RAG Resources

A curated collection of tools, frameworks, tutorials, and papers for RAG systems.

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🛠️ Frameworks

RAG Orchestration

Framework	Description	Link
LangChain	Most popular LLM application framework	langchain.com
LlamaIndex	Data indexing and querying framework	llamaindex.ai
Haystack	End-to-end NLP framework	haystack.deepset.ai
Semantic Kernel	Microsoft's AI orchestration SDK	learn.microsoft.com

Evaluation

Tool	Description	Link
RAGAS	RAG Assessment framework	ragas.io
TruLens	LLM app evaluation	trulens.org
Phoenix	ML observability	arize.com/phoenix

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🗄️ Vector Databases

Managed

Database	Type	Free Tier
Pinecone	Cloud	✅ Limited
Weaviate Cloud	Cloud	✅ Sandbox
Zilliz Cloud	Milvus hosted	✅ Limited

Self-Hosted

Database	Language	Best For
Chroma	Python	Development
Qdrant	Rust	Production
Milvus	Go/C++	Large scale
pgvector	PostgreSQL	Existing PG
FAISS	C++/Python	In-memory

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🤖 Embedding Models

Commercial APIs

Provider	Model	Dimensions
OpenAI	text-embedding-3-small	1536
OpenAI	text-embedding-3-large	3072
Cohere	embed-v3	1024
Voyage AI	voyage-2	1024

Open Source

Model	Source	Dimensions
BGE-large	BAAI	1024
E5-large	Microsoft	1024
all-MiniLM-L6	Sentence-Transformers	384
GTE-large	Alibaba	1024

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📚 Learning Resources

Official Documentation

• LangChain Docs
• LlamaIndex Docs
• OpenAI Cookbook
• Pinecone Learning Center

Tutorials

• Building RAG with LangChain
• LlamaIndex Starter Tutorial
• RAG from Scratch (Pinecone)

Courses

Course	Provider	Level
LangChain for LLM Development	DeepLearning.AI	Beginner
Building with LLMs	Weights & Biases	Intermediate
Full Stack LLM Bootcamp	FSDL	Advanced

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📄 Key Papers

Foundational

Paper	Year	Topic
RAG for Knowledge-Intensive NLP	2020	Original RAG paper
Dense Passage Retrieval	2020	DPR for QA
REALM	2020	Retrieval-enhanced LM

Advanced Techniques

Paper	Year	Topic
Self-RAG	2023	Self-reflective RAG
HyDE	2022	Hypothetical documents
Lost in the Middle	2023	Context length analysis

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🔧 Tools

Development

Tool	Purpose
Jupyter/Colab	Prototyping
Streamlit	Quick UIs
Gradio	Demo interfaces

Observability

Tool	Purpose
LangSmith	LangChain tracing
Weights & Biases	Experiment tracking
Arize	ML observability

Deployment

Platform	Type
Modal	Serverless Python
Railway	Easy deployment
Render	Web services
AWS/GCP/Azure	Enterprise

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💬 Communities

Platform	Link
LangChain Discord	discord.gg/langchain
LlamaIndex Discord	discord.gg/llamaindex
r/LocalLLaMA	reddit.com/r/LocalLLaMA
AI Twitter/X	Follow #RAG hashtag

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📊 Benchmarks

Benchmark	Purpose	Link
MTEB	Embedding models	huggingface.co/spaces/mteb
BEIR	Retrieval benchmark	github.com/beir-cellar
MS MARCO	Passage ranking	microsoft.github.io/msmarco

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Recommended Reading Order

1. Start: LangChain RAG tutorial
2. Understand: Original RAG paper
3. Deep dive: Dense Passage Retrieval
4. Advanced: HyDE and Self-RAG papers
5. Practice: Build projects from Module 10

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