Update app.py

app.py

@@ -21,13 +21,13 @@ HF_TOKEN = os.getenv("HF_TOKEN")  # Make sure to set this environment variable
 
 
 class AgentState(TypedDict):
-    question: Annotated[List[str], operator.add]
-    current_step: Annotated[str, "input"]
+    question: Annotated[str, operator.or_]
+    current_step: Annotated[str, operator.or_]
     tool_output: Annotated[str, "input"]
     final_answer: Annotated[str, "input"]
     history: Annotated[List[Dict[str, str]], operator.add]
     needs_more_info: Annotated[bool, "input"]
-    search_query: Annotated[str, "input"]
+    search_query: Annotated[str, operator.or_]
 
 class BasicAgent:
     def __init__(self):
@@ -103,10 +103,7 @@ class BasicAgent:
 
     def _analyze_question(self, state: AgentState) -> AgentState:
         """Analyze the question and determine the next step."""
-        # Get the most recent question from the list
-        current_question = state["question"][-1]
-        
-        prompt = f"""Analyze this question and determine what needs to be done: {current_question}
+        prompt = f"""Analyze this question and determine what needs to be done: {state['question']}
 
 Return only a valid Python dictionary in this exact format:
 {{
@@ -130,7 +127,7 @@ Do not include any other text or explanation. Only return the dictionary.
             print(f"Error parsing LLM response: {e}")
             # Default to search if we can't parse the response
             state["needs_more_info"] = True
-            state["search_query"] = current_question
+            state["search_query"] = state["question"]
             state["current_step"] = 'search'
         
         return state
@@ -161,13 +158,10 @@ Do not include any other text or explanation. Only return the dictionary.
 
     def _generate_final_answer(self, state: AgentState) -> AgentState:
         """Generate the final answer based on all gathered information."""
-        # Get the most recent question from the list
-        current_question = state["question"][-1]
-        
         history_str = "\n".join([f"{h['step']}: {h.get('output', h.get('results', h.get('error', '')))}" 
                                for h in state["history"]])
         
-        prompt = f"""Based on the following information and history, provide a final answer to the question: {current_question}
+        prompt = f"""Based on the following information and history, provide a final answer to the question: {state['question']}
         
         History of steps taken:
         {history_str}
@@ -185,7 +179,7 @@ Do not include any other text or explanation. Only return the dictionary.
         try:
             # Initialize the state
             initial_state: AgentState = {
-                "question": [question],  # Initialize as a list with one question
+                "question": question,  # Now a string, not a list
                 "current_step": "analyze",
                 "tool_output": "",
                 "final_answer": "",
@@ -270,7 +264,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         try:
             # Initialize the state for this question
             initial_state = {
-                "question": [question_text],  # Initialize as a list with one question
+                "question": question_text,  # Now a string, not a list
                 "current_step": "analyze",
                 "tool_output": "",
                 "final_answer": "",