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import streamlit as st
from langchain_core.messages import SystemMessage, HumanMessage, AIMessage
from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI
from loguru import logger
from ui.Component import side_bar_links
st.set_page_config(
page_title='工具箱',
page_icon='🔨',
layout='centered',
)
st.title("学术中英互译")
def clean_screen():
st.session_state.ac_translate_history = []
st.session_state.ac_code_text = ''
with st.sidebar:
side_bar_links()
st.toggle('翻译模式', key='is_en2zh')
if st.session_state.get('is_en2zh'):
st.caption('en → zh')
else:
st.caption('zh → en')
st.button("清屏", on_click=clean_screen)
if 'ac_translate_history' not in st.session_state:
st.session_state.ac_translate_history = []
if 'ac_code_text' not in st.session_state:
st.session_state.ac_code_text = ''
chat_container = st.container(height=600, border=False)
with chat_container:
for message in st.session_state.ac_translate_history:
icon = 'logo.png' if message['role'] != 'user' else None
with st.chat_message(message['role']):
st.markdown(message['content'])
if st.session_state.ac_code_text:
with st.container(height=120, border=False):
st.code(st.session_state.ac_code_text, 'markdown')
def ac_translate(original_text: str, is_en2zh: bool):
if is_en2zh:
_prompt = ChatPromptTemplate.from_messages(
[
SystemMessage(content="你的任务是将用户给出的英文文本翻译为**语句通顺的**中文，同时务必注意不能漏翻或错翻。"
"对于专有名词或公式等，若没有合适的译文可以保留原本英文文本不做翻译。"
"对于原句子中被markdown代码块或latex公式包裹的内容，不做改动原样返回。"),
("human", "这是你需要翻译的句子:\n{original_text}\n\n注意你的回答只需要给出翻译后的英文文本，不要包含其他东西")
]
)
else:
_prompt = ChatPromptTemplate.from_messages(
[
SystemMessage(content="你的任务是以**学术论文的风格**将用户给出的中文文本翻译成英文，务必注意不能漏翻或错翻。"),
("human", "这是你需要翻译的句子:\n{original_text}\n\n注意你的回答只需要给出翻译后的英文文本，不要包含其他东西")
]
)
llm = ChatOpenAI(
model_name="gpt-4o-mini",
temperature=0,
openai_api_key=st.secrets['gpt_key'],
streaming=True
)
chain = _prompt | llm
llm_result = chain.stream({"original_text": original_text})
return llm_result
if prompt := st.chat_input():
logger.info(f'[translate]: {prompt}')
chat_container.chat_message("human").write(prompt)
st.session_state.ac_translate_history.append({'role': 'user', 'content': prompt})
response = ac_translate(prompt, st.session_state.get('is_en2zh'))
translate_result = chat_container.chat_message("ai").write_stream(response)
st.session_state.ac_translate_history.append({'role': 'assistant', 'content': translate_result})
st.session_state.ac_code_text = translate_result
st.rerun()
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