LangChain

Reliable, fully local RAG agents with LLaMA3

RAG From Scratch: Part 1 (Overview)

Building Corrective RAG from scratch with open-source, local LLMs

LangGraph: Multi-Agent Workflows

LangGraph: Intro

Building a self-corrective coding assistant from scratch

LangSmith Studio: The first agent IDE

Fully local RAG agents with Llama 3.1

Reliable, fully local RAG agents with LLaMA3.2-3b

Build a Customer Support Bot | LangGraph

RAG From Scratch: Part 2 (Indexing)

LangGraph: Agent Executor

LangChain v0.1.0 Launch: Retrieval

Flow Engineering with LangChain/LangGraph and CodiumAI

Streaming Events: Introducing a new `stream_events` method

LangChain Documentation Update

Text to SQL Agent for Data Visualization

LangChain Low-Code/No-Code Webinar

LangChain Prompt Injection Webinar

Effectively Building with LLMs in the Browser with Jacob

LangChain "Characters" Webinar

RAG from scratch: Part 9 (Query Translation -- HyDE)

Using Natural Language to Query Postgres with Jacob

Intro to Generative UI with LangChain

Building a Generative UI App With LangChain Python

Build Agents that Never Forget: LangMem Semantic Memory Tutorial

Build Computing Olympiad Agents with LangGraph

Local Tool Calling with llamacpp

Building a web RAG chatbot: using LangChain, Exa (prev. Metaphor), LangSmith, and Hosted Langserve

Understanding and Effectively Using AI Reasoning Models

Introducing Agent Chat UI

LangChain "Hallucinations in Document Question-Answering" Webinar

Building and Testing Reliable Agents

What Is LangSmith? Explained in 5 Minutes

Memory for agents (conceptual video)

Building a Generative UI App With LangChain.js

Deep Agent CLI: Coding Assistant with Memory

Custom Evaluators | LangSmith Evaluations - Part 6

Generative UI Computer Use Agent with LangGraph.js

Conceptual Guide: Multi Agent Architectures

Web Search & File Uploads in Open Canvas

Building Effective Agents with LangGraph

Building an LLM Application with Audio by AssemblyAI

Getting Started with LangSmith (4/8): Playground & Prompts

RAG for long context LLMs

Prompt Engineering in LangSmith Studio

Deep Dive: How to Monitor AI Agents in Production

The Agent Development Lifecycle: Build, Test, Deploy, Monitor | Interrupt 26

Why Most AI Agents Fail — and How a Simple Todo List Fixes It

Tool Calling with LangChain

Build a Full Stack RAG App With TypeScript

Small OSS Models with LangGraph.js

Context Engineering for Agents

trustcall: Reliable and efficient structure data extraction using JSON patch operations

LangGraph interrupt: Making it easier to build human-in-the-loop agents