Update app.py

app.py

@@ -37,24 +37,23 @@ class NewAgent:
             description="Fetches the most downloaded model from a specific author on the Hugging Face Hub."
         )
         # Generate the chat interface, including the tools
-        llm = HuggingFaceEndpoint(
-            repo_id="Qwen/Qwen2.5-Coder-32B-Instruct",
-            huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN,
-        )
-        chat = ChatHuggingFace(llm=llm, verbose=True)
         tools = [
             search_tool,
             # weather_info_tool,
             hub_stats_tool,
         ]
-        chat_with_tools = chat.bind_tools(tools)
+        llm = ChatOpenAI(model="gpt-4o")
+        llm_with_tools = llm.bind_tools(tools, parallel_tool_calls=False)
+        
         # Generate the AgentState and Agent graph
         class AgentState(TypedDict):
             messages: Annotated[list[AnyMessage], add_messages]
         def assistant(state: AgentState):
+            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.")
             return {
-                "messages": [chat_with_tools.invoke(state["messages"])],
+                "messages": [llm_with_tools.invoke([sys_msg] + state["messages"])],
             }
+            
         ## The graph
         builder = StateGraph(AgentState)
         # Define nodes: these do the work