Upload app.py

app.py

@@ -1,13 +1,11 @@
-""" Basic Agent Evaluation Runner"""
 import os
-import inspect
 import gradio as gr
 import requests
+import inspect
 import pandas as pd
-from langchain_core.messages import HumanMessage
-from agent import build_graph
-
 
+from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+from smolagents import OpenAIServerModel, DuckDuckGoSearchTool, CodeAgent, WikipediaSearchTool
 
 # (Keep Constants as is)
 # --- Constants ---
@@ -15,22 +13,20 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
-
-
 class BasicAgent:
-    """A langgraph agent."""
     def __init__(self):
+        self.agent = CodeAgent(
+            model=OpenAIServerModel(model_id="gpt-4o-mini", api_key="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"),
+            tools=[DuckDuckGoSearchTool(), WikipediaSearchTool()],
+            add_base_tools=True,
+        )
         print("BasicAgent initialized.")
-        self.graph = build_graph()
-
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-        # Wrap the question in a HumanMessage from langchain_core
-        messages = [HumanMessage(content=question)]
-        messages = self.graph.invoke({"messages": messages})
-        answer = messages['messages'][-1].content
-        print(f"answer is - {answer}")
-        return answer[14:]
+        # fixed_answer = "This is a default answer."
+        fixed_answer = self.agent.run(question)
+        print(f"Agent returning fixed answer: {fixed_answer}")
+        return fixed_answer
 
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
@@ -95,6 +91,8 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             continue
         try:
             submitted_answer = agent(question_text)
+            if not isinstance(submitted_answer, str):
+                submitted_answer = str(submitted_answer)
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
         except Exception as e:
@@ -160,11 +158,9 @@ with gr.Blocks() as demo:
     gr.Markdown(
         """
         **Instructions:**
-
         1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
         2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
         3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
-
         ---
         **Disclaimers:**
         Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).