rag-frameworks

v2026.09.24

Use when "RAG", "retrieval augmented generation", "LangChain", "LlamaIndex", "sentence transformers", "embeddings", "document QA", "chatbot with documents", "semantic search"

GitHub
Install command
npx skhub add eyadsibai/rag-frameworks
Markdown
SKILL.md

RAG Frameworks

Frameworks for building retrieval-augmented generation applications.

Comparison

FrameworkBest ForLearning CurveFlexibility
LangChainAgents, chains, toolsSteeperHighest
LlamaIndexData indexing, simple RAGGentleMedium
Sentence TransformersCustom embeddingsLowHigh

LangChain

Orchestration framework for building complex LLM applications.

Core concepts:

  • Chains: Sequential operations (retrieve → prompt → generate)
  • Agents: LLM decides which tools to use
  • LCEL: Declarative pipeline syntax with | operator
  • Retrievers: Abstract interface to vector stores

Strengths: Rich ecosystem, many integrations, agent capabilities Limitations: Abstractions can be confusing, rapid API changes

Key concept: LCEL (LangChain Expression Language) for composable pipelines.


LlamaIndex

Data framework focused on connecting LLMs to external data.

Core concepts:

  • Documents → Nodes: Automatic chunking and indexing
  • Index types: Vector, keyword, tree, knowledge graph
  • Query engines: Retrieve and synthesize answers
  • Chat engines: Stateful conversation over data

Strengths: Simple API, great for document QA, data connectors Limitations: Less flexible for complex agent workflows

Key concept: "Load data, index it, query it" - simpler mental model than LangChain.


Sentence Transformers

Generate high-quality embeddings for semantic similarity.

Popular models:

ModelDimensionsQualitySpeed
all-MiniLM-L6-v2384GoodFast
all-mpnet-base-v2768BetterMedium
e5-large-v21024BestSlow

Key concept: Bi-encoder architecture - encode query and documents separately, compare with cosine similarity.


RAG Architecture Patterns

PatternDescriptionWhen to Use
Naive RAGRetrieve top-k, stuff in promptSimple QA
Parent-ChildRetrieve chunks, return parent docsContext preservation
Hybrid SearchVector + keyword searchBetter recall
Re-rankingRetrieve many, re-rank with cross-encoderHigher precision
Query ExpansionGenerate variations of queryAmbiguous queries

Decision Guide

ScenarioRecommendation
Simple document QALlamaIndex
Complex agents/toolsLangChain
Custom embedding pipelineSentence Transformers
Production RAGLangChain or custom
Quick prototypeLlamaIndex
Maximum controlBuild custom with Sentence Transformers

Resources

Discovery
Tags

No tags published for this skill.

Version
Latest version metadata

Version

v2026.09.24

Published

Sep 24, 2026

Category

Uncategorized

License

Not specified

Source path

plugins/ltk-data/skills/rag-frameworks

Default branch

master

Latest commit

f8e8569

Tree SHA

8bcd589