init customize base on streamlit
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.gitignore
vendored
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.gitignore
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# Default ignored files
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venv
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.idea
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customize.css
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customize.css
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main.py
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main.py
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# This is a sample Python script.
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# Press Shift+F10 to execute it or replace it with your code.
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# Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.
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def print_hi(name):
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# Use a breakpoint in the code line below to debug your script.
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print(f'Hi, {name}') # Press Ctrl+F8 to toggle the breakpoint.
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# Press the green button in the gutter to run the script.
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if __name__ == '__main__':
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print_hi('PyCharm')
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# See PyCharm help at https://www.jetbrains.com/help/pycharm/
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origin.py
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origin.py
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import os
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import streamlit as st
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import torch
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from transformers import AutoModel, AutoTokenizer
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MODEL_PATH = os.environ.get('MODEL_PATH', 'THUDM/chatglm3-6b')
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TOKENIZER_PATH = os.environ.get("TOKENIZER_PATH", MODEL_PATH)
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DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'
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# 设置页面标题、图标和布局
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st.set_page_config(
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page_title="ChatGLM3-6B 演示",
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page_icon=":robot:",
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layout="wide"
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)
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@st.cache_resource
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def get_model():
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tokenizer = AutoTokenizer.from_pretrained(TOKENIZER_PATH, trust_remote_code=True)
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if 'cuda' in DEVICE: # AMD, NVIDIA GPU can use Half Precision
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model = AutoModel.from_pretrained(MODEL_PATH, trust_remote_code=True).to(DEVICE).eval()
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else: # CPU, Intel GPU and other GPU can use Float16 Precision Only
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model = AutoModel.from_pretrained(MODEL_PATH, trust_remote_code=True).float().to(DEVICE).eval()
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# 多显卡支持,使用下面两行代替上面一行,将num_gpus改为你实际的显卡数量
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# from utils import load_model_on_gpus
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# model = load_model_on_gpus("THUDM/chatglm3-6b", num_gpus=2)
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return tokenizer, model
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# 加载Chatglm3的model和tokenizer
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tokenizer, model = get_model()
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# 初始化历史记录和past key values
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if "history" not in st.session_state:
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st.session_state.history = []
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if "past_key_values" not in st.session_state:
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st.session_state.past_key_values = None
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# 设置max_length、top_p和temperature
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max_length = st.sidebar.slider("max_length", 0, 32768, 8192, step=1)
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top_p = st.sidebar.slider("top_p", 0.0, 1.0, 0.8, step=0.01)
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temperature = st.sidebar.slider("temperature", 0.0, 1.0, 0.6, step=0.01)
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# 清理会话历史
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buttonClean = st.sidebar.button("清理会话历史", key="clean")
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if buttonClean:
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st.session_state.history = []
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st.session_state.past_key_values = None
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if torch.cuda.is_available():
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torch.cuda.empty_cache()
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st.rerun()
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# 渲染聊天历史记录
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for i, message in enumerate(st.session_state.history):
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if message["role"] == "user":
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with st.chat_message(name="user", avatar="user"):
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st.markdown(message["content"])
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else:
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with st.chat_message(name="assistant", avatar="assistant"):
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st.markdown(message["content"])
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# 输入框和输出框
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with st.chat_message(name="user", avatar="user"):
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input_placeholder = st.empty()
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with st.chat_message(name="assistant", avatar="assistant"):
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message_placeholder = st.empty()
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# 获取用户输入
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prompt_text = st.chat_input("请输入您的问题")
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# 如果用户输入了内容,则生成回复
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if prompt_text:
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input_placeholder.markdown(prompt_text)
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history = st.session_state.history
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past_key_values = st.session_state.past_key_values
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for response, history, past_key_values in model.stream_chat(
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tokenizer,
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prompt_text,
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history,
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past_key_values=past_key_values,
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max_length=max_length,
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top_p=top_p,
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temperature=temperature,
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return_past_key_values=True,
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):
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message_placeholder.markdown(response)
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# 更新历史记录和past key values
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st.session_state.history = history
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st.session_state.past_key_values = past_key_values
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105
web_demo.py
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web_demo.py
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import streamlit as st
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st.set_page_config(
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page_title="web-demo",
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page_icon=":web-demo:",
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layout="wide",
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)
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st.markdown(""" <link rel="stylesheet" type="text/css" href="http://localhost:4173/customize.css"> """,
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unsafe_allow_html=True)
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# 初始化历史记录和past key values
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if "history" not in st.session_state:
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st.session_state.history = []
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if "past_key_values" not in st.session_state:
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st.session_state.past_key_values = None
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# 设置max_length、top_p和temperature
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# max_length = st.sidebar.slider("max_length", 0, 32768, 8192, step=1)
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# top_p = st.sidebar.slider("top_p", 0.0, 1.0, 0.8, step=0.01)
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# temperature = st.sidebar.slider("temperature", 0.0, 1.0, 0.6, step=0.01)
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# 清理会话历史
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# buttonClean = st.sidebar.button("清理会话历史", key="clean")
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# if buttonClean:
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# st.session_state.history = []
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# st.session_state.past_key_values = None
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# st.rerun()
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mainContainer = st.container()
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if len(st.session_state.history) == 0:
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emptyContent = st.markdown("""<div class="example">
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<div class="chat-demo">
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<div><img class="logo" src="https://chat.topaiart.cn/assets/logo-3-d4405d8e.png"/></div>
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<div class="case-list">
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<div class="case-col">
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<div class="case-title">例子</div>
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<div class="case-item">用简单的术语解释质量守恒定律</div>
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<div class="case-item">对 10 岁生日有什么创意吗？</div>
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<div class="case-item">
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如何在 Javascript 中发出 HTTP 请求？request in Javascript?
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</div>
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</div>
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<div class="case-col">
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<div class="case-title">能力</div>
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<div class="case-item">能记住用户早些时候的对话</div>
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<div class="case-item">允许用户提供后续更正</div>
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<div class="case-item">会拒绝不当的请求</div>
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</div>
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<div class="case-col">
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<div class="case-title">提醒</div>
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<div class="case-item">少数可能会产生错误信息</div>
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<div class="case-item">可能会产生不当的指令或有偏见的内容</div>
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<div class="case-item">对 2021 年后的世界和事件的了解有限</div>
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</div>
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</div>
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</div>
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</div>""", unsafe_allow_html=True)
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else:
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# 渲染聊天历史记录
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for i, message in enumerate(st.session_state.history):
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if message["role"] == "user":
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with mainContainer.chat_message(name="user", avatar="user"):
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st.markdown(message["content"])
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else:
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with mainContainer.chat_message(name="assistant", avatar="assistant"):
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st.markdown(message["content"])
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# 输入框和输出框
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with mainContainer.chat_message(name="user", avatar="user"):
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input_placeholder = st.empty()
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with mainContainer.chat_message(name="assistant", avatar="assistant"):
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message_placeholder = st.empty()
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# 获取用户输入
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prompt_text = st.chat_input("请输入您的问题")
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# 如果用户输入了内容,则生成回复
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if prompt_text:
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# 处理历史为空的情况
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if len(st.session_state.history) == 0:
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emptyContent.empty()
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# 输入框和输出框
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with mainContainer.chat_message(name="user", avatar="user"):
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input_placeholder = st.empty()
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with mainContainer.chat_message(name="assistant", avatar="assistant"):
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message_placeholder = st.empty()
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history = st.session_state.history
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past_key_values = st.session_state.past_key_values
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history.append({
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'content': prompt_text, "role": 'user'
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})
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response = "您的问题:”" + prompt_text + "“,我暂时无法处理！请重新问一个问题吧!"
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history.append({
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'content': response, "role": 'system'
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})
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input_placeholder.markdown(prompt_text)
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message_placeholder.markdown(response)
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# 更新历史记录和past key values
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st.session_state.history = history
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st.session_state.past_key_values = past_key_values
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# st.markdown("""
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# <footer>
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# <div>您的反馈将帮助我们改进<br/>我们的目标是让您和AI更自然、更安全地进行互动</div>
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# </footer>
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# """, unsafe_allow_html=True)
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