🧠🤖 Deep Agents Code

Deep Agents Code

Quick Install

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

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

agentcore all-providers all-sandboxes anthropic baseten bedrock cohere daytona deepseek fireworks google-genai groq huggingface ibm litellm media meta mistralai modal nvidia ollama openai openrouter perplexity quickjs runloop together vercel vertex xai

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