Update app.py

app.py

@@ -3,6 +3,8 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+from smolagents import DuckDuckGoSearchTool
+from tools import hub_stats_tool
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -19,6 +21,57 @@ class BasicAgent:
         print(f"Agent returning fixed answer: {fixed_answer}")
         return fixed_answer
 
+class NewAgent:
+    def __init__(self):
+        print("NewAgent initialized.")
+        
+        
+        # Initialize the web search tool
+        search_tool = DuckDuckGoSearchTool()
+        # Initialize the Hub stats tool
+        hub_stats_tool = HubStatsTool()
+        # 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)
+        # Generate the AgentState and Agent graph
+        class AgentState(TypedDict):
+            messages: Annotated[list[AnyMessage], add_messages]
+        def assistant(state: AgentState):
+            return {
+                "messages": [chat_with_tools.invoke(state["messages"])],
+            }
+        ## The graph
+        builder = StateGraph(AgentState)
+        # Define nodes: these do the work
+        builder.add_node("assistant", assistant)
+        builder.add_node("tools", ToolNode(tools))
+        # Define edges: these determine how the control flow moves
+        builder.add_edge(START, "assistant")
+        builder.add_conditional_edges(
+            "assistant",
+            # If the latest message requires a tool, route to tools
+            # Otherwise, provide a direct response
+            tools_condition,
+        )
+        builder.add_edge("tools", "assistant")
+        alfred = builder.compile()
+
+    def __call__(self, question: str) -> str:
+        print(f"Agent received question (first 50 chars): {question[:50]}...")
+        # fixed_answer = "This is a default answer."
+        # print(f"Agent returning fixed answer: {fixed_answer}")
+        # return fixed_answer
+        messages = [HumanMessage(content=question)]
+        response = alfred.invoke({"messages": messages})
+        
+
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
@@ -40,7 +93,8 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
-        agent = BasicAgent()
+        # agent = BasicAgent()
+        agent = NewAgent()
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None