import os
import gradio as gr
from dotenv import load_dotenv
from openai import OpenAI
from prompts.initial_prompt import INITIAL_PROMPT
from prompts.main_prompt import MAIN_PROMPT

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

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
client = OpenAI(api_key=OPENAI_API_KEY)

def gpt_call(history, user_message, model="gpt-4o-mini", max_tokens=1024, temperature=0.7, top_p=0.95):
    messages = [{"role": "system", "content": MAIN_PROMPT}]
    
    for user_text, assistant_text in history:
        if user_text:
            messages.append({"role": "user", "content": user_text})
        if assistant_text:
            messages.append({"role": "assistant", "content": assistant_text})

    messages.append({"role": "user", "content": user_message})
    
    completion = client.chat.completions.create(model=model, messages=messages, max_tokens=max_tokens, temperature=temperature, top_p=top_p)
    
    return completion.choices[0].message.content

def respond(user_message, history):
    if not user_message:
        return "", history

    assistant_reply = gpt_call(history, user_message)
    history.append((user_message, assistant_reply))
    return "", history

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

    chatbot = gr.Chatbot(value=[("", INITIAL_PROMPT)], height=600)
    state_history = gr.State([("", INITIAL_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)