app.py

""" Basic Agent Evaluation Runner"""
import os
import inspect
import gradio as gr
import requests
import pandas as pd
import time
from langchain_core.messages import HumanMessage
from agent import build_graph
import re


# (Keep Constants as is)
# --- Constants ---
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"

# --- Basic Agent Definition ---
# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------


cached_answers = []

def parse_final_answer(raw: str) -> str:
    raw = raw.strip()
    if "FINAL ANSWER:" in raw:
        return raw.split("FINAL ANSWER:")[-1].strip()
    return raw.split("Final Answer:")[-1].strip() if "Final Answer:" in raw else raw

class BasicAgent:
    def __init__(self):
        self.graph = build_graph()

    def __call__(self, question: str) -> str:
        messages = [HumanMessage(content=question)]
        output = self.graph.invoke({"messages": messages})
        return parse_final_answer(output['messages'][-1].content)

def run_agent_only(profile: gr.OAuthProfile | None):
    global cached_answers
    cached_answers = []
    results_log = []

    if not profile:
        return "Please login first.", None

    try:
        agent = BasicAgent()
    except Exception as e:
        return f"Agent Init Error: {e}", None

    try:
        questions = requests.get("https://agents-course-unit4-scoring.hf.space/questions", timeout=15).json()
    except Exception as e:
        return f"Error fetching questions: {e}", None

    with open("system_prompt.txt", "r") as f:
        system_prompt = f.read().strip()

    for item in questions:
        task_id = item.get("task_id")
        question = item.get("question")
        file_name = item.get("file_name")

        if not task_id or not question:
            continue

        try:
            user_message = question + (f"\n\nFile to use: {file_name}" if file_name else "")
            answer = agent(system_prompt + "\n\n" + user_message)
            cached_answers.append({"task_id": task_id, "submitted_answer": answer})
            results_log.append({"Task ID": task_id, "Question": question, "Submitted Answer": answer})
        except Exception as e:
            results_log.append({"Task ID": task_id, "Question": question, "Submitted Answer": f"AGENT ERROR: {e}"})

    return "Agent finished. Click 'Submit Cached Answers' next.", pd.DataFrame(results_log)

def submit_cached_answers(profile: gr.OAuthProfile | None):
    if not profile or not cached_answers:
        return "Nothing to submit. Run the agent first.", None

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

    try:
        response = requests.post("https://agents-course-unit4-scoring.hf.space/submit", json=payload, timeout=60)
        result = response.json()
        score = result.get("score", "?")
        correct = result.get("correct_count", "?")
        total = result.get("total_attempted", "?")
        return f"Submission complete. Score: {score}% ({correct}/{total})", None
    except Exception as e:
        return f"Submission failed: {e}", None

with gr.Blocks() as demo:
    gr.Markdown("""# Agent Evaluator
1. Login with Hugging Face
2. Run agent only
3. Submit answers""")

    gr.LoginButton()
    run_button = gr.Button("Run Agent")
    submit_button = gr.Button("Submit Cached Answers")
    status_box = gr.Textbox(label="Status", lines=4)
    table = gr.DataFrame(label="Answers Log")

    run_button.click(fn=run_agent_only, outputs=[status_box, table])
    submit_button.click(fn=submit_cached_answers, outputs=[status_box, table]))

if __name__ == "__main__":
    print("\n" + "-"*30 + " App Starting " + "-"*30)
    space_host_startup = os.getenv("SPACE_HOST")
    space_id_startup = os.getenv("SPACE_ID")

    if space_host_startup:
        print(f"✅ SPACE_HOST found: {space_host_startup}")
        print(f"   Runtime URL: https://{space_host_startup}.hf.space")
    else:
        print("ℹ️  No SPACE_HOST found.")

    if space_id_startup:
        print(f"✅ SPACE_ID found: {space_id_startup}")
        print(f"   Repo URL: https://huggingface.co/spaces/{space_id_startup}")
    else:
        print("ℹ️  No SPACE_ID found.")

    print("Launching Gradio Interface...")
    demo.launch(debug=True, share=False)