Refactor intent extraction logic in AI chat

- Moved the check for non-JSON responses to after content cleanup in the `extract_and_update_intent` function, improving clarity and ensuring that the response is properly processed before validation.
- Enhanced logging for non-JSON responses to aid in debugging and provide better context for the user experience.

ai_chat.py

@@ -155,11 +155,6 @@ async def extract_and_update_intent(state):
     response = await llm.ainvoke([{"role":"user","content":extraction_prompt}])
     print(f"LLM response for intent extraction: {response.content}")
     
-    # Check if response is an explanatory answer rather than JSON
-    if not response.content.strip().startswith("{"):
-        state["response"] = response.content
-        return state
-    
     import json
     try:
         # Clean up the response content (remove markdown formatting if present)
@@ -175,6 +170,12 @@ async def extract_and_update_intent(state):
         content = content.strip()
         print(f"Final cleaned content: {repr(content)}")
         
+        # Check if cleaned content is JSON
+        if not content.startswith("{"):
+            print("Cleaned content is not JSON, treating as explanatory answer")
+            state["response"] = response.content
+            return state
+        
         extracted = json.loads(content)
         print(f"Successfully parsed intent JSON: {extracted}")
     except Exception as e: