Chroma
Skill Verifiziert AktivOpen-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.
To serve as a powerful, self-hosted, and open-source embedding database for AI applications, enabling efficient semantic search and retrieval.
Funktionen
- Store embeddings and metadata
- Perform vector and full-text search
- Filter search results by metadata
- Support for multiple embedding functions (OpenAI, HuggingFace, custom)
- Integration with LangChain and LlamaIndex
Anwendungsfälle
- Building RAG (retrieval-augmented generation) applications
- Implementing semantic search over documents
- Prototyping AI applications locally
- Storing and querying vector embeddings with associated metadata
Nicht-Ziele
- Acting as a managed cloud vector database (alternatives like Pinecone are mentioned)
- Performing similarity search without metadata filtering (like FAISS)
- Replacing production ML-native databases (like Weaviate or Qdrant, though Chroma scales to production)
Installation
Zuerst Marketplace hinzufügen
/plugin marketplace add Orchestra-Research/AI-Research-SKILLs/plugin install AI-Research-SKILLs@ai-research-skillsQualitätspunktzahl
VerifiziertVertrauenssignale
Ähnliche Erweiterungen
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Sentence Transformers
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Hybrid Search Implementation
98Combine vector and keyword search for improved retrieval. Use when implementing RAG systems, building search engines, or when neither approach alone provides sufficient recall.