base on DORA (Dataflow-Oriented Robotic Architecture) is middleware designed to streamline and simplify the creation of AI-based robotic applications. It offers low latency, composable, and distributed dataflow capabilities. Applications are modeled as directed graphs, also referred to as pipelines. # <p align="center"> <img src="https://raw.githubusercontent.com/dora-rs/dora/main/docs/src/logo.svg" width="400"/> </p> <h2 align="center"> <a href="https://www.dora-rs.ai">Website</a> | <a href="https://dora-rs.ai/docs/guides/getting-started/conversation_py/">Python API</a> | <a href="https://docs.rs/dora-node-api/latest/dora_node_api/">Rust API</a> | <a href="https://www.dora-rs.ai/docs/guides/">Guide</a> | <a href="https://discord.gg/6eMGGutkfE">Discord</a> </h2> <div align="center"> <a href="https://github.com/dora-rs/dora/actions"> <img src="https://github.com/dora-rs/dora/workflows/CI/badge.svg" alt="Build and test"/> </a> <a href="https://crates.io/crates/dora-rs"> <img src="https://img.shields.io/crates/v/dora_node_api.svg"/> </a> <a href="https://docs.rs/dora-node-api/latest/dora_node_api/"> <img src="https://docs.rs/dora-node-api/badge.svg" alt="rust docs"/> </a> <a href="https://pypi.org/project/dora-rs/"> <img src="https://img.shields.io/pypi/v/dora-rs.svg" alt="PyPi Latest Release"/> </a> </div> An extremely fast and simple **dataflow oriented robotic** framework to manage your projects and run complex **apps**, written in Rust. <p align="center"> <picture align="center"> <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/dora-rs/dora/main/docs/src/bar_chart_dark.svg"> <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/dora-rs/dora/main/docs/src/bar_chart_light.svg"> <img src="https://raw.githubusercontent.com/dora-rs/dora/main/docs/src/bar_chart_light.svg"> </picture> </p> <p align="center"> <a href="https://github.com/dora-rs/dora-benchmark/" > <i>Latency benchmark with Python API for both framework, sending 40M of random bytes.</i> </a> </p> ## Highlights - 🚀 A single CLI to launch your Python and Rust robotic projects. - ⚡️ [10-17x faster](https://github.com/dora-rs/dora-benchmark) than `ros2`. - 🐍 Easy and Fast prototyping with a clean [Python API](https://dora-rs.ai/docs/guides/getting-started/conversation_py/). - 🖥️ 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. ## Installation Install dora with our standalone installers, or from [crates.io](https://crates.io/crates/dora-cli): ### On macOS and Linux ```bash curl --proto '=https' --tlsv1.2 -sSf https://raw.githubusercontent.com/dora-rs/dora/main/install.sh | bash ``` ### On Windows ```powershell powershell -c "irm https://raw.githubusercontent.com/dora-rs/dora/main/install.ps1 | iex" ``` ### With cargo ```bash cargo install dora-cli ``` ## Documentation The full documentation is available on [our website](https://dora-rs.ai/). A lot of guides are available on [this section](https://dora-rs.ai/docs/guides/) of our website. ## Getting Started 1. Run the benchmark example (Rust must be installed): ```bash git clone https://github.com/dora-rs/dora cd dora cargo run --example benchmark --release ``` 2. Run some Python examples (A venv must be activated): ```bash # activate your venv here cd dora/examples/python-dataflow dora up dora build dataflow.yml dora start dataflow.yml ``` > Make sure to have a webcam To stop your dataflow, you can use <kbd>ctrl</kbd>+<kbd>c</kbd> ## What is Dora? And what features does Dora offer? **D**ataflow-**O**riented **R**obotic **A**rchitecture (`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. ```yaml 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. <p align="center"> <picture align="center"> <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/dora-rs/dora/main/docs/src/dora_diag_dark.svg"> <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/dora-rs/dora/main/docs/src/dora_diag_light.svg"> <img src="https://raw.githubusercontent.com/dora-rs/dora/main/docs/src/dora_diag_light.svg"> </picture> </p> --- 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](https://github.com/apache/arrow-rs) 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](https://opentelemetry.io/) 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. ### Hot-Reloading dora-rs implements Hot-Reloading for python which means you can change code at runtime in Python while keeping your state intact. Using the feature flag: `--attach --hot-reload`, dora-rs watch for code change and reload nodes that has been modified. You can check fail-safe mechanism at: https://github.com/dora-rs/dora/pull/239. See [this demo](http://www.youtube.com/watch?v=NvvTEP8Jak8). ### ROS2 Bridge **Note**: this feature is marked as unstable. - Compilation Free Message passing to ROS 2 - Automatic conversion ROS 2 Message <-> Arrow Array ```python 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](examples/python-operator-dataflow) <p align="center"> <picture align="center"> <source media="(prefers-color-scheme: dark)" srcset="https://raw.githubusercontent.com/dora-rs/dora/main/docs/src/self_coding_dark.svg"> <source media="(prefers-color-scheme: light)" srcset="https://raw.githubusercontent.com/dora-rs/dora/main/docs/src/self_coding_light.svg"> <img src="https://raw.githubusercontent.com/dora-rs/dora/main/docs/src/self_coding_light.svg"> </picture> </p> 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](https://arxiv.org/pdf/2304.05128.pdf) - [memory](https://github.com/cpacker/MemGPT) - [function calling](https://github.com/ShishirPatil/gorilla) ### Cool Hardwares Cool hardware that we think might be good fit to try out dora-rs 🙋 We are not sponsored by manufacturers: | | Price | Open Source | Github | type | Dora Project | | --------------------------------- | ----- | ------------------ | ---------------------------------------------------- | ---------- | ------------------------------------------------------- | | DJI Robomaster S1 | 550$ | SDK | https://github.com/dji-sdk/RoboMaster-SDK | Rover | https://huggingface.co/datasets/dora-rs/dora-robomaster | | DJI Robomaster EP Core | 950$ | SDK | https://github.com/dji-sdk/RoboMaster-SDK | Rover, Arm | | | DJI Tello | 100$ | | | Drone | | | BitCraze Crazyflies | 225$ | Firmware, Lib, SDK | https://github.com/bitcraze | Drone | | | AlexanderKoch-Koch/low_cost_robot | 250$ | Everything | https://github.com/AlexanderKoch-Koch/low_cost_robot | Arm | | | xArm 1S | 200$ | | | Arm | | | Wavego | 250$ | | | Quadruplet | | | AINex | 800$ | | | Humanoid | | > For more: https://docs.google.com/spreadsheets/d/1YYeW2jfOIWDVgdEgqnMvltonHquQ7K8OZCrnJRELL6o/edit#gid=0 ## Support Matrix | | dora-rs | Hoped for | | --------------------------------- | --------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------- | | **Tier 1 Support** | Python, Rust | C, C++, ROS 2 | | **Tier 2 Support** | C, C++, ROS2 | | **Hot-reloading** | Python | Rust (https://github.com/orgs/dora-rs/discussions/360) | | **Message Format** | Arrow | Native | | **Local Communication** | Shared Memory | Custom Middleware, [zero-copy GPU IPC](https://arrow.apache.org/docs/python/api/cuda.html), intra-process `tokio::channel` communication | | **Remote Communication** | TCP | Custom Middleware, [Zenoh](https://zenoh.io/) | | **Metrics, Tracing, and Logging** | Opentelemetry | Native logging libraries into Opentelemetry | | **Data archives** | Parquet ([dora-record](https://github.com/dora-rs/dora/tree/main/node-hub/dora-record)) | | **Visualization and annotation** | OpenCV | [rerun.io](rerun.io) | | **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](https://github.com/dora-rs/dora/blob/main/CONTRIBUTING.md) to get started. ## Discussions Our main communication channels are: - [Our Discord server](https://discord.gg/6eMGGutkfE) - [Our Github Project Discussion](https://github.com/orgs/dora-rs/discussions) Feel free to reach out on any topic, issues or ideas. We also have [a contributing guide](CONTRIBUTING.md). ## License This project is licensed under Apache-2.0. Check out [NOTICE.md](NOTICE.md) for more information. ", Assign "at most 3 tags" to the expected json: {"id":"9190","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"