DEV Community

#rag

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

Posts

đź‘‹ Sign in for the ability to sort posts by relevant, latest, or top.
Build a Knowledge-Based Q&A Bot using Bedrock + S3 + DynamoDB/OpenSearch via AWS CDK

Build a Knowledge-Based Q&A Bot using Bedrock + S3 + DynamoDB/OpenSearch via AWS CDK

1
Comments
25 min read
Beyond Simple RAG: Building an Agentic Workflow with Next.js, Python, and Supabase

Beyond Simple RAG: Building an Agentic Workflow with Next.js, Python, and Supabase

Comments 1
2 min read
VectorDatabase Showdown 2025: Pinecone vs Qdrant vs Weaviate con Benchmarks Reales

VectorDatabase Showdown 2025: Pinecone vs Qdrant vs Weaviate con Benchmarks Reales

Comments
3 min read
Building an AI Assistant That Actually Understands Company Policy

Building an AI Assistant That Actually Understands Company Policy

Comments
3 min read
Can tools automate ingestion and chunking steps reliably?

Can tools automate ingestion and chunking steps reliably?

2
Comments 2
3 min read
The Engineering guide to Context window efficiency

The Engineering guide to Context window efficiency

7
Comments
7 min read
How do I reduce hallucinations when pulling mixed data sources in an LLM-based chatbot?

How do I reduce hallucinations when pulling mixed data sources in an LLM-based chatbot?

Comments
1 min read
What parts of an AI workflow are actually automatable?

What parts of an AI workflow are actually automatable?

1
Comments 2
2 min read
Como Implementar um Sistema RAG do Zero em Python

Como Implementar um Sistema RAG do Zero em Python

8
Comments
4 min read
Advanced RAG: LongRAG, Self-RAG and GraphRAG Explained

Advanced RAG: LongRAG, Self-RAG and GraphRAG Explained

Comments
12 min read
Optimizing Milvus Standalone for Production: Achieving 70% Memory Reduction While Maintaining Performance

Optimizing Milvus Standalone for Production: Achieving 70% Memory Reduction While Maintaining Performance

Comments
3 min read
Research Survey on RAG Development Practices & Challenges (8-10 mins)

Research Survey on RAG Development Practices & Challenges (8-10 mins)

Comments
1 min read
Building a Page-Level PDF Processing Pipeline for Smarter RAG Systems

Building a Page-Level PDF Processing Pipeline for Smarter RAG Systems

8
Comments
7 min read
RAG Evaluation Metrics: Measuring What Actually Matters

RAG Evaluation Metrics: Measuring What Actually Matters

1
Comments
10 min read
Building NovaMem: The Local-First, Open-Source Vector Database for AI Agents

Building NovaMem: The Local-First, Open-Source Vector Database for AI Agents

Comments 2
3 min read
đź‘‹ Sign in for the ability to sort posts by relevant, latest, or top.