---
type: entity
subtype: tool
title: "LangChain"
description: "The framework used in prior masterclass videos to build the Asana agent; its message objects and invoke/stream methods underpin the chatbot logic."
resource: "https://www.langchain.com/"
tags: [agent-framework, python, javascript, rag, llm-abstraction]
videos: [google-just-dropped-a-masterclass-on-agentic-engineering-its-so-good, googles-agents-cli-the-cli-skills-combination-to-ship-ai-agents-easily, why-is-everyone-missing-this-with-ai-agents-memory-tools-that-scale, context-engineering-is-the-new-vibe-coding-learn-this-now, google-anthropic-and-openais-guides-to-ai-agents-all-in-18-minutes, openais-brand-new-agents-sdk-crash-course, introducing-archon-an-ai-agent-that-builds-ai-agents, you-have-to-try-agentic-rag-with-deepseek-r1-insane-results, i-created-the-best-ai-agent-platform-in-just-2-months, flowise-n8n-the-best-no-code-local-ai-agent-combo, qwen-just-casually-started-the-local-ai-revolution, this-boltnew-fork-is-exploding-dont-miss-out-on-whats-happening, im-building-the-best-open-source-ai-coding-assistant-with-your-help, openais-swarm-a-game-changer-for-ai-agents, get-qualified-leads-while-you-sleep-with-ai, this-slack-ai-personal-assistant-is-better-than-a-real-person, llama-32-is-insane-but-does-it-beat-gpt-as-an-ai-agent, the-hard-truth-about-hosting-your-own-llms, dont-sleep-on-the-ultimate-ai-agent-combo-n8n-langchain-python, openais-o1-is-barely-usable-but-i-fixed-it, run-all-your-ai-locally-in-minutes-llms-rag-and-more, complete-guide-to-langserve-make-your-ai-agent-actually-useful, i-found-the-limits-of-the-most-popular-llms, no-code-rag-agents-you-have-to-check-out-n8n-langchain, the-most-profitable-ai-niche-no-one-is-talking-about, youre-wasting-time-coding-your-ai-agents, the-best-tool-for-ai-agent-workflows-langgraph-full-guide, this-ai-agent-with-rag-manages-my-life, the-most-value-packed-rag-guide-on-youtube-feat-llama-31-405b, new-llama-3-model-beats-gpt-and-claude-with-function-calling, build-a-hilarious-ai-game-from-scratch-in-10-minutes, function-calling-with-any-llm-for-local-ai-agents-feat-langchain-huggingface-and-llama-3, ai-agents-just-got-sexy-ai-agents-masterclass-3, i-made-a-custom-ai-chatbot-site-in-47-lines-of-code, the-secret-sauce-for-simple-powerful-ai-apps-ai-agents-masterclass-2, the-only-ai-developer-roadmap-you-need-in-2024, introducing-trainers-ally-nvidia-ai-agents-competition-submission, i-will-win-the-nvidia-ai-agents-developer-contest]
created: 2026-07-21
updated: 2026-07-21
---

# LangChain

LangChain is a Python (and JavaScript) library that packages the plumbing every LLM application needs, and it was Cole's original workhorse before Pydantic AI: "LangChain is my favorite tool out of any tool I ever use for anything AI related seriously LangChain is amazing" [0:08:21]. He describes it plainly as "a suite of tools basically python libraries that help you build AI applications by taking care of a lot of the groundwork for you" [0:08:36], covering the recurring needs of "memory and Rag and building prompt templates all that good stuff" [0:01:02]. In the early AI Agents Masterclass series it is the framework behind the Asana agent chatbot, where LangChain message objects and the invoke/stream methods carry the conversation logic.

Its strongest, most durable use in Cole's content is [RAG](../../concepts/rag.md) and model abstraction. LangChain's document loaders and splitters do the ingestion legwork, and its uniform chat classes make swapping models trivial: "we'll instantiate the right chat class from LangChain based on if it's an OpenAI model an Anthropic model or a model from Groq" [0:03:14], which is [provider independence](../../concepts/provider-independence.md) in practice and a natural fit for [local AI](../../concepts/local-ai.md). Its [tool-calling](../../concepts/tool-use.md) binding also collapses boilerplate: "this is a LangChain function that makes it so simple this would be a lot of lines of code if it wasn't for LangChain" [0:18:30]. LangChain also underpins no-code tools he covers (Flowise is "built on top of LangChain") and the wider LangGraph and LangServe ecosystem.

Over time Cole moved his agent-building to Pydantic AI and now flags LangChain as a cautionary example of over-abstraction: "a lot of the other Frameworks out there like LangChain for example they are what's called an [abstraction distraction](../../concepts/abstraction-distraction.md) in my mind" [0:07:29]. The verdict is nuanced rather than dismissive: he still praises LangChain for RAG loaders, model abstraction, and as the foundation LangGraph builds on, while steering agent construction toward lower-abstraction frameworks.

## Realizes

- [Retrieval-Augmented Generation (RAG)](../../concepts/rag.md) - Grounding an LLM's answers by retrieving relevant documents from an external knowledge base and injecting them into the prompt at query time.
- [Tool Calling](../../concepts/tool-use.md) - Letting an LLM invoke external functions and APIs so it can take actions and fetch data beyond its parametric knowledge.
- [Model Selection](../../concepts/model-selection.md) - Choosing the right LLM per task by trading off quality, speed, and cost, often routing easy requests to cheap models and hard ones to expensive models.
- [Provider Independence](../../concepts/provider-independence.md) - Architecting agents so the underlying model, framework, or client can be swapped without a rewrite, avoiding lock-in through low-level abstractions.
- [Local & Self-Hosted AI](../../concepts/local-ai.md) - Running open-weight models on your own hardware or cloud for privacy, cost control, and independence from API providers.

## Works with

- [LangChain Deep Agents](./langchain-deep-agents.md) - LangChain's harness implementation for long-running (not just coding) agents that manages context by offloading to file-system tools.
- [LangGraph](./langgraph.md) - The orchestration framework wiring agents into a stateful graph of nodes and edges, used here to run agents in parallel and add human-in-the-loop.
- [LangServe](./langserve.md) - LangChain's library that wraps any chain or LangGraph runnable in a FastAPI web server via a single add_routes call, plus a RemoteRunnable client.
- [Flowise](./flowise.md) - Low-code LLM app / agent builder included and exposed in the stack.
- [n8n](./n8n.md) - A no-code AI automation platform for building agents and workflows that integrate with 500+ applications.

## Contrasts with

- [Pydantic AI](./pydantic-ai.md) - Cole's framework for the individual agents, structured around three parts: dependencies, the agent definition, and tools.
- [OpenAI Agents SDK](./openai-agents-sdk.md) - OpenAI's agent framework, which their guide leans on heavily with code examples.
- [CrewAI](./crewai.md) - Multi-agent framework named as one of the interchangeable backends AG-UI supports.

## Related

- [Tool Design](../../concepts/tool-design.md) - Designing agent tools to be few, single-purpose, and well-described (often via docstrings) so the model uses them reliably.
- [Abstraction Distraction](../../concepts/abstraction-distraction.md) - The trap of reaching for heavy frameworks and abstractions that get in the way instead of writing simple, direct code.

## Sources

- [The ONLY AI Developer Roadmap You Need in 2024](../../sources/the-only-ai-developer-roadmap-you-need-in-2024.md) - "[0:08:21] LangChain is my favorite tool out of any tool I ever use for anything AI related seriously LangChain is amazing"
- [The Secret Sauce for SIMPLE + POWERFUL AI Apps - AI Agents Masterclass #2](../../sources/the-secret-sauce-for-simple-powerful-ai-apps-ai-agents-masterclass-2.md) - "[0:00:16] LangChain is a really powerful python Library which basically just gives you a suite of tools that lays the groundwork for you to build really powerful AI applications"
- [AI Agents Just Got Sexy - AI Agents Masterclass #3](../../sources/ai-agents-just-got-sexy-ai-agents-masterclass-3.md) - "[0:00:30] we had from the last Master Class video where we incorporate LangChain to make our Asana AI agent chatbot much simpler and more powerful"
- [Introducing Archon - an AI Agent that BUILDS AI Agents](../../sources/introducing-archon-an-ai-agent-that-builds-ai-agents.md) - "[0:07:29] a lot of the other Frameworks out there like LangChain for example they are what's called an abstraction distraction in my mind"
- [THE BEST Tool for AI Agent Workflows - LangGraph FULL Guide](../../sources/the-best-tool-for-ai-agent-workflows-langgraph-full-guide.md) - "[0:01:14] LangChain is like the best library for working with large language models so it makes sense that LangGraph would be the best for working with agentic workflows"
- [Why is Everyone Missing This with AI Agents?! (Memory + Tools that Scale)](../../sources/why-is-everyone-missing-this-with-ai-agents-memory-tools-that-scale.md) - "[0:11:27] I don't cover LangChain a lot on my channel. I generally use Pydantic AI for my agent framework, but this is just what works really well with Arcade"
