#embeddings
11 pages tagged embeddings.
weaviate-client
Package-level reference for weaviate-client on PyPI — install variants, the v3 → v4 API split, gRPC, and alternative vector stores.
sentence-transformers
Package-level reference for the sentence-transformers library on PyPI — install, transformers/torch deps, model registry, and embedding alternatives.
qdrant-client
Package-level reference for qdrant-client on PyPI — install variants, server version matching, gRPC vs HTTP, fastembed extras, and alternatives.
chromadb
Package-level reference for chromadb on PyPI — install variants, server/client split, embedding-function extras, and alternative vector stores.
Retrieval-Augmented Generation (RAG)
Grounding LLM responses in chunks retrieved from an external corpus so the model reasons over real, citable sources instead of parametric memory alone.
RAG Implementation Checklist
End-to-end checklist and code for building reliable Retrieval-Augmented Generation pipelines — chunking, embedding, vector DBs, retrieval, and evaluation.
Sentence Transformers
Comprehensive reference for the sentence-transformers Python library — embeddings, similarity, clustering, retrieval, fine-tuning, and popular models (BGE, E5, GTE, Nomic, Jina).
weaviate-client
Store, search, and manage vector embeddings with the Weaviate Python client. Covers collections, CRUD, vector/hybrid/BM25 search, multi-tenancy, generative search, and batch import.
qdrant-client
Store and search vector embeddings with the Qdrant Python client. Covers collections, CRUD, filtered vector search, payload indexing, batch upsert, sparse/dense hybrid search, and integrations.
LlamaIndex
Build RAG pipelines and LLM-powered data applications with LlamaIndex. Covers document loading, indexing, query engines, custom LLMs and embeddings, persistent storage, and agents.
ChromaDB
Store and query vector embeddings locally or over a network with ChromaDB. Covers client types, collections, add, query, metadata filters, embedding functions, and LangChain/LlamaIndex integration.