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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)
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