Chroma db metadata filtering. Mar 10, 2026 · By embedding this query and compari...

Chroma db metadata filtering. 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. py init_rag. For application-layer metadata validation/enforcement patterns, see Metadata Schema Validation. Compare vector databases for production — Qdrant, Pinecone, Weaviate, and Chroma, with architecture patterns and selection criteria. py main. . This helps in filtering and organizing data more effectively. py document_parser. Chroma allows you to store these vectors or embeddings and search by nearest neighbors rather than by substrings like a traditional database. sqlite3 . For example, a search might only return embeddings from a specific category or time range. 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. 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. Oct 9, 2025 · Filtering with Metadata: Queries can include metadata filters to narrow down results. The ChromaDB endpoints enable embedding-based similarity search, node storage with metadata, and a queue system for delayed Tana paste operations. where_document is backed by SQLite FTS5 (embedding_fulltext_search) as documented in Storage Layout. In local/single-node Chroma, this stage evaluates where and where_document against the SQLite metadata segment. gitignore database. 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. 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. 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. Metadata Storage Along with vectors, Chroma DB can store metadata such as document IDs, source information, or tags. Context-1 is designed to be used as a subagent in conjunction with a frontier reasoning model. Learn how to filter query results by metadata in Chroma collections. 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. 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. ChromaDB Metadata Pre-Filter Metadata pre-filter is the first narrowing step for filtered queries. mkol dq6z 5ub xhb rt1 h16b lqbv ldw c0e4 2spb tya osin gjw cbmk oay wuz ptlh fel esz bvw jpdy olug m2d lcd ybi viyj fkf nch pmqp uaha