mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-21 21:22:11 -03:00
177b20263d
- Import and register two new nodes: LoraDemoNode and LoraRandomizerNode - Update import exception handling for better readability with multi-line formatting - Add comprehensive documentation file `docs/custom-node-ui-output.md` for UI output usage in custom nodes - Ensure proper node registration in NODE_CLASS_MAPPINGS for ComfyUI integration - Maintain backward compatibility with existing node structure and import fallbacks
335 lines
13 KiB
Python
335 lines
13 KiB
Python
import asyncio
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import logging
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from aiohttp import web
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from typing import Dict
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from server import PromptServer # type: ignore
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from .base_model_routes import BaseModelRoutes
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from .model_route_registrar import ModelRouteRegistrar
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from ..services.lora_service import LoraService
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from ..services.service_registry import ServiceRegistry
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from ..utils.utils import get_lora_info
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logger = logging.getLogger(__name__)
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class LoraRoutes(BaseModelRoutes):
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"""LoRA-specific route controller"""
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def __init__(self):
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"""Initialize LoRA routes with LoRA service"""
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super().__init__()
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self.template_name = "loras.html"
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async def initialize_services(self):
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"""Initialize services from ServiceRegistry"""
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lora_scanner = await ServiceRegistry.get_lora_scanner()
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update_service = await ServiceRegistry.get_model_update_service()
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self.service = LoraService(lora_scanner, update_service=update_service)
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self.set_model_update_service(update_service)
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# Attach service dependencies
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self.attach_service(self.service)
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def setup_routes(self, app: web.Application):
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"""Setup LoRA routes"""
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# Schedule service initialization on app startup
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app.on_startup.append(lambda _: self.initialize_services())
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# Setup common routes with 'loras' prefix (includes page route)
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super().setup_routes(app, 'loras')
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def setup_specific_routes(self, registrar: ModelRouteRegistrar, prefix: str):
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"""Setup LoRA-specific routes"""
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# LoRA-specific query routes
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registrar.add_prefixed_route('GET', '/api/lm/{prefix}/letter-counts', prefix, self.get_letter_counts)
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registrar.add_prefixed_route('GET', '/api/lm/{prefix}/get-trigger-words', prefix, self.get_lora_trigger_words)
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registrar.add_prefixed_route('GET', '/api/lm/{prefix}/usage-tips-by-path', prefix, self.get_lora_usage_tips_by_path)
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# Randomizer routes
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registrar.add_prefixed_route('POST', '/api/lm/{prefix}/random-sample', prefix, self.get_random_loras)
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# ComfyUI integration
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registrar.add_prefixed_route('POST', '/api/lm/{prefix}/get_trigger_words', prefix, self.get_trigger_words)
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def _parse_specific_params(self, request: web.Request) -> Dict:
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"""Parse LoRA-specific parameters"""
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params = {}
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# LoRA-specific parameters
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if 'first_letter' in request.query:
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params['first_letter'] = request.query.get('first_letter')
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# Handle fuzzy search parameter name variation
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if request.query.get('fuzzy') == 'true':
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params['fuzzy_search'] = True
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# Handle additional filter parameters for LoRAs
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if 'lora_hash' in request.query:
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if not params.get('hash_filters'):
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params['hash_filters'] = {}
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params['hash_filters']['single_hash'] = request.query['lora_hash'].lower()
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elif 'lora_hashes' in request.query:
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if not params.get('hash_filters'):
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params['hash_filters'] = {}
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params['hash_filters']['multiple_hashes'] = [h.lower() for h in request.query['lora_hashes'].split(',')]
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return params
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def _validate_civitai_model_type(self, model_type: str) -> bool:
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"""Validate CivitAI model type for LoRA"""
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from ..utils.constants import VALID_LORA_TYPES
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return model_type.lower() in VALID_LORA_TYPES
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def _get_expected_model_types(self) -> str:
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"""Get expected model types string for error messages"""
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return "LORA, LoCon, or DORA"
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# LoRA-specific route handlers
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async def get_letter_counts(self, request: web.Request) -> web.Response:
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"""Get count of LoRAs for each letter of the alphabet"""
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try:
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letter_counts = await self.service.get_letter_counts()
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return web.json_response({
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'success': True,
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'letter_counts': letter_counts
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})
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except Exception as e:
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logger.error(f"Error getting letter counts: {e}")
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return web.json_response({
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'success': False,
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'error': str(e)
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}, status=500)
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async def get_lora_notes(self, request: web.Request) -> web.Response:
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"""Get notes for a specific LoRA file"""
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try:
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lora_name = request.query.get('name')
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if not lora_name:
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return web.Response(text='Lora file name is required', status=400)
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notes = await self.service.get_lora_notes(lora_name)
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if notes is not None:
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return web.json_response({
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'success': True,
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'notes': notes
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})
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else:
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return web.json_response({
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'success': False,
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'error': 'LoRA not found in cache'
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}, status=404)
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except Exception as e:
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logger.error(f"Error getting lora notes: {e}", exc_info=True)
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return web.json_response({
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'success': False,
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'error': str(e)
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}, status=500)
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async def get_lora_trigger_words(self, request: web.Request) -> web.Response:
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"""Get trigger words for a specific LoRA file"""
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try:
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lora_name = request.query.get('name')
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if not lora_name:
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return web.Response(text='Lora file name is required', status=400)
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trigger_words = await self.service.get_lora_trigger_words(lora_name)
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return web.json_response({
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'success': True,
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'trigger_words': trigger_words
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})
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except Exception as e:
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logger.error(f"Error getting lora trigger words: {e}", exc_info=True)
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return web.json_response({
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'success': False,
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'error': str(e)
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}, status=500)
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async def get_lora_usage_tips_by_path(self, request: web.Request) -> web.Response:
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"""Get usage tips for a LoRA by its relative path"""
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try:
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relative_path = request.query.get('relative_path')
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if not relative_path:
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return web.Response(text='Relative path is required', status=400)
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usage_tips = await self.service.get_lora_usage_tips_by_relative_path(relative_path)
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return web.json_response({
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'success': True,
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'usage_tips': usage_tips or ''
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})
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except Exception as e:
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logger.error(f"Error getting lora usage tips by path: {e}", exc_info=True)
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return web.json_response({
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'success': False,
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'error': str(e)
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}, status=500)
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async def get_lora_preview_url(self, request: web.Request) -> web.Response:
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"""Get the static preview URL for a LoRA file"""
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try:
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lora_name = request.query.get('name')
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if not lora_name:
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return web.Response(text='Lora file name is required', status=400)
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preview_url = await self.service.get_lora_preview_url(lora_name)
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if preview_url:
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return web.json_response({
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'success': True,
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'preview_url': preview_url
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})
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else:
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return web.json_response({
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'success': False,
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'error': 'No preview URL found for the specified lora'
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}, status=404)
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except Exception as e:
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logger.error(f"Error getting lora preview URL: {e}", exc_info=True)
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return web.json_response({
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'success': False,
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'error': str(e)
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}, status=500)
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async def get_lora_civitai_url(self, request: web.Request) -> web.Response:
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"""Get the Civitai URL for a LoRA file"""
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try:
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lora_name = request.query.get('name')
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if not lora_name:
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return web.Response(text='Lora file name is required', status=400)
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result = await self.service.get_lora_civitai_url(lora_name)
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if result['civitai_url']:
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return web.json_response({
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'success': True,
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**result
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})
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else:
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return web.json_response({
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'success': False,
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'error': 'No Civitai data found for the specified lora'
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}, status=404)
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except Exception as e:
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logger.error(f"Error getting lora Civitai URL: {e}", exc_info=True)
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return web.json_response({
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'success': False,
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'error': str(e)
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}, status=500)
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async def get_random_loras(self, request: web.Request) -> web.Response:
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"""Get random LoRAs based on filters and strength ranges"""
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try:
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json_data = await request.json()
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# Parse parameters
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count = json_data.get('count', 5)
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count_min = json_data.get('count_min')
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count_max = json_data.get('count_max')
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model_strength_min = float(json_data.get('model_strength_min', 0.0))
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model_strength_max = float(json_data.get('model_strength_max', 1.0))
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use_same_clip_strength = json_data.get('use_same_clip_strength', True)
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clip_strength_min = float(json_data.get('clip_strength_min', 0.0))
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clip_strength_max = float(json_data.get('clip_strength_max', 1.0))
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locked_loras = json_data.get('locked_loras', [])
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pool_config = json_data.get('pool_config')
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# Determine target count
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if count_min is not None and count_max is not None:
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import random
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target_count = random.randint(count_min, count_max)
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else:
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target_count = count
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# Validate parameters
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if target_count < 1 or target_count > 100:
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return web.json_response({
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'success': False,
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'error': 'Count must be between 1 and 100'
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}, status=400)
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if model_strength_min < 0 or model_strength_max > 10:
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return web.json_response({
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'success': False,
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'error': 'Model strength must be between 0 and 10'
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}, status=400)
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# Get random LoRAs from service
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result_loras = await self.service.get_random_loras(
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count=target_count,
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model_strength_min=model_strength_min,
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model_strength_max=model_strength_max,
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use_same_clip_strength=use_same_clip_strength,
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clip_strength_min=clip_strength_min,
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clip_strength_max=clip_strength_max,
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locked_loras=locked_loras,
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pool_config=pool_config
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)
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return web.json_response({
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'success': True,
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'loras': result_loras,
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'count': len(result_loras)
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})
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except ValueError as e:
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logger.error(f"Invalid parameter for random LoRAs: {e}")
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return web.json_response({
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'success': False,
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'error': str(e)
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}, status=400)
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except Exception as e:
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logger.error(f"Error getting random LoRAs: {e}", exc_info=True)
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return web.json_response({
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'success': False,
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'error': str(e)
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}, status=500)
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async def get_trigger_words(self, request: web.Request) -> web.Response:
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"""Get trigger words for specified LoRA models"""
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try:
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json_data = await request.json()
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lora_names = json_data.get("lora_names", [])
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node_ids = json_data.get("node_ids", [])
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all_trigger_words = []
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for lora_name in lora_names:
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_, trigger_words = get_lora_info(lora_name)
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all_trigger_words.extend(trigger_words)
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# Format the trigger words
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trigger_words_text = ",, ".join(all_trigger_words) if all_trigger_words else ""
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# Send update to all connected trigger word toggle nodes
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for entry in node_ids:
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node_identifier = entry
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graph_identifier = None
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if isinstance(entry, dict):
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node_identifier = entry.get("node_id")
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graph_identifier = entry.get("graph_id")
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try:
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parsed_node_id = int(node_identifier)
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except (TypeError, ValueError):
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parsed_node_id = node_identifier
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payload = {
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"id": parsed_node_id,
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"message": trigger_words_text
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}
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if graph_identifier is not None:
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payload["graph_id"] = str(graph_identifier)
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PromptServer.instance.send_sync("trigger_word_update", payload)
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return web.json_response({"success": True})
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except Exception as e:
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logger.error(f"Error getting trigger words: {e}")
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return web.json_response({
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"success": False,
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"error": str(e)
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}, status=500)
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