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Build a RAG Pipeline

Difficulty: intermediate

Build a retrieval-augmented generation system from document ingestion to answer quality

Step 1: Prepare your documents

Recommended: Unstructured, Firecrawl

Extract clean text from PDFs, web pages, and other document formats

Step 2: Choose a vector database

Recommended: ChromaDB, Weaviate, Qdrant, Pinecone

ChromaDB for prototyping, Weaviate/Qdrant for production, Pinecone for managed

Step 3: Build the RAG pipeline

Recommended: LlamaIndex, LangChain, Haystack

LlamaIndex is RAG-focused, LangChain is general-purpose, Haystack is production-ready

Step 4: Evaluate and iterate

Recommended: Ragas, LangFuse

Use Ragas metrics to measure quality, Langfuse to trace and debug

Curated with care for the AI developer community