import os
import gradio as gr
import requests
import pandas as pd
from smolagents import CodeAgent, DuckDuckGoSearchTool
from smolagents.models import OpenAIServerModel
import openai

# --- Setup ---
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
if not OPENAI_API_KEY:
    raise RuntimeError("Please set OPENAI_API_KEY in your Space secrets.")
openai.api_key = OPENAI_API_KEY

DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
OPENAI_MODEL_ID = os.getenv("OPENAI_MODEL_ID", "gpt-4o")

model = OpenAIServerModel(model_id=OPENAI_MODEL_ID, api_key=OPENAI_API_KEY)
search_tool = DuckDuckGoSearchTool()
agent = CodeAgent(tools=[search_tool], model=model)

answer_formatting_prompt = """
You are a smart assistant with access to tools like DuckDuckGoSearchTool(query: str). 
Think step-by-step, then output your response.

IMPORTANT: 
FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers/strings. 
Do NOT include commas, $ or % unless asked.
Write digits plainly (e.g., '10', not 'ten').

Use format:
FINAL ANSWER: <your_answer>
"""

def show_profile(profile):
    if not profile:
        return "⚠️ Not logged in."
    return f"✅ Logged in as: {profile['username']}"

def run_and_submit_all(login_info):
    # login_info comes from LoginButton, it's None if not logged in
    if not login_info:
        return "⚠️ Please log in with your Hugging Face account.", pd.DataFrame()

    username = login_info["username"]
    space_id = os.getenv("SPACE_ID", "")
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"

    try:
        resp = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
        resp.raise_for_status()
        questions = resp.json()
    except Exception as e:
        return f"❌ Error fetching questions: {e}", pd.DataFrame()

    results, payload = [], []
    for item in questions:
        task_id = item.get("task_id")
        question = item.get("question")
        if not task_id or not question:
            continue
        prompt = answer_formatting_prompt.strip() + f"\n\nQUESTION: {question.strip()}"
        try:
            answer = agent.run(prompt)
        except Exception as e:
            answer = f"AGENT ERROR: {e}"
        results.append({"Task ID": task_id, "Question": question, "Submitted Answer": answer})
        payload.append({"task_id": task_id, "submitted_answer": answer})

    if not payload:
        return "⚠️ Agent returned no answers.", pd.DataFrame(results)

    try:
        post = requests.post(
            f"{DEFAULT_API_URL}/submit",
            json={"username": username, "agent_code": agent_code, "answers": payload},
            timeout=60
        )
        post.raise_for_status()
        result = post.json()
        score = result.get("score", "N/A")
        correct = result.get("correct_count", "?")
        attempted = result.get("total_attempted", "?")
        message = result.get("message", "")
        return (
            f"✅ Submission Successful!\nUser: {username}\nScore: {score}% "
            f"({correct}/{attempted})\nMessage: {message}",
            pd.DataFrame(results)
        )
    except Exception as e:
        return f"❌ Submission failed: {e}", pd.DataFrame(results)


with gr.Blocks() as demo:
    gr.Markdown("# Basic Agent Evaluation Runner")

    login_button = gr.LoginButton()
    login_status = gr.Textbox(label="Login Status")

    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)

    # Show login status when user logs in
    login_button.click(fn=show_profile, inputs=[login_button], outputs=[login_status])

    # Run evaluation on click, pass login_button's state as input
    run_button.click(fn=run_and_submit_all, inputs=[login_button], outputs=[status_output, results_table])


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


#import gradio as gr

#def show_profile(profile):
 #   if not profile:
   #     return "⚠️ Not logged in."
  #  return f"✅ Logged in as: {profile['username']}"

 # with gr.Blocks() as demo:
   #   gr.Markdown("## 🔐 Hugging Face OAuth Login")

   #   login_button = gr.LoginButton()
   #   output = gr.Textbox(label="Login Status")

    #  login_button.click(fn=show_profile, inputs=[login_button], outputs=[output])

 # demo.launch()