RAG

Retrieval Augmented Generation, Vector Search, Embeddings, Context

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Scoured 118 posts in 11.4 ms

Quiz: Embeddings and Vector Databases With ChromaDB

 🔎Information Retrieval
realpython.com·

How to Build an Agentic RAG with RubyLLM and Rails

 💬Prompt Engineering  Content type: Blog
panasiti.me··Hacker News

I Built a Private AI That Answers Questions From My Own PDFs — Entirely on My Laptop

 🔎Information Retrieval
pub.towardsai.net
·

TA-RAG: Tone-Aware Retrieval-Augmented Generation for Peer-Support Health Communication

 🔍Search Algorithms  Content type: Academic
arxiv.org·

A Fun & Absurd Introduction to Vector Databases • Alexander Chatzizacharias

 🔢Algebraic Datatypes  Content type: Video
youtu.be··r/programming

How to Set Up Codebase Indexing in Kilo Code

 💻Terminal UIs  Content type: News  Content type: Blog
blog.kilo.ai·

What is Agentic RAG? Building Multi-Agent Agentic RAG Systems

 📓Jupyter Notebooks
pub.towardsai.net
·

Agentic Hybrid RAG for Evidence-Grounded Muon Collider Analysis

 🔎Information Retrieval  Content type: Academic
arxiv.org·

Show HN: Incremental RAG ingestion, only changed chunks get re-embedded

 🏠Self-Hosting  Content type: Code
github.com··Hacker News

Measuring Embedding Drift: Why Hybrid Search Saves Stale Models.

 💬Prompt Engineering
pub.towardsai.net
·

MolE-RAG: Molecular Structure-Enhanced Retrieval-Augmented Generation for Chemistry

 🔍Search Algorithms  Content type: Academic
arxiv.org·

ashp15205/guardian-runtime: A zero-latency, local-first runtime firewall for LLMs. Intercept every prompt and response locally to stop data leaks and runaway token costs.

 💬Prompt Engineering  Content type: Code
github.com··Hacker News

Phoenix

 💬Interactive REPLs
arize.com·

LangChain Series #2: Models Explained — LLMs, Chat Models, and Embeddings with Practical…

 🌉Language Bridges
pub.towardsai.net
·

Reducing Hallucinations in Complex Question Answering using Simple Graph-based Retrieval-Augmented Generation (long version)

 📝Computational Linguistics  Content type: Academic
arxiv.org·

Fine-Tuning vs. RAG vs. Prompting: the Definitive Decision Framework for 2026

 💬Prompt Engineering
pub.towardsai.net
·

SIFT: Selective-Index For Fast Compute of RAG Prefill by Exploiting Attention Invariance

 🗺️Region Inference  Content type: Academic
arxiv.org·

LangChain Explained: Understanding Models, Prompts, Chains, Memory, Indexes, and Agents

 💬REPL Design
pub.towardsai.net
·

Revisiting Vul-RAG: Reproducibility and Replicability of RAG-based Vulnerability Detection with Open-Weight Models

 🚂Cranelift IR  Content type: Academic
arxiv.org·

How RAG Actually Finds Answers (Part 2): HNSW, IVF, BM25, Hybrid Search and Re-Ranking | M011 |…

 🔎Information Retrieval
pub.towardsai.net
·

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