0-3-2-understand-chroma-query

name	0.3.2-understand-chroma_query
description	[0.3.2] A search request containing a query vector (or text to embed) plus optional top-k and metadata filter paramete

understand-chroma_query

CALL NUMBER: deep_vector_database.chroma_query DEFINITION: A search request containing a query vector (or text to embed) plus optional top-k and metadata filter parameters.

Invoke this skill to understand chroma_query down to its primitives. The RELATIVE ROOT below is the least-fixed-point closure of everything it bundles from — the full import cone, grouped by the lib each prim comes from. Projected from a prover-typed KB (MAP/SWI-Prolog consistency gate): every reference below resolves.

THE RELATIVE ROOT (the import cone, by lib)

from deep_vector_database

• chroma_collection (d1): A named namespace within Chroma that stores embeddings, associated documents, metadata, and IDs as an isolated group.
• chroma_distance_metric (d1): The similarity measure used for nearest-neighbor ranking; Chroma supports cosine, euclidean, and dot product distances.
• chroma_filter (d1): A metadata predicate applied at query time to restrict which entries are considered during approximate nearest-neighbor search.
• chroma_document (d2): The raw text or payload string that is embedded and stored alongside its vector representation in a collection.
• chroma_embedding (d2): A dense vector of floating-point numbers produced by an embedding function, representing the semantic position of a document in high-dimensional space.
• chroma_entry_id (d2): A unique identifier string assigned to each embedded document within a collection; used for targeted get/delete operations.
• chroma_metadata (d2): Structured key-value attributes attached to an embedding entry; enables filtering and payload queries at query time.
• chroma_embedding_function (d3): A callable that converts raw input documents into embedding vectors; Chroma supports multiple backends (sentence-transformers, OpenAI, Cohere, etc.).

CONSUMERS (what needs this)

chroma_result_set

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Projected from the vector databases and embeddings KB (262 concepts / 150 relations) — consistency-typed by MAP; the facet list after the colon IS the cross-lib dependency web.

(leaf — this is an actual skill.)