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| import gradio as gr | |
| import os | |
| import markdown, mdtex2html | |
| from predict import predict | |
| from show_math import convert as convert_math | |
| 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() | |
| initial_prompt = "Serve me as a writing and programming assistant." | |
| title_html = """<h1 align="center">ChatGPT 学术优化</h1>""" | |
| import logging | |
| os.makedirs('gpt_log', exist_ok=True) | |
| logging.basicConfig(filename='gpt_log/predict.log', level=logging.INFO) | |
| 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] = "<p>"+lines[i].replace(" ", " ")+"</p>" | |
| 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']) + '<br><br>' + \ | |
| markdown.markdown(convert_math(txt, splitParagraphs=False),extensions=['fenced_code','tables']) | |
| else: | |
| return markdown.markdown(txt,extensions=['fenced_code','tables']) | |
| # math_config = {'mdx_math': {'enable_dollar_delimiter': True}} | |
| # markdown.markdown(txt, extensions=['fenced_code', 'tables', 'mdx_math'], extension_configs=math_config) | |
| 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) | |
| statusDisplay = gr.Markdown("status: ready") | |
| 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) | |