Python
4 results
LangChain vs LangGraph: Which One Should You Use?
LangChain handles linear pipelines. LangGraph handles everything that needs loops, branching, or persistent state. Here's the exact decision framework — with code showing when each breaks and why.
Structured Output from AI APIs: JSON Every Time
How to reliably get JSON, typed objects, and formatted data from ChatGPT, Claude, and Gemini APIs. Covers response_format, tool use, Pydantic, and every technique that actually works in production.
LangGraph: Build Stateful AI Agents That Actually Work
LangGraph extends LangChain with graph-based agent architecture — nodes, edges, state, and cycles. Learn how to build reliable multi-step AI agents with real Python code examples.
LangChain Explained: Build LLM Apps Without Boilerplate
LangChain is the most widely used framework for building applications on top of LLMs. This guide covers chains, prompt templates, output parsers, and LCEL — with real Python code snippets throughout.