Spaces:
Sleeping
Sleeping
File size: 3,022 Bytes
a64869d 3745377 273daa5 fee4a07 273daa5 36694ba 273daa5 36694ba efec88a 273daa5 a64869d 23345a5 8f69443 a64869d |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
'''
import subprocess
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="text-davinci-003", prompt=prompt, max_tokens=1024, n=1, temperature=0.5,)
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)
'''
python -m pip install --upgrade pip
import subprocess
subprocess.check_call(["pip", "install", "-q", "openai"])
subprocess.check_call(["pip", "install", "-q", "gradio", "transformers", "python-dotenv"])
import openai
import gradio as gr
openai.api_key = "OPENAI_API_KEY"
def predict(message, history):
history_openai_format = []
for human, assistant in history:
history_openai_format.append({"role": "user", "content": human })
history_openai_format.append({"role": "assistant", "content":assistant})
history_openai_format.append({"role": "user", "content": message})
response = openai.ChatCompletion.create(
model='gpt-3.5-turbo',
messages= history_openai_format,
temperature=1.0,
stream=True
)
partial_message = ""
for chunk in response:
if len(chunk['choices'][0]['delta']) != 0:
partial_message = partial_message + chunk['choices'][0]['delta']['content']
yield partial_message
gr.ChatInterface(predict).queue().launch() |