Store embeddings and perform semantic searches with metadata filtering.
npx skills add https://github.com/MesferAli/XCircle --skill chroma-mesferali
Please help me install this Agent Skill. Skill: chroma Source: https://github.com/MesferAli/XCircle/tree/main/.claude/skills/chroma Command: npx skills add https://github.com/MesferAli/XCircle --skill chroma-mesferali
This Skill provides a local, open-source solution for storing and searching vector embeddings, enabling AI applications to understand and retrieve information based on semantic meaning rather than just keywords.
Use the chroma skill to create a new collection named 'my_documents' and add the provided text documents with their associated metadata.
High-intent search queries and answers about installing and using this skill.
To store and search vector embeddings for semantic search, you need a vector database that manages AI-generated embeddings and performs similarity searches. This Skill provides an open-source solution to store embeddings with metadata and retrieve conceptually related information.
The best way to provide relevant context to LLMs for RAG applications is using an AI-native embedding database. It retrieves semantically relevant documents based on vector searches, supplying the fetched context directly to the LLM to augment its generation process.
Yes, you can filter vector database search results by metadata. This Skill supports storing associated metadata alongside embeddings, allowing you to perform full-text searches and apply metadata filters to refine the retrieved documents.
Yes, this semantic search database scales from local development to production clusters. It is designed to manage an open-source, AI-native embedding database that supports applications requiring semantic search and retrieval at various scales.
Yes, you need sentence-transformers to use this vector database. It is a required dependency used alongside chromadb to generate the vector embeddings from text documents that are then stored, managed, and searched within the database.
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