Update alz_companion/agent.py

alz_companion/agent.py

@@ -102,7 +102,8 @@ def describe_image(image_path: str) -> str:
 
 # In agent.py
 
-def detect_tags_from_query(query: str, behavior_options: list, emotion_options: list, topic_options: list, context_options: list) -> Dict[str, Any]:
+# def detect_tags_from_query(query: str, behavior_options: list, emotion_options: list, topic_options: list, context_options: list) -> Dict[str, Any]:
+def detect_tags_from_query(query: str, behavior_options: list, emotion_options: list, topic_options: list, context_options: list, settings: dict = None) -> Dict[str, Any]:
     """Uses a Chain-of-Thought prompt to classify the user's query."""
     behavior_str = ", ".join(f'"{opt}"' for opt in behavior_options if opt != "None")
     emotion_str = ", ".join(f'"{opt}"' for opt in emotion_options if opt != "None")
@@ -119,8 +120,10 @@ def detect_tags_from_query(query: str, behavior_options: list, emotion_options:
     
     messages = [{"role": "system", "content": "You are a helpful NLU classification assistant. Follow the instructions precisely."}, {"role": "user", "content": prompt}]
     response_str = call_llm(messages, temperature=0.1)
-    
-    print(f"\n--- NLU Full Response ---\n{response_str}\n-----------------------\n")
+
+    # logging based on debug mode
+    if settings and settings.get("debug_mode"):
+        print(f"\n--- NLU Full Response ---\n{response_str}\n-----------------------\n")
     
     result_dict = {
         "detected_behaviors": [], "detected_emotion": "None",