remote::weaviate
Description​
Weaviate is a vector database provider for Llama Stack. It allows you to store and query vectors directly within a Weaviate database. That means you're not limited to storing vectors in memory or in a separate service.
Features​
Weaviate supports:
- Store embeddings and their metadata
- Vector search
- Full-text search
- Hybrid search
- Document storage
- Metadata filtering
- Multi-modal retrieval
Usage​
To use Weaviate in your Llama Stack project, follow these steps:
- Install the necessary dependencies.
- Configure your Llama Stack project to use chroma.
- Start storing and querying vectors.
Installation​
To install Weaviate see the Weaviate quickstart documentation.
Documentation​
See Weaviate's documentation for more details about Weaviate in general.
Configuration​
| Field | Type | Required | Default | Description |
|---|---|---|---|---|
weaviate_api_key | str | None | No | The API key for the Weaviate instance | |
weaviate_cluster_url | str | None | No | localhost:8080 | The URL of the Weaviate cluster |
kvstore | utils.kvstore.config.RedisKVStoreConfig | utils.kvstore.config.SqliteKVStoreConfig | utils.kvstore.config.PostgresKVStoreConfig | utils.kvstore.config.MongoDBKVStoreConfig, annotation=NoneType, required=False, default='sqlite', discriminator='type' | No | Config for KV store backend (SQLite only for now) |
Sample Configuration​
weaviate_api_key: null
weaviate_cluster_url: ${env.WEAVIATE_CLUSTER_URL:=localhost:8080}
kvstore:
type: sqlite
db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/weaviate_registry.db