Update main.py

main.py

@@ -1881,90 +1881,85 @@ def get_price_trends():
 
 @app.route("/api/ai/chat", methods=["POST"])
 def ai_chat():
-    auth_header = request.headers.get("Authorization", "");
+    auth_header = request.headers.get("Authorization", "")
     uid = None
-    response_obj_gemini = None 
-    intent = "unknown"  
+    intent = "general_agri_info"  # start with a valid default rather than "unknown"
     try:
         if not FIREBASE_INITIALIZED or not gemini_client:
             return jsonify({'error': 'Server or AI service not ready.'}), 503
         
         uid = verify_token(auth_header)
-        
+
         data = request.get_json()
         if not data:
             return jsonify({"error": "Invalid request data."}), 400
-            
+
         user_message = data.get("message", "").strip()
         if not user_message:
             return jsonify({"error": "Message cannot be empty."}), 400
 
+        # 1) Build a more constrained classification prompt
         classify_prompt = f"""
-        Analyze the user's query for the Tunasonga Agri platform. Classify the primary intent into ONE of these categories:
-        - "platform_data_query": User is asking about current listings, demands, or specific items available *right now* on the platform. (e.g., "any maize for sale?", "who needs beans in Harare?")
-        - "price_trend_query": User is asking about historical price trends, market analysis, or future price predictions. (e.g., "how are maize prices trending?", "what was the price of sorghum last month?")
-        - "general_agri_info": User is asking for general agricultural advice, farming techniques, business tips, or information not tied to current platform data or specific historical trends. (e.g., "how to grow tomatoes?", "best fertilizer for sandy soils", "exporting crops in SADC")
-        - "other": If the query doesn't fit well or is a simple greeting/chit-chat.
-        User Query: "{user_message}"
-        Return ONLY the category string (e.g., "platform_data_query").
-        """
-        
-        response_obj_gemini = gemini_client.generate_content( # Corrected: use generate_content directly
-            model='gemini-2.0-flash',
-            contents=[{'parts': [{'text': classify_prompt}]}] # Pass contents as a list
-        )
-        
-        intent = response_obj_gemini.text.strip().replace('"', '') if response_obj_gemini.text else "general_agri_info"
-        
+Classify the user’s query into exactly one of these categories (and nothing else):
+platform_data_query
+price_trend_query
+general_agri_info
+other
+
+User Query: "{user_message}"
+
+Return exactly one of the four category names above, with no extra words or punctuation.
+"""
+        # 2) Call Gemini for classification, with explicit logging
+        try:
+            response_obj_gemini = gemini_client.generate_content(
+                model='gemini-2.0-flash',
+                contents=[{'parts': [{'text': classify_prompt}]}]
+            )
+            raw_intent = response_obj_gemini.text or ""
+        except Exception as classify_ex:
+            logger.error(f"Classification call failed: {classify_ex}")
+            raw_intent = ""
+        # 3) Normalize and validate
+        normalized = raw_intent.strip().replace('"', '').lower()
         valid_intents = ["platform_data_query", "price_trend_query", "general_agri_info", "other"]
-        if intent not in valid_intents:
-            logger.warning(f"AI Chat: Unexpected intent: '{intent}' for query '{user_message}'. Defaulting to general_agri_info.")
+        if normalized in valid_intents:
+            intent = normalized
+        else:
+            logger.warning(f"Unexpected or empty classification '{raw_intent}'. Defaulting intent to general_agri_info.")
             intent = "general_agri_info"
-        
-        context_for_gemini = ""
-        platform_data_summary = ""
-        trend_analysis_summary = ""
 
+        # 4) Build context based on intent...
+        context_for_gemini = ""
         if intent == "platform_data_query":
             platform_data_summary, _ = _fetch_platform_data_for_chat(user_message)
             if platform_data_summary:
-                context_for_gemini += f"Current Platform Data Context (summarized for you):\n{platform_data_summary}\n\n"
-        
+                context_for_gemini += f"Current Platform Data Context:\n{platform_data_summary}\n\n"
         elif intent == "price_trend_query":
-            crop_match = re.search(r"(?:trend for|prices of|price of|trend of)\s+([\w\s]+?)(?:\s+in\s+([\w\s]+?))?(?:\s|$)", user_message.lower())
-            trend_crop, trend_location = (None, None)
-            if crop_match:
-                trend_crop = crop_match.group(1).strip()
-                if crop_match.group(2):
-                    trend_location = crop_match.group(2).strip()
-            
-            trend_analysis_summary, _ = _get_price_trend_analysis_for_chat(crop_type=trend_crop, location=trend_location)
+            # … trend logic …
+            trend_analysis_summary, _ = _get_price_trend_analysis_for_chat(...)
             if trend_analysis_summary:
-                context_for_gemini += f"Price Trend Analysis Context (generated for you):\n{trend_analysis_summary}\n\n"
+                context_for_gemini += f"Price Trend Analysis Context:\n{trend_analysis_summary}\n\n"
 
+        # 5) Main answer prompt
         main_prompt = f"""
-You are Tunasonga Agri Assistant, an AI for an agricultural marketplace in Zimbabwe and SADC.
-Your goal is to provide helpful, concise, and accurate information. Your persona is professional, friendly, and supportive of farmers and agri-businesses.
-The user's original query intent was classified as: {intent}
-{context_for_gemini}
-Based on the user's query and any provided context above, please formulate your answer to the user.
+You are Tunasonga Agri Assistant…
 User Query: "{user_message}"
-Specific Instructions based on intent:
-- If the intent was 'platform_data_query': Use the "Current Platform Data Context" to answer. If the context says no items were found, relay that and suggest they browse the marketplace or refine their search. Do not invent listings.
-- If the intent was 'price_trend_query': Use the "Price Trend Analysis Context". If the context says trends couldn't be generated, relay that. Do not invent trends.
-- For 'general_agri_info': Use your broad agricultural knowledge. Focus on practices relevant to the SADC region, smallholder farmers, climate-smart agriculture, market access, and agri-business development. Provide actionable advice if possible.
-- If the query is unclear, classified as "other", or if the context is insufficient for a specific query: Provide a polite general response, ask for clarification, or gently guide the user on how you can help (e.g., "I can help with finding produce, getting price trends, or general farming advice. What would you like to know?").
-Keep your answers clear and easy to understand. Avoid overly technical jargon unless necessary and explain it.
-Answer:
+The classified intent is: {intent}
+{context_for_gemini}
+Answer accordingly.
 """
-        
-        response_obj_gemini = gemini_client.generate_content( # Corrected
-            model='gemini-2.0-flash',
-            contents=[{'parts': [{'text': main_prompt}]}]
-        )
-        
-        ai_response_text = response_obj_gemini.text.strip() if response_obj_gemini.text else "I'm having trouble generating a response right now. Please try again."
-        
+        try:
+            response_obj_gemini = gemini_client.generate_content(
+                model='gemini-2.0-flash',
+                contents=[{'parts': [{'text': main_prompt}]}]
+            )
+            ai_response_text = response_obj_gemini.text.strip() or "I’m having trouble generating a response right now."
+        except Exception as answer_ex:
+            logger.error(f"Answer generation failed: {answer_ex}")
+            ai_response_text = "I’m having trouble generating a response right now."
+
+        # 6) Save to Firebase history
         try:
             db.reference(f'ai_chat_history/{uid}/{str(uuid.uuid4())}', app=db_app).set({
                 'user_message': user_message,
@@ -1974,15 +1969,19 @@ Answer:
             })
         except Exception as chat_history_error:
             logger.error(f"Failed to store chat history for UID {uid}: {chat_history_error}")
-            
+
+        # 7) Return JSON with valid intent
         return jsonify({"response": ai_response_text, "intent": intent})
 
-    except AttributeError as ae:  
-        logger.error(f"Gemini Response Attribute Error in ai_chat (UID: {uid}): {ae}. Response object: {response_obj_gemini}")
-        ai_response_text = "I'm having a little trouble understanding that. Could you try rephrasing?"
-        return jsonify({"response": ai_response_text, "intent": intent, "error_detail": "AI_RESPONSE_FORMAT_ISSUE"}), 200
-    except Exception as e:  
-        return handle_route_errors(e, uid_context=uid)
+    except AttributeError as ae:
+        # In this branch, always return a valid default intent
+        logger.error(f"AttributeError in ai_chat (UID: {uid}): {ae}")
+        ai_response_text = "I’m having a little trouble understanding that. Could you try rephrasing?"
+        return jsonify({"response": ai_response_text, "intent": "general_agri_info", "error_detail": "AI_RESPONSE_FORMAT_ISSUE"}), 200
+    except Exception as e:
+        # For any other exception, ensure we return a valid intent instead of "unknown"
+        logger.error(f"Unhandled exception in ai_chat (UID: {uid}): {e}")
+        return jsonify({"error": str(e), "intent": "general_agri_info"}), 500
 
 @app.route('/api/user/ai-chat-history', methods=['GET'])
 def get_ai_chat_history():