SemanticScuttle - klotz.me

klotz: semantic search* + rag*

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1. Discovering Semantic Search and RAG with Large Language Models (LLMs)

   Foundational concepts, practical implementation of semantic search, and the workflow of RAG, highlighting its advantages and versatile applications.
   
   The article provides a step-by-step guide to implementing a basic semantic search using TF-IDF and cosine similarity. This includes preprocessing steps, converting text to embeddings, and searching for relevant documents based on query similarity.

   2024-10-04 Tags: llm, semantic search, rag, nlp, embeddings, asymmetric by klotz
2. How to Use Hybrid Search for Better LLM RAG Retrieval

   Combining dense embeddings with BM25 for advanced local LLM RAG pipeline

   2024-08-12 Tags: rag, lm, bm25, hybrid search, semantic search, keyword search by klotz
3. Advanced RAG Techniques

   This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.

   2024-08-01 Tags: rag, nlp, machine learning, information retrieval, natural language processing, llm, embeddings, semantic search by klotz
4. Getting Started with RAG

   This article explains Retrieval Augmented Generation (RAG), a method to reduce the risk of hallucinations in Large Language Models (LLMs) by limiting the context in which they generate answers. RAG is demonstrated using txtai, an open-source embeddings database for semantic search, LLM orchestration, and language model workflows.

   2024-06-23 Tags: rag, llm, hallucinations, txtai, embeddings database, semantic search, orchestration, text, github by klotz

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