Store embeddings and metadata with vector and full-text search.
npx skills add https://github.com/kaminocorp/hermes-alpha --skill chroma-kaminocorp
Please help me install this Agent Skill. Skill: chroma Source: https://github.com/kaminocorp/hermes-alpha/tree/main/hermes-agent/skills/mlops/vector-databases/chroma Command: npx skills add https://github.com/kaminocorp/hermes-alpha --skill chroma-kaminocorp
Open-source embedding databases are essential for building AI applications that remember context. Chroma provides a lightweight store for embeddings and metadata with fast vector and full-text search, enabling offline or self-hosted workflows.
Instantiate a Chroma client, create a collection, add documents with embeddings, and perform a similarity query.
High-intent search queries and answers about installing and using this skill.
Store embeddings for semantic search by adding vector data and metadata to a collection, then querying it via a simple API. This enables fast document retrieval for RAG pipelines across local and production environments.
Filter document retrieval results by metadata directly when querying a vector database. You can add documents with associated metadata and apply filters during similarity search to narrow down returned records.
An open-source vector database for local LLM memory provides lightweight storage for embeddings and metadata. It allows offline semantic search and document retrieval, making it suitable for self-hosted workflows.
This vector database supports full-text search alongside vector similarity search. You can perform both semantic retrieval and text matching across large datasets within the same collection queries.
Scale semantic search from notebooks to production deployments using a 4-function API that handles add, get, update, and delete operations. It provides scalable storage designed to transition seamlessly between environments.
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CarlosAndresBF1Build RAG pipelines with vector stores and retrieval strategies for document Q&A.
cloudlinessHost a scalable managed vector database for similarity search.
