mirror of
https://github.com/RYDE-WORK/Langchain-Chatchat.git
synced 2026-01-24 07:43:16 +08:00
71b528a2d1
* fix chat and knowledge_base_chat * 更新多卡部署 * update readme * update api and webui: 1. add download_doc to api 2. return local path or http url in kowledge_base_chat depends on no_remote_api 3. change assistant avater in webui * 解决多卡启动问题 * fix chat and knowledge_base_chat * 更新readme的lora加载方式 * update readme * 更新readme --------- Co-authored-by: liunux4odoo <liunu@qq.com>
64 lines
2.4 KiB
Python
64 lines
2.4 KiB
Python
from fastapi import Body
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from fastapi.responses import StreamingResponse
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from configs.model_config import llm_model_dict, LLM_MODEL
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from server.chat.utils import wrap_done
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from langchain.chat_models import ChatOpenAI
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from langchain import LLMChain
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from langchain.callbacks import AsyncIteratorCallbackHandler
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from typing import AsyncIterable
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import asyncio
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from langchain.prompts.chat import ChatPromptTemplate
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from typing import List
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from server.chat.utils import History
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def chat(query: str = Body(..., description="用户输入", examples=["恼羞成怒"]),
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history: List[History] = Body([],
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description="历史对话",
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examples=[[
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{"role": "user", "content": "我们来玩成语接龙，我先来，生龙活虎"},
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{"role": "assistant", "content": "虎头虎脑"}]]
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),
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stream: bool = Body(False, description="流式输出"),
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):
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history = [History(**h) if isinstance(h, dict) else h for h in history]
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async def chat_iterator(query: str,
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history: List[History] = [],
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) -> AsyncIterable[str]:
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callback = AsyncIteratorCallbackHandler()
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model = ChatOpenAI(
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streaming=True,
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verbose=True,
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callbacks=[callback],
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openai_api_key=llm_model_dict[LLM_MODEL]["api_key"],
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openai_api_base=llm_model_dict[LLM_MODEL]["api_base_url"],
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model_name=LLM_MODEL
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)
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chat_prompt = ChatPromptTemplate.from_messages(
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[i.to_msg_tuple() for i in history] + [("human", "{input}")])
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chain = LLMChain(prompt=chat_prompt, llm=model)
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# Begin a task that runs in the background.
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task = asyncio.create_task(wrap_done(
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chain.acall({"input": query}),
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callback.done),
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)
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if stream:
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async for token in callback.aiter():
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# Use server-sent-events to stream the response
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yield token
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else:
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answer = ""
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async for token in callback.aiter():
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answer += token
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yield answer
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await task
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return StreamingResponse(chat_iterator(query, history),
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media_type="text/event-stream")
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