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38 lines
1.1 KiB
Python
38 lines
1.1 KiB
Python
import streamlit as st
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from streamlit_chat import message
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from fastllm_pytools import llm
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import sys
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st.set_page_config(
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page_title="fastllm web demo",
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page_icon=":robot:"
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)
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@st.cache_resource
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def get_model():
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model = llm.model(sys.argv[1])
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return model
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if "messages" not in st.session_state:
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st.session_state.messages = []
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for i, (prompt, response) in enumerate(st.session_state.messages):
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with st.chat_message("user"):
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st.markdown(prompt)
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with st.chat_message("assistant"):
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st.markdown(response)
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if prompt := st.chat_input("请开始对话"):
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model = get_model()
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with st.chat_message("user"):
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st.markdown(prompt)
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with st.chat_message("assistant"):
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message_placeholder = st.empty()
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full_response = ""
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for chunk in model.stream_response(prompt, st.session_state.messages, one_by_one = True):
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full_response += chunk
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message_placeholder.markdown(full_response + "▌")
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message_placeholder.markdown(full_response)
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st.session_state.messages.append((prompt, full_response))
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