Retrievers are the backbone of every RAG system. This guide covers what they are, how they work, and which types to use, with practical LangChain examples for building smarter AI search and chatbot applications.
Sameer Singh
Discover how vector stores power modern AI search and RAG systems. Learn about embeddings, semantic similarity, indexing techniques, and how to use Chroma with LangChain to build intelligent applications.
Sameer Singh
Text splitting is the backbone of every RAG system. Learn how chunking works, why chunk size and overlap matter, and which LangChain splitter to use for production-grade AI applications.
Sameer Singh
Learn how RAG works in LangChain with hands-on examples. Covers Document Loaders like TextLoader, PyPDFLoader, WebBaseLoader, CSVLoader, and DirectoryLoader to build powerful AI apps that answer from your own data.
Sameer Singh
Master LangChain Runnables from scratch. Learn what they are, why they replaced chains, and how LCEL helps you build flexible AI pipelines with clean, modular code.
Sameer Singh
Learn how LangChain Chains work with real examples. Build sequential, parallel, and conditional pipelines to create powerful, production-ready LLM apps from scratch.
Sameer Singh
Stop struggling with unstructured LLM outputs. This guide breaks down LangChain Output Parsers into simple concepts with code examples, helping you build reliable, production-grade AI applications.
Sameer Singh
Learn how structured output in LangChain turns raw LLM responses into machine-readable data, enabling AI apps to talk to databases, APIs, and tools. Master TypedDict, Pydantic, and JSON Schema.
Sameer Singh
Learn LangChain Prompts from scratch — covering static vs dynamic prompts, PromptTemplate, ChatPromptTemplate, message types, and MessagePlaceholder with practical examples to build smarter AI apps.
Sameer Singh
LangChain's Model component is the core of every AI app. Learn how LLMs, Chat Models, and Embeddings actually work - from token generation to semantic search - with practical code and real-world examples.
Sameer Singh
Learn the 6 core building blocks of LangChain - Models, Prompts, Chains, Indexes, Memory, and Agents. Understand what each component does, why it exists, and how they work together to power real AI apps.
Sameer Singh
Master LangChain from the ground up. Learn how RAG systems work, how LLM memory is managed, and how agents take action - complete with working Python code. Your full roadmap to building real-world AI apps.
Sameer Singh