dora/README.md

• • Latest News 🎉
  • Highlights
  • Node Hub
  • • Camera
    • Peripheral
    • Actuator
    • Chassis
    • Arm
    • Robot
    • Voice Activity Detection
    • Speech to Text
    • Vision Language Model
    • Large Language Model
    • Vision Language Action
    • Object Detection
    • Segmentation
    • Translation
    • Text to Speech
    • Recorder
    • Visualization
    • Simulator
  • Quick Start
  • • Installation
    • With cargo
    • With Github release for macOS and Linux
    • With Github release for Windows
    • With Source
  • Documentation
  • Getting Started
  • What is Dora? And what features does Dora offer?
  • • TCP Communication and Shared Memory
    • Arrow Message Format
    • Opentelemetry
    • ROS2 Bridge
  • Showcases
  • • Self-Coding Robot: Code RAG (WIP)
  • Support Matrix
  • Contributing
  • Discussions
  • License

Website | Python API | Rust API | Guide | Discord

An extremely fast and simple dataflow oriented robotic framework to manage your projects and run complex apps, written in Rust.

Latency benchmark with Python API for both framework, sending 40M of random bytes.

Latest News 🎉

2025

• [2025/03/05] dora-rs has been accepted to GSoC 2025 🎉, with the following idea list.
• [2025/03/04] Add support for Zenoh for distributed dataflow.
• [2025/03/04] Add support for Meta SAM2, Kokoro(TTS), Improved Qwen2.5 Performance using llama.cpp.
• [2025/02/25] Add support for Qwen2.5(LLM), Qwen2.5-VL(VLM), outetts(TTS)

Highlights

• 🚀 A single CLI to launch your Python and Rust robotic projects.
• ⚡️ 10-17x faster than ros2.
• 🐍 Easy and Fast prototyping with a clean Python API.
• 🖥️ Supports macOS, Linux, and Windows.
• ⏬ Installable without Rust via curl or powershell.
• ❇️ Includes a large set of pre-packaged nodes for fast prototyping.
• 🛠️ Build and Run applications without compilation step beyond the native compiler of your favourite language.
• 🤖 Simplifies building robotic applications by integrating hardware, algorithms, and AI models to facilitate seamless communication.
• ⚙️ Eases integration of hardware and software by supporting Python, C, C++, and ROS2, while ensuring low-latency communication with zero-copy Arrow messages.

Node Hub

Camera

Title	Description	Shields
PyOrbbeckSDK	Image and depth from Orbbeck Camera
PyRealsense	Image and depth from Realsense
Video Capture	Image stream from Camera

Peripheral

Title	Description	Shields
Keyboard	Keyboard char listener
Microphone	Audio from microphone
PyAudio(Speaker)	Output audio from speaker

Actuator

Title	Description	Shields
Feetech	Feetech Client
Dynamixel	Dynamixel Client

Chassis

Title	Description	Shields
Agilex - UGV	Robomaster Client
DJI - Robomaster S1	Robomaster Client
Dora Kit Car	Open Source Chassis

Arm

Title	Description	Shields
Alex Koch - Low Cost Robot	Alex Koch - Low Cost Robot Client
Lebai - LM3	Lebai client
Agilex - Piper	Agilex arm client

Robot

Title	Description	Shields
Pollen - Reachy 1	Reachy 1 Client
Pollen - Reachy 2	Reachy 2 client
Trossen - Aloha	Aloha client

Voice Activity Detection

Title	Description	Shields
Silero VAD	Silero Voice activity detection

Speech to Text

Title	Description	Shields
Whisper	Transcribe audio to text

Vision Language Model

Title	Description	Shields
Qwen2.5-vl	Vision Language Model using Qwen2.5 VL
InternVL	InternVL is a vision language model

Large Language Model

Title	Description	Shields
Qwen2.5	Large Language Model using Qwen

Vision Language Action

Title	Description	Shields
RDT-1B	Infer policy using Robotic Diffusion Transformer

Object Detection

Title	Description	Shields
Yolov8	Object detection

Segmentation

Title	Description	Shields
SAM2	Segment Anything

Translation

Title	Description	Shields
ArgosTranslate	Open Source translation engine
Opus MT	Translate text between language

Text to Speech

Title	Description	Shields
Kokoro TTS	Efficient Text to Speech

Recorder

Title	Description	Shields
Llama Factory Recorder	Record data to train LLM and VLM
LeRobot Recorder	LeRobot Recorder helper

Visualization

Title	Description	Shields
Plot	Simple OpenCV plot visualization
Rerun	Visualization tool

Simulator

Title	Description	Shields
Mujoco	Mujoco Simulator
Carla	Carla Simulator
Gymnasium	Experimental OpenAI Gymnasium bridge

Quick Start

Installation

pip install dora-rs-cli

Additional installation methods

Install dora with our standalone installers, or from crates.io:

With cargo

cargo install dora-cli

With Github release for macOS and Linux

curl --proto '=https' --tlsv1.2 -sSf https://raw.githubusercontent.com/dora-rs/dora/main/install.sh | bash

With Github release for Windows

powershell -c "irm https://raw.githubusercontent.com/dora-rs/dora/main/install.ps1 | iex"

With Source

git clone https://github.com/dora-rs/dora.git
cd dora
cargo build --release -p dora-cli
PATH=$PATH:$(pwd)/target/release

Documentation

The full documentation is available on our website.
A lot of guides are available on this section of our website.

Getting Started

1. Run some Python examples:

uv venv --seed -p 3.11
dora build https://raw.githubusercontent.com/dora-rs/dora/refs/heads/main/examples/object-detection/yolo.yml --uv
dora run yolo.yml --uv

Make sure to have a webcam

To stop your dataflow, you can use ctrl+c

What is Dora? And what features does Dora offer?

Dataflow-Oriented Robotic Architecture (dora-rs) is a framework that makes creation of robotic applications fast and simple.

dora-rs implements a declarative dataflow paradigm where tasks are split between nodes isolated as individual processes.

Each node defines its inputs and outputs to connect with other nodes.

nodes:
  - id: camera
    path: opencv-video-capture
    inputs:
      tick: dora/timer/millis/20
    outputs:
      - image
      -
  - id: plot
    path: opencv-plot
    inputs:
      image: camera/image

The dataflow paradigm has the advantage of creating an abstraction layer that makes robotic applications modular and easily configurable.

---

It offers several features, such as:

TCP Communication and Shared Memory

Communication between nodes is handled with shared memory on a same machine and TCP on distributed machines. Our shared memory implementation tracks messages across processes and discards them when obsolete. Shared memory slots are cached to avoid new memory allocation.

Arrow Message Format

Nodes communicate with Apache Arrow Data Format.

Apache Arrow is a universal memory format for flat and hierarchical data. The Arrow memory format supports zero-copy reads for lightning-fast data access without serialization overhead. It defines a C data interface without any build-time or link-time dependency requirement, that means that dora-rs has no compilation step beyond the native compiler of your favourite language.

Opentelemetry

dora-rs uses Opentelemetry to record all your logs, metrics and traces. This means that the data and telemetry can be linked using a shared abstraction.

Opentelemetry is an open source observability standard that makes dora-rs telemetry collectable by most backends such as elasticsearch, prometheus, Datadog...

Opentelemetry is language independent, backend agnostic, and easily collect distributed data, making it perfect for dora-rs applications.

ROS2 Bridge

Note: this feature is marked as unstable.

• Compilation Free Message passing to ROS 2
• Automatic conversion ROS 2 Message <-> Arrow Array

import pyarrow as pa

# Configuration Boilerplate...
turtle_twist_writer = ...

## Arrow Based ROS2 Twist Message
## which does not require ROS2 import
message = pa.array([{
            "linear": {
                "x": 1,
            },
            "angular": {
                "z": 1
            },
        }])

turtle_twist_writer.publish(message)

You might want to use ChatGPT to write the Arrow Formatting: https://chat.openai.com/share/4eec1c6d-dbd2-46dc-b6cd-310d2895ba15

Showcases

Self-Coding Robot: Code RAG (WIP)

You can easily create a self-coding robot, by combining Hot-reloading with a Retrieval Augmented Generation (RAG) that is going to generate code modification from your prompt.
See:examples/python-operator-dataflow

Self-Coding Robot is just the tip of the iceberg of robotics combined with llm, that we hope to power. There is so much more that we haven't explored yet like:

• self-debugging
• memory
• function calling

Support Matrix

	dora-rs	Hoped for
Tier 1 Support	Python, Rust	C, C++, ROS 2
Tier 2 Support	C, C++, ROS2
Message Format	Arrow	Native
Local Communication	Shared Memory, Cuda zero-copy IPC	Custom Middleware, intra-process tokio::channel communication
Remote Communication	Zenoh	Custom Middleware
Metrics, Tracing, and Logging	Opentelemetry	Native logging libraries into Opentelemetry
Supported Platforms (x86)	Windows, MacOS, Linux
Supported Platforms (ARM)	MacOS, Linux
Configuration	YAML

Contributing

We are passionate about supporting contributors of all levels of experience and would love to see
you get involved in the project. See the
contributing guide to get started.

Discussions

Our main communication channels are:

• Our Discord server
• Our Github Project Discussion

Feel free to reach out on any topic, issues or ideas.

We also have a contributing guide.

License

This project is licensed under Apache-2.0. Check out NOTICE.md for more information.