import os
import requests
import pandas as pd
import gradio as gr

from smolagents import ToolCallingAgent, OpenAIServerModel
from audio_transcriber import AudioTranscriptionTool
from image_analyzer import ImageAnalysisTool
from wikipedia_searcher import WikipediaSearcher

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

class GaiaAgent:
    def __init__(self):
        tools = [
            AudioTranscriptionTool(),
            ImageAnalysisTool(),
            WikipediaSearcher()
        ]

        model_id = os.getenv("OPENAI_MODEL_ID", "gpt-3.5-turbo")
        self.agent = ToolCallingAgent(
            model=OpenAIServerModel(model_id=model_id),
            tools=tools
        )

    def __call__(self, query: str) -> str:
        result = self.agent.run(query)
        return result.get("output", "No output returned")

def run_and_submit_all(profile: gr.OAuthProfile | None):
    space_id = os.getenv("SPACE_ID")

    if profile:
        username = profile.username
        if isinstance(username, list):
            username = username[0]
        username = username.strip()
        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:
        print(f"Error initializing agent: {e}")
        return f"Error initializing agent: {e}", None

    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
    print(f"Agent code URL: {agent_code}")

    try:
        response = requests.get(questions_url, timeout=15)
        response.raise_for_status()
        questions_data = response.json()
        if not questions_data:
            return "Fetched questions list is empty or invalid format.", None
        print(f"Fetched {len(questions_data)} questions.")
    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")
        if not task_id:
            continue

        question_text = item.get("question", "")

        file_url = item.get("file_url")
        local_file_path = None
        if file_url:
            try:
                ext = file_url.split(".")[-1].lower()
                if ext in ["mp3", "wav", "jpeg", "jpg", "png"]:
                    local_file_path = f"./temp_{task_id}.{ext}"
                    with requests.get(file_url, stream=True) as r:
                        r.raise_for_status()
                        with open(local_file_path, "wb") as f:
                            for chunk in r.iter_content(chunk_size=8192):
                                f.write(chunk)
                    print(f"Downloaded file for task {task_id} to {local_file_path}")
                    question_text += f"\n\nFile path: {local_file_path}"
            except Exception as e:
                print(f"Failed to download file for task {task_id}: {e}")

        try:
            submitted_answer = agent(question_text)
            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:
            error_msg = f"AGENT ERROR: {e}"
            results_log.append({
                "Task ID": task_id,
                "Question": question_text,
                "Submitted Answer": error_msg
            })

        if local_file_path:
            try:
                os.remove(local_file_path)
            except Exception:
                pass

    if not answers_payload:
        return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)

    submission_data = {
        "username": username,
        "agent_code": agent_code,
        "answers": answers_payload
    }

    print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
    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.')}"
        )
        results_df = pd.DataFrame(results_log)
        return final_status, results_df
    except requests.exceptions.HTTPError as e:
        try:
            detail = e.response.json().get("detail", e.response.text)
        except Exception:
            detail = e.response.text[:500]
        return f"Submission Failed: {detail}", pd.DataFrame(results_log)
    except requests.exceptions.Timeout:
        return "Submission Failed: The request timed out.", pd.DataFrame(results_log)
    except Exception as e:
        return f"An unexpected error occurred during submission: {e}", pd.DataFrame(results_log)


# Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("# Basic Agent Evaluation Runner")
    gr.Markdown("""
        **Instructions:**
        1. Clone this space and define your agent and tools.
        2. Log in to your Hugging Face account using the button below.
        3. Click 'Run Evaluation & Submit All Answers' to test your agent and submit results.
    """)

    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("\n" + "-"*30 + " App Starting " + "-"*30)
    space_host = os.getenv("SPACE_HOST")
    space_id = os.getenv("SPACE_ID")

    if space_host:
        print(f"✅ SPACE_HOST found: {space_host}")
        print(f"   Runtime URL should be: https://{space_host}.hf.space")
    else:
        print("ℹ️  SPACE_HOST not found.")

    if space_id:
        print(f"✅ SPACE_ID found: {space_id}")
        print(f"   Repo URL: https://huggingface.co/spaces/{space_id}")
    else:
        print("ℹ️  SPACE_ID not found.")

    print("-"*(60 + len(" App Starting ")) + "\n")
    demo.launch(debug=True, share=False)