app.py

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

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

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")

client = OpenAI(api_key=OPENAI_API_KEY)

# ✅ FastAPI App for Serving Prompts
fastapi_app = FastAPI()

@fastapi_app.get("/initial_prompt")
async def get_initial_prompt():
    return {"prompt": INITIAL_PROMPT}

@fastapi_app.get("/main_prompt")
async def get_main_prompt():
    return {"prompt": MAIN_PROMPT}

# ✅ Chatbot Function
def gpt_call(history, user_message,
             model="gpt-4o-mini",
             max_tokens=512,
             temperature=0.7,
             top_p=0.95):
    """
    OpenAI ChatCompletion API call
    """
    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

# ✅ Gradio Chatbot UI
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

# ✅ Gradio UI
def launch_gradio():
    with gr.Blocks() as gradio_app:
        gr.Markdown("## Simple Chat Interface")

        chatbot = gr.Chatbot(
            value=[{"role": "assistant", "content": INITIAL_PROMPT}],
            height=500,
            type="messages"
        )

        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]
        )

    gradio_app.launch(server_name="0.0.0.0", server_port=7860, show_error=True, enable_queue=True)

# ✅ Run FastAPI and Gradio Separately
if __name__ == "__main__":
    threading.Thread(target=launch_gradio, daemon=True).start()
    uvicorn.run(fastapi_app, host="0.0.0.0", port=8000)