Create models.py

src/models.py

@@ -0,0 +1,37 @@
+import logging
+from typing import Dict, Any, Optional
+
+logger = logging.getLogger(__name__)
+
+def load_all_models() -> Dict[str, Any]:
+    models = {
+        "status": False,
+        "deep_learning_analyzer": None,
+        "rag_handler": None,
+        "llm": None
+    }
+    
+    try:
+        from src.core.deep_learning_analyzer import MultiModelInterviewAnalyzer
+        models["deep_learning_analyzer"] = MultiModelInterviewAnalyzer()
+        logger.info("✅ Deep Learning Analyzer chargé")
+    except Exception as e:
+        logger.error(f"❌ Erreur chargement Deep Learning Analyzer: {e}")
+    
+    try:
+        from src.core.rag_handler import get_rag_handler
+        models["rag_handler"] = get_rag_handler()
+        logger.info("✅ RAG Handler chargé")
+    except Exception as e:
+        logger.error(f"❌ Erreur chargement RAG Handler: {e}")
+    
+    try:
+        from src.config import crew_openai
+        models["llm"] = crew_openai()
+        logger.info("✅ LLM chargé")
+    except Exception as e:
+        logger.error(f"❌ Erreur chargement LLM: {e}")
+    
+    models["status"] = all(v is not None for k, v in models.items() if k != "status")
+    
+    return models