update streamlit ui: support latest knowledge base and search engine
chat api; export messages to markdown.
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liunux4odoo
parent
27d49be706
commit
3318cef751
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@ -18,5 +18,6 @@ unstructured[local-inference]
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streamlit>=1.25.0
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streamlit-option-menu
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streamlit-chatbox>=1.1.0
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streamlit-antd-components
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streamlit-chatbox>=1.1.6
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httpx
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9
webui.py
9
webui.py
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@ -1,5 +1,5 @@
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# 运行方式：
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# 1. 安装必要的包：pip install streamlit-option-menu streamlit-chatbox>=1.1.4
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# 1. 安装必要的包：pip install streamlit-option-menu streamlit-chatbox>=1.1.6
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# 2. 运行本机fastchat服务：python server\llm_api.py 或者 运行对应的sh文件
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# 3. 运行API服务器：python server/api.py。如果使用api = ApiRequest(no_remote_api=True)，该步可以跳过。
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# 4. 运行WEB UI：streamlit run webui.py --server.port 7860
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@ -9,11 +9,16 @@ from webui_pages.utils import *
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from streamlit_option_menu import option_menu
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from webui_pages import *
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api = ApiRequest()
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api = ApiRequest(base_url="http://127.0.0.1:7861", no_remote_api=False)
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if __name__ == "__main__":
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st.set_page_config("langchain-chatglm WebUI", layout="wide")
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if not chat_box.chat_inited:
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st.toast(f"欢迎使用 [`Langchain-Chatglm`](https://github.com/chatchat-space/langchain-chatglm) ! \n\n当前使用模型`{LLM_MODEL}`, 您可以开始提问了.")
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st.toast(" ")
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# pages = {"对话1": {"icon": "chat",
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# "func": dialogue_page,
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# },
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@ -1,3 +1,3 @@
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from .dialogue import dialogue_page
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from .dialogue import dialogue_page, chat_box
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from .knowledge_base import knowledge_base_page
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from .model_config import model_config_page
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@ -1 +1 @@
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from .dialogue import dialogue_page
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from .dialogue import dialogue_page, chat_box
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@ -1,41 +1,18 @@
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import streamlit as st
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from webui_pages.utils import *
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from streamlit_chatbox import *
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from datetime import datetime
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import streamlit_antd_components as sac
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from server.chat.search_engine_chat import SEARCH_ENGINES
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chat_box = ChatBox(
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greetings=[
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f"欢迎使用 [`Langchain-Chatglm`](https://github.com/chatchat-space/langchain-chatglm) ! 当前使用模型`{LLM_MODEL}`, 您可以开始提问了.",
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]
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)
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chat_box = ChatBox()
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def dialogue_page(api: ApiRequest):
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chat_box.init_session()
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with st.sidebar:
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def on_mode_change():
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mode = st.session_state.dialogue_mode
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text = f"已切换到 {mode} 模式。"
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if mode == "知识库问答":
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cur_kb = st.session_state.get("selected_kb")
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if cur_kb:
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text = f"{text} 当前知识库： `{cur_kb}`。"
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chat_box.ai_say(text, not_render=True)
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dialogue_mode = st.radio("请选择对话模式",
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["LLM 对话",
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"知识库问答",
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"Bing 搜索问答",
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"Duck 搜索问答",
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],
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on_change=on_mode_change,
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key="dialogue_mode",
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)
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history_len = st.slider("历史对话轮数：", 1, 10, 1, disabled=True)
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# todo: support history len
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with st.expander("会话管理", True):
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if st.button("清除历史对话内容"):
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chat_box.reset_history()
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col_input, col_btn = st.columns(2)
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new_chat_name = col_input.text_input(
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"新会话名称",
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@ -51,33 +28,58 @@ def dialogue_page(api: ApiRequest):
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st.session_state.new_chat_name = ""
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col_btn.button("新建会话", on_click=on_btn_new_chat)
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cols = st.columns(2)
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chat_list = chat_box.get_chat_names()
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try:
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index = chat_list.index(chat_box.cur_chat_name)
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except:
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index = 0
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cur_chat_name = cols[0].selectbox("当前会话：", chat_list, index, label_visibility="collapsed")
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cur_chat_name = sac.buttons(chat_list, 0)
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chat_box.use_chat_name(cur_chat_name)
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if cols[1].button("清除会话"):
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chat_box.del_chat_name(cur_chat_name)
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cols = st.columns(3)
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export_btn = cols[0]
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if cols[1].button("Clear"):
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chat_box.reset_history()
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if cols[2].button("Delete"):
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chat_box.del_chat_name(cur_chat_name, disabled=len(chat_list) <= 1)
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def on_mode_change():
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mode = st.session_state.dialogue_mode
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text = f"已切换到 {mode} 模式。"
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if mode == "知识库问答":
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cur_kb = st.session_state.get("selected_kb")
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if cur_kb:
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text = f"{text} 当前知识库： `{cur_kb}`。"
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st.toast(text)
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# sac.alert(text, description="descp", type="success", closable=True, banner=True)
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dialogue_mode = st.radio("请选择对话模式",
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["LLM 对话",
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"知识库问答",
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"搜索引擎问答",
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],
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on_change=on_mode_change,
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key="dialogue_mode",
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)
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history_len = st.slider("历史对话轮数：", 1, 10, 1, disabled=True)
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# todo: support history len
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def on_kb_change():
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chat_box.ai_say(f"已加载知识库： {st.session_state.selected_kb}", not_render=True)
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st.toast(f"已加载知识库： {st.session_state.selected_kb}")
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if dialogue_mode == "知识库问答":
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with st.expander("知识库配置", True):
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kb_list = api.list_knowledge_bases()
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kb_list = api.list_knowledge_bases(no_remote_api=True)
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selected_kb = st.selectbox(
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"请选择知识库：",
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kb_list,
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on_change=on_kb_change,
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key="selected_kb",
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)
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top_k = st.slider("匹配知识条数：", 1, 20, 3)
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kb_top_k = st.slider("匹配知识条数：", 1, 20, 3)
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score_threshold = st.slider("知识匹配分数阈值：", 0, 1000, 0, disabled=True)
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chunk_content = st.checkbox("关联上下文", False, disabled=True)
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chunk_size = st.slider("关联长度：", 0, 500, 250, disabled=True)
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elif dialogue_mode == "搜索引擎问答":
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search_engine = sac.buttons(SEARCH_ENGINES.keys(), 0)
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se_top_k = st.slider("匹配搜索结果条数：", 1, 20, 3)
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# Display chat messages from history on app rerun
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chat_box.output_messages()
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@ -93,23 +95,32 @@ def dialogue_page(api: ApiRequest):
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chat_box.update_msg(text)
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chat_box.update_msg(text, streaming=False) # 更新最终的字符串，去除光标
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elif dialogue_mode == "知识库问答":
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chat_box.ai_say(f"正在查询知识库： `{selected_kb}` ...")
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chat_box.ai_say([
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f"正在查询知识库： `{selected_kb}` ...",
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Markdown("...", in_expander=True, title="知识库匹配结果"),
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])
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text = ""
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for t in api.knowledge_base_chat(prompt, selected_kb, top_k):
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text += t
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chat_box.update_msg(text)
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chat_box.update_msg(text, streaming=False)
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elif dialogue_mode == "Bing 搜索问答":
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chat_box.ai_say("正在执行Bing搜索...")
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for d in api.knowledge_base_chat(prompt, selected_kb, kb_top_k):
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text += d["answer"]
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chat_box.update_msg(text, 0)
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chat_box.update_msg("\n\n".join(d["docs"]), 1, streaming=False)
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chat_box.update_msg(text, 0, streaming=False)
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elif dialogue_mode == "搜索引擎问答":
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chat_box.ai_say([
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f"正在执行{search_engine}搜索...",
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Markdown("...", in_expander=True, title="网络搜索结果"),
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])
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text = ""
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for t in api.bing_search_chat(prompt):
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text += t
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chat_box.update_msg(text)
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chat_box.update_msg(text, streaming=False)
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elif dialogue_mode == "Duck 搜索问答":
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chat_box.ai_say("正在执行Duckduck搜索...")
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text = ""
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for t in api.duckduckgo_search_chat(prompt):
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text += t
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chat_box.update_msg(text)
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chat_box.update_msg(text, streaming=False)
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for d in api.bing_search_chat(prompt, search_engine, se_top_k):
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text += d["answer"]
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chat_box.update_msg(text, 0)
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chat_box.update_msg("\n\n".join(d["docs"]), 1, streaming=False)
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chat_box.update_msg(text, 0, streaming=False)
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now = datetime.now()
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cols[0].download_button(
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"Export",
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"".join(chat_box.export2md(cur_chat_name)),
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file_name=f"{now:%Y-%m-%d %H.%M}_{cur_chat_name}.md",
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mime="text/markdown",
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)
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