Skip to main content

🧠🤖 Deep Agents Code

PyPI - Version PyPI - License PyPI - Downloads Twitter

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

📕 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.

Metadata

Release files for zjcode 0.0.16

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for zjcode 0.0.16
File Size Uploaded Provenance Actions
zjcode-0.0.16.tar.gz 3.2 MB With provenance Details for zjcode-0.0.16.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for zjcode 0.0.16
File Interpreter ABI Platform Actions
zjcode-0.0.16-py3-none-any.whl Python 3 none any Details for zjcode-0.0.16-py3-none-any.whl

Total release size: 4.4 MB

Release files / zjcode-0.0.16.tar.gz

Download URL zjcode-0.0.16.tar.gz
Size 3.2 MB
Tags Source
SHA-256 checksum
How to use checksums
b3f035657406bcbb72d110490ce55700fb98ec3833b90139bd2e46b65aa90e3a
BLAKE2b-256 checksum
How to use checksums
f4a2b9ccaf694a36a51a1c071dcc342365007bfe86f59a7dd3649f52754bc0fb
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Aug 2, 2026.

Transparency log

Release files / zjcode-0.0.16-py3-none-any.whl

Download URL zjcode-0.0.16-py3-none-any.whl
Size 1.2 MB
Tags Python 3
SHA-256 checksum
How to use checksums
95322f31e6fffe07836a4cbfbd01005c9e1ed43594bfe725225b285a39b946a2
BLAKE2b-256 checksum
How to use checksums
7670a36932cb74c2529bea0ff8ecc90991b1fd337651474fa19f9cfb61c659db
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/7.0.0 CPython/3.13.14

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Aug 2, 2026.

Transparency log

Security for zjcode 0.0.16

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Full provenance

All 2 files in this release have been uploaded with provenance metadata.

Select from 2 files

Attestation for zjcode-0.0.16.tar.gz

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Aug 2, 2026.

Transparency log

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page