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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)
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