app.py

import subprocess
subprocess.check_call(["pip", "install", "openai"])
subprocess.check_call(["pip", "install", "gradio", "transformers", "python-dotenv","torch"])
import torch
import random
import gradio as gr
from transformers import TFAutoModelForCausalLM, AutoTokenizer
import openai
from dotenv import load_dotenv
import os

load_dotenv() # load environment variables from .env file
api_key = os.getenv("OPENAI_API_KEY") # access the value of the OPENAI_API_KEY environment variable
'''
def openai_chat(prompt):
    if "who are you" in prompt.lower() or "your name" in prompt.lower() or "name" in prompt.lower():
        return "My name is ChatSherman. How can I assist you today?"
    else:
        prompt = "I'm an AI chatbot named ChatSherman designed by a super intelligent student named ShermanAI at the Department of Electronic and Information Engineering at the Hong Kong Polytechnic University to help you with your engineering questions. Also, I can assist with a wide range of topics and questions." + prompt
        completions = openai.Completion.create(engine="text-davinci-003", prompt=prompt, max_tokens=10000, n=1, temperature=0.5,)
        message = completions.choices[0].text
        return message.strip()
'''
def getresponse(message, history):            
    system_prompt = "I'm an AI chatbot named ChatSherman designed by a super intelligent student named ShermanAI at the Department of Electronic and Information Engineering at the Hong Kong Polytechnic University to help you with your engineering questions. Also, I can assist with a wide range of topics and questions."

    messages = [{"role":"system","content":system_prompt}]
    for human, assistant in history:
        messages.append({"role":"user", "content":human})
        messages.append({"role":"assistant", "content":assistant})

    if message != '':
        messages.append({"role":"user", "content":message})
    
    response = openai.ChatCompletion.create(engine = "text-davinci-003",
    messages = messages, 
    temperature =0.5,
    max_tokens = 10000,
    top_p = 0.95,
    frequency_penalty = 1,
    presence_penalty = 1,
    stop = None)
    
    return response["choices"][0]["message"]["content"]



title = "ChatSherman"
description = "This is an AI chatbot powered by ShermanAI. Enter your question below to get started."
examples = [
    ["What is ChatSherman, and how does it work?"],
    ["Is my personal information and data safe when I use the ChatSherman chatbot?"],
    ["What are some common applications of deep learning in engineering?"]
]

gr.Interface(getresponse, title=title, description=description, examples=examples).launch() # ChatInterface