import os, threading
import gradio as gr
from crew import run_crew
from utils import get_questions

def ask(question, openai_api_key, gemini_api_key, anthropic_api_key, file_name = ""):
    """
    Ask General AI Assistant a question to answer.

    Args:
        question (str): The question to answer
        openai_api_key (str): OpenAI API key
        gemini_api_key (str): Gemini API key
        anthropic_api_key (str): Anthropic API key
        file_name (str): Optional file name

    Returns:
        str: The answer to the question
    """
    if not question:
        raise gr.Error("Question is required.")

    if not openai_api_key:
        raise gr.Error("OpenAI API Key is required.")
    
    if not gemini_api_key:
        raise gr.Error("Gemini API Key is required.")

    if not anthropic_api_key:
        raise gr.Error("Anthropic API Key is required.")
        
    if file_name:
        file_name = f"data/{file_name}"
    
    lock = threading.Lock()

    with lock:
        answer = ""

        try:
            os.environ["OPENAI_API_KEY"] = openai_api_key
            os.environ["GEMINI_API_KEY"] = gemini_api_key
            os.environ["MODEL_API_KEY"] = anthropic_api_key
            
            answer = run_crew(question, file_name)
        except Exception as e:
            raise gr.Error(e)
        finally:
            del os.environ["OPENAI_API_KEY"]
            del os.environ["GEMINI_API_KEY"]
            del os.environ["MODEL_API_KEY"]
        
        return answer

gr.close_all()

with gr.Blocks() as grady:
    gr.Markdown("## Grady - General AI Assistant")

    with gr.Tab("Solution"):
        gr.Markdown(os.environ.get("DESCRIPTION"))

        with gr.Row():
            with gr.Column(scale=3):
                with gr.Row():
                    question = gr.Textbox(
                        label="Question *",
                        placeholder="In the 2025 Gradio Agents & MCP Hackathon, what percentage of participants submitted a solution during the last 24 hours?",
                        interactive=True
                    )
                with gr.Row():
                    level = gr.Radio(
                        choices=[1, 2, 3],
                        label="GAIA Benchmark Level",
                        interactive=True,
                        scale=1
                    )
                    ground_truth = gr.Textbox(
                        label="Ground Truth",
                        interactive=True,
                        scale=1
                    )
                    file_name = gr.Textbox(
                        label="File Name",
                        interactive=True,
                        scale=2
                    )
                with gr.Row():
                    openai_api_key = gr.Textbox(
                        label="OpenAI API Key *",
                        type="password",
                        placeholder="sk‑...",
                        interactive=True
                    )
                    gemini_api_key = gr.Textbox(
                        label="Gemini API Key *",
                        type="password",
                        interactive=True
                    )
                    anthropic_api_key = gr.Textbox(
                        label="Anthropic API Key *",
                        type="password",
                        placeholder="sk-ant-...",
                        interactive=True
                    )
                with gr.Row():
                    clear_btn = gr.ClearButton(
                        components=[question, level, ground_truth, file_name]
                    )
                    submit_btn = gr.Button("Submit", variant="primary")
            with gr.Column(scale=1):
                answer = gr.Textbox(
                    label="Answer",
                    lines=1,
                    interactive=False
                )
    
        submit_btn.click(
            fn=ask,
            inputs=[question, openai_api_key, gemini_api_key, anthropic_api_key, file_name],
            outputs=answer
        )
    
        QUESTION_FILE_PATH = "data/gaia_validation.jsonl"
        
        gr.Examples(
            label="GAIA Benchmark Level 1 Problems",
            examples=get_questions(QUESTION_FILE_PATH, 1),
            inputs=[question, level, ground_truth, file_name, openai_api_key, gemini_api_key, anthropic_api_key],
            outputs=answer,
            cache_examples=False
        )
    
        gr.Examples(
            label="GAIA Benchmark Level 2 Problems",
            examples=get_questions(QUESTION_FILE_PATH, 2),
            inputs=[question, level, ground_truth, file_name, openai_api_key, gemini_api_key, anthropic_api_key],
            outputs=answer,
            cache_examples=False
        )
    
        gr.Examples(
            label="GAIA Benchmark Level 3 Problems",
            examples=get_questions(QUESTION_FILE_PATH, 3),
            inputs=[question, level, ground_truth, file_name, openai_api_key, gemini_api_key, anthropic_api_key],
            outputs=answer,
            cache_examples=False
        )
    with gr.Tab("Documentation"):
        gr.Markdown(os.environ.get("DOCUMENTATION"))

grady.launch(mcp_server=True)