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from django.apps import AppConfig
import os
import logging
logger = logging.getLogger(__name__)
class CoreConfig(AppConfig):
default_auto_field = "django.db.models.AutoField"
name = "hue_portal.core"
def ready(self):
print('[CoreConfig] 🔔 ready() method called', flush=True)
logger.info('[CoreConfig] ready() method called')
from . import signals # noqa: F401
# Preload models in worker process (Gunicorn workers are separate processes)
# This ensures models are loaded when worker starts, not on first request
# Skip preload if running migrations or other management commands
import sys
if 'migrate' in sys.argv or 'collectstatic' in sys.argv or 'generate_legal_questions' in sys.argv or 'train_intent' in sys.argv or 'populate_legal_tsv' in sys.argv:
print('[CoreConfig] ⏭️ Skipping model preload (management command)', flush=True)
logger.info('[CoreConfig] Skipping model preload (management command)')
return
django_settings = os.environ.get('DJANGO_SETTINGS_MODULE')
print(f'[CoreConfig] 🔍 DJANGO_SETTINGS_MODULE: {django_settings}', flush=True)
logger.info(f'[CoreConfig] DJANGO_SETTINGS_MODULE: {django_settings}')
if django_settings:
try:
print('[CoreConfig] 🔄 Preloading models in worker process...', flush=True)
logger.info('[CoreConfig] Preloading models in worker process...')
# 1. Preload Embedding Model (BGE-M3)
try:
print('[CoreConfig] 📦 Preloading embedding model (BGE-M3)...', flush=True)
from .embeddings import get_embedding_model
embedding_model = get_embedding_model()
if embedding_model:
print('[CoreConfig] ✅ Embedding model preloaded successfully', flush=True)
logger.info('[CoreConfig] Embedding model preloaded successfully')
else:
print('[CoreConfig] ⚠️ Embedding model not loaded', flush=True)
except Exception as e:
print(f'[CoreConfig] ⚠️ Embedding model preload failed: {e}', flush=True)
logger.warning(f'[CoreConfig] Embedding model preload failed: {e}')
# 2. Preload LLM Model (llama.cpp)
llm_provider = os.environ.get('DEFAULT_LLM_PROVIDER') or os.environ.get('LLM_PROVIDER', '')
if llm_provider.lower() == 'llama_cpp':
try:
print('[CoreConfig] 📦 Preloading LLM model (llama.cpp)...', flush=True)
from hue_portal.chatbot.llm_integration import get_llm_generator
llm_gen = get_llm_generator()
if llm_gen and hasattr(llm_gen, 'llama_cpp') and llm_gen.llama_cpp:
print('[CoreConfig] ✅ LLM model preloaded successfully', flush=True)
logger.info('[CoreConfig] LLM model preloaded successfully')
else:
print('[CoreConfig] ⚠️ LLM model not loaded (may load on first request)', flush=True)
except Exception as e:
print(f'[CoreConfig] ⚠️ LLM model preload failed: {e} (will load on first request)', flush=True)
logger.warning(f'[CoreConfig] LLM model preload failed: {e}')
else:
print(f'[CoreConfig] ⏭️ Skipping LLM preload (provider is {llm_provider or "not set"}, not llama_cpp)', flush=True)
# 3. Preload Reranker Model
try:
print('[CoreConfig] 📦 Preloading reranker model...', flush=True)
from .reranker import get_reranker
reranker = get_reranker()
if reranker:
print('[CoreConfig] ✅ Reranker model preloaded successfully', flush=True)
logger.info('[CoreConfig] Reranker model preloaded successfully')
else:
print('[CoreConfig] ⚠️ Reranker model not loaded (may load on first request)', flush=True)
except Exception as e:
print(f'[CoreConfig] ⚠️ Reranker preload failed: {e} (will load on first request)', flush=True)
logger.warning(f'[CoreConfig] Reranker preload failed: {e}')
print('[CoreConfig] ✅ Model preload completed in worker process', flush=True)
logger.info('[CoreConfig] Model preload completed in worker process')
except Exception as e:
print(f'[CoreConfig] ⚠️ Model preload error: {e} (models will load on first request)', flush=True)
logger.warning(f'[CoreConfig] Model preload error: {e}')
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