What Is LangChain? Complete LangChain Tutorial (2025) — Build LLM Apps, RAG & Agents in Python
New to LangChain? In this step-by-step tutorial, you’ll learn what LangChain is and how to use it to build production-ready LLM applications—from simple chains to RAG (Retrieval-Augmented Generation) and AI agents with tools. We cover core concepts (prompts, chains, memory), vector databases and embeddings, streaming, callbacks, LangGraph for multi-step workflows, and basic deployment.
What you’ll learn
LangChain fundamentals: Prompts, Chains, Memory, Tools
RAG end-to-end: chunking, embeddings, vector stores (FAISS/Chroma), retrieval
Agents & tools: calling external APIs, safety & retries
Observability: Callbacks & tracing with LangSmith
Bonus: LangGraph for stateful agent workflows; deploy with FastAPI
Prereqs: Basic Python, an LLM API key (OpenAI/Anthropic or local model), and pip.
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