Add Vector Search semantic product discovery example#153
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janniklasrose wants to merge 2 commits intomainfrom
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Add Vector Search semantic product discovery example#153janniklasrose wants to merge 2 commits intomainfrom
janniklasrose wants to merge 2 commits intomainfrom
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Demonstrates a Direct Access Vector Search index and endpoint declared
as bundle resources (vector_search_endpoints, vector_search_indexes),
tested e2e against staging with the direct engine.
Key design decisions:
- Jobs use resource references (${resources.*.name}) for endpoint and
index names so dev-mode prefixing flows through automatically
- schema_json uses flat {"col":"type"} format required by the API
- Notebooks embed descriptions/queries explicitly (Direct Access indexes
don't auto-embed; that's a Delta Sync feature)
- engine: direct set in bundle config so no env var is needed
Co-authored-by: Isaac
Co-authored-by: Isaac
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Summary
Adds a Declarative Automation Bundle under
contrib/vector_search_product_discovery/that demonstrates semantic product search end-to-end with Databricks Vector Search:vector_search_endpoints+vector_search_indexesdeclared as bundle resources, with jobs referencing them via${resources.*.name}so dev-mode prefixing flows through automaticallyengine: directindatabricks.yml); descriptions are embedded explicitly in01_upsert_products.pyand the query notebook embeds the query before callingsimilarity_search— Direct Access indexes don't auto-embed (that's a Delta Sync feature)schema_jsonuses the flat{"col":"type"}form required by the APIDependency
Requires databricks/cli#5123 (still open), which lands
vector_search_indexesas a first-class DABs resource on the direct engine. Until that PR merges and ships in a CLI release,databricks bundle deployagainst this example will fail to recognize thevector_search_indexesresource type.Test plan
databricks bundle validateagainst a CLI built from Add vector_search_indexes resource (direct engine) cli#5123databricks bundle deploy— endpoint reaches ONLINE, index createddatabricks bundle run product_discovery_setup— products embedded and upserteddatabricks bundle run product_discovery_query --params "query=footwear for slippery wet trails"— returns ranked resultsdatabricks bundle destroy— clean teardownThis pull request and its description were written by Isaac.