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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 | |
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 = """<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']) | |
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) | |