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# -*- coding: utf-8 -*-
"""
@author:XuMing([email protected])
@description:
"""
import gradio as gr
import os
import json
import requests
from loguru import logger
from dotenv import load_dotenv
logger.add('gradio_server.log', rotation='10 MB', encoding='utf-8', level='DEBUG')
def get_api_key():
api_key = ''
if os.path.isfile('.env'):
load_dotenv()
if os.environ.get('API_KEY') is not None:
api_key = os.environ.get('API_KEY')
return api_key
def set_new_api_key(api_key):
# Write the api key to the .env file
with open('.env', 'w') as f:
f.write(f'API_KEY={api_key}')
# Streaming endpoint for OPENAI ChatGPT
API_URL = "https://api.openai.com/v1/chat/completions"
# Predict function for CHATGPT
def predict_chatgpt(inputs, top_p_chatgpt, temperature_chatgpt, openai_api_key, chat_counter_chatgpt,
chatbot_chatgpt=[], history=[]):
# Define payload and header for chatgpt API
payload = {
"model": "gpt-3.5-turbo",
"messages": [{"role": "user", "content": f"{inputs}"}],
"temperature": 1.0,
"top_p": 1.0,
"n": 1,
"stream": True,
"presence_penalty": 0,
"frequency_penalty": 0,
}
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {openai_api_key}"
}
# Handling the different roles for ChatGPT
if chat_counter_chatgpt != 0:
messages = []
for data in chatbot_chatgpt:
temp1 = {}
temp1["role"] = "user"
temp1["content"] = data[0]
temp2 = {}
temp2["role"] = "assistant"
temp2["content"] = data[1]
messages.append(temp1)
messages.append(temp2)
temp3 = {}
temp3["role"] = "user"
temp3["content"] = inputs
messages.append(temp3)
payload = {
"model": "gpt-3.5-turbo",
"messages": messages, # [{"role": "user", "content": f"{inputs}"}],
"temperature": temperature_chatgpt, # 1.0,
"top_p": top_p_chatgpt, # 1.0,
"n": 1,
"stream": True,
"presence_penalty": 0,
"frequency_penalty": 0,
}
chat_counter_chatgpt += 1
history.append(inputs)
# make a POST request to the API endpoint using the requests.post method, passing in stream=True
response = requests.post(API_URL, headers=headers, json=payload, stream=True)
token_counter = 0
partial_words = ""
counter = 0
for chunk in response.iter_lines():
# Skipping the first chunk
if counter == 0:
counter += 1
continue
# check whether each line is non-empty
if chunk.decode():
chunk = chunk.decode()
# decode each line as response data is in bytes
if len(chunk) > 13 and "content" in json.loads(chunk[6:])['choices'][0]["delta"]:
partial_words = partial_words + json.loads(chunk[6:])['choices'][0]["delta"]["content"]
if token_counter == 0:
history.append(" " + partial_words)
else:
history[-1] = partial_words
chat = [(history[i], history[i + 1]) for i in
range(0, len(history) - 1, 2)] # convert to tuples of list
token_counter += 1
yield chat, history, chat_counter_chatgpt # this resembles {chatbot: chat, state: history}
logger.info(f"input: {inputs}, output: {partial_words}")
def reset_textbox():
return gr.update(value="")
def reset_chat(chatbot, state):
return None, []
title = """<h1 align="center">🔥🔥 ChatGPT Gradio Demo </h1><br><h3 align="center">🚀For ChatBot</h3>"""
description = """<center>author: shibing624</center>"""
with gr.Blocks(css="""#col_container {width: 1200px; margin-left: auto; margin-right: auto;}
#chatgpt {height: 520px; overflow: auto;} """) as demo:
# chattogether {height: 520px; overflow: auto;} """ ) as demo:
# clear {width: 100px; height:50px; font-size:12px}""") as demo:
gr.HTML(title)
with gr.Row():
with gr.Column(scale=14):
with gr.Box():
with gr.Row():
with gr.Column(scale=13):
api_key = get_api_key()
if not api_key:
openai_api_key = gr.Textbox(type='password',
label="Enter your OpenAI API key here for ChatGPT")
else:
openai_api_key = gr.Textbox(type='password',
label="Enter your OpenAI API key here for ChatGPT",
value=api_key, visible=False)
inputs = gr.Textbox(lines=4, placeholder="Hi there!",
label="Type input question and press Shift+Enter ⤵️ ")
with gr.Column(scale=1):
b1 = gr.Button('🏃Run', elem_id='run').style(full_width=True)
b2 = gr.Button('🔄Clear up Chatbots!', elem_id='clear').style(full_width=True)
state_chatgpt = gr.State([])
with gr.Box():
with gr.Row():
chatbot_chatgpt = gr.Chatbot(elem_id="chatgpt", label='ChatGPT API - OPENAI')
with gr.Column(scale=2, elem_id='parameters'):
with gr.Box():
gr.HTML("Parameters for OpenAI's ChatGPT")
top_p_chatgpt = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True,
label="Top-p", )
temperature_chatgpt = gr.Slider(minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True,
label="Temperature", )
chat_counter_chatgpt = gr.Number(value=0, visible=False, precision=0)
inputs.submit(reset_textbox, [], [inputs])
inputs.submit(predict_chatgpt,
[inputs, top_p_chatgpt, temperature_chatgpt, openai_api_key, chat_counter_chatgpt, chatbot_chatgpt,
state_chatgpt],
[chatbot_chatgpt, state_chatgpt, chat_counter_chatgpt], )
b1.click(predict_chatgpt,
[inputs, top_p_chatgpt, temperature_chatgpt, openai_api_key, chat_counter_chatgpt, chatbot_chatgpt,
state_chatgpt],
[chatbot_chatgpt, state_chatgpt, chat_counter_chatgpt], )
b2.click(reset_chat, [chatbot_chatgpt, state_chatgpt], [chatbot_chatgpt, state_chatgpt])
gr.HTML(
"""<center>Link to:<a href="https://github.com/shibing624/ChatGPT-API-server">https://github.com/shibing624/ChatGPT-API-server</a></center>""")
gr.Markdown(description)
if __name__ == '__main__':
demo.queue(concurrency_count=3).launch(height=2500, server_name='0.0.0.0', server_port=8080, debug=False)
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