---

name: rag-and-vector-search description: "Use for Feast RAG, vector search, vector-indexed fields, vector online stores, document embedding/chunking, retrieve_online_documents APIs, DocEmbedder, FeastVectorStore, and FeastRAGRetriever workflows." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Feast RAG And Vector Search

Use this sub-skill when the user asks to build, configure, debug, or validate Feast-powered vector retrieval or RAG workflows.

Route Here For

• Vector schema fields using Field(..., vector_index=True, vector_length=..., vector_search_metric=...).
• Vector online store choices and feature_store.yaml settings for Milvus, SQLite vector mode, Postgres/pgvector, Elasticsearch, Qdrant, MongoDB, or Faiss.
• SDK retrieval with FeatureStore.retrieve_online_documents_v2(...) or legacy retrieve_online_documents(...).
• RAG helper APIs: DocEmbedder, TextChunker, MultiModalEmbedder, FeastVectorStore, FeastIndex, and FeastRAGRetriever.
• Document ingestion: chunk documents, create embeddings, write vectors to the online store, retrieve top-k context, and format context for an LLM.

Route Elsewhere

• Generic Feast object modeling that is not vector-specific: ../feature-definitions/SKILL.md.
• Non-vector online/historical retrieval, materialization, or push ingestion: ../retrieval-and-materialization/SKILL.md.
• Feature server, MCP, auth, TLS, and remote endpoint setup: ../servers-and-remote/SKILL.md.
• Optional dependency selection across non-vector stores or custom store implementation: ../integrations-and-extensibility/SKILL.md.

Start Here

1. Read references/vector-reference.md to choose schema, store config, and retrieval API.
2. Read references/rag-workflows.md for document ingestion, DocEmbedder, FeastVectorStore, and FeastRAGRetriever patterns.
3. Use references/troubleshooting.md for install, optional extra, vector dimension, service, and API failures.
4. Run scripts/vector_config_lint.py --help before asking users to connect to a vector database.

Fast Safety Checks

python scripts/vector_config_lint.py path/to/feature_repo.py
python scripts/vector_config_lint.py feature_store.yaml --config-only
python scripts/vector_config_lint.py vector_snippet.json

Expected success output includes OK: lines and a final Summary:. Any ERROR: should be fixed before feast apply, materialization, or remote service debugging.