Try to use proper tool doc

app.py

@@ -6,171 +6,86 @@ import requests
 import inspect
 import pandas as pd
 
-from langgraph.graph import StateGraph, START, END
+from langgraph.graph import StateGraph, START
 from langgraph.graph.message import add_messages
 from langgraph.prebuilt import ToolNode, tools_condition
 
 from langchain_openai import ChatOpenAI
 from langchain_community.tools import DuckDuckGoSearchRun
-from langchain_core.messages import AnyMessage, SystemMessage, HumanMessage, ToolMessage
+from langchain_core.messages import SystemMessage, HumanMessage
+
 
-# (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-
 class State(TypedDict):
     question: str
     messages: List[Dict[str, Any]]
 
 
-# --- Basic Agent Definition ---
-# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
-    
     def __init__(self):
-        
-        self.tools = [
-            self.search_tool, 
-            # self.image_analyze_tool, 
-            # self.file_operating_tool
-        ]
+        self.tools = [self.search_tool]
 
+        # Chat model with tool support
         self.model = ChatOpenAI(model="gpt-4o", temperature=0)
         self.model_with_tools = self.model.bind_tools(self.tools, parallel_tool_calls=False)
 
+        # LangGraph
         self.graph = StateGraph(State)
         self.graph.add_node("assistant", self.assistant)
         self.graph.add_node("tools", ToolNode(self.tools))
 
-        # Start the edges
         self.graph.add_edge(START, "assistant")
-        self.graph.add_conditional_edges(
-            "assistant",
-            tools_condition
-        )
-        self.graph.add_edge("tools", "assistant")
-        
-        # Compile the graph
-        self.compiled_graph = self.graph.compile()
+        self.graph.add_conditional_edges("assistant", tools_condition)  # decide if tools should be called
+        self.graph.add_edge("tools", "assistant")  # loop back
 
+        self.compiled_graph = self.graph.compile()
         print("BasicAgent initialized.")
 
-    def __call__(self, question: str) -> Tuple[str, TypedDict]:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
+    def __call__(self, question: str) -> Tuple[str, List[Dict[str, Any]]]:
+        print(f"Agent received question: {question}")
         state = State(question=question, messages=[HumanMessage(content=question)])
         result = self.compiled_graph.invoke(state)
         final_answer = result["messages"][-1].content
-        print(f"Agent returning fixed answer: {final_answer}")
+        print(f"Final Answer: {final_answer}")
         return final_answer, result["messages"]
 
-    # def assistant(self, state: State):
-    #     print("Assistant call state:", state)
-    #     messages = state.get("messages", [])
-        
-    #     # Add system message only once
-    #     if not any(isinstance(m, SystemMessage) for m in messages):
-    #         textual_description_of_tool="""
-    #             search_tool(question: str, max_length: int = 2048) -> str:
-    #                 Search info in the web.
-    #                 Call example:
-                    
-    #                     self.search_tool("Who won the election 2008 in the USA?", max_length = 4096)
-                
-    #                 Args:
-    #                     question: Question string
-    #                     max_length: maximum chars in the output (if exceeded the first "max_length" characters will be taken)
-                
-    #                 Returns:
-    #                     A single string containing the info from the web.
-    
-    #         """
-            
-    #         sys_msg = SystemMessage(
-    #             content=f"""You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string. 
-    #             You can use provided tools:\n{textual_description_of_tool}"""
-    #         )
-    #         messages = [sys_msg] + messages
-    
-    #     print("Calling model with tools invoke...")
-    #     new_msg = self.model_with_tools.invoke(messages)
-    #     print("Calling model with tools invoke finished, result:", new_msg)
-
-    #     # Detect tool call
-    #     if "tool_calls" in new_msg.additional_kwargs:
-    #         tool_call = new_msg.additional_kwargs["tool_calls"][0]
-    #         tool_response = self.search_tool(**eval(tool_call["function"]["arguments"]))
-    
-        #     tool_msg = ToolMessage(
-        #         tool_call_id=tool_call["id"],
-        #         content=tool_response,
-        #         name=tool_call["function"]["name"]
-        #     )
-    
-        #     return {
-        #         "question": state["question"],
-        #         "messages": messages + [new_msg, tool_msg],
-        #     }
-    
-        # # new_messages = add_messages(messages, [new_msg])
-        # return {
-        #     "question": state["question"],
-        #     "messages": messages + [new_msg],
-        # }
-
     def assistant(self, state: State):
-        print("Assistant call state:", state)
+        print("Assistant invoked.")
         messages = state.get("messages", [])
-    
+
         # Add system message only once
         if not any(isinstance(m, SystemMessage) for m in messages):
-            textual_description_of_tool = """
-                search_tool(question: str, max_length: int = 2048) -> str:
-                    Search info on the web.
-                    Call example:
-    
-                        self.search_tool("Who won the election 2008 in the USA?", max_length = 4096)
-    
-                    Args:
-                        question: Question string
-                        max_length: maximum chars in the output (if exceeded, the first "max_length" characters will be taken)
-    
-                    Returns:
-                        A single string containing the info from the web.
+            tool_doc = """
+search_tool(question: str, max_length: int = 2048) -> str:
+    Search info on the web.
+    Args:
+        question: Question string
+        max_length: maximum characters in the output
+    Returns:
+        A single string containing the info from the web.
             """
-            
             sys_msg = SystemMessage(
-                content=f"""You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending on whether the element to be put in the list is a number or a string. 
-    You can use provided tools:\n{textual_description_of_tool}"""
+                content=f"""You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. You can use provided tools:\n{tool_doc}"""
             )
             messages = [sys_msg] + messages
-    
-        print("Calling model with tools invoke...")
-        new_msg = self.model_with_tools.invoke(messages)
-        print("Calling model with tools invoke finished, result:", new_msg)
-    
-        # Let LangGraph handle tool routing
+
+        # Invoke model with tools (LangGraph handles tool routing)
+        response = self.model_with_tools.invoke(messages)
+        print("Assistant response:", response)
+
         return {
             "question": state["question"],
-            "messages": add_messages(messages, [new_msg]),
+            "messages": add_messages(messages, [response]),
         }
 
-
     def search_tool(self, question: str, max_length: int = 2048) -> str:
-        """
-            Search info in the web.
-            
-            Args:
-                question: Question string
-                max_length: Maximum length of response (default 2048 chars)
-            
-            Returns:
-                A single string containing the info from the web.
-        """
+        print(f"Calling search tool with: {question}")
         search = DuckDuckGoSearchRun()
-        res = search.invoke(question)
-        print("Search res:", res)
-        return res[:max_length]
+        result = search.invoke(question)
+        print("Tool result:", result)
+        return result[:max_length]
     
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):