SemanticScuttle - klotz.me

Tags: sentence transformers* + vector database*

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1. How to Combine LLM Embeddings, TF-IDF, and Metadata in One Scikit-Learn Pipeline

   This tutorial demonstrates how to combine LLM embeddings, TF-IDF vectors, and metadata features into a single Scikit-learn pipeline for document retrieval and search. It covers generating embeddings with Sentence Transformers, calculating TF-IDF, handling metadata, and building a combined retrieval system.

   2026-02-28 Tags: llm, embeddings, tf-idf, scikit-learn, pipeline, document retrieval, search, sentence transformers, metadata, vector database by klotz
2. Let’s Build a RAG-Powered Research Paper Assistant

   This article details building a Retrieval-Augmented Generation (RAG) system to assist with research paper tasks, specifically question answering over a PDF document. It covers document loading, splitting, embedding with Sentence Transformers, using ChromaDB as a vector database, and implementing a query interface with LangChain.

   2025-04-23 Tags: docker, rag, langchain, sentence transformers, chromadb, vector database, pdf, llm by klotz

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