La manera mas sencilla de realizar una o muchas consultas a la vez en MySQL y trabajar el resultado sin muchas linea de codigo.

This repository implements Retrieval-Augmented Generation (RAG) for Query Translation and Semantic Search. It processes documents from a given URL, splits and indexes them, and uses different retrieval methods (multi-query, fusion, and decomposition) to accurately answer user queries.

Examples of using different retrievers in LangChain, including Wikipedia, Vector Store, MMR, MultiQuery, and Contextual Compression retrievers. Demonstrates how to fetch relevant context for semantic search, Q&A, summarization, and retrieval-augmented generation (RAG).

LangChain