> ## Documentation Index
> Fetch the complete documentation index at: https://praison.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Vector Stores

> Vector database integrations

# Vector Stores

Vector stores provide embeddings storage and similarity search capabilities.

## Available Providers

| Provider              | Description             |
| --------------------- | ----------------------- |
| `MemoryVectorStore`   | In-memory (development) |
| `PineconeVectorStore` | Pinecone cloud          |
| `WeaviateVectorStore` | Weaviate                |
| `QdrantVectorStore`   | Qdrant                  |
| `ChromaVectorStore`   | ChromaDB                |

## Quick Start

```typescript theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
import { createMemoryVectorStore } from 'praisonai';

const store = createMemoryVectorStore('my-store');

// Create index
await store.createIndex({
  indexName: 'documents',
  dimension: 1536,
  metric: 'cosine'
});

// Upsert vectors
await store.upsert({
  indexName: 'documents',
  vectors: [{
    id: 'doc1',
    vector: [...],
    metadata: { text: 'Hello world' }
  }]
});

// Query
const results = await store.query({
  indexName: 'documents',
  vector: [...],
  topK: 5
});
```

## Pinecone

```typescript theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
import { createPineconeStore } from 'praisonai';

const store = createPineconeStore({
  apiKey: process.env.PINECONE_API_KEY,
  environment: 'us-east-1'
});
```

## CLI Usage

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
praisonai-ts vector info
praisonai-ts vector providers --json
```