Update app.py

app.py

@@ -176,6 +176,7 @@ def get_kw_model():
     return kw_model
 
 def self_reasoning(query, context):
+    print("🧪 self_reasoning received context of length:", len(context))
     llm = GeminiLLM()
     reasoning_prompt = f"""
     You are an AI assistant that analyzes the context provided to answer the user's query comprehensively and clearly. 
@@ -200,7 +201,13 @@ def self_reasoning(query, context):
 
     **Answer:**
     """
-    return llm._call(reasoning_prompt)
+    try:
+        result = llm._call(reasoning_prompt)
+        print("✅ Gemini returned a result.")
+        return result
+    except Exception as e:
+        print("❌ Error in self_reasoning:", e)
+        return f"⚠️ Gemini failed: {e}"
 
 def faiss_search_with_keywords(query):
     global vectorstore_global
@@ -266,19 +273,27 @@ def handle_user_query(query):
         if vectorstore_global is None:
             raise ValueError("Vectorstore is not initialized.")
 
+        print("🔍 Starting handle_user_query with:", query)
+
         if "how" in query.lower():
+            print("🧠 Routing to: faiss_search_with_reasoning")
             context = faiss_search_with_reasoning(query)
         else:
+            print("🧠 Routing to: faiss_search_with_keywords")
             context = faiss_search_with_keywords(query)
 
+        print("📚 Context length:", len(context))
+        print("✍️ Calling self_reasoning...")
+
         answer = self_reasoning(query, context)
-        if not answer or answer.strip() == "":
-            raise ValueError("No answer was generated.")
+
+        print("✅ Answer generated.")
         return answer
 
     except Exception as e:
-        print("Error in handle_user_query:", e)
-        return f"Sorry, an error occurred: {str(e)}"
+        print("❌ Error in handle_user_query:", e)
+        return f"⚠️ Error: {e}"
+
 
 def save_feedback_to_huggingface():
     try: