langchain-runnables

Step-by-step LangChain tutorials covering models, prompts, chains, retrievers, tools, and agents — theory to full implementation.

The applications of frameworks like Langchain and APIs for creating AI agents and RAGs

Langchain Tutorial

demonstrates LangChain Runnables for building modular AI workflows. It covers sequential execution, parallel processing, conditional branching, lambda-based transformations, and direct passthroughs using Google Gemini and OpenAI models. Each file showcases a different runnable: generating reports, summarization, joke creation and content writing

Examples of LangChain Runnables including Sequence, Parallel, Passthrough, Lambda, and Branch. Demonstrates how to build modular, scalable pipelines for tasks like text processing, summarization, and conditional workflows using reusable components.