# -*- coding: utf-8 -*- """ @author:XuMing(xuming624@qq.com) @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 = """

🔥🔥 ChatGPT Gradio Demo


🚀For ChatBot

""" description = """
author: shibing624
""" 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( """
Link to:https://github.com/shibing624/ChatGPT-API-server
""") gr.Markdown(description) if __name__ == '__main__': demo.queue(concurrency_count=3).launch(height=2500)