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> [!CAUTION] > Merging this PR will automatically publish to **PyPI** and create a **GitHub release**. For the full release process, see [`.github/RELEASING.md`](https://github.com/langchain-ai/deepagents/blob/main/.github/RELEASING.md). --- _Release notes preview: keep this section in sync with the package `CHANGELOG.md`. The published GitHub release body is extracted from the merged `CHANGELOG.md` by `release.yml`, not from this PR description._ --- ## [0.1.44](https://github.com/langchain-ai/deepagents/compare/deepagents-code==0.1.43...deepagents-code==0.1.44) (2026-07-20) ### Bug Fixes - Improved approval handling by hiding the `Auto` option when it isn't eligible and moving Auto mode path checks off the event loop. ([#4839](https://github.com/langchain-ai/deepagents/issues/4839), [#4856](https://github.com/langchain-ai/deepagents/issues/4856)) - Warmed MCP auth imports off the event loop to avoid blocking runtime work. ([#4855](https://github.com/langchain-ai/deepagents/issues/4855)) _End release notes preview._ --- > [!NOTE] > A **New Contributors** section is appended to the GitHub release notes automatically at publish time (see [Release Pipeline](https://github.com/langchain-ai/deepagents/blob/main/.github/RELEASING.md#release-pipeline), step 2). --------- Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com> Co-authored-by: langchain-oss-automated-triage[bot] <248757908+langchain-oss-automated-triage[bot]@users.noreply.github.com>
🧠🤖 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.