Store embeddings and metadata for vector and full-text search.
npx skills add https://github.com/gqf2008/hermez-ai --skill chroma-gqf2008
Please help me install this Agent Skill. Skill: chroma Source: https://github.com/gqf2008/hermez-ai/tree/main/skills/mlops/chroma Command: npx skills add https://github.com/gqf2008/hermez-ai --skill chroma-gqf2008
Open-source, self-hosted embedding database for AI applications to store embeddings and metadata, enabling efficient vector and full-text search with metadata-based filtering.
Install chromadb and create a collection to run a basic similarity search.
High-intent search queries and answers about installing and using this skill.
You can store embeddings and metadata for local RAG workflows using a self-hosted vector database that manages document retrieval and metadata filtering efficiently.
The best way to run semantic search on your own documents is using a self-hosted embedding database that supports vector search and metadata filtering across local setups.
Yes, you can use this lightweight, scalable vector database for document retrieval in production clusters, as it transitions smoothly from notebooks to production environments.
A self-hosted embedding database can support both fast vector and full-text search, allowing you to retrieve relevant documents using multiple search methods.
Metadata filtering in vector search works by storing associated metadata alongside embeddings, allowing you to apply specific filters to narrow down your document retrieval results.
No, you do not need a complex API to manage a local vector store, as this solution exposes a simple four-function API to handle embeddings and search operations.
lewisperez999Generate text embeddings with OpenAI and search by cosine similarity in Upstash Vector or pg-vector.
jhl-labsRetrieve relevant documents and augment LLM prompts with vector search.
brittaniebuffiecsuStore and retrieve embeddings and metadata for semantic search.
Clay-HHKStore embeddings and metadata in Chroma for vector search and RAG applications.
