app.py

import os
import gradio as gr
import requests
import inspect
import pandas as pd
from smolagents import HfApiModel


# --- Constants ---
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"

# --- Enhanced Agent Definition ---
class GAIAAgent:
    def __init__(self):
        print("GAIAAgent with HfApiModel initialized.")
        self.model = gr.load(
           "models/deepseek-ai/DeepSeek-R1",
           provider="novita",
        )

    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)
        try:
            print("Prompt sent to model:", prompt)
            result = self.model(prompt)
            print("Model raw result:", result)
            if not result or not isinstance(result, str):
                return "AGENT ERROR: Empty or invalid response"
            return result.strip().split("Answer:")[-1].strip()
        except Exception as e:
            print(f"Model inference failed: {e}")
            return f"AGENT ERROR: {e}"


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)