RIA Toolkit OSS is the open-source version of the RIA Toolkit, providing the fundamental components to help engineers and researchers get started building, testing, and deploying radio intelligence applications.
## 🌟 Key features
- Core classes for loading, managing, and interacting with machine learning assets, including recordings, models, and datasets.
- Fundamental recording augmentations and impairments for radio ML dataset preparation.
- (Coming soon) A unified interface for interacting with software-defined radios, including [USRP](https://www.ettus.com/products/), [BladeRF](https://www.nuand.com/), [PlutoSDR](https://www.analog.com/en/resources/evaluation-hardware-and-software/evaluation-boards-kits/adalm-pluto.html), [RTL-SDR](https://www.rtl-sdr.com/), [HackRF](https://greatscottgadgets.com/hackrf/), and [thinkRF](https://thinkrf.com/).
- (Coming soon) Basic model training and testing utilities.
- **[RIA Toolkit](https://qoherent.ai/radioinferenceapps/)**: The full, unthrottled set of tools for developing, testing, and deploying radio intelligence applications.
- **[RIA Hub](https://riahub.ai/)**: Wield the RIA Hub Toolkit plus purpose-built automations directly in your browser, without the need to write code or setup infrastructure. Additionally, unlock access to Qoherent's rich IP library as well as community projects.
- **[RIA RAN](https://qoherent.ai/intelligent-5g-ran/)**: Radio intelligence solutions engineered to seamlessly integrate with existing RAN environments, including ORAN-compliant networks.
RIA Hub Toolkit OSS can be installed either as a standard Python package or as a Conda package.
### Installation with Conda (recommended)
RIA Toolkit OSS is available is available as a Conda packages on the [RIA Hub Conda Package Registry](https://riahub.ai/qoherent/-/packages/conda/ria-toolkit-oss).
RIA Toolkit OSS can be installed into any Conda environment. However, it is recommended to install within the base environment of [Radioconda](https://github.com/radioconda/radioconda-installer), which includes GNU Radio and several pre-configured libraries for common SDR devices. Detailed instructions for installing and setting up Radioconda are available in the project README.
This ensures that the Conda package manager is fully up-to-date, allowing new or updated packages to be installed into the base environment without conflicts.
The `<version>` and `<build>` may differ depending on the release you installed.
### Installation with Pip
RIA Toolkit OSS is available as a standard Python package on both the [RIA Hub PyPI Package Registry](https://riahub.ai/qoherent/-/packages/pypi/ria-toolkit-oss) and [PyPI](https://pypi.org/project/ria-toolkit-oss/).
These packages can be installed into a standard Python virtual environment using Pip. Additional information on Python virtual environments can be found here: [W3Schools: Python Virtual Environment](https://www.w3schools.com/python/python_virtualenv.asp).
Please follow the steps below to install RIA Toolkit OSS using Pip:
While RIA Toolkit OSS can also be installed from the RIA Hub PyPI Package Registry, RIA Hub does not yet support a proxy or cache for public packages. We intend to add this missing functionality to RIA Hub soon. In the meantime, you need to use the `--no-deps` option with pip to skip automatic dependency installation, and then manually install each dependency afterward.
Finally, RIA Toolkit OSS can be installed directly from the source code. This approach is only recommended if you require an unpublished or development version of the project. Follow the steps below to install RIA Toolkit OSS from source:
Once the project is installed, you can import its modules, functions, and classes for use in your Python code. For example, you can use the following import statement to access the `Recording` object:
Contributions are always welcome! Whether it's an enhancement, bug fix, or new usage example, your input is valuable. If you'd like to contribute to the project, please reach out to the project maintainers.
If you have a larger project in mind, please [contact us](https://www.qoherent.ai/contact/) directly, we'd love to collaborate with you. 🚀
## 🖊️ Authorship
RIA Toolkit OSS is developed and maintained by [Qoherent](https://qoherent.ai/), with the invaluable support of many independent contributors.
If you are doing research with RIA Toolkit OSS, please cite the project:
If you like what we're doing, don't forget to give the project a star! ⭐
## 📄 License
RIA Toolkit OSS is **free and open-source**, released under AGPLv3.
Alternative permissive and commercial licensing options are available upon request. Please [contact us](https://qoherent.ai/contact/) for further details.
## 💻 Developer information
This project adheres to [Qoherent's Coding Guidelines](https://github.com/qoherent/.github/blob/main/docs/CODING.md). We kindly ask you to review them before getting started.
### Poetry
To ensure a consistent development environment, this project uses [Poetry](https://python-poetry.org/) for dependency management. You can initialize a new Poetry environment by running `install` from anywhere within the project:
```bash
poetry install
```
Running `install` when a `poetry.lock` file is present resolves and installs all dependencies listed in `pyproject.toml`, but Poetry uses the exact versions listed in `poetry.lock` to ensure that the package versions are consistent for everyone working on your project. Please note that the project itself will be installed in editable mode when running `poetry install`.
Unit tests can be run with the following command:
```bash
poetry run pytest
```
Source and wheels archives can be built with the following command:
```bash
poetry build
```
For more information on basic Poetry usage, start [here](https://python-poetry.org/docs/basic-usage/).
### Sphinx
Project documentation is auto-generated from project docstrings using [Sphinx](https://www.sphinx-doc.org/en/master/). Therefore, all importable components require comprehensive docstrings, complete with doctests demonstrating usage.
It's recommended to use `sphinx-autobuild`, which eliminates the need to manually rebuild the docs after making changes:
Once the documentation is built, you can view it by opening `docs/build/html/index.html` in a web browser. Please note that this strategy requires manually rebuilding the documentation to view updates.