Langchain-Chatchat/webui_pages/dialogue/dialogue.py

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import streamlit as st
from webui_pages.utils import *
from streamlit_chatbox import *
from datetime import datetime
import streamlit_antd_components as sac
from server.chat.search_engine_chat import SEARCH_ENGINES
from typing import List, Dict
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chat_box = ChatBox()
def get_messages_history(history_len: int) -> List[Dict]:
def filter(msg):
'''
针对当前简单文本对话只返回每条消息的第一个element的内容
'''
content = [x._content for x in msg["elements"] if x._output_method in ["markdown", "text"]]
return {
"role": msg["role"],
"content": content[0] if content else "",
}
history = chat_box.filter_history(history_len, filter)
return history
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def dialogue_page(api: ApiRequest):
chat_box.init_session()
with st.sidebar:
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with st.expander("会话管理", True):
col_input, col_btn = st.columns(2)
new_chat_name = col_input.text_input(
"新会话名称",
placeholder="新会话名称",
label_visibility="collapsed",
key="new_chat_name",
)
def on_btn_new_chat():
new_chat_name = st.session_state.new_chat_name
if new_chat_name:
chat_box.use_chat_name(new_chat_name)
st.session_state.new_chat_name = ""
col_btn.button("新建会话", on_click=on_btn_new_chat)
chat_list = chat_box.get_chat_names()
cur_chat_name = sac.buttons(chat_list, 0)
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chat_box.use_chat_name(cur_chat_name)
cols = st.columns(3)
export_btn = cols[0]
if cols[1].button("Clear"):
chat_box.reset_history()
if cols[2].button("Delete"):
chat_box.del_chat_name(cur_chat_name, disabled=len(chat_list) <= 1)
def on_mode_change():
mode = st.session_state.dialogue_mode
text = f"已切换到 {mode} 模式。"
if mode == "知识库问答":
cur_kb = st.session_state.get("selected_kb")
if cur_kb:
text = f"{text} 当前知识库: `{cur_kb}`。"
st.toast(text)
# sac.alert(text, description="descp", type="success", closable=True, banner=True)
dialogue_mode = st.radio("请选择对话模式",
["LLM 对话",
"知识库问答",
"搜索引擎问答",
],
on_change=on_mode_change,
key="dialogue_mode",
)
history_len = st.slider("历史对话轮数:", 1, 10, 3)
# todo: support history len
def on_kb_change():
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):
kb_list = api.list_knowledge_bases(no_remote_api=True)
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selected_kb = st.selectbox(
"请选择知识库:",
kb_list,
on_change=on_kb_change,
key="selected_kb",
)
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)
chunk_content = st.checkbox("关联上下文", False, disabled=True)
chunk_size = st.slider("关联长度:", 0, 500, 250, disabled=True)
elif dialogue_mode == "搜索引擎问答":
search_engine = sac.buttons(SEARCH_ENGINES.keys(), 0)
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
chat_box.output_messages()
if prompt := st.chat_input("请输入对话内容换行请使用Ctrl+Enter"):
history = get_messages_history(history_len)
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chat_box.user_say(prompt)
if dialogue_mode == "LLM 对话":
chat_box.ai_say("正在思考...")
text = ""
r = api.chat_chat(prompt, history)
for t in r:
text += t
chat_box.update_msg(text)
chat_box.update_msg(text, streaming=False) # 更新最终的字符串,去除光标
elif dialogue_mode == "知识库问答":
history = get_messages_history(history_len)
chat_box.ai_say([
f"正在查询知识库: `{selected_kb}` ...",
Markdown("...", in_expander=True, title="知识库匹配结果"),
])
text = ""
for d in api.knowledge_base_chat(prompt, selected_kb, kb_top_k, history):
text += d["answer"]
chat_box.update_msg(text, 0)
chat_box.update_msg("\n\n".join(d["docs"]), 1, streaming=False)
chat_box.update_msg(text, 0, streaming=False)
elif dialogue_mode == "搜索引擎问答":
chat_box.ai_say([
f"正在执行{search_engine}搜索...",
Markdown("...", in_expander=True, title="网络搜索结果"),
])
text = ""
for d in api.bing_search_chat(prompt, search_engine, se_top_k):
text += d["answer"]
chat_box.update_msg(text, 0)
chat_box.update_msg("\n\n".join(d["docs"]), 1, streaming=False)
chat_box.update_msg(text, 0, streaming=False)
now = datetime.now()
export_btn.download_button(
"Export",
"".join(chat_box.export2md(cur_chat_name)),
file_name=f"{now:%Y-%m-%d %H.%M}_{cur_chat_name}.md",
mime="text/markdown",
)