Update app.py

app.py

@@ -628,7 +628,7 @@ Your goal: Provide the EXACT answer in the EXACT format requested.
             chat_llm = ChatGroq(
                 temperature=0,  # Maximum determinism
                 groq_api_key=GROQ_API_KEY,
-                model_name="qwen/qwen3-32b",  # Best reasoning model
+                model_name="openai/gpt-oss-120b",  # Best reasoning model
                 max_tokens=4096,
                 timeout=60
             )
@@ -641,77 +641,77 @@ Your goal: Provide the EXACT answer in the EXACT format requested.
         print("✅ Tools bound to LLM")
         
         # --- Agent Node ---
-def agent_node(state: AgentState):
-            
-            # --- Turn Counter Logic ---
-            # We need to check if this is a retry of a failed turn (e.g., Turn 1 violation)
-            # We identify a retry if the *last* message was our "Protocol Violation" message
-            last_msg = state['messages'][-1]
-            is_a_retry = False
-            if isinstance(last_msg, SystemMessage) and "Protocol Violation" in last_msg.content:
-                is_a_retry = True
-            
-            # Get the state's current turn number
-            current_turn = state.get('turn', 0)
-            
-            # If this is NOT a retry, increment the turn.
-            # If it IS a retry, we *stay on the same turn number*
-            if not is_a_retry:
-                current_turn += 1
-            
-            # Handle the very first run (where state['turn'] is 0)
-            if current_turn == 0:
-                current_turn = 1
-            # --- End Turn Counter Logic ---
-
-            print(f"\n{'='*60}")
-            print(f"AGENT TURN {current_turn}/{MAX_TURNS}")
-            if is_a_retry:
-                print("--- (Re-trying after protocol violation) ---")
-            print('='*60)
-            
-            messages_to_send = state["messages"]
-            
-            # Retry logic with exponential backoff
-            max_retries = 3
-            ai_message = None
-            
-            for attempt in range(max_retries):
-                try:
-                    ai_message = self.llm_with_tools.invoke(messages_to_send)
-                    break
-                except Exception as e:
-                    print(f"⚠️ LLM attempt {attempt+1}/{max_retries} failed: {e}")
-                    if attempt == max_retries - 1:
-                        error_msg = AIMessage(
-                            content=f"Error: LLM failed after {max_retries} attempts: {str(e)}"
-                        )
-                        return {"messages": [error_msg], "turn": current_turn}
-                    time.sleep(2 ** attempt)  # Exponential backoff
-            
-            # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
-            # --- (FIX #1) RULE ENFORCEMENT BLOCK ---
-            #
-            # If it's Turn 1 AND the agent tried to call tools, we reject it
-            # and force it to re-do Turn 1.
-            if current_turn == 1 and ai_message.tool_calls:
-                print("⚠️ AGENT VIOLATION: Tried to call tools on Turn 1. Forcing replan.")
+    def agent_node(state: AgentState):
                 
-                # Strip the illegal tool call
-                ai_message.tool_calls = []
+                # --- Turn Counter Logic ---
+                # We need to check if this is a retry of a failed turn (e.g., Turn 1 violation)
+                # We identify a retry if the *last* message was our "Protocol Violation" message
+                last_msg = state['messages'][-1]
+                is_a_retry = False
+                if isinstance(last_msg, SystemMessage) and "Protocol Violation" in last_msg.content:
+                    is_a_retry = True
                 
-                # Create the correction message that forces the plan
-                correction_message = SystemMessage(
-                    content="SYSTEM: Protocol Violation. Your FIRST turn MUST be a plan with NO tool calls. "
-                            "You are not allowed to call any tools on your first turn. "
-                            "Re-read the protocol and provide your 2-3 sentence plan now."
-                )
+                # Get the state's current turn number
+                current_turn = state.get('turn', 0)
+                
+                # If this is NOT a retry, increment the turn.
+                # If it IS a retry, we *stay on the same turn number*
+                if not is_a_retry:
+                    current_turn += 1
+                
+                # Handle the very first run (where state['turn'] is 0)
+                if current_turn == 0:
+                    current_turn = 1
+                # --- End Turn Counter Logic ---
+
+                print(f"\n{'='*60}")
+                print(f"AGENT TURN {current_turn}/{MAX_TURNS}")
+                if is_a_retry:
+                    print("--- (Re-trying after protocol violation) ---")
+                print('='*60)
+                
+                messages_to_send = state["messages"]
                 
-                # Return the messages.
-                # Critically, we set the state's turn counter back to 1.
-                # This ensures the *next* run of this node is *still* Turn 1.
-                return {"messages": [ai_message, correction_message], "turn": 1}
-            # --- END OF RULE ENFORCEMENT BLOCK ---
+                # Retry logic with exponential backoff
+                max_retries = 3
+                ai_message = None
+                
+                for attempt in range(max_retries):
+                    try:
+                        ai_message = self.llm_with_tools.invoke(messages_to_send)
+                        break
+                    except Exception as e:
+                        print(f"⚠️ LLM attempt {attempt+1}/{max_retries} failed: {e}")
+                        if attempt == max_retries - 1:
+                            error_msg = AIMessage(
+                                content=f"Error: LLM failed after {max_retries} attempts: {str(e)}"
+                            )
+                            return {"messages": [error_msg], "turn": current_turn}
+                        time.sleep(2 ** attempt)  # Exponential backoff
+                
+                # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+                # --- (FIX #1) RULE ENFORCEMENT BLOCK ---
+                #
+                # If it's Turn 1 AND the agent tried to call tools, we reject it
+                # and force it to re-do Turn 1.
+                if current_turn == 1 and ai_message.tool_calls:
+                    print("⚠️ AGENT VIOLATION: Tried to call tools on Turn 1. Forcing replan.")
+                    
+                    # Strip the illegal tool call
+                    ai_message.tool_calls = []
+                    
+                    # Create the correction message that forces the plan
+                    correction_message = SystemMessage(
+                        content="SYSTEM: Protocol Violation. Your FIRST turn MUST be a plan with NO tool calls. "
+                                "You are not allowed to call any tools on your first turn. "
+                                "Re-read the protocol and provide your 2-3 sentence plan now."
+                    )
+                    
+                    # Return the messages.
+                    # Critically, we set the state's turn counter back to 1.
+                    # This ensures the *next* run of this node is *still* Turn 1.
+                    return {"messages": [ai_message, correction_message], "turn": 1}
+                # --- END OF RULE ENFORCEMENT BLOCK ---
 # +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
             # --- FIX #2: REPLACE THE FALLBACK PARSING BLOCK ---
             #