app.py

import os
import time
import gradio as gr
import requests
import pandas as pd
import tiktoken  # For token length

from smolagents import CodeAgent, OpenAIServerModel
from smolagents.tools import code_tools  # Includes WebSearchTool and more

# Constants
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
MAX_TOKENS = 3000  # Limit to avoid GPT-4 token overflow

# Token counting helper
def token_length(text: str, model: str = "gpt-4") -> int:
    try:
        encoding = tiktoken.encoding_for_model(model)
        return len(encoding.encode(text))
    except Exception:
        return len(text) // 4  # fallback estimate

# Main agent class
class SmartGAIAAgent:
    def __init__(self):
        key = os.getenv("OPENAI_API_KEY")
        if not key:
            raise ValueError("Missing OPENAI_API_KEY")
        model = OpenAIServerModel(model_id="gpt-4", api_key=key)
        self.agent = CodeAgent(
            tools=code_tools(),  # Includes WebSearchTool, Code Interpreter, etc.
            model=model
        )

    def __call__(self, question: str) -> str:
        try:
            return self.agent.run(question).strip()
        except Exception as e:
            print("Agent error:", e)
            return "error"

# Run agent + submit answers to API
def run_and_submit_all(profile: gr.OAuthProfile | None):
    username = profile.username if profile else None
    if not username:
        return "Please login to Hugging Face", None

    try:
        agent = SmartGAIAAgent()
    except Exception as e:
        return f"Error initializing agent: {e}", None

    # Fetch questions
    try:
        resp = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
        resp.raise_for_status()
        questions = resp.json()
    except Exception as e:
        return f"Failed to fetch questions: {e}", None

    skip_kw = ['.mp3', '.wav', '.png', '.jpg', 'youtube', 'video', 'watch', 'listen']
    payload, logs = [], []

    for item in questions:
        tid = item.get("task_id")
        q = item.get("question", "")
        if not tid or not q:
            continue
        if token_length(q) > MAX_TOKENS or any(k in q.lower() for k in skip_kw):
            continue

        try:
            ans = agent(q)
        except Exception as e:
            print(f"[Error Task {tid}] {e}")
            ans = "error"

        payload.append({"task_id": tid, "submitted_answer": ans})
        logs.append({"Task ID": tid, "Question": q, "Submitted Answer": ans})

    if not payload:
        return "No valid questions to submit.", pd.DataFrame(logs)

    sub = {
        "username": username,
        "agent_code": f"https://huggingface.co/spaces/{os.getenv('SPACE_ID')}/tree/main",
        "answers": payload
    }

    try:
        resp = requests.post(f"{DEFAULT_API_URL}/submit", json=sub, timeout=60)
        resp.raise_for_status()
        result = resp.json()
        score = result.get("score")
        correct = result.get("correct_count")
        attempted = result.get("total_attempted")
        status = f"Score: {score}% ({correct}/{attempted})"
    except Exception as e:
        status = f"Submission failed: {e}"

    return status, pd.DataFrame(logs)

# Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("# GAIA Agent")
    gr.LoginButton()
    run_btn = gr.Button("Run & Submit")
    status = gr.Textbox(lines=4, label="Result")
    table = gr.DataFrame()
    run_btn.click(run_and_submit_all, outputs=[status, table])

if __name__ == "__main__":
    demo.launch(debug=True, share=False)