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from meutils.pipe import * |
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from chatllm.applications import ChatBase |
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from chatllm.utils import llm_load4chat |
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import streamlit as st |
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from appzoo.streamlit_app.utils import display_pdf, reply4input |
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st.set_page_config('🔥ChatLLM', layout='centered', initial_sidebar_state='collapsed') |
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@st.cache_resource |
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def get_chat_func(): |
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chat_func = llm_load4chat() |
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return chat_func |
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chat_func = get_chat_func() |
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qa = ChatBase(chat_func=chat_func) |
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def reply_func(query): |
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for response, _ in qa(query=query): |
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yield response |
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container = st.container() |
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text = st.text_area(label="用户输入", height=100, placeholder="请在这儿输入您的问题") |
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if st.button("发送", key="predict"): |
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with st.spinner("AI正在思考,请稍等........"): |
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history = st.session_state.get('state') |
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st.session_state["state"] = reply4input(text, history, container=container, reply_func=reply_func) |
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