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bin_public/app/Chatbot.py

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+# -*- coding:utf-8 -*-
+
+import sys
+from bin_public.utils.utils import *
+from bin_public.utils.utils_db import *
+from bin_public.config.presets import *
+
+my_api_key = ""
+
+# if we are running in Docker
+if os.environ.get('dockerrun') == 'yes':
+    dockerflag = True
+else:
+    dockerflag = False
+
+authflag = False
+
+if dockerflag:
+    my_api_key = os.environ.get('my_api_key')
+    if my_api_key == "empty":
+        print("Please give a api key!")
+        sys.exit(1)
+    # auth
+    username = os.environ.get('USERNAME')
+    password = os.environ.get('PASSWORD')
+    if not (isinstance(username, type(None)) or isinstance(password, type(None))):
+        authflag = True
+else:
+    '''if not my_api_key and os.path.exists("api_key.txt") and os.path.getsize("api_key.txt"):  # API key 所在的文件
+        with open("api_key.txt", "r") as f:
+            my_api_key = f.read().strip()'''
+
+
+
+    if os.path.exists("auth.json"):
+        with open("auth.json", "r") as f:
+            auth = json.load(f)
+            username = auth["username"]
+            password = auth["password"]
+            if username != "" and password != "":
+                authflag = True
+
+gr.Chatbot.postprocess = postprocess
+
+with gr.Blocks(css=customCSS) as demo:
+    history = gr.State([])
+    token_count = gr.State([])
+    invite_code = gr.State()
+    promptTemplates = gr.State(load_template(get_template_names(plain=True)[0], mode=2))
+    TRUECOMSTANT = gr.State(True)
+    FALSECONSTANT = gr.State(False)
+    topic = gr.State("未命名对话历史记录")
+
+    # gr.HTML("""
+    # <div style="text-align: center; margin-top: 20px;">
+    # """)
+    gr.HTML(title)
+
+    with gr.Row(scale=1).style(equal_height=True):
+        with gr.Column(scale=5):
+            with gr.Row(scale=1):
+                chatbot = gr.Chatbot().style(height=600)  # .style(color_map=("#1D51EE", "#585A5B"))
+            with gr.Row(scale=1):
+                with gr.Column(scale=12):
+                    user_input = gr.Textbox(show_label=False, placeholder="在这里输入").style(
+                        container=False)
+                with gr.Column(min_width=50, scale=1):
+                    submitBtn = gr.Button("🚀", variant="primary")
+            with gr.Row(scale=1):
+                emptyBtn = gr.Button("🧹 新的对话", )
+                retryBtn = gr.Button("🔄 重新生成")
+                delLastBtn = gr.Button("🗑️ 删除一条对话")
+                reduceTokenBtn = gr.Button("♻️ 总结对话")
+
+        with gr.Column():
+            with gr.Column(min_width=50, scale=1):
+                status_display = gr.Markdown("status: ready")
+                with gr.Tab(label="ChatGPT"):
+                    keyTXT = gr.Textbox(show_label=True, placeholder=f"OpenAI API-key...",
+                                        type="password", visible=not HIDE_MY_KEY, label="API-Key/Invite-Code")
+
+                    keyTxt = gr.Textbox(visible=False)
+
+                    key_button = gr.Button("Enter")
+
+                    model_select_dropdown = gr.Dropdown(label="选择模型", choices=MODELS, multiselect=False,
+                                                        value=MODELS[0])
+                    with gr.Accordion("参数", open=False):
+                        temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0,
+                                                step=0.1, interactive=True, label="Temperature", )
+                        top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.05,
+                                          interactive=True, label="Top-p (nucleus sampling)", visible=False)
+                    use_streaming_checkbox = gr.Checkbox(label="实时传输回答", value=True, visible=enable_streaming_option)
+                    use_websearch_checkbox = gr.Checkbox(label="使用在线搜索", value=False)
+
+                with gr.Tab(label="Prompt"):
+                    systemPromptTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入System Prompt...",
+                                                 label="System prompt", value=initial_prompt).style(container=True)
+                    with gr.Accordion(label="加载Prompt模板", open=True):
+                        with gr.Column():
+                            with gr.Row():
+                                with gr.Column(scale=6):
+                                    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])
+                                with gr.Column(scale=1):
+                                    templateRefreshBtn = gr.Button("🔄 刷新")
+                            with gr.Row():
+                                with gr.Column():
+                                    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])
+
+                with gr.Tab(label="保存/加载"):
+                    with gr.Accordion(label="保存/加载对话历史记录", open=True):
+                        with gr.Column():
+                            with gr.Row():
+                                with gr.Column(scale=6):
+                                    saveFileName = gr.Textbox(
+                                        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)
+                                with gr.Column(scale=1):
+                                    saveHistoryBtn = gr.Button("💾 保存对话")
+                            with gr.Row():
+                                with gr.Column(scale=6):
+                                    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])
+                                with gr.Column(scale=1):
+                                    historyRefreshBtn = gr.Button("🔄 刷新")
+
+    gr.HTML("""
+    <div style="text-align: center; margin-top: 20px; margin-bottom: 20px;">
+    """)
+    gr.Markdown(description)
+
+    # 输入为api key则保持不变，为邀请码则调用中心的api key
+    key_button.click(key_preprocessing, [keyTXT], [status_display, keyTxt, invite_code])
+
+    user_input.submit(predict, [keyTxt, invite_code, 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)
+    user_input.submit(reset_textbox, [], [user_input])
+
+    submitBtn.click(predict, [keyTxt, invite_code, 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)
+    submitBtn.click(reset_textbox, [], [user_input])
+
+    emptyBtn.click(reset_state, outputs=[chatbot, history, token_count, status_display], show_progress=True)
+
+    retryBtn.click(retry,
+                   [keyTxt, invite_code, systemPromptTxt, history, chatbot, token_count, top_p, temperature, use_streaming_checkbox,
+                    model_select_dropdown], [chatbot, history, status_display, token_count], show_progress=True)
+
+    delLastBtn.click(delete_last_conversation, [chatbot, history, token_count], [
+        chatbot, history, token_count, status_display], show_progress=True)
+
+    reduceTokenBtn.click(reduce_token_size, [keyTxt, invite_code, systemPromptTxt, history, chatbot, token_count, top_p,
+                                             temperature, use_streaming_checkbox, model_select_dropdown],
+                         [chatbot, history, status_display, token_count], show_progress=True)
+
+    saveHistoryBtn.click(save_chat_history, [
+        saveFileName, systemPromptTxt, history, chatbot], None, show_progress=True)
+
+    saveHistoryBtn.click(get_history_names, None, [historyFileSelectDropdown])
+
+    historyRefreshBtn.click(get_history_names, None, [historyFileSelectDropdown])
+
+    historyFileSelectDropdown.change(load_chat_history, [historyFileSelectDropdown, systemPromptTxt, history, chatbot],
+                                     [saveFileName, systemPromptTxt, history, chatbot], show_progress=True)
+
+    templateRefreshBtn.click(get_template_names, None, [templateFileSelectDropdown])
+
+    templateFileSelectDropdown.change(load_template, [templateFileSelectDropdown],
+                                      [promptTemplates, templateSelectDropdown], show_progress=True)
+
+    templateSelectDropdown.change(get_template_content, [promptTemplates, templateSelectDropdown, systemPromptTxt],
+                                  [systemPromptTxt], show_progress=True)
+
+logging.info( "\n访问 http://localhost:7860 查看界面")
+# 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
+demo.title = "ChatGPT-长江商学院 🚀"
+
+if __name__ == "__main__":
+    #if running in Docker
+    if dockerflag:
+        if authflag:
+            demo.queue().launch(server_name="0.0.0.0", server_port=7860,auth=(username, password))
+        else:
+            demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False)
+    #if not running in Docker
+    else:
+        if authflag:
+            demo.queue().launch(share=False, auth=(username, password))
+        else:
+            demo.queue().launch(share=False) # 改为 share=True 可以创建公开分享链接

bin_public/app/app.py

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+# -*- coding:utf-8 -*-
+import sys
+from bin.utils.utils import *
+from bin.config.presets import *
+
+my_api_key = ""
+
+# if we are running in Docker
+if os.environ.get('dockerrun') == 'yes':
+    dockerflag = True
+else:
+    dockerflag = False
+
+authflag = False
+
+if dockerflag:
+    my_api_key = os.environ.get('my_api_key')
+    if my_api_key == "empty":
+        print("Please give a api key!")
+        sys.exit(1)
+    # auth
+    username = os.environ.get('USERNAME')
+    password = os.environ.get('PASSWORD')
+    if not (isinstance(username, type(None)) or isinstance(password, type(None))):
+        authflag = True
+else:
+    '''if not my_api_key and os.path.exists("api_key.txt") and os.path.getsize("api_key.txt"):  # API key 所在的文件
+        with open("api_key.txt", "r") as f:
+            my_api_key = f.read().strip()'''
+
+
+
+    if os.path.exists("auth.json"):
+        with open("auth.json", "r") as f:
+            auth = json.load(f)
+            username = auth["username"]
+            password = auth["password"]
+            if username != "" and password != "":
+                authflag = True
+
+gr.Chatbot.postprocess = postprocess
+
+with gr.Blocks(css=customCSS, ) as demo:
+    history = gr.State([])
+    token_count = gr.State([])
+    promptTemplates = gr.State(load_template(get_template_names(plain=True)[0], mode=2))
+    TRUECOMSTANT = gr.State(True)
+    FALSECONSTANT = gr.State(False)
+    topic = gr.State("未命名对话历史记录")
+
+    # gr.HTML("""
+    # <div style="text-align: center; margin-top: 20px;">
+    # """)
+    gr.HTML(title)
+
+    with gr.Row(scale=1).style(equal_height=True):
+        with gr.Column(scale=5):
+            with gr.Row(scale=1):
+                chatbot = gr.Chatbot().style(height=600)  # .style(color_map=("#1D51EE", "#585A5B"))
+            with gr.Row(scale=1):
+                with gr.Column(scale=12):
+                    user_input = gr.Textbox(show_label=False, placeholder="在这里输入").style(
+                        container=False)
+                with gr.Column(min_width=50, scale=1):
+                    submitBtn = gr.Button("🚀", variant="primary")
+            with gr.Row(scale=1):
+                emptyBtn = gr.Button("🧹 新的对话", )
+                retryBtn = gr.Button("🔄 重新生成")
+                delLastBtn = gr.Button("🗑️ 删除一条对话")
+                reduceTokenBtn = gr.Button("♻️ 总结对话")
+
+        with gr.Column():
+            with gr.Column(min_width=50, scale=1):
+                status_display = gr.Markdown("status: ready")
+                with gr.Tab(label="ChatGPT"):
+                    keyTXT = gr.Textbox(show_label=True, placeholder=f"OpenAI API-key...",
+                                        type="password", visible=not HIDE_MY_KEY, label="API-Key/Invite-Code")
+
+                    keyTxt = gr.Textbox(visible=False)
+
+                    key_button = gr.Button("Enter")
+
+                    model_select_dropdown = gr.Dropdown(label="选择模型", choices=MODELS, multiselect=False,
+                                                        value=MODELS[0])
+                    with gr.Accordion("参数", open=False):
+                        temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0,
+                                                step=0.1, interactive=True, label="Temperature", )
+                        top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.05,
+                                          interactive=True, label="Top-p (nucleus sampling)", visible=False)
+                    use_streaming_checkbox = gr.Checkbox(label="实时传输回答", value=True, visible=enable_streaming_option)
+                    use_websearch_checkbox = gr.Checkbox(label="使用在线搜索", value=False)
+
+                with gr.Tab(label="Prompt"):
+                    systemPromptTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入System Prompt...",
+                                                 label="System prompt", value=initial_prompt).style(container=True)
+                    with gr.Accordion(label="加载Prompt模板", open=True):
+                        with gr.Column():
+                            with gr.Row():
+                                with gr.Column(scale=6):
+                                    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])
+                                with gr.Column(scale=1):
+                                    templateRefreshBtn = gr.Button("🔄 刷新")
+                            with gr.Row():
+                                with gr.Column():
+                                    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])
+
+                with gr.Tab(label="保存/加载"):
+                    with gr.Accordion(label="保存/加载对话历史记录", open=True):
+                        with gr.Column():
+                            with gr.Row():
+                                with gr.Column(scale=6):
+                                    saveFileName = gr.Textbox(
+                                        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)
+                                with gr.Column(scale=1):
+                                    saveHistoryBtn = gr.Button("💾 保存对话")
+                            with gr.Row():
+                                with gr.Column(scale=6):
+                                    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])
+                                with gr.Column(scale=1):
+                                    historyRefreshBtn = gr.Button("🔄 刷新")
+
+    gr.HTML("""
+    <div style="text-align: center; margin-top: 20px; margin-bottom: 20px;">
+    """)
+    gr.Markdown(description)
+
+    # 输入为api key则保持不变，为邀请码则调用中心的api key
+    key_button.click(key_preprocessing, [keyTXT], [status, keyTxt, status_display])
+
+    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)
+    user_input.submit(reset_textbox, [], [user_input])
+
+    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)
+    submitBtn.click(reset_textbox, [], [user_input])
+
+    emptyBtn.click(reset_state, outputs=[chatbot, history, token_count, status_display], show_progress=True)
+
+    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)
+
+    delLastBtn.click(delete_last_conversation, [chatbot, history, token_count], [
+        chatbot, history, token_count, status_display], show_progress=True)
+
+    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)
+
+    saveHistoryBtn.click(save_chat_history, [
+        saveFileName, systemPromptTxt, history, chatbot], None, show_progress=True)
+
+    saveHistoryBtn.click(get_history_names, None, [historyFileSelectDropdown])
+
+    historyRefreshBtn.click(get_history_names, None, [historyFileSelectDropdown])
+
+    historyFileSelectDropdown.change(load_chat_history, [historyFileSelectDropdown, systemPromptTxt, history, chatbot],
+                                     [saveFileName, systemPromptTxt, history, chatbot], show_progress=True)
+
+    templateRefreshBtn.click(get_template_names, None, [templateFileSelectDropdown])
+
+    templateFileSelectDropdown.change(load_template, [templateFileSelectDropdown],
+                                      [promptTemplates, templateSelectDropdown], show_progress=True)
+
+    templateSelectDropdown.change(get_template_content, [promptTemplates, templateSelectDropdown, systemPromptTxt],
+                                  [systemPromptTxt], show_progress=True)
+
+logging.info(colorama.Back.GREEN + "\n访问 http://localhost:7860 查看界面" + colorama.Style.RESET_ALL)
+# 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
+demo.title = "ChatGPT-长江商学院 🚀"
+
+if __name__ == "__main__":
+    #if running in Docker
+    if dockerflag:
+        if authflag:
+            demo.queue().launch(server_name="0.0.0.0", server_port=7860,auth=(username, password))
+        else:
+            demo.queue().launch(server_name="0.0.0.0", server_port=7860, share=False)
+    #if not running in Docker
+    else:
+        if authflag:
+            demo.queue().launch(share=False, auth=(username, password))
+        else:
+            demo.queue().launch(share=False) # 改为 share=True 可以创建公开分享链接

bin_public/config/presets.py

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+# -*- coding:utf-8 -*-
+title = """<h1 align="center">ChatGPT-长江商学院 🚀</h1>"""
+description = """<div align=center>
+</div>
+"""
+customCSS = """
+code {
+    display: inline;
+    white-space: break-spaces;
+    border-radius: 6px;
+    margin: 0 2px 0 2px;
+    padding: .2em .4em .1em .4em;
+    background-color: rgba(175,184,193,0.2);
+}
+pre code {
+    display: block;
+    white-space: pre;
+    background-color: hsla(0, 0%, 0%, 72%);
+    border: solid 5px var(--color-border-primary) !important;
+    border-radius: 10px;
+    padding: 0 1.2rem 1.2rem;
+    margin-top: 1em !important;
+    color: #FFF;
+    box-shadow: inset 0px 8px 16px hsla(0, 0%, 0%, .2)
+}
+*{
+    transition: all 0.6s;
+}
+"""
+
+summarize_prompt = "你是谁？我们刚才聊了什么？" # 总结对话时的 prompt
+# 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
+MODELS = ["gpt-3.5-turbo-0301"]
+websearch_prompt = """Web search results:
+{web_results}
+Current date: {current_date}
+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.
+Query: {query}
+"""
+
+# 错误信息
+standard_error_msg = "☹️发生了错误：" # 错误信息的标准前缀
+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
+connection_timeout_prompt = "连接超时，无法获取对话。" # 连接超时
+read_timeout_prompt = "读取超时，无法获取对话。" # 读取超时
+proxy_error_prompt = "代理错误，无法获取对话。" # 代理错误
+ssl_error_prompt = "SSL错误，无法获取对话。" # SSL 错误
+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
+no_invite_code_msg = "输入的invite code不存在"
+no_useful_invite_code_msg = "输入的invite code状态不可用"
+
+
+max_token_streaming = 3500 # 流式对话时的最大 token 数
+timeout_streaming = 30 # 流式对话时的超时时间
+max_token_all = 3500 # 非流式对话时的最大 token 数
+timeout_all = 200 # 非流式对话时的超时时间
+enable_streaming_option = True  # 是否启用选择选择是否实时显示回答的勾选框
+HIDE_MY_KEY = False # 如果你想在UI中隐藏你的 API 密钥，将此值设置为 True

bin_public/utils/utils.py

@@ -0,0 +1,446 @@
+# -*- coding:utf-8 -*-
+from __future__ import annotations
+from typing import TYPE_CHECKING, List, Tuple
+import logging
+import json
+import gradio as gr
+# import openai
+import os
+import requests
+# import markdown
+import csv
+import mdtex2html
+from pypinyin import lazy_pinyin
+from bin.config.presets import *
+import tiktoken
+from tqdm import tqdm
+from duckduckgo_search import ddg
+from bin_public.utils.utils_db import *
+import datetime
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s")
+
+if TYPE_CHECKING:
+    from typing import TypedDict
+
+    class DataframeData(TypedDict):
+        headers: List[str]
+        data: List[List[str | int | bool]]
+
+initial_prompt = "You are a helpful assistant."
+API_URL = "https://api.openai.com/v1/chat/completions"
+HISTORY_DIR = "history"
+TEMPLATES_DIR = "templates"
+
+
+def postprocess(
+        self, y: List[Tuple[str | None, str | None]]
+    ) -> List[Tuple[str | None, str | None]]:
+        """
+        Parameters:
+            y: List of tuples representing the message and response pairs. Each message and response should be a string, which may be in Markdown format.
+        Returns:
+            List of tuples representing the message and response. Each message and response will be a string of HTML.
+        """
+        if y is None:
+            return []
+        for i, (message, response) in enumerate(y):
+            y[i] = (
+                # None if message is None else markdown.markdown(message),
+                # None if response is None else markdown.markdown(response),
+                None if message is None else mdtex2html.convert((message)),
+                None if response is None else mdtex2html.convert(response),
+            )
+        return y
+
+
+def count_token(input_str):
+    encoding = tiktoken.get_encoding("cl100k_base")
+    length = len(encoding.encode(input_str))
+    return length
+
+
+def parse_text(text):
+    lines = text.split("\n")
+    lines = [line for line in lines if line != ""]
+    count = 0
+    for i, line in enumerate(lines):
+        if "```" in line:
+            count += 1
+            items = line.split('`')
+            if count % 2 == 1:
+                lines[i] = f'<pre><code class="language-{items[-1]}">'
+            else:
+                lines[i] = f'<br></code></pre>'
+        else:
+            if i > 0:
+                if count % 2 == 1:
+                    line = line.replace("`", "\`")
+                    line = line.replace("<", "&lt;")
+                    line = line.replace(">", "&gt;")
+                    line = line.replace(" ", "&nbsp;")
+                    line = line.replace("*", "&ast;")
+                    line = line.replace("_", "&lowbar;")
+                    line = line.replace("-", "&#45;")
+                    line = line.replace(".", "&#46;")
+                    line = line.replace("!", "&#33;")
+                    line = line.replace("(", "&#40;")
+                    line = line.replace(")", "&#41;")
+                    line = line.replace("$", "&#36;")
+                lines[i] = "<br>"+line
+    text = "".join(lines)
+    return text
+
+
+def construct_text(role, text):
+    return {"role": role, "content": text}
+
+
+def construct_user(text):
+    return construct_text("user", text)
+
+
+def construct_system(text):
+    return construct_text("system", text)
+
+
+def construct_assistant(text):
+    return construct_text("assistant", text)
+
+
+def construct_token_message(token, stream=False):
+    return f"Token 计数: {token}"
+
+
+def get_response(openai_api_key, system_prompt, history, temperature, top_p, stream, selected_model):
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {openai_api_key}"
+    }
+
+    history = [construct_system(system_prompt), *history]
+
+    payload = {
+        "model": selected_model,
+        "messages": history,  # [{"role": "user", "content": f"{inputs}"}],
+        "temperature": temperature,  # 1.0,
+        "top_p": top_p,  # 1.0,
+        "n": 1,
+        "stream": stream,
+        "presence_penalty": 0,
+        "frequency_penalty": 0,
+    }
+    if stream:
+        timeout = timeout_streaming
+    else:
+        timeout = timeout_all
+    response = requests.post(API_URL, headers=headers, json=payload, stream=True, timeout=timeout)
+    return response
+
+
+def stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, selected_model):
+    def get_return_value():
+        return chatbot, history, status_text, all_token_counts
+
+    logging.info("实时回答模式")
+    partial_words = ""
+    counter = 0
+    status_text = "开始实时传输回答……"
+    history.append(construct_user(inputs))
+    history.append(construct_assistant(""))
+    chatbot.append((parse_text(inputs), ""))
+    user_token_count = 0
+    if len(all_token_counts) == 0:
+        system_prompt_token_count = count_token(system_prompt)
+        user_token_count = count_token(inputs) + system_prompt_token_count
+    else:
+        user_token_count = count_token(inputs)
+    all_token_counts.append(user_token_count)
+    logging.info(f"输入token计数: {user_token_count}")
+    yield get_return_value()
+    try:
+        response = get_response(openai_api_key, system_prompt, history, temperature, top_p, True, selected_model)
+    except requests.exceptions.ConnectTimeout:
+        status_text = standard_error_msg + connection_timeout_prompt + error_retrieve_prompt
+        yield get_return_value()
+        return
+    except requests.exceptions.ReadTimeout:
+        status_text = standard_error_msg + read_timeout_prompt + error_retrieve_prompt
+        yield get_return_value()
+        return
+
+    yield get_return_value()
+    error_json_str = ""
+
+    for chunk in tqdm(response.iter_lines()):
+        if counter == 0:
+            counter += 1
+            continue
+        counter += 1
+        # check whether each line is non-empty
+        if chunk:
+            chunk = chunk.decode()
+            chunklength = len(chunk)
+            try:
+                chunk = json.loads(chunk[6:])
+            except json.JSONDecodeError:
+                logging.info(chunk)
+                error_json_str += chunk
+                status_text = f"JSON解析错误。请重置对话。收到的内容: {error_json_str}"
+                yield get_return_value()
+                continue
+            # decode each line as response data is in bytes
+            if chunklength > 6 and "delta" in chunk['choices'][0]:
+                finish_reason = chunk['choices'][0]['finish_reason']
+                status_text = construct_token_message(sum(all_token_counts), stream=True)
+                if finish_reason == "stop":
+                    yield get_return_value()
+                    break
+                try:
+                    partial_words = partial_words + chunk['choices'][0]["delta"]["content"]
+                except KeyError:
+                    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。请重置对话。当前Token计数: " + str(sum(all_token_counts))
+                    yield get_return_value()
+                    break
+                history[-1] = construct_assistant(partial_words)
+                chatbot[-1] = (parse_text(inputs), parse_text(partial_words))
+                all_token_counts[-1] += 1
+                yield get_return_value()
+
+
+def predict_all(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, selected_model):
+    logging.info("一次性回答模式")
+    history.append(construct_user(inputs))
+    history.append(construct_assistant(""))
+    chatbot.append((parse_text(inputs), ""))
+    all_token_counts.append(count_token(inputs))
+    try:
+        response = get_response(openai_api_key, system_prompt, history, temperature, top_p, False, selected_model)
+    except requests.exceptions.ConnectTimeout:
+        status_text = standard_error_msg + connection_timeout_prompt + error_retrieve_prompt
+        return chatbot, history, status_text, all_token_counts
+    except requests.exceptions.ProxyError:
+        status_text = standard_error_msg + proxy_error_prompt + error_retrieve_prompt
+        return chatbot, history, status_text, all_token_counts
+    except requests.exceptions.SSLError:
+        status_text = standard_error_msg + ssl_error_prompt + error_retrieve_prompt
+        return chatbot, history, status_text, all_token_counts
+    response = json.loads(response.text)
+    content = response["choices"][0]["message"]["content"]
+    history[-1] = construct_assistant(content)
+    chatbot[-1] = (parse_text(inputs), parse_text(content))
+    total_token_count = response["usage"]["total_tokens"]
+    all_token_counts[-1] = total_token_count - sum(all_token_counts)
+    status_text = construct_token_message(total_token_count)
+    return chatbot, history, status_text, all_token_counts
+
+
+def predict(openai_api_key, invite_code, 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
+    # logging.info("输入为：" +colorama.Fore.BLUE + f"{inputs}" + colorama.Style.RESET_ALL)
+    if use_websearch_checkbox:
+        results = ddg(inputs, max_results=3)
+        web_results = []
+        for idx, result in enumerate(results):
+            logging.info(f"搜索结果{idx + 1}：{result}")
+            web_results.append(f'[{idx+1}]"{result["body"]}"\nURL: {result["href"]}')
+        web_results = "\n\n".join(web_results)
+        today = datetime.datetime.today().strftime("%Y-%m-%d")
+        inputs = websearch_prompt.replace("{current_date}", today).replace("{query}", inputs).replace("{web_results}", web_results)
+    if len(openai_api_key) != 51:
+        status_text = standard_error_msg + no_apikey_msg
+        logging.info(status_text)
+        chatbot.append((parse_text(inputs), ""))
+        if len(history) == 0:
+            history.append(construct_user(inputs))
+            history.append("")
+            all_token_counts.append(0)
+        else:
+            history[-2] = construct_user(inputs)
+        yield chatbot, history, status_text, all_token_counts
+        return
+    if stream:
+        yield chatbot, history, "开始生成回答……", all_token_counts
+    if stream:
+        logging.info("使用流式传输")
+        iter = stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, selected_model)
+        for chatbot, history, status_text, all_token_counts in iter:
+            yield chatbot, history, status_text, all_token_counts
+    else:
+        logging.info("不使用流式传输")
+        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)
+        yield chatbot, history, status_text, all_token_counts
+    logging.info(f"传输完毕。当前token计数为{all_token_counts}")
+    if len(history) > 1 and history[-1]['content'] != inputs:
+        # logging.info("回答为：" +colorama.Fore.BLUE + f"{history[-1]['content']}" + colorama.Style.RESET_ALL)
+        try:
+            token = all_token_counts[-1]
+        except:
+            token = 0
+        holo_query_insert_chat_message(invite_code, inputs, history[-1]['content'], token, history)
+    if stream:
+        max_token = max_token_streaming
+    else:
+        max_token = max_token_all
+    if sum(all_token_counts) > max_token and should_check_token_count:
+        status_text = f"精简token中{all_token_counts}/{max_token}"
+        logging.info(status_text)
+        yield chatbot, history, status_text, all_token_counts
+        iter = reduce_token_size(openai_api_key, invite_code, system_prompt, history, chatbot, all_token_counts, top_p, temperature, stream=False, selected_model=selected_model, hidden=True)
+        for chatbot, history, status_text, all_token_counts in iter:
+            status_text = f"Token 达到上限，已自动降低Token计数至 {status_text}"
+            yield chatbot, history, status_text, all_token_counts
+
+
+def retry(openai_api_key, invite_code, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False, selected_model = MODELS[0]):
+    logging.info("重试中……")
+    if len(history) == 0:
+        yield chatbot, history, f"{standard_error_msg}上下文是空的", token_count
+        return
+    history.pop()
+    inputs = history.pop()["content"]
+    token_count.pop()
+    iter = predict(openai_api_key, invite_code, system_prompt, history, inputs, chatbot, token_count, top_p, temperature, stream=stream, selected_model=selected_model)
+    logging.info("重试完毕")
+    for x in iter:
+        yield x
+
+
+def reduce_token_size(openai_api_key, invite_code, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False, selected_model = MODELS[0], hidden=False):
+    logging.info("开始减少token数量……")
+    iter = predict(openai_api_key, invite_code, system_prompt, history, summarize_prompt, chatbot, token_count, top_p, temperature, stream=stream, selected_model = selected_model, should_check_token_count=False)
+    logging.info(f"chatbot: {chatbot}")
+    for chatbot, history, status_text, previous_token_count in iter:
+        history = history[-2:]
+        token_count = previous_token_count[-1:]
+        if hidden:
+            chatbot.pop()
+        yield chatbot, history, construct_token_message(sum(token_count), stream=stream), token_count
+    logging.info("减少token数量完毕")
+
+
+def delete_last_conversation(chatbot, history, previous_token_count):
+    if len(chatbot) > 0 and standard_error_msg in chatbot[-1][1]:
+        logging.info("由于包含报错信息，只删除chatbot记录")
+        chatbot.pop()
+        return chatbot, history
+    if len(history) > 0:
+        logging.info("删除了一组对话历史")
+        history.pop()
+        history.pop()
+    if len(chatbot) > 0:
+        logging.info("删除了一组chatbot对话")
+        chatbot.pop()
+    if len(previous_token_count) > 0:
+        logging.info("删除了一组对话的token计数记录")
+        previous_token_count.pop()
+    return chatbot, history, previous_token_count, construct_token_message(sum(previous_token_count))
+
+
+def save_chat_history(filename, system, history, chatbot):
+    logging.info("保存对话历史中……")
+    if filename == "":
+        return
+    if not filename.endswith(".json"):
+        filename += ".json"
+    os.makedirs(HISTORY_DIR, exist_ok=True)
+    json_s = {"system": system, "history": history, "chatbot": chatbot}
+    logging.info(json_s)
+    with open(os.path.join(HISTORY_DIR, filename), "w") as f:
+        json.dump(json_s, f, ensure_ascii=False, indent=4)
+    logging.info("保存对话历史完毕")
+
+
+def load_chat_history(filename, system, history, chatbot):
+    logging.info("加载对话历史中……")
+    try:
+        with open(os.path.join(HISTORY_DIR, filename), "r") as f:
+            json_s = json.load(f)
+        try:
+            if type(json_s["history"][0]) == str:
+                logging.info("历史记录格式为旧版，正在转换……")
+                new_history = []
+                for index, item in enumerate(json_s["history"]):
+                    if index % 2 == 0:
+                        new_history.append(construct_user(item))
+                    else:
+                        new_history.append(construct_assistant(item))
+                json_s["history"] = new_history
+                logging.info(new_history)
+        except:
+            # 没有对话历史
+            pass
+        logging.info("加载对话历史完毕")
+        return filename, json_s["system"], json_s["history"], json_s["chatbot"]
+    except FileNotFoundError:
+        logging.info("没有找到对话历史文件，不执行任何操作")
+        return filename, system, history, chatbot
+
+
+def sorted_by_pinyin(list):
+    return sorted(list, key=lambda char: lazy_pinyin(char)[0][0])
+
+
+def get_file_names(dir, plain=False, filetypes=[".json"]):
+    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}")
+    files = []
+    try:
+        for type in filetypes:
+            files += [f for f in os.listdir(dir) if f.endswith(type)]
+    except FileNotFoundError:
+        files = []
+    files = sorted_by_pinyin(files)
+    if files == []:
+        files = [""]
+    if plain:
+        return files
+    else:
+        return gr.Dropdown.update(choices=files)
+
+
+def get_history_names(plain=False):
+    logging.info("获取历史记录文件名列表")
+    return get_file_names(HISTORY_DIR, plain)
+
+
+def load_template(filename, mode=0):
+    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）")
+    lines = []
+    logging.info("Loading template...")
+    if filename.endswith(".json"):
+        with open(os.path.join(TEMPLATES_DIR, filename), "r", encoding="utf8") as f:
+            lines = json.load(f)
+        lines = [[i["act"], i["prompt"]] for i in lines]
+    else:
+        with open(os.path.join(TEMPLATES_DIR, filename), "r", encoding="utf8") as csvfile:
+            reader = csv.reader(csvfile)
+            lines = list(reader)
+        lines = lines[1:]
+    if mode == 1:
+        return sorted_by_pinyin([row[0] for row in lines])
+    elif mode == 2:
+        return {row[0]:row[1] for row in lines}
+    else:
+        choices = sorted_by_pinyin([row[0] for row in lines])
+        return {row[0]:row[1] for row in lines}, gr.Dropdown.update(choices=choices, value=choices[0])
+
+
+def get_template_names(plain=False):
+    logging.info("获取模板文件名列表")
+    return get_file_names(TEMPLATES_DIR, plain, filetypes=[".csv", "json"])
+
+
+def get_template_content(templates, selection, original_system_prompt):
+    logging.info(f"应用模板中，选择为{selection}，原始系统提示为{original_system_prompt}")
+    try:
+        return templates[selection]
+    except:
+        return original_system_prompt
+
+
+def reset_state():
+    logging.info("重置状态")
+    return [], [], [], construct_token_message(0)
+
+
+def reset_textbox():
+    return gr.update(value='')

bin_public/utils/utils_db.py

@@ -0,0 +1,94 @@
+import psycopg2
+import datetime
+#from bin_public.config.config import HOLOGRES_CONFIG
+from bin_public.config.presets import *
+from dateutil import tz
+import os
+
+
+def current_time(type):
+    if type == 'ymd':
+        return datetime.datetime.now().strftime("%Y-%m-%d")
+    if type == 'ymdhms':
+        return datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+
+
+# hologres 基础函数：查询
+def holo_query_func(run_sql, is_query=0):
+    conn = psycopg2.connect(host=os.environ['host'],
+                            port=os.environ['port'],
+                            dbname=os.environ['dbname'],
+                            user=os.environ['ak'],
+                            password=os.environ['sk'])
+    cur = conn.cursor()
+    cur.execute(run_sql)
+    if is_query:
+        data = cur.fetchall()
+    cur.close()
+    conn.close()
+    if is_query:
+        return data
+
+def holo_query_account_mapping(invite_code):
+    run_sql = f"""
+        select end_date, status, mapping_ak
+        from s_account_invite_code 
+        where invite_code = '{invite_code}'
+        order by gmt_modify desc
+        limit 1
+    """
+    data = holo_query_func(run_sql, is_query=1)
+    # 数据库中查不到，则返回no_invite_code_msg
+    if len(data) == 0:
+        status_text = standard_error_msg + no_invite_code_msg
+        return status_text, None
+    # 数据库中查到，判断是否可用
+    if len(data) == 1:
+        end_date = data[0][0]
+        status = data[0][1]
+        mapping_ak = data[0][2]
+        if end_date < datetime.datetime.now().strftime("%Y%m%d") or status != '1':
+            status_text = standard_error_msg + no_useful_invite_code_msg
+            return status_text, None
+    return 'Success status: ready', mapping_ak
+
+
+def key_preprocessing(keyTxt):
+    invite_code = keyTxt
+    # 这里先用这个逻辑，到时候等实际的邀请码来了就改一下这个函数就行
+    if keyTxt.startswith("ckgsb_"):
+        status_display, keyTxt = holo_query_account_mapping(keyTxt)
+        yield status_display, keyTxt, invite_code
+        return
+    else:
+        if len(keyTxt) != 51:
+            status_display = standard_error_msg + no_apikey_msg
+            yield status_display, keyTxt, invite_code
+            return
+        yield 'Success status: ready', keyTxt, invite_code
+        return
+
+
+def holo_query_insert_chat_message(invite_code, prompt, response, all_token_cnt, history):
+    run_sql = f"""
+        insert into s_account_chat_message(
+            gmt_create
+            ,invite_code
+            ,prompt
+            ,response
+            ,all_token_cnt
+            ,history
+            ,chat_seq
+            ,log_timestamp
+        )
+        select 
+             '{datetime.datetime.now().replace(tzinfo=tz.gettz('Asina/Shanghai')).strftime("%Y-%m-%d %H:%M:%S")}' as gmt_create
+            ,'{str(invite_code).replace("'", '"')}' as invite_code
+            ,'{str(prompt).replace("'", '"')}' as prompt
+            ,'{str(response).replace("'", '"')}' as response
+            ,'{str(all_token_cnt).replace("'", '"')}' as all_token_cnt
+            ,'{str(history).replace("'", '"')}' as history
+            ,'{len(history)}' as chat_seq
+            ,localtimestamp as log_timestamp
+    """
+    holo_query_func(run_sql, is_query=0)

requirements.txt

@@ -0,0 +1,11 @@
+gradio
+mdtex2html
+pypinyin
+tiktoken
+socksio
+tqdm
+colorama
+duckduckgo_search
+jieba
+psycopg2-binary
+python-dateutil