import gradio as gr import os import markdown, mdtex2html from predict import predict from show_math import convert as convert_math try: from config_private import proxies, WEB_PORT # 放自己的秘密如API和代理网址 os.path.exists('config_private.py') except: from config import proxies, WEB_PORT def find_free_port(): import socket from contextlib import closing with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as s: s.bind(('', 0)) s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) return s.getsockname()[1] PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT initial_prompt = "Serve me as a writing and programming assistant." title_html = """

ChatGPT 学术优化

""" import logging os.makedirs('gpt_log', exist_ok=True) logging.basicConfig(filename='gpt_log/chat_secrets.log', level=logging.INFO, encoding='utf-8') print('所有问询记录将自动保存在本地目录./gpt_log/chat_secrets.log,请注意自我隐私保护哦!') from functional import get_functionals functional = get_functionals() def reset_textbox(): return gr.update(value='') def text_divide_paragraph(text): if '```' in text: # careful input return text else: # wtf input lines = text.split("\n") for i, line in enumerate(lines): if i!=0: lines[i] = "

"+lines[i].replace(" ", " ")+"

" text = "".join(lines) return text def markdown_convertion(txt): if ('$' in txt) and ('```' not in txt): math_config = {'mdx_math': {'enable_dollar_delimiter': True}} return markdown.markdown(txt,extensions=['fenced_code','tables']) + '

' + \ markdown.markdown(convert_math(txt, splitParagraphs=False),extensions=['fenced_code','tables']) else: return markdown.markdown(txt,extensions=['fenced_code','tables']) def format_io(self,y): if y is None: return [] i_ask, gpt_reply = y[-1] i_ask = text_divide_paragraph(i_ask) # 输入部分太自由,预处理一波 y[-1] = ( None if i_ask is None else markdown.markdown(i_ask, extensions=['fenced_code','tables']), None if gpt_reply is None else markdown_convertion(gpt_reply) ) return y gr.Chatbot.postprocess = format_io with gr.Blocks() as demo: gr.HTML(title_html) with gr.Row(): with gr.Column(scale=2): chatbot = gr.Chatbot() chatbot.style(height=700) chatbot.style() history = gr.State([]) TRUE = gr.State(True) FALSE = gr.State(False) with gr.Column(scale=1): with gr.Row(): with gr.Column(scale=12): txt = gr.Textbox(show_label=False, placeholder="Input question here.").style(container=False) with gr.Column(scale=1): submitBtn = gr.Button("Ask", variant="primary") with gr.Row(): for k in functional: variant = functional[k]["Color"] if "Color" in functional[k] else "secondary" functional[k]["Button"] = gr.Button(k, variant=variant) from check_proxy import check_proxy statusDisplay = gr.Markdown(f"{check_proxy(proxies)}") systemPromptTxt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt).style(container=True) #inputs, top_p, temperature, top_k, repetition_penalty with gr.Accordion("arguments", open=False): top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",) temperature = gr.Slider(minimum=-0, maximum=5.0, value=1.0, step=0.01, interactive=True, label="Temperature",) txt.submit(predict, [txt, top_p, temperature, chatbot, history, systemPromptTxt], [chatbot, history, statusDisplay]) submitBtn.click(predict, [txt, top_p, temperature, chatbot, history, systemPromptTxt], [chatbot, history, statusDisplay], show_progress=True) # submitBtn.click(reset_textbox, [], [txt]) for k in functional: functional[k]["Button"].click(predict, [txt, top_p, temperature, chatbot,history, systemPromptTxt, FALSE, TRUE, gr.State(k)], [chatbot, history, statusDisplay], show_progress=True) print(f"URL http://localhost:{PORT}") demo.title = "ChatGPT 学术优化" def auto_opentab_delay(): import threading, webbrowser, time def open(): time.sleep(2) webbrowser.open_new_tab(f'http://localhost:{PORT}') t = threading.Thread(target=open) t.daemon = True; t.start() auto_opentab_delay() demo.queue().launch(server_name="0.0.0.0", share=True, server_port=PORT)