app.py

import os
import gradio as gr
import requests
import pandas as pd
import time
import io
import re
from smolagents import LiteLLMModel, tool, CodeAgent

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

# ====================== TOOLS ======================

@tool
def web_search(query: str) -> str:
    """
    Search the web using DuckDuckGo.
    Args:
        query: The search query string.
    """
    try:
        from duckduckgo_search import DDGS
        with DDGS() as ddgs:
            results = list(ddgs.text(query, max_results=5))
            if not results:
                return "No results found."
            return "\n".join([f"{r.get('title')}: {r.get('body')}" for r in results])
    except Exception as e:
        return f"Search failed: {str(e)}"

@tool
def download_and_read_file(task_id: str) -> str:
    """
    Downloads the file for a task and returns its content.
    Args:
        task_id: The unique ID for the task file.
    """
    url = f"{DEFAULT_API_URL}/files/{task_id}"
    try:
        r = requests.get(url, timeout=30)
        r.raise_for_status()
        content_type = r.headers.get("content-type", "").lower()

        if "csv" in content_type or task_id.lower().endswith(".csv"):
            df = pd.read_csv(io.BytesIO(r.content))
            return f"CSV Content (First 15 rows):\n{df.head(15).to_string()}\n\nColumns: {df.columns.tolist()}"
        elif "text" in content_type or task_id.lower().endswith(".txt"):
            return f"Text Content (Snippet):\n{r.text[:2000]}"
        else:
            return (
                f"File downloaded. Size: {len(r.content)} bytes. "
                f"If this is an image/pdf, use web_search to find related facts about task {task_id}."
            )
    except Exception as e:
        return f"Download failed: {str(e)}"

# ====================== AGENT ======================

class GaiaAgent:
    def __init__(self):
        groq_api_key = os.getenv("GROQ_API_KEY")
        if not groq_api_key:
            raise ValueError("❌ GROQ_API_KEY secret is not set! Add it in HF Spaces → Settings → Secrets.")

        # llama-3.3-70b-versatile is the best free model on Groq for reasoning
        self.model = LiteLLMModel(
            model_id="groq/llama-3.3-70b-versatile",
            api_key=groq_api_key,
        )

        self.agent = CodeAgent(
            tools=[web_search, download_and_read_file],
            model=self.model,
            add_base_tools=True,
            max_steps=12,
        )

    def clean_answer(self, raw_result: str) -> str:
        """Removes conversational filler that fails the GAIA grader."""
        text = str(raw_result).strip()
        # Remove common prefixes like "The answer is:"
        text = re.sub(
            r'^(the answer is|final answer|result is|answer)[:\s]*',
            '', text, flags=re.IGNORECASE
        )
        # Strip trailing punctuation
        text = text.strip(".").strip()
        return text

    def __call__(self, question: str, task_id: str) -> str:
        prompt = f"""Task ID: {task_id}
Question: {question}

INSTRUCTIONS:
- Use your tools to find the exact factual answer.
- If the question mentions a file or attachment, call download_and_read_file("{task_id}") first.
- If you need up-to-date facts, use web_search.
- YOUR FINAL ANSWER MUST BE EXTREMELY BRIEF AND EXACT:
  * Numbers: just the number, e.g. '42' or '4.52'
  * Names: just the name, e.g. 'Marie Curie'
  * Dates: just the date, e.g. '1923' or 'July 4, 1776'
  * Lists: comma-separated, e.g. 'apple, banana, cherry'
- Do NOT write sentences. Do NOT explain. Just the answer.
"""
        try:
            result = self.agent.run(prompt)
            return self.clean_answer(str(result))
        except Exception as e:
            print(f"Agent error on task {task_id}: {e}")
            return "Unknown"

# ====================== MAIN LOGIC ======================

def run_and_submit_all(profile: gr.OAuthProfile | None):
    if not profile:
        return "❌ Please Login with Hugging Face first!", None

    username = profile.username
    print(f"✅ Logged in as: {username}")

    try:
        agent = GaiaAgent()
    except ValueError as e:
        return str(e), None

    try:
        resp = requests.get(f"{DEFAULT_API_URL}/questions", timeout=30)
        resp.raise_for_status()
        questions = resp.json()
    except Exception as e:
        return f"❌ Failed to fetch questions: {e}", None

    print(f"📋 Fetched {len(questions)} questions.")

    answers_payload = []
    results_log = []

    for i, item in enumerate(questions):
        t_id = item.get("task_id")
        q_text = item.get("question")

        print(f"\n--- [{i+1}/{len(questions)}] Task: {t_id} ---")
        print(f"Q: {q_text[:120]}...")

        answer = agent(q_text, t_id)
        print(f"A: {answer}")

        answers_payload.append({"task_id": t_id, "submitted_answer": str(answer)})
        results_log.append({"Task ID": t_id, "Question": q_text[:80], "Answer": str(answer)})

        # Small sleep — Groq free tier allows ~30 req/min, no need for 38s waits
        time.sleep(3)

    # ===== SUBMIT =====
    space_id = os.getenv("SPACE_ID", "unknown")
    submission_data = {
        "username": username,
        "agent_code": f"https://huggingface.co/spaces/{space_id}",
        "answers": answers_payload,
    }

    try:
        r = requests.post(f"{DEFAULT_API_URL}/submit", json=submission_data, timeout=300)
        if r.status_code == 200:
            res = r.json()
            score = res.get("score", 0)
            message = res.get("message", "")
            return f"✅ SCORE: {score}% | {message}", pd.DataFrame(results_log)
        else:
            return f"❌ Submission Error {r.status_code}: {r.text}", pd.DataFrame(results_log)
    except Exception as e:
        return f"❌ Submission Failed: {str(e)}", pd.DataFrame(results_log)

# ====================== UI ======================

with gr.Blocks(theme=gr.themes.Default()) as demo:
    gr.Markdown("# 🏆 GAIA Certificate Agent (Unit 4 Final)")
    gr.Markdown(
        "**Steps:** 1) Login with HF below → 2) Click Start → 3) Wait ~5 mins → 4) Check your score!\n\n"
        "> Make sure `GROQ_API_KEY` is set in your Space **Settings → Secrets**."
    )

    with gr.Row():
        gr.LoginButton()
        run_btn = gr.Button("🚀 Start Evaluation", variant="primary")

    status_output = gr.Textbox(label="Final Result", lines=3)
    table_output = gr.DataFrame(label="Answer Log")

    run_btn.click(fn=run_and_submit_all, outputs=[status_output, table_output])

if __name__ == "__main__":
    demo.launch()