Vector Stores in LangChain: Embeddings, Semantic Search & Similarity Retrieval

Learn how vector stores work in LangChain, from embeddings and similarity search to using Chroma for storing, querying, filtering, and managing high-dimensional vector data in RAG and recommendation systems.

January 23, 2026 · 6 min · 1082 words · Nirajan Khatiwada

Retrieval Augmented Generation (RAG) in LangChain: Architecture & Practical Example

Learn how Retrieval Augmented Generation (RAG) works in LangChain with clear architecture diagrams and a complete YouTube summarizer chatbot implementation using Chroma, Ollama, and runnable chains.

January 26, 2026 · 5 min · 910 words · Nirajan Khatiwada