4.1 Why RAG?
The hallucination problem, knowledge cutoff, and grounding LLMs in facts.
7 docs tagged with "rag"
View All Tags4.2 Document Loading & Chunking
Chunk size, overlap, and splitting strategies for structured data in RAG pipelines.
4.3 Embeddings & Vector Stores
OpenAI/Cohere embeddings, ChromaDB, FAISS, and similarity search.
4.4 RAG Pipeline Architecture
Query → retrieve → augment → generate flow for building RAG systems.
4.5 Advanced RAG
Hybrid search, re-ranking, multi-query retrieval, and metadata filtering.
4.6 RAG for Structured & Tabular Data
SQL generation, pandas integration, and cricket scorecards as structured RAG input.
Building a RAG Pipeline with LangChain and ChromaDB
Learn to build a production-ready Retrieval-Augmented Generation pipeline using LangChain 0.2 and ChromaDB — from document ingestion to streamed answers.