Update tools/analysis_tools.py

tools/analysis_tools.py

@@ -1,32 +1,33 @@
 import logging
 from langchain_core.tools import tool
-from src.services.analysis_service import AnalysisService # Assurez-vous que le chemin d'importation est correct
-
+from src.services.analysis_service import AnalysisService 
+import json
+from typing import List, Dict
+from src.models import load_all_models
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
 @tool
-def trigger_interview_analysis(user_id: str, job_offer_id: str, conversation_history: list):
+def trigger_interview_analysis(user_id: str, job_offer_id: str, conversation_history: List[Dict], job_description: str):
     """
-    Call this tool to end the interview and start the final analysis.
-    This should be the very last step of the conversation.
-    Do not ask the user for confirmation before calling this tool.
+    Appelle cet outil pour terminer l'entretien et lancer l'analyse finale.
+    Tu DOIS fournir le user_id, le job_offer_id, l'historique complet de la conversation (conversation_history), et la description complète du poste (job_description).
     """
     try:
-        logger.info(f"Tool 'trigger_interview_analysis' called for user_id: {user_id} and job_offer_id: {job_offer_id}.")
-        
-        # Initialisez et lancez votre service d'analyse exactement comme avant
-        analysis_service = AnalysisService(
-            user_id=user_id,
-            job_offer_id=job_offer_id,
-            conversation_history=conversation_history
+        logger.info(f"Outil 'trigger_interview_analysis' appelé pour user_id: {user_id}")
+        models = load_all_models()
+        analysis_service = AnalysisService(models=models)
+        feedback_data = analysis_service.run_analysis(
+            conversation_history=conversation_history,
+            job_description=job_description
         )
-        
-        # Lance la tâche de fond
-        analysis_service.run_analysis_in_background()
-        
-        logger.info("Analysis task successfully started in the background.")
-        return "Analysis has been successfully triggered. The user has been notified."
+        feedback_path = f"/tmp/feedbacks/{user_id}.json"
+        with open(feedback_path, "w", encoding="utf-8") as f:
+            json.dump({"status": "completed", "feedback_data": feedback_data}, f, ensure_ascii=False, indent=4)
+
+        logger.info(f"Analyse pour l'utilisateur {user_id} terminée et sauvegardée dans {feedback_path}.")
+        return "L'analyse a été déclenchée et terminée avec succès."
+
     except Exception as e:
-        logger.error(f"Error calling analysis tool: {e}", exc_info=True)
-        return "An error occurred while trying to start the analysis."
+        logger.error(f"Erreur dans l'outil d'analyse : {e}", exc_info=True)
+        return "Une erreur est survenue lors du lancement de l'analyse."