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Retrieval augmented generation, or RAG, is an architectural approach that can improve the efficacy of large language model (LLM) applications by leveraging custom data.

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A Cognitive Benchmark for Code-RAG Retrieval: Part 2 — Why Model Rankings Depend on the Pipeline
miftakhov profile

A Cognitive Benchmark for Code-RAG Retrieval: Part 2 — Why Model Rankings Depend on the Pipeline

#rag #ai #java #machinelearning
Comments
15 min read
The most underrated feature in a website AI assistant: saying "I don't know"
klymentiev profile

The most underrated feature in a website AI assistant: saying "I don't know"

#ai #webdev #llm #rag
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2 min read
Documents Aren't Bags of Chunks
valerykot profile

Documents Aren't Bags of Chunks

#ai #rag #programming #machinelearning
15
Comments 35
3 min read
Portfolio de IA open source: 20+ proyectos con LLMs self-hosted en producción
adrian_368e1d3e691afab697 profile

Portfolio de IA open source: 20+ proyectos con LLMs self-hosted en producción

#iaopensource #llmselfhosted #rag #fastapi
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3 min read
Book Library: A Local RAG That Answers From My Own PDFs
bsymbolic profile

Book Library: A Local RAG That Answers From My Own PDFs

#rag #python #localllm #gpu
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5 min read
Your AI Agent's Memory Has No Expiry Date: I Scored Freshness on a Real Corpus
0012303 profile

Your AI Agent's Memory Has No Expiry Date: I Scored Freshness on a Real Corpus

#ai #llm #rag #python
Comments
14 min read
Building a Four-Tier Parallel RAG Pipeline with Gemini
danishrazabangash profile

Building a Four-Tier Parallel RAG Pipeline with Gemini

#ai #rag #mongodb #node
2
Comments 4
2 min read
RAG - Semantic Caching
ramya_perumal profile

RAG - Semantic Caching

#ai #rag #beginners #nlp
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3 min read
Optimizing RAG Pipelines, Migrating AI Agents, and LLM-Powered Troubleshooting
soytuber profile
soy

Optimizing RAG Pipelines, Migrating AI Agents, and LLM-Powered Troubleshooting

#ai #rag #automation
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3 min read
Building a RAG System from Scratch — AI Agents: Memory, Planning, and Multi-Step Reasoning
hiroki-kameyama profile

Building a RAG System from Scratch — AI Agents: Memory, Planning, and Multi-Step Reasoning

#rag #ai #python #llm
Comments 1
7 min read
Your RAG System Is Lying To You About That Table
saksheessawant profile

Your RAG System Is Lying To You About That Table

#discuss #ai #rag #llm
13
Comments 2
4 min read
A Chinese 8B model beat the Western 8B models at Japanese RAG. I still wouldn't put it in the default deployment — and that distinction is the point.
elvisyao007 profile

A Chinese 8B model beat the Western 8B models at Japanese RAG. I still wouldn't put it in the default deployment — and that distinction is the point.

#llm #rag #machinelearning #japan
Comments
4 min read
Part 5 — Installing a Black Box Recorder in Your RAG System: 4-Layer Metadata + 3-Level Verification, Root Cause in 5 Minutes
jamesli profile

Part 5 — Installing a Black Box Recorder in Your RAG System: 4-Layer Metadata + 3-Level Verification, Root Cause in 5 Minutes

#ai #architecture #monitoring #rag
6
Comments
9 min read
Part 2 — Why Does One System Need Three Chunking Strategies? And One Document Type Shouldn't Be Chunked At All
jamesli profile

Part 2 — Why Does One System Need Three Chunking Strategies? And One Document Type Shouldn't Be Chunked At All

#ai #architecture #llm #rag
6
Comments
9 min read
Part 3 — Vector Retrieval in Domain-Specific Terminology Scenarios: From Model Selection to Dual Validation
jamesli profile

Part 3 — Vector Retrieval in Domain-Specific Terminology Scenarios: From Model Selection to Dual Validation

#ai #architecture #nlp #rag
6
Comments
10 min read
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