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import os
import gradio as gr
from dotenv import load_dotenv
from openai import OpenAI
from prompts.main_prompt import MAIN_PROMPT  # Ensure this file exists and is fixed

# Load API key from .env file
if os.path.exists(".env"):
    load_dotenv(".env")

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")

if not OPENAI_API_KEY:
    raise ValueError("OpenAI API key is missing! Set it in the .env file.")

client = OpenAI(api_key=OPENAI_API_KEY)

# Chatbot Response Function
def respond(user_message, history):
    if not user_message:
        return "", history

    try:
        assistant_reply = client.chat.completions.create(
            model="gpt-4o",
            messages=[
                {"role": "system", "content": MAIN_PROMPT},
                *[
                    {"role": "user", "content": u} if i % 2 == 0 else {"role": "assistant", "content": a}
                    for i, (u, a) in enumerate(history)
                ],
                {"role": "user", "content": user_message}
            ],
            max_tokens=512,
            temperature=0.7,
        ).choices[0].message.content

        history.append((user_message, assistant_reply))

        return "", history

    except Exception as e:
        return f"An error occurred: {str(e)}", history

# Gradio UI Setup
with gr.Blocks() as demo:
    gr.Markdown("## AI-Guided Math PD Chatbot")

    chatbot = gr.Chatbot(value=[(MAIN_PROMPT, "")], height=500) 
    state_history = gr.State([(MAIN_PROMPT, "")]) 

    user_input = gr.Textbox(placeholder="Type your message here...", label="Your Input")

    user_input.submit(
        respond,
        inputs=[user_input, state_history],
        outputs=[user_input, chatbot]
    ).then(
        fn=lambda _, h: h,
        inputs=[user_input, chatbot],
        outputs=[state_history]
    )

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860, share=True)