mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-24 14:42:11 -03:00
checkpoint
This commit is contained in:
Will Miao
@@ -3,10 +3,17 @@ import logging
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import sys
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from aiohttp import web
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from typing import Dict
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import tempfile
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import json
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import aiohttp
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import asyncio
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from ..utils.exif_utils import ExifUtils
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from ..services.civitai_client import CivitaiClient
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from ..services.recipe_scanner import RecipeScanner
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from ..services.lora_scanner import LoraScanner
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from ..config import config
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import time # Add this import at the top
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logger = logging.getLogger(__name__)
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print("Recipe Routes module loaded", file=sys.stderr)
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@@ -17,6 +24,7 @@ class RecipeRoutes:
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def __init__(self):
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print("Initializing RecipeRoutes", file=sys.stderr)
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self.recipe_scanner = RecipeScanner(LoraScanner())
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self.civitai_client = CivitaiClient()
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# Pre-warm the cache
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self._init_cache_task = None
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@@ -28,6 +36,9 @@ class RecipeRoutes:
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routes = cls()
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app.router.add_get('/api/recipes', routes.get_recipes)
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app.router.add_get('/api/recipe/{recipe_id}', routes.get_recipe_detail)
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app.router.add_post('/api/recipes/analyze-image', routes.analyze_recipe_image)
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app.router.add_post('/api/recipes/download-missing-loras', routes.download_missing_loras)
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app.router.add_post('/api/recipes/save', routes.save_recipe)
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# Start cache initialization
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app.on_startup.append(routes._init_cache)
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@@ -143,4 +154,295 @@ class RecipeRoutes:
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def _format_timestamp(self, timestamp: float) -> str:
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"""Format timestamp for display"""
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from datetime import datetime
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return datetime.fromtimestamp(timestamp).strftime('%Y-%m-%d %H:%M:%S')
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return datetime.fromtimestamp(timestamp).strftime('%Y-%m-%d %H:%M:%S')
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async def analyze_recipe_image(self, request: web.Request) -> web.Response:
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"""Analyze an uploaded image for recipe metadata"""
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temp_path = None
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try:
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reader = await request.multipart()
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field = await reader.next()
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if field.name != 'image':
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return web.json_response({
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"error": "No image field found",
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"loras": []
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}, status=400)
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# Create a temporary file to store the uploaded image
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with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as temp_file:
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while True:
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chunk = await field.read_chunk()
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if not chunk:
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break
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temp_file.write(chunk)
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temp_path = temp_file.name
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# Extract metadata from the image using ExifUtils
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user_comment = ExifUtils.extract_user_comment(temp_path)
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print(f"User comment: {user_comment}", file=sys.stderr)
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# If no metadata found, return a more specific error
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if not user_comment:
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return web.json_response({
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"error": "No metadata found in this image",
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"loras": [] # Return empty loras array to prevent client-side errors
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}, status=200) # Return 200 instead of 400 to handle gracefully
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# Parse the recipe metadata
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metadata = ExifUtils.parse_recipe_metadata(user_comment)
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print(f"Metadata: {metadata}", file=sys.stderr)
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# Look for Civitai resources in the metadata
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civitai_resources = metadata.get('loras', [])
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checkpoint = metadata.get('checkpoint')
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if not civitai_resources and not checkpoint:
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return web.json_response({
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"error": "No LoRA information found in this image",
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"loras": [] # Return empty loras array
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}, status=200) # Return 200 instead of 400
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# Process the resources to get LoRA information
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loras = []
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base_model = None
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# Set base model from checkpoint if available
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if checkpoint:
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base_model = checkpoint.get('modelName', '')
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# Process LoRAs
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for resource in civitai_resources:
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# Get model version ID
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model_version_id = resource.get('modelVersionId')
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if not model_version_id:
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continue
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# Get additional info from Civitai
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civitai_info = await self.civitai_client.get_model_version_info(model_version_id)
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print(f"Civitai info: {civitai_info}", file=sys.stderr)
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# Check if this LoRA exists locally by SHA256 hash
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exists_locally = False
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local_path = ""
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if civitai_info and 'files' in civitai_info and civitai_info['files']:
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sha256 = civitai_info['files'][0].get('hashes', {}).get('SHA256', '')
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if sha256:
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sha256 = sha256.lower() # Convert to lowercase for consistency
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exists_locally = self.recipe_scanner._lora_scanner.has_lora_hash(sha256)
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if exists_locally:
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local_path = self.recipe_scanner._lora_scanner.get_lora_path_by_hash(sha256) or ""
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# Create LoRA entry
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lora_entry = {
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'id': model_version_id,
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'name': resource.get('modelName', ''),
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'version': resource.get('modelVersionName', ''),
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'type': resource.get('type', 'lora'),
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'weight': resource.get('weight', 1.0),
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'existsLocally': exists_locally,
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'localPath': local_path,
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'thumbnailUrl': '',
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'baseModel': '',
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'size': 0,
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'downloadUrl': ''
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}
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# Add Civitai info if available
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if civitai_info:
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# Get thumbnail URL from first image
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if 'images' in civitai_info and civitai_info['images']:
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lora_entry['thumbnailUrl'] = civitai_info['images'][0].get('url', '')
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# Get base model
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lora_entry['baseModel'] = civitai_info.get('baseModel', '')
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# Get file size
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if 'files' in civitai_info and civitai_info['files']:
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lora_entry['size'] = civitai_info['files'][0].get('sizeKB', 0) * 1024
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# Get download URL
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lora_entry['downloadUrl'] = civitai_info.get('downloadUrl', '')
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loras.append(lora_entry)
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return web.json_response({
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'base_model': base_model,
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'loras': loras
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})
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except Exception as e:
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logger.error(f"Error analyzing recipe image: {e}", exc_info=True)
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return web.json_response({
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"error": str(e),
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"loras": [] # Return empty loras array to prevent client-side errors
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}, status=500)
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finally:
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# Clean up the temporary file in the finally block
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if temp_path and os.path.exists(temp_path):
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try:
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os.unlink(temp_path)
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except Exception as e:
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logger.error(f"Error deleting temporary file: {e}")
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async def download_missing_loras(self, request: web.Request) -> web.Response:
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"""Download missing LoRAs for a recipe"""
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try:
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data = await request.json()
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loras = data.get('loras', [])
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lora_root = data.get('lora_root', '')
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relative_path = data.get('relative_path', '')
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if not loras:
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return web.json_response({"error": "No LoRAs specified"}, status=400)
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if not lora_root:
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return web.json_response({"error": "No LoRA root directory specified"}, status=400)
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# Create target directory if it doesn't exist
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target_dir = os.path.join(lora_root, relative_path) if relative_path else lora_root
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os.makedirs(target_dir, exist_ok=True)
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# Download each LoRA
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downloaded = []
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for lora in loras:
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download_url = lora.get('downloadUrl')
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if not download_url:
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continue
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# Generate filename from LoRA name
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filename = f"{lora.get('name', 'lora')}.safetensors"
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filename = filename.replace(' ', '_').replace('/', '_').replace('\\', '_')
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# Download the file
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target_path = os.path.join(target_dir, filename)
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async with aiohttp.ClientSession() as session:
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async with session.get(download_url, allow_redirects=True) as response:
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if response.status != 200:
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continue
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with open(target_path, 'wb') as f:
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while True:
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chunk = await response.content.read(1024 * 1024) # 1MB chunks
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if not chunk:
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break
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f.write(chunk)
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downloaded.append({
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'id': lora.get('id'),
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'localPath': target_path
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})
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return web.json_response({
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'downloaded': downloaded
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})
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except Exception as e:
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logger.error(f"Error downloading missing LoRAs: {e}", exc_info=True)
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return web.json_response({"error": str(e)}, status=500)
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async def save_recipe(self, request: web.Request) -> web.Response:
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"""Save a recipe to the recipes folder"""
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try:
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reader = await request.multipart()
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# Process form data
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image = None
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name = None
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tags = []
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recipe_data = None
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while True:
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field = await reader.next()
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if field is None:
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break
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if field.name == 'image':
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# Read image data
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image_data = b''
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while True:
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chunk = await field.read_chunk()
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if not chunk:
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break
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image_data += chunk
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image = image_data
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elif field.name == 'name':
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name = await field.text()
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elif field.name == 'tags':
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tags_text = await field.text()
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try:
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tags = json.loads(tags_text)
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except:
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tags = []
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elif field.name == 'recipe_data':
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recipe_data_text = await field.text()
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try:
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recipe_data = json.loads(recipe_data_text)
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except:
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recipe_data = {}
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if not image or not name or not recipe_data:
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return web.json_response({"error": "Missing required fields"}, status=400)
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# Create recipes directory if it doesn't exist
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recipes_dir = os.path.join(config.loras_roots[0], "recipes")
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os.makedirs(recipes_dir, exist_ok=True)
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# Generate filename from recipe name
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filename = f"{name}.jpg"
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filename = filename.replace(' ', '_').replace('/', '_').replace('\\', '_')
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# Ensure filename is unique
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counter = 1
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base_name, ext = os.path.splitext(filename)
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while os.path.exists(os.path.join(recipes_dir, filename)):
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filename = f"{base_name}_{counter}{ext}"
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counter += 1
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# Save the image
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target_path = os.path.join(recipes_dir, filename)
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with open(target_path, 'wb') as f:
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f.write(image)
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# Add metadata to the image
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from PIL import Image
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from PIL.ExifTags import TAGS
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from piexif import dump, load
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import piexif.helper
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# Prepare metadata
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metadata = {
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'recipe_name': name,
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'recipe_tags': json.dumps(tags),
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'recipe_data': json.dumps(recipe_data),
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'created_date': str(time.time())
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}
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# Write metadata to image
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img = Image.open(target_path)
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exif_dict = {"0th": {}, "Exif": {}, "GPS": {}, "1st": {}, "thumbnail": None}
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for key, value in metadata.items():
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exif_dict["0th"][piexif.ImageIFD.XPComment] = piexif.helper.UserComment.dump(
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json.dumps({key: value})
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)
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exif_bytes = dump(exif_dict)
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img.save(target_path, exif=exif_bytes)
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# Force refresh the recipe cache
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await self.recipe_scanner.get_cached_data(force_refresh=True)
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return web.json_response({
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'success': True,
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'file_path': target_path
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})
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except Exception as e:
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logger.error(f"Error saving recipe: {e}", exc_info=True)
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return web.json_response({"error": str(e)}, status=500)
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