Development environment
Prepare Python and native code inside the Linux environment.
Develop inside the Linux environment provided by the installed AidLux image. The image determines which Python version, native libraries, and accelerator backends are available.
Inspect the toolchain
python3 --version
python3 -m pip --version
cc --version
If a command is missing, use the package manager supplied with the image. Do not assume that packages from another board or AidLux release have compatible binaries.
Create a Python environment
Use a project environment for application dependencies when the image supports venv:
cd ~/projects/my-app
python3 -m venv .venv
. .venv/bin/activate
python -m pip --version
Hardware SDK packages sometimes install outside the virtual environment. If an SDK import fails in venv, check how that SDK is packaged before copying system files into the project.
Keep a reproducible record
Record the board revision, image version, SDK versions, model format, and runtime backend with the application. A model working on one release may require a different converter or accelerator runtime on another.
For AI applications, continue with the inference workflow. For robot applications, continue with ROS 2 integration.