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# Weaviate vector store

The `WeaviateVector` class provides vector search using [Weaviate](https://weaviate.io/), an open-source vector database. Collections are created with `vectorizer: none`, so Mastra supplies the embeddings, and Mastra manages ids, distance metrics, and metadata filtering on your behalf.

## Constructor options

**id** (`string`): Unique identifier for this vector store instance.

**httpHost** (`string`): Hostname of the Weaviate HTTP server. (Default: `localhost`)

**httpPort** (`number`): Port of the Weaviate HTTP server. (Default: `8080`)

**httpSecure** (`boolean`): Whether to use a secure (TLS) connection to the HTTP server. (Default: `false`)

**grpcHost** (`string`): Hostname of the Weaviate gRPC server. Defaults to the HTTP host.

**grpcPort** (`number`): Port of the Weaviate gRPC server. (Default: `50051`)

**grpcSecure** (`boolean`): Whether to use a secure (TLS) connection to the gRPC server. (Default: `false`)

**apiKey** (`string`): API key for authenticating with Weaviate (e.g. Weaviate Cloud).

**headers** (`Record<string, string>`): Additional headers to include in requests (e.g. third-party vectorizer API keys).

## Methods

### `createIndex()`

**indexName** (`string`): Name of the index to create.

**dimension** (`number`): Vector dimension (must match your embedding model).

**metric** (`'cosine' | 'euclidean' | 'dotproduct'`): Distance metric for similarity search. Mapped to Weaviate distances (cosine, l2-squared, dot). (Default: `cosine`)

### `upsert()`

**indexName** (`string`): Name of the index to upsert into.

**vectors** (`number[][]`): Array of embedding vectors.

**metadata** (`Record<string, any>[]`): Metadata for each vector.

**ids** (`string[]`): Optional vector ids. Auto-generated if not provided. Arbitrary ids are preserved via a deterministic UUIDv5 mapping.

### `query()`

**indexName** (`string`): Name of the index to query.

**queryVector** (`number[]`): Query vector to find similar vectors for.

**topK** (`number`): Number of results to return. (Default: `10`)

**filter** (`Record<string, any>`): Metadata filters (see below).

**includeVector** (`boolean`): Whether to include the stored vector in the results. (Default: `false`)

The store also implements `listIndexes()`, `describeIndex()`, `deleteIndex()`, `updateVector()`, `deleteVector()`, and `deleteVectors()`.

## Basic usage

```ts
import { WeaviateVector } from '@mastra/weaviate'

const store = new WeaviateVector({ id: 'my-store' })

await store.createIndex({ indexName: 'my_index', dimension: 1536, metric: 'cosine' })

await store.upsert({
  indexName: 'my_index',
  vectors: [[0.1, 0.2 /* ... */]],
  metadata: [{ text: 'sample', category: 'docs' }],
})

const results = await store.query({
  indexName: 'my_index',
  queryVector: [0.1, 0.2 /* ... */],
  topK: 5,
  filter: { category: 'docs' },
})
```

## Connecting to Weaviate Cloud

```ts
const store = new WeaviateVector({
  id: 'my-store',
  httpHost: 'my-cluster.weaviate.network',
  httpPort: 443,
  httpSecure: true,
  grpcHost: 'grpc-my-cluster.weaviate.network',
  grpcPort: 443,
  grpcSecure: true,
  apiKey: process.env.WEAVIATE_API_KEY,
})
```

## Metadata filtering

Filters use a MongoDB-style syntax and are translated to Weaviate's native filter API:

- Comparison: `$eq`, `$ne`, `$gt`, `$gte`, `$lt`, `$lte`
- Array: `$in`, `$nin`, `$all`
- Element: `$exists`
- Logical: `$and`, `$or`, `$not`

```ts
const results = await store.query({
  indexName: 'my_index',
  queryVector: [0.1, 0.2 /* ... */],
  filter: {
    $and: [{ category: { $in: ['docs', 'guides'] } }, { views: { $gt: 100 } }],
  },
})
```

### Notes and limitations

- Weaviate doesn't distinguish an explicitly stored `null` from an absent field, so null round-tripping isn't supported.
- `$regex`, `$size`, `$elemMatch`, `$nor`, and `$contains` aren't supported.
- Collection names are capitalized by Weaviate. The original index name is preserved in the collection description and returned by `listIndexes()` and `describeIndex()`.

## Related

- [Metadata Filters](https://mastra.ai/reference/rag/metadata-filters)