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+---
+title: AlloyDB plugin
+description: Learn how to configure and use the Genkit AlloyDB plugin for Go to integrate with pgvector extension.
+---
+
+The AlloyDB plugin provides indexer and retriever implementatons that use the [AlloyDB](https://cloud.google.com/alloydb/docs) and [pgvector](https://github.com/pgvector/pgvector) extension.
+
+## Configuration
+
+To use this plugin, follow these steps: 
+
+1. Import the plugin 
+
+	```go
+	import "github.com/firebase/genkit/go/plugins/alloydb"
+	```
+
+2. Create a `PostgresEngine` instance:
+
+	- Using basic authentication
+		```go
+		pEngine, err := alloydb.NewPostgresEngine(ctx,
+				WithUser('user'),
+				WithPassword('password'),
+				WithAlloyDBInstance('my-project', 'us-central1', 'my-cluster', 'my-instance'),
+				WithDatabase('my-database')
+		```
+	- Using email authentication
+		```go
+		pEngine, err := alloydb.NewPostgresEngine(ctx,
+			WithAlloyDBInstance('my-project', 'us-central1', 'my-cluster', 'my-instance'),
+			WithDatabase('my-database'),
+			WithIAMAccountEmail('mail@company.com'))
+		```
+	- Using custom pool
+		```go
+
+
+
+		pool, err := pgxpool.New(ctx, "add_your_connection_string")
+		if err != nil {
+			return err
+		}
+
+		pEngine, err := alloydb.NewPostgresEngine(ctx,
+			WithDatabase("db_test"),
+			WithPool(pool))
+
+		```
+
+3. Create the Postgres plugin
+	- Using plugin method Init
+
+
+		```go
+			postgres := &alloydb.Postgres{
+				engine: pEngine,
+			}
+
+			if err := (postgres).Init(ctx, g); err != nil {
+				return err
+			}
+		```
+
+	- Using the genkit method init
+
+		```go
+			postgres := &alloydb.Postgres{
+				engine: pEngine,
+			}
+
+			g, err := genkit.Init(ctx, genkit.WithPlugins(postgres))
+
+			if  err != nil {
+				return err
+			}
+
+		```
+
+## Usage
+
+To add documents to a AlloyDB index, first create an index definition that specifies the features of the table:
+
+```go
+cfg := &alloydb.Config{
+	TableName:             'documents',
+	SchemaName:            'public',
+	ContentColumn:         "content",
+	EmbeddingColumn:       "embedding",
+	MetadataColumns:       []string{"source", "category"},
+	IDColumn:              "custom_id",
+	MetadataJSONColumn:    "custom_metadata",
+	Embedder:              embedder,
+	EmbedderOptions:       nil,
+}
+
+doc, retriever, err := postgresql.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
+}
+```
+
+Similarly, to retrieve documents from an index,use the retriever
+method:
+
+```go
+doc,  retriever, err := alloydb.DefineRetriever(ctx, g, postgres, cfg)
+if err != nil {
+  retrun 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
+}
+```
+
+It's also posible to use the Retrieve method from Retriever
+
+```go
+
+d2 := ai.DocumentFromText( "The product features include..." , nil)
+
+retrieverOptions := &alloydb.RetrieverOptions{
+	k:5,
+    filter: "source='website' AND category='product-docs'"
+}
+
+resp, err := ai.Retrieve(ctx, retriever,ai.WithDocs(d2), &ai.WithConfig(retrieverOptions))
+if err != nil {
+    retrun err
+}
+```
+
+
+See the [Retrieval-augmented generation](/go/docs/rag) page for a general
+discussion on using indexers and retrievers for RAG.