app.py

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
from fastapi import FastAPI

# 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)

# ✅ Create FastAPI app
app = FastAPI()

# ✅ API Endpoints to Serve Prompts
@app.get("/initial_prompt")
def get_initial_prompt():
    return {"prompt": INITIAL_PROMPT}

@app.get("/main_prompt")
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

with gr.Blocks() as demo:
    gr.Markdown("## Simple Chat Interface")

    chatbot = gr.Chatbot(
        value=[("", INITIAL_PROMPT)],  
        height=500
    )

    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]
    )

# ✅ Launch Gradio and FastAPI together
import threading

def run_gradio():
    demo.launch(server_name="0.0.0.0", server_port=7860, share=True)

threading.Thread(target=run_gradio).start()