LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis.

Self-paced bootcamp on Generative AI. Tutorials on ML fundamentals, Ollama, LLMs, RAGs, LangChain, LangGraph, Fine-tuning, DSPy & AI Agents (CrewAI), (Using ChatGPT, gpt-oss, Claude, Qwen, Gemma, Llama, Gemini)

langchain 工具,流程设计组件,服务,代理以及相关学习文档的合集(agent,service,tutorials,flow-design)

LangChain Tutorial 3 动画演示透彻解释 Agent 概念 以及 实现Demo

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A tutorial for building autonomous agents: with LangChain and from scratch

Comprehensive tutorial and code examples for building multi-agent systems with LangChain

This YouTube tutorial goes over the architecture and concepts used for easily spinning up agents with using LangChain using OpenAI's API

A beginner-friendly, project-driven tutorial on generative AI and LangChain agents. You'll learn core concepts like prompt engineering, vector embedding, chain orchestration, and building retrieval-augmented chat agents—all via clear, hands-on examples.

The "lcel-tutorial" repo is designed for mastering LangChain Expression Language (LCEL), offering exercises to build stateful, multi-actor LLM applications. It's a hands-on guide to leveraging LCEL for complex workflows and agent-like behaviors. Perfect for enthusiasts eager to explore LLM's potential.

欢迎来到 “LLM Tutorial 一起学大模型” GitHub 仓库！在这里，你将找到本系列课程的所有代码、文档和资源，涵盖大模型开发的核心主题。我们将重点探索 LangChain 和 LangGraph 框架，同时包括大模型微调、理论基础和 Agents 开发等内容。 无论你是初学者还是有经验的开发者，这里都是一个学习与分享的理想空间。欢迎大家下载、交流，和我一起在大模型的旅程中成长！ 如有任何问题或建议，欢迎在仓库中提交 issue 或 pull request，期待与你的互动！

Tutorial in Question Answering with Langchain Agent

Storing all dummy data

This tutorial covers how to use LangChain for Agents and RAG. Local models from Ollama are employed.

📚 Panduan belajar RAG dengan LangChain dari nol dalam Bahasa Indonesia | LangChain tutorial in Indonesian - prompts, RAG, agents, LangGraph

Tutorial on how to create LLM Agent using LangChain and Gemini

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

This is a tutorial project. This project achieved an LLM Agent with several tools and without any other agent package like langchain

A hands-on learning journey into Generative AI with LangChain, inspired by the CampusX tutorial series. This repository contains Python scripts, Jupyter notebooks, notes, and experiments showcasing practical examples of working with LLMs, prompts, chains, memory, and agents.

A step-by-step guide to understanding and implementing Retrieval-Augmented Generation. This repository contains all the tutorial notebooks for the course, covering fundamental RAG techniques with LangChain and building advanced, agentic workflows with LangGraph.

Tutorials from https://learn.deeplearning.ai/; llm, agent, langchain related

LangChain is a framework for building LLM-powered applications. This repository provides hands-on Python examples and tutorials for LangChain, demonstrating everything from basic use of language models to advanced agent workflows. It includes examples of prompt templates, embeddings, chains, and agent usage.

A comprehensive, hands-on tutorial repository for learning and mastering LangChain - the powerful framework for building applications with Large Language Models (LLMs). This codebase provides a structured learning path with practical examples covering everything from basic chat models to advanced AI agents, organized in a progressive curriculum.

A tutorial on how to create a RAG agent with LangChain

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LangChain-LangGraph-tutorial Chatbot Agent

following python.langchain.com/docs/tutorials/agents

A collection of LangChain agents from a tutorial.

Going through Langchain's official tutorial for ambient agents (https://academy.langchain.com/courses/take/ambient-agents)