explaingit

langchain-ai/deepagents

Analysis updated 2026-06-21

22,351PythonAudience · developerComplexity · 3/5LicenseSetup · moderate

TLDR

Deep Agents is a ready-to-use AI agent framework that gives you a fully wired AI assistant out of the box, with file access, shell commands, multi-step planning, and sub-agent delegation, in a single Python function call, built on LangGraph.

Mindmap

mindmap
  root((deepagents))
    What it does
      AI agent framework
      Multi-step task execution
      One function call setup
    Built-in Tools
      File system access
      Shell commands
      Todo planning
      Sub-agent delegation
    Tech stack
      Python
      LangGraph
      TypeScript version
    Audience
      Developers
      AI app builders
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filefunction / class

What do people build with it?

USE CASE 1

Build an automated coding assistant that can read, write, and edit files on your behalf using AI

USE CASE 2

Create a multi-step task runner where an AI agent breaks down a goal and executes shell commands

USE CASE 3

Set up a CLI AI coding tool powered by your own choice of language model

USE CASE 4

Delegate complex research or file-processing tasks to sub-agents that run independently

What is it built with?

PythonTypeScriptLangGraph

How does it compare?

langchain-ai/deepagentsprefecthq/prefectyoheinakajima/babyagi
Stars22,35122,31622,256
LanguagePythonPythonPython
Setup difficultymoderateeasyeasy
Complexity3/53/53/5
Audiencedeveloperdatadeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires an API key for a language model provider that supports tool use, such as OpenAI or Anthropic.

Free to use for any purpose including commercial projects, as long as you include the MIT license notice.

In plain English

Deep Agents is a ready-to-use AI agent framework built by the LangChain team. An AI agent is a program that uses a language model to plan and carry out multi-step tasks, not just answering a single question, but breaking down a goal, taking actions (like reading files, running commands, searching the web), and working toward a result. The project solves the problem of setup friction: instead of building all the plumbing yourself, connecting a language model to tools, managing conversation history, handling long context windows, Deep Agents gives you a fully wired agent out of the box with one function call. It comes pre-equipped with planning tools (to-do tracking), file system access (read, write, edit files), shell command execution, and the ability to delegate subtasks to separate sub-agents. You would use Deep Agents when building an automated assistant, a coding helper, or any system where you want an AI to complete complex multi-step tasks with access to tools and the file system. It also ships with a command-line interface that works similarly to AI coding tools, powered by your choice of language model. The framework is written in Python (with a TypeScript version available separately), built on LangGraph, works with any language model that supports tool use, and is licensed under MIT.

Copy-paste prompts

Prompt 1
Using langchain-ai/deepagents, create a Python agent that reads all .py files in a folder, summarizes what each one does, and writes the summaries to a README.md file.
Prompt 2
How do I configure Deep Agents to use Anthropic Claude as the language model for a file-editing agent?
Prompt 3
I want to build a coding assistant with Deep Agents that can run shell commands and edit files. Show me the minimal Python setup code.
Prompt 4
How does Deep Agents handle sub-agent delegation? Show me an example where a parent agent breaks a task into subtasks and assigns them to child agents.
Prompt 5
Walk me through running the Deep Agents CLI on my machine and using it to complete a multi-step programming task.

Frequently asked questions

What is deepagents?

Deep Agents is a ready-to-use AI agent framework that gives you a fully wired AI assistant out of the box, with file access, shell commands, multi-step planning, and sub-agent delegation, in a single Python function call, built on LangGraph.

What language is deepagents written in?

Mainly Python. The stack also includes Python, TypeScript, LangGraph.

What license does deepagents use?

Free to use for any purpose including commercial projects, as long as you include the MIT license notice.

How hard is deepagents to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is deepagents for?

Mainly developer.

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