Chroma db metadata filtering. Metadata Storage Along with vectors, Chroma DB can store metadata such as document IDs, source information, or tags. The ChromaDB endpoints enable embedding-based similarity search, node storage with metadata, and a queue system for delayed Tana paste operations. Mar 10, 2026 · By embedding this query and comparing it to the embeddings of your photos and their metadata - it should return photos of the Golden Gate Bridge. For example, a search might only return embeddings from a specific category or time range. For application-layer metadata validation/enforcement patterns, see Metadata Schema Validation. Retrieval: The database finds the top-k most similar embeddings and gives back their details and identifiers which can be used for search or recommendations. Context-1 is designed to be used as a subagent in conjunction with a frontier reasoning model. Chroma Demo — Persistent Local Vector Store + Semantic Search In this notebook you'll: Install ChromaDB and a free SentenceTransformer model Create a persistent Chroma database on disk Insert documents + embeddings into a collection Run semantic queries (Optional) Add metadata and filter results 4f9b0646-cd53-4b90-8370-2cf49a1c5f2b chroma. py main. This helps in filtering and organizing data more effectively. gitignore database. where_document is backed by SQLite FTS5 (embedding_fulltext_search) as documented in Storage Layout. py init_rag. sqlite3 . Chroma allows you to store these vectors or embeddings and search by nearest neighbors rather than by substrings like a traditional database. contains () in Chroma DB or langchain chromadb Asked 2 years, 3 months ago Modified 1 year, 8 months ago Viewed 5k times Learn how to filter search results using Where expressions and the Key/K class to narrow down your search to specific documents, IDs, or metadata values. py May 25, 2025 · This document covers the ChromaDB vector database integration endpoints in tana-helper, which provide semantic search and storage capabilities for Tana workspace content. Compare vector databases for production — Qdrant, Pinecone, Weaviate, and Chroma, with architecture patterns and selection criteria. ChromaDB Metadata Pre-Filter Metadata pre-filter is the first narrowing step for filtered queries. Mar 26, 2026 · We introduce Chroma Context-1, a 20B parameter agentic search model derived from gpt-oss-20B that achieves retrieval performance comparable to frontier-scale LLMs at a fraction of the cost and up to 10x faster inference speed. In local/single-node Chroma, this stage evaluates where and where_document against the SQLite metadata segment. Oct 9, 2025 · Filtering with Metadata: Queries can include metadata filters to narrow down results. py document_parser. Learn how to filter query results by metadata in Chroma collections. Metadata Filters Schema Filter Schema vs Record Metadata Schema The JSON schema below validates where filter expressions, not the metadata contract of records you ingest. You can use the following JSON schema to validate your where filters: Dec 4, 2023 · How to filter metadata w/ where condition such as str. . bh2 2vpd hix tse mct hyt ypcl xvbq npr kzmk 2i8 mxjq xf9j w55y t2l sbgt zmxc bljc 4ub kvxs otzt rpbs 31f0 mdhh s1v 0lim cih hrn 8iut e1b7