嵌入
¥Embeddings
嵌入模型 创建一段文本的矢量表示。
¥Embedding models create a vector representation of a piece of text.
本页面记录了与各种模型提供商的集成,这些集成允许你在 LangChain 中使用嵌入。
¥This page documents integrations with various model providers that allow you to use embeddings in LangChain.
Pick your embedding model:
- OpenAI
- Azure
- AWS
- VertexAI
- MistralAI
- Cohere
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/openai
yarn add @langchain/openai
pnpm add @langchain/openai
OPENAI_API_KEY=your-api-key
import { OpenAIEmbeddings } from "@langchain/openai";
const embeddings = new OpenAIEmbeddings({
model: "text-embedding-3-large"
});
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/openai
yarn add @langchain/openai
pnpm add @langchain/openai
AZURE_OPENAI_API_INSTANCE_NAME=<YOUR_INSTANCE_NAME>
AZURE_OPENAI_API_KEY=<YOUR_KEY>
AZURE_OPENAI_API_VERSION="2024-02-01"
import { AzureOpenAIEmbeddings } from "@langchain/openai";
const embeddings = new AzureOpenAIEmbeddings({
azureOpenAIApiEmbeddingsDeploymentName: "text-embedding-ada-002"
});
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/aws
yarn add @langchain/aws
pnpm add @langchain/aws
BEDROCK_AWS_REGION=your-region
import { BedrockEmbeddings } from "@langchain/aws";
const embeddings = new BedrockEmbeddings({
model: "amazon.titan-embed-text-v1"
});
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/google-vertexai
yarn add @langchain/google-vertexai
pnpm add @langchain/google-vertexai
GOOGLE_APPLICATION_CREDENTIALS=credentials.json
import { VertexAIEmbeddings } from "@langchain/google-vertexai";
const embeddings = new VertexAIEmbeddings({
model: "text-embedding-004"
});
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/mistralai
yarn add @langchain/mistralai
pnpm add @langchain/mistralai
MISTRAL_API_KEY=your-api-key
import { MistralAIEmbeddings } from "@langchain/mistralai";
const embeddings = new MistralAIEmbeddings({
model: "mistral-embed"
});
Install dependencies
- npm
- yarn
- pnpm
npm i @langchain/cohere
yarn add @langchain/cohere
pnpm add @langchain/cohere
COHERE_API_KEY=your-api-key
import { CohereEmbeddings } from "@langchain/cohere";
const embeddings = new CohereEmbeddings({
model: "embed-english-v3.0"
});
await embeddings.embedQuery("Hello, world!");
| Name | Description |
|---|---|
| 阿里巴巴统一 | alibaba-tongyi} |
| 百度千帆 | baidu-qianfan} |
| DeepInfra | deepinfra-embeddings} |
| Gradient AI | gradient-ai} |
| HuggingFace 推断 | huggingface-inference} |
| Jina | jina-embeddings} |
| Llama CPP | llama-cpp} |
| Minimax | minimax} |
| Mixedbread AI | mixedbread-ai} |
| Nomic | nomic} |
| Prem AI | prem-ai} |
| 腾讯混元 | tencenthunyuan} |
| TensorFlow | tensorflow} |
| HuggingFace Transformers | huggingface-transformers} |
| Voyage AI | voyage-ai} |
| ZhipuAI | zhipuai} |