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bin_public/app/Chatbot.py

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+# -*- coding:utf-8 -*-
+
+import sys
+from overwrites import *
+from chat_func import *
+from bin_public.utils.tools 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
+PromptHelper.compact_text_chunks = compact_text_chunks
+
+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)
+                    index_files = gr.Files(label="上传索引文件", type="file", multiple=True)
+
+
+                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):
+                                    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],
+                                        visible=False
+                                    )
+
+                            with gr.Row():
+                                with gr.Column(scale=6):
+                                    saveFileName = gr.Textbox(
+                                        show_label=True,
+                                        placeholder=f"设置文件名: 默认为.json，可选为.md",
+                                        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")
+                                    exportMarkdownBtn = gr.Button("📝 导出为Markdown")
+                                    #gr.Markdown("默认保存于history文件夹")
+                            with gr.Row():
+                                with gr.Column():
+                                    downloadFile = gr.File(interactive=True)
+
+    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,
+            index_files],
+                      [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,
+            index_files],
+                    [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)
+    # History
+    saveHistoryBtn.click(
+        save_chat_history,
+        [saveFileName, systemPromptTxt, history, chatbot],
+        downloadFile,
+        show_progress=True,
+    )
+    saveHistoryBtn.click(get_history_names, None, [historyFileSelectDropdown])
+    exportMarkdownBtn.click(
+        export_markdown,
+        [saveFileName, systemPromptTxt, history, chatbot],
+        downloadFile,
+        show_progress=True,
+    )
+    #historyRefreshBtn.click(get_history_names, None, [historyFileSelectDropdown])
+    historyFileSelectDropdown.change(
+        load_chat_history,
+        [historyFileSelectDropdown, systemPromptTxt, history, chatbot],
+        [saveFileName, systemPromptTxt, history, chatbot],
+        show_progress=True,
+    )
+    downloadFile.change(
+        load_chat_history,
+        [downloadFile, systemPromptTxt, history, chatbot],
+        [saveFileName, systemPromptTxt, history, chatbot],
+    )
+
+
+    # Template
+    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 overwrites import *
+from chat_func import *
+from bin_public.utils.tools 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
+PromptHelper.compact_text_chunks = compact_text_chunks
+
+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)
+                    index_files = gr.Files(label="上传索引文件", type="file", multiple=True)
+
+
+                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):
+                                    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],
+                                        visible=False
+                                    )
+
+                            with gr.Row():
+                                with gr.Column(scale=6):
+                                    saveFileName = gr.Textbox(
+                                        show_label=True,
+                                        placeholder=f"设置文件名: 默认为.json，可选为.md",
+                                        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")
+                                    exportMarkdownBtn = gr.Button("📝 导出为Markdown")
+                                    #gr.Markdown("默认保存于history文件夹")
+                            with gr.Row():
+                                with gr.Column():
+                                    downloadFile = gr.File(interactive=True)
+
+    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,
+            index_files],
+                      [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,
+            index_files],
+                    [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)
+    # History
+    saveHistoryBtn.click(
+        save_chat_history,
+        [saveFileName, systemPromptTxt, history, chatbot],
+        downloadFile,
+        show_progress=True,
+    )
+    saveHistoryBtn.click(get_history_names, None, [historyFileSelectDropdown])
+    exportMarkdownBtn.click(
+        export_markdown,
+        [saveFileName, systemPromptTxt, history, chatbot],
+        downloadFile,
+        show_progress=True,
+    )
+    #historyRefreshBtn.click(get_history_names, None, [historyFileSelectDropdown])
+    historyFileSelectDropdown.change(
+        load_chat_history,
+        [historyFileSelectDropdown, systemPromptTxt, history, chatbot],
+        [saveFileName, systemPromptTxt, history, chatbot],
+        show_progress=True,
+    )
+    downloadFile.change(
+        load_chat_history,
+        [downloadFile, systemPromptTxt, history, chatbot],
+        [saveFileName, systemPromptTxt, history, chatbot],
+    )
+
+
+    # Template
+    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/chat_func.py

@@ -0,0 +1,452 @@
+# -*- coding:utf-8 -*-
+from __future__ import annotations
+
+import requests
+import urllib3
+
+from tqdm import tqdm
+from duckduckgo_search import ddg
+from llama_func import *
+from bin_public.utils.tools import *
+from bin_public.utils.utils_db import *
+# 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 = r"/templates"
+
+
+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
+
+    # 获取环境变量中的代理设置
+    http_proxy = os.environ.get("HTTP_PROXY") or os.environ.get("http_proxy")
+    https_proxy = os.environ.get("HTTPS_PROXY") or os.environ.get("https_proxy")
+
+    # 如果存在代理设置，使用它们
+    proxies = {}
+    if http_proxy:
+        logging.info(f"Using HTTP proxy: {http_proxy}")
+        proxies["http"] = http_proxy
+    if https_proxy:
+        logging.info(f"Using HTTPS proxy: {https_proxy}")
+        proxies["https"] = https_proxy
+
+    # 如果有代理，使用代理发送请求，否则使用默认设置发送请求
+    if proxies:
+        response = requests.post(
+            API_URL,
+            headers=headers,
+            json=payload,
+            stream=True,
+            timeout=timeout,
+            proxies=proxies,
+        )
+    else:
+        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,
+    fake_input=None
+):
+    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(""))
+    if fake_input:
+        chatbot.append((parse_text(fake_input), ""))
+    else:
+        chatbot.append((parse_text(inputs), ""))
+    user_token_count = 0
+    if len(all_token_counts) == 0:
+        system_prompt_token_count = count_token(construct_system(system_prompt))
+        user_token_count = (
+            count_token(construct_user(inputs)) + system_prompt_token_count
+        )
+    else:
+        user_token_count = count_token(construct_user(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计数达到上限了。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] = (chatbot[-1][0], 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,
+    fake_input=None
+):
+    logging.info("一次性回答模式")
+    history.append(construct_user(inputs))
+    history.append(construct_assistant(""))
+    if fake_input:
+        chatbot.append((parse_text(fake_input), ""))
+    else:
+        chatbot.append((parse_text(inputs), ""))
+    all_token_counts.append(count_token(construct_user(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] = (chatbot[-1][0], 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=False,
+    files = None,
+    should_check_token_count=True,
+):  # repetition_penalty, top_k
+    logging.info("输入为：" + colorama.Fore.BLUE + f"{inputs}" + colorama.Style.RESET_ALL)
+    if files:
+        msg = "构建索引中……（这可能需要比较久的时间）"
+        logging.info(msg)
+        yield chatbot, history, msg, all_token_counts
+        index = construct_index(openai_api_key, file_src=files)
+        msg = "索引构建完成，获取回答中……"
+        yield chatbot, history, msg, all_token_counts
+        history, chatbot, status_text = chat_ai(openai_api_key, index, inputs, history, chatbot)
+        yield chatbot, history, status_text, all_token_counts
+        return
+
+    old_inputs = ""
+    link_references = []
+    if use_websearch:
+        search_results = ddg(inputs, max_results=5)
+        old_inputs = inputs
+        web_results = []
+        for idx, result in enumerate(search_results):
+            logging.info(f"搜索结果{idx + 1}：{result}")
+            domain_name = urllib3.util.parse_url(result["href"]).host
+            web_results.append(f'[{idx+1}]"{result["body"]}"\nURL: {result["href"]}')
+            link_references.append(f"[{idx+1}]: [{domain_name}]({result['href']})")
+        inputs = (
+            replace_today(WEBSEARCH_PTOMPT_TEMPLATE)
+            .replace("{query}", inputs)
+            .replace("{web_results}", "\n\n".join(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
+
+    yield chatbot, history, "��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,
+            fake_input=old_inputs
+        )
+        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,
+            fake_input=old_inputs
+        )
+        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 use_websearch:
+        response = history[-1]['content']
+        response += "\n\n" + "\n".join(link_references)
+        logging.info(f"Added link references.")
+        logging.info(response)
+        chatbot[-1] = (parse_text(old_inputs), response)
+        yield chatbot, history, status_text, all_token_counts
+
+    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")

bin_public/app/llama_func.py

@@ -0,0 +1,187 @@
+from llama_index import GPTSimpleVectorIndex
+from llama_index import download_loader
+from llama_index import (
+    Document,
+    LLMPredictor,
+    PromptHelper,
+    QuestionAnswerPrompt,
+    RefinePrompt,
+)
+from langchain.llms import OpenAI
+import colorama
+
+from bin_public.utils.tools import *
+
+
+def get_documents(file_src):
+    documents = []
+    index_name = ""
+    logging.debug("Loading documents...")
+    logging.debug(f"file_src: {file_src}")
+    for file in file_src:
+        logging.debug(f"file: {file.name}")
+        index_name += file.name
+        if os.path.splitext(file.name)[1] == ".pdf":
+            logging.debug("Loading PDF...")
+            CJKPDFReader = download_loader("CJKPDFReader")
+            loader = CJKPDFReader()
+            documents += loader.load_data(file=file.name)
+        elif os.path.splitext(file.name)[1] == ".docx":
+            logging.debug("Loading DOCX...")
+            DocxReader = download_loader("DocxReader")
+            loader = DocxReader()
+            documents += loader.load_data(file=file.name)
+        elif os.path.splitext(file.name)[1] == ".epub":
+            logging.debug("Loading EPUB...")
+            EpubReader = download_loader("EpubReader")
+            loader = EpubReader()
+            documents += loader.load_data(file=file.name)
+        else:
+            logging.debug("Loading text file...")
+            with open(file.name, "r", encoding="utf-8") as f:
+                text = add_space(f.read())
+                documents += [Document(text)]
+    index_name = sha1sum(index_name)
+    return documents, index_name
+
+
+def construct_index(
+    api_key,
+    file_src,
+    max_input_size=4096,
+    num_outputs=1,
+    max_chunk_overlap=20,
+    chunk_size_limit=600,
+    embedding_limit=None,
+    separator=" ",
+    num_children=10,
+    max_keywords_per_chunk=10,
+):
+    os.environ["OPENAI_API_KEY"] = api_key
+    chunk_size_limit = None if chunk_size_limit == 0 else chunk_size_limit
+    embedding_limit = None if embedding_limit == 0 else embedding_limit
+    separator = " " if separator == "" else separator
+
+    llm_predictor = LLMPredictor(
+        llm=OpenAI(model_name="gpt-3.5-turbo-0301", openai_api_key=api_key)
+    )
+    prompt_helper = PromptHelper(
+        max_input_size,
+        num_outputs,
+        max_chunk_overlap,
+        embedding_limit,
+        chunk_size_limit,
+        separator=separator,
+    )
+    documents, index_name = get_documents(file_src)
+    if os.path.exists(f"./index/{index_name}.json"):
+        logging.info("找到了缓存的索引文件，加载中……")
+        return GPTSimpleVectorIndex.load_from_disk(f"./index/{index_name}.json")
+    else:
+        try:
+            logging.debug("构建索引中……")
+            index = GPTSimpleVectorIndex(
+                documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper
+            )
+            # os.makedirs("./index", exist_ok=True)
+            # index.save_to_disk(f"./index/{index_name}.json")
+            return index
+        except Exception as e:
+            print(e)
+            return None
+
+
+def chat_ai(
+    api_key,
+    index,
+    question,
+    context,
+    chatbot,
+):
+    os.environ["OPENAI_API_KEY"] = api_key
+
+    logging.info(f"Question: {question}")
+
+    response, chatbot_display, status_text = ask_ai(
+        api_key,
+        index,
+        question,
+        replace_today(PROMPT_TEMPLATE),
+        REFINE_TEMPLATE,
+        SIM_K,
+        INDEX_QUERY_TEMPERATURE,
+        context,
+    )
+    if response is None:
+        status_text = "查询失败，请换个问法试试"
+        return context, chatbot
+    response = response
+
+    context.append({"role": "user", "content": question})
+    context.append({"role": "assistant", "content": response})
+    chatbot.append((question, chatbot_display))
+
+    os.environ["OPENAI_API_KEY"] = ""
+    return context, chatbot, status_text
+
+
+def ask_ai(
+    api_key,
+    index,
+    question,
+    prompt_tmpl,
+    refine_tmpl,
+    sim_k=1,
+    temprature=0,
+    prefix_messages=[],
+):
+    os.environ["OPENAI_API_KEY"] = api_key
+
+    logging.debug("Index file found")
+    logging.debug("Querying index...")
+    llm_predictor = LLMPredictor(
+        llm=OpenAI(
+            temperature=temprature,
+            model_name="gpt-3.5-turbo-0301",
+            prefix_messages=prefix_messages,
+        )
+    )
+
+    response = None  # Initialize response variable to avoid UnboundLocalError
+    qa_prompt = QuestionAnswerPrompt(prompt_tmpl)
+    rf_prompt = RefinePrompt(refine_tmpl)
+    response = index.query(
+        question,
+        llm_predictor=llm_predictor,
+        similarity_top_k=sim_k,
+        text_qa_template=qa_prompt,
+        refine_template=rf_prompt,
+        response_mode="compact",
+    )
+
+    if response is not None:
+        logging.info(f"Response: {response}")
+        ret_text = response.response
+        nodes = []
+        for index, node in enumerate(response.source_nodes):
+            brief = node.source_text[:25].replace("\n", "")
+            nodes.append(
+                f"<details><summary>[{index+1}]\t{brief}...</summary><p>{node.source_text}</p></details>"
+            )
+        new_response = ret_text + "\n----------\n" + "\n\n".join(nodes)
+        logging.info(
+            f"Response: {colorama.Fore.BLUE}{ret_text}{colorama.Style.RESET_ALL}"
+        )
+        os.environ["OPENAI_API_KEY"] = ""
+        return ret_text, new_response, f"查询消耗了{llm_predictor.last_token_usage} tokens"
+    else:
+        logging.warning("No response found, returning None")
+        os.environ["OPENAI_API_KEY"] = ""
+        return None
+
+
+def add_space(text):
+    punctuations = {"，": "， ", "。": "。 ", "？": "？ ", "！": "！ ", "：": "： ", "；": "； "}
+    for cn_punc, en_punc in punctuations.items():
+        text = text.replace(cn_punc, en_punc)
+    return text

bin_public/app/overwrites.py

@@ -0,0 +1,38 @@
+from __future__ import annotations
+
+from llama_index import Prompt
+from typing import List, Tuple
+import mdtex2html
+
+from llama_func import *
+
+
+def compact_text_chunks(self, prompt: Prompt, text_chunks: List[str]) -> List[str]:
+    logging.debug("Compacting text chunks...🚀🚀🚀")
+    combined_str = [c.strip() for c in text_chunks if c.strip()]
+    combined_str = [f"[{index+1}] {c}" for index, c in enumerate(combined_str)]
+    combined_str = "\n\n".join(combined_str)
+    # resplit based on self.max_chunk_overlap
+    text_splitter = self.get_text_splitter_given_prompt(prompt, 1, padding=1)
+    return text_splitter.split_text(combined_str)
+
+
+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 message,
+            None if response is None else mdtex2html.convert(response, extensions=['fenced_code','codehilite','tables']),
+        )
+    return y

bin_public/config/presets.py

@@ -116,6 +116,9 @@ pre code {
 }
 """
 
+SIM_K = 5
+INDEX_QUERY_TEMPERATURE = 1.0
+
 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"]
@@ -144,3 +147,40 @@ 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
+
+WEBSEARCH_PTOMPT_TEMPLATE = """\
+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}
+Reply in 中文"""
+
+PROMPT_TEMPLATE = """\
+Context information is below.
+---------------------
+{context_str}
+---------------------
+Current date: {current_date}.
+Using the provided context information, write a comprehensive reply to the given query.
+Make sure to cite results using [number] notation after the reference.
+If the provided context information refer to multiple subjects with the same name, write separate answers for each subject.
+Use prior knowledge only if the given context didn't provide enough information.
+Answer the question: {query_str}
+Reply in 中文
+"""
+
+REFINE_TEMPLATE = """\
+The original question is as follows: {query_str}
+We have provided an existing answer: {existing_answer}
+We have the opportunity to refine the existing answer
+(only if needed) with some more context below.
+------------
+{context_msg}
+------------
+Given the new context, refine the original answer to better
+Answer in the same language as the question, such as English, 中文, 日本語, Español, Français, or Deutsch.
+If the context isn't useful, return the original answer.
+"""

bin_public/utils/tools.py

@@ -0,0 +1,299 @@
+# -*- coding:utf-8 -*-
+from __future__ import annotations
+from typing import TYPE_CHECKING, List
+import logging
+import json
+import os
+import datetime
+import hashlib
+import csv
+
+import gradio as gr
+from pypinyin import lazy_pinyin
+import tiktoken
+
+from bin_public.config.presets import *
+
+# 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 count_token(message):
+    encoding = tiktoken.get_encoding("cl100k_base")
+    input_str = f"role: {message['role']}, content: {message['content']}"
+    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 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_file(filename, system, history, chatbot):
+    logging.info("保存对话历史中……")
+    os.makedirs(HISTORY_DIR, exist_ok=True)
+    if filename.endswith(".json"):
+        json_s = {"system": system, "history": history, "chatbot": chatbot}
+        print(json_s)
+        with open(os.path.join(HISTORY_DIR, filename), "w") as f:
+            json.dump(json_s, f)
+    elif filename.endswith(".md"):
+        md_s = f"system: \n- {system} \n"
+        for data in history:
+            md_s += f"\n{data['role']}: \n- {data['content']} \n"
+        with open(os.path.join(HISTORY_DIR, filename), "w", encoding="utf8") as f:
+            f.write(md_s)
+    logging.info("保存对话历史完毕")
+    return os.path.join(HISTORY_DIR, filename)
+
+
+def save_chat_history(filename, system, history, chatbot):
+    if filename == "":
+        return
+    if not filename.endswith(".json"):
+        filename += ".json"
+    return save_file(filename, system, history, chatbot)
+
+
+def export_markdown(filename, system, history, chatbot):
+    if filename == "":
+        return
+    if not filename.endswith(".md"):
+        filename += ".md"
+    return save_file(filename, system, history, chatbot)
+
+
+def load_chat_history(filename, system, history, chatbot):
+    logging.info("加载对话历史中……")
+    if type(filename) != str:
+        filename = filename.name
+    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="")
+
+
+def reset_default():
+    global API_URL
+    API_URL = "https://api.openai.com/v1/chat/completions"
+    os.environ.pop("HTTPS_PROXY", None)
+    os.environ.pop("https_proxy", None)
+    return gr.update(value=API_URL), gr.update(value=""), "API URL 和代理已重置"
+
+
+def change_api_url(url):
+    global API_URL
+    API_URL = url
+    msg = f"API地址更改为了{url}"
+    logging.info(msg)
+    return msg
+
+
+def change_proxy(proxy):
+    os.environ["HTTPS_PROXY"] = proxy
+    msg = f"代理更改为了{proxy}"
+    logging.info(msg)
+    return msg
+
+
+def hide_middle_chars(s):
+    if len(s) <= 8:
+        return s
+    else:
+        head = s[:4]
+        tail = s[-4:]
+        hidden = "*" * (len(s) - 8)
+        return head + hidden + tail
+
+
+def submit_key(key):
+    key = key.strip()
+    msg = f"API密钥更改为了{hide_middle_chars(key)}"
+    logging.info(msg)
+    return key, msg
+
+
+def sha1sum(filename):
+    sha1 = hashlib.sha1()
+    sha1.update(filename.encode("utf-8"))
+    return sha1.hexdigest()
+
+
+def replace_today(prompt):
+    today = datetime.datetime.today().strftime("%Y-%m-%d")
+    return prompt.replace("{current_date}", today)

bin_public/utils/utils_db.py

@@ -1,6 +1,5 @@
 import psycopg2
 import datetime
-#from bin_public.config.config import HOLOGRES_CONFIG
 from bin_public.config.presets import *
 from dateutil import tz
 import os