87 lines
3.6 KiB
Python
87 lines
3.6 KiB
Python
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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def dialogue_page(api: ApiRequest):
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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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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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if st.button("清除历史对话"):
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chat_box.reset_history()
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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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if dialogue_mode == "知识库问答":
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kb_list = api.list_knowledge_bases()
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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, disabled=True)
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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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# Display chat messages from history on app rerun
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chat_box.output_messages()
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if prompt := st.chat_input("请输入对话内容，换行请使用Ctrl+Enter"):
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chat_box.user_say(prompt)
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if dialogue_mode == "LLM 对话":
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chat_box.ai_say("正在思考...")
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text = ""
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r = api.chat_chat(prompt, no_remote_api=True)
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for t in r:
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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) # 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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text = ""
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for t in api.knowledge_base_chat(prompt, selected_kb):
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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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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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