| import os |
| import gradio as gr |
| import requests |
| import pandas as pd |
|
|
| from smolagents import ( |
| CodeAgent, |
| DuckDuckGoSearchTool, |
| InferenceClientModel |
| ) |
|
|
| |
| |
| |
| DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space" |
|
|
|
|
| |
| |
| |
| class BasicAgent: |
| def __init__(self): |
|
|
| print("Initializing Smart Agent...") |
|
|
| |
| search_tool = DuckDuckGoSearchTool() |
|
|
| |
| model = InferenceClientModel( |
| model_id="meta-llama/Llama-3.1-8B-Instruct" |
| ) |
|
|
| |
| self.agent = CodeAgent( |
| tools=[search_tool], |
| model=model, |
| add_base_tools=True, |
| max_steps=5 |
| ) |
|
|
| def __call__(self, question: str) -> str: |
|
|
| print(f"Question: {question}") |
|
|
| prompt = f""" |
| You are a GAIA benchmark assistant. |
| |
| IMPORTANT RULES: |
| - Return ONLY the final answer |
| - Do NOT explain your reasoning |
| - Do NOT write 'FINAL ANSWER' |
| - Keep answers short and exact |
| - If the answer is a number, return only the number |
| - If the answer is text, return only the text |
| |
| Question: |
| {question} |
| """ |
|
|
| try: |
| response = self.agent.run(prompt) |
|
|
| answer = str(response).strip() |
|
|
| print(f"Agent answer: {answer}") |
|
|
| return answer |
|
|
| except Exception as e: |
| print(f"Error while solving question: {e}") |
|
|
| return "Error" |
|
|
|
|
| |
| |
| |
| def run_and_submit_all(profile: gr.OAuthProfile | None): |
|
|
| space_id = os.getenv("SPACE_ID") |
|
|
| if profile: |
| username = f"{profile.username}" |
| print(f"User logged in: {username}") |
| else: |
| return "Please login with Hugging Face first.", None |
|
|
| api_url = DEFAULT_API_URL |
|
|
| questions_url = f"{api_url}/questions" |
| submit_url = f"{api_url}/submit" |
|
|
| |
| |
| |
| try: |
| agent = BasicAgent() |
|
|
| except Exception as e: |
| return f"Error initializing agent: {e}", None |
|
|
| |
| |
| |
| agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" |
|
|
| print(agent_code) |
|
|
| |
| |
| |
| try: |
| response = requests.get( |
| questions_url, |
| timeout=30 |
| ) |
|
|
| response.raise_for_status() |
|
|
| questions_data = response.json() |
|
|
| print(f"Fetched {len(questions_data)} questions") |
|
|
| except Exception as e: |
| return f"Error fetching questions: {e}", None |
|
|
| |
| |
| |
| results_log = [] |
|
|
| answers_payload = [] |
|
|
| for item in questions_data: |
|
|
| task_id = item.get("task_id") |
|
|
| question_text = item.get("question") |
|
|
| if not task_id or question_text is None: |
| continue |
|
|
| try: |
| submitted_answer = agent(question_text) |
|
|
| 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: |
|
|
| results_log.append({ |
| "Task ID": task_id, |
| "Question": question_text, |
| "Submitted Answer": f"ERROR: {e}" |
| }) |
|
|
| |
| |
| |
| submission_data = { |
| "username": username.strip(), |
| "agent_code": agent_code, |
| "answers": answers_payload |
| } |
|
|
| try: |
|
|
| response = requests.post( |
| submit_url, |
| json=submission_data, |
| timeout=120 |
| ) |
|
|
| response.raise_for_status() |
|
|
| result_data = response.json() |
|
|
| final_status = ( |
| f"Submission Successful!\n\n" |
| f"User: {result_data.get('username')}\n" |
| f"Score: {result_data.get('score')}%\n" |
| f"Correct: {result_data.get('correct_count')}/" |
| f"{result_data.get('total_attempted')}\n\n" |
| f"Message: {result_data.get('message')}" |
| ) |
|
|
| results_df = pd.DataFrame(results_log) |
|
|
| return final_status, results_df |
|
|
| except Exception as e: |
|
|
| results_df = pd.DataFrame(results_log) |
|
|
| return f"Submission Failed: {e}", results_df |
|
|
|
|
| |
| |
| |
| with gr.Blocks() as demo: |
|
|
| gr.Markdown("# GAIA Agent Evaluation") |
|
|
| gr.Markdown( |
| """ |
| Login with Hugging Face and run your AI agent on GAIA questions. |
| """ |
| ) |
|
|
| gr.LoginButton() |
|
|
| run_button = gr.Button( |
| "Run Evaluation & Submit All Answers" |
| ) |
|
|
| status_output = gr.Textbox( |
| label="Status", |
| lines=8 |
| ) |
|
|
| results_table = gr.DataFrame( |
| label="Agent Results" |
| ) |
|
|
| run_button.click( |
| fn=run_and_submit_all, |
| outputs=[ |
| status_output, |
| results_table |
| ] |
| ) |
|
|
|
|
| |
| |
| |
| if __name__ == "__main__": |
|
|
| print("Starting GAIA Agent App...") |
|
|
| demo.launch( |
| debug=True, |
| share=False |
| ) |