deepagents
The batteries-included agent harness.
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.
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.
Where it fits
- Build an automated coding assistant that can read, write, and edit files on your behalf using AI
- Create a multi-step task runner where an AI agent breaks down a goal and executes shell commands
- Set up a CLI AI coding tool powered by your own choice of language model
- Delegate complex research or file-processing tasks to sub-agents that run independently