Results for “vector128”

Reference for configuring and using LangChain4j vector stores, covering setup, search, filtering, and ingestion.

Enables semantic file search across a codebase using a vector-powered CLI, with integration for Claude and Codex agents.

Test vector stores for embedding inversion, cross-tenant leakage, and poisoning.

Build production RAG and semantic search systems with a high-performance vector database written in Rust, supporting hybrid search, filtering, and horizontal scaling.

Enables fast similarity search and clustering of dense vectors using FAISS, supporting billions of vectors, GPU acceleration, and various index types.

Generates and manages vector embeddings for semantic search and RAG retrieval across knowledge bases, with self-learning capabilities.