langchain and langchain-langgraph-tutorial
LangChain is the foundational agent framework that B's tutorials teach users how to implement in practice, making them complementary tools where the tutorial depends on and extends the core platform.
About langchain
langchain-ai/langchain
The agent engineering platform
Provides unified abstractions for LLM models, embeddings, vector stores, and retrieval tools across 100+ provider integrations, enabling seamless model swapping and real-time data augmentation. Built on a modular, component-based architecture that supports chains and orchestration patterns, with optional integration to LangGraph for complex agentic workflows and LangSmith for observability and evals.
About langchain-langgraph-tutorial
doomL/langchain-langgraph-tutorial
Comprehensive tutorials for LangChain, LangGraph, and LangSmith using Groq LLM. Learn to build advanced AI systems, from basics to production-ready applications. Covers key concepts, real-world examples, and best practices. Ideal for beginners and experts alike. Elevate your AI development skills!
The tutorials progressively build from LangChain fundamentals through LangGraph's state-machine graph architecture, covering agent types (ReAct, zero-shot, plan-and-execute), memory systems, and RAG implementations. It demonstrates practical patterns like integrating Pydantic for structured outputs, combining LangChain components within LangGraph workflows, and implementing production concerns including rate limiting, cost optimization, and monitoring. Real-world applications span content moderation, customer support automation, and semantic search pipelines, all accelerated by Groq's high-performance inference.
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