README.md•3.13 kB
# AlloyDB plugin
AlloyDB plugin provides indexer and retriever implementations that use AlloyDB with the pgvector extension for vector similarity search.
## Configuration
To use this plugin, first create a `PostgresEngine` instance:
```go
// Create PostgresEngine instance
// with basic authentication
pEngine, err := NewPostgresEngine(ctx,
WithUser('user'),
WithPassword('password'),
WithAlloyDBInstance('my-project', 'us-central1', 'my-cluster', 'my-instance'),
WithDatabase('my-database')
// with email authentication
pEngine, err := NewPostgresEngine(ctx,
WithCloudSQLInstance('my-project', 'us-central1', 'my-cluster', 'my-instance'),
WithDatabase('my-database'),
WithIAMAccountEmail('mail@company.com'))
// with custom pool
pool, err := pgxpool.New(ctx, "add_your_connection_string")
if err != nil {
return err
}
pEngine, err := NewPostgresEngine(ctx,
WithDatabase("db_test"),
WithPool(pool))
// Create the vector store table
err = pEngine.InitVectorstoreTable(ctx, VectorstoreTableOptions{
TableName: "documents",
VectorSize: 768,
SchemaName: "public",
ContentColumnName: "content",
EmbeddingColumn: "embedding",
MetadataJSONColumn: "custom_metadata",
IDColumn: Column{
Name: custom_id,
Nullable: false,
},
MetadataColumns: []Column{
{
Name: "source",
DataType: "text",
Nullable: true,
},
{
Name: "category",
DataType: "text",
Nullable: true,
},
},
OverwriteExisting: true,
StoreMetadata: true,
})
```
Then, specify the plugin when you initialize Genkit:
```go
postgres := &Postgres{
engine: pEngine,
}
g, err := genkit.Init(ctx, genkit.WithPlugins(postgres))
if err != nil {
return err
}
// To use the table you configured when you loaded the plugin:
cfg := &Config{
TableName: 'documents',
SchemaName: 'public',
ContentColumn: "content",
EmbeddingColumn: "embedding",
MetadataColumns: []string{"source", "category"},
IDColumn: "custom_id",
MetadataJSONColumn: "custom_metadata",
Embedder: embedder,
EmbedderOptions: nil,
}
// To index and retrieve from the configured table:
doc, retriever, err := DefineRetriever(ctx, g, postgres, cfg)
if err != nil {
retrun err
}
docs: []*ai.Document{{
Content: []*ai.Part{{
Kind: ai.PartText,
ContentType: "text/plain",
Text: "The product features include...",
}},
Metadata: map[string]any{"source": "website", "category": "product-docs", "custom_id": "doc-123"},
}}
if err := doc.Index(ctx, docs); err != nil {
return err
}
d2 := ai.DocumentFromText( "The product features include..." , nil)
resp, err := retriever.Retrieve(ctx, &ai.RetrieverRequest{
Query: d2,
k:5,
filter: "source='website' AND category='product-docs'"
})
if err != nil {
retrun err
}
```
See the [Retrieval-augmented generation](../rag.md) page for a general discussion on indexers and retrievers.