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ChatLiteLLM 和 ChatLiteLLMRouter

LiteLLM 是一个简化调用 Anthropic、Azure、Huggingface、Replicate 等服务的库。

本笔记本介绍了如何开始使用 LangChain + LiteLLM I/O 库。

此集成包含两个主要类

  • ChatLiteLLM:用于 LiteLLM 基本用法的 LangChain 主要包装器(文档)。
  • ChatLiteLLMRouter:一个 ChatLiteLLM 包装器,利用 LiteLLM 的路由器(文档)。

目录

  1. 概述
  2. 设置
  3. 凭证
  4. 安装
  5. 实例化
  6. 调用
  7. 异步和流式功能
  8. API 参考

概述

集成详情

类别本地可序列化JS 支持包下载量最新包版本
ChatLiteLLMlangchain-litellmPyPI - DownloadsPyPI - Version
ChatLiteLLMRouterlangchain-litellmPyPI - DownloadsPyPI - Version

模型特性

工具调用结构化输出JSON 模式图片输入音频输入视频输入逐令牌流式传输原生异步令牌使用量对数概率

设置

要访问 ChatLiteLLMChatLiteLLMRouter 模型,您需要安装 langchain-litellm 包,并创建一个 OpenAI、Anthropic、Azure、Replicate、OpenRouter、Hugging Face、Together AI 或 Cohere 账户。然后,您必须获取 API 密钥并将其导出为环境变量。

凭证

您必须选择您想要的 LLM 提供商并注册以获取其 API 密钥。

示例 - Anthropic

前往 https://console.anthropic.com/ 注册 Anthropic 并生成 API 密钥。完成后,设置 ANTHROPIC_API_KEY 环境变量。

示例 - OpenAI

前往 https://platform.openai.com/api-keys 注册 OpenAI 并生成 API 密钥。完成后,设置 OPENAI_API_KEY 环境变量。

## Set ENV variables
import os

os.environ["OPENAI_API_KEY"] = "your-openai-key"
os.environ["ANTHROPIC_API_KEY"] = "your-anthropic-key"

安装

LangChain LiteLLM 集成可在 langchain-litellm 包中获取

%pip install -qU langchain-litellm

实例化

ChatLiteLLM

您可以通过提供 LiteLLM 支持的模型名称来实例化 ChatLiteLLM 模型。

from langchain_litellm import ChatLiteLLM

llm = ChatLiteLLM(model="gpt-4.1-nano", temperature=0.1)

ChatLiteLLMRouter

您还可以通过 此处 指定的方式定义模型列表,从而利用 LiteLLM 的路由功能。

from langchain_litellm import ChatLiteLLMRouter
from litellm import Router

model_list = [
{
"model_name": "gpt-4.1",
"litellm_params": {
"model": "azure/gpt-4.1",
"api_key": "<your-api-key>",
"api_version": "2024-10-21",
"api_base": "https://<your-endpoint>.openai.azure.com/",
},
},
{
"model_name": "gpt-4o",
"litellm_params": {
"model": "azure/gpt-4o",
"api_key": "<your-api-key>",
"api_version": "2024-10-21",
"api_base": "https://<your-endpoint>.openai.azure.com/",
},
},
]
litellm_router = Router(model_list=model_list)
llm = ChatLiteLLMRouter(router=litellm_router, model_name="gpt-4.1", temperature=0.1)

调用

无论您实例化的是 ChatLiteLLM 还是 ChatLiteLLMRouter,现在都可以通过 LangChain 的 API 使用 ChatModel。

response = await llm.ainvoke(
"Classify the text into neutral, negative or positive. Text: I think the food was okay. Sentiment:"
)
print(response)
content='Neutral' additional_kwargs={} response_metadata={'token_usage': Usage(completion_tokens=2, prompt_tokens=30, total_tokens=32, completion_tokens_details=CompletionTokensDetailsWrapper(accepted_prediction_tokens=0, audio_tokens=0, reasoning_tokens=0, rejected_prediction_tokens=0, text_tokens=None), prompt_tokens_details=PromptTokensDetailsWrapper(audio_tokens=0, cached_tokens=0, text_tokens=None, image_tokens=None)), 'model': 'gpt-3.5-turbo', 'finish_reason': 'stop', 'model_name': 'gpt-3.5-turbo'} id='run-ab6a3b21-eae8-4c27-acb2-add65a38221a-0' usage_metadata={'input_tokens': 30, 'output_tokens': 2, 'total_tokens': 32}

异步和流式功能

ChatLiteLLMChatLiteLLMRouter 也支持异步和流式功能

async for token in llm.astream("Hello, please explain how antibiotics work"):
print(token.text(), end="")
Antibiotics are medications that fight bacterial infections in the body. They work by targeting specific bacteria and either killing them or preventing their growth and reproduction.

There are several different mechanisms by which antibiotics work. Some antibiotics work by disrupting the cell walls of bacteria, causing them to burst and die. Others interfere with the protein synthesis of bacteria, preventing them from growing and reproducing. Some antibiotics target the DNA or RNA of bacteria, disrupting their ability to replicate.

It is important to note that antibiotics only work against bacterial infections and not viral infections. It is also crucial to take antibiotics as prescribed by a healthcare professional and to complete the full course of treatment, even if symptoms improve before the medication is finished. This helps to prevent antibiotic resistance, where bacteria become resistant to the effects of antibiotics.

API 参考

有关所有 ChatLiteLLMChatLiteLLMRouter 功能和配置的详细文档,请查阅 API 参考:https://github.com/Akshay-Dongare/langchain-litellm