Forem

# 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 AI Agent Memory From Scratch — Tutorial For Dummies
Cover image for Build AI Agent Memory From Scratch — Tutorial For Dummies

Build AI Agent Memory From Scratch — Tutorial For Dummies

9
Comments 4
12 min read
How docs AI search works: Mintlify-Style with OpenAI Agents SDK
Cover image for How docs AI search works: Mintlify-Style with OpenAI Agents SDK

How docs AI search works: Mintlify-Style with OpenAI Agents SDK

11
Comments
3 min read
Thriving as a Personal Tech Consultant: Navigating the AI Revolution

Thriving as a Personal Tech Consultant: Navigating the AI Revolution

2
Comments
6 min read
Generic RAG Frameworks: Why They Can’t Catch On
Cover image for Generic RAG Frameworks: Why They Can’t Catch On

Generic RAG Frameworks: Why They Can’t Catch On

17
Comments
5 min read
DIY — Building a Cost-Effective Questionnaire Automation with Bedrock

DIY — Building a Cost-Effective Questionnaire Automation with Bedrock

2
Comments
3 min read
Exploring RAG: Hypothetical Document Embeddings (HyDE)
Cover image for Exploring RAG: Hypothetical Document Embeddings (HyDE)

Exploring RAG: Hypothetical Document Embeddings (HyDE)

1
Comments
2 min read
Buat AI chatbot dengan Deepseek R1: Studi Kasus chatbot untuk C Level
Cover image for Buat AI chatbot dengan Deepseek R1: Studi Kasus chatbot untuk C Level

Buat AI chatbot dengan Deepseek R1: Studi Kasus chatbot untuk C Level

5
Comments
2 min read
Enhancing Retrieval-Augmented Generation with SurrealDB
Cover image for Enhancing Retrieval-Augmented Generation with SurrealDB

Enhancing Retrieval-Augmented Generation with SurrealDB

13
Comments
22 min read
Using “Docling Parse”!

Using “Docling Parse”!

2
Comments
4 min read
Common Use Cases for CAMEL-AI

Common Use Cases for CAMEL-AI

1
Comments
2 min read
Improving RAG Systems with Amazon Bedrock Knowledge Base: Practical Techniques from Real Implementation

Improving RAG Systems with Amazon Bedrock Knowledge Base: Practical Techniques from Real Implementation

4
Comments 2
6 min read
Docling's new “SmolDocling-256M” Rocks

Docling's new “SmolDocling-256M” Rocks

3
Comments
9 min read
What if scaling context windows isn’t the answer to higher accuracy?
Cover image for What if scaling context windows isn’t the answer to higher accuracy?

What if scaling context windows isn’t the answer to higher accuracy?

5
Comments 1
1 min read
Fine-Tune Your LLM in MINUTES with Nebius ⚡️
Cover image for Fine-Tune Your LLM in MINUTES with Nebius ⚡️

Fine-Tune Your LLM in MINUTES with Nebius ⚡️

70
Comments 10
8 min read
The Evolution of Knowledge Work: A Comprehensive Guide to Agentic Retrieval-Augmented Generation (RAG)
Cover image for The Evolution of Knowledge Work: A Comprehensive Guide to Agentic Retrieval-Augmented Generation (RAG)

The Evolution of Knowledge Work: A Comprehensive Guide to Agentic Retrieval-Augmented Generation (RAG)

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