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Runtime error
XingHe0127
commited on
Commit
•
5851510
1
Parent(s):
04b3136
Upload 6 files
Browse files- Chatbot.py +72 -65
- README.md +360 -10
- presets.py +58 -11
- requirements.txt +5 -0
- utils.py +167 -75
Chatbot.py
CHANGED
@@ -1,11 +1,13 @@
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import gradio as gr
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# import openai
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import os
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import sys
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import argparse
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from utils import *
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from presets import *
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my_api_key = os.getenv("OpenAI-API") # 在这里输入你的 API 密钥
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@@ -20,7 +22,7 @@ authflag = False
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if dockerflag:
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my_api_key = os.environ.get('my_api_key')
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if my_api_key == "empty":
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sys.exit(1)
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#auth
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username = os.environ.get('USERNAME')
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gr.Chatbot.postprocess = postprocess
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with gr.Blocks(css=customCSS) as demo:
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gr.HTML(title)
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with gr.Row():
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keyTxt = gr.Textbox(show_label=False, placeholder=f"在这里输入你的OpenAI API-key...",
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value=my_api_key, type="password", visible=not HIDE_MY_KEY).style(container=True)
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use_streaming_checkbox = gr.Checkbox(label="实时传输回答", value=True, visible=enable_streaming_option)
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chatbot = gr.Chatbot() # .style(color_map=("#1D51EE", "#585A5B"))
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history = gr.State([])
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token_count = gr.State([])
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promptTemplates = gr.State(load_template(get_template_names(plain=True)[0], mode=2))
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topic = gr.State("未命名对话历史记录")
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with gr.Row():
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templateRefreshBtn = gr.Button("🔄 刷新")
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templaeFileReadBtn = gr.Button("📂 读入模板")
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with gr.Row():
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with gr.Column(scale=6):
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templateSelectDropdown = gr.Dropdown(label="从Prompt模板中加载", choices=load_template(get_template_names(plain=True)[0], mode=1), multiselect=False, value=load_template(get_template_names(plain=True)[0], mode=1)[0])
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with gr.Column(scale=1):
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templateApplyBtn = gr.Button("⬇️ 应用")
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with gr.Accordion(label="保存/加载对话历史记录", open=False):
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with gr.Column():
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with gr.
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with gr.
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user_input.submit(predict, [keyTxt, systemPromptTxt, history, user_input, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
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user_input.submit(reset_textbox, [], [user_input])
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submitBtn.click(predict, [keyTxt, systemPromptTxt, history, user_input, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
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submitBtn.click(reset_textbox, [], [user_input])
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emptyBtn.click(reset_state, outputs=[chatbot, history, token_count, status_display], show_progress=True)
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retryBtn.click(retry, [keyTxt, systemPromptTxt, history, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
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delLastBtn.click(delete_last_conversation, [chatbot, history, token_count
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chatbot, history, token_count, status_display], show_progress=True)
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reduceTokenBtn.click(reduce_token_size, [keyTxt, systemPromptTxt, history, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
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saveHistoryBtn.click(save_chat_history, [
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saveFileName, systemPromptTxt, history, chatbot], None, show_progress=True)
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historyRefreshBtn.click(get_history_names, None, [historyFileSelectDropdown])
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templateRefreshBtn.click(get_template_names, None, [templateFileSelectDropdown])
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# 默认开启本地服务器,默认可以直接从IP访问,默认不创建公开分享链接
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demo.title = "Chatbot"
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# -*- coding:utf-8 -*-
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import gradio as gr
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import os
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import logging
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import sys
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import argparse
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from utils import *
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from presets import *
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logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s")
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my_api_key = os.getenv("OpenAI-API") # 在这里输入你的 API 密钥
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if dockerflag:
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my_api_key = os.environ.get('my_api_key')
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if my_api_key == "empty":
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logging.error("Please give a api key!")
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sys.exit(1)
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#auth
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username = os.environ.get('USERNAME')
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gr.Chatbot.postprocess = postprocess
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with gr.Blocks(css=customCSS) as demo:
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history = gr.State([])
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token_count = gr.State([])
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promptTemplates = gr.State(load_template(get_template_names(plain=True)[0], mode=2))
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topic = gr.State("未命名对话历史记录")
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with gr.Row():
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gr.HTML(title)
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status_display = gr.Markdown("status: ready", elem_id="status_display")
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with gr.Row(scale=1).style(equal_height=True):
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with gr.Column(scale=5):
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with gr.Row(scale=1):
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chatbot = gr.Chatbot().style(height=600) # .style(color_map=("#1D51EE", "#585A5B"))
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with gr.Row(scale=1):
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with gr.Column(scale=12):
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user_input = gr.Textbox(show_label=False, placeholder="在这里输入").style(
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container=False)
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with gr.Column(min_width=50, scale=1):
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submitBtn = gr.Button("🚀", variant="primary")
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with gr.Row(scale=1):
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emptyBtn = gr.Button("🧹 新的对话",)
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retryBtn = gr.Button("🔄 重新生成")
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delLastBtn = gr.Button("🗑️ 删除一条对话")
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reduceTokenBtn = gr.Button("♻️ 总结对话")
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with gr.Column():
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with gr.Column(min_width=50,scale=1):
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with gr.Tab(label="ChatGPT"):
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keyTxt = gr.Textbox(show_label=True, placeholder=f"OpenAI API-key...",value=my_api_key, type="password", visible=not HIDE_MY_KEY, label="API-Key")
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model_select_dropdown = gr.Dropdown(label="选择模型", choices=MODELS, multiselect=False, value=MODELS[0])
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with gr.Accordion("参数", open=False):
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top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.05,
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interactive=True, label="Top-p (nucleus sampling)",)
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temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0,
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step=0.1, interactive=True, label="Temperature",)
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use_streaming_checkbox = gr.Checkbox(label="实时传输回答", value=True, visible=enable_streaming_option)
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use_websearch_checkbox = gr.Checkbox(label="使用在线搜索", value=False)
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with gr.Tab(label="Prompt"):
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systemPromptTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入System Prompt...", label="System prompt", value=initial_prompt).style(container=True)
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with gr.Accordion(label="加载Prompt模板", open=True):
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with gr.Column():
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with gr.Row():
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with gr.Column(scale=6):
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templateFileSelectDropdown = gr.Dropdown(label="选择Prompt模板集合文件", choices=get_template_names(plain=True), multiselect=False, value=get_template_names(plain=True)[0])
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with gr.Column(scale=1):
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templateRefreshBtn = gr.Button("🔄 刷新")
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with gr.Row():
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with gr.Column():
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templateSelectDropdown = gr.Dropdown(label="从Prompt模板中加载", choices=load_template(get_template_names(plain=True)[0], mode=1), multiselect=False, value=load_template(get_template_names(plain=True)[0], mode=1)[0])
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with gr.Tab(label="保存/加载"):
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with gr.Accordion(label="保存/加载对话历史记录", open=True):
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with gr.Column():
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with gr.Row():
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with gr.Column(scale=6):
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saveFileName = gr.Textbox(
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show_label=True, placeholder=f"在这里输入保存的文件名...", label="设置保存文件名", value="对话历史记录").style(container=True)
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with gr.Column(scale=1):
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saveHistoryBtn = gr.Button("💾 保存对话")
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with gr.Row():
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with gr.Column(scale=6):
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historyFileSelectDropdown = gr.Dropdown(label="从列表中加载对话", choices=get_history_names(plain=True), multiselect=False, value=get_history_names(plain=True)[0])
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with gr.Column(scale=1):
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historyRefreshBtn = gr.Button("🔄 刷新")
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gr.Markdown(description)
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user_input.submit(predict, [keyTxt, systemPromptTxt, history, user_input, chatbot, token_count, top_p, temperature, use_streaming_checkbox, model_select_dropdown, use_websearch_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
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user_input.submit(reset_textbox, [], [user_input])
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submitBtn.click(predict, [keyTxt, systemPromptTxt, history, user_input, chatbot, token_count, top_p, temperature, use_streaming_checkbox, model_select_dropdown, use_websearch_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
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submitBtn.click(reset_textbox, [], [user_input])
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emptyBtn.click(reset_state, outputs=[chatbot, history, token_count, status_display], show_progress=True)
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retryBtn.click(retry, [keyTxt, systemPromptTxt, history, chatbot, token_count, top_p, temperature, use_streaming_checkbox, model_select_dropdown], [chatbot, history, status_display, token_count], show_progress=True)
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delLastBtn.click(delete_last_conversation, [chatbot, history, token_count], [
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chatbot, history, token_count, status_display], show_progress=True)
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reduceTokenBtn.click(reduce_token_size, [keyTxt, systemPromptTxt, history, chatbot, token_count, top_p, temperature, use_streaming_checkbox, model_select_dropdown], [chatbot, history, status_display, token_count], show_progress=True)
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saveHistoryBtn.click(save_chat_history, [
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saveFileName, systemPromptTxt, history, chatbot], None, show_progress=True)
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historyRefreshBtn.click(get_history_names, None, [historyFileSelectDropdown])
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historyFileSelectDropdown.change(load_chat_history, [historyFileSelectDropdown, systemPromptTxt, history, chatbot], [saveFileName, systemPromptTxt, history, chatbot], show_progress=True)
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templateRefreshBtn.click(get_template_names, None, [templateFileSelectDropdown])
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templateFileSelectDropdown.change(load_template, [templateFileSelectDropdown], [promptTemplates, templateSelectDropdown], show_progress=True)
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templateSelectDropdown.change(get_template_content, [promptTemplates, templateSelectDropdown, systemPromptTxt], [systemPromptTxt], show_progress=True)
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logging.info(colorama.Back.GREEN + "\n温馨提示:访问 http://localhost:7860 查看界面" + colorama.Style.RESET_ALL)
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# 默认开启本地服务器,默认可以直接从IP访问,默认不创建公开分享链接
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demo.title = "Chatbot"
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README.md
CHANGED
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---
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title: Chatbot
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emoji: 💻
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colorFrom: yellow
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colorTo: red
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sdk: gradio
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sdk_version: 3.20.1
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app_file: Chatbot.py
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pinned: false
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---
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|
1 |
+
<img height="128" align="left" src="https://user-images.githubusercontent.com/51039745/222689546-7612df0e-e28b-4693-9f5f-4ef2be3daf48.png" alt="Logo">
|
2 |
+
|
3 |
+
# 川虎 ChatGPT 🐯 Chuanhu ChatGPT
|
4 |
+
|
5 |
+
[![LICENSE](https://img.shields.io/github/license/GaiZhenbiao/ChuanhuChatGPT)](https://github.com/GaiZhenbiao/ChuanhuChatGPT/blob/main/LICENSE)
|
6 |
+
[![Base](https://img.shields.io/badge/Base-Gradio-fb7d1a?style=flat)](https://gradio.app/)
|
7 |
+
[![Bilibili](https://img.shields.io/badge/Bilibili-%E8%A7%86%E9%A2%91%E6%95%99%E7%A8%8B-ff69b4?style=flat&logo=bilibili)](https://www.bilibili.com/video/BV1mo4y1r7eE)
|
8 |
+
|
9 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
10 |
|
11 |
+
为ChatGPT API提供了一个Web图形界面。在Bilibili上[观看视频教程](https://www.bilibili.com/video/BV1mo4y1r7eE/)。也可以在Hugging Face上[在线体验](https://huggingface.co/spaces/JohnSmith9982/ChuanhuChatGPT)。
|
12 |
+
|
13 |
+
![Animation Demo](https://user-images.githubusercontent.com/51039745/223148794-f4fd2fcb-3e48-4cdf-a759-7aa463d3f14c.gif)
|
14 |
+
|
15 |
+
|
16 |
+
## 重大更新 🎉🎉🎉
|
17 |
+
|
18 |
+
- 像官方ChatGPT那样实时回复
|
19 |
+
- 无限长度对话
|
20 |
+
- 从互联网搜索结果
|
21 |
+
- 改进的保存/加载功能
|
22 |
+
- 从Prompt模板中选择预设
|
23 |
+
- 将大段代码显示在代码块中
|
24 |
+
- 渲染输出中的LaTex公式
|
25 |
+
|
26 |
+
## 目录
|
27 |
+
|[功能](#功能)|[使用技巧](#使用技巧)|[安装方式](#安装方式)|[疑难杂症解决](#疑难杂症解决)|
|
28 |
+
| ---- | ---- | ---- | ---- |
|
29 |
+
|
30 |
+
|
31 |
+
## 功能
|
32 |
+
- [x] 像官方客户端那样支持实时显示回答!
|
33 |
+
- [x] 重试对话,让ChatGPT再回答一次。
|
34 |
+
- [x] 优化Tokens,减少Tokens占用,以支持更长的对话。
|
35 |
+
- [x] 设置System Prompt,有效地设定前置条件
|
36 |
+
- [x] 保存/加载对话历史记录
|
37 |
+
- [x] 在图形界面中添加API key
|
38 |
+
- [x] System Prompt模板功能,从预置的Prompt库中选择System Prompt
|
39 |
+
- [x] 实时显示Tokens用量
|
40 |
+
|
41 |
+
## 使用技巧
|
42 |
+
|
43 |
+
- 使用System Prompt可以很有效地设定前提条件
|
44 |
+
- 对于长对话,可以使用“优化Tokens”按钮减少Tokens占用。
|
45 |
+
- 如果部署到服务器,将程序最后一句改成`demo.launch(server_name="0.0.0.0", server_port=99999)`。其中`99999`是端口号,应该是1000-65535任意可用端口,请自行更改为实际端口号。
|
46 |
+
- 如果需要获取公共链接,将程序最后一句改成`demo.launch(share=True)`。注意程序必须在运行,才能通过公共链接访问
|
47 |
+
- 使用Prompt模板功能时,请先选择模板文件(`.csv`),然后点击载入按钮,然后就可以从下拉菜单中选择想要的prompt了,点击应用填入System Prmpt
|
48 |
+
- 输入框支持换行,按`shift enter`即可
|
49 |
+
- 在Hugging Face上使用时,建议在右上角**复制Space**再使用,这样能大大减少排队时间,App反应也会更加迅速。
|
50 |
+
<img width="300" alt="image" src="https://user-images.githubusercontent.com/51039745/223447310-e098a1f2-0dcf-48d6-bcc5-49472dd7ca0d.png">
|
51 |
+
|
52 |
+
## 安装方式
|
53 |
+
|
54 |
+
### 本地部署
|
55 |
+
|
56 |
+
1. **下载本项目**
|
57 |
+
|
58 |
+
```shell
|
59 |
+
git clone https://github.com/GaiZhenbiao/ChuanhuChatGPT.git
|
60 |
+
cd ChuanhuChatGPT
|
61 |
+
```
|
62 |
+
或者,点击网页右上角的 `Download ZIP`,下载并解压完成后进入文件夹,进入`终端`或`命令提示符`。
|
63 |
+
|
64 |
+
<img width="200" alt="downloadZIP" src="https://user-images.githubusercontent.com/23137268/223696317-b89d2c71-c74d-4c6d-8060-a21406cfb8c8.png">
|
65 |
+
|
66 |
+
2. **填写API密钥**
|
67 |
+
|
68 |
+
以下3种方法任选其一:
|
69 |
+
|
70 |
+
<details><summary>1. 在图形界面中填写你的API密钥</summary>
|
71 |
+
|
72 |
+
这样设置的密钥会在页面刷新后被清除。
|
73 |
+
|
74 |
+
<img width="760" alt="image" src="https://user-images.githubusercontent.com/51039745/222873756-3858bb82-30b9-49bc-9019-36e378ee624d.png"></details>
|
75 |
+
<details><summary>2. 在直接代码中填入你的 OpenAI API 密钥</summary>
|
76 |
+
|
77 |
+
这样设置的密钥会成为默认密钥。在这里还可以选择是否在UI中隐藏密钥输入框。
|
78 |
+
|
79 |
+
<img width="525" alt="image" src="https://user-images.githubusercontent.com/51039745/223440375-d472de4b-aa7f-4eae-9170-6dc2ed9f5480.png"></details>
|
80 |
+
|
81 |
+
<details><summary>3. 在文件中设定默认密钥、用户名密码</summary>
|
82 |
+
|
83 |
+
这样设置的密钥可以在拉取项目更新之后保留。
|
84 |
+
|
85 |
+
在项目文件夹中新建这两个文件:`api_key.txt` 和 `auth.json`。
|
86 |
+
|
87 |
+
在`api_key.txt`中填写你的API-Key,注意不要填写任何无关内容。
|
88 |
+
|
89 |
+
在`auth.json`中填写你的用户名和密码。
|
90 |
+
|
91 |
+
```
|
92 |
+
{
|
93 |
+
"username": "用户名",
|
94 |
+
"password": "密码"
|
95 |
+
}
|
96 |
+
```
|
97 |
+
|
98 |
+
</details>
|
99 |
+
|
100 |
+
3. **安装依赖**
|
101 |
+
|
102 |
+
```shell
|
103 |
+
pip install -r requirements.txt
|
104 |
+
```
|
105 |
+
|
106 |
+
如果报错,试试
|
107 |
+
|
108 |
+
```shell
|
109 |
+
pip3 install -r requirements.txt
|
110 |
+
```
|
111 |
+
|
112 |
+
如果还是不行,请先[安装Python](https://www.runoob.com/python/python-install.html)。
|
113 |
+
|
114 |
+
如果下载慢,建议[配置清华源](https://mirrors.tuna.tsinghua.edu.cn/help/pypi/),或者科学上网。
|
115 |
+
|
116 |
+
4. **启动**
|
117 |
+
|
118 |
+
```shell
|
119 |
+
python ChuanhuChatbot.py
|
120 |
+
```
|
121 |
+
|
122 |
+
如果报错,试试
|
123 |
+
|
124 |
+
```shell
|
125 |
+
python3 ChuanhuChatbot.py
|
126 |
+
```
|
127 |
+
|
128 |
+
如果还是不行,请先[安装Python](https://www.runoob.com/python/python-install.html)。
|
129 |
+
<br />
|
130 |
+
|
131 |
+
如果一切顺利,现在,你应该已经可以在浏览器地址栏中输入 [`http://localhost:7860`](http://localhost:7860) 查看并使用 ChuanhuChatGPT 了。
|
132 |
+
|
133 |
+
**如果你在安装过程中碰到了问题,请先查看[疑难杂症解决](#疑难杂症解决)部分。**
|
134 |
+
|
135 |
+
<details><summary><h3>或者,使用Docker 运行</h3></summary>
|
136 |
+
|
137 |
+
#### 拉取镜像
|
138 |
+
|
139 |
+
```shell
|
140 |
+
docker pull tuchuanhuhuhu/chuanhuchatgpt:latest
|
141 |
+
```
|
142 |
+
|
143 |
+
#### 运行
|
144 |
+
|
145 |
+
```shell
|
146 |
+
docker run -d --name chatgpt \
|
147 |
+
-e my_api_key="替换成API" \
|
148 |
+
-e USERNAME="替换成用户名" \
|
149 |
+
-e PASSWORD="替换成密码" \
|
150 |
+
-v ~/chatGPThistory:/app/history \
|
151 |
+
-p 7860:7860 \
|
152 |
+
tuchuanhuhuhu/chuanhuchatgpt:latest
|
153 |
+
```
|
154 |
+
|
155 |
+
注:`USERNAME` 和 `PASSWORD` 两行可省略。若省略则不会启用认证。
|
156 |
+
|
157 |
+
#### 查看运行状态
|
158 |
+
```shell
|
159 |
+
docker logs chatgpt
|
160 |
+
```
|
161 |
+
|
162 |
+
#### 也可修改脚本后手动构建镜像
|
163 |
+
|
164 |
+
```shell
|
165 |
+
docker build -t chuanhuchatgpt:latest .
|
166 |
+
```
|
167 |
+
</details>
|
168 |
+
|
169 |
+
|
170 |
+
### 远程部署
|
171 |
+
|
172 |
+
<details><summary>如果需要在公网服务器部署本项目,请阅读本部分</summary>
|
173 |
+
|
174 |
+
### 部署到公网服务器
|
175 |
+
|
176 |
+
将最后一句修改为
|
177 |
+
|
178 |
+
```
|
179 |
+
demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False) # 可自定义端口
|
180 |
+
```
|
181 |
+
### 用账号密码保护页面
|
182 |
+
|
183 |
+
将最后一句修改为
|
184 |
+
|
185 |
+
```
|
186 |
+
demo.queue().launch(server_name="0.0.0.0", server_port=7860,auth=("在这里填写用户名", "在这里填写密码")) # 可设置用户名与密码
|
187 |
+
```
|
188 |
+
|
189 |
+
### 配置 Nginx 反向代理
|
190 |
+
|
191 |
+
注意:配置反向代理不是必须的。如果需要使用域名,则需要配置 Nginx 反向代理。
|
192 |
+
|
193 |
+
又及:目前配置认证后,Nginx 必须配置 SSL,否则会出现 [Cookie 不匹配问题](https://github.com/GaiZhenbiao/ChuanhuChatGPT/issues/89)。
|
194 |
+
|
195 |
+
添加独立配置文件:
|
196 |
+
```nginx
|
197 |
+
server {
|
198 |
+
listen 80;
|
199 |
+
server_name /域名/; # 请填入你设定的域名
|
200 |
+
access_log off;
|
201 |
+
error_log off;
|
202 |
+
location / {
|
203 |
+
proxy_pass http://127.0.0.1:7860; # 注意端口号
|
204 |
+
proxy_redirect off;
|
205 |
+
proxy_set_header Host $host;
|
206 |
+
proxy_set_header X-Real-IP $remote_addr;
|
207 |
+
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
|
208 |
+
proxy_set_header Upgrade $http_upgrade; # Websocket配置
|
209 |
+
proxy_set_header Connection $connection_upgrade; #Websocket配置
|
210 |
+
proxy_max_temp_file_size 0;
|
211 |
+
client_max_body_size 10m;
|
212 |
+
client_body_buffer_size 128k;
|
213 |
+
proxy_connect_timeout 90;
|
214 |
+
proxy_send_timeout 90;
|
215 |
+
proxy_read_timeout 90;
|
216 |
+
proxy_buffer_size 4k;
|
217 |
+
proxy_buffers 4 32k;
|
218 |
+
proxy_busy_buffers_size 64k;
|
219 |
+
proxy_temp_file_write_size 64k;
|
220 |
+
}
|
221 |
+
}
|
222 |
+
```
|
223 |
+
|
224 |
+
修改`nginx.conf`配置文件(通常在`/etc/nginx/nginx.conf`),向http部分添加如下配置:
|
225 |
+
(这一步是为了配置websocket连接,如之前配置过可忽略)
|
226 |
+
```nginx
|
227 |
+
map $http_upgrade $connection_upgrade {
|
228 |
+
default upgrade;
|
229 |
+
'' close;
|
230 |
+
}
|
231 |
+
```
|
232 |
+
|
233 |
+
为了同时配置域名访问和身份认证,需要配置SSL的证书,可以参考[这篇博客](https://www.gzblog.tech/2020/12/25/how-to-config-hexo/#%E9%85%8D%E7%BD%AEHTTPS)一键配置
|
234 |
+
|
235 |
+
</details>
|
236 |
+
|
237 |
+
## 疑难杂症解决
|
238 |
+
|
239 |
+
首先,请尝试拉取本项目的最新更改,使用最新的代码重试。
|
240 |
+
|
241 |
+
点击网页上的 `Download ZIP` 下载最新代码,或
|
242 |
+
```shell
|
243 |
+
git pull https://github.com/GaiZhenbiao/ChuanhuChatGPT.git main -f
|
244 |
+
```
|
245 |
+
|
246 |
+
如果还有问题,可以再尝试重装 gradio:
|
247 |
+
|
248 |
+
```
|
249 |
+
pip install gradio --upgrade --force-reinstall
|
250 |
+
```
|
251 |
+
|
252 |
+
很多时候,这样就可以解决问题。
|
253 |
+
|
254 |
+
<details><summary><h3><code>No module named '_bz2'</code></h3></summary>
|
255 |
+
|
256 |
+
> 部署在CentOS7.6,Python3.11.0上,最后报错ModuleNotFoundError: No module named '_bz2'
|
257 |
+
|
258 |
+
安装python前先下载 `bzip` 编译环境
|
259 |
+
|
260 |
+
```
|
261 |
+
sudo yum install bzip2-devel
|
262 |
+
```
|
263 |
+
</details>
|
264 |
+
|
265 |
+
<details><summary><h3><code>openai.error.APIConnectionError</code></h3></summary>
|
266 |
+
|
267 |
+
> 如果有人也出现了`openai.error.APIConnectionError`提示的报错,那可能是`urllib3`的版本导致的。`urllib3`版本大于`1.25.11`,就会出现这个问题。
|
268 |
+
>
|
269 |
+
> 解决方案是卸载`urllib3`然后重装至`1.25.11`版本再重新运行一遍就可以
|
270 |
+
|
271 |
+
参见:[#5](https://github.com/GaiZhenbiao/ChuanhuChatGPT/issues/5)
|
272 |
+
|
273 |
+
在终端或命令提示符中卸载`urllib3`
|
274 |
+
|
275 |
+
```
|
276 |
+
pip uninstall urllib3
|
277 |
+
```
|
278 |
+
|
279 |
+
然后,通过使用指定版本号的`pip install`命令来安装所需的版本:
|
280 |
+
|
281 |
+
```
|
282 |
+
pip install urllib3==1.25.11
|
283 |
+
```
|
284 |
+
|
285 |
+
参考自:
|
286 |
+
[解决OpenAI API 挂了代理还是连接不上的问题](https://zhuanlan.zhihu.com/p/611080662)
|
287 |
+
</details>
|
288 |
+
|
289 |
+
<details><summary><h3>在 Python 文件里 设定 API Key 之后验证失败</h3></summary>
|
290 |
+
|
291 |
+
> 在ChuanhuChatbot.py中设置APIkey后验证出错,提示“发生了未知错误Orz”
|
292 |
+
|
293 |
+
参见:[#26](https://github.com/GaiZhenbiao/ChuanhuChatGPT/issues/26)
|
294 |
+
</details>
|
295 |
+
|
296 |
+
<details><summary><h3>一直等待/SSL Error</h3></summary>
|
297 |
+
|
298 |
+
> 更新脚本文件后,SSLError [#49](https://github.com/GaiZhenbiao/ChuanhuChatGPT/issues/49)
|
299 |
+
>
|
300 |
+
> 跑起来之后,输入问题好像就没反应了,也没报错 [#25](https://github.com/GaiZhenbiao/ChuanhuChatGPT/issues/25)
|
301 |
+
>
|
302 |
+
> ```
|
303 |
+
> requests.exceptions.SSLError: HTTPSConnectionPool(host='api.openai.com', port=443): Max retries exceeded with url: /v1/chat/completions (Caused by SSLError(SSLEOFError(8, 'EOF occurred in violation of protocol (_ssl.c:1129)')))
|
304 |
+
> ```
|
305 |
+
|
306 |
+
请将`openai.com`加入你使用的代理App的代理规则。注意不要将`127.0.0.1`加入代理,否则会有下一个错误。
|
307 |
+
|
308 |
+
例如,在Clash配置文件中,加入:
|
309 |
+
|
310 |
+
```
|
311 |
+
rule-providers:
|
312 |
+
private:
|
313 |
+
type: http
|
314 |
+
behavior: domain
|
315 |
+
url: "https://cdn.jsdelivr.net/gh/Loyalsoldier/clash-rules@release/lancidr.txt"
|
316 |
+
path: ./ruleset/ads.yaml
|
317 |
+
interval: 86400
|
318 |
+
|
319 |
+
rules:
|
320 |
+
- RULE-SET,private,DIRECT
|
321 |
+
- DOMAIN-SUFFIX,openai.com,你的代理规则
|
322 |
+
```
|
323 |
+
|
324 |
+
Surge:
|
325 |
+
|
326 |
+
```
|
327 |
+
[Rule]
|
328 |
+
DOMAIN-SET,https://cdn.jsdelivr.net/gh/Loyalsoldier/surge-rules@release/private.txt,DIRECT
|
329 |
+
DOMAIN-SUFFIX,openai.com,你的代理规则
|
330 |
+
```
|
331 |
+
</details>
|
332 |
+
|
333 |
+
<details><summary><h3>网页提示错误 Something went wrong</h3></summary>
|
334 |
+
|
335 |
+
> ```
|
336 |
+
> Something went wrong
|
337 |
+
> Expecting value: 1ine 1 column 1 (char o)
|
338 |
+
> ```
|
339 |
+
|
340 |
+
出现这个错误的原因是`127.0.0.1`被代理了,导致网页无法和后端通信。请设置代理软件,将`127.0.0.1`加入直连。
|
341 |
+
</details>
|
342 |
+
|
343 |
+
<details><summary><h3><code>No matching distribution found for openai>=0.27.0</code></h3></summary>
|
344 |
+
|
345 |
+
`openai`这个依赖已经被移除了。请尝试下载最新版脚本。
|
346 |
+
</details>
|
347 |
+
|
348 |
+
## Starchart
|
349 |
+
|
350 |
+
[![Star History Chart](https://api.star-history.com/svg?repos=GaiZhenbiao/ChuanhuChatGPT&type=Date)](https://star-history.com/#GaiZhenbiao/ChuanhuChatGPT&Date)
|
351 |
+
|
352 |
+
## Contributors
|
353 |
+
|
354 |
+
<a href="https://github.com/GaiZhenbiao/ChuanhuChatGPT/graphs/contributors">
|
355 |
+
<img src="https://contrib.rocks/image?repo=GaiZhenbiao/ChuanhuChatGPT" />
|
356 |
+
</a>
|
357 |
+
|
358 |
+
## 捐款
|
359 |
+
|
360 |
+
🐯请作者喝可乐~
|
361 |
+
|
362 |
+
<img width="350" alt="image" src="https://user-images.githubusercontent.com/51039745/223626874-f471e5f5-8a06-43d5-aa31-9d2575b6f631.JPG">
|
presets.py
CHANGED
@@ -1,13 +1,39 @@
|
|
1 |
-
|
2 |
-
|
|
|
3 |
|
4 |
-
|
5 |
-
|
6 |
-
Chatbot Mar 12 Version.
|
7 |
|
8 |
</div>
|
9 |
"""
|
10 |
customCSS = """
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
11 |
code {
|
12 |
display: inline;
|
13 |
white-space: break-spaces;
|
@@ -27,14 +53,35 @@ pre code {
|
|
27 |
color: #FFF;
|
28 |
box-shadow: inset 0px 8px 16px hsla(0, 0%, 0%, .2)
|
29 |
}
|
|
|
|
|
|
|
|
|
30 |
"""
|
31 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
32 |
standard_error_msg = "☹️发生了错误:" # 错误信息的标准前缀
|
33 |
-
error_retrieve_prompt = "
|
34 |
-
|
35 |
-
|
36 |
-
|
37 |
-
|
|
|
|
|
|
|
|
|
|
|
38 |
timeout_all = 200 # 非流式对话时的超时时间
|
39 |
-
enable_streaming_option =
|
40 |
HIDE_MY_KEY = True # 如果你想在UI中隐藏你的 API 密钥,将此值设置为 True
|
|
|
1 |
+
# -*- coding:utf-8 -*-
|
2 |
+
title = """<h1 align="left" style="min-width:200px; margin-top:0;"></h1>"""
|
3 |
+
description = """<div align="center" style="margin:16px 0">
|
4 |
|
5 |
+
Chatbot Mar 17 Version.
|
|
|
|
|
6 |
|
7 |
</div>
|
8 |
"""
|
9 |
customCSS = """
|
10 |
+
#status_display {
|
11 |
+
display: flex;
|
12 |
+
min-height: 2.5em;
|
13 |
+
align-items: flex-end;
|
14 |
+
justify-content: flex-end;
|
15 |
+
}
|
16 |
+
#status_display p {
|
17 |
+
font-size: .85em;
|
18 |
+
font-family: monospace;
|
19 |
+
color: var(--text-color-subdued) !important;
|
20 |
+
}
|
21 |
+
[class *= "message"] {
|
22 |
+
border-radius: var(--radius-xl) !important;
|
23 |
+
border: none;
|
24 |
+
padding: var(--spacing-xl) !important;
|
25 |
+
font-size: var(--text-md) !important;
|
26 |
+
line-height: var(--line-md) !important;
|
27 |
+
}
|
28 |
+
[data-testid = "bot"] {
|
29 |
+
max-width: 85%;
|
30 |
+
border-bottom-left-radius: 0 !important;
|
31 |
+
}
|
32 |
+
[data-testid = "user"] {
|
33 |
+
max-width: 85%;
|
34 |
+
width: auto !important;
|
35 |
+
border-bottom-right-radius: 0 !important;
|
36 |
+
}
|
37 |
code {
|
38 |
display: inline;
|
39 |
white-space: break-spaces;
|
|
|
53 |
color: #FFF;
|
54 |
box-shadow: inset 0px 8px 16px hsla(0, 0%, 0%, .2)
|
55 |
}
|
56 |
+
|
57 |
+
* {
|
58 |
+
transition: all 0.6s;
|
59 |
+
}
|
60 |
"""
|
61 |
|
62 |
+
summarize_prompt = "你是谁?我们刚才聊了什么?" # 总结对话时的 prompt
|
63 |
+
MODELS = ["gpt-3.5-turbo", "gpt-3.5-turbo-0301", "gpt-4","gpt-4-0314", "gpt-4-32k", "gpt-4-32k-0314"] # 可选的模型
|
64 |
+
websearch_prompt = """Web search results:
|
65 |
+
|
66 |
+
{web_results}
|
67 |
+
Current date: {current_date}
|
68 |
+
|
69 |
+
Instructions: Using the provided web search results, write a comprehensive reply to the given query. Make sure to cite results using [[number](URL)] notation after the reference. If the provided search results refer to multiple subjects with the same name, write separate answers for each subject.
|
70 |
+
Query: {query}
|
71 |
+
Reply in 中文"""
|
72 |
+
|
73 |
+
# 错误信息
|
74 |
standard_error_msg = "☹️发生了错误:" # 错误信息的标准前缀
|
75 |
+
error_retrieve_prompt = "请检查网络连接,或者API-Key是否有效。" # 获取对话时发生错误
|
76 |
+
connection_timeout_prompt = "连接超时,无法获取对话。" # 连接超时
|
77 |
+
read_timeout_prompt = "读取超时,无法获取对话。" # 读取超时
|
78 |
+
proxy_error_prompt = "代理错误,无法获取对话。" # 代理错误
|
79 |
+
ssl_error_prompt = "SSL错误,无法获取对话。" # SSL 错误
|
80 |
+
no_apikey_msg = "API key长度不是51位,请检查是否输入正确。" # API key 长度不足 51 位
|
81 |
+
|
82 |
+
max_token_streaming = 3500 # 流式对话时的最大 token 数
|
83 |
+
timeout_streaming = 15 # 流式对话时的超时时间
|
84 |
+
max_token_all = 3500 # 非流式对话时的最大 token 数
|
85 |
timeout_all = 200 # 非流式对话时的超时时间
|
86 |
+
enable_streaming_option = True # 是否启用选择选择是否实时显示回答的勾选框
|
87 |
HIDE_MY_KEY = True # 如果你想在UI中隐藏你的 API 密钥,将此值设置为 True
|
requirements.txt
CHANGED
@@ -1,3 +1,8 @@
|
|
1 |
gradio
|
2 |
mdtex2html
|
3 |
pypinyin
|
|
|
|
|
|
|
|
|
|
|
|
1 |
gradio
|
2 |
mdtex2html
|
3 |
pypinyin
|
4 |
+
tiktoken
|
5 |
+
socksio
|
6 |
+
tqdm
|
7 |
+
colorama
|
8 |
+
duckduckgo_search
|
utils.py
CHANGED
@@ -1,9 +1,7 @@
|
|
1 |
-
|
2 |
-
Along with the docs for each component, you can find the names of example demos that use
|
3 |
-
each component. These demos are located in the `demo` directory."""
|
4 |
-
|
5 |
from __future__ import annotations
|
6 |
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Tuple, Type
|
|
|
7 |
import json
|
8 |
import gradio as gr
|
9 |
# import openai
|
@@ -15,6 +13,13 @@ import csv
|
|
15 |
import mdtex2html
|
16 |
from pypinyin import lazy_pinyin
|
17 |
from presets import *
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
18 |
|
19 |
if TYPE_CHECKING:
|
20 |
from typing import TypedDict
|
@@ -23,7 +28,7 @@ if TYPE_CHECKING:
|
|
23 |
headers: List[str]
|
24 |
data: List[List[str | int | bool]]
|
25 |
|
26 |
-
initial_prompt = "
|
27 |
API_URL = "https://api.openai.com/v1/chat/completions"
|
28 |
HISTORY_DIR = "history"
|
29 |
TEMPLATES_DIR = "templates"
|
@@ -48,6 +53,11 @@ def postprocess(
|
|
48 |
)
|
49 |
return y
|
50 |
|
|
|
|
|
|
|
|
|
|
|
51 |
def parse_text(text):
|
52 |
lines = text.split("\n")
|
53 |
lines = [line for line in lines if line != ""]
|
@@ -92,10 +102,9 @@ def construct_assistant(text):
|
|
92 |
return construct_text("assistant", text)
|
93 |
|
94 |
def construct_token_message(token, stream=False):
|
95 |
-
|
96 |
-
return f"{extra}Token 计数: {token}"
|
97 |
|
98 |
-
def get_response(openai_api_key, system_prompt, history, temperature, top_p, stream):
|
99 |
headers = {
|
100 |
"Content-Type": "application/json",
|
101 |
"Authorization": f"Bearer {openai_api_key}"
|
@@ -104,7 +113,7 @@ def get_response(openai_api_key, system_prompt, history, temperature, top_p, str
|
|
104 |
history = [construct_system(system_prompt), *history]
|
105 |
|
106 |
payload = {
|
107 |
-
"model":
|
108 |
"messages": history, # [{"role": "user", "content": f"{inputs}"}],
|
109 |
"temperature": temperature, # 1.0,
|
110 |
"top_p": top_p, # 1.0,
|
@@ -120,25 +129,41 @@ def get_response(openai_api_key, system_prompt, history, temperature, top_p, str
|
|
120 |
response = requests.post(API_URL, headers=headers, json=payload, stream=True, timeout=timeout)
|
121 |
return response
|
122 |
|
123 |
-
def stream_predict(openai_api_key, system_prompt, history, inputs, chatbot,
|
124 |
def get_return_value():
|
125 |
-
return chatbot, history, status_text,
|
126 |
-
|
|
|
127 |
partial_words = ""
|
128 |
counter = 0
|
129 |
-
status_text = "
|
130 |
history.append(construct_user(inputs))
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
131 |
try:
|
132 |
-
response = get_response(openai_api_key, system_prompt, history, temperature, top_p, True)
|
133 |
except requests.exceptions.ConnectTimeout:
|
134 |
-
status_text = standard_error_msg + error_retrieve_prompt
|
|
|
|
|
|
|
|
|
135 |
yield get_return_value()
|
136 |
return
|
137 |
|
138 |
-
chatbot.append((parse_text(inputs), ""))
|
139 |
yield get_return_value()
|
|
|
140 |
|
141 |
-
for chunk in response.iter_lines():
|
142 |
if counter == 0:
|
143 |
counter += 1
|
144 |
continue
|
@@ -147,130 +172,200 @@ def stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, prev
|
|
147 |
if chunk:
|
148 |
chunk = chunk.decode()
|
149 |
chunklength = len(chunk)
|
150 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
151 |
# decode each line as response data is in bytes
|
152 |
if chunklength > 6 and "delta" in chunk['choices'][0]:
|
153 |
finish_reason = chunk['choices'][0]['finish_reason']
|
154 |
-
status_text = construct_token_message(sum(
|
155 |
if finish_reason == "stop":
|
156 |
yield get_return_value()
|
157 |
break
|
158 |
-
|
159 |
-
|
160 |
-
|
161 |
-
|
162 |
-
|
|
|
|
|
163 |
chatbot[-1] = (parse_text(inputs), parse_text(partial_words))
|
164 |
-
|
165 |
yield get_return_value()
|
166 |
|
167 |
|
168 |
-
def predict_all(openai_api_key, system_prompt, history, inputs, chatbot,
|
|
|
169 |
history.append(construct_user(inputs))
|
|
|
|
|
|
|
170 |
try:
|
171 |
-
response = get_response(openai_api_key, system_prompt, history, temperature, top_p, False)
|
172 |
except requests.exceptions.ConnectTimeout:
|
173 |
-
status_text = standard_error_msg + error_retrieve_prompt
|
174 |
-
return chatbot, history, status_text,
|
|
|
|
|
|
|
|
|
|
|
|
|
175 |
response = json.loads(response.text)
|
176 |
content = response["choices"][0]["message"]["content"]
|
177 |
-
history
|
178 |
-
chatbot
|
179 |
total_token_count = response["usage"]["total_tokens"]
|
180 |
-
|
181 |
status_text = construct_token_message(total_token_count)
|
182 |
-
return chatbot, history, status_text,
|
183 |
-
|
184 |
-
|
185 |
-
def predict(openai_api_key, system_prompt, history, inputs, chatbot,
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
186 |
if stream:
|
187 |
-
|
188 |
-
|
189 |
-
|
|
|
190 |
else:
|
191 |
-
|
192 |
-
|
|
|
|
|
|
|
|
|
193 |
if stream:
|
194 |
max_token = max_token_streaming
|
195 |
else:
|
196 |
max_token = max_token_all
|
197 |
-
if sum(
|
198 |
-
|
199 |
-
|
200 |
-
|
201 |
-
|
202 |
-
|
203 |
-
|
204 |
-
|
|
|
|
|
|
|
|
|
205 |
if len(history) == 0:
|
206 |
yield chatbot, history, f"{standard_error_msg}上下文是空的", token_count
|
207 |
return
|
208 |
history.pop()
|
209 |
inputs = history.pop()["content"]
|
210 |
token_count.pop()
|
211 |
-
iter = predict(openai_api_key, system_prompt, history, inputs, chatbot, token_count, top_p, temperature, stream=stream)
|
|
|
212 |
for x in iter:
|
213 |
yield x
|
214 |
|
215 |
|
216 |
-
def reduce_token_size(openai_api_key, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False, hidden=False):
|
217 |
-
|
|
|
|
|
218 |
for chatbot, history, status_text, previous_token_count in iter:
|
219 |
history = history[-2:]
|
220 |
token_count = previous_token_count[-1:]
|
221 |
if hidden:
|
222 |
chatbot.pop()
|
223 |
yield chatbot, history, construct_token_message(sum(token_count), stream=stream), token_count
|
|
|
224 |
|
225 |
|
226 |
-
def delete_last_conversation(chatbot, history, previous_token_count
|
227 |
if len(chatbot) > 0 and standard_error_msg in chatbot[-1][1]:
|
|
|
228 |
chatbot.pop()
|
229 |
return chatbot, history
|
230 |
if len(history) > 0:
|
|
|
231 |
history.pop()
|
232 |
history.pop()
|
233 |
if len(chatbot) > 0:
|
|
|
234 |
chatbot.pop()
|
235 |
if len(previous_token_count) > 0:
|
|
|
236 |
previous_token_count.pop()
|
237 |
-
return chatbot, history, previous_token_count, construct_token_message(sum(previous_token_count)
|
238 |
|
239 |
|
240 |
def save_chat_history(filename, system, history, chatbot):
|
|
|
241 |
if filename == "":
|
242 |
return
|
243 |
if not filename.endswith(".json"):
|
244 |
filename += ".json"
|
245 |
os.makedirs(HISTORY_DIR, exist_ok=True)
|
246 |
json_s = {"system": system, "history": history, "chatbot": chatbot}
|
247 |
-
|
248 |
with open(os.path.join(HISTORY_DIR, filename), "w") as f:
|
249 |
-
json.dump(json_s, f)
|
|
|
250 |
|
251 |
|
252 |
def load_chat_history(filename, system, history, chatbot):
|
|
|
253 |
try:
|
254 |
with open(os.path.join(HISTORY_DIR, filename), "r") as f:
|
255 |
json_s = json.load(f)
|
256 |
-
|
257 |
-
|
258 |
-
|
259 |
-
|
260 |
-
|
261 |
-
|
262 |
-
|
263 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
264 |
return filename, json_s["system"], json_s["history"], json_s["chatbot"]
|
265 |
except FileNotFoundError:
|
266 |
-
|
267 |
return filename, system, history, chatbot
|
268 |
|
269 |
def sorted_by_pinyin(list):
|
270 |
return sorted(list, key=lambda char: lazy_pinyin(char)[0][0])
|
271 |
|
272 |
def get_file_names(dir, plain=False, filetypes=[".json"]):
|
273 |
-
|
274 |
files = []
|
275 |
try:
|
276 |
for type in filetypes:
|
@@ -286,11 +381,13 @@ def get_file_names(dir, plain=False, filetypes=[".json"]):
|
|
286 |
return gr.Dropdown.update(choices=files)
|
287 |
|
288 |
def get_history_names(plain=False):
|
|
|
289 |
return get_file_names(HISTORY_DIR, plain)
|
290 |
|
291 |
def load_template(filename, mode=0):
|
|
|
292 |
lines = []
|
293 |
-
|
294 |
if filename.endswith(".json"):
|
295 |
with open(os.path.join(TEMPLATES_DIR, filename), "r", encoding="utf8") as f:
|
296 |
lines = json.load(f)
|
@@ -309,24 +406,19 @@ def load_template(filename, mode=0):
|
|
309 |
return {row[0]:row[1] for row in lines}, gr.Dropdown.update(choices=choices, value=choices[0])
|
310 |
|
311 |
def get_template_names(plain=False):
|
|
|
312 |
return get_file_names(TEMPLATES_DIR, plain, filetypes=[".csv", "json"])
|
313 |
|
314 |
def get_template_content(templates, selection, original_system_prompt):
|
|
|
315 |
try:
|
316 |
return templates[selection]
|
317 |
except:
|
318 |
return original_system_prompt
|
319 |
|
320 |
def reset_state():
|
|
|
321 |
return [], [], [], construct_token_message(0)
|
322 |
|
323 |
-
def compose_system(system_prompt):
|
324 |
-
return {"role": "system", "content": system_prompt}
|
325 |
-
|
326 |
-
|
327 |
-
def compose_user(user_input):
|
328 |
-
return {"role": "user", "content": user_input}
|
329 |
-
|
330 |
-
|
331 |
def reset_textbox():
|
332 |
return gr.update(value='')
|
|
|
1 |
+
# -*- coding:utf-8 -*-
|
|
|
|
|
|
|
2 |
from __future__ import annotations
|
3 |
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Tuple, Type
|
4 |
+
import logging
|
5 |
import json
|
6 |
import gradio as gr
|
7 |
# import openai
|
|
|
13 |
import mdtex2html
|
14 |
from pypinyin import lazy_pinyin
|
15 |
from presets import *
|
16 |
+
import tiktoken
|
17 |
+
from tqdm import tqdm
|
18 |
+
import colorama
|
19 |
+
from duckduckgo_search import ddg
|
20 |
+
import datetime
|
21 |
+
|
22 |
+
# logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s")
|
23 |
|
24 |
if TYPE_CHECKING:
|
25 |
from typing import TypedDict
|
|
|
28 |
headers: List[str]
|
29 |
data: List[List[str | int | bool]]
|
30 |
|
31 |
+
initial_prompt = "You are a helpful assistant."
|
32 |
API_URL = "https://api.openai.com/v1/chat/completions"
|
33 |
HISTORY_DIR = "history"
|
34 |
TEMPLATES_DIR = "templates"
|
|
|
53 |
)
|
54 |
return y
|
55 |
|
56 |
+
def count_token(input_str):
|
57 |
+
encoding = tiktoken.get_encoding("cl100k_base")
|
58 |
+
length = len(encoding.encode(input_str))
|
59 |
+
return length
|
60 |
+
|
61 |
def parse_text(text):
|
62 |
lines = text.split("\n")
|
63 |
lines = [line for line in lines if line != ""]
|
|
|
102 |
return construct_text("assistant", text)
|
103 |
|
104 |
def construct_token_message(token, stream=False):
|
105 |
+
return f"Token 计数: {token}"
|
|
|
106 |
|
107 |
+
def get_response(openai_api_key, system_prompt, history, temperature, top_p, stream, selected_model):
|
108 |
headers = {
|
109 |
"Content-Type": "application/json",
|
110 |
"Authorization": f"Bearer {openai_api_key}"
|
|
|
113 |
history = [construct_system(system_prompt), *history]
|
114 |
|
115 |
payload = {
|
116 |
+
"model": selected_model,
|
117 |
"messages": history, # [{"role": "user", "content": f"{inputs}"}],
|
118 |
"temperature": temperature, # 1.0,
|
119 |
"top_p": top_p, # 1.0,
|
|
|
129 |
response = requests.post(API_URL, headers=headers, json=payload, stream=True, timeout=timeout)
|
130 |
return response
|
131 |
|
132 |
+
def stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, selected_model):
|
133 |
def get_return_value():
|
134 |
+
return chatbot, history, status_text, all_token_counts
|
135 |
+
|
136 |
+
logging.info("实时回答模式")
|
137 |
partial_words = ""
|
138 |
counter = 0
|
139 |
+
status_text = "开始实时传输回答……"
|
140 |
history.append(construct_user(inputs))
|
141 |
+
history.append(construct_assistant(""))
|
142 |
+
chatbot.append((parse_text(inputs), ""))
|
143 |
+
user_token_count = 0
|
144 |
+
if len(all_token_counts) == 0:
|
145 |
+
system_prompt_token_count = count_token(system_prompt)
|
146 |
+
user_token_count = count_token(inputs) + system_prompt_token_count
|
147 |
+
else:
|
148 |
+
user_token_count = count_token(inputs)
|
149 |
+
all_token_counts.append(user_token_count)
|
150 |
+
logging.info(f"输入token计数: {user_token_count}")
|
151 |
+
yield get_return_value()
|
152 |
try:
|
153 |
+
response = get_response(openai_api_key, system_prompt, history, temperature, top_p, True, selected_model)
|
154 |
except requests.exceptions.ConnectTimeout:
|
155 |
+
status_text = standard_error_msg + connection_timeout_prompt + error_retrieve_prompt
|
156 |
+
yield get_return_value()
|
157 |
+
return
|
158 |
+
except requests.exceptions.ReadTimeout:
|
159 |
+
status_text = standard_error_msg + read_timeout_prompt + error_retrieve_prompt
|
160 |
yield get_return_value()
|
161 |
return
|
162 |
|
|
|
163 |
yield get_return_value()
|
164 |
+
error_json_str = ""
|
165 |
|
166 |
+
for chunk in tqdm(response.iter_lines()):
|
167 |
if counter == 0:
|
168 |
counter += 1
|
169 |
continue
|
|
|
172 |
if chunk:
|
173 |
chunk = chunk.decode()
|
174 |
chunklength = len(chunk)
|
175 |
+
try:
|
176 |
+
chunk = json.loads(chunk[6:])
|
177 |
+
except json.JSONDecodeError:
|
178 |
+
logging.info(chunk)
|
179 |
+
error_json_str += chunk
|
180 |
+
status_text = f"JSON解析错误。请重置对话。收到的内容: {error_json_str}"
|
181 |
+
yield get_return_value()
|
182 |
+
continue
|
183 |
# decode each line as response data is in bytes
|
184 |
if chunklength > 6 and "delta" in chunk['choices'][0]:
|
185 |
finish_reason = chunk['choices'][0]['finish_reason']
|
186 |
+
status_text = construct_token_message(sum(all_token_counts), stream=True)
|
187 |
if finish_reason == "stop":
|
188 |
yield get_return_value()
|
189 |
break
|
190 |
+
try:
|
191 |
+
partial_words = partial_words + chunk['choices'][0]["delta"]["content"]
|
192 |
+
except KeyError:
|
193 |
+
status_text = standard_error_msg + "API回复中找不到内容。很可能是Token计数达到上限了。请重置对话。当前Token计数: " + str(sum(all_token_counts))
|
194 |
+
yield get_return_value()
|
195 |
+
break
|
196 |
+
history[-1] = construct_assistant(partial_words)
|
197 |
chatbot[-1] = (parse_text(inputs), parse_text(partial_words))
|
198 |
+
all_token_counts[-1] += 1
|
199 |
yield get_return_value()
|
200 |
|
201 |
|
202 |
+
def predict_all(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, selected_model):
|
203 |
+
logging.info("一次性回答模式")
|
204 |
history.append(construct_user(inputs))
|
205 |
+
history.append(construct_assistant(""))
|
206 |
+
chatbot.append((parse_text(inputs), ""))
|
207 |
+
all_token_counts.append(count_token(inputs))
|
208 |
try:
|
209 |
+
response = get_response(openai_api_key, system_prompt, history, temperature, top_p, False, selected_model)
|
210 |
except requests.exceptions.ConnectTimeout:
|
211 |
+
status_text = standard_error_msg + connection_timeout_prompt + error_retrieve_prompt
|
212 |
+
return chatbot, history, status_text, all_token_counts
|
213 |
+
except requests.exceptions.ProxyError:
|
214 |
+
status_text = standard_error_msg + proxy_error_prompt + error_retrieve_prompt
|
215 |
+
return chatbot, history, status_text, all_token_counts
|
216 |
+
except requests.exceptions.SSLError:
|
217 |
+
status_text = standard_error_msg + ssl_error_prompt + error_retrieve_prompt
|
218 |
+
return chatbot, history, status_text, all_token_counts
|
219 |
response = json.loads(response.text)
|
220 |
content = response["choices"][0]["message"]["content"]
|
221 |
+
history[-1] = construct_assistant(content)
|
222 |
+
chatbot[-1] = (parse_text(inputs), parse_text(content))
|
223 |
total_token_count = response["usage"]["total_tokens"]
|
224 |
+
all_token_counts[-1] = total_token_count - sum(all_token_counts)
|
225 |
status_text = construct_token_message(total_token_count)
|
226 |
+
return chatbot, history, status_text, all_token_counts
|
227 |
+
|
228 |
+
|
229 |
+
def predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, stream=False, selected_model = MODELS[0], use_websearch_checkbox = False, should_check_token_count = True): # repetition_penalty, top_k
|
230 |
+
logging.info("输入为:" +colorama.Fore.BLUE + f"{inputs}" + colorama.Style.RESET_ALL)
|
231 |
+
if use_websearch_checkbox:
|
232 |
+
results = ddg(inputs, max_results=3)
|
233 |
+
web_results = []
|
234 |
+
for idx, result in enumerate(results):
|
235 |
+
logging.info(f"搜索结果{idx + 1}:{result}")
|
236 |
+
web_results.append(f'[{idx+1}]"{result["body"]}"\nURL: {result["href"]}')
|
237 |
+
web_results = "\n\n".join(web_results)
|
238 |
+
today = datetime.datetime.today().strftime("%Y-%m-%d")
|
239 |
+
inputs = websearch_prompt.replace("{current_date}", today).replace("{query}", inputs).replace("{web_results}", web_results)
|
240 |
+
if len(openai_api_key) != 51:
|
241 |
+
status_text = standard_error_msg + no_apikey_msg
|
242 |
+
logging.info(status_text)
|
243 |
+
chatbot.append((parse_text(inputs), ""))
|
244 |
+
if len(history) == 0:
|
245 |
+
history.append(construct_user(inputs))
|
246 |
+
history.append("")
|
247 |
+
all_token_counts.append(0)
|
248 |
+
else:
|
249 |
+
history[-2] = construct_user(inputs)
|
250 |
+
yield chatbot, history, status_text, all_token_counts
|
251 |
+
return
|
252 |
+
if stream:
|
253 |
+
yield chatbot, history, "开始生成回答……", all_token_counts
|
254 |
if stream:
|
255 |
+
logging.info("使用流式传输")
|
256 |
+
iter = stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, selected_model)
|
257 |
+
for chatbot, history, status_text, all_token_counts in iter:
|
258 |
+
yield chatbot, history, status_text, all_token_counts
|
259 |
else:
|
260 |
+
logging.info("不使用流式传输")
|
261 |
+
chatbot, history, status_text, all_token_counts = predict_all(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, selected_model)
|
262 |
+
yield chatbot, history, status_text, all_token_counts
|
263 |
+
logging.info(f"传输完毕。当前token计数为{all_token_counts}")
|
264 |
+
if len(history) > 1 and history[-1]['content'] != inputs:
|
265 |
+
logging.info("回答为:" +colorama.Fore.BLUE + f"{history[-1]['content']}" + colorama.Style.RESET_ALL)
|
266 |
if stream:
|
267 |
max_token = max_token_streaming
|
268 |
else:
|
269 |
max_token = max_token_all
|
270 |
+
if sum(all_token_counts) > max_token and should_check_token_count:
|
271 |
+
status_text = f"精简token中{all_token_counts}/{max_token}"
|
272 |
+
logging.info(status_text)
|
273 |
+
yield chatbot, history, status_text, all_token_counts
|
274 |
+
iter = reduce_token_size(openai_api_key, system_prompt, history, chatbot, all_token_counts, top_p, temperature, stream=False, selected_model=selected_model, hidden=True)
|
275 |
+
for chatbot, history, status_text, all_token_counts in iter:
|
276 |
+
status_text = f"Token 达到上限,已自动降低Token计数至 {status_text}"
|
277 |
+
yield chatbot, history, status_text, all_token_counts
|
278 |
+
|
279 |
+
|
280 |
+
def retry(openai_api_key, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False, selected_model = MODELS[0]):
|
281 |
+
logging.info("重试中……")
|
282 |
if len(history) == 0:
|
283 |
yield chatbot, history, f"{standard_error_msg}上下文是空的", token_count
|
284 |
return
|
285 |
history.pop()
|
286 |
inputs = history.pop()["content"]
|
287 |
token_count.pop()
|
288 |
+
iter = predict(openai_api_key, system_prompt, history, inputs, chatbot, token_count, top_p, temperature, stream=stream, selected_model=selected_model)
|
289 |
+
logging.info("重试完毕")
|
290 |
for x in iter:
|
291 |
yield x
|
292 |
|
293 |
|
294 |
+
def reduce_token_size(openai_api_key, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False, selected_model = MODELS[0], hidden=False):
|
295 |
+
logging.info("开始减少token数量……")
|
296 |
+
iter = predict(openai_api_key, system_prompt, history, summarize_prompt, chatbot, token_count, top_p, temperature, stream=stream, selected_model = selected_model, should_check_token_count=False)
|
297 |
+
logging.info(f"chatbot: {chatbot}")
|
298 |
for chatbot, history, status_text, previous_token_count in iter:
|
299 |
history = history[-2:]
|
300 |
token_count = previous_token_count[-1:]
|
301 |
if hidden:
|
302 |
chatbot.pop()
|
303 |
yield chatbot, history, construct_token_message(sum(token_count), stream=stream), token_count
|
304 |
+
logging.info("减少token数量完毕")
|
305 |
|
306 |
|
307 |
+
def delete_last_conversation(chatbot, history, previous_token_count):
|
308 |
if len(chatbot) > 0 and standard_error_msg in chatbot[-1][1]:
|
309 |
+
logging.info("由于包含报错信息,只删除chatbot记录")
|
310 |
chatbot.pop()
|
311 |
return chatbot, history
|
312 |
if len(history) > 0:
|
313 |
+
logging.info("删除了一组对话历史")
|
314 |
history.pop()
|
315 |
history.pop()
|
316 |
if len(chatbot) > 0:
|
317 |
+
logging.info("删除了一组chatbot对话")
|
318 |
chatbot.pop()
|
319 |
if len(previous_token_count) > 0:
|
320 |
+
logging.info("删除了一组对话的token计数记录")
|
321 |
previous_token_count.pop()
|
322 |
+
return chatbot, history, previous_token_count, construct_token_message(sum(previous_token_count))
|
323 |
|
324 |
|
325 |
def save_chat_history(filename, system, history, chatbot):
|
326 |
+
logging.info("保存对话历史中……")
|
327 |
if filename == "":
|
328 |
return
|
329 |
if not filename.endswith(".json"):
|
330 |
filename += ".json"
|
331 |
os.makedirs(HISTORY_DIR, exist_ok=True)
|
332 |
json_s = {"system": system, "history": history, "chatbot": chatbot}
|
333 |
+
logging.info(json_s)
|
334 |
with open(os.path.join(HISTORY_DIR, filename), "w") as f:
|
335 |
+
json.dump(json_s, f, ensure_ascii=False, indent=4)
|
336 |
+
logging.info("保存对话历史完毕")
|
337 |
|
338 |
|
339 |
def load_chat_history(filename, system, history, chatbot):
|
340 |
+
logging.info("加载对话历史中……")
|
341 |
try:
|
342 |
with open(os.path.join(HISTORY_DIR, filename), "r") as f:
|
343 |
json_s = json.load(f)
|
344 |
+
try:
|
345 |
+
if type(json_s["history"][0]) == str:
|
346 |
+
logging.info("历史记录格式为旧版,正在转换……")
|
347 |
+
new_history = []
|
348 |
+
for index, item in enumerate(json_s["history"]):
|
349 |
+
if index % 2 == 0:
|
350 |
+
new_history.append(construct_user(item))
|
351 |
+
else:
|
352 |
+
new_history.append(construct_assistant(item))
|
353 |
+
json_s["history"] = new_history
|
354 |
+
logging.info(new_history)
|
355 |
+
except:
|
356 |
+
# 没有对话历史
|
357 |
+
pass
|
358 |
+
logging.info("加载对话历史完毕")
|
359 |
return filename, json_s["system"], json_s["history"], json_s["chatbot"]
|
360 |
except FileNotFoundError:
|
361 |
+
logging.info("没有找到对话历史文件,不执行任何操作")
|
362 |
return filename, system, history, chatbot
|
363 |
|
364 |
def sorted_by_pinyin(list):
|
365 |
return sorted(list, key=lambda char: lazy_pinyin(char)[0][0])
|
366 |
|
367 |
def get_file_names(dir, plain=False, filetypes=[".json"]):
|
368 |
+
logging.info(f"获取文件名列表,目录为{dir},文件类型为{filetypes},是否为纯文本列表{plain}")
|
369 |
files = []
|
370 |
try:
|
371 |
for type in filetypes:
|
|
|
381 |
return gr.Dropdown.update(choices=files)
|
382 |
|
383 |
def get_history_names(plain=False):
|
384 |
+
logging.info("获取历史记录文件名列表")
|
385 |
return get_file_names(HISTORY_DIR, plain)
|
386 |
|
387 |
def load_template(filename, mode=0):
|
388 |
+
logging.info(f"加载模板文件{filename},模式为{mode}(0为返回字典和下拉菜单,1为返回下拉菜单,2为返回字典)")
|
389 |
lines = []
|
390 |
+
logging.info("Loading template...")
|
391 |
if filename.endswith(".json"):
|
392 |
with open(os.path.join(TEMPLATES_DIR, filename), "r", encoding="utf8") as f:
|
393 |
lines = json.load(f)
|
|
|
406 |
return {row[0]:row[1] for row in lines}, gr.Dropdown.update(choices=choices, value=choices[0])
|
407 |
|
408 |
def get_template_names(plain=False):
|
409 |
+
logging.info("获取模板文件名列表")
|
410 |
return get_file_names(TEMPLATES_DIR, plain, filetypes=[".csv", "json"])
|
411 |
|
412 |
def get_template_content(templates, selection, original_system_prompt):
|
413 |
+
logging.info(f"应用模板中,选择为{selection},原始系统提示为{original_system_prompt}")
|
414 |
try:
|
415 |
return templates[selection]
|
416 |
except:
|
417 |
return original_system_prompt
|
418 |
|
419 |
def reset_state():
|
420 |
+
logging.info("重置状态")
|
421 |
return [], [], [], construct_token_message(0)
|
422 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
423 |
def reset_textbox():
|
424 |
return gr.update(value='')
|