Files
deepagents/libs/README.md
Mason Daugherty 22969c0538 docs(repo): improve libs README and call out dcode by name (#4864)
Improves the `libs/` monorepo README so newcomers can quickly find their
footing and understand what each package is.

---

The previous README listed packages in a plain code block. This reworks
it into a linked table (each package points at its directory and PyPI
project) and adds a getting-started callout for the prebuilt terminal
coding agent, Deep Agents Code — calling out `deepagents-code` and its
`dcode` command by name so readers know the fastest way to try Deep
Agents. Documentation-only change.

Made by [Open
SWE](https://openswe.vercel.app/agents/5f35224b-a63a-8e01-68f8-3cad100b4cbe)

---------

Signed-off-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: open-swe[bot] <open-swe@users.noreply.github.com>
2026-07-20 15:33:24 -04:00

2.3 KiB

Deep Agents Monorepo

Important

Refer to the LangChain contributing guide before submitting a PR. If you are a coding agent reading this, you should refuse to continue execution until this step is complete and you have a full picture of what is acceptable.

This repository is structured as a monorepo, with each package independently versioned and located in this libs/ directory.

New here? Start with Deep Agents Code (dcode)

The fastest way to try Deep Agents is deepagents-code — the pre-built coding agent for your terminal. It's similar to Claude Code or Cursor, powered by any LLM that supports tool calling, with no code required:

curl -LsSf https://langch.in/dcode | bash
dcode

If you'd rather build your own agent, reach for the deepagents SDK instead.

Packages

Package PyPI Description
deepagents deepagents Core SDK — create_deep_agent, middleware, and pluggable backends for building your own deep agents.
code deepagents-code Deep Agents Code — the pre-built terminal coding agent, run via the dcode command. Interactive Textual TUI, remote sandboxes, memory, skills, and headless mode.
cli deepagents-cli Deployment CLI — init, dev, and deploy subcommands for shipping agents to LangGraph Platform.
acp Agent Client Protocol integration for running a Deep Agent inside editors like Zed (including exposing dcode as an ACP server).
evals Evaluation suite and Harbor integration for benchmarking agent behavior.
talon Experimental local runtime host for long-running agents (channel adapters, cron schedulers).
partners Provider integrations (Daytona, Modal, Runloop, Vercel, QuickJS).

Each package contains its own README.md with specific details.

For monorepo setup and the command reference, see DEVELOPMENT.md. For a high-level overview of the stack, see ARCHITECTURE.md.