You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Contextual Retrieval solves this problem by prepending chunk-specific explanatory context to each chunk before embedding (“Contextual Embeddings”) and creating the BM25 index (“Contextual BM25”).
ContextualRetriever enhances document retrieval accuracy by leveraging Voyage AI models for embedding & reranking models, and the GEMINI model for context and retrieval generation.
A powerful toolkit for text chunking and semantic search using OpenSearch. This toolkit provides various text chunking strategies and embedding capabilities for efficient document retrieval.