1、安装环境

!pip install langchain openai langserve fastapi uvicorn sse_starlette

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2、设置项目路径，设置环境变量

# 导入 Google Colab 的 drive 模块，用来挂载 Google 云端硬盘
from google.colab import drive

# 把你的 Google Drive 挂载到 Colab 的 /content/drive 目录
drive.mount('/content/drive')

# 导入 os 模块，用来进行路径切换等文件系统操作
import os

# 定义你的项目路径（这里是你在 Google Drive 里的 LangServe 目录）
path = "/content/drive/My Drive/Colab/langchain/LangServe/"

# 将当前工作目录切换到上述路径，这样后续读写文件都以这个目录为根
os.chdir(path)

Mounted at /content/drive

# 设置OpenAI KEY环境变量
import os
import getpass
os.environ['OPENAI_API_KEY'] = getpass.getpass('OpenAI API Key:')

OpenAI API Key:··········

3、定义服务文件

from typing import List

from fastapi import FastAPI
from langchain.prompts import ChatPromptTemplate
from langchain.chat_models import ChatOpenAI
from langchain.schema import BaseOutputParser
from langserve import add_routes

# 定义链
class CommaSeparatedListOutputParser(BaseOutputParser[List[str]]):
    "将LLM的输出内容解析为列表"
    def parse(self, text:str):
        "解析LLM调用的输出"
        return text.strip().split(",")


template = """你是一个能生成以逗号分隔的列表的助手，用户会传入一个类别，你应该生成该类别下的5个对象，并以逗号分隔的形式返回。
只返回以逗号分隔的内容，不要包含其他内容。"""
human_template = "{text}"

chat_prompt = ChatPromptTemplate.from_messages([("system", template),("human", human_template),])
first_chain = chat_prompt | ChatOpenAI() | CommaSeparatedListOutputParser()

# 应用定义
app = FastAPI(title = "第一个LangChain应用", version = "0.0.1", description = "LangChain应用接口",)

# 添加链路由
add_routes(app, first_chain, path="/first_app")
if __name__ == "__main__":
    import uvicorn
    uvicorn.run(app, host="localhost", port=8000)

4、启动服务

!python serve.py

/usr/local/lib/python3.10/dist-packages/langchain/chat_models/__init__.py:31: LangChainDeprecationWarning: Importing chat models from langchain is deprecated. Importing from langchain will no longer be supported as of langchain==0.2.0. Please import from langchain-community instead:

`from langchain_community.chat_models import ChatOpenAI`.

To install langchain-community run `pip install -U langchain-community`.
  warnings.warn(
/usr/local/lib/python3.10/dist-packages/langchain_core/_api/deprecation.py:119: LangChainDeprecationWarning: The class `ChatOpenAI` was deprecated in LangChain 0.0.10 and will be removed in 0.3.0. An updated version of the class exists in the langchain-openai package and should be used instead. To use it run `pip install -U langchain-openai` and import as `from langchain_openai import ChatOpenAI`.
  warn_deprecated(
[32mINFO[0m:     Started server process [[36m1897[0m]
[32mINFO[0m:     Waiting for application startup.

 __          ___      .__   __.   _______      _______. _______ .______     ____    ____  _______
|  |        /   \     |  \ |  |  /  _____|    /       ||   ____||   _  \    \   \  /   / |   ____|
|  |       /  ^  \    |   \|  | |  |  __     |   (----`|  |__   |  |_)  |    \   \/   /  |  |__
|  |      /  /_\  \   |  . `  | |  | |_ |     \   \    |   __|  |      /      \      /   |   __|
|  `----./  _____  \  |  |\   | |  |__| | .----)   |   |  |____ |  |\  \----.  \    /    |  |____
|_______/__/     \__\ |__| \__|  \______| |_______/    |_______|| _| `._____|   \__/     |_______|

[1;32;40mLANGSERVE:[0m Playground for chain "/first_app/" is live at:
[1;32;40mLANGSERVE:[0m  │
[1;32;40mLANGSERVE:[0m  └──> /first_app/playground/
[1;32;40mLANGSERVE:[0m
[1;32;40mLANGSERVE:[0m See all available routes at /docs/

[1;31;40mLANGSERVE:[0m ⚠️ Using pydantic 2.7.1. OpenAPI docs for invoke, batch, stream, stream_log endpoints will not be generated. API endpoints and playground should work as expected. If you need to see the docs, you can downgrade to pydantic 1. For example, `pip install pydantic==1.10.13`. See https://github.com/tiangolo/fastapi/issues/10360 for details.

[32mINFO[0m:     Application startup complete.
[31mERROR[0m:    [Errno 99] error while attempting to bind on address ('::1', 8001, 0, 0): cannot assign requested address
[32mINFO[0m:     Waiting for application shutdown.
[32mINFO[0m:     Application shutdown complete.