groupByModel": "모델별 그룹화",
|
||||
"groupByModelHelp": "활성화하면 각 CivitAI 모델의 최신 버전만 단일 카드로 표시되며, 이전 버전은 숨겨집니다.",
|
||||
"stickyControls": "작업 표시줄 항상 표시",
|
||||
"stickyControlsHelp": "활성화하면 작업 표시줄(새로고침, 다운로드 등)이 스크롤 시 브레드크럼 내비게이션과 함께 상단에 고정됩니다.",
|
||||
"displayDensity": "표시 밀도",
|
||||
"displayDensityOptions": {
|
||||
"default": "기본",
|
||||
@@ -814,6 +819,7 @@
|
||||
"setContentRating": "모든 모델에 콘텐츠 등급 설정",
|
||||
"copyAll": "모든 문법 복사",
|
||||
"refreshAll": "모든 메타데이터 새로고침",
|
||||
"repairMetadata": "선택한 레시피 메타데이터 복구",
|
||||
"rematchMetadata": "선택 항목을 로컬 모델에 다시 매칭",
|
||||
"reimportMetadata": "소스에서 다시 가져오기",
|
||||
"checkUpdates": "선택 항목 업데이트 확인",
|
||||
@@ -869,6 +875,7 @@
|
||||
"replacePreview": "미리보기 교체",
|
||||
"setContentRating": "콘텐츠 등급 설정",
|
||||
"moveToFolder": "폴더로 이동",
|
||||
"repairMetadata": "메타데이터 복구",
|
||||
"rematchMetadata": "로컬 모델에 다시 매칭",
|
||||
"reimportMetadata": "소스에서 다시 가져오기",
|
||||
"excludeModel": "모델 제외",
|
||||
@@ -1121,6 +1128,13 @@
|
||||
"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"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "소스에서 레시피를 다시 가져오는 중...",
|
||||
"success": "레시피를 다시 가져왔습니다",
|
||||
@@ -2222,6 +2236,9 @@
|
||||
"batchImportBrowseFailed": "폴더를 찾아보지 못했습니다: {message}",
|
||||
"batchImportDirectorySelected": "선택한 폴더: {path}",
|
||||
"noRecipesSelected": "선택한 레시피가 없습니다",
|
||||
"repairBulkComplete": "복구 완료: {repaired}개 복구, {skipped}개 건너뜀 (총 {total}개)",
|
||||
"repairBulkSkipped": "선택한 {total}개 레시피는 복구가 필요하지 않습니다",
|
||||
"repairBulkFailed": "선택한 레시피 복구 실패: {message}",
|
||||
"rematchComplete": "{recipes}개 레시피에서 {entries}개 항목이 매칭되었습니다",
|
||||
"rematchCompleteErrors": "{recipes}개 레시피에서 {entries}개 항목이 매칭되었습니다. {failures}개 실패",
|
||||
"rematchAllFailed": "선택한 {total}개 레시피 중 {failures}개 재매칭 실패",
|
||||
|
||||
+19
-2
@@ -212,6 +212,13 @@
|
||||
"none": "У всех {typePlural} уже есть метаданные лицензии",
|
||||
"error": "Не удалось обновить метаданные лицензии для {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}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "Повторное сопоставление рецептов с локальными моделями",
|
||||
"loading": "Повторное сопоставление рецептов с локальными моделями...",
|
||||
@@ -477,8 +484,6 @@
|
||||
"layoutSettings": {
|
||||
"groupByModel": "Группировать по модели",
|
||||
"groupByModelHelp": "При включении отображается только последняя версия каждой модели CivitAI в виде одной карточки. Старые версии скрыты.",
|
||||
"stickyControls": "Держать панель действий видимой",
|
||||
"stickyControlsHelp": "При включении панель действий (Обновить, Загрузить и т. д.) остаётся закреплённой вверху при прокрутке вместе с навигацией по папкам.",
|
||||
"displayDensity": "Плотность отображения",
|
||||
"displayDensityOptions": {
|
||||
"default": "По умолчанию",
|
||||
@@ -814,6 +819,7 @@
|
||||
"setContentRating": "Установить рейтинг контента для всех",
|
||||
"copyAll": "Копировать весь синтаксис",
|
||||
"refreshAll": "Обновить все метаданные",
|
||||
"repairMetadata": "Восстановить метаданные для выбранных",
|
||||
"rematchMetadata": "Сопоставить выбранные с локальными моделями",
|
||||
"reimportMetadata": "Переимпортировать из источника",
|
||||
"checkUpdates": "Проверить обновления для выбранных",
|
||||
@@ -869,6 +875,7 @@
|
||||
"replacePreview": "Заменить превью",
|
||||
"setContentRating": "Установить рейтинг контента",
|
||||
"moveToFolder": "Переместить в папку",
|
||||
"repairMetadata": "Восстановить метаданные",
|
||||
"rematchMetadata": "Сопоставить с локальными моделями",
|
||||
"reimportMetadata": "Переимпортировать из источника",
|
||||
"excludeModel": "Исключить модель",
|
||||
@@ -1121,6 +1128,13 @@
|
||||
"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"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "Переимпорт рецепта из источника...",
|
||||
"success": "Рецепт успешно переимпортирован",
|
||||
@@ -2222,6 +2236,9 @@
|
||||
"batchImportBrowseFailed": "Не удалось открыть папку: {message}",
|
||||
"batchImportDirectorySelected": "Выбрана папка: {path}",
|
||||
"noRecipesSelected": "Рецепты не выбраны",
|
||||
"repairBulkComplete": "Восстановление завершено: {repaired} восстановлено, {skipped} пропущено (из {total})",
|
||||
"repairBulkSkipped": "Ни один из {total} выбранных рецептов не требует восстановления",
|
||||
"repairBulkFailed": "Не удалось восстановить выбранные рецепты: {message}",
|
||||
"rematchComplete": "Сопоставлено записей: {entries} в рецептах: {recipes}",
|
||||
"rematchCompleteErrors": "Сопоставлено записей: {entries} в рецептах: {recipes}, ошибок: {failures}",
|
||||
"rematchAllFailed": "Не удалось сопоставить: {failures} из {total} выбранных рецептов",
|
||||
|
||||
+19
-2
@@ -212,6 +212,13 @@
|
||||
"none": "所有 {typePlural} 都已具备许可证元数据",
|
||||
"error": "刷新 {typePlural} 的许可证元数据失败：{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}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "将配方重新匹配到本地模型",
|
||||
"loading": "正在将配方重新匹配到本地模型...",
|
||||
@@ -477,8 +484,6 @@
|
||||
"layoutSettings": {
|
||||
"groupByModel": "按模型分组",
|
||||
"groupByModelHelp": "开启后，每个 CivitAI 模型仅显示最新版本的单张卡片，旧版本将被隐藏。",
|
||||
"stickyControls": "保持操作栏可见",
|
||||
"stickyControlsHelp": "开启后，操作栏（刷新、下载等）会在滚动时与路径导航一起固定在页面顶部。",
|
||||
"displayDensity": "显示密度",
|
||||
"displayDensityOptions": {
|
||||
"default": "默认",
|
||||
@@ -814,6 +819,7 @@
|
||||
"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",
|
||||
"repairMetadata": "修复所选中元数据",
|
||||
"rematchMetadata": "将所选中重新匹配到本地模型",
|
||||
"reimportMetadata": "从源重新导入",
|
||||
"checkUpdates": "检查所选更新",
|
||||
@@ -869,6 +875,7 @@
|
||||
"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",
|
||||
"rematchMetadata": "重新匹配到本地模型",
|
||||
"reimportMetadata": "从源重新导入",
|
||||
"excludeModel": "排除模型",
|
||||
@@ -1121,6 +1128,13 @@
|
||||
"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"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "正在从源重新导入配方...",
|
||||
"success": "配方已从源重新导入成功",
|
||||
@@ -2222,6 +2236,9 @@
|
||||
"batchImportBrowseFailed": "浏览目录失败：{message}",
|
||||
"batchImportDirectorySelected": "已选择目录：{path}",
|
||||
"noRecipesSelected": "未选择任何配方",
|
||||
"repairBulkComplete": "修复完成：{repaired} 个已修复，{skipped} 个已跳过（共 {total} 个）",
|
||||
"repairBulkSkipped": "所选 {total} 个配方无需修复",
|
||||
"repairBulkFailed": "修复所选配方失败：{message}",
|
||||
"rematchComplete": "已匹配 {entries} 个条目，涉及 {recipes} 个配方",
|
||||
"rematchCompleteErrors": "已匹配 {entries} 个条目，涉及 {recipes} 个配方，{failures} 个失败",
|
||||
"rematchAllFailed": "{failures}/{total} 个所选配方重新匹配失败",
|
||||
|
||||
+19
-2
@@ -212,6 +212,13 @@
|
||||
"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}"
|
||||
},
|
||||
"rematchRecipes": {
|
||||
"label": "將配方重新匹配到本地模型",
|
||||
"loading": "正在將配方重新匹配到本地模型...",
|
||||
@@ -477,8 +484,6 @@
|
||||
"layoutSettings": {
|
||||
"groupByModel": "按模型分組",
|
||||
"groupByModelHelp": "啟用後，每個 CivitAI 模型僅顯示最新版本的單張卡片，舊版本將被隱藏。",
|
||||
"stickyControls": "保持操作列可見",
|
||||
"stickyControlsHelp": "啟用後，操作列（重新整理、下載等）會在捲動時與麵包屑導覽一起固定在頁面頂端。",
|
||||
"displayDensity": "顯示密度",
|
||||
"displayDensityOptions": {
|
||||
"default": "預設",
|
||||
@@ -814,6 +819,7 @@
|
||||
"setContentRating": "為全部設定內容分級",
|
||||
"copyAll": "複製全部語法",
|
||||
"refreshAll": "刷新全部 metadata",
|
||||
"repairMetadata": "修復所選中元數據",
|
||||
"rematchMetadata": "將所選中重新匹配到本地模型",
|
||||
"reimportMetadata": "從來源重新匯入",
|
||||
"checkUpdates": "檢查所選更新",
|
||||
@@ -869,6 +875,7 @@
|
||||
"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",
|
||||
"rematchMetadata": "重新匹配到本地模型",
|
||||
"reimportMetadata": "從來源重新匯入",
|
||||
"excludeModel": "排除模型",
|
||||
@@ -1121,6 +1128,13 @@
|
||||
"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"
|
||||
},
|
||||
"reimport": {
|
||||
"starting": "正在從來源重新匯入配方...",
|
||||
"success": "配方已從來源重新匯入成功",
|
||||
@@ -2222,6 +2236,9 @@
|
||||
"batchImportBrowseFailed": "瀏覽目錄失敗：{message}",
|
||||
"batchImportDirectorySelected": "已選擇目錄：{path}",
|
||||
"noRecipesSelected": "未選取任何配方",
|
||||
"repairBulkComplete": "修復完成：{repaired} 個已修復，{skipped} 個已跳過（共 {total} 個）",
|
||||
"repairBulkSkipped": "所選 {total} 個配方無需修復",
|
||||
"repairBulkFailed": "修復所選配方失敗：{message}",
|
||||
"rematchComplete": "已匹配 {entries} 個條目，涉及 {recipes} 個配方",
|
||||
"rematchCompleteErrors": "已匹配 {entries} 個條目，涉及 {recipes} 個配方，{failures} 個失敗",
|
||||
"rematchAllFailed": "{failures}/{total} 個所選配方重新匹配失敗",
|
||||
|
||||
@@ -129,6 +129,11 @@ class RecipeHandlerSet:
|
||||
"get_recipes_for_checkpoint": self.query.get_recipes_for_checkpoint,
|
||||
"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,
|
||||
"repair_recipes_bulk": self.management.repair_recipes_bulk,
|
||||
"get_repair_progress": self.management.get_repair_progress,
|
||||
"rematch_recipes": self.management.rematch_recipes,
|
||||
"cancel_rematch": self.management.cancel_rematch,
|
||||
"rematch_recipe": self.management.rematch_recipe,
|
||||
@@ -791,6 +796,157 @@ 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_recipes_bulk(self, request: web.Request) -> web.Response:
|
||||
"""Bulk repair metadata for multiple recipes by their IDs.
|
||||
|
||||
Accepts a JSON body with a "recipe_ids" array and iterates
|
||||
repair_recipe_by_id over each entry, collecting statistics.
|
||||
"""
|
||||
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,
|
||||
)
|
||||
|
||||
data = await request.json()
|
||||
recipe_ids = data.get("recipe_ids", [])
|
||||
if not recipe_ids:
|
||||
return web.json_response(
|
||||
{"success": False, "error": "recipe_ids are required"},
|
||||
status=400,
|
||||
)
|
||||
|
||||
total = len(recipe_ids)
|
||||
repaired = 0
|
||||
skipped = 0
|
||||
errors = 0
|
||||
recipes = []
|
||||
|
||||
for recipe_id in recipe_ids:
|
||||
try:
|
||||
result = await recipe_scanner.repair_recipe_by_id(recipe_id)
|
||||
if result.get("success"):
|
||||
repaired += result.get("repaired", 0)
|
||||
skipped += result.get("skipped", 0)
|
||||
if result.get("recipe"):
|
||||
recipes.append(result["recipe"])
|
||||
else:
|
||||
errors += 1
|
||||
except RecipeNotFoundError:
|
||||
skipped += 1
|
||||
except Exception as exc:
|
||||
self._logger.error(
|
||||
"Error repairing recipe %s: %s", recipe_id, exc
|
||||
)
|
||||
errors += 1
|
||||
|
||||
return web.json_response({
|
||||
"success": True,
|
||||
"total": total,
|
||||
"repaired": repaired,
|
||||
"skipped": skipped,
|
||||
"errors": errors,
|
||||
"recipes": recipes,
|
||||
})
|
||||
except Exception as exc:
|
||||
self._logger.error(
|
||||
"Error performing bulk 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 rematch_recipes(self, request: web.Request) -> web.Response:
|
||||
try:
|
||||
await self._ensure_dependencies_ready()
|
||||
@@ -802,9 +958,12 @@ class RecipeManagementHandler:
|
||||
)
|
||||
|
||||
# Mutual exclusion: a global rematch cannot start while a rematch
|
||||
# is already running — both mutate recipes under the same
|
||||
# mutation lock.
|
||||
if self._ws_manager.is_recipe_rematch_running():
|
||||
# OR a repair is already running — both mutate recipes under the
|
||||
# same mutation lock.
|
||||
if (
|
||||
self._ws_manager.is_recipe_rematch_running()
|
||||
or self._ws_manager.is_recipe_repair_running()
|
||||
):
|
||||
return web.json_response(
|
||||
{"success": False, "error": "Recipe rematch already in progress"},
|
||||
status=409,
|
||||
@@ -1072,6 +1231,18 @@ class RecipeManagementHandler:
|
||||
)
|
||||
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()
|
||||
|
||||
@@ -84,6 +84,11 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
|
||||
"GET", "/api/lm/recipes/for-checkpoint", "get_recipes_for_checkpoint"
|
||||
),
|
||||
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("POST", "/api/lm/recipes/repair-bulk", "repair_recipes_bulk"),
|
||||
RouteDefinition("GET", "/api/lm/recipes/repair-progress", "get_repair_progress"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/rematch", "rematch_recipes"),
|
||||
RouteDefinition("POST", "/api/lm/recipes/rematch-bulk", "rematch_recipes_bulk"),
|
||||
RouteDefinition("POST", "/api/lm/recipe/{recipe_id}/rematch", "rematch_recipe"),
|
||||
|
||||
@@ -58,7 +58,7 @@ async def _load_model_catalog() -> Dict[str, List[str]]:
|
||||
logger.warning("Model catalog returned HTTP %s", resp.status)
|
||||
return _catalog_cache or {}
|
||||
data = await resp.json()
|
||||
except (aiohttp.ClientError, asyncio.TimeoutError, json.JSONDecodeError, UnicodeDecodeError) as exc:
|
||||
except (aiohttp.ClientError, asyncio.TimeoutError, json.JSONDecodeError) as exc:
|
||||
logger.warning("Failed to fetch model catalog: %s", exc)
|
||||
return _catalog_cache or {}
|
||||
|
||||
@@ -131,7 +131,7 @@ async def fetch_ollama_models(api_base: str) -> List[str]:
|
||||
logger.debug("Ollama API returned HTTP %s from %s", resp.status, api_base)
|
||||
return []
|
||||
data = await resp.json()
|
||||
except (aiohttp.ClientError, asyncio.TimeoutError, json.JSONDecodeError, UnicodeDecodeError) as exc:
|
||||
except (aiohttp.ClientError, asyncio.TimeoutError, json.JSONDecodeError) as exc:
|
||||
logger.debug("Ollama not reachable at %s: %s", api_base, exc)
|
||||
return []
|
||||
|
||||
|
||||
@@ -52,6 +52,7 @@ class PersistentRecipeCache:
|
||||
"file_mtime",
|
||||
"file_size",
|
||||
"favorite",
|
||||
"repair_version",
|
||||
"preview_nsfw_level",
|
||||
"loras_json",
|
||||
"checkpoint_json",
|
||||
@@ -441,6 +442,7 @@ class PersistentRecipeCache:
|
||||
file_mtime REAL,
|
||||
file_size INTEGER,
|
||||
favorite INTEGER DEFAULT 0,
|
||||
repair_version INTEGER DEFAULT 0,
|
||||
preview_nsfw_level INTEGER DEFAULT 0,
|
||||
loras_json TEXT,
|
||||
checkpoint_json TEXT,
|
||||
@@ -539,6 +541,7 @@ class PersistentRecipeCache:
|
||||
file_mtime,
|
||||
file_size,
|
||||
1 if recipe.get("favorite") else 0,
|
||||
int(recipe.get("repair_version") or 0),
|
||||
int(recipe.get("preview_nsfw_level") or 0),
|
||||
loras_json,
|
||||
checkpoint_json,
|
||||
@@ -596,6 +599,7 @@ class PersistentRecipeCache:
|
||||
"created_date": row["created_date"] or 0.0,
|
||||
"modified": row["modified"] or 0.0,
|
||||
"favorite": bool(row["favorite"]),
|
||||
"repair_version": row["repair_version"] or 0,
|
||||
"preview_nsfw_level": row["preview_nsfw_level"] or 0,
|
||||
"has_workflow": bool(row["has_workflow"]),
|
||||
"loras": loras,
|
||||
|
||||
@@ -94,6 +94,8 @@ class RecipeScanner:
|
||||
cls._instance._civitai_client = None # Will be lazily initialized
|
||||
return cls._instance
|
||||
|
||||
REPAIR_VERSION = 4
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
lora_scanner: Optional[LoraScanner] = None,
|
||||
@@ -809,6 +811,207 @@ class RecipeScanner:
|
||||
"""Check if cancellation has been requested."""
|
||||
return self._cancel_requested
|
||||
|
||||
async def repair_all_recipes(
|
||||
self, progress_callback: Optional[Callable[[Dict[str, Any]], Any]] = None
|
||||
) -> Dict[str, Any]:
|
||||
"""Repair all recipes by enrichment with Civitai and embedded metadata.
|
||||
|
||||
Args:
|
||||
persistence_service: Service for saving updated recipes
|
||||
progress_callback: Optional callback for progress updates
|
||||
|
||||
Returns:
|
||||
Dict summary of repair results
|
||||
"""
|
||||
if progress_callback:
|
||||
await progress_callback({"status": "started"})
|
||||
async with self._mutation_lock:
|
||||
cache = await self.get_cached_data()
|
||||
all_recipes = list(cache.raw_data)
|
||||
total = len(all_recipes)
|
||||
repaired_count = 0
|
||||
skipped_count = 0
|
||||
errors_count = 0
|
||||
|
||||
civitai_client = await self._get_civitai_client()
|
||||
self.reset_cancellation()
|
||||
|
||||
for i, recipe in enumerate(all_recipes):
|
||||
if self.is_cancelled():
|
||||
logger.info("Recipe repair cancelled by user")
|
||||
if progress_callback:
|
||||
await progress_callback(
|
||||
{
|
||||
"status": "cancelled",
|
||||
"current": i,
|
||||
"total": total,
|
||||
"repaired": repaired_count,
|
||||
"skipped": skipped_count,
|
||||
"errors": errors_count,
|
||||
}
|
||||
)
|
||||
return {
|
||||
"success": False,
|
||||
"status": "cancelled",
|
||||
"repaired": repaired_count,
|
||||
"skipped": skipped_count,
|
||||
"errors": errors_count,
|
||||
"total": total,
|
||||
}
|
||||
|
||||
try:
|
||||
# Report progress
|
||||
if progress_callback:
|
||||
await progress_callback(
|
||||
{
|
||||
"status": "processing",
|
||||
"current": i + 1,
|
||||
"total": total,
|
||||
"recipe_name": recipe.get("name", "Unknown"),
|
||||
}
|
||||
)
|
||||
|
||||
if await self._repair_single_recipe(recipe, civitai_client):
|
||||
repaired_count += 1
|
||||
else:
|
||||
skipped_count += 1
|
||||
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
f"Error repairing recipe {recipe.get('file_path')}: {e}"
|
||||
)
|
||||
errors_count += 1
|
||||
|
||||
# Final progress update
|
||||
if progress_callback:
|
||||
await progress_callback(
|
||||
{
|
||||
"status": "completed",
|
||||
"repaired": repaired_count,
|
||||
"skipped": skipped_count,
|
||||
"errors": errors_count,
|
||||
"total": total,
|
||||
}
|
||||
)
|
||||
|
||||
return {
|
||||
"success": True,
|
||||
"repaired": repaired_count,
|
||||
"skipped": skipped_count,
|
||||
"errors": errors_count,
|
||||
"total": total,
|
||||
}
|
||||
|
||||
async def repair_recipe_by_id(self, recipe_id: str) -> Dict[str, Any]:
|
||||
"""Repair a single recipe by its ID.
|
||||
|
||||
Args:
|
||||
recipe_id: ID of the recipe to repair
|
||||
|
||||
Returns:
|
||||
Dict summary of repair result
|
||||
"""
|
||||
async with self._mutation_lock:
|
||||
# Get raw recipe from cache directly to avoid formatted fields
|
||||
cache = await self.get_cached_data()
|
||||
recipe = next(
|
||||
(r for r in cache.raw_data if str(r.get("id", "")) == recipe_id), None
|
||||
)
|
||||
|
||||
if not recipe:
|
||||
raise RecipeNotFoundError(f"Recipe {recipe_id} not found")
|
||||
|
||||
civitai_client = await self._get_civitai_client()
|
||||
success = await self._repair_single_recipe(recipe, civitai_client)
|
||||
|
||||
# If successfully repaired, we should return the formatted version for the UI
|
||||
return {
|
||||
"success": True,
|
||||
"repaired": 1 if success else 0,
|
||||
"skipped": 0 if success else 1,
|
||||
"recipe": await self.get_recipe_by_id(recipe_id) if success else recipe,
|
||||
}
|
||||
|
||||
async def _repair_single_recipe(
|
||||
self, recipe: Dict[str, Any], civitai_client: Any
|
||||
) -> bool:
|
||||
"""Internal helper to repair a single recipe object.
|
||||
|
||||
Args:
|
||||
recipe: The recipe dictionary to repair (modified in-place)
|
||||
civitai_client: Authenticated Civitai client
|
||||
|
||||
Returns:
|
||||
bool: True if recipe was repaired or updated, False if skipped
|
||||
"""
|
||||
# 1. Skip if already at latest repair version
|
||||
if recipe.get("repair_version", 0) >= self.REPAIR_VERSION:
|
||||
return False
|
||||
|
||||
# 1.5 Detect and clear corrupted checkpoint (LoRA data saved as checkpoint).
|
||||
# A checkpoint whose modelVersionId also appears in a LoRA entry is
|
||||
# definitely wrong — the CivitAI import code used to pick
|
||||
# modelVersionIds[0] as the checkpoint, which was often a LoRA.
|
||||
# Clearing it lets the enrichment flow re-resolve the correct
|
||||
# checkpoint from CivitAI image metadata.
|
||||
cp = recipe.get("checkpoint")
|
||||
lora_mvids = {
|
||||
l.get("modelVersionId")
|
||||
for l in recipe.get("loras", [])
|
||||
if l.get("modelVersionId")
|
||||
}
|
||||
if cp and cp.get("modelVersionId") and cp["modelVersionId"] in lora_mvids:
|
||||
cp_mvid = cp["modelVersionId"]
|
||||
logger.info(
|
||||
"Recipe %s: checkpoint modelVersionId %s matches a LoRA — "
|
||||
"clearing corrupted checkpoint and removing matching LoRA entry",
|
||||
recipe.get("id"),
|
||||
cp_mvid,
|
||||
)
|
||||
recipe["checkpoint"] = None
|
||||
recipe["loras"] = [
|
||||
l for l in recipe.get("loras", [])
|
||||
if l.get("modelVersionId") != cp_mvid
|
||||
]
|
||||
|
||||
# 2. Identification: Is repair needed?
|
||||
has_checkpoint = (
|
||||
"checkpoint" in recipe
|
||||
and recipe["checkpoint"]
|
||||
and recipe["checkpoint"].get("name")
|
||||
)
|
||||
gen_params = recipe.get("gen_params", {})
|
||||
has_prompt = bool(gen_params.get("prompt"))
|
||||
|
||||
needs_repair = not has_checkpoint or not has_prompt
|
||||
|
||||
if not needs_repair:
|
||||
# Even if no repair needed, we mark it with version if it was processed
|
||||
# Always update and save because if we are here, the version is old (checked in step 1)
|
||||
recipe["repair_version"] = self.REPAIR_VERSION
|
||||
await self._save_recipe_persistently(recipe)
|
||||
return True
|
||||
|
||||
# 3. Use Enricher to repair/enrich
|
||||
try:
|
||||
from ..recipes.enrichment import RecipeEnricher
|
||||
|
||||
updated = await RecipeEnricher.enrich_recipe(recipe, civitai_client)
|
||||
except Exception as e:
|
||||
logger.error(f"Error enriching recipe {recipe.get('id')}: {e}")
|
||||
updated = False
|
||||
|
||||
# 4. Mark version and save if updated or just marking version
|
||||
# If we updated it, OR if the version is old (which we know it is if we are here), save it.
|
||||
# Actually, if we are here and updated is False, it means we tried to repair but couldn't/didn't need to.
|
||||
# But we still want to mark it as processed so we don't try again until version bump.
|
||||
if updated or recipe.get("repair_version", 0) < self.REPAIR_VERSION:
|
||||
recipe["repair_version"] = self.REPAIR_VERSION
|
||||
await self._save_recipe_persistently(recipe)
|
||||
return True
|
||||
|
||||
return False
|
||||
|
||||
async def rematch_recipe_by_id(self, recipe_id: str) -> Dict[str, Any]:
|
||||
"""Rematch a single recipe's deleted lora/checkpoint entries locally.
|
||||
|
||||
|
||||
@@ -116,7 +116,6 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
|
||||
"backup_retention_count": 5,
|
||||
"use_new_license_icons": True,
|
||||
"group_by_model": False,
|
||||
"sticky_controls": False,
|
||||
# AI / LLM provider configuration (BYOK)
|
||||
"llm_provider": "openai", # "openai" | "ollama" | "custom"
|
||||
"llm_api_key": "",
|
||||
|
||||
@@ -20,6 +20,8 @@ class WebSocketManager:
|
||||
self._last_init_progress: Dict[str, Dict[str, Any]] = {}
|
||||
# Add auto-organize progress tracking
|
||||
self._auto_organize_progress: Optional[Dict[str, Any]] = None
|
||||
# Add recipe repair progress tracking
|
||||
self._recipe_repair_progress: Optional[Dict[str, Any]] = None
|
||||
# Add recipe rematch progress tracking
|
||||
self._recipe_rematch_progress: Optional[Dict[str, Any]] = None
|
||||
self._auto_organize_lock = asyncio.Lock()
|
||||
@@ -191,6 +193,14 @@ class WebSocketManager:
|
||||
# Broadcast via WebSocket
|
||||
await self.broadcast(data)
|
||||
|
||||
async def broadcast_recipe_repair_progress(self, data: Dict[str, Any]):
|
||||
"""Broadcast recipe repair progress to connected clients"""
|
||||
# Store progress data in memory
|
||||
self._recipe_repair_progress = data
|
||||
|
||||
# Broadcast via WebSocket
|
||||
await self.broadcast(data)
|
||||
|
||||
def get_auto_organize_progress(self) -> Optional[Dict[str, Any]]:
|
||||
"""Get current auto-organize progress"""
|
||||
return self._auto_organize_progress
|
||||
@@ -199,6 +209,22 @@ class WebSocketManager:
|
||||
"""Clear auto-organize progress data"""
|
||||
self._auto_organize_progress = None
|
||||
|
||||
def get_recipe_repair_progress(self) -> Optional[Dict[str, Any]]:
|
||||
"""Get current recipe repair progress"""
|
||||
return self._recipe_repair_progress
|
||||
|
||||
def cleanup_recipe_repair_progress(self):
|
||||
"""Clear recipe repair progress data if it is in a finished state"""
|
||||
if self._recipe_repair_progress and self._recipe_repair_progress.get('status') in ['completed', 'cancelled', 'error']:
|
||||
self._recipe_repair_progress = None
|
||||
|
||||
def is_recipe_repair_running(self) -> bool:
|
||||
"""Check if recipe repair is currently running"""
|
||||
if not self._recipe_repair_progress:
|
||||
return False
|
||||
status = self._recipe_repair_progress.get('status')
|
||||
return status in ['started', 'processing']
|
||||
|
||||
async def broadcast_recipe_rematch_progress(self, data: Dict[str, Any]):
|
||||
"""Broadcast recipe rematch progress to connected clients"""
|
||||
# Store progress data in memory
|
||||
|
||||
@@ -174,7 +174,7 @@
|
||||
z-index: var(--z-toast);
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
/* No align-items (defaults to stretch) so every toast shares one equal width */
|
||||
align-items: flex-end;
|
||||
gap: 10px;
|
||||
padding: 8px 20px 0; /* Small breathing room below the header */
|
||||
pointer-events: none; /* Allow clicking through the container */
|
||||
|
||||
+8
-33
@@ -25,23 +25,6 @@
|
||||
box-shadow: var(--shadow-xs);
|
||||
}
|
||||
|
||||
/* Wrapper around the controls bar and breadcrumb nav. With the sticky-controls
|
||||
setting off it is transparent to layout (display: contents), preserving the
|
||||
original behavior (only the breadcrumb stays visible). When enabled, the whole
|
||||
wrapper sticks as one unit so the two bars can never drift apart. */
|
||||
.sticky-topbar {
|
||||
display: contents;
|
||||
}
|
||||
|
||||
body.sticky-controls .sticky-topbar {
|
||||
display: block;
|
||||
position: sticky;
|
||||
top: 0;
|
||||
z-index: calc(var(--z-header) - 1);
|
||||
background: var(--bg-color);
|
||||
box-shadow: var(--shadow-xs);
|
||||
}
|
||||
|
||||
/* Responsive container for larger screens */
|
||||
@media (min-width: 2150px) {
|
||||
.container {
|
||||
@@ -218,17 +201,20 @@ body.sticky-controls .sticky-topbar {
|
||||
display: inline-flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
min-width: 16px;
|
||||
height: 16px;
|
||||
padding: 0 4px;
|
||||
font-size: 10px;
|
||||
font-weight: 500;
|
||||
margin-left: 6px;
|
||||
min-width: 18px;
|
||||
height: 18px;
|
||||
padding: 0 5px;
|
||||
font-size: 11px;
|
||||
font-weight: 600;
|
||||
line-height: 1;
|
||||
text-transform: uppercase;
|
||||
border-radius: var(--border-radius-xs);
|
||||
background-color: var(--shortcut-bg);
|
||||
border: 1px solid var(--shortcut-border);
|
||||
box-shadow: var(--shortcut-shadow);
|
||||
color: var(--shortcut-text);
|
||||
vertical-align: middle;
|
||||
opacity: 0.8;
|
||||
transition: var(--transition-base);
|
||||
}
|
||||
@@ -239,21 +225,10 @@ body.sticky-controls .sticky-topbar {
|
||||
border-color: var(--shortcut-border-hover);
|
||||
}
|
||||
|
||||
/* Invert the keycap on active (accent-filled) buttons for contrast.
|
||||
Must come after the hover rule above so it wins on active+hover. */
|
||||
.control-group button.active .shortcut-key,
|
||||
.control-group button.active:hover .shortcut-key {
|
||||
color: var(--lora-accent);
|
||||
background: rgba(255, 255, 255, 0.92);
|
||||
border-color: transparent;
|
||||
opacity: 1;
|
||||
}
|
||||
|
||||
/* Ensure correct vertical alignment for text+shortcut */
|
||||
.control-group button span {
|
||||
display: inline-flex;
|
||||
align-items: center;
|
||||
gap: 6px;
|
||||
}
|
||||
|
||||
/* Select dropdown styling */
|
||||
|
||||
@@ -20,6 +20,7 @@ const RECIPE_ENDPOINTS = {
|
||||
move: '/api/lm/recipe/move',
|
||||
moveBulk: '/api/lm/recipes/move-bulk',
|
||||
bulkDelete: '/api/lm/recipes/bulk-delete',
|
||||
repairBulk: '/api/lm/recipes/repair-bulk',
|
||||
rematchBulk: '/api/lm/recipes/rematch-bulk',
|
||||
rematchSingle: '/api/lm/recipe/{recipe_id}/rematch',
|
||||
};
|
||||
@@ -677,6 +678,38 @@ export class RecipeSidebarApiClient {
|
||||
};
|
||||
}
|
||||
|
||||
async repairBulkModels(filePaths) {
|
||||
if (!filePaths || filePaths.length === 0) {
|
||||
throw new Error('No file paths provided');
|
||||
}
|
||||
|
||||
const recipeIds = filePaths
|
||||
.map((path) => extractRecipeId(path))
|
||||
.filter((id) => !!id);
|
||||
|
||||
if (recipeIds.length === 0) {
|
||||
throw new Error('No recipe IDs could be derived from file paths');
|
||||
}
|
||||
|
||||
const response = await fetch(this.apiConfig.endpoints.repairBulk, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
recipe_ids: recipeIds,
|
||||
}),
|
||||
});
|
||||
|
||||
const result = await response.json();
|
||||
|
||||
if (!response.ok || !result.success) {
|
||||
throw new Error(result.error || 'Failed to repair recipes');
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
async rematchBulkModels(filePaths) {
|
||||
if (!filePaths || filePaths.length === 0) {
|
||||
throw new Error('No file paths provided');
|
||||
|
||||
@@ -41,9 +41,13 @@ export class BulkContextMenu extends BaseContextMenu {
|
||||
const autoOrganizeItem = this.menu.querySelector('[data-action="auto-organize"]');
|
||||
const deleteAllItem = this.menu.querySelector('[data-action="delete-all"]');
|
||||
const downloadMissingLorasItem = this.menu.querySelector('[data-action="download-missing-loras"]');
|
||||
const repairMetadataItem = this.menu.querySelector('[data-action="repair-metadata"]');
|
||||
const reimportMetadataItem = this.menu.querySelector('[data-action="reimport-metadata"]');
|
||||
const rematchMetadataItem = this.menu.querySelector('[data-action="rematch-metadata"]');
|
||||
|
||||
if (repairMetadataItem) {
|
||||
repairMetadataItem.style.display = config.repairMetadata ? 'flex' : 'none';
|
||||
}
|
||||
if (reimportMetadataItem) {
|
||||
reimportMetadataItem.style.display = config.reimportMetadata ? 'flex' : 'none';
|
||||
}
|
||||
@@ -279,6 +283,9 @@ export class BulkContextMenu extends BaseContextMenu {
|
||||
case 'delete-all':
|
||||
bulkManager.showBulkDeleteModal();
|
||||
break;
|
||||
case 'repair-metadata':
|
||||
bulkManager.repairSelectedRecipes();
|
||||
break;
|
||||
case 'rematch-metadata':
|
||||
bulkManager.rematchSelectedRecipes();
|
||||
break;
|
||||
|
||||
@@ -23,6 +23,7 @@ export class GlobalContextMenu extends BaseContextMenu {
|
||||
const downloadExamplesItem = this.menu.querySelector('[data-action="download-example-images"]');
|
||||
const cleanupExamplesItem = this.menu.querySelector('[data-action="cleanup-example-images-folders"]');
|
||||
const excludedModelsItem = this.menu.querySelector('[data-action="manage-excluded-models"]');
|
||||
const repairRecipesItem = this.menu.querySelector('[data-action="repair-recipes"]');
|
||||
const rematchRecipesItem = this.menu.querySelector('[data-action="rematch-recipes"]');
|
||||
const groupByModelItem = this.menu.querySelector('[data-action="toggle-group-by-model"]');
|
||||
const groupByModelCheck = groupByModelItem?.querySelector('.check-indicator');
|
||||
@@ -40,6 +41,7 @@ export class GlobalContextMenu extends BaseContextMenu {
|
||||
cleanupExamplesItem?.classList.add('hidden');
|
||||
excludedModelsItem?.classList.add('hidden');
|
||||
groupByModelItem?.classList.add('hidden');
|
||||
repairRecipesItem?.classList.remove('hidden');
|
||||
rematchRecipesItem?.classList.remove('hidden');
|
||||
} else {
|
||||
modelUpdateItem?.classList.remove('hidden');
|
||||
@@ -48,6 +50,7 @@ export class GlobalContextMenu extends BaseContextMenu {
|
||||
cleanupExamplesItem?.classList.remove('hidden');
|
||||
excludedModelsItem?.classList.remove('hidden');
|
||||
groupByModelItem?.classList.remove('hidden');
|
||||
repairRecipesItem?.classList.add('hidden');
|
||||
rematchRecipesItem?.classList.add('hidden');
|
||||
}
|
||||
|
||||
@@ -92,6 +95,11 @@ export class GlobalContextMenu extends BaseContextMenu {
|
||||
console.error('Failed to refresh missing license metadata:', error);
|
||||
});
|
||||
break;
|
||||
case 'repair-recipes':
|
||||
this.repairRecipes(menuItem).catch((error) => {
|
||||
console.error('Failed to repair recipes:', error);
|
||||
});
|
||||
break;
|
||||
case 'rematch-recipes':
|
||||
this.rematchRecipes(menuItem).catch((error) => {
|
||||
console.error('Failed to rematch recipes:', error);
|
||||
@@ -363,6 +371,99 @@ export class GlobalContextMenu extends BaseContextMenu {
|
||||
return `${displayName}s`;
|
||||
}
|
||||
|
||||
async repairRecipes(menuItem) {
|
||||
if (this._repairInProgress) {
|
||||
return;
|
||||
}
|
||||
|
||||
this._repairInProgress = true;
|
||||
menuItem?.classList.add('disabled');
|
||||
|
||||
const loadingMessage = translate(
|
||||
'globalContextMenu.repairRecipes.loading',
|
||||
{},
|
||||
'Repairing recipe data...'
|
||||
);
|
||||
|
||||
const progressUI = state.loadingManager?.showEnhancedProgress(loadingMessage);
|
||||
progressUI?.showCancelButton(() => this.cancelRepair());
|
||||
|
||||
try {
|
||||
const response = await fetch('/api/lm/recipes/repair', {
|
||||
method: 'POST',
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
});
|
||||
|
||||
const result = await response.json();
|
||||
if (!response.ok || !result.success) {
|
||||
throw new Error(result.error || 'Failed to start repair');
|
||||
}
|
||||
|
||||
// Poll for progress (or wait for WebSocket if preferred, but polling is simpler for this implementation)
|
||||
let isComplete = false;
|
||||
while (!isComplete && this._repairInProgress) {
|
||||
const progressResponse = await fetch('/api/lm/recipes/repair-progress');
|
||||
if (progressResponse.ok) {
|
||||
const progressResult = await progressResponse.json();
|
||||
if (progressResult.success && progressResult.progress) {
|
||||
const p = progressResult.progress;
|
||||
if (p.status === 'processing') {
|
||||
const percent = (p.current / p.total) * 100;
|
||||
progressUI?.updateProgress(percent, p.recipe_name, `${loadingMessage} (${p.current}/${p.total})`);
|
||||
} else if (p.status === 'completed') {
|
||||
isComplete = true;
|
||||
progressUI?.complete(translate(
|
||||
'globalContextMenu.repairRecipes.success',
|
||||
{ count: p.repaired },
|
||||
`Repaired ${p.repaired} recipes.`
|
||||
));
|
||||
showToast('globalContextMenu.repairRecipes.success', { count: p.repaired }, 'success');
|
||||
// Refresh recipes page if active
|
||||
if (window.recipesPage) {
|
||||
window.recipesPage.refresh();
|
||||
}
|
||||
} else if (p.status === 'error') {
|
||||
throw new Error(p.error || 'Repair failed');
|
||||
} else if (p.status === 'cancelled') {
|
||||
isComplete = true;
|
||||
progressUI?.complete(translate(
|
||||
'globalContextMenu.repairRecipes.cancelled',
|
||||
{ count: p.repaired },
|
||||
`Repair cancelled. ${p.repaired} recipes were repaired.`
|
||||
));
|
||||
showToast('globalContextMenu.repairRecipes.cancelled', { count: p.repaired }, 'info');
|
||||
}
|
||||
} else if (progressResponse.status === 404) {
|
||||
// Progress might have finished quickly and been cleaned up
|
||||
isComplete = true;
|
||||
progressUI?.complete();
|
||||
}
|
||||
}
|
||||
|
||||
if (!isComplete) {
|
||||
await new Promise(resolve => setTimeout(resolve, 1000));
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Recipe repair failed:', error);
|
||||
progressUI?.complete(translate('globalContextMenu.repairRecipes.error', { message: error.message }, 'Repair failed: {message}'));
|
||||
showToast('globalContextMenu.repairRecipes.error', { message: error.message }, 'error');
|
||||
} finally {
|
||||
this._repairInProgress = false;
|
||||
menuItem?.classList.remove('disabled');
|
||||
}
|
||||
}
|
||||
|
||||
async cancelRepair() {
|
||||
try {
|
||||
await fetch('/api/lm/recipes/cancel-repair', {
|
||||
method: 'POST',
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('Failed to cancel recipe repair:', error);
|
||||
}
|
||||
}
|
||||
|
||||
async rematchRecipes(menuItem) {
|
||||
if (this._rematchInProgress) {
|
||||
return;
|
||||
|
||||
@@ -93,6 +93,10 @@ export class RecipeContextMenu extends BaseContextMenu {
|
||||
// Download missing LoRAs
|
||||
this.downloadMissingLoRAs(recipeId);
|
||||
break;
|
||||
case 'repair':
|
||||
// Repair recipe metadata
|
||||
this.repairRecipe(recipeId);
|
||||
break;
|
||||
case 'rematch':
|
||||
// Rematch recipe resources to local models
|
||||
this.rematchRecipe(recipeId);
|
||||
@@ -293,6 +297,44 @@ export class RecipeContextMenu extends BaseContextMenu {
|
||||
}
|
||||
}
|
||||
|
||||
// Repair recipe metadata
|
||||
async repairRecipe(recipeId) {
|
||||
if (!recipeId) {
|
||||
showToast('recipes.contextMenu.repair.missingId', {}, 'error');
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
showToast('recipes.contextMenu.repair.starting', {}, 'info');
|
||||
|
||||
const response = await fetch(`/api/lm/recipe/${recipeId}/repair`, {
|
||||
method: 'POST'
|
||||
});
|
||||
const result = await response.json();
|
||||
|
||||
if (result.success) {
|
||||
if (result.repaired > 0) {
|
||||
showToast('recipes.contextMenu.repair.success', {}, 'success');
|
||||
const detailResponse = await fetch(`/api/lm/recipe/${recipeId}`);
|
||||
if (detailResponse.ok) {
|
||||
const updatedRecipe = await detailResponse.json();
|
||||
const filePath = this.currentCard?.dataset?.filepath;
|
||||
if (filePath && state.virtualScroller) {
|
||||
state.virtualScroller.updateSingleItem(filePath, updatedRecipe);
|
||||
}
|
||||
}
|
||||
} else {
|
||||
showToast('recipes.contextMenu.repair.skipped', {}, 'info');
|
||||
}
|
||||
} else {
|
||||
throw new Error(result.error || 'Repair failed');
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error repairing recipe:', error);
|
||||
showToast('recipes.contextMenu.repair.failed', { message: error.message }, 'error');
|
||||
}
|
||||
}
|
||||
|
||||
async rematchRecipe(recipeId) {
|
||||
if (!recipeId) {
|
||||
showToast('toast.recipes.rematchFailed', { message: 'Missing recipe ID' }, 'error');
|
||||
|
||||
@@ -103,6 +103,7 @@ export class BulkManager {
|
||||
skipMetadataRefresh: false,
|
||||
setFavorite: true,
|
||||
unfavorite: true,
|
||||
repairMetadata: true,
|
||||
reimportMetadata: true,
|
||||
rematchMetadata: true
|
||||
}
|
||||
@@ -909,6 +910,76 @@ export class BulkManager {
|
||||
}
|
||||
}
|
||||
|
||||
async repairSelectedRecipes() {
|
||||
if (state.selectedModels.size === 0) {
|
||||
showToast('toast.recipes.noRecipesSelected', {}, 'warning');
|
||||
return;
|
||||
}
|
||||
|
||||
if (state.currentPageType !== 'recipes') {
|
||||
showToast('This operation is only available for recipes', {}, 'warning');
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
const apiClient = this.getActiveApiClient();
|
||||
const filePaths = Array.from(state.selectedModels);
|
||||
|
||||
if (typeof apiClient.repairBulkModels !== 'function') {
|
||||
showToast('Bulk repair is not supported for this model type', {}, 'error');
|
||||
return;
|
||||
}
|
||||
|
||||
state.loadingManager.showSimpleLoading('Repairing recipe metadata...');
|
||||
|
||||
const result = await apiClient.repairBulkModels(filePaths);
|
||||
|
||||
if (result.success) {
|
||||
const total = result.total || filePaths.length;
|
||||
const repaired = result.repaired || 0;
|
||||
const skipped = result.skipped || 0;
|
||||
|
||||
const recipes = result.recipes || [];
|
||||
for (const recipe of recipes) {
|
||||
if (recipe.file_path) {
|
||||
state.virtualScroller.updateSingleItem(
|
||||
recipe.file_path,
|
||||
recipe
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
if (repaired > 0) {
|
||||
showToast(
|
||||
'toast.recipes.repairBulkComplete',
|
||||
{ repaired, skipped, total },
|
||||
'success'
|
||||
);
|
||||
} else {
|
||||
showToast(
|
||||
'toast.recipes.repairBulkSkipped',
|
||||
{ total },
|
||||
'info'
|
||||
);
|
||||
}
|
||||
|
||||
if (state.bulkMode) this.toggleBulkMode();
|
||||
} else {
|
||||
throw new Error(result.error || 'Bulk repair failed');
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error during bulk recipe repair:', error);
|
||||
showToast('toast.recipes.repairBulkFailed', { message: error.message }, 'error');
|
||||
} finally {
|
||||
if (state.loadingManager?.hide) {
|
||||
state.loadingManager.hide();
|
||||
}
|
||||
if (typeof state.loadingManager?.restoreProgressBar === 'function') {
|
||||
state.loadingManager.restoreProgressBar();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
async rematchSelectedRecipes() {
|
||||
if (state.selectedModels.size === 0) {
|
||||
showToast('toast.recipes.noRecipesSelected', {}, 'warning');
|
||||
|
||||
@@ -1047,12 +1047,6 @@ export class SettingsManager {
|
||||
groupByModelCheckbox.checked = !!state.global.settings.group_by_model;
|
||||
}
|
||||
|
||||
// Set sticky controls
|
||||
const stickyControlsCheckbox = document.getElementById('stickyControls');
|
||||
if (stickyControlsCheckbox) {
|
||||
stickyControlsCheckbox.checked = !!state.global.settings.sticky_controls;
|
||||
}
|
||||
|
||||
// Set model name display setting
|
||||
const modelNameDisplaySelect = document.getElementById('modelNameDisplay');
|
||||
if (modelNameDisplaySelect) {
|
||||
@@ -3402,10 +3396,6 @@ export class SettingsManager {
|
||||
const groupByModel = !!state.global.settings.group_by_model;
|
||||
document.body.classList.toggle('group-by-model', groupByModel);
|
||||
|
||||
// Apply sticky controls mode (keeps the action bar visible while scrolling)
|
||||
const stickyControls = !!state.global.settings.sticky_controls;
|
||||
document.body.classList.toggle('sticky-controls', stickyControls);
|
||||
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -59,7 +59,6 @@ const DEFAULT_SETTINGS_BASE = Object.freeze({
|
||||
strip_lora_on_copy: false,
|
||||
use_new_license_icons: true,
|
||||
group_by_model: false,
|
||||
sticky_controls: false,
|
||||
llm_provider: 'openai',
|
||||
llm_api_key: '',
|
||||
llm_api_base: '',
|
||||
|
||||
@@ -54,10 +54,8 @@
|
||||
{% endblock %}
|
||||
|
||||
{% block content %}
|
||||
<div class="sticky-topbar">
|
||||
{% include 'components/controls.html' %}
|
||||
{% include 'components/breadcrumb.html' %}
|
||||
</div>
|
||||
{% include 'components/duplicates_banner.html' %}
|
||||
{% include 'components/folder_sidebar.html' %}
|
||||
|
||||
|
||||
@@ -94,6 +94,9 @@
|
||||
<div class="context-menu-item" data-action="check-updates">
|
||||
<i class="fas fa-bell"></i> <span>{{ t('loras.bulkOperations.checkUpdates') }}</span>
|
||||
</div>
|
||||
<div class="context-menu-item" data-action="repair-metadata">
|
||||
<i class="fas fa-tools"></i> <span>{{ t('loras.bulkOperations.repairMetadata') }}</span> (Deprecated)
|
||||
</div>
|
||||
<div class="context-menu-item" data-action="rematch-metadata">
|
||||
<i class="fas fa-link"></i> <span>{{ t('loras.bulkOperations.rematchMetadata') }}</span>
|
||||
</div>
|
||||
@@ -199,6 +202,9 @@
|
||||
<i class="fas fa-layer-group"></i> <span>{{ t('globalContextMenu.groupByModel.label') }}</span>
|
||||
<i class="fas fa-check check-indicator" style="margin-left:auto;display:none"></i>
|
||||
</div>
|
||||
<div class="context-menu-item" data-action="repair-recipes">
|
||||
<i class="fas fa-tools"></i> <span>{{ t('globalContextMenu.repairRecipes.label') }}</span> (Deprecated)
|
||||
</div>
|
||||
<div class="context-menu-item" data-action="rematch-recipes">
|
||||
<i class="fas fa-link"></i> <span>{{ t('globalContextMenu.rematchRecipes.label') }}</span>
|
||||
</div>
|
||||
|
||||
@@ -79,9 +79,6 @@
|
||||
<!-- Group by model toggle -->
|
||||
{{ sm.setting_toggle('groupByModel', 'group_by_model', 'settings.layoutSettings.groupByModel', 'settings.layoutSettings.groupByModelHelp') }}
|
||||
|
||||
<!-- Sticky controls toggle -->
|
||||
{{ sm.setting_toggle('stickyControls', 'sticky_controls', 'settings.layoutSettings.stickyControls', 'settings.layoutSettings.stickyControlsHelp') }}
|
||||
|
||||
{{ sm.setting_select('cardInfoDisplay', 'card_info_display', 'settings.layoutSettings.cardInfoDisplay', [
|
||||
('always', 'settings.layoutSettings.cardInfoDisplayOptions.always'),
|
||||
('hover', 'settings.layoutSettings.cardInfoDisplayOptions.hover'),
|
||||
|
||||
@@ -53,10 +53,8 @@
|
||||
{% endblock %}
|
||||
|
||||
{% block content %}
|
||||
<div class="sticky-topbar">
|
||||
{% include 'components/controls.html' %}
|
||||
{% include 'components/breadcrumb.html' %}
|
||||
</div>
|
||||
{% include 'components/duplicates_banner.html' %}
|
||||
{% include 'components/folder_sidebar.html' %}
|
||||
|
||||
|
||||
@@ -8,10 +8,8 @@
|
||||
{% block init_check_url %}/api/loras/list?page=1&page_size=1{% endblock %}
|
||||
|
||||
{% block content %}
|
||||
<div class="sticky-topbar">
|
||||
{% include 'components/controls.html' %}
|
||||
{% include 'components/breadcrumb.html' %}
|
||||
</div>
|
||||
{% include 'components/duplicates_banner.html' %}
|
||||
{% include 'components/folder_sidebar.html' %}
|
||||
|
||||
|
||||
@@ -18,6 +18,9 @@
|
||||
<div id="recipeContextMenu" class="context-menu" style="display: none;">
|
||||
<!-- <div class="context-menu-item" data-action="details"><i class="fas fa-info-circle"></i> View Details</div> -->
|
||||
<!-- Metadata -->
|
||||
<div class="context-menu-item" data-action="repair">
|
||||
<i class="fas fa-tools"></i> {{ t('loras.contextMenu.repairMetadata') }} (Deprecated)
|
||||
</div>
|
||||
<div class="context-menu-item" data-action="rematch">
|
||||
<i class="fas fa-link"></i> {{ t('loras.contextMenu.rematchMetadata') }}
|
||||
</div>
|
||||
@@ -61,12 +64,10 @@
|
||||
{% block init_check_url %}/api/recipes?page=1&page_size=1{% endblock %}
|
||||
|
||||
{% block content %}
|
||||
<!-- Sticky topbar: controls + breadcrumb -->
|
||||
<div class="sticky-topbar">
|
||||
<!-- Recipe controls -->
|
||||
{% include 'components/controls.html' %}
|
||||
<!-- Breadcrumb Navigation -->
|
||||
{% include 'components/breadcrumb.html' %}
|
||||
</div>
|
||||
|
||||
<!-- Duplicates banner (hidden by default) -->
|
||||
<div id="duplicatesBanner" class="duplicates-banner" style="display: none;">
|
||||
|
||||
@@ -253,4 +253,126 @@ describe('AutoComplete active-filters flag', () => {
|
||||
|
||||
expect(autoComplete.dropdown.querySelector('.lm-autocomplete-first-run-hint')).toBeNull();
|
||||
});
|
||||
|
||||
it('broadcasts a setting-toggled window event when /activefilters is accepted', async () => {
|
||||
const events = [];
|
||||
const listener = (event) => events.push(event.detail);
|
||||
window.addEventListener('lora-manager:setting-toggled', listener);
|
||||
try {
|
||||
const input = document.createElement('textarea');
|
||||
input.value = '/activefilters';
|
||||
input.selectionStart = input.value.length;
|
||||
input.focus = vi.fn();
|
||||
input.setSelectionRange = vi.fn();
|
||||
document.body.append(input);
|
||||
|
||||
caretHelperInstance.getBeforeCursor.mockReturnValue('/activefilters');
|
||||
|
||||
const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
|
||||
const autoComplete = new AutoComplete(input, 'loras', { showPreview: false, minChars: 1 });
|
||||
input.dispatchEvent(new Event('input', { bubbles: true }));
|
||||
|
||||
// The command token is cleared after acceptance; simulate the caret
|
||||
// helper seeing the cleared input so the synthetic input event does
|
||||
// not re-trigger command parsing (same pattern as behavior tests).
|
||||
caretHelperInstance.getBeforeCursor.mockReturnValue('');
|
||||
await Promise.resolve();
|
||||
await Promise.resolve();
|
||||
expect(events).toContainEqual({
|
||||
settingId: 'loramanager.lora_active_filters_autocomplete',
|
||||
value: true,
|
||||
});
|
||||
} finally {
|
||||
window.removeEventListener('lora-manager:setting-toggled', listener);
|
||||
}
|
||||
});
|
||||
|
||||
it('removes a stale first-run hint when the toggle is switched on while the dropdown stays open', async () => {
|
||||
localStorage.removeItem('lm:activefilters-tip-dismissed');
|
||||
let enabled = false;
|
||||
settingGetMock.mockImplementation((key) => {
|
||||
if (key === 'loramanager.lora_active_filters_autocomplete') return enabled;
|
||||
if (key === 'loramanager.autocomplete_append_comma') return false;
|
||||
if (key === 'loramanager.autocomplete_auto_format') return false;
|
||||
if (key === 'loramanager.autocomplete_accept_key') return 'both';
|
||||
return undefined;
|
||||
});
|
||||
|
||||
fetchApiMock.mockResolvedValue({
|
||||
json: () => Promise.resolve({ success: true, relative_paths: ['models/example.safetensors'] }),
|
||||
});
|
||||
|
||||
const input = document.createElement('textarea');
|
||||
input.value = 'example';
|
||||
input.selectionStart = 7;
|
||||
document.body.append(input);
|
||||
caretHelperInstance.getBeforeCursor.mockReturnValue('example');
|
||||
|
||||
const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
|
||||
const autoComplete = new AutoComplete(input, 'loras', {
|
||||
debounceDelay: 0,
|
||||
showPreview: false,
|
||||
minChars: 1,
|
||||
});
|
||||
|
||||
const triggerShow = async () => {
|
||||
input.dispatchEvent(new Event('input', { bubbles: true }));
|
||||
await vi.runOnlyPendingTimersAsync();
|
||||
await vi.runOnlyPendingTimersAsync();
|
||||
await Promise.resolve();
|
||||
return autoComplete.dropdown.querySelector('.lm-autocomplete-first-run-hint');
|
||||
};
|
||||
|
||||
// OFF → the enable hint is shown in the suggestions dropdown.
|
||||
expect(await triggerShow()).not.toBeNull();
|
||||
|
||||
// The node's filter chip toggles the setting ON while the dropdown is
|
||||
// still open (ComfyUI can keep focus in the textarea, so no blur/hide
|
||||
// fires). settings.js broadcasts the setting-toggled event.
|
||||
enabled = true;
|
||||
window.dispatchEvent(new CustomEvent('lora-manager:setting-toggled', {
|
||||
detail: { settingId: 'loramanager.lora_active_filters_autocomplete', value: true },
|
||||
}));
|
||||
|
||||
// The stale OFF hint must be gone even though the dropdown never closed.
|
||||
expect(autoComplete.dropdown.querySelector('.lm-autocomplete-first-run-hint')).toBeNull();
|
||||
|
||||
// Further typing while ON must not resurrect the enable hint.
|
||||
expect(await triggerShow()).toBeNull();
|
||||
});
|
||||
|
||||
it('updates the command-list footer when the toggle changes while the command list is open', async () => {
|
||||
let enabled = false;
|
||||
settingGetMock.mockImplementation((key) => {
|
||||
if (key === 'loramanager.lora_active_filters_autocomplete') return enabled;
|
||||
return undefined;
|
||||
});
|
||||
|
||||
const input = document.createElement('textarea');
|
||||
input.value = '/';
|
||||
input.selectionStart = 1;
|
||||
document.body.append(input);
|
||||
caretHelperInstance.getBeforeCursor.mockReturnValue('/');
|
||||
|
||||
const { AutoComplete } = await import(AUTOCOMPLETE_MODULE);
|
||||
const autoComplete = new AutoComplete(input, 'loras', { showPreview: false, minChars: 1 });
|
||||
input.dispatchEvent(new Event('input', { bubbles: true }));
|
||||
await vi.runOnlyPendingTimersAsync();
|
||||
await Promise.resolve();
|
||||
|
||||
const footer = () => autoComplete.dropdown.querySelector('.lm-autocomplete-command-footer');
|
||||
expect(footer()).not.toBeNull();
|
||||
expect(footer().textContent).toContain('Active Filters Search: OFF');
|
||||
expect(footer().textContent).toContain('/activefilters to enable');
|
||||
|
||||
enabled = true;
|
||||
window.dispatchEvent(new CustomEvent('lora-manager:setting-toggled', {
|
||||
detail: { settingId: 'loramanager.lora_active_filters_autocomplete', value: true },
|
||||
}));
|
||||
|
||||
expect(footer()).not.toBeNull();
|
||||
expect(footer().textContent).toContain('Active Filters Search: ON');
|
||||
expect(footer().textContent).toContain('/noactivefilters to disable');
|
||||
});
|
||||
|
||||
});
|
||||
|
||||
@@ -54,6 +54,7 @@ const setSettingValueMock = vi.fn();
|
||||
vi.mock(SETTINGS_MODULE, () => ({
|
||||
LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID:
|
||||
"loramanager.lora_active_filters_autocomplete",
|
||||
SETTING_TOGGLED_EVENT_NAME: "lora-manager:setting-toggled",
|
||||
getLoraActiveFiltersAutocompletePreference: getActiveFiltersPreferenceMock,
|
||||
setLoraManagerSettingValue: setSettingValueMock,
|
||||
}));
|
||||
|
||||
@@ -42,6 +42,7 @@ def sample_recipe_data() -> Dict[str, Any]:
|
||||
"created_date": 1700000000.0,
|
||||
"modified": 1700000100.0,
|
||||
"favorite": False,
|
||||
"repair_version": 1,
|
||||
"preview_nsfw_level": 0,
|
||||
"loras": [
|
||||
{"hash": "lora1hash", "file_name": "test_lora1", "strength": 0.8},
|
||||
|
||||
@@ -226,6 +226,15 @@ _REMATCH_ROUTE_DEFS = {
|
||||
("GET", "/api/lm/recipes/rematch-progress", "get_rematch_progress"),
|
||||
}
|
||||
|
||||
_REPAIR_ROUTE_DEFS = {
|
||||
("POST", "/api/lm/recipes/repair", "repair_recipes"),
|
||||
("POST", "/api/lm/recipes/cancel-repair", "cancel_repair"),
|
||||
("POST", "/api/lm/recipe/{recipe_id}/repair", "repair_recipe"),
|
||||
("POST", "/api/lm/recipes/repair-bulk", "repair_recipes_bulk"),
|
||||
("GET", "/api/lm/recipes/repair-progress", "get_repair_progress"),
|
||||
}
|
||||
|
||||
|
||||
def test_rematch_route_definitions_registered():
|
||||
registered = {
|
||||
(d.method, d.path, d.handler_name)
|
||||
@@ -234,6 +243,14 @@ def test_rematch_route_definitions_registered():
|
||||
assert _REMATCH_ROUTE_DEFS <= registered
|
||||
|
||||
|
||||
def test_repair_route_definitions_still_registered():
|
||||
registered = {
|
||||
(d.method, d.path, d.handler_name)
|
||||
for d in recipe_route_registrar.ROUTE_DEFINITIONS
|
||||
}
|
||||
assert _REPAIR_ROUTE_DEFS <= registered
|
||||
|
||||
|
||||
def test_rematch_handler_names_resolve_in_to_route_mapping(monkeypatch: pytest.MonkeyPatch):
|
||||
"""Oracle R1-F4: register_routes KeyErrors at startup if to_route_mapping
|
||||
lacks any name present in ROUTE_DEFINITIONS, so the real handler set must
|
||||
|
||||
@@ -1874,14 +1874,20 @@ async def test_create_from_example_does_not_recompute_stored_autov3(
|
||||
def _clean_recipe_run_progress_state():
|
||||
"""Keep the shared WS manager run-state isolated between tests."""
|
||||
ws_manager._recipe_rematch_progress = None
|
||||
ws_manager._recipe_repair_progress = None
|
||||
yield
|
||||
ws_manager._recipe_rematch_progress = None
|
||||
ws_manager._recipe_repair_progress = None
|
||||
|
||||
|
||||
def _set_rematch_running(status: str = "processing") -> None:
|
||||
ws_manager._recipe_rematch_progress = {"status": status}
|
||||
|
||||
|
||||
def _set_repair_running(status: str = "processing") -> None:
|
||||
ws_manager._recipe_repair_progress = {"status": status}
|
||||
|
||||
|
||||
async def test_rematch_recipes_starts_background_run(monkeypatch, tmp_path: Path) -> None:
|
||||
async with recipe_harness(monkeypatch, tmp_path) as harness:
|
||||
response = await harness.client.post("/api/lm/recipes/rematch")
|
||||
@@ -1905,6 +1911,15 @@ async def test_rematch_recipes_409_when_rematch_running(monkeypatch, tmp_path: P
|
||||
assert "already in progress" in payload["error"].lower()
|
||||
|
||||
|
||||
async def test_rematch_recipes_409_when_repair_running(monkeypatch, tmp_path: Path) -> None:
|
||||
async with recipe_harness(monkeypatch, tmp_path) as harness:
|
||||
_set_repair_running()
|
||||
response = await harness.client.post("/api/lm/recipes/rematch")
|
||||
payload = await response.json()
|
||||
assert response.status == 409
|
||||
assert payload["success"] is False
|
||||
assert "already in progress" in payload["error"].lower()
|
||||
|
||||
|
||||
async def test_rematch_recipe_409_when_rematch_running(monkeypatch, tmp_path: Path) -> None:
|
||||
async with recipe_harness(monkeypatch, tmp_path) as harness:
|
||||
|
||||
@@ -8,9 +8,8 @@ from unittest import mock
|
||||
|
||||
import pytest
|
||||
|
||||
from py.services import llm_service as llm_module
|
||||
from py.services.llm_service import LLMService
|
||||
from py.services.errors import LLMNotConfiguredError, LLMRateLimitError, LLMResponseError
|
||||
from py.services.llm_service import LLMService, fetch_ollama_models
|
||||
|
||||
|
||||
class MockSettings:
|
||||
@@ -315,61 +314,3 @@ class TestLLMServiceChatCompletionJson:
|
||||
system_prompt="test",
|
||||
user_prompt="test",
|
||||
)
|
||||
|
||||
|
||||
class MockGetSession:
|
||||
"""Minimal aiohttp session mock supporting get() for catalog tests."""
|
||||
|
||||
def __init__(self, response):
|
||||
self._response = response
|
||||
|
||||
def get(self, url):
|
||||
return self._response
|
||||
|
||||
async def __aenter__(self):
|
||||
return self
|
||||
|
||||
async def __aexit__(self, *args):
|
||||
pass
|
||||
|
||||
|
||||
class CorruptJsonResponse(MockResponse):
|
||||
"""Response whose body cannot be decoded as UTF-8 (like the issue's 0x9a byte)."""
|
||||
|
||||
async def json(self):
|
||||
raise UnicodeDecodeError("utf-8", b"\x9a", 0, 1, "invalid start byte")
|
||||
|
||||
|
||||
class TestModelCatalog:
|
||||
"""Tests for _load_model_catalog / fetch_ollama_models error handling."""
|
||||
|
||||
@pytest.fixture(autouse=True)
|
||||
def _reset_catalog_cache(self):
|
||||
"""Reset the module-level catalog cache around each test."""
|
||||
llm_module._catalog_cache = None
|
||||
llm_module._model_output_limits = {}
|
||||
yield
|
||||
llm_module._catalog_cache = None
|
||||
llm_module._model_output_limits = {}
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_load_model_catalog_falls_back_on_unicode_decode_error(self):
|
||||
"""Corrupted catalog body must not raise — fall back to an empty dict."""
|
||||
response = CorruptJsonResponse(200)
|
||||
session = MockGetSession(response)
|
||||
|
||||
with mock.patch("aiohttp.ClientSession", return_value=session):
|
||||
catalog = await llm_module._load_model_catalog()
|
||||
|
||||
assert catalog == {}
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_fetch_ollama_models_falls_back_on_unicode_decode_error(self):
|
||||
"""Corrupted Ollama response must not raise — fall back to an empty list."""
|
||||
response = CorruptJsonResponse(200)
|
||||
session = MockGetSession(response)
|
||||
|
||||
with mock.patch("aiohttp.ClientSession", return_value=session):
|
||||
models = await fetch_ollama_models("http://localhost:11434/v1")
|
||||
|
||||
assert models == []
|
||||
|
||||
@@ -0,0 +1,327 @@
|
||||
import pytest
|
||||
import asyncio
|
||||
from typing import Any, Dict
|
||||
from unittest.mock import AsyncMock, MagicMock
|
||||
from py.services.recipe_scanner import RecipeScanner
|
||||
from types import SimpleNamespace
|
||||
|
||||
# We define these here to help with spec= if needed
|
||||
class MockCivitaiClient:
|
||||
async def get_image_info(self, image_id, source_url=None):
|
||||
pass
|
||||
|
||||
class MockPersistenceService:
|
||||
async def save_recipe(self, recipe):
|
||||
pass
|
||||
|
||||
@pytest.fixture
|
||||
def mock_civitai_client():
|
||||
client = MagicMock(spec=MockCivitaiClient)
|
||||
client.get_image_info = AsyncMock()
|
||||
return client
|
||||
|
||||
@pytest.fixture
|
||||
def mock_metadata_provider():
|
||||
provider = MagicMock()
|
||||
provider.get_model_version_info = AsyncMock(return_value=(None, None))
|
||||
provider.get_model_by_hash = AsyncMock(return_value=(None, None))
|
||||
return provider
|
||||
|
||||
@pytest.fixture
|
||||
def recipe_scanner():
|
||||
lora_scanner = MagicMock()
|
||||
lora_scanner.get_cached_data = AsyncMock(return_value=SimpleNamespace(raw_data=[]))
|
||||
|
||||
scanner = RecipeScanner(lora_scanner=lora_scanner)
|
||||
return scanner
|
||||
|
||||
@pytest.fixture
|
||||
def setup_scanner(recipe_scanner, mock_civitai_client, mock_metadata_provider, monkeypatch):
|
||||
monkeypatch.setattr(recipe_scanner, "_get_civitai_client", AsyncMock(return_value=mock_civitai_client))
|
||||
|
||||
# Wrap the real method with a mock so we can check calls but still execute it
|
||||
real_save = recipe_scanner._save_recipe_persistently
|
||||
mock_save = AsyncMock(side_effect=real_save)
|
||||
monkeypatch.setattr(recipe_scanner, "_save_recipe_persistently", mock_save)
|
||||
|
||||
monkeypatch.setattr("py.recipes.enrichment.get_default_metadata_provider", AsyncMock(return_value=mock_metadata_provider))
|
||||
|
||||
# Mock get_recipe_json_path to avoid file system issues in tests
|
||||
recipe_scanner.get_recipe_json_path = AsyncMock(return_value="/tmp/test_recipe.json")
|
||||
# Mock open to avoid actual file writing
|
||||
monkeypatch.setattr("builtins.open", MagicMock())
|
||||
monkeypatch.setattr("json.dump", MagicMock())
|
||||
monkeypatch.setattr("os.path.exists", MagicMock(return_value=False)) # avoid EXIF logic
|
||||
|
||||
return recipe_scanner, mock_civitai_client, mock_metadata_provider
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_skip_up_to_date(setup_scanner):
|
||||
recipe_scanner, _, _ = setup_scanner
|
||||
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[
|
||||
{"id": "r1", "repair_version": RecipeScanner.REPAIR_VERSION, "title": "Up to date"}
|
||||
])
|
||||
|
||||
# Run
|
||||
results = await recipe_scanner.repair_all_recipes()
|
||||
|
||||
# Verify
|
||||
assert results["repaired"] == 0
|
||||
assert results["skipped"] == 1
|
||||
recipe_scanner._save_recipe_persistently.assert_not_called()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_with_enriched_checkpoint_id(setup_scanner):
|
||||
recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
|
||||
|
||||
recipe = {
|
||||
"id": "r1",
|
||||
"title": "Old Recipe",
|
||||
"source_path": "https://civitai.com/images/12345",
|
||||
"checkpoint": None,
|
||||
"gen_params": {"prompt": ""}
|
||||
}
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
|
||||
|
||||
# Mock image info returning modelVersionId
|
||||
mock_civitai_client.get_image_info.return_value = {
|
||||
"modelVersionId": 5678,
|
||||
"meta": {"prompt": "a beautiful forest", "Checkpoint": "basic_name.safetensors"}
|
||||
}
|
||||
|
||||
# Mock metadata provider returning full info
|
||||
mock_metadata_provider.get_model_version_info.return_value = ({
|
||||
"id": 5678,
|
||||
"modelId": 1234,
|
||||
"name": "v1.0",
|
||||
"model": {"name": "Full Model Name", "type": "Checkpoint"},
|
||||
"baseModel": "SDXL 1.0",
|
||||
"images": [{"url": "https://image.url/thumb.jpg"}],
|
||||
"files": [{"type": "Model", "hashes": {"SHA256": "ABCDEF"}, "name": "full_filename.safetensors"}]
|
||||
}, None)
|
||||
|
||||
# Run
|
||||
results = await recipe_scanner.repair_all_recipes()
|
||||
|
||||
# Verify
|
||||
assert results["repaired"] == 1
|
||||
mock_metadata_provider.get_model_version_info.assert_called_with("5678")
|
||||
|
||||
saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
|
||||
checkpoint = saved_recipe["checkpoint"]
|
||||
assert checkpoint["modelName"] == "Full Model Name"
|
||||
assert checkpoint["modelVersionName"] == "v1.0"
|
||||
assert checkpoint["modelId"] == 1234
|
||||
assert checkpoint["modelVersionId"] == 5678
|
||||
assert checkpoint["type"] == "checkpoint"
|
||||
assert "name" not in checkpoint
|
||||
assert "version" not in checkpoint
|
||||
assert "hash" not in checkpoint
|
||||
assert "file_name" not in checkpoint
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_supports_civitai_red_source_url(setup_scanner):
|
||||
recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
|
||||
|
||||
recipe = {
|
||||
"id": "r1",
|
||||
"title": "Red Recipe",
|
||||
"source_path": "https://civitai.red/images/12345",
|
||||
"checkpoint": None,
|
||||
"gen_params": {"prompt": ""},
|
||||
}
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
|
||||
|
||||
mock_civitai_client.get_image_info.return_value = {
|
||||
"modelVersionId": 5678,
|
||||
"meta": {"prompt": "from red"},
|
||||
}
|
||||
mock_metadata_provider.get_model_version_info.return_value = (
|
||||
{
|
||||
"id": 5678,
|
||||
"modelId": 1234,
|
||||
"name": "v1.0",
|
||||
"model": {"name": "Full Model Name", "type": "Checkpoint"},
|
||||
"baseModel": "SDXL 1.0",
|
||||
"images": [{"url": "https://image.url/thumb.jpg"}],
|
||||
"files": [
|
||||
{
|
||||
"type": "Model",
|
||||
"hashes": {"SHA256": "ABCDEF"},
|
||||
"name": "full_filename.safetensors",
|
||||
}
|
||||
],
|
||||
},
|
||||
None,
|
||||
)
|
||||
|
||||
results = await recipe_scanner.repair_all_recipes()
|
||||
|
||||
assert results["repaired"] == 1
|
||||
mock_civitai_client.get_image_info.assert_called_with(
|
||||
"12345", source_url="https://civitai.red/images/12345"
|
||||
)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_with_enriched_checkpoint_hash(setup_scanner):
|
||||
recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
|
||||
|
||||
recipe = {
|
||||
"id": "r1",
|
||||
"title": "Embedded Only",
|
||||
"checkpoint": None,
|
||||
"gen_params": {
|
||||
"prompt": "",
|
||||
"Model hash": "hash123"
|
||||
}
|
||||
}
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
|
||||
|
||||
# Mock metadata provider lookup by hash
|
||||
mock_metadata_provider.get_model_by_hash.return_value = ({
|
||||
"id": 999,
|
||||
"modelId": 888,
|
||||
"name": "v2.0",
|
||||
"model": {"name": "Hashed Model", "type": "Checkpoint"},
|
||||
"baseModel": "SD 1.5",
|
||||
"files": [{"type": "Model", "hashes": {"SHA256": "hash123"}, "name": "hashed.safetensors"}]
|
||||
}, None)
|
||||
|
||||
# Run
|
||||
results = await recipe_scanner.repair_all_recipes()
|
||||
|
||||
# Verify
|
||||
assert results["repaired"] == 1
|
||||
mock_metadata_provider.get_model_by_hash.assert_called_with("hash123")
|
||||
|
||||
saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
|
||||
checkpoint = saved_recipe["checkpoint"]
|
||||
assert checkpoint["modelName"] == "Hashed Model"
|
||||
assert checkpoint["modelVersionName"] == "v2.0"
|
||||
assert checkpoint["modelId"] == 888
|
||||
assert checkpoint["type"] == "checkpoint"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_fallback_to_basic(setup_scanner):
|
||||
recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
|
||||
|
||||
recipe = {
|
||||
"id": "r1",
|
||||
"title": "No Meta Lookup",
|
||||
"checkpoint": None,
|
||||
"gen_params": {
|
||||
"prompt": "",
|
||||
"Checkpoint": "just_a_name.safetensors"
|
||||
}
|
||||
}
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
|
||||
|
||||
# Mock metadata provider returning nothing
|
||||
mock_metadata_provider.get_model_by_hash.return_value = (None, "Model not found")
|
||||
|
||||
# Run
|
||||
results = await recipe_scanner.repair_all_recipes()
|
||||
|
||||
# Verify
|
||||
assert results["repaired"] == 1
|
||||
saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
|
||||
assert saved_recipe["checkpoint"]["modelName"] == "just_a_name.safetensors"
|
||||
assert saved_recipe["checkpoint"]["type"] == "checkpoint"
|
||||
assert "modelId" not in saved_recipe["checkpoint"]
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_progress_callback(setup_scanner):
|
||||
recipe_scanner, _, _ = setup_scanner
|
||||
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[
|
||||
{"id": "r1", "title": "R1", "checkpoint": None},
|
||||
{"id": "r2", "title": "R2", "checkpoint": None}
|
||||
])
|
||||
|
||||
progress_calls = []
|
||||
async def progress_callback(data):
|
||||
progress_calls.append(data)
|
||||
|
||||
# Run
|
||||
await recipe_scanner.repair_all_recipes(
|
||||
progress_callback=progress_callback
|
||||
)
|
||||
|
||||
# Verify
|
||||
assert len(progress_calls) >= 2
|
||||
assert progress_calls[-1]["status"] == "completed"
|
||||
assert progress_calls[-1]["total"] == 2
|
||||
assert progress_calls[-1]["repaired"] == 2
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_repair_all_recipes_strips_runtime_fields(setup_scanner):
|
||||
recipe_scanner, mock_civitai_client, mock_metadata_provider = setup_scanner
|
||||
|
||||
# Recipe with runtime fields
|
||||
recipe: Dict[str, Any] = {
|
||||
"id": "r1",
|
||||
"title": "Cleanup Test",
|
||||
"checkpoint": {
|
||||
"name": "CP",
|
||||
"inLibrary": True,
|
||||
"localPath": "/path/to/cp",
|
||||
"thumbnailUrl": "thumb.jpg"
|
||||
},
|
||||
"loras": [
|
||||
{
|
||||
"name": "L1",
|
||||
"weight": 0.8,
|
||||
"inLibrary": True,
|
||||
"localPath": "/path/to/l1",
|
||||
"preview_url": "p.jpg"
|
||||
}
|
||||
],
|
||||
"gen_params": {"prompt": ""}
|
||||
}
|
||||
recipe_scanner._cache = SimpleNamespace(raw_data=[recipe])
|
||||
# Set high version to trigger repair if needed (or just ensure it processes)
|
||||
recipe["repair_version"] = 0
|
||||
|
||||
# Run
|
||||
await recipe_scanner.repair_all_recipes()
|
||||
|
||||
# Verify sanitation
|
||||
assert recipe_scanner._save_recipe_persistently.called
|
||||
saved_recipe = recipe_scanner._save_recipe_persistently.call_args[0][0]
|
||||
|
||||
# 1. Check LORA
|
||||
lora = saved_recipe["loras"][0]
|
||||
assert "inLibrary" not in lora
|
||||
assert "localPath" not in lora
|
||||
assert "preview_url" not in lora
|
||||
assert "strength" in lora # weight renamed to strength
|
||||
assert lora["strength"] == 0.8
|
||||
|
||||
# 2. Check Checkpoint
|
||||
cp = saved_recipe["checkpoint"]
|
||||
assert "inLibrary" not in cp
|
||||
assert "localPath" not in cp
|
||||
assert "thumbnailUrl" not in cp
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_sanitize_recipe_for_storage(recipe_scanner):
|
||||
|
||||
recipe = {
|
||||
"loras": [{"name": "L1", "inLibrary": True, "weight": 0.5}],
|
||||
"checkpoint": {"name": "CP", "localPath": "/tmp/cp"}
|
||||
}
|
||||
|
||||
clean = recipe_scanner._sanitize_recipe_for_storage(recipe)
|
||||
|
||||
assert "inLibrary" not in clean["loras"][0]
|
||||
assert "strength" in clean["loras"][0]
|
||||
assert clean["loras"][0]["strength"] == 0.5
|
||||
assert "localPath" not in clean["checkpoint"]
|
||||
# Testing based on what enricher would produce if it ran,
|
||||
# but here we are just testing the sanitizer which handles what is ALREADY there.
|
||||
# However, the sanitizer doesn't rename fields, it just removes runtime ones.
|
||||
# Since we changed the enricher to NOT put 'name' anymore, this test case
|
||||
# should probably reflect the new fields if it's simulating a real recipe.
|
||||
assert clean["checkpoint"]["name"] == "CP"
|
||||
@@ -242,14 +242,22 @@ async def test_is_recipe_rematch_running_by_status(manager, status, expected):
|
||||
assert manager.is_recipe_rematch_running() is expected
|
||||
|
||||
|
||||
async def test_rematch_progress_channel_updates_and_cleans_up(manager):
|
||||
# Rematch progress is stored and reported as running while processing.
|
||||
async def test_rematch_and_repair_channels_are_independent(manager):
|
||||
# Rematch progress must not leak into the repair channel
|
||||
await manager.broadcast_recipe_rematch_progress({"status": "processing", "current": 1})
|
||||
assert manager.is_recipe_rematch_running() is True
|
||||
assert manager.is_recipe_repair_running() is False
|
||||
assert manager.get_recipe_repair_progress() is None
|
||||
|
||||
# Repair progress must not overwrite the rematch state
|
||||
await manager.broadcast_recipe_repair_progress({"status": "processing", "current": 1})
|
||||
assert manager.is_recipe_repair_running() is True
|
||||
assert manager.is_recipe_rematch_running() is True
|
||||
assert manager.get_recipe_rematch_progress() == {"status": "processing", "current": 1}
|
||||
|
||||
# Finished states clear on cleanup.
|
||||
# Cleaning the rematch channel must leave the repair channel untouched
|
||||
await manager.broadcast_recipe_rematch_progress({"status": "completed"})
|
||||
manager.cleanup_recipe_rematch_progress()
|
||||
assert manager.get_recipe_rematch_progress() is None
|
||||
assert manager.is_recipe_rematch_running() is False
|
||||
assert manager.get_recipe_repair_progress() == {"status": "processing", "current": 1}
|
||||
assert manager.is_recipe_repair_running() is True
|
||||
|
||||
@@ -40,6 +40,7 @@ def sample_recipes() -> List[Dict[str, Any]]:
|
||||
"created_date": 1700000000.0,
|
||||
"modified": 1700000100.0,
|
||||
"favorite": True,
|
||||
"repair_version": 3,
|
||||
"preview_nsfw_level": 1,
|
||||
"loras": [
|
||||
{"hash": "hash1", "file_name": "lora1", "strength": 0.8},
|
||||
@@ -59,6 +60,7 @@ def sample_recipes() -> List[Dict[str, Any]]:
|
||||
"created_date": 1700000200.0,
|
||||
"modified": 1700000300.0,
|
||||
"favorite": False,
|
||||
"repair_version": 2,
|
||||
"preview_nsfw_level": 0,
|
||||
"loras": [{"hash": "hash3", "file_name": "lora3", "strength": 0.5}],
|
||||
"gen_params": {"prompt": "another prompt"},
|
||||
@@ -99,6 +101,7 @@ class TestPersistentRecipeCache:
|
||||
assert r1["base_model"] == "SD1.5"
|
||||
assert r1["fingerprint"] == "abc123"
|
||||
assert r1["favorite"] is True
|
||||
assert r1["repair_version"] == 3
|
||||
assert len(r1["loras"]) == 2
|
||||
assert r1["loras"][0]["hash"] == "hash1"
|
||||
assert r1["checkpoint"]["name"] == "model.safetensors"
|
||||
@@ -161,6 +164,7 @@ class TestPersistentRecipeCache:
|
||||
file_mtime REAL,
|
||||
file_size INTEGER,
|
||||
favorite INTEGER DEFAULT 0,
|
||||
repair_version INTEGER DEFAULT 0,
|
||||
preview_nsfw_level INTEGER DEFAULT 0,
|
||||
loras_json TEXT,
|
||||
checkpoint_json TEXT,
|
||||
@@ -706,6 +710,7 @@ class TestHasWorkflowColumn:
|
||||
file_mtime REAL,
|
||||
file_size INTEGER,
|
||||
favorite INTEGER DEFAULT 0,
|
||||
repair_version INTEGER DEFAULT 0,
|
||||
preview_nsfw_level INTEGER DEFAULT 0,
|
||||
loras_json TEXT,
|
||||
checkpoint_json TEXT,
|
||||
|
||||
@@ -27,6 +27,18 @@
|
||||
<line x1="6" y1="6" x2="18" y2="18" />
|
||||
</svg>
|
||||
</button>
|
||||
<button
|
||||
v-if="isLorasMode"
|
||||
type="button"
|
||||
class="active-filters-toggle"
|
||||
:class="{ 'is-active': activeFiltersEnabled }"
|
||||
:title="activeFiltersToggleTitle"
|
||||
@click="toggleActiveFiltersSearch"
|
||||
>
|
||||
<svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2">
|
||||
<polygon points="22 3 2 3 10 12.46 10 19 14 21 14 12.46 22 3" />
|
||||
</svg>
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</template>
|
||||
@@ -34,6 +46,8 @@
|
||||
<script setup lang="ts">
|
||||
import { ref, onMounted, onUnmounted, computed } from 'vue'
|
||||
import { useAutocomplete } from '@/composables/useAutocomplete'
|
||||
// @ts-ignore - ComfyUI external module
|
||||
import { LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID, SETTING_TOGGLED_EVENT_NAME, getLoraActiveFiltersAutocompletePreference, setLoraManagerSettingValue } from '../../../web/comfyui/settings.js'
|
||||
|
||||
// Access LiteGraph global for initial mode detection
|
||||
declare const LiteGraph: { vueNodesMode?: boolean } | undefined
|
||||
@@ -73,10 +87,10 @@ const inputWrapperRef = ref<HTMLElement | null>(null)
|
||||
// Width of the textarea's own vertical scrollbar gutter. When the content
|
||||
// overflows and a classic (non-overlay) scrollbar is shown, the scrollbar
|
||||
// occupies the textarea's rightmost pixels and the absolutely-positioned
|
||||
// corner clear (x) button would overlap it. We expose this width as a CSS
|
||||
// var so the button can shift left of the scrollbar; it is 0 when there is
|
||||
// no scrollbar (content fits, or platform overlay scrollbars that float
|
||||
// over the content).
|
||||
// corner buttons (clear x / active-filters filter) would overlap it. We
|
||||
// expose this width as a CSS var so those buttons can shift left of the
|
||||
// scrollbar; it is 0 when there is no scrollbar (content fits, or platform
|
||||
// overlay scrollbars that float over the content).
|
||||
const vScrollbarWidth = ref(0)
|
||||
let scrollbarResizeObserver: ResizeObserver | null = null
|
||||
|
||||
@@ -111,6 +125,48 @@ const hasText = ref(false)
|
||||
// Show clear button when there is text
|
||||
const showClearButton = computed(() => hasText.value)
|
||||
|
||||
// Active-filters search indicator (loras nodes only). Mirrors the
|
||||
// loramanager.lora_active_filters_autocomplete setting so users can
|
||||
// discover and toggle the /activefilters mode without opening the
|
||||
// dropdown or the settings dialog.
|
||||
const isLorasMode = (props.modelType ?? 'loras') === 'loras'
|
||||
const activeFiltersEnabled = ref(false)
|
||||
|
||||
const refreshActiveFiltersState = () => {
|
||||
if (isLorasMode) {
|
||||
activeFiltersEnabled.value = getLoraActiveFiltersAutocompletePreference()
|
||||
}
|
||||
}
|
||||
|
||||
const onSettingToggled = (event: Event) => {
|
||||
const detail = (event as CustomEvent<{ settingId?: string; value?: unknown }>).detail
|
||||
if (detail?.settingId === LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID) {
|
||||
activeFiltersEnabled.value = detail.value === true
|
||||
}
|
||||
}
|
||||
|
||||
const activeFiltersToggleTitle = computed(() =>
|
||||
activeFiltersEnabled.value
|
||||
? 'Active Filters Search is ON: suggestions respect the LoRA Manager page filters. Click to disable, or type /noactivefilters.'
|
||||
: 'Active Filters Search is OFF: suggestions search the full library. Click to enable, or type /activefilters.'
|
||||
)
|
||||
|
||||
const toggleActiveFiltersSearch = async () => {
|
||||
const newValue = !activeFiltersEnabled.value
|
||||
try {
|
||||
const success = await setLoraManagerSettingValue(
|
||||
LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID,
|
||||
newValue
|
||||
)
|
||||
if (!success) {
|
||||
throw new Error('settings API unavailable')
|
||||
}
|
||||
activeFiltersEnabled.value = newValue
|
||||
} catch (error) {
|
||||
console.error('[Lora Manager] Failed to toggle active filters search:', error)
|
||||
}
|
||||
}
|
||||
|
||||
// Initialize autocomplete with direct ref access
|
||||
useAutocomplete(
|
||||
textareaRef,
|
||||
@@ -200,9 +256,6 @@ const onWheel = (event: WheelEvent) => {
|
||||
|
||||
// Handle external value changes (e.g., from "send lora to workflow")
|
||||
const onExternalValueChange = () => {
|
||||
// The DOM value was set synchronously by the caller; the new content may
|
||||
// have toggled the vertical scrollbar on/off.
|
||||
updateVScrollbarWidth()
|
||||
updateHasTextState()
|
||||
}
|
||||
|
||||
@@ -212,9 +265,6 @@ const setupWidgetOnSetValue = () => {
|
||||
props.widget.onSetValue = (value: string) => {
|
||||
// The DOM value is already set by setValue, just update our state
|
||||
hasText.value = value.length > 0
|
||||
// Programmatic sets can toggle the scrollbar; re-measure so the
|
||||
// corner clear button stays clear of it.
|
||||
updateVScrollbarWidth()
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -305,6 +355,11 @@ onMounted(() => {
|
||||
// Setup widget.onSetValue callback
|
||||
setupWidgetOnSetValue()
|
||||
|
||||
// Active-filters indicator: read initial state and stay in sync with
|
||||
// slash-command / context-menu toggles dispatched via settings.js
|
||||
refreshActiveFiltersState()
|
||||
window.addEventListener(SETTING_TOGGLED_EVENT_NAME, onSettingToggled)
|
||||
|
||||
// Keep the corner buttons clear of the textarea's vertical scrollbar.
|
||||
updateVScrollbarWidth()
|
||||
observeScrollbarWidth()
|
||||
@@ -336,6 +391,7 @@ onUnmounted(() => {
|
||||
|
||||
// Remove event listener
|
||||
document.removeEventListener('lora-manager:vue-mode-change', onModeChange)
|
||||
window.removeEventListener(SETTING_TOGGLED_EVENT_NAME, onSettingToggled)
|
||||
})
|
||||
</script>
|
||||
|
||||
@@ -428,6 +484,58 @@ onUnmounted(() => {
|
||||
height: 12px;
|
||||
}
|
||||
|
||||
/* Active-filters search indicator (loras nodes only) */
|
||||
.active-filters-toggle {
|
||||
position: absolute;
|
||||
top: 3px;
|
||||
right: calc(3px + var(--lm-vscrollbar-width, 0px));
|
||||
width: 16px;
|
||||
height: 16px;
|
||||
padding: 2px;
|
||||
margin: 0;
|
||||
border: none;
|
||||
border-radius: 4px;
|
||||
background: rgba(128, 128, 128, 0.25);
|
||||
color: rgba(255, 255, 255, 0.5);
|
||||
cursor: pointer;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
opacity: 0.7;
|
||||
transition: opacity 0.2s ease, background-color 0.2s ease, color 0.2s ease;
|
||||
z-index: 10;
|
||||
}
|
||||
|
||||
.active-filters-toggle:hover {
|
||||
opacity: 1;
|
||||
background: rgba(128, 128, 128, 0.45);
|
||||
color: rgba(255, 255, 255, 0.85);
|
||||
}
|
||||
|
||||
.active-filters-toggle.is-active {
|
||||
background: rgba(59, 130, 246, 0.35);
|
||||
color: #7db8ff;
|
||||
opacity: 1;
|
||||
}
|
||||
|
||||
.active-filters-toggle svg {
|
||||
width: 11px;
|
||||
height: 11px;
|
||||
}
|
||||
|
||||
/* Vue DOM mode adjustments for the indicator */
|
||||
.text-input.vue-dom-mode ~ .active-filters-toggle {
|
||||
top: 8px;
|
||||
right: calc(8px + var(--lm-vscrollbar-width, 0px));
|
||||
width: 20px;
|
||||
height: 20px;
|
||||
}
|
||||
|
||||
.text-input.vue-dom-mode ~ .active-filters-toggle svg {
|
||||
width: 13px;
|
||||
height: 13px;
|
||||
}
|
||||
|
||||
/* Vue DOM mode adjustments for clear button */
|
||||
.text-input.vue-dom-mode ~ .clear-button {
|
||||
right: calc(8px + var(--lm-vscrollbar-width, 0px));
|
||||
|
||||
@@ -10,13 +10,13 @@
|
||||
|
||||
import { nextTick } from 'vue'
|
||||
import { shallowMount } from '@vue/test-utils'
|
||||
import { describe, expect, it, vi, afterEach } from 'vitest'
|
||||
import { describe, expect, it, vi, beforeEach, afterEach } from 'vitest'
|
||||
import AutocompleteTextWidget from '@/components/AutocompleteTextWidget.vue'
|
||||
|
||||
function createMockWidget() {
|
||||
return {
|
||||
callback: vi.fn(),
|
||||
onSetValue: undefined as ((v: string) => void) | undefined,
|
||||
onSetValue: undefined,
|
||||
inputEl: undefined,
|
||||
metadataWidget: undefined,
|
||||
name: 'text',
|
||||
@@ -135,15 +135,121 @@ describe('AutocompleteTextWidget clear button', () => {
|
||||
})
|
||||
})
|
||||
|
||||
/**
|
||||
* Tests for the active-filters search indicator (loras mode only).
|
||||
*
|
||||
* The small filter chip in the textarea corner mirrors the
|
||||
* loramanager.lora_active_filters_autocomplete setting: it reflects the
|
||||
* current state, can toggle it, and stays in sync with slash-command /
|
||||
* context-menu toggles via the lora-manager:setting-toggled window event.
|
||||
*/
|
||||
|
||||
const settingsMocks = vi.hoisted(() => ({
|
||||
getPreference: vi.fn(),
|
||||
setValue: vi.fn(),
|
||||
}))
|
||||
|
||||
vi.mock('../../../web/comfyui/settings.js', () => ({
|
||||
LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID:
|
||||
'loramanager.lora_active_filters_autocomplete',
|
||||
SETTING_TOGGLED_EVENT_NAME: 'lora-manager:setting-toggled',
|
||||
getLoraActiveFiltersAutocompletePreference: settingsMocks.getPreference,
|
||||
setLoraManagerSettingValue: settingsMocks.setValue,
|
||||
}))
|
||||
|
||||
const getActiveFiltersPreferenceMock = settingsMocks.getPreference
|
||||
const setSettingValueMock = settingsMocks.setValue
|
||||
|
||||
function mountLorasWidget() {
|
||||
const widget = createMockWidget()
|
||||
const node = { id: 1 }
|
||||
const wrapper = shallowMount(AutocompleteTextWidget, {
|
||||
props: { widget, node, modelType: 'loras' },
|
||||
attachTo: document.body,
|
||||
})
|
||||
return { wrapper, widget }
|
||||
}
|
||||
|
||||
describe('AutocompleteTextWidget active-filters indicator', () => {
|
||||
beforeEach(() => {
|
||||
getActiveFiltersPreferenceMock.mockReset()
|
||||
getActiveFiltersPreferenceMock.mockReturnValue(false)
|
||||
setSettingValueMock.mockReset()
|
||||
setSettingValueMock.mockResolvedValue(true)
|
||||
})
|
||||
|
||||
it('renders only in loras mode', () => {
|
||||
const loras = mountLorasWidget()
|
||||
expect(loras.wrapper.find('.active-filters-toggle').exists()).toBe(true)
|
||||
|
||||
const widget = createMockWidget()
|
||||
const prompt = shallowMount(AutocompleteTextWidget, {
|
||||
props: { widget, node: { id: 2 }, modelType: 'prompt' },
|
||||
attachTo: document.body,
|
||||
})
|
||||
expect(prompt.find('.active-filters-toggle').exists()).toBe(false)
|
||||
})
|
||||
|
||||
it('reflects the current setting state', async () => {
|
||||
const { wrapper } = mountLorasWidget()
|
||||
await nextTick()
|
||||
expect(wrapper.find('.active-filters-toggle').classes()).not.toContain('is-active')
|
||||
|
||||
getActiveFiltersPreferenceMock.mockReturnValue(true)
|
||||
const wrapper2 = mountLorasWidget().wrapper
|
||||
await nextTick()
|
||||
expect(wrapper2.find('.active-filters-toggle').classes()).toContain('is-active')
|
||||
})
|
||||
|
||||
it('toggles the setting when clicked', async () => {
|
||||
const { wrapper } = mountLorasWidget()
|
||||
await nextTick()
|
||||
|
||||
await wrapper.find('.active-filters-toggle').trigger('click')
|
||||
expect(setSettingValueMock).toHaveBeenCalledWith(
|
||||
'loramanager.lora_active_filters_autocomplete',
|
||||
true
|
||||
)
|
||||
await nextTick()
|
||||
expect(wrapper.find('.active-filters-toggle').classes()).toContain('is-active')
|
||||
})
|
||||
|
||||
it('stays in sync with setting-toggled window events', async () => {
|
||||
const { wrapper } = mountLorasWidget()
|
||||
await nextTick()
|
||||
expect(wrapper.find('.active-filters-toggle').classes()).not.toContain('is-active')
|
||||
|
||||
window.dispatchEvent(
|
||||
new CustomEvent('lora-manager:setting-toggled', {
|
||||
detail: {
|
||||
settingId: 'loramanager.lora_active_filters_autocomplete',
|
||||
value: true,
|
||||
},
|
||||
})
|
||||
)
|
||||
await nextTick()
|
||||
expect(wrapper.find('.active-filters-toggle').classes()).toContain('is-active')
|
||||
|
||||
window.dispatchEvent(
|
||||
new CustomEvent('lora-manager:setting-toggled', {
|
||||
detail: { settingId: 'loramanager.some_other_setting', value: true },
|
||||
})
|
||||
)
|
||||
await nextTick()
|
||||
// Unrelated settings must not flip the indicator
|
||||
expect(wrapper.find('.active-filters-toggle').classes()).toContain('is-active')
|
||||
})
|
||||
})
|
||||
|
||||
/**
|
||||
* Tests for the vertical-scrollbar inset.
|
||||
*
|
||||
* When the textarea content overflows and a classic (non-overlay) scrollbar
|
||||
* is shown, the absolutely-positioned corner clear (x) button would sit on
|
||||
* top of the scrollbar. The component measures the scrollbar gutter and
|
||||
* exposes it as the --lm-vscrollbar-width CSS var on .input-wrapper so the
|
||||
* button shifts left of the scrollbar. jsdom does no layout, so overflow is
|
||||
* simulated by overriding the scroll/dimension props.
|
||||
* is shown, the absolutely-positioned corner buttons (clear x, active-filters
|
||||
* filter chip) would sit on top of the scrollbar. The component measures the
|
||||
* scrollbar gutter and exposes it as the --lm-vscrollbar-width CSS var on
|
||||
* .input-wrapper so the buttons shift left of the scrollbar. jsdom does no
|
||||
* layout, so overflow is simulated by overriding the scroll/dimension props.
|
||||
*/
|
||||
describe('AutocompleteTextWidget vertical scrollbar inset', () => {
|
||||
function overrideTextareaMetrics(
|
||||
@@ -216,66 +322,4 @@ describe('AutocompleteTextWidget vertical scrollbar inset', () => {
|
||||
await nextTick()
|
||||
expect(wrapperEl.style.getPropertyValue('--lm-vscrollbar-width')).toBe('0px')
|
||||
})
|
||||
|
||||
it('re-measures the inset when the value is set programmatically via onSetValue', async () => {
|
||||
const { wrapper, widget } = mountWidget()
|
||||
const textarea = wrapper.find('textarea').element as HTMLTextAreaElement
|
||||
|
||||
// Start with no overflow
|
||||
overrideTextareaMetrics(textarea, {
|
||||
scrollHeight: 100,
|
||||
clientHeight: 100,
|
||||
offsetWidth: 320,
|
||||
clientWidth: 320,
|
||||
})
|
||||
await nextTick()
|
||||
|
||||
// Simulate an external setValue (e.g. "send lora to workflow"): the DOM
|
||||
// value is set by the caller and widget.onSetValue fires without an
|
||||
// input event. Content now overflows → inset must be re-measured.
|
||||
overrideTextareaMetrics(textarea, {
|
||||
scrollHeight: 200,
|
||||
clientHeight: 100,
|
||||
offsetWidth: 320,
|
||||
clientWidth: 305, // 15px scrollbar gutter
|
||||
})
|
||||
if (!widget.onSetValue) throw new Error('onSetValue not installed by component')
|
||||
widget.onSetValue('long content')
|
||||
await nextTick()
|
||||
|
||||
const wrapperEl = wrapper.find('.input-wrapper').element as HTMLElement
|
||||
expect(wrapperEl.style.getPropertyValue('--lm-vscrollbar-width')).toBe('15px')
|
||||
})
|
||||
|
||||
it('re-measures the inset on external value-change events', async () => {
|
||||
const { wrapper } = mountWidget()
|
||||
const textarea = wrapper.find('textarea').element as HTMLTextAreaElement
|
||||
|
||||
// Start with no overflow
|
||||
overrideTextareaMetrics(textarea, {
|
||||
scrollHeight: 100,
|
||||
clientHeight: 100,
|
||||
offsetWidth: 320,
|
||||
clientWidth: 320,
|
||||
})
|
||||
await nextTick()
|
||||
|
||||
// The lora-manager:autocomplete-value-changed event fires when the
|
||||
// widget value is set externally; content now overflows → re-measure.
|
||||
overrideTextareaMetrics(textarea, {
|
||||
scrollHeight: 200,
|
||||
clientHeight: 100,
|
||||
offsetWidth: 320,
|
||||
clientWidth: 305, // 15px scrollbar gutter
|
||||
})
|
||||
textarea.dispatchEvent(
|
||||
new CustomEvent('lora-manager:autocomplete-value-changed', {
|
||||
detail: { value: 'long content' },
|
||||
})
|
||||
)
|
||||
await nextTick()
|
||||
|
||||
const wrapperEl = wrapper.find('.input-wrapper').element as HTMLElement
|
||||
expect(wrapperEl.style.getPropertyValue('--lm-vscrollbar-width')).toBe('15px')
|
||||
})
|
||||
})
|
||||
|
||||
@@ -1,86 +1,12 @@
|
||||
import { defineConfig } from 'vite'
|
||||
import vue from '@vitejs/plugin-vue'
|
||||
import cssInjectedByJsPlugin from 'vite-plugin-css-injected-by-js'
|
||||
import { dirname, resolve } from 'path'
|
||||
|
||||
// Specifiers that must stay external. The bundle is emitted to
|
||||
// web/comfyui/vue-widgets/, and ComfyUI serves that directory's parent
|
||||
// (web/comfyui) at /extensions/ComfyUI-Lora-Manager/, so one "../" from the
|
||||
// bundle reaches web/comfyui modules and three "../../.." reach ComfyUI's
|
||||
// own runtime scripts at runtime.
|
||||
//
|
||||
// scripts/app.js and scripts/api.js are intentionally NOT listed here: they
|
||||
// are externalized by the keep-runtime-modules-external plugin below, which
|
||||
// also rewrites the shallower "../../scripts/*" specifiers used by modules
|
||||
// inlined from web/comfyui/ so every binding dedupes into a single import.
|
||||
const EXTERNAL_SPECIFIERS = [
|
||||
'../loras_widget.js',
|
||||
'../autocomplete.js',
|
||||
'../preview_tooltip.js'
|
||||
]
|
||||
import { resolve } from 'path'
|
||||
|
||||
export default defineConfig({
|
||||
plugins: [
|
||||
vue(),
|
||||
cssInjectedByJsPlugin(), // Inject CSS into JS for ComfyUI compatibility
|
||||
// Keep shared runtime modules external instead of inlining them into
|
||||
// the bundle. This guards against the inlined-shim bug class (the
|
||||
// removed active-filters chip ended up writing settings to a dead
|
||||
// in-memory store this way):
|
||||
//
|
||||
// 1. Modules under web/comfyui/ import the repo-root scripts/app.js
|
||||
// TEST SHIM as "../../scripts/app.js" — a depth that resolves to
|
||||
// the shim on the build filesystem but 404s at the bundle's
|
||||
// runtime location. Rewrite to the canonical bundle-depth
|
||||
// specifier so every app/api binding in the bundle is the REAL
|
||||
// ComfyUI module.
|
||||
// 2. web/comfyui/settings.js must never be duplicated into the
|
||||
// bundle: it registers settings via a module-level side effect
|
||||
// and owns module state. Externalize it to "../settings.js" so
|
||||
// the bundle binds to the SAME vanilla module instance that the
|
||||
// ComfyUI extension loader already loaded.
|
||||
{
|
||||
name: 'lora-manager:keep-runtime-modules-external',
|
||||
enforce: 'pre',
|
||||
resolveId(source, importer) {
|
||||
const scriptsMatch = source.match(/^(\.\.\/)+scripts\/(app|api)\.js$/)
|
||||
if (scriptsMatch) {
|
||||
return { id: `../../../scripts/${scriptsMatch[2]}.js`, external: true }
|
||||
}
|
||||
if (
|
||||
importer &&
|
||||
/[\\/]web[\\/]comfyui[\\/]settings\.js$/.test(
|
||||
resolve(dirname(importer), source)
|
||||
)
|
||||
) {
|
||||
return { id: '../settings.js', external: true }
|
||||
}
|
||||
return null
|
||||
},
|
||||
},
|
||||
// Warning twin of the rewrite above: importing web/comfyui/* from
|
||||
// widget source inlines that module into the bundle, duplicating any
|
||||
// module-level side effects/state it owns. The settings.js and
|
||||
// scripts/app|api.js imports are made safe by the plugin above, but
|
||||
// review any further such import deliberately.
|
||||
{
|
||||
name: 'lora-manager:warn-web-comfyui-imports',
|
||||
enforce: 'pre',
|
||||
resolveId(source, importer) {
|
||||
if (
|
||||
importer &&
|
||||
/[\\/]vue-widgets[\\/]src[\\/]/.test(importer) &&
|
||||
/[\\/]web[\\/]comfyui[\\/]/.test(source)
|
||||
) {
|
||||
this.warn(
|
||||
`[vue-widgets] Inlining web/comfyui module "${source}" into the bundle. ` +
|
||||
'settings.js and scripts/app|api.js imports are externalized by this config, ' +
|
||||
'but the inlined copy still duplicates module-level side effects — verify that is intended.'
|
||||
)
|
||||
}
|
||||
return null
|
||||
},
|
||||
},
|
||||
cssInjectedByJsPlugin() // Inject CSS into JS for ComfyUI compatibility
|
||||
],
|
||||
resolve: {
|
||||
alias: {
|
||||
@@ -94,7 +20,13 @@ export default defineConfig({
|
||||
fileName: 'lora-manager-widgets'
|
||||
},
|
||||
rollupOptions: {
|
||||
external: EXTERNAL_SPECIFIERS,
|
||||
external: [
|
||||
'../../../scripts/app.js',
|
||||
'../../../scripts/api.js',
|
||||
'../loras_widget.js',
|
||||
'../autocomplete.js',
|
||||
'../preview_tooltip.js'
|
||||
],
|
||||
output: {
|
||||
dir: '../web/comfyui/vue-widgets',
|
||||
entryFileNames: 'lora-manager-widgets.js',
|
||||
@@ -109,4 +41,3 @@ export default defineConfig({
|
||||
'process.env.NODE_ENV': JSON.stringify('production')
|
||||
}
|
||||
})
|
||||
|
||||
|
||||
@@ -14,9 +14,11 @@ import {
|
||||
getAutocompleteAppendCommaPreference,
|
||||
getAutocompleteAutoFormatPreference,
|
||||
getAutocompleteAcceptKeyPreference,
|
||||
LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID,
|
||||
getLoraActiveFiltersAutocompletePreference,
|
||||
getPromptTagAutocompletePreference,
|
||||
getTagSpaceReplacementPreference,
|
||||
SETTING_TOGGLED_EVENT_NAME,
|
||||
setLoraManagerSettingValue,
|
||||
} from "./settings.js";
|
||||
import { showToast } from "./utils.js";
|
||||
@@ -607,6 +609,7 @@ class AutoComplete {
|
||||
this.onBlur = null;
|
||||
this.onDocumentClick = null;
|
||||
this.onScroll = null;
|
||||
this.onSettingToggled = null;
|
||||
|
||||
this.init();
|
||||
}
|
||||
@@ -774,6 +777,22 @@ class AutoComplete {
|
||||
};
|
||||
document.addEventListener('click', this.onDocumentClick);
|
||||
|
||||
// React to setting changes that happen underneath an open dropdown
|
||||
// (e.g. toggling the active-filters search from the node's filter
|
||||
// chip can keep the dropdown open in ComfyUI). Refresh the state
|
||||
// hints so they never show a message for the previous state.
|
||||
if (this.onSettingToggled) {
|
||||
window.removeEventListener(SETTING_TOGGLED_EVENT_NAME, this.onSettingToggled);
|
||||
}
|
||||
this.onSettingToggled = (e) => {
|
||||
const detail = e && e.detail;
|
||||
if (!detail || detail.settingId !== LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID) {
|
||||
return;
|
||||
}
|
||||
this._refreshStateHints();
|
||||
};
|
||||
window.addEventListener(SETTING_TOGGLED_EVENT_NAME, this.onSettingToggled);
|
||||
|
||||
// Mark this element as having autocomplete events bound
|
||||
this.inputElement._autocompleteEventsBound = true;
|
||||
|
||||
@@ -1811,15 +1830,37 @@ class AutoComplete {
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Refresh state-dependent dropdown decorations (first-run Tip and the
|
||||
* slash-command-list footer) from the live setting. Called when the
|
||||
* active-filters toggle changes underneath an open dropdown, so the
|
||||
* dropdown never keeps showing a message for the previous state.
|
||||
*/
|
||||
_refreshStateHints() {
|
||||
if (!this.isVisible || this.modelType !== 'loras') {
|
||||
return;
|
||||
}
|
||||
if (this.showingCommands) {
|
||||
// Command list: footer text carries the ON/OFF state.
|
||||
this._renderCommandListFooter();
|
||||
} else {
|
||||
// Plain suggestions: the first-run Tip advertises /activefilters
|
||||
// only while the feature is disabled.
|
||||
this._maybeShowFirstRunHint();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Show a one-time, dismissible hint inside the dropdown surfacing the
|
||||
* toggle commands: prompt nodes advertise /noautocomplete, loras nodes
|
||||
* advertise /activefilters. Dismissal is persisted in localStorage.
|
||||
*/
|
||||
_maybeShowFirstRunHint() {
|
||||
if (this.firstRunHint) {
|
||||
return;
|
||||
}
|
||||
// Dropdown decorations can outlive a state change (the dropdown may
|
||||
// stay open when the setting is toggled from the node, e.g. clicking
|
||||
// the active-filters filter chip). Always recompute from the live
|
||||
// state so a stale Tip is never kept for the previous state.
|
||||
this._removeFirstRunHint();
|
||||
|
||||
let hintText = null;
|
||||
let storageKey = null;
|
||||
@@ -3178,6 +3219,11 @@ class AutoComplete {
|
||||
this.onDocumentClick = null;
|
||||
}
|
||||
|
||||
if (this.onSettingToggled) {
|
||||
window.removeEventListener(SETTING_TOGGLED_EVENT_NAME, this.onSettingToggled);
|
||||
this.onSettingToggled = null;
|
||||
}
|
||||
|
||||
if (this.onScroll && this.scrollContainer) {
|
||||
this.scrollContainer.removeEventListener('scroll', this.onScroll);
|
||||
this.onScroll = null;
|
||||
|
||||
+21
-1
@@ -175,23 +175,42 @@ const getPromptTagAutocompletePreference = (() => {
|
||||
/**
|
||||
* Persist a LoRA Manager setting through ComfyUI's setting API.
|
||||
* Returns true when the setting was written successfully.
|
||||
*
|
||||
* Every successful write broadcasts a "lora-manager:setting-toggled" window
|
||||
* event (see SETTING_TOGGLED_EVENT_NAME) so widgets mirroring the setting
|
||||
* (e.g. the active-filters indicator in the autocomplete text widget) stay in
|
||||
* sync with slash-command / context-menu toggles.
|
||||
*/
|
||||
const SETTING_TOGGLED_EVENT_NAME = "lora-manager:setting-toggled";
|
||||
|
||||
const setLoraManagerSettingValue = async (settingId, value) => {
|
||||
const settingManager = app?.extensionManager?.setting;
|
||||
if (settingManager && typeof settingManager.set === "function") {
|
||||
await settingManager.set(settingId, value);
|
||||
_notifySettingToggled(settingId, value);
|
||||
return true;
|
||||
}
|
||||
|
||||
const setting = app?.ui?.settings?.settingsById?.[settingId];
|
||||
if (setting) {
|
||||
app.ui.settings.setSettingValue(settingId, value);
|
||||
_notifySettingToggled(settingId, value);
|
||||
return true;
|
||||
}
|
||||
|
||||
return false;
|
||||
};
|
||||
|
||||
const _notifySettingToggled = (settingId, value) => {
|
||||
try {
|
||||
window.dispatchEvent(new CustomEvent(SETTING_TOGGLED_EVENT_NAME, {
|
||||
detail: { settingId, value },
|
||||
}));
|
||||
} catch (error) {
|
||||
// Best-effort notification; ignore non-browser environments
|
||||
}
|
||||
};
|
||||
|
||||
const getAutocompleteAppendCommaPreference = (() => {
|
||||
let settingsUnavailableLogged = false;
|
||||
|
||||
@@ -450,7 +469,7 @@ app.registerExtension({
|
||||
name: "Search LoRA autocomplete within active filters",
|
||||
type: "boolean",
|
||||
defaultValue: LORA_ACTIVE_FILTERS_AUTOCOMPLETE_DEFAULT,
|
||||
tooltip: "When enabled, LoRA autocomplete suggestions respect the active filters (folder/base model/tags) set in the LoRA Manager page. You can also toggle it by typing /activefilters or /noactivefilters in the LoRA field, or from the node's right-click menu.",
|
||||
tooltip: "When enabled, LoRA autocomplete suggestions respect the active filters (folder/base model/tags) set in the LoRA Manager page. Commands /activefilters and /noactivefilters toggle this mode.",
|
||||
category: ["LoRA Manager", "Autocomplete", "LoRA Active Filters"],
|
||||
},
|
||||
{
|
||||
@@ -598,6 +617,7 @@ app.registerExtension({
|
||||
export {
|
||||
PROMPT_TAG_AUTOCOMPLETE_SETTING_ID,
|
||||
LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID,
|
||||
SETTING_TOGGLED_EVENT_NAME,
|
||||
getWheelSensitivity,
|
||||
getAutoPathCorrectionPreference,
|
||||
getAutocompleteAppendCommaPreference,
|
||||
|
||||
@@ -2118,14 +2118,14 @@ to { transform: rotate(360deg);
|
||||
padding: 20px 0;
|
||||
}
|
||||
|
||||
.autocomplete-text-widget[data-v-793d67d2] {
|
||||
.autocomplete-text-widget[data-v-22743258] {
|
||||
background: transparent;
|
||||
height: 100%;
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
box-sizing: border-box;
|
||||
}
|
||||
.input-wrapper[data-v-793d67d2] {
|
||||
.input-wrapper[data-v-22743258] {
|
||||
position: relative;
|
||||
flex: 1;
|
||||
display: flex;
|
||||
@@ -2133,7 +2133,7 @@ to { transform: rotate(360deg);
|
||||
}
|
||||
|
||||
/* Canvas mode styles (default) - matches built-in comfy-multiline-input */
|
||||
.text-input[data-v-793d67d2] {
|
||||
.text-input[data-v-22743258] {
|
||||
flex: 1;
|
||||
width: 100%;
|
||||
background-color: var(--comfy-input-bg, #222);
|
||||
@@ -2152,7 +2152,7 @@ to { transform: rotate(360deg);
|
||||
}
|
||||
|
||||
/* Vue DOM mode styles - matches built-in p-textarea in Vue DOM mode */
|
||||
.text-input.vue-dom-mode[data-v-793d67d2] {
|
||||
.text-input.vue-dom-mode[data-v-22743258] {
|
||||
background-color: var(--color-charcoal-400, #313235);
|
||||
color: #fff;
|
||||
padding: 8px 12px 30px 12px; /* Reserve bottom space for clear button */
|
||||
@@ -2161,12 +2161,12 @@ to { transform: rotate(360deg);
|
||||
font-size: 12px;
|
||||
font-family: inherit;
|
||||
}
|
||||
.text-input[data-v-793d67d2]:focus {
|
||||
.text-input[data-v-22743258]:focus {
|
||||
outline: none;
|
||||
}
|
||||
|
||||
/* Clear button styles */
|
||||
.clear-button[data-v-793d67d2] {
|
||||
.clear-button[data-v-22743258] {
|
||||
position: absolute;
|
||||
right: calc(6px + var(--lm-vscrollbar-width, 0px));
|
||||
bottom: 6px; /* Changed from top to bottom */
|
||||
@@ -2189,31 +2189,79 @@ to { transform: rotate(360deg);
|
||||
}
|
||||
|
||||
/* Show clear button when hovering over input wrapper */
|
||||
.input-wrapper:hover .clear-button[data-v-793d67d2] {
|
||||
.input-wrapper:hover .clear-button[data-v-22743258] {
|
||||
opacity: 0.7;
|
||||
pointer-events: auto;
|
||||
}
|
||||
.clear-button[data-v-793d67d2]:hover {
|
||||
.clear-button[data-v-22743258]:hover {
|
||||
opacity: 1;
|
||||
background: rgba(255, 100, 100, 0.8);
|
||||
}
|
||||
.clear-button svg[data-v-793d67d2] {
|
||||
.clear-button svg[data-v-22743258] {
|
||||
width: 12px;
|
||||
height: 12px;
|
||||
}
|
||||
|
||||
/* Active-filters search indicator (loras nodes only) */
|
||||
.active-filters-toggle[data-v-22743258] {
|
||||
position: absolute;
|
||||
top: 3px;
|
||||
right: calc(3px + var(--lm-vscrollbar-width, 0px));
|
||||
width: 16px;
|
||||
height: 16px;
|
||||
padding: 2px;
|
||||
margin: 0;
|
||||
border: none;
|
||||
border-radius: 4px;
|
||||
background: rgba(128, 128, 128, 0.25);
|
||||
color: rgba(255, 255, 255, 0.5);
|
||||
cursor: pointer;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
opacity: 0.7;
|
||||
transition: opacity 0.2s ease, background-color 0.2s ease, color 0.2s ease;
|
||||
z-index: 10;
|
||||
}
|
||||
.active-filters-toggle[data-v-22743258]:hover {
|
||||
opacity: 1;
|
||||
background: rgba(128, 128, 128, 0.45);
|
||||
color: rgba(255, 255, 255, 0.85);
|
||||
}
|
||||
.active-filters-toggle.is-active[data-v-22743258] {
|
||||
background: rgba(59, 130, 246, 0.35);
|
||||
color: #7db8ff;
|
||||
opacity: 1;
|
||||
}
|
||||
.active-filters-toggle svg[data-v-22743258] {
|
||||
width: 11px;
|
||||
height: 11px;
|
||||
}
|
||||
|
||||
/* Vue DOM mode adjustments for the indicator */
|
||||
.text-input.vue-dom-mode ~ .active-filters-toggle[data-v-22743258] {
|
||||
top: 8px;
|
||||
right: calc(8px + var(--lm-vscrollbar-width, 0px));
|
||||
width: 20px;
|
||||
height: 20px;
|
||||
}
|
||||
.text-input.vue-dom-mode ~ .active-filters-toggle svg[data-v-22743258] {
|
||||
width: 13px;
|
||||
height: 13px;
|
||||
}
|
||||
|
||||
/* Vue DOM mode adjustments for clear button */
|
||||
.text-input.vue-dom-mode ~ .clear-button[data-v-793d67d2] {
|
||||
.text-input.vue-dom-mode ~ .clear-button[data-v-22743258] {
|
||||
right: calc(8px + var(--lm-vscrollbar-width, 0px));
|
||||
bottom: 10px; /* Changed from top to bottom, adjusted for Vue DOM padding */
|
||||
width: 20px;
|
||||
height: 20px;
|
||||
background: rgba(107, 114, 128, 0.6);
|
||||
}
|
||||
.text-input.vue-dom-mode ~ .clear-button[data-v-793d67d2]:hover {
|
||||
.text-input.vue-dom-mode ~ .clear-button[data-v-22743258]:hover {
|
||||
background: oklch(62% 0.18 25);
|
||||
}
|
||||
.text-input.vue-dom-mode ~ .clear-button svg[data-v-793d67d2] {
|
||||
.text-input.vue-dom-mode ~ .clear-button svg[data-v-22743258] {
|
||||
width: 14px;
|
||||
height: 14px;
|
||||
}
|
||||
@@ -2481,9 +2529,8 @@ to { transform: rotate(360deg);
|
||||
}
|
||||
})();
|
||||
var _a;
|
||||
import { app } from "../../../scripts/app.js";
|
||||
import { api } from "../../../scripts/api.js";
|
||||
import "../settings.js";
|
||||
import { app as app$1 } from "../../../scripts/app.js";
|
||||
import { api as api$1 } from "../../../scripts/api.js";
|
||||
/**
|
||||
* @vue/shared v3.5.26
|
||||
* (c) 2018-present Yuxi (Evan) You and Vue contributors
|
||||
@@ -11053,7 +11100,7 @@ const _sfc_main$o = /* @__PURE__ */ defineComponent({
|
||||
const EditButton = /* @__PURE__ */ _export_sfc(_sfc_main$o, [["__scopeId", "data-v-8da8aa4b"]]);
|
||||
const _hoisted_1$k = { class: "section" };
|
||||
const _hoisted_2$j = { class: "section__header" };
|
||||
const _hoisted_3$g = { class: "section__content" };
|
||||
const _hoisted_3$h = { class: "section__content" };
|
||||
const _hoisted_4$f = {
|
||||
key: 0,
|
||||
class: "section__placeholder"
|
||||
@@ -11083,7 +11130,7 @@ const _sfc_main$n = /* @__PURE__ */ defineComponent({
|
||||
onClick: _cache[0] || (_cache[0] = ($event) => _ctx.$emit("edit"))
|
||||
})
|
||||
]),
|
||||
createBaseVNode("div", _hoisted_3$g, [
|
||||
createBaseVNode("div", _hoisted_3$h, [
|
||||
__props.selected.length === 0 ? (openBlock(), createElementBlock("div", _hoisted_4$f, " All models ")) : (openBlock(), createElementBlock("div", _hoisted_5$d, [
|
||||
(openBlock(true), createElementBlock(Fragment, null, renderList(__props.selected, (name) => {
|
||||
return openBlock(), createBlock(FilterChip, {
|
||||
@@ -11102,7 +11149,7 @@ const _sfc_main$n = /* @__PURE__ */ defineComponent({
|
||||
const BaseModelSection = /* @__PURE__ */ _export_sfc(_sfc_main$n, [["__scopeId", "data-v-12f059e2"]]);
|
||||
const _hoisted_1$j = { class: "section" };
|
||||
const _hoisted_2$i = { class: "section__columns" };
|
||||
const _hoisted_3$f = { class: "section__column" };
|
||||
const _hoisted_3$g = { class: "section__column" };
|
||||
const _hoisted_4$e = { class: "section__column-header" };
|
||||
const _hoisted_5$c = { class: "section__column-content" };
|
||||
const _hoisted_6$c = {
|
||||
@@ -11138,7 +11185,7 @@ const _sfc_main$m = /* @__PURE__ */ defineComponent({
|
||||
createBaseVNode("span", { class: "section__title" }, "TAGS")
|
||||
], -1)),
|
||||
createBaseVNode("div", _hoisted_2$i, [
|
||||
createBaseVNode("div", _hoisted_3$f, [
|
||||
createBaseVNode("div", _hoisted_3$g, [
|
||||
createBaseVNode("div", _hoisted_4$e, [
|
||||
_cache[2] || (_cache[2] = createBaseVNode("span", { class: "section__column-title section__column-title--include" }, "INCLUDE", -1)),
|
||||
createVNode(EditButton, {
|
||||
@@ -11184,7 +11231,7 @@ const _sfc_main$m = /* @__PURE__ */ defineComponent({
|
||||
const TagsSection = /* @__PURE__ */ _export_sfc(_sfc_main$m, [["__scopeId", "data-v-b869b780"]]);
|
||||
const _hoisted_1$i = { class: "section" };
|
||||
const _hoisted_2$h = { class: "section__columns" };
|
||||
const _hoisted_3$e = { class: "section__column" };
|
||||
const _hoisted_3$f = { class: "section__column" };
|
||||
const _hoisted_4$d = { class: "section__column-header" };
|
||||
const _hoisted_5$b = { class: "section__content" };
|
||||
const _hoisted_6$b = {
|
||||
@@ -11232,7 +11279,7 @@ const _sfc_main$l = /* @__PURE__ */ defineComponent({
|
||||
createBaseVNode("span", { class: "section__title" }, "FOLDERS")
|
||||
], -1)),
|
||||
createBaseVNode("div", _hoisted_2$h, [
|
||||
createBaseVNode("div", _hoisted_3$e, [
|
||||
createBaseVNode("div", _hoisted_3$f, [
|
||||
createBaseVNode("div", _hoisted_4$d, [
|
||||
_cache[3] || (_cache[3] = createBaseVNode("span", { class: "section__column-title section__column-title--include" }, "INCLUDE", -1)),
|
||||
createBaseVNode("button", {
|
||||
@@ -11300,7 +11347,7 @@ const _sfc_main$l = /* @__PURE__ */ defineComponent({
|
||||
const FoldersSection = /* @__PURE__ */ _export_sfc(_sfc_main$l, [["__scopeId", "data-v-af9caf84"]]);
|
||||
const _hoisted_1$h = { class: "section" };
|
||||
const _hoisted_2$g = { class: "section__header" };
|
||||
const _hoisted_3$d = { class: "section__toggle" };
|
||||
const _hoisted_3$e = { class: "section__toggle" };
|
||||
const _hoisted_4$c = ["checked"];
|
||||
const _hoisted_5$a = { class: "section__columns" };
|
||||
const _hoisted_6$a = { class: "section__column" };
|
||||
@@ -11356,7 +11403,7 @@ const _sfc_main$k = /* @__PURE__ */ defineComponent({
|
||||
return openBlock(), createElementBlock("div", _hoisted_1$h, [
|
||||
createBaseVNode("div", _hoisted_2$g, [
|
||||
_cache[4] || (_cache[4] = createBaseVNode("span", { class: "section__title" }, "NAME PATTERNS", -1)),
|
||||
createBaseVNode("label", _hoisted_3$d, [
|
||||
createBaseVNode("label", _hoisted_3$e, [
|
||||
createBaseVNode("input", {
|
||||
type: "checkbox",
|
||||
checked: __props.useRegex,
|
||||
@@ -11440,7 +11487,7 @@ const _sfc_main$k = /* @__PURE__ */ defineComponent({
|
||||
const NamePatternsSection = /* @__PURE__ */ _export_sfc(_sfc_main$k, [["__scopeId", "data-v-9995b5ed"]]);
|
||||
const _hoisted_1$g = { class: "section" };
|
||||
const _hoisted_2$f = { class: "section__toggles" };
|
||||
const _hoisted_3$c = { class: "toggle-item" };
|
||||
const _hoisted_3$d = { class: "toggle-item" };
|
||||
const _hoisted_4$b = ["aria-checked"];
|
||||
const _hoisted_5$9 = { class: "toggle-item" };
|
||||
const _hoisted_6$9 = ["aria-checked"];
|
||||
@@ -11458,7 +11505,7 @@ const _sfc_main$j = /* @__PURE__ */ defineComponent({
|
||||
createBaseVNode("span", { class: "section__title" }, "LICENSE")
|
||||
], -1)),
|
||||
createBaseVNode("div", _hoisted_2$f, [
|
||||
createBaseVNode("label", _hoisted_3$c, [
|
||||
createBaseVNode("label", _hoisted_3$d, [
|
||||
_cache[3] || (_cache[3] = createBaseVNode("span", {
|
||||
class: "toggle-item__label",
|
||||
title: "Use the model without crediting the creator"
|
||||
@@ -11498,7 +11545,7 @@ const _sfc_main$j = /* @__PURE__ */ defineComponent({
|
||||
const LicenseSection = /* @__PURE__ */ _export_sfc(_sfc_main$j, [["__scopeId", "data-v-07ddd3df"]]);
|
||||
const _hoisted_1$f = { class: "preview" };
|
||||
const _hoisted_2$e = { class: "preview__title" };
|
||||
const _hoisted_3$b = ["disabled"];
|
||||
const _hoisted_3$c = ["disabled"];
|
||||
const _hoisted_4$a = {
|
||||
key: 0,
|
||||
class: "preview__tooltip"
|
||||
@@ -11557,7 +11604,7 @@ const _sfc_main$i = /* @__PURE__ */ defineComponent({
|
||||
d: "M8 3c-1.552 0-2.94.707-3.857 1.818a.5.5 0 1 1-.771-.636A6.002 6.002 0 0 1 13.917 7H12.9A5.002 5.002 0 0 0 8 3zM3.1 9a5.002 5.002 0 0 0 8.757 2.182.5.5 0 1 1 .771.636A6.002 6.002 0 0 1 2.083 9H3.1z"
|
||||
})
|
||||
], -1)
|
||||
])], 10, _hoisted_3$b)
|
||||
])], 10, _hoisted_3$c)
|
||||
], 32),
|
||||
createVNode(Transition, { name: "tooltip" }, {
|
||||
default: withCtx(() => [
|
||||
@@ -11669,7 +11716,7 @@ const _sfc_main$h = /* @__PURE__ */ defineComponent({
|
||||
const LoraPoolSummaryView = /* @__PURE__ */ _export_sfc(_sfc_main$h, [["__scopeId", "data-v-83235a00"]]);
|
||||
const _hoisted_1$d = { class: "lora-pool-modal__header" };
|
||||
const _hoisted_2$c = { class: "lora-pool-modal__title-container" };
|
||||
const _hoisted_3$a = { class: "lora-pool-modal__title" };
|
||||
const _hoisted_3$b = { class: "lora-pool-modal__title" };
|
||||
const _hoisted_4$9 = {
|
||||
key: 0,
|
||||
class: "lora-pool-modal__subtitle"
|
||||
@@ -11729,7 +11776,7 @@ const _sfc_main$g = /* @__PURE__ */ defineComponent({
|
||||
}, [
|
||||
createBaseVNode("div", _hoisted_1$d, [
|
||||
createBaseVNode("div", _hoisted_2$c, [
|
||||
createBaseVNode("h3", _hoisted_3$a, toDisplayString(__props.title), 1),
|
||||
createBaseVNode("h3", _hoisted_3$b, toDisplayString(__props.title), 1),
|
||||
__props.subtitle ? (openBlock(), createElementBlock("p", _hoisted_4$9, toDisplayString(__props.subtitle), 1)) : createCommentVNode("", true)
|
||||
]),
|
||||
createBaseVNode("button", {
|
||||
@@ -11757,7 +11804,7 @@ const _sfc_main$g = /* @__PURE__ */ defineComponent({
|
||||
const ModalWrapper = /* @__PURE__ */ _export_sfc(_sfc_main$g, [["__scopeId", "data-v-7b4de03d"]]);
|
||||
const _hoisted_1$c = { class: "search-container" };
|
||||
const _hoisted_2$b = { class: "model-list" };
|
||||
const _hoisted_3$9 = ["checked", "onChange"];
|
||||
const _hoisted_3$a = ["checked", "onChange"];
|
||||
const _hoisted_4$8 = { class: "model-checkbox-visual" };
|
||||
const _hoisted_5$6 = {
|
||||
key: 0,
|
||||
@@ -11867,7 +11914,7 @@ const _sfc_main$f = /* @__PURE__ */ defineComponent({
|
||||
checked: isSelected(model.name),
|
||||
onChange: ($event) => toggleModel(model.name),
|
||||
class: "model-checkbox"
|
||||
}, null, 40, _hoisted_3$9),
|
||||
}, null, 40, _hoisted_3$a),
|
||||
createBaseVNode("span", _hoisted_4$8, [
|
||||
isSelected(model.name) ? (openBlock(), createElementBlock("svg", _hoisted_5$6, [..._cache[4] || (_cache[4] = [
|
||||
createBaseVNode("path", { d: "M13.854 3.646a.5.5 0 0 1 0 .708l-7 7a.5.5 0 0 1-.708 0l-3.5-3.5a.5.5 0 1 1 .708-.708L6.5 10.293l6.646-6.647a.5.5 0 0 1 .708 0z" }, null, -1)
|
||||
@@ -11888,7 +11935,7 @@ const _sfc_main$f = /* @__PURE__ */ defineComponent({
|
||||
const BaseModelModal = /* @__PURE__ */ _export_sfc(_sfc_main$f, [["__scopeId", "data-v-e02ca44a"]]);
|
||||
const _hoisted_1$b = { class: "search-container" };
|
||||
const _hoisted_2$a = ["onClick"];
|
||||
const _hoisted_3$8 = {
|
||||
const _hoisted_3$9 = {
|
||||
key: 0,
|
||||
class: "no-results"
|
||||
};
|
||||
@@ -12032,7 +12079,7 @@ const _sfc_main$e = /* @__PURE__ */ defineComponent({
|
||||
onClick: ($event) => toggleTag(tag.tag)
|
||||
}, toDisplayString(tag.tag), 11, _hoisted_2$a);
|
||||
}), 128)),
|
||||
visibleTags.value.length === 0 ? (openBlock(), createElementBlock("div", _hoisted_3$8, " No tags found ")) : createCommentVNode("", true),
|
||||
visibleTags.value.length === 0 ? (openBlock(), createElementBlock("div", _hoisted_3$9, " No tags found ")) : createCommentVNode("", true),
|
||||
hasMoreTags.value ? (openBlock(), createElementBlock("div", _hoisted_4$7, " Scroll to load more... ")) : createCommentVNode("", true)
|
||||
], 544)
|
||||
]),
|
||||
@@ -12047,7 +12094,7 @@ const _hoisted_2$9 = {
|
||||
key: 1,
|
||||
class: "tree-node__toggle-spacer"
|
||||
};
|
||||
const _hoisted_3$7 = { class: "tree-node__checkbox-label" };
|
||||
const _hoisted_3$8 = { class: "tree-node__checkbox-label" };
|
||||
const _hoisted_4$6 = ["checked"];
|
||||
const _hoisted_5$5 = {
|
||||
key: 0,
|
||||
@@ -12108,7 +12155,7 @@ const _sfc_main$d = /* @__PURE__ */ defineComponent({
|
||||
createBaseVNode("path", { d: "M4.646 1.646a.5.5 0 0 1 .708 0l6 6a.5.5 0 0 1 0 .708l-6 6a.5.5 0 0 1-.708-.708L10.293 8 4.646 2.354a.5.5 0 0 1 0-.708z" }, null, -1)
|
||||
])], 2))
|
||||
])) : (openBlock(), createElementBlock("span", _hoisted_2$9)),
|
||||
createBaseVNode("label", _hoisted_3$7, [
|
||||
createBaseVNode("label", _hoisted_3$8, [
|
||||
createBaseVNode("input", {
|
||||
type: "checkbox",
|
||||
class: "tree-node__checkbox",
|
||||
@@ -12154,7 +12201,7 @@ const _sfc_main$d = /* @__PURE__ */ defineComponent({
|
||||
const FolderTreeNode = /* @__PURE__ */ _export_sfc(_sfc_main$d, [["__scopeId", "data-v-90187dd4"]]);
|
||||
const _hoisted_1$9 = { class: "search-container" };
|
||||
const _hoisted_2$8 = { class: "folder-tree" };
|
||||
const _hoisted_3$6 = {
|
||||
const _hoisted_3$7 = {
|
||||
key: 1,
|
||||
class: "no-results"
|
||||
};
|
||||
@@ -12253,7 +12300,7 @@ const _sfc_main$c = /* @__PURE__ */ defineComponent({
|
||||
onToggleExpand: toggleExpand,
|
||||
onToggleSelect: toggleSelect
|
||||
}, null, 8, ["node", "selected", "expanded", "variant"]);
|
||||
}), 128)) : (openBlock(), createElementBlock("div", _hoisted_3$6, " No folders found "))
|
||||
}), 128)) : (openBlock(), createElementBlock("div", _hoisted_3$7, " No folders found "))
|
||||
])
|
||||
]),
|
||||
_: 1
|
||||
@@ -12659,7 +12706,7 @@ const _sfc_main$b = /* @__PURE__ */ defineComponent({
|
||||
const LoraPoolWidget = /* @__PURE__ */ _export_sfc(_sfc_main$b, [["__scopeId", "data-v-ed73eab5"]]);
|
||||
const _hoisted_1$8 = { class: "last-used-preview" };
|
||||
const _hoisted_2$7 = { class: "last-used-preview__content" };
|
||||
const _hoisted_3$5 = ["src", "onError"];
|
||||
const _hoisted_3$6 = ["src", "onError"];
|
||||
const _hoisted_4$5 = {
|
||||
key: 1,
|
||||
class: "last-used-preview__thumb last-used-preview__thumb--placeholder"
|
||||
@@ -12711,7 +12758,7 @@ const _sfc_main$a = /* @__PURE__ */ defineComponent({
|
||||
src: previewUrls.value[lora.name],
|
||||
class: "last-used-preview__thumb",
|
||||
onError: ($event) => onImageError(lora.name)
|
||||
}, null, 40, _hoisted_3$5)) : (openBlock(), createElementBlock("div", _hoisted_4$5, [..._cache[0] || (_cache[0] = [
|
||||
}, null, 40, _hoisted_3$6)) : (openBlock(), createElementBlock("div", _hoisted_4$5, [..._cache[0] || (_cache[0] = [
|
||||
createBaseVNode("svg", {
|
||||
viewBox: "0 0 16 16",
|
||||
fill: "currentColor"
|
||||
@@ -13152,7 +13199,7 @@ const _sfc_main$8 = /* @__PURE__ */ defineComponent({
|
||||
const DualRangeSlider = /* @__PURE__ */ _export_sfc(_sfc_main$8, [["__scopeId", "data-v-e0c8dc9f"]]);
|
||||
const _hoisted_1$5 = { class: "randomizer-settings" };
|
||||
const _hoisted_2$5 = { class: "setting-section" };
|
||||
const _hoisted_3$4 = { class: "count-mode-tabs" };
|
||||
const _hoisted_3$5 = { class: "count-mode-tabs" };
|
||||
const _hoisted_4$4 = ["checked"];
|
||||
const _hoisted_5$3 = ["checked"];
|
||||
const _hoisted_6$3 = { class: "slider-container" };
|
||||
@@ -13217,7 +13264,7 @@ const _sfc_main$7 = /* @__PURE__ */ defineComponent({
|
||||
], -1)),
|
||||
createBaseVNode("div", _hoisted_2$5, [
|
||||
_cache[20] || (_cache[20] = createBaseVNode("label", { class: "setting-label" }, "LoRA Count", -1)),
|
||||
createBaseVNode("div", _hoisted_3$4, [
|
||||
createBaseVNode("div", _hoisted_3$5, [
|
||||
createBaseVNode("label", {
|
||||
class: normalizeClass(["count-mode-tab", { active: __props.countMode === "fixed" }])
|
||||
}, [
|
||||
@@ -13848,7 +13895,7 @@ const _sfc_main$6 = /* @__PURE__ */ defineComponent({
|
||||
const LoraRandomizerWidget = /* @__PURE__ */ _export_sfc(_sfc_main$6, [["__scopeId", "data-v-ca6e8cec"]]);
|
||||
const _hoisted_1$4 = { class: "cycler-settings" };
|
||||
const _hoisted_2$4 = { class: "setting-section progress-section" };
|
||||
const _hoisted_3$3 = { class: "progress-label" };
|
||||
const _hoisted_3$4 = { class: "progress-label" };
|
||||
const _hoisted_4$3 = ["title"];
|
||||
const _hoisted_5$2 = { class: "progress-counter" };
|
||||
const _hoisted_6$2 = { class: "progress-index" };
|
||||
@@ -13973,7 +14020,7 @@ const _sfc_main$5 = /* @__PURE__ */ defineComponent({
|
||||
class: normalizeClass(["progress-info", { disabled: __props.isPauseDisabled }]),
|
||||
onClick: handleOpenSelector
|
||||
}, [
|
||||
createBaseVNode("span", _hoisted_3$3, toDisplayString(__props.isWorkflowExecuting ? "Using LoRA:" : "Next LoRA:"), 1),
|
||||
createBaseVNode("span", _hoisted_3$4, toDisplayString(__props.isWorkflowExecuting ? "Using LoRA:" : "Next LoRA:"), 1),
|
||||
createBaseVNode("span", {
|
||||
class: normalizeClass(["progress-name clickable", { disabled: __props.isPauseDisabled, "no-lora": __props.isNoLora }]),
|
||||
title: __props.currentLoraFilename
|
||||
@@ -14173,7 +14220,7 @@ const _sfc_main$5 = /* @__PURE__ */ defineComponent({
|
||||
const LoraCyclerSettingsView = /* @__PURE__ */ _export_sfc(_sfc_main$5, [["__scopeId", "data-v-f0663be4"]]);
|
||||
const _hoisted_1$3 = { class: "search-container" };
|
||||
const _hoisted_2$3 = { class: "lora-list" };
|
||||
const _hoisted_3$2 = ["onMouseenter", "onClick"];
|
||||
const _hoisted_3$3 = ["onMouseenter", "onClick"];
|
||||
const _hoisted_4$2 = { class: "lora-index" };
|
||||
const _hoisted_5$1 = ["title"];
|
||||
const _hoisted_6$1 = {
|
||||
@@ -14354,7 +14401,7 @@ const _sfc_main$4 = /* @__PURE__ */ defineComponent({
|
||||
title: item.lora.file_name
|
||||
}, toDisplayString(item.lora.file_name), 9, _hoisted_5$1),
|
||||
__props.currentIndex === item.index ? (openBlock(), createElementBlock("span", _hoisted_6$1, "Current")) : createCommentVNode("", true)
|
||||
], 42, _hoisted_3$2);
|
||||
], 42, _hoisted_3$3);
|
||||
}), 128)),
|
||||
filteredList.value.length === 0 ? (openBlock(), createElementBlock("div", _hoisted_7$1, " No LoRAs found ")) : createCommentVNode("", true)
|
||||
])
|
||||
@@ -14970,7 +15017,7 @@ const _hoisted_2$2 = {
|
||||
class: "json-content",
|
||||
ref: "contentRef"
|
||||
};
|
||||
const _hoisted_3$1 = ["innerHTML"];
|
||||
const _hoisted_3$2 = ["innerHTML"];
|
||||
const _hoisted_4$1 = {
|
||||
key: 1,
|
||||
class: "placeholder"
|
||||
@@ -15065,7 +15112,7 @@ const _sfc_main$2 = /* @__PURE__ */ defineComponent({
|
||||
hasMetadata.value ? (openBlock(), createElementBlock("pre", {
|
||||
key: 0,
|
||||
innerHTML: highlightedJson.value
|
||||
}, null, 8, _hoisted_3$1)) : (openBlock(), createElementBlock("div", _hoisted_4$1, "No metadata available"))
|
||||
}, null, 8, _hoisted_3$2)) : (openBlock(), createElementBlock("div", _hoisted_4$1, "No metadata available"))
|
||||
], 512)
|
||||
]);
|
||||
};
|
||||
@@ -15137,8 +15184,71 @@ function useAutocomplete(textareaRef, modelType = "loras", options = {}) {
|
||||
refreshCaretHelper
|
||||
};
|
||||
}
|
||||
const settingsStore = /* @__PURE__ */ new Map();
|
||||
const app = {
|
||||
extensionManager: {
|
||||
setting: {
|
||||
get: (id) => settingsStore.has(id) ? settingsStore.get(id) : void 0,
|
||||
set: async (id, value) => {
|
||||
settingsStore.set(id, value);
|
||||
}
|
||||
}
|
||||
}
|
||||
};
|
||||
const LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID = "loramanager.lora_active_filters_autocomplete";
|
||||
const LORA_ACTIVE_FILTERS_AUTOCOMPLETE_DEFAULT = false;
|
||||
const SETTING_TOGGLED_EVENT_NAME = "lora-manager:setting-toggled";
|
||||
const setLoraManagerSettingValue = async (settingId, value) => {
|
||||
var _a2, _b, _c, _d;
|
||||
const settingManager = (_a2 = app == null ? void 0 : app.extensionManager) == null ? void 0 : _a2.setting;
|
||||
if (settingManager && typeof settingManager.set === "function") {
|
||||
await settingManager.set(settingId, value);
|
||||
_notifySettingToggled(settingId, value);
|
||||
return true;
|
||||
}
|
||||
const setting = (_d = (_c = (_b = app == null ? void 0 : app.ui) == null ? void 0 : _b.settings) == null ? void 0 : _c.settingsById) == null ? void 0 : _d[settingId];
|
||||
if (setting) {
|
||||
app.ui.settings.setSettingValue(settingId, value);
|
||||
_notifySettingToggled(settingId, value);
|
||||
return true;
|
||||
}
|
||||
return false;
|
||||
};
|
||||
const _notifySettingToggled = (settingId, value) => {
|
||||
try {
|
||||
window.dispatchEvent(new CustomEvent(SETTING_TOGGLED_EVENT_NAME, {
|
||||
detail: { settingId, value }
|
||||
}));
|
||||
} catch (error) {
|
||||
}
|
||||
};
|
||||
const getLoraActiveFiltersAutocompletePreference = /* @__PURE__ */ (() => {
|
||||
let settingsUnavailableLogged = false;
|
||||
return () => {
|
||||
var _a2;
|
||||
const settingManager = (_a2 = app == null ? void 0 : app.extensionManager) == null ? void 0 : _a2.setting;
|
||||
if (!settingManager || typeof settingManager.get !== "function") {
|
||||
if (!settingsUnavailableLogged) {
|
||||
console.warn("LoRA Manager: settings API unavailable, using default lora active filters autocomplete setting.");
|
||||
settingsUnavailableLogged = true;
|
||||
}
|
||||
return LORA_ACTIVE_FILTERS_AUTOCOMPLETE_DEFAULT;
|
||||
}
|
||||
try {
|
||||
const value = settingManager.get(LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID);
|
||||
return value ?? LORA_ACTIVE_FILTERS_AUTOCOMPLETE_DEFAULT;
|
||||
} catch (error) {
|
||||
if (!settingsUnavailableLogged) {
|
||||
console.warn("LoRA Manager: unable to read lora active filters autocomplete setting, using default.", error);
|
||||
settingsUnavailableLogged = true;
|
||||
}
|
||||
return LORA_ACTIVE_FILTERS_AUTOCOMPLETE_DEFAULT;
|
||||
}
|
||||
};
|
||||
})();
|
||||
const _hoisted_1$1 = { class: "autocomplete-text-widget" };
|
||||
const _hoisted_2$1 = ["placeholder", "spellcheck"];
|
||||
const _hoisted_3$1 = ["title"];
|
||||
const _sfc_main$1 = /* @__PURE__ */ defineComponent({
|
||||
__name: "AutocompleteTextWidget",
|
||||
props: {
|
||||
@@ -15187,6 +15297,37 @@ const _sfc_main$1 = /* @__PURE__ */ defineComponent({
|
||||
};
|
||||
const hasText = ref(false);
|
||||
const showClearButton = computed(() => hasText.value);
|
||||
const isLorasMode = (props.modelType ?? "loras") === "loras";
|
||||
const activeFiltersEnabled = ref(false);
|
||||
const refreshActiveFiltersState = () => {
|
||||
if (isLorasMode) {
|
||||
activeFiltersEnabled.value = getLoraActiveFiltersAutocompletePreference();
|
||||
}
|
||||
};
|
||||
const onSettingToggled = (event) => {
|
||||
const detail = event.detail;
|
||||
if ((detail == null ? void 0 : detail.settingId) === LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID) {
|
||||
activeFiltersEnabled.value = detail.value === true;
|
||||
}
|
||||
};
|
||||
const activeFiltersToggleTitle = computed(
|
||||
() => activeFiltersEnabled.value ? "Active Filters Search is ON: suggestions respect the LoRA Manager page filters. Click to disable, or type /noactivefilters." : "Active Filters Search is OFF: suggestions search the full library. Click to enable, or type /activefilters."
|
||||
);
|
||||
const toggleActiveFiltersSearch = async () => {
|
||||
const newValue = !activeFiltersEnabled.value;
|
||||
try {
|
||||
const success = await setLoraManagerSettingValue(
|
||||
LORA_ACTIVE_FILTERS_AUTOCOMPLETE_SETTING_ID,
|
||||
newValue
|
||||
);
|
||||
if (!success) {
|
||||
throw new Error("settings API unavailable");
|
||||
}
|
||||
activeFiltersEnabled.value = newValue;
|
||||
} catch (error) {
|
||||
console.error("[Lora Manager] Failed to toggle active filters search:", error);
|
||||
}
|
||||
};
|
||||
useAutocomplete(
|
||||
textareaRef,
|
||||
props.modelType ?? "loras",
|
||||
@@ -15239,14 +15380,12 @@ const _sfc_main$1 = /* @__PURE__ */ defineComponent({
|
||||
}
|
||||
};
|
||||
const onExternalValueChange = () => {
|
||||
updateVScrollbarWidth();
|
||||
updateHasTextState();
|
||||
};
|
||||
const setupWidgetOnSetValue = () => {
|
||||
if (props.widget) {
|
||||
props.widget.onSetValue = (value) => {
|
||||
hasText.value = value.length > 0;
|
||||
updateVScrollbarWidth();
|
||||
};
|
||||
}
|
||||
};
|
||||
@@ -15296,6 +15435,8 @@ const _sfc_main$1 = /* @__PURE__ */ defineComponent({
|
||||
props.widget.callback(textareaRef.value.value);
|
||||
}
|
||||
setupWidgetOnSetValue();
|
||||
refreshActiveFiltersState();
|
||||
window.addEventListener(SETTING_TOGGLED_EVENT_NAME, onSettingToggled);
|
||||
updateVScrollbarWidth();
|
||||
observeScrollbarWidth();
|
||||
document.addEventListener("lora-manager:vue-mode-change", onModeChange);
|
||||
@@ -15315,6 +15456,7 @@ const _sfc_main$1 = /* @__PURE__ */ defineComponent({
|
||||
props.widget.onSetValue = void 0;
|
||||
}
|
||||
document.removeEventListener("lora-manager:vue-mode-change", onModeChange);
|
||||
window.removeEventListener(SETTING_TOGGLED_EVENT_NAME, onSettingToggled);
|
||||
});
|
||||
return (_ctx, _cache) => {
|
||||
return openBlock(), createElementBlock("div", _hoisted_1$1, [
|
||||
@@ -15361,13 +15503,29 @@ const _sfc_main$1 = /* @__PURE__ */ defineComponent({
|
||||
y2: "18"
|
||||
})
|
||||
], -1)
|
||||
])])) : createCommentVNode("", true)
|
||||
])])) : createCommentVNode("", true),
|
||||
isLorasMode ? (openBlock(), createElementBlock("button", {
|
||||
key: 1,
|
||||
type: "button",
|
||||
class: normalizeClass(["active-filters-toggle", { "is-active": activeFiltersEnabled.value }]),
|
||||
title: activeFiltersToggleTitle.value,
|
||||
onClick: toggleActiveFiltersSearch
|
||||
}, [..._cache[1] || (_cache[1] = [
|
||||
createBaseVNode("svg", {
|
||||
viewBox: "0 0 24 24",
|
||||
fill: "none",
|
||||
stroke: "currentColor",
|
||||
"stroke-width": "2"
|
||||
}, [
|
||||
createBaseVNode("polygon", { points: "22 3 2 3 10 12.46 10 19 14 21 14 12.46 22 3" })
|
||||
], -1)
|
||||
])], 10, _hoisted_3$1)) : createCommentVNode("", true)
|
||||
], 4)
|
||||
]);
|
||||
};
|
||||
}
|
||||
});
|
||||
const AutocompleteTextWidget = /* @__PURE__ */ _export_sfc(_sfc_main$1, [["__scopeId", "data-v-793d67d2"]]);
|
||||
const AutocompleteTextWidget = /* @__PURE__ */ _export_sfc(_sfc_main$1, [["__scopeId", "data-v-22743258"]]);
|
||||
const _hoisted_1 = { class: "lora-info-tabs" };
|
||||
const _hoisted_2 = { class: "tab-content notes-tab" };
|
||||
const _hoisted_3 = { class: "info-field" };
|
||||
@@ -15784,6 +15942,11 @@ function createModeChangeCallback(node, updateDownstreamLoaders2, nodeSpecificCa
|
||||
updateDownstreamLoaders2(node);
|
||||
};
|
||||
}
|
||||
const api = {
|
||||
fetchApi: (...args) => fetch(...args),
|
||||
addEventListener: (eventName, handler) => document.addEventListener(eventName, handler),
|
||||
removeEventListener: (eventName, handler) => document.removeEventListener(eventName, handler)
|
||||
};
|
||||
let _loraSyntaxFormatCache = null;
|
||||
let _loraSyntaxFormatRefreshPromise = null;
|
||||
async function _fetchLoraSyntaxFormat() {
|
||||
@@ -16140,8 +16303,8 @@ const AUTOCOMPLETE_TEXT_MIN_WIDTH_DEFAULT = 400;
|
||||
const AUTOCOMPLETE_TEXT_MIN_HEIGHT_DEFAULT = 300;
|
||||
const AUTOCOMPLETE_METADATA_VERSION = 1;
|
||||
const LORA_MANAGER_WIDGET_IDS_PROPERTY = "__lm_widget_ids";
|
||||
const originalGraphToPrompt = app.graphToPrompt.bind(app);
|
||||
app.graphToPrompt = async (...args) => {
|
||||
const originalGraphToPrompt = app$1.graphToPrompt.bind(app$1);
|
||||
app$1.graphToPrompt = async (...args) => {
|
||||
const result = await originalGraphToPrompt(...args);
|
||||
stripAutocompleteMetadataFromPromptResult(result);
|
||||
return result;
|
||||
@@ -16150,7 +16313,7 @@ function forwardMiddleMouseToCanvas(container) {
|
||||
if (!container) return;
|
||||
container.addEventListener("pointerdown", (event) => {
|
||||
if (event.button === 1) {
|
||||
const canvas = app.canvas;
|
||||
const canvas = app$1.canvas;
|
||||
if (canvas && typeof canvas.processMouseDown === "function") {
|
||||
canvas.processMouseDown(event);
|
||||
}
|
||||
@@ -16158,7 +16321,7 @@ function forwardMiddleMouseToCanvas(container) {
|
||||
});
|
||||
container.addEventListener("pointermove", (event) => {
|
||||
if ((event.buttons & 4) === 4) {
|
||||
const canvas = app.canvas;
|
||||
const canvas = app$1.canvas;
|
||||
if (canvas && typeof canvas.processMouseMove === "function") {
|
||||
canvas.processMouseMove(event);
|
||||
}
|
||||
@@ -16166,7 +16329,7 @@ function forwardMiddleMouseToCanvas(container) {
|
||||
});
|
||||
container.addEventListener("pointerup", (event) => {
|
||||
if (event.button === 1) {
|
||||
const canvas = app.canvas;
|
||||
const canvas = app$1.canvas;
|
||||
if (canvas && typeof canvas.processMouseUp === "function") {
|
||||
canvas.processMouseUp(event);
|
||||
}
|
||||
@@ -16284,7 +16447,7 @@ function createLoraRandomizerWidget(node) {
|
||||
const vueApp = createApp(LoraRandomizerWidget, {
|
||||
widget,
|
||||
node,
|
||||
api
|
||||
api: api$1
|
||||
});
|
||||
vueApp.use(PrimeVue, {
|
||||
unstyled: true,
|
||||
@@ -16359,7 +16522,7 @@ function createLoraCyclerWidget(node) {
|
||||
const vueApp = createApp(LoraCyclerWidget, {
|
||||
widget,
|
||||
node,
|
||||
api
|
||||
api: api$1
|
||||
});
|
||||
vueApp.use(PrimeVue, {
|
||||
unstyled: true,
|
||||
@@ -16547,13 +16710,13 @@ function applyAutocompleteTextLayoutFix(widget, _container, isVueMode) {
|
||||
}
|
||||
const initVueDomModeListener = () => {
|
||||
var _a2, _b;
|
||||
if ((_b = (_a2 = app.ui) == null ? void 0 : _a2.settings) == null ? void 0 : _b.addEventListener) {
|
||||
app.ui.settings.addEventListener("Comfy.VueNodes.Enabled.change", () => {
|
||||
if ((_b = (_a2 = app$1.ui) == null ? void 0 : _a2.settings) == null ? void 0 : _b.addEventListener) {
|
||||
app$1.ui.settings.addEventListener("Comfy.VueNodes.Enabled.change", () => {
|
||||
requestAnimationFrame(() => {
|
||||
var _a3, _b2, _c, _d, _e2, _f;
|
||||
const isVueDomMode = ((_c = (_b2 = (_a3 = app.ui) == null ? void 0 : _a3.settings) == null ? void 0 : _b2.getSettingValue) == null ? void 0 : _c.call(_b2, "Comfy.VueNodes.Enabled")) ?? false;
|
||||
if ((_d = app.graph) == null ? void 0 : _d.nodes) {
|
||||
for (const node of app.graph.nodes) {
|
||||
const isVueDomMode = ((_c = (_b2 = (_a3 = app$1.ui) == null ? void 0 : _a3.settings) == null ? void 0 : _b2.getSettingValue) == null ? void 0 : _c.call(_b2, "Comfy.VueNodes.Enabled")) ?? false;
|
||||
if ((_d = app$1.graph) == null ? void 0 : _d.nodes) {
|
||||
for (const node of app$1.graph.nodes) {
|
||||
const textWidget = (_e2 = node.widgets) == null ? void 0 : _e2.find(
|
||||
(w2) => w2.type === "AUTOCOMPLETE_TEXT_LORAS"
|
||||
);
|
||||
@@ -16568,7 +16731,7 @@ const initVueDomModeListener = () => {
|
||||
const grid = nodeEl.querySelector('[data-testid="node-widgets"]');
|
||||
if (!grid) continue;
|
||||
const nodeId = nodeEl.getAttribute("data-node-id");
|
||||
const node = (_a4 = app.graph) == null ? void 0 : _a4.getNodeById(nodeId);
|
||||
const node = (_a4 = app$1.graph) == null ? void 0 : _a4.getNodeById(nodeId);
|
||||
if (!node) continue;
|
||||
const rows = [];
|
||||
let needsFix = false;
|
||||
@@ -16589,7 +16752,7 @@ const initVueDomModeListener = () => {
|
||||
}
|
||||
}
|
||||
});
|
||||
(_f = app.canvas) == null ? void 0 : _f.setDirty(true, true);
|
||||
(_f = app$1.canvas) == null ? void 0 : _f.setDirty(true, true);
|
||||
document.dispatchEvent(new CustomEvent("lora-manager:vue-mode-change", {
|
||||
detail: { isVueDomMode }
|
||||
}));
|
||||
@@ -16597,12 +16760,12 @@ const initVueDomModeListener = () => {
|
||||
});
|
||||
}
|
||||
};
|
||||
if ((_a = app.ui) == null ? void 0 : _a.settings) {
|
||||
if ((_a = app$1.ui) == null ? void 0 : _a.settings) {
|
||||
initVueDomModeListener();
|
||||
} else {
|
||||
const checkAppReady = setInterval(() => {
|
||||
var _a2;
|
||||
if ((_a2 = app.ui) == null ? void 0 : _a2.settings) {
|
||||
if ((_a2 = app$1.ui) == null ? void 0 : _a2.settings) {
|
||||
initVueDomModeListener();
|
||||
clearInterval(checkAppReady);
|
||||
}
|
||||
@@ -16641,8 +16804,8 @@ function createLoraInfoWidget(node) {
|
||||
const vueApp = createApp(LoraInfoWidget, {
|
||||
widget,
|
||||
node,
|
||||
api,
|
||||
app,
|
||||
api: api$1,
|
||||
app: app$1,
|
||||
isVueMode: typeof LiteGraph !== "undefined" && LiteGraph.vueNodesMode
|
||||
});
|
||||
vueApp.use(PrimeVue, {
|
||||
@@ -16737,7 +16900,7 @@ function createAutocompleteTextWidgetFactory(node, widgetName, modelType, inputO
|
||||
}
|
||||
);
|
||||
widget.metadataWidget = metadataWidget;
|
||||
const spellcheck = ((_c = (_b = (_a2 = app.ui) == null ? void 0 : _a2.settings) == null ? void 0 : _b.getSettingValue) == null ? void 0 : _c.call(_b, "Comfy.TextareaWidget.Spellcheck")) ?? false;
|
||||
const spellcheck = ((_c = (_b = (_a2 = app$1.ui) == null ? void 0 : _a2.settings) == null ? void 0 : _b.getSettingValue) == null ? void 0 : _c.call(_b, "Comfy.TextareaWidget.Spellcheck")) ?? false;
|
||||
const maxHeight = modelType === "loras" ? AUTOCOMPLETE_TEXT_WIDGET_MAX_HEIGHT : void 0;
|
||||
const vueApp = createApp(AutocompleteTextWidget, {
|
||||
widget,
|
||||
@@ -16775,7 +16938,7 @@ function createAutocompleteTextWidgetFactory(node, widgetName, modelType, inputO
|
||||
const minHeight = modelType === "loras" ? void 0 : AUTOCOMPLETE_TEXT_MIN_HEIGHT_DEFAULT;
|
||||
return { widget, minWidth, minHeight };
|
||||
}
|
||||
app.registerExtension({
|
||||
app$1.registerExtension({
|
||||
name: "LoraManager.VueWidgets",
|
||||
getCustomWidgets() {
|
||||
return {
|
||||
|
||||
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user