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import os | |
from langchain.chat_models import ChatOpenAI | |
from langchain.schema import AIMessage, HumanMessage | |
import gradio as gr | |
os.environ["OPENAI_API_KEY"] = "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" | |
llm = ChatOpenAI(model='gpt-3.5-turbo-0613', streaming=True) | |
def stream_resp(message, history, flag1, flag2): | |
history_langchain_format = [] | |
for human, ai in history: | |
history_langchain_format.append(HumanMessage(content=human)) | |
history_langchain_format.append(AIMessage(content=ai)) | |
history_langchain_format.append(HumanMessage(content=message)) | |
partial_message = "" | |
for chunk in llm.stream(history_langchain_format): | |
partial_message = partial_message + chunk.content | |
yield partial_message | |
demo = gr.ChatInterface( | |
stream_resp, | |
chatbot=gr.Chatbot(height=430, label="ChatReport"), | |
textbox=gr.Textbox(placeholder="请输入问题", container=False, scale=7), | |
title="研报助手", | |
description="清芬院研报助手", | |
theme="soft", | |
examples=["你好", "你是谁"], | |
cache_examples=True, | |
retry_btn="retry", | |
undo_btn="清空输入框", | |
clear_btn="清空聊天记录", | |
additional_inputs=[ | |
gr.Checkbox(label = "研报问答"), | |
gr.Checkbox(label = "研报生成"), | |
], | |
).queue() | |
if __name__ == "__main__": | |
demo.launch(server_port=8080, share=True) | |