app.py

import os
import openai
from openai import OpenAI
import json
import re
from dotenv import load_dotenv, find_dotenv
import io
import IPython.display
from PIL import Image
import base64
import requests, json
import gradio as gr

requests.adapters.DEFAULT_TIMEOUT = 60

import random

# API Keys
_ = load_dotenv(find_dotenv())  # read local .env file

openai.api_key = os.environ['OPENAI_API_KEY']
client = OpenAI()


def chat(system_prompt, user_prompt, model='gpt-3.5-turbo', temperature=0, verbose=False):
    messages = [
        {"role": "system", "content": system_prompt},
        {"role": "user", "content": user_prompt}
    ]
    completion = client.chat.completions.create(
        model=model,
        temperature=0,
        messages=messages
    )
    ai_response = completion.choices[0].message.content

    if verbose:
        print('User prompt:', user_prompt)
        print('GPT response:', ai_response)

    return ai_response


def respond(message, chat_history):
    # No LLM here, just respond with a random pre-made message
    bot_message = random.choice(["1-Tell me ore about it",
                                 "2-Cool, but I'm not interested",
                                 "3-Hmmmm, ok then"])
    chat_history.append((message, bot_message))
    return "", chat_history


with gr.Blocks() as demo:
    chatbot = gr.Chatbot(height=240)  # just to fit the notebook
    msg = gr.Textbox(label="Prompt")
    btn = gr.Button("Submit")
    clear = gr.ClearButton(components=[msg, chatbot], value="Clear console")

    btn.click(respond, inputs=[msg, chatbot], outputs=[msg, chatbot])
    msg.submit(respond, inputs=[msg, chatbot], outputs=[msg, chatbot])  # Press enter to submit
gr.close_all()
demo.launch(share=True)