72 lines
2.4 KiB
Python
72 lines
2.4 KiB
Python
import streamlit as st
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from streamlit_chatbox import *
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from webui_utils import *
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from streamlit_option_menu import option_menu
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api = ApiRequest()
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def dialogue_page():
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with st.sidebar:
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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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history_len = st.slider("历史对话轮数：", 1, 10, 1)
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if dialogue_mode == "知识库问答":
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selected_kb = st.selectbox("请选择知识库：", get_kb_list())
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with st.expander(f"{selected_kb} 中已存储文件"):
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st.write(get_kb_files(selected_kb))
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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("What is up?"):
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chat_box.user_say(prompt)
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chat_box.ai_say("正在思考...")
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# with api.chat_fastchat([{"role": "user", "content": "prompt"}], stream=streaming) as r: # todo: support history len
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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)
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# with api.chat_chat(prompt) as r:
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# for t in r.iter_text(None):
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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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def knowledge_base_edit_page():
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pass
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def config_page():
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pass
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if __name__ == "__main__":
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st.set_page_config("langchain-chatglm WebUI")
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chat_box = ChatBox()
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pages = {"对话": {"icon": "chat",
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"func": dialogue_page,
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},
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"知识库管理": {"icon": "database-fill-gear",
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"func": knowledge_base_edit_page,
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},
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"模型配置": {"icon": "gear",
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"func": config_page,
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}
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}
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with st.sidebar:
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selected_page = option_menu("langchain-chatglm",
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options=list(pages.keys()),
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icons=[i["icon"] for i in pages.values()],
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menu_icon="chat-quote",
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default_index=0)
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pages[selected_page]["func"]()
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