import subprocess subprocess.check_call(["pip", "install", "--upgrade", "gradio"]) subprocess.check_call(["pip", "install", "-q", "openai"]) subprocess.check_call(["pip", "install", "-q", "gradio", "transformers", "python-dotenv"]) 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 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="gpt-3.5-turbo-0613", prompt=prompt, max_tokens=4096, n=1, temperature=0.5,) #'gpt-3.5-davinc-turbo-0613',texti-003, gpt-3.5-turbo, gpt-3.5-turbo-0301 message = completions.choices[0].text return message.strip() def chatbot(talk_to_chatsherman, history=[]): output = openai_chat(talk_to_chatsherman) history.append((talk_to_chatsherman, output)) return history, history 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?", []] ] inputs = [gr.inputs.Textbox(label="Talk to ChatSherman: "), "state"] outputs = ["chatbot", "state"] interface = gr.Interface(fn=chatbot, inputs=inputs, outputs=outputs, title=title, description=description, examples=examples) interface.launch(debug=True)