import gradio as gr
import openai
from fastapi import FastAPI, Request
import uvicorn
import json

openai.api_key = ""

app = FastAPI()
conversation_history = []

@app.post("/chat")
async def chat(request: Request):
    global conversation_history
    message = await request.json()

    # Convert the user's message to JSON
    message_json = json.dumps(message)
    conversation_history.append({"role": "user", "content": message_json})

    # Prepare the messages for the GPT-3 API call
    messages = conversation_history.copy()
    # Add a system message to instruct the model
    messages.insert(0, {"role": "system", "content": "You are a story writer. What ever the prompt you always write a story"})

    completion = openai.ChatCompletion.create(
        model="gpt-4",
        messages=messages
    )
    reply = completion.choices[0].message.content

    # Append the model's reply to the conversation history
    conversation_history.append({"role": "assistant", "content": reply})

    return reply

def gradio_chat(message):
    reply = chat(message)
    return reply

with gr.ChatInterface(fn=gradio_chat) as chatbot:
    chatbot.launch(server_name="0.0.0.0", server_port=7860)

# Run the FastAPI app
if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=7860)