> ## Documentation Index
> Fetch the complete documentation index at: https://cndoc-langchain.site/llms.txt
> Use this file to discover all available pages before exploring further.

# QdrantVectorStore 集成

> 使用 LangChain JavaScript 与 QdrantVectorStore 进行集成。

<Tip>
  **兼容性**：仅在 Node.js 上可用。
</Tip>

[Qdrant](https://qdrant.tech/) 是一个向量相似性搜索引擎。它提供了一个生产就绪的服务，具有便捷的 API，用于存储、搜索和管理点——带有附加负载的向量。

本指南提供了快速入门 Qdrant [向量存储](/oss/javascript/integrations/vectorstores) 的概览。有关所有 `QdrantVectorStore` 功能和配置的详细文档，请参阅 [API 参考](https://reference.langchain.com/javascript/langchain-qdrant/QdrantVectorStore)。

## 概述

### 集成详情

| 类                                                                                                    | 包                                                          | [Python 支持](https://python.langchain.com/docs/integrations/vectorstores/qdrant/) |                                               版本                                               |
| :--------------------------------------------------------------------------------------------------- | :--------------------------------------------------------- | :------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------: |
| [`QdrantVectorStore`](https://reference.langchain.com/javascript/langchain-qdrant/QdrantVectorStore) | [`@langchain/qdrant`](https://npmjs.com/@langchain/qdrant) |                                         ✅                                        | ![NPM - Version](https://img.shields.io/npm/v/@langchain/qdrant?style=flat-square\&label=%20&) |

## 设置

要使用 Qdrant 向量存储，您需要设置一个 Qdrant 实例并安装 `@langchain/qdrant` 集成包。

本指南还将使用 [OpenAI 嵌入](/oss/javascript/integrations/embeddings/openai)，这需要您安装 `@langchain/openai` 集成包。如果您愿意，也可以使用[其他支持的嵌入模型](/oss/javascript/integrations/embeddings)。

<CodeGroup>
  ```bash npm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  npm install @langchain/qdrant @langchain/core @langchain/openai
  ```

  ```bash yarn theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  yarn add @langchain/qdrant @langchain/core @langchain/openai
  ```

  ```bash pnpm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  pnpm add @langchain/qdrant @langchain/core @langchain/openai
  ```
</CodeGroup>

安装所需的依赖项后，请按照 [Qdrant 设置说明](https://qdrant.tech/documentation/quickstart/) 使用 Docker 在您的计算机上运行一个 Qdrant 实例。记下您的容器运行的 URL。

### 凭证

完成此操作后，设置一个 `QDRANT_URL` 环境变量：

```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
// 例如 http://localhost:6333
process.env.QDRANT_URL = "your-qdrant-url"
```

如果您在本指南中使用 OpenAI 嵌入，您还需要设置您的 OpenAI 密钥：

```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
process.env.OPENAI_API_KEY = "YOUR_API_KEY";
```

如果您想获得模型调用的自动跟踪，也可以通过取消注释以下内容来设置您的 [LangSmith](/langsmith/home) API 密钥：

```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
// process.env.LANGSMITH_TRACING="true"
// process.env.LANGSMITH_API_KEY="your-api-key"
```

## 实例化

```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
import { QdrantVectorStore } from "@langchain/qdrant";
import { OpenAIEmbeddings } from "@langchain/openai";

const embeddings = new OpenAIEmbeddings({
  model: "text-embedding-3-small",
});

const vectorStore = await QdrantVectorStore.fromExistingCollection(embeddings, {
  url: process.env.QDRANT_URL,
  collectionName: "langchainjs-testing",
});
```

## 管理向量存储

### 向向量存储添加项目

```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
import type { Document } from "@langchain/core/documents";

const document1: Document = {
  pageContent: "The powerhouse of the cell is the mitochondria",
  metadata: { source: "https://example.com" }
};

const document2: Document = {
  pageContent: "Buildings are made out of brick",
  metadata: { source: "https://example.com" }
};

const document3: Document = {
  pageContent: "Mitochondria are made out of lipids",
  metadata: { source: "https://example.com" }
};

const document4: Document = {
  pageContent: "The 2024 Olympics are in Paris",
  metadata: { source: "https://example.com" }
}

const documents = [document1, document2, document3, document4];

await vectorStore.addDocuments(documents);
```

目前不支持顶级文档 ID 和删除。

## 查询向量存储

一旦您的向量存储已创建并且相关文档已添加，您很可能希望在链或代理运行期间对其进行查询。

### 直接查询

执行简单的相似性搜索可以按如下方式进行：

```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const filter = {
  "must": [
      { "key": "metadata.source", "match": { "value": "https://example.com" } },
  ]
};

const similaritySearchResults = await vectorStore.similaritySearch("biology", 2, filter);

for (const doc of similaritySearchResults) {
  console.log(`* ${doc.pageContent} [${JSON.stringify(doc.metadata, null)}]`);
}
```

```text theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
* The powerhouse of the cell is the mitochondria [{"source":"https://example.com"}]
* Mitochondria are made out of lipids [{"source":"https://example.com"}]
```

有关 Qdrant 过滤语法的更多信息，请参阅[此页面](https://qdrant.tech/documentation/concepts/filtering/)。请注意，所有值必须以 `metadata.` 为前缀。

如果您想执行相似性搜索并接收相应的分数，可以运行：

```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const similaritySearchWithScoreResults = await vectorStore.similaritySearchWithScore("biology", 2, filter)

for (const [doc, score] of similaritySearchWithScoreResults) {
  console.log(`* [SIM=${score.toFixed(3)}] ${doc.pageContent} [${JSON.stringify(doc.metadata)}]`);
}
```

```text theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
* [SIM=0.165] The powerhouse of the cell is the mitochondria [{"source":"https://example.com"}]
* [SIM=0.148] Mitochondria are made out of lipids [{"source":"https://example.com"}]
```

### 通过转换为检索器进行查询

您还可以将向量存储转换为[检索器](/oss/javascript/langchain/retrieval)，以便在您的链中更轻松地使用。

```typescript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const retriever = vectorStore.asRetriever({
  // 可选过滤器
  filter: filter,
  k: 2,
});
await retriever.invoke("biology");
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
  Document {
    pageContent: 'The powerhouse of the cell is the mitochondria',
    metadata: { source: 'https://example.com' },
    id: undefined
  },
  Document {
    pageContent: 'Mitochondria are made out of lipids',
    metadata: { source: 'https://example.com' },
    id: undefined
  }
]
```

### 用于检索增强生成

有关如何将此向量存储用于检索增强生成 (RAG) 的指南，请参阅以下部分：

* [使用 LangChain 构建 RAG 应用](/oss/javascript/langchain/rag)。
* [代理式 RAG](/oss/javascript/langgraph/agentic-rag)
* [检索文档](/oss/javascript/langchain/retrieval)

***

## API 参考

有关所有 `QdrantVectorStore` 功能和配置的详细文档，请参阅 [API 参考](https://reference.langchain.com/javascript/langchain-qdrant/QdrantVectorStore)。

***

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