A developer's analysis of RAG retrieval architectures shows that vector-only search fails on exact-match queries like product codes and error numbers, and that hybrid search combining lexical and vect…
A new curated list of Model Context Protocol (MCP) servers enforces a strict open-source, self-hostable, no-lock-in policy, excluding any tool that requires a paid proprietary backend or vendor cloud …
Local Search Agent, a new Python framework for offline document search and retrieval-augmented generation (RAG), eliminates the need for embeddings, vector stores, and cloud uploads by using BM25 keyw…
A Rust developer at Meilisearch presents techniques for deferring error handling during development, such as using `unwrap` and `clone` to bypass compilation errors temporarily, and relying on CI with…
A developer introduced the Hybrid Retrieval pattern, which combines semantic vector search with keyword-based BM25 search using Reciprocal Rank Fusion (RRF) to improve retrieval precision. The pattern…
This article provides a tutorial on building a semantic search API in Go using the Fiber web framework and Meilisearch, a typo-tolerant search engine. The architecture includes filter support, configu…
To build a production-ready Retrieval-Augmented Generation (RAG) pipeline in Python using BM25 retrieval via Meilisearch instead of a vector database, arguing that BM25 achieves 85–95% of the recall o…