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app.py
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150
app.py
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import os; os.environ['no_proxy'] = '*' # 避免代理网络产生意外污染
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import gradio as gr
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from predict import predict
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from toolbox import format_io, find_free_port, on_file_uploaded, on_report_generated, get_conf
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# 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
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proxies, WEB_PORT, LLM_MODEL, CONCURRENT_COUNT, AUTHENTICATION, CHATBOT_HEIGHT = \
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get_conf('proxies', 'WEB_PORT', 'LLM_MODEL', 'CONCURRENT_COUNT', 'AUTHENTICATION', 'CHATBOT_HEIGHT')
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# 如果WEB_PORT是-1, 则随机选取WEB端口
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PORT = find_free_port() if WEB_PORT <= 0 else WEB_PORT
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if not AUTHENTICATION: AUTHENTICATION = None
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initial_prompt = "Serve me as a writing and programming assistant."
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title_html = "<h1 align=\"center\">ChatGPT 学术优化</h1>"
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description = """代码开源和更新[地址🚀](https://github.com/binary-husky/chatgpt_academic)，感谢热情的[开发者们❤️](https://github.com/binary-husky/chatgpt_academic/graphs/contributors)"""
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# 问询记录, python 版本建议3.9+（越新越好）
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import logging
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os.makedirs("gpt_log", exist_ok=True)
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try:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO, encoding="utf-8")
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except:logging.basicConfig(filename="gpt_log/chat_secrets.log", level=logging.INFO)
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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！")
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# 一些普通功能模块
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from functional import get_functionals
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functional = get_functionals()
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# 高级函数插件
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from functional_crazy import get_crazy_functionals
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crazy_fns = get_crazy_functionals()
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# 处理markdown文本格式的转变
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gr.Chatbot.postprocess = format_io
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# 做一些外观色彩上的调整
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from theme import adjust_theme, advanced_css
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set_theme = adjust_theme()
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cancel_handles = []
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with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
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gr.HTML(title_html)
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# To add a Duplicate Space badge
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gr.HTML('''<center><a href="https://huggingface.co/spaces/qingxu98/gpt-academic?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>请您打开此页面后务必点击上方的“复制空间”（Duplicate Space）按钮！<br/>切忌在“复制空间”（Duplicate Space）之前填入API_KEY或进行提问，否则您的API_KEY将极可能被空间所有者攫取！</center>''')
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with gr.Row().style(equal_height=True):
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with gr.Column(scale=2):
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chatbot = gr.Chatbot()
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chatbot.style(height=CHATBOT_HEIGHT)
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history = gr.State([])
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with gr.Column(scale=1):
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with gr.Row():
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api_key = gr.Textbox(show_label=False, placeholder="输入API_KEY，输入后自动生效.").style(container=False)
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with gr.Row():
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txt = gr.Textbox(show_label=False, placeholder="输入问题.").style(container=False)
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with gr.Row():
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submitBtn = gr.Button("提交", variant="primary")
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with gr.Row():
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resetBtn = gr.Button("重置", variant="secondary"); resetBtn.style(size="sm")
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stopBtn = gr.Button("停止", variant="secondary"); stopBtn.style(size="sm")
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with gr.Row():
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from check_proxy import check_proxy
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status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {check_proxy(proxies)}")
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with gr.Accordion("基础功能区", open=True) as area_basic_fn:
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with gr.Row():
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for k in functional:
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variant = functional[k]["Color"] if "Color" in functional[k] else "secondary"
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functional[k]["Button"] = gr.Button(k, variant=variant)
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with gr.Accordion("函数插件区", open=True) as area_crazy_fn:
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with gr.Row():
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gr.Markdown("注意：以下“红颜色”标识的函数插件需从input区读取路径作为参数.")
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with gr.Row():
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for k in crazy_fns:
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if not crazy_fns[k].get("AsButton", True): continue
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variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
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crazy_fns[k]["Button"] = gr.Button(k, variant=variant)
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with gr.Row():
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with gr.Accordion("更多函数插件", open=True):
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dropdown_fn_list = [k for k in crazy_fns.keys() if not crazy_fns[k].get("AsButton", True)]
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with gr.Column(scale=1):
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dropdown = gr.Dropdown(dropdown_fn_list, value=r"打开插件列表", label="").style(container=False)
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with gr.Column(scale=1):
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switchy_bt = gr.Button(r"请先从插件列表中选择", variant="secondary")
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with gr.Row():
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with gr.Accordion("点击展开“文件上传区”。上传本地文件可供红色函数插件调用。", open=False) as area_file_up:
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file_upload = gr.Files(label="任何文件, 但推荐上传压缩文件(zip, tar)", file_count="multiple")
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with gr.Accordion("展开SysPrompt & 交互界面布局 & Github地址", open=False):
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system_prompt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt)
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top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",)
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temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",)
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checkboxes = gr.CheckboxGroup(["基础功能区", "函数插件区"], value=["基础功能区", "函数插件区"], label="显示/隐藏功能区")
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gr.Markdown(description)
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# 功能区显示开关与功能区的互动
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def fn_area_visibility(a):
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ret = {}
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ret.update({area_basic_fn: gr.update(visible=("基础功能区" in a))})
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ret.update({area_crazy_fn: gr.update(visible=("函数插件区" in a))})
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return ret
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checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn] )
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# 整理反复出现的控件句柄组合
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input_combo = [txt, top_p, api_key, temperature, chatbot, history, system_prompt]
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output_combo = [chatbot, history, status]
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predict_args = dict(fn=predict, inputs=input_combo, outputs=output_combo)
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empty_txt_args = dict(fn=lambda: "", inputs=[], outputs=[txt]) # 用于在提交后清空输入栏
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# 提交按钮、重置按钮
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cancel_handles.append(txt.submit(**predict_args)) #; txt.submit(**empty_txt_args) 在提交后清空输入栏
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cancel_handles.append(submitBtn.click(**predict_args)) #; submitBtn.click(**empty_txt_args) 在提交后清空输入栏
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resetBtn.click(lambda: ([], [], "已重置"), None, output_combo)
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# 基础功能区的回调函数注册
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for k in functional:
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click_handle = functional[k]["Button"].click(predict, [*input_combo, gr.State(True), gr.State(k)], output_combo)
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cancel_handles.append(click_handle)
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# 文件上传区，接收文件后与chatbot的互动
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file_upload.upload(on_file_uploaded, [file_upload, chatbot, txt], [chatbot, txt])
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# 函数插件-固定按钮区
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for k in crazy_fns:
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if not crazy_fns[k].get("AsButton", True): continue
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click_handle = crazy_fns[k]["Button"].click(crazy_fns[k]["Function"], [*input_combo, gr.State(PORT)], output_combo)
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click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
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cancel_handles.append(click_handle)
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# 函数插件-下拉菜单与随变按钮的互动
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def on_dropdown_changed(k):
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variant = crazy_fns[k]["Color"] if "Color" in crazy_fns[k] else "secondary"
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return {switchy_bt: gr.update(value=k, variant=variant)}
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dropdown.select(on_dropdown_changed, [dropdown], [switchy_bt] )
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# 随变按钮的回调函数注册
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def route(k, *args, **kwargs):
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if k in [r"打开插件列表", r"请先从插件列表中选择"]: return
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yield from crazy_fns[k]["Function"](*args, **kwargs)
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click_handle = switchy_bt.click(route,[switchy_bt, *input_combo, gr.State(PORT)], output_combo)
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click_handle.then(on_report_generated, [file_upload, chatbot], [file_upload, chatbot])
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# def expand_file_area(file_upload, area_file_up):
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# if len(file_upload)>0: return {area_file_up: gr.update(open=True)}
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# click_handle.then(expand_file_area, [file_upload, area_file_up], [area_file_up])
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cancel_handles.append(click_handle)
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# 终止按钮的回调函数注册
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stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
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# gradio的inbrowser触发不太稳定，回滚代码到原始的浏览器打开函数
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def auto_opentab_delay():
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import threading, webbrowser, time
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print(f"如果浏览器没有自动打开，请复制并转到以下URL: http://localhost:{PORT}")
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def open():
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time.sleep(2)
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webbrowser.open_new_tab(f"http://localhost:{PORT}")
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threading.Thread(target=open, name="open-browser", daemon=True).start()
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auto_opentab_delay()
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demo.title = "ChatGPT 学术优化"
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demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", share=False)
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@ -132,7 +132,7 @@ def get_name(_url_):
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@CatchException
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def 下载arxiv论文并翻译摘要(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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def 下载arxiv论文并翻译摘要(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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CRAZY_FUNCTION_INFO = "下载arxiv论文并翻译摘要，函数插件作者[binary-husky]。正在提取摘要并下载PDF文档……"
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import glob
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@ -172,7 +172,7 @@ def 下载arxiv论文并翻译摘要(txt, top_p, temperature, chatbot, history,
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yield chatbot, history, '正常'
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msg = '正常'
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# ** gpt request **
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
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chatbot[-1] = (i_say_show_user, gpt_say)
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history.append(i_say_show_user); history.append(gpt_say)
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yield chatbot, history, msg
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@ -5,7 +5,7 @@ from toolbox import CatchException, write_results_to_file
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@CatchException
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def 全项目切换英文(txt, top_p, temperature, chatbot, history, sys_prompt, WEB_PORT):
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def 全项目切换英文(txt, top_p, api_key, temperature, chatbot, history, sys_prompt, WEB_PORT):
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history = [] # 清空历史，以免输入溢出
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# 集合文件
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import time, glob, os
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@ -32,7 +32,7 @@ def 全项目切换英文(txt, top_p, temperature, chatbot, history, sys_prompt,
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file_content = f.read()
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i_say = f'接下来请将以下代码中包含的所有中文转化为英文，只输出代码，文件名是{fp}，文件代码是 ```{file_content}```'
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# ** gpt request **
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gpt_say = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
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gpt_say = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history, sys_prompt=sys_prompt)
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mutable_return[index] = gpt_say
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# 所有线程同时开始执行任务函数
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@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file, pre
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fast_debug = False
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def 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
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def 解析docx(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
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import time, os
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# pip install python-docx 用于docx格式，跨平台
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# pip install pywin32 用于doc格式，仅支持Win平台
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@ -40,7 +40,7 @@ def 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, histo
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if not fast_debug:
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msg = '正常'
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# ** gpt request **
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature,
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature,
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history=[]) # 带超时倒计时
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chatbot[-1] = (i_say_show_user, gpt_say)
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history.append(i_say_show_user);
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@ -66,7 +66,7 @@ def 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, histo
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if not fast_debug:
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msg = '正常'
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# ** gpt request **
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature,
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature,
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history=history) # 带超时倒计时
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chatbot[-1] = (i_say, gpt_say)
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@ -79,7 +79,7 @@ def 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, histo
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@CatchException
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def 总结word文档(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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def 总结word文档(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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import glob, os
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# 基本信息：功能、贡献者
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@ -124,4 +124,4 @@ def 总结word文档(txt, top_p, temperature, chatbot, history, systemPromptTxt,
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return
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# 开始正式执行任务
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yield from 解析docx(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
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yield from 解析docx(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
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@ -57,7 +57,7 @@ def clean_text(raw_text):
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return final_text.strip()
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def 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
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def 解析PDF(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
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import time, glob, os, fitz
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print('begin analysis on:', file_manifest)
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for index, fp in enumerate(file_manifest):
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@ -78,7 +78,7 @@ def 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, histor
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if not fast_debug:
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msg = '正常'
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# ** gpt request **
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
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print('[2] end gpt req')
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chatbot[-1] = (i_say_show_user, gpt_say)
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@ -96,7 +96,7 @@ def 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, histor
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if not fast_debug:
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msg = '正常'
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# ** gpt request **
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
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gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
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chatbot[-1] = (i_say, gpt_say)
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history.append(i_say); history.append(gpt_say)
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@ -107,7 +107,7 @@ def 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, histor
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@CatchException
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def 批量总结PDF文档(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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def 批量总结PDF文档(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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import glob, os
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# 基本信息：功能、贡献者
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@ -151,4 +151,4 @@ def 批量总结PDF文档(txt, top_p, temperature, chatbot, history, systemPromp
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return
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# 开始正式执行任务
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yield from 解析PDF(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
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yield from 解析PDF(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
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@ -61,7 +61,7 @@ def readPdf(pdfPath):
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return outTextList
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def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
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def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
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import time, glob, os
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from bs4 import BeautifulSoup
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print('begin analysis on:', file_manifest)
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@ -83,7 +83,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
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if not fast_debug:
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msg = '正常'
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# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
|
||||
|
||||
print('[2] end gpt req')
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
@ -101,7 +101,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
history.append(i_say); history.append(gpt_say)
|
||||
@ -113,7 +113,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
|
||||
|
||||
|
||||
@CatchException
|
||||
def 批量总结PDF文档pdfminer(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 批量总结PDF文档pdfminer(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
import glob, os
|
||||
|
||||
@ -147,5 +147,5 @@ def 批量总结PDF文档pdfminer(txt, top_p, temperature, chatbot, history, sys
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex或pdf文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
|
||||
@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file, pre
|
||||
fast_debug = False
|
||||
|
||||
|
||||
def 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
|
||||
def 生成函数注释(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
|
||||
import time, glob, os
|
||||
print('begin analysis on:', file_manifest)
|
||||
for index, fp in enumerate(file_manifest):
|
||||
@ -19,7 +19,7 @@ def 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbo
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
|
||||
|
||||
print('[2] end gpt req')
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
@ -37,7 +37,7 @@ def 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbo
|
||||
|
||||
|
||||
@CatchException
|
||||
def 批量生成函数注释(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 批量生成函数注释(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@ -54,4 +54,4 @@ def 批量生成函数注释(txt, top_p, temperature, chatbot, history, systemPr
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 生成函数注释(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
@ -2,7 +2,7 @@ from predict import predict_no_ui
|
||||
from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down
|
||||
fast_debug = False
|
||||
|
||||
def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
|
||||
def 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
|
||||
import time, glob, os
|
||||
print('begin analysis on:', file_manifest)
|
||||
for index, fp in enumerate(file_manifest):
|
||||
@ -19,7 +19,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot,
|
||||
msg = '正常'
|
||||
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
history.append(i_say_show_user); history.append(gpt_say)
|
||||
@ -34,7 +34,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot,
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
history.append(i_say); history.append(gpt_say)
|
||||
@ -47,7 +47,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot,
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 解析项目本身(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
import time, glob, os
|
||||
file_manifest = [f for f in glob.glob('./*.py') if ('test_project' not in f) and ('gpt_log' not in f)] + \
|
||||
@ -65,8 +65,8 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx
|
||||
|
||||
if not fast_debug:
|
||||
# ** gpt request **
|
||||
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature)
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[], long_connection=True) # 带超时倒计时
|
||||
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature)
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[], long_connection=True) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
history.append(i_say_show_user); history.append(gpt_say)
|
||||
@ -79,8 +79,8 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx
|
||||
|
||||
if not fast_debug:
|
||||
# ** gpt request **
|
||||
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature, history=history)
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history, long_connection=True) # 带超时倒计时
|
||||
# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history)
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history, long_connection=True) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
history.append(i_say); history.append(gpt_say)
|
||||
@ -90,7 +90,7 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx
|
||||
yield chatbot, history, '正常'
|
||||
|
||||
@CatchException
|
||||
def 解析一个Python项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 解析一个Python项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@ -105,11 +105,11 @@ def 解析一个Python项目(txt, top_p, temperature, chatbot, history, systemPr
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何python文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析一个C项目的头文件(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 解析一个C项目的头文件(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@ -126,10 +126,10 @@ def 解析一个C项目的头文件(txt, top_p, temperature, chatbot, history, s
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.h头文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
@CatchException
|
||||
def 解析一个C项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 解析一个C项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@ -146,11 +146,11 @@ def 解析一个C项目(txt, top_p, temperature, chatbot, history, systemPromptT
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.h头文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析一个Java项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 解析一个Java项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@ -168,11 +168,11 @@ def 解析一个Java项目(txt, top_p, temperature, chatbot, history, systemProm
|
||||
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何java文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析一个Rect项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 解析一个Rect项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@ -191,11 +191,11 @@ def 解析一个Rect项目(txt, top_p, temperature, chatbot, history, systemProm
|
||||
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何Rect文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
|
||||
@CatchException
|
||||
def 解析一个Golang项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 解析一个Golang项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@ -210,4 +210,4 @@ def 解析一个Golang项目(txt, top_p, temperature, chatbot, history, systemPr
|
||||
report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何golang文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file, pre
|
||||
fast_debug = False
|
||||
|
||||
|
||||
def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
|
||||
def 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
|
||||
import time, glob, os
|
||||
print('begin analysis on:', file_manifest)
|
||||
for index, fp in enumerate(file_manifest):
|
||||
@ -20,7 +20,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[]) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[]) # 带超时倒计时
|
||||
|
||||
print('[2] end gpt req')
|
||||
chatbot[-1] = (i_say_show_user, gpt_say)
|
||||
@ -38,7 +38,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
|
||||
if not fast_debug:
|
||||
msg = '正常'
|
||||
# ** gpt request **
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, temperature, history=history) # 带超时倒计时
|
||||
gpt_say = yield from predict_no_ui_but_counting_down(i_say, i_say, chatbot, top_p, api_key, temperature, history=history) # 带超时倒计时
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
history.append(i_say); history.append(gpt_say)
|
||||
@ -50,7 +50,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
|
||||
|
||||
|
||||
@CatchException
|
||||
def 读文章写摘要(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 读文章写摘要(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
import glob, os
|
||||
if os.path.exists(txt):
|
||||
@ -67,4 +67,4 @@ def 读文章写摘要(txt, top_p, temperature, chatbot, history, systemPromptTx
|
||||
report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
|
||||
yield chatbot, history, '正常'
|
||||
return
|
||||
yield from 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
|
||||
yield from 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
|
||||
|
||||
@ -3,7 +3,7 @@ from toolbox import CatchException, report_execption, write_results_to_file
|
||||
import datetime
|
||||
|
||||
@CatchException
|
||||
def 高阶功能模板函数(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def 高阶功能模板函数(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
history = [] # 清空历史，以免输入溢出
|
||||
chatbot.append(("这是什么功能？", "[Local Message] 请注意，您正在调用一个[函数插件]的模板，该函数面向希望实现更多有趣功能的开发者，它可以作为创建新功能函数的模板。为了做到简单易读，该函数只有25行代码，所以不会实时反馈文字流或心跳，请耐心等待程序输出完成。此外我们也提供可同步处理大量文件的多线程Demo供您参考。您若希望分享新的功能模组，请不吝PR！"))
|
||||
yield chatbot, history, '正常' # 由于请求gpt需要一段时间，我们先及时地做一次状态显示
|
||||
@ -17,7 +17,7 @@ def 高阶功能模板函数(txt, top_p, temperature, chatbot, history, systemPr
|
||||
|
||||
# history = [] 每次询问不携带之前的询问历史
|
||||
gpt_say = predict_no_ui_long_connection(
|
||||
inputs=i_say, top_p=top_p, temperature=temperature, history=[],
|
||||
inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=[],
|
||||
sys_prompt="当你想发送一张照片时，请使用Markdown, 并且不要有反斜线, 不要用代码块。使用 Unsplash API (https://source.unsplash.com/1280x720/? < PUT_YOUR_QUERY_HERE >)。") # 请求gpt，需要一段时间
|
||||
|
||||
chatbot[-1] = (i_say, gpt_say)
|
||||
|
||||
13
main.py
13
main.py
@ -1,3 +1,5 @@
|
||||
assert False, "Huggingface Version Please Run app.py"
|
||||
|
||||
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
|
||||
@ -40,6 +42,9 @@ set_theme = adjust_theme()
|
||||
cancel_handles = []
|
||||
with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as demo:
|
||||
gr.HTML(title_html)
|
||||
# To add a Duplicate Space badge
|
||||
gr.HTML('''<center><a href="https://huggingface.co/spaces/qingxu98/gpt-academic?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>请您打开此页面后务必点击上方的“复制空间”（Duplicate Space）按钮！<br/>切忌在“复制空间”（Duplicate Space）之前填入API_KEY或进行提问，否则您的API_KEY将极可能被空间所有者攫取！</center>''')
|
||||
|
||||
with gr.Row().style(equal_height=True):
|
||||
with gr.Column(scale=2):
|
||||
chatbot = gr.Chatbot()
|
||||
@ -47,7 +52,9 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
|
||||
history = gr.State([])
|
||||
with gr.Column(scale=1):
|
||||
with gr.Row():
|
||||
txt = gr.Textbox(show_label=False, placeholder="Input question here.").style(container=False)
|
||||
api_key = gr.Textbox(show_label=False, placeholder="输入API_KEY，输入后自动生效.").style(container=False)
|
||||
with gr.Row():
|
||||
txt = gr.Textbox(show_label=False, placeholder="输入问题.").style(container=False)
|
||||
with gr.Row():
|
||||
submitBtn = gr.Button("提交", variant="primary")
|
||||
with gr.Row():
|
||||
@ -93,7 +100,7 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
|
||||
return ret
|
||||
checkboxes.select(fn_area_visibility, [checkboxes], [area_basic_fn, area_crazy_fn] )
|
||||
# 整理反复出现的控件句柄组合
|
||||
input_combo = [txt, top_p, temperature, chatbot, history, system_prompt]
|
||||
input_combo = [txt, top_p, api_key, temperature, chatbot, history, system_prompt]
|
||||
output_combo = [chatbot, history, status]
|
||||
predict_args = dict(fn=predict, inputs=input_combo, outputs=output_combo)
|
||||
empty_txt_args = dict(fn=lambda: "", inputs=[], outputs=[txt]) # 用于在提交后清空输入栏
|
||||
@ -142,4 +149,4 @@ def auto_opentab_delay():
|
||||
|
||||
auto_opentab_delay()
|
||||
demo.title = "ChatGPT 学术优化"
|
||||
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", share=True, server_port=PORT, auth=AUTHENTICATION)
|
||||
demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", share=False)
|
||||
|
||||
20
predict.py
20
predict.py
@ -38,18 +38,18 @@ def get_full_error(chunk, stream_response):
|
||||
break
|
||||
return chunk
|
||||
|
||||
def predict_no_ui(inputs, top_p, temperature, history=[], sys_prompt=""):
|
||||
def predict_no_ui(inputs, top_p, api_key, temperature, history=[], sys_prompt=""):
|
||||
"""
|
||||
发送至chatGPT，等待回复，一次性完成，不显示中间过程。
|
||||
predict函数的简化版。
|
||||
用于payload比较大的情况，或者用于实现多线、带嵌套的复杂功能。
|
||||
|
||||
inputs 是本次问询的输入
|
||||
top_p, temperature是chatGPT的内部调优参数
|
||||
top_p, api_key, temperature是chatGPT的内部调优参数
|
||||
history 是之前的对话列表
|
||||
（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误，然后raise ConnectionAbortedError）
|
||||
"""
|
||||
headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt=sys_prompt, stream=False)
|
||||
headers, payload = generate_payload(inputs, top_p, api_key, temperature, history, system_prompt=sys_prompt, stream=False)
|
||||
|
||||
retry = 0
|
||||
while True:
|
||||
@ -71,11 +71,11 @@ def predict_no_ui(inputs, top_p, temperature, history=[], sys_prompt=""):
|
||||
raise ConnectionAbortedError("Json解析不合常规，可能是文本过长" + response.text)
|
||||
|
||||
|
||||
def predict_no_ui_long_connection(inputs, top_p, temperature, history=[], sys_prompt=""):
|
||||
def predict_no_ui_long_connection(inputs, top_p, api_key, temperature, history=[], sys_prompt=""):
|
||||
"""
|
||||
发送至chatGPT，等待回复，一次性完成，不显示中间过程。但内部用stream的方法避免有人中途掐网线。
|
||||
"""
|
||||
headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt=sys_prompt, stream=True)
|
||||
headers, payload = generate_payload(inputs, top_p, api_key, temperature, history, system_prompt=sys_prompt, stream=True)
|
||||
|
||||
retry = 0
|
||||
while True:
|
||||
@ -112,13 +112,13 @@ def predict_no_ui_long_connection(inputs, top_p, temperature, history=[], sys_pr
|
||||
return result
|
||||
|
||||
|
||||
def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='',
|
||||
def predict(inputs, top_p, api_key, temperature, chatbot=[], history=[], system_prompt='',
|
||||
stream = True, additional_fn=None):
|
||||
"""
|
||||
发送至chatGPT，流式获取输出。
|
||||
用于基础的对话功能。
|
||||
inputs 是本次问询的输入
|
||||
top_p, temperature是chatGPT的内部调优参数
|
||||
top_p, api_key, temperature是chatGPT的内部调优参数
|
||||
history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
|
||||
chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
|
||||
additional_fn代表点击的哪个按钮，按钮见functional.py
|
||||
@ -136,7 +136,7 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
|
||||
chatbot.append((inputs, ""))
|
||||
yield chatbot, history, "等待响应"
|
||||
|
||||
headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt, stream)
|
||||
headers, payload = generate_payload(inputs, top_p, api_key, temperature, history, system_prompt, stream)
|
||||
history.append(inputs); history.append(" ")
|
||||
|
||||
retry = 0
|
||||
@ -198,13 +198,13 @@ def predict(inputs, top_p, temperature, chatbot=[], history=[], system_prompt=''
|
||||
yield chatbot, history, "Json异常" + error_msg
|
||||
return
|
||||
|
||||
def generate_payload(inputs, top_p, temperature, history, system_prompt, stream):
|
||||
def generate_payload(inputs, top_p, api_key, temperature, history, system_prompt, stream):
|
||||
"""
|
||||
整合所有信息，选择LLM模型，生成http请求，为发送请求做准备
|
||||
"""
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer {API_KEY}"
|
||||
"Authorization": f"Bearer {api_key}"
|
||||
}
|
||||
|
||||
conversation_cnt = len(history) // 2
|
||||
|
||||
@ -90,12 +90,12 @@ async def run(context, max_token=512):
|
||||
|
||||
|
||||
|
||||
def predict_tgui(inputs, top_p, temperature, chatbot=[], history=[], system_prompt='', stream = True, additional_fn=None):
|
||||
def predict_tgui(inputs, top_p, api_key, temperature, chatbot=[], history=[], system_prompt='', stream = True, additional_fn=None):
|
||||
"""
|
||||
发送至chatGPT，流式获取输出。
|
||||
用于基础的对话功能。
|
||||
inputs 是本次问询的输入
|
||||
top_p, temperature是chatGPT的内部调优参数
|
||||
top_p, api_key, temperature是chatGPT的内部调优参数
|
||||
history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
|
||||
chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
|
||||
additional_fn代表点击的哪个按钮，按钮见functional.py
|
||||
@ -144,7 +144,7 @@ def predict_tgui(inputs, top_p, temperature, chatbot=[], history=[], system_prom
|
||||
|
||||
|
||||
|
||||
def predict_tgui_no_ui(inputs, top_p, temperature, history=[], sys_prompt=""):
|
||||
def predict_tgui_no_ui(inputs, top_p, api_key, temperature, history=[], sys_prompt=""):
|
||||
raw_input = "What I would like to say is the following: " + inputs
|
||||
prompt = inputs
|
||||
tgui_say = ""
|
||||
|
||||
@ -131,11 +131,11 @@
|
||||
|
||||
这个程序文件中包含了几个函数，分别是：
|
||||
|
||||
1. `解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)`：通过输入文件路径列表对程序文件进行逐文件分析，根据分析结果做出整体功能和构架的概括，并生成包括每个文件功能的markdown表格。
|
||||
2. `解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`：对当前文件夹下的所有Python文件及其子文件夹进行逐文件分析，并生成markdown表格。
|
||||
3. `解析一个Python项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`：对指定路径下的所有Python文件及其子文件夹进行逐文件分析，并生成markdown表格。
|
||||
4. `解析一个C项目的头文件(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`：对指定路径下的所有头文件进行逐文件分析，并生成markdown表格。
|
||||
5. `解析一个C项目(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`：对指定路径下的所有.h、.cpp、.c文件及其子文件夹进行逐文件分析，并生成markdown表格。
|
||||
1. `解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)`：通过输入文件路径列表对程序文件进行逐文件分析，根据分析结果做出整体功能和构架的概括，并生成包括每个文件功能的markdown表格。
|
||||
2. `解析项目本身(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`：对当前文件夹下的所有Python文件及其子文件夹进行逐文件分析，并生成markdown表格。
|
||||
3. `解析一个Python项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`：对指定路径下的所有Python文件及其子文件夹进行逐文件分析，并生成markdown表格。
|
||||
4. `解析一个C项目的头文件(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`：对指定路径下的所有头文件进行逐文件分析，并生成markdown表格。
|
||||
5. `解析一个C项目(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)`：对指定路径下的所有.h、.cpp、.c文件及其子文件夹进行逐文件分析，并生成markdown表格。
|
||||
|
||||
程序中还包含了一些辅助函数和变量，如CatchException装饰器函数，report_execption函数、write_results_to_file函数等。在执行过程中还会调用其他模块中的函数，如toolbox模块的函数和predict模块的函数。
|
||||
|
||||
|
||||
28
toolbox.py
28
toolbox.py
@ -16,13 +16,13 @@ def get_reduce_token_percent(text):
|
||||
except:
|
||||
return 0.5, '不详'
|
||||
|
||||
def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temperature, history=[], sys_prompt='', long_connection=True):
|
||||
def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, api_key, temperature, history=[], sys_prompt='', long_connection=True):
|
||||
"""
|
||||
调用简单的predict_no_ui接口，但是依然保留了些许界面心跳功能，当对话太长时，会自动采用二分法截断
|
||||
i_say: 当前输入
|
||||
i_say_show_user: 显示到对话界面上的当前输入，例如，输入整个文件时，你绝对不想把文件的内容都糊到对话界面上
|
||||
chatbot: 对话界面句柄
|
||||
top_p, temperature: gpt参数
|
||||
top_p, api_key, temperature: gpt参数
|
||||
history: gpt参数 对话历史
|
||||
sys_prompt: gpt参数 sys_prompt
|
||||
long_connection: 是否采用更稳定的连接方式（推荐）
|
||||
@ -39,9 +39,9 @@ def predict_no_ui_but_counting_down(i_say, i_say_show_user, chatbot, top_p, temp
|
||||
while True:
|
||||
try:
|
||||
if long_connection:
|
||||
mutable[0] = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||||
mutable[0] = predict_no_ui_long_connection(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||||
else:
|
||||
mutable[0] = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||||
mutable[0] = predict_no_ui(inputs=i_say, top_p=top_p, api_key=api_key, temperature=temperature, history=history, sys_prompt=sys_prompt)
|
||||
break
|
||||
except ConnectionAbortedError as token_exceeded_error:
|
||||
# 尝试计算比例，尽可能多地保留文本
|
||||
@ -108,9 +108,9 @@ def CatchException(f):
|
||||
装饰器函数，捕捉函数f中的异常并封装到一个生成器中返回，并显示到聊天当中。
|
||||
"""
|
||||
@wraps(f)
|
||||
def decorated(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
def decorated(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
|
||||
try:
|
||||
yield from f(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
|
||||
yield from f(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT)
|
||||
except Exception as e:
|
||||
from check_proxy import check_proxy
|
||||
from toolbox import get_conf
|
||||
@ -313,14 +313,14 @@ def read_single_conf_with_lru_cache(arg):
|
||||
try: r = getattr(importlib.import_module('config_private'), arg)
|
||||
except: r = getattr(importlib.import_module('config'), arg)
|
||||
# 在读取API_KEY时，检查一下是不是忘了改config
|
||||
if arg=='API_KEY':
|
||||
# 正确的 API_KEY 是 "sk-" + 48 位大小写字母数字的组合
|
||||
API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", r)
|
||||
if API_MATCH:
|
||||
print(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功")
|
||||
else:
|
||||
assert False, "正确的 API_KEY 是 'sk-' + '48 位大小写字母数字' 的组合，请在config文件中修改API密钥, 添加海外代理之后再运行。" + \
|
||||
"（如果您刚更新过代码，请确保旧版config_private文件中没有遗留任何新增键值）"
|
||||
# if arg=='API_KEY':
|
||||
# # 正确的 API_KEY 是 "sk-" + 48 位大小写字母数字的组合
|
||||
# API_MATCH = re.match(r"sk-[a-zA-Z0-9]{48}$", r)
|
||||
# if API_MATCH:
|
||||
# print(f"[API_KEY] 您的 API_KEY 是: {r[:15]}*** API_KEY 导入成功")
|
||||
# else:
|
||||
# assert False, "正确的 API_KEY 是 'sk-' + '48 位大小写字母数字' 的组合，请在config文件中修改API密钥, 添加海外代理之后再运行。" + \
|
||||
# "（如果您刚更新过代码，请确保旧版config_private文件中没有遗留任何新增键值）"
|
||||
if arg=='proxies':
|
||||
if r is None:
|
||||
print('[PROXY] 网络代理状态：未配置。无代理状态下很可能无法访问。建议：检查USE_PROXY选项是否修改。')
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user