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Choose a vector-store adapter ​

Level: Pattern · Estimated time: 35 minutes

Outcome ​

Move the same embedDocuments and VectorSearchIndex flow from local memory to a durable backend without coupling agent code to a vendor SDK.

When to use it ​

Use an adapter when embeddings must survive restarts, serve multiple workers, or exceed local memory. Keep InMemoryVectorStore for deterministic tests and small demonstrations.

Shared flow ​

application documents → embedDocuments → adapter connect(...) → upsertDocuments(...) → store.index(embeddingModel) → search(...) or .asTool(...).

pgvector example ​

ts
import { embedDocuments } from "@anvia/core/embeddings";
import { PgVectorStore } from "@anvia/pgvector";

const store = await PgVectorStore.connect<Note>({
  connectionString: process.env.DATABASE_URL!,
  tableName: "anvia_notes",
  vectorSize: 384,
});
await store.upsertDocuments(embedded);
const index = store.index(embeddingModel);
const results = await index.search({ query: "technology demand", topK: 5 });

vectorSize must match the embedding model. Provision tables, collections, indexes, namespaces, and credentials using deployment automation rather than request handlers.

Swap at the composition root ​

Keep your application dependent on the common search surface and select the adapter in one module. Current packages cover Chroma, LanceDB, Milvus, pgvector, Pinecone, Qdrant, Redis, and Weaviate. Connection options and filter support remain backend-specific, so swapping is not configuration-only until your contract tests pass.

Expected behavior ​

After an upsert, another process can search the same durable collection. Re-upserting a stable ID replaces that document according to the adapter contract. Search returns common result objects with score, ID, original document, and optional metadata.

Failure cases ​

Dimension mismatch, missing indexes, connection loss, rate limits, partial batches, unsupported filters, namespace mistakes, and consistency lag require explicit recovery. Do not automatically create production resources from an untrusted request.

Security and ownership ​

The application owns database credentials, network access, tenant routing, encryption, backups, retention, and deletion. Use least-privileged service accounts and separate environments. Treat metadata filters as one policy layer, not your only tenant boundary.

Production changes and tests ​

Add health checks, timeouts, bounded batches, retry/idempotency policy, migrations, capacity alerts, and backup/restore drills. Run the same adapter contract suite for upsert, search, thresholds, filters, deletion, inspection, empty collections, and dimension errors.

Runnable references ​

Extensions ​

Build a shadow-read migration, adapter latency dashboards, per-tenant namespaces, hybrid search, and a corpus re-embedding plan with explicit model-version metadata.

Built for Anvia.