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

Website | Python API | Rust API | Guide | Discord

Highlights

• 🚀 dora-rs is a framework to run realtime multi-AI and multi-hardware applications.
• 🦀 dora-rs internals are 100% Rust making it extremely fast compared to alternative such as being ⚡️ 10-17x faster than ros2.
• ❇️ Includes a large set of pre-packaged nodes for fast prototyping which simplifies integration of hardware, algorithms, and AI models.

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

Latest News 🎉

2025

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

Support Matrix

	dora-rs
APIs	Python >= 3.7 ✅ Rust ✅ C/C++ 🆗 ROS2 >= Foxy 🆗
OS	Linux: Arm 32 ✅ Arm 64 ✅ x64_86 ✅ MacOS: Arm 64 ✅ x64_86 ✅ Windows: x64_86 🆗 Android: 🛠️ (Blocked by: https://github.com/elast0ny/shared_memory/issues/32) IOS: 🛠️
Message Format	Arrow ✅ Standard Specification 🛠️
Local Communication	Shared Memory ✅ Cuda IPC 📐
Remote Communication	Zenoh 📐
Metrics, Tracing, and Logging	Opentelemetry 📐
Configuration	YAML ✅
Package Manager	pip: Python Node ✅ Rust Node ✅ C/C++ Node 🛠️ cargo: Rust Node ✅

• ✅ = First Class Support
• 🆗 = Best Effort Support
• 📐 = Experimental and looking for contributions
• 🛠️ = Unsupported but hoped for through contributions

Everything is open for contributions 🙋

Node Hub

Feel free to modify this README with your own nodes so that it benefits the community.

Camera

Title	Support	Description	Downloads	License	Release
PyOrbbeckSDK	📐	Image and depth from Orbbeck Camera
PyRealsense	Linux🆗 Mac🛠️	Image and depth from Realsense
Video Capture	✅	Image stream from Camera

Peripheral

Title	Support	Description	Downloads	License	Release
Keyboard	✅	Keyboard char listener
Microphone	✅	Audio from microphone
PyAudio(Speaker)	✅	Output audio from speaker

Actuator

Title	Support	Description	Downloads	License	Release
Feetech	📐	Feetech Client
Dynamixel	📐	Dynamixel Client

Chassis

Title	Support	Description	Downloads	License	Release
Agilex - UGV	🆗	Robomaster Client
DJI - Robomaster S1	📐	Robomaster Client
Dora Kit Car	🆗	Open Source Chassis

Arm

Title	Support	Description	Downloads	License	Release
Alex Koch - Low Cost Robot	📐	Alex Koch - Low Cost Robot Client
Lebai - LM3	📐	Lebai client
Agilex - Piper	🆗	Agilex arm client

Robot

Title	Support	Description	Downloads	License	Release
Pollen - Reachy 1	📐	Reachy 1 Client
Pollen - Reachy 2	🆗	Reachy 2 client
Trossen - Aloha	📐	Aloha client

Voice Activity Detection(VAD)

Title	Support	Description	Downloads	License	Release
Silero VAD	✅	Silero Voice activity detection

Speech to Text(STT)

Title	Support	Description	Downloads	License	Release
Whisper	✅	Transcribe audio to text

Object Detection

Title	Support	Description	Downloads	License	Release
Yolov8	✅	Object detection

Segmentation

Title	Support	Description	Downloads	License	Release
SAM2	Cuda✅ Metal🛠️	Segment Anything

Large Language Model(LLM)

Title	Support	Description	Downloads	License	Release
Qwen2.5	✅	Large Language Model using Qwen

Vision Language Model(VLM)

Title	Support	Description	Downloads	License	Release
Qwen2.5-vl	✅	Vision Language Model using Qwen2.5 VL
InternVL	🆗	InternVL is a vision language model

Vision Language Action(VLA)

Title	Support	Description	Downloads	License	Release
RDT-1B	🆗	Infer policy using Robotic Diffusion Transformer

Translation

Title	Support	Description	Downloads	License	Release
ArgosTranslate	🆗	Open Source translation engine
Opus MT	🆗	Translate text between language

Text to Speech(TTS)

Title	Support	Description	Downloads	License	Release
Kokoro TTS	✅	Efficient Text to Speech

Recorder

Title	Support	Description	Downloads	License	Release
Llama Factory Recorder	🆗	Record data to train LLM and VLM
LeRobot Recorder	📐	LeRobot Recorder helper

Visualization

Title	Support	Description	Downloads	License	Release
Plot	✅	Simple OpenCV plot visualization
Rerun	✅	Visualization tool

Simulator

Title	Support	Description	Downloads	License	Release
Mujoco	📐	Mujoco Simulator
Carla	📐	Carla Simulator
Gymnasium	📐	Experimental OpenAI Gymnasium bridge

Getting Started

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

Run

• Run the yolo python example:

## Create a virtual environment
uv venv --seed -p 3.11

## Install nodes dependencies of a remote graph
dora build https://raw.githubusercontent.com/dora-rs/dora/refs/heads/main/examples/object-detection/yolo.yml --uv

## Run yolo graph
dora run yolo.yml --uv

Make sure to have a webcam

To stop your dataflow, you can use ctrl+c

• To understand what is happening, you can look at the dataflow with:

cat yolo.yml

• Resulting in:

nodes:
  - id: camera
    build: pip install opencv-video-capture
    path: opencv-video-capture
    inputs:
      tick: dora/timer/millis/20
    outputs:
      - image
    env:
      CAPTURE_PATH: 0
      IMAGE_WIDTH: 640
      IMAGE_HEIGHT: 480

  - id: object-detection
    build: pip install dora-yolo
    path: dora-yolo
    inputs:
      image: camera/image
    outputs:
      - bbox

  - id: plot
    build: pip install dora-rerun
    path: dora-rerun
    inputs:
      image: camera/image
      boxes2d: object-detection/bbox

• In the above example, we can understand that the camera is sending image to both the rerun viewer as well as a yolo model that generates bounding box that is visualized within rerun.

Documentation

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

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.

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

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

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.