import os import gradio as gr import requests import pandas as pd from smolagents import CodeAgent, DuckDuckGoSearchTool, OpenAIServerModel # --- Constants --- DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space" # --- Enhanced Agent Definition --- class GAIAAgent: def __init__(self): print("GAIAAgent initialized.") model = OpenAIServerModel(model_id="gpt-4o") search_tool = DuckDuckGoSearchTool() self.agent = CodeAgent(model=model, tools=[search_tool]) def format_prompt(self, question: str, file_content: str = None) -> str: prompt = ( "You are a helpful AI agent solving a question from the GAIA benchmark. " "Respond only with the final answer." ) if file_content: prompt += f"\nAttached File Content:\n{file_content}\n" prompt += f"\nQuestion: {question}\nAnswer:" return prompt def read_file(self, filename: str) -> str: filepath = os.path.join("./", filename) if filename.endswith(".txt") and os.path.exists(filepath): with open(filepath, "r") as file: return file.read()[:1000] # limit to 1000 chars return "" def __call__(self, question: str, file_name: str = None) -> str: file_content = self.read_file(file_name) if file_name else None prompt = self.format_prompt(question, file_content) result = self.agent.run(prompt) return result.strip() 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: print("User not logged in.") return "Please Login to Hugging Face with the button.", None api_url = DEFAULT_API_URL questions_url = f"{api_url}/questions" submit_url = f"{api_url}/submit" try: agent = GAIAAgent() except Exception as e: return f"Error initializing agent: {e}", None agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" try: response = requests.get(questions_url, timeout=15) response.raise_for_status() questions_data = response.json() 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") file_name = item.get("file_name") if not task_id or question_text is None: continue try: submitted_answer = agent(question_text, file_name) 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"AGENT ERROR: {e}"}) if not answers_payload: return "Agent did not produce any answers to submit.", pd.DataFrame(results_log) submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload} try: response = requests.post(submit_url, json=submission_data, timeout=60) response.raise_for_status() result_data = response.json() final_status = ( f"Submission Successful!\n" f"User: {result_data.get('username')}\n" f"Overall Score: {result_data.get('score', 'N/A')}% " f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n" f"Message: {result_data.get('message', 'No message received.')}" ) return final_status, pd.DataFrame(results_log) except Exception as e: return f"Submission Failed: {e}", pd.DataFrame(results_log) with gr.Blocks() as demo: gr.Markdown("# GAIA Agent Evaluation Runner") gr.Markdown(""" **Instructions:** 1. Log in to your Hugging Face account. 2. Click the button to run the agent and submit answers. 3. Your score will be printed below. """) gr.LoginButton() run_button = gr.Button("Run Evaluation & Submit All Answers") status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False) results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True) run_button.click( fn=run_and_submit_all, outputs=[status_output, results_table] ) if __name__ == "__main__": print("Launching GAIA agent app...") demo.launch(debug=True, share=False)