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@ -40,6 +40,9 @@ 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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@ -47,7 +50,9 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
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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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txt = gr.Textbox(show_label=False, placeholder="Input question here.").style(container=False)
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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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@ -93,7 +98,7 @@ with gr.Blocks(theme=set_theme, analytics_enabled=False, css=advanced_css) as de
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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, temperature, chatbot, history, system_prompt]
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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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@ -142,4 +147,4 @@ def auto_opentab_delay():
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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=True, server_port=PORT, auth=AUTHENTICATION)
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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 **
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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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@ -101,7 +101,7 @@ 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 **
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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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@ -113,7 +113,7 @@ def 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, hist
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@CatchException
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def 批量总结PDF文档pdfminer(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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def 批量总结PDF文档pdfminer(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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history = [] # 清空历史，以免输入溢出
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import glob, os
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@ -147,5 +147,5 @@ def 批量总结PDF文档pdfminer(txt, top_p, temperature, chatbot, history, sys
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report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex或pdf文件: {txt}")
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yield chatbot, history, '正常'
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return
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yield from 解析Paper(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
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yield from 解析Paper(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
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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 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
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def 生成函数注释(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
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import time, glob, os
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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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@ -19,7 +19,7 @@ def 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbo
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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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@ -37,7 +37,7 @@ def 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbo
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@CatchException
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def 批量生成函数注释(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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def 批量生成函数注释(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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history = [] # 清空历史，以免输入溢出
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import glob, os
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if os.path.exists(txt):
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@ -54,4 +54,4 @@ def 批量生成函数注释(txt, top_p, temperature, chatbot, history, systemPr
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report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
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yield chatbot, history, '正常'
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return
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yield from 生成函数注释(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt)
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yield from 生成函数注释(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt)
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@ -2,7 +2,7 @@ from predict import predict_no_ui
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from toolbox import CatchException, report_execption, write_results_to_file, predict_no_ui_but_counting_down
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fast_debug = False
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def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot, history, systemPromptTxt):
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def 解析源代码(file_manifest, project_folder, top_p, api_key, temperature, chatbot, history, systemPromptTxt):
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import time, glob, os
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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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@ -19,7 +19,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot,
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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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@ -34,7 +34,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot,
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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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@ -47,7 +47,7 @@ def 解析源代码(file_manifest, project_folder, top_p, temperature, chatbot,
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@CatchException
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def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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def 解析项目本身(txt, top_p, api_key, temperature, chatbot, history, systemPromptTxt, WEB_PORT):
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history = [] # 清空历史，以免输入溢出
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import time, glob, os
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file_manifest = [f for f in glob.glob('./*.py') if ('test_project' not in f) and ('gpt_log' not in f)] + \
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@ -65,8 +65,8 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx
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if not fast_debug:
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# ** gpt request **
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# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, temperature=temperature)
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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=[], long_connection=True) # 带超时倒计时
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# gpt_say = predict_no_ui(inputs=i_say, top_p=top_p, api_key=api_key, temperature=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, history=[], long_connection=True) # 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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@ -79,8 +79,8 @@ def 解析项目本身(txt, top_p, temperature, chatbot, history, systemPromptTx
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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)
|
||||
|
||||
248
predict.py
248
predict.py
@ -1,248 +0,0 @@
|
||||
# 借鉴了 https://github.com/GaiZhenbiao/ChuanhuChatGPT 项目
|
||||
|
||||
"""
|
||||
该文件中主要包含三个函数
|
||||
|
||||
不具备多线程能力的函数：
|
||||
1. predict: 正常对话时使用，具备完备的交互功能，不可多线程
|
||||
|
||||
具备多线程调用能力的函数
|
||||
2. predict_no_ui：高级实验性功能模块调用，不会实时显示在界面上，参数简单，可以多线程并行，方便实现复杂的功能逻辑
|
||||
3. predict_no_ui_long_connection：在实验过程中发现调用predict_no_ui处理长文档时，和openai的连接容易断掉，这个函数用stream的方式解决这个问题，同样支持多线程
|
||||
"""
|
||||
|
||||
import json
|
||||
import gradio as gr
|
||||
import logging
|
||||
import traceback
|
||||
import requests
|
||||
import importlib
|
||||
|
||||
# config_private.py放自己的秘密如API和代理网址
|
||||
# 读取时首先看是否存在私密的config_private配置文件（不受git管控），如果有，则覆盖原config文件
|
||||
from toolbox import get_conf
|
||||
proxies, API_URL, API_KEY, TIMEOUT_SECONDS, MAX_RETRY, LLM_MODEL = \
|
||||
get_conf('proxies', 'API_URL', 'API_KEY', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'LLM_MODEL')
|
||||
|
||||
timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
|
||||
'网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。'
|
||||
|
||||
def get_full_error(chunk, stream_response):
|
||||
"""
|
||||
获取完整的从Openai返回的报错
|
||||
"""
|
||||
while True:
|
||||
try:
|
||||
chunk += next(stream_response)
|
||||
except:
|
||||
break
|
||||
return chunk
|
||||
|
||||
def predict_no_ui(inputs, top_p, 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
|
||||
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)
|
||||
|
||||
retry = 0
|
||||
while True:
|
||||
try:
|
||||
# make a POST request to the API endpoint, stream=False
|
||||
response = requests.post(API_URL, headers=headers, proxies=proxies,
|
||||
json=payload, stream=False, timeout=TIMEOUT_SECONDS*2); break
|
||||
except requests.exceptions.ReadTimeout as e:
|
||||
retry += 1
|
||||
traceback.print_exc()
|
||||
if retry > MAX_RETRY: raise TimeoutError
|
||||
if MAX_RETRY!=0: print(f'请求超时，正在重试 ({retry}/{MAX_RETRY}) ……')
|
||||
|
||||
try:
|
||||
result = json.loads(response.text)["choices"][0]["message"]["content"]
|
||||
return result
|
||||
except Exception as e:
|
||||
if "choices" not in response.text: print(response.text)
|
||||
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=""):
|
||||
"""
|
||||
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)
|
||||
|
||||
retry = 0
|
||||
while True:
|
||||
try:
|
||||
# make a POST request to the API endpoint, stream=False
|
||||
response = requests.post(API_URL, headers=headers, proxies=proxies,
|
||||
json=payload, stream=True, timeout=TIMEOUT_SECONDS); break
|
||||
except requests.exceptions.ReadTimeout as e:
|
||||
retry += 1
|
||||
traceback.print_exc()
|
||||
if retry > MAX_RETRY: raise TimeoutError
|
||||
if MAX_RETRY!=0: print(f'请求超时，正在重试 ({retry}/{MAX_RETRY}) ……')
|
||||
|
||||
stream_response = response.iter_lines()
|
||||
result = ''
|
||||
while True:
|
||||
try: chunk = next(stream_response).decode()
|
||||
except StopIteration: break
|
||||
if len(chunk)==0: continue
|
||||
if not chunk.startswith('data:'):
|
||||
error_msg = get_full_error(chunk.encode('utf8'), stream_response).decode()
|
||||
if "reduce the length" in error_msg:
|
||||
raise ConnectionAbortedError("OpenAI拒绝了请求:" + error_msg)
|
||||
else:
|
||||
raise RuntimeError("OpenAI拒绝了请求：" + error_msg)
|
||||
json_data = json.loads(chunk.lstrip('data:'))['choices'][0]
|
||||
delta = json_data["delta"]
|
||||
if len(delta) == 0: break
|
||||
if "role" in delta: continue
|
||||
if "content" in delta: result += delta["content"]; print(delta["content"], end='')
|
||||
else: raise RuntimeError("意外Json结构："+delta)
|
||||
if json_data['finish_reason'] == 'length':
|
||||
raise ConnectionAbortedError("正常结束，但显示Token不足。")
|
||||
return result
|
||||
|
||||
|
||||
def predict(inputs, top_p, 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
|
||||
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
|
||||
"""
|
||||
if additional_fn is not None:
|
||||
import functional
|
||||
importlib.reload(functional) # 热更新prompt
|
||||
functional = functional.get_functionals()
|
||||
if "PreProcess" in functional[additional_fn]: inputs = functional[additional_fn]["PreProcess"](inputs) # 获取预处理函数（如果有的话）
|
||||
inputs = functional[additional_fn]["Prefix"] + inputs + functional[additional_fn]["Suffix"]
|
||||
|
||||
if stream:
|
||||
raw_input = inputs
|
||||
logging.info(f'[raw_input] {raw_input}')
|
||||
chatbot.append((inputs, ""))
|
||||
yield chatbot, history, "等待响应"
|
||||
|
||||
headers, payload = generate_payload(inputs, top_p, temperature, history, system_prompt, stream)
|
||||
history.append(inputs); history.append(" ")
|
||||
|
||||
retry = 0
|
||||
while True:
|
||||
try:
|
||||
# make a POST request to the API endpoint, stream=True
|
||||
response = requests.post(API_URL, headers=headers, proxies=proxies,
|
||||
json=payload, stream=True, timeout=TIMEOUT_SECONDS);break
|
||||
except:
|
||||
retry += 1
|
||||
chatbot[-1] = ((chatbot[-1][0], timeout_bot_msg))
|
||||
retry_msg = f"，正在重试 ({retry}/{MAX_RETRY}) ……" if MAX_RETRY > 0 else ""
|
||||
yield chatbot, history, "请求超时"+retry_msg
|
||||
if retry > MAX_RETRY: raise TimeoutError
|
||||
|
||||
gpt_replying_buffer = ""
|
||||
|
||||
is_head_of_the_stream = True
|
||||
if stream:
|
||||
stream_response = response.iter_lines()
|
||||
while True:
|
||||
chunk = next(stream_response)
|
||||
# print(chunk.decode()[6:])
|
||||
if is_head_of_the_stream:
|
||||
# 数据流的第一帧不携带content
|
||||
is_head_of_the_stream = False; continue
|
||||
|
||||
if chunk:
|
||||
try:
|
||||
if len(json.loads(chunk.decode()[6:])['choices'][0]["delta"]) == 0:
|
||||
# 判定为数据流的结束，gpt_replying_buffer也写完了
|
||||
logging.info(f'[response] {gpt_replying_buffer}')
|
||||
break
|
||||
# 处理数据流的主体
|
||||
chunkjson = json.loads(chunk.decode()[6:])
|
||||
status_text = f"finish_reason: {chunkjson['choices'][0]['finish_reason']}"
|
||||
# 如果这里抛出异常，一般是文本过长，详情见get_full_error的输出
|
||||
gpt_replying_buffer = gpt_replying_buffer + json.loads(chunk.decode()[6:])['choices'][0]["delta"]["content"]
|
||||
history[-1] = gpt_replying_buffer
|
||||
chatbot[-1] = (history[-2], history[-1])
|
||||
yield chatbot, history, status_text
|
||||
|
||||
except Exception as e:
|
||||
traceback.print_exc()
|
||||
yield chatbot, history, "Json解析不合常规"
|
||||
chunk = get_full_error(chunk, stream_response)
|
||||
error_msg = chunk.decode()
|
||||
if "reduce the length" in error_msg:
|
||||
chatbot[-1] = (chatbot[-1][0], "[Local Message] Input (or history) is too long, please reduce input or clear history by refreshing this page.")
|
||||
history = [] # 清除历史
|
||||
elif "Incorrect API key" in error_msg:
|
||||
chatbot[-1] = (chatbot[-1][0], "[Local Message] Incorrect API key provided.")
|
||||
elif "exceeded your current quota" in error_msg:
|
||||
chatbot[-1] = (chatbot[-1][0], "[Local Message] You exceeded your current quota. OpenAI以账户额度不足为由，拒绝服务.")
|
||||
else:
|
||||
from toolbox import regular_txt_to_markdown
|
||||
tb_str = '```\n' + traceback.format_exc() + '```'
|
||||
chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk.decode()[4:])}")
|
||||
yield chatbot, history, "Json异常" + error_msg
|
||||
return
|
||||
|
||||
def generate_payload(inputs, top_p, 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}"
|
||||
}
|
||||
|
||||
conversation_cnt = len(history) // 2
|
||||
|
||||
messages = [{"role": "system", "content": system_prompt}]
|
||||
if conversation_cnt:
|
||||
for index in range(0, 2*conversation_cnt, 2):
|
||||
what_i_have_asked = {}
|
||||
what_i_have_asked["role"] = "user"
|
||||
what_i_have_asked["content"] = history[index]
|
||||
what_gpt_answer = {}
|
||||
what_gpt_answer["role"] = "assistant"
|
||||
what_gpt_answer["content"] = history[index+1]
|
||||
if what_i_have_asked["content"] != "":
|
||||
if what_gpt_answer["content"] == "": continue
|
||||
if what_gpt_answer["content"] == timeout_bot_msg: continue
|
||||
messages.append(what_i_have_asked)
|
||||
messages.append(what_gpt_answer)
|
||||
else:
|
||||
messages[-1]['content'] = what_gpt_answer['content']
|
||||
|
||||
what_i_ask_now = {}
|
||||
what_i_ask_now["role"] = "user"
|
||||
what_i_ask_now["content"] = inputs
|
||||
messages.append(what_i_ask_now)
|
||||
|
||||
payload = {
|
||||
"model": LLM_MODEL,
|
||||
"messages": messages,
|
||||
"temperature": temperature, # 1.0,
|
||||
"top_p": top_p, # 1.0,
|
||||
"n": 1,
|
||||
"stream": stream,
|
||||
"presence_penalty": 0,
|
||||
"frequency_penalty": 0,
|
||||
}
|
||||
|
||||
print(f" {LLM_MODEL} : {conversation_cnt} : {inputs}")
|
||||
return headers,payload
|
||||
|
||||
|
||||
@ -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