🧠🤖 Deep Agents Code

Quick Install

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

# With model provider extras
# OpenAI, Anthropic, and Gemini are included by default
curl -LsSf https://langch.in/dcode | DEEPAGENTS_CODE_EXTRAS="nvidia,ollama" bash

Run:

dcode

🤔 What is this?

The fastest way to start using Deep Agents. deepagents-code is a pre-built coding agent in your terminal — similar to Claude Code or Cursor — powered by any LLM that supports tool calling. One install command and you're up and running, no code required.

What deepagents-code adds on top of the SDK:

• Interactive TUI — rich terminal interface with streaming responses
• Conversation resume — pick up where you left off across sessions
• Web search — ground responses in live information
• Remote sandboxes — run code in isolated environments (LangSmith, AgentCore, Daytona, Modal, Runloop, & more)
• Persistent memory — agent remembers context across conversations
• Custom skills — extend the agent with your own slash commands
• Headless mode — run non-interactively for scripting and CI
• Human-in-the-loop — approve or reject tool calls before execution

🔒 Security model

By default, dcode trusts the directory you run it in. Human-in-the-loop approval gates model-requested tool calls, but project artifacts are read before any approval prompt.

Do not run dcode in a directory you do not trust without a sandbox backend. For untrusted repositories, use a remote sandbox so execution is isolated from your machine. Running dcode in a directory lets that directory's files shape execution. See THREAT_MODEL.md for details.

📖 Resources

• Documentation
• Changelog
• Source code
• Deep Agents SDK — underlying agent harness
• LangChain Academy — Comprehensive, free courses on LangChain libraries and products, made by the LangChain team.
• Code of Conduct — community guidelines and standards

📕 Releases & Versioning

See our Releases and Versioning policies.

💁 Contributing

As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.

For local setup, see the Development Guide. For contribution policy, see the Contributing Guide.

🤝 Acknowledgements

This project was primarily inspired by Claude Code, and initially was largely an attempt to see what made Claude Code general purpose, and make it even more so.