gpt-academic / main.py
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feat(读文章写摘要):支持pdf文件批量阅读及总结
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import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
import gradio as gr
from predict import predict
from toolbox import format_io, find_free_port
# 建议您复制一个config_private.py放自己的秘密, 如API和代理网址, 避免不小心传github被别人看到
from config_private import proxies, WEB_PORT, LLM_MODEL
# 如果WEB_PORT是-1, 则随机选取WEB端口
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>"""
# 问询记录, python 版本建议3.9+(越新越好)
import logging
os.makedirs('gpt_log', exist_ok=True)
try:logging.basicConfig(filename='gpt_log/chat_secrets.log', level=logging.INFO, encoding='utf-8')
except:logging.basicConfig(filename='gpt_log/chat_secrets.log', level=logging.INFO)
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!')
# 一些普通功能模块
from functional import get_functionals
functional = get_functionals()
# 对一些丧心病狂的实验性功能模块进行测试
from functional_crazy import get_crazy_functionals, on_file_uploaded, on_report_generated
crazy_functional = get_crazy_functionals()
# 处理markdown文本格式的转变
gr.Chatbot.postprocess = format_io
# 做一些外观色彩上的调整
from theme import adjust_theme
set_theme = adjust_theme()
with gr.Blocks(theme=set_theme, analytics_enabled=False) as demo:
gr.HTML(title_html)
with gr.Row():
with gr.Column(scale=2):
chatbot = gr.Chatbot()
chatbot.style(height=1000)
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("提交", variant="primary")
with gr.Row():
from check_proxy import check_proxy
statusDisplay = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行. \nNetwork: {check_proxy(proxies)}\nModel: {LLM_MODEL}")
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)
with gr.Row():
gr.Markdown("以下部分实验性功能需从input框读取路径.")
with gr.Row():
for k in crazy_functional:
variant = crazy_functional[k]["Color"] if "Color" in crazy_functional[k] else "secondary"
crazy_functional[k]["Button"] = gr.Button(k, variant=variant)
with gr.Row():
gr.Markdown("上传本地文件供上面的实验性功能调用.")
with gr.Row():
file_upload = gr.Files(label='任何文件,但推荐上传压缩文件(zip, tar)', file_count="multiple")
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)
for k in functional:
functional[k]["Button"].click(predict,
[txt, top_p, temperature, chatbot, history, systemPromptTxt, TRUE, gr.State(k)], [chatbot, history, statusDisplay], show_progress=True)
file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt], [chatbot, txt])
for k in crazy_functional:
click_handle = crazy_functional[k]["Button"].click(crazy_functional[k]["Function"],
[txt, top_p, temperature, chatbot, history, systemPromptTxt, gr.State(PORT)], [chatbot, history, statusDisplay]
)
try: click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
except: pass
# 延迟函数, 做一些准备工作, 最后尝试打开浏览器
def auto_opentab_delay():
import threading, webbrowser, time
print(f"URL http://localhost:{PORT}")
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.title = "ChatGPT 学术优化"
demo.queue().launch(server_name="0.0.0.0", share=True, server_port=PORT)