Update app.py

app.py

@@ -32,6 +32,15 @@ from langchain_community.llms import HuggingFaceHub
 from langchain_community.chat_models import ChatHuggingFace
 
 
+from langchain.schema import HumanMessage  # Or your framework's equivalent
+
+def init_state(question: str):
+    return {
+        "question": question,
+        "history": [HumanMessage(content=question)]
+    }
+
+
 # ====== Tool Definitions ======
 @tool
 def duckduckgo_search(query: str) -> str:
@@ -272,27 +281,29 @@ class BasicAgent:
     def __call__(self, question: str) -> str:
         print(f"Agent received question: {question[:50]}{'...' if len(question) > 50 else ''}")
         
-        # Initialize state with the question
-        state = init_state(question)
-        
-        # Execute the workflow
+        # Ensure proper HumanMessage in history
+        state = {
+            "question": question,
+            "history": [HumanMessage(content=question)]
+        }
+    
         final_state = self.workflow.invoke(state)
-        
-        # Debug: Print the final state structure
+    
         print(f"Final state keys: {list(final_state.keys())}")
         if 'history' in final_state:
             print(f"History length: {len(final_state['history'])}")
             for i, msg in enumerate(final_state['history']):
                 print(f"Message {i}: {type(msg).__name__} - {msg.content[:100]}...")
-        
-        # Extract final answer from history
+    
         for msg in reversed(final_state['history']):
             if isinstance(msg, AIMessage) and "FINAL ANSWER:" in msg.content:
-                # Extract and clean the final answer
                 answer = msg.content.split("FINAL ANSWER:")[1].strip()
                 print(f"Agent returning answer: {answer}")
                 return answer
     
+        raise ValueError("No FINAL ANSWER found in agent history.")
+
+    
 
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):