ubiquitouslearning Install pymllm
Goal
Help the user install the pymllm package with the right configuration for their use case.
Workflow
Step 1: Ask the user which install mode they want
Use AskUserQuestion to present two options:
Full Install (with C++ build)
- Compiles the C++ mllm runtime and FFI extension via CMake
- Required if the user needs mobile inference, model conversion with FFI, or CPU/QNN backends
- Slower (several minutes depending on the machine)
- Command:
pip wheel -v -w dist . && pip install dist/*.whl --force-reinstall
Fast Install (Python-only, skip CMake)
- Skips the entire CMake build step
- Only installs the pure Python package
- Recommended for users who only use CUDA backends (FlashInfer, TileLang) and do not need the C++ mllm runtime
- Much faster (seconds)
- Command:
SKBUILD_WHEEL_CMAKE=false pip install -e .
Step 2: Ask editable or non-editable
Use AskUserQuestion to ask:
- Editable (
pip install -e .): For active development. Python imports point to the source tree. Changes to.pyfiles take effect immediately without reinstalling. - Non-editable (wheel): For stable usage. Installs a wheel into site-packages.
Step 3: Ask whether the user needs CUDA optional dependencies
Use AskUserQuestion to ask whether the user needs CUDA support (FlashInfer, TileLang, pyzmq, etc.).
This determines whether to append [cuda] to the install specifier (e.g. pip install -e ".[cuda]" instead of pip install -e .).
This applies to ALL install modes. For fast-install users this is especially important since the CUDA packages are the primary compute backend.
Step 4: Execute the install
Based on user choices, compose and run the appropriate command. The install specifier is either . or ".[cuda]" depending on Step 3.
| Mode | Editable | CUDA | Command |
|---|---|---|---|
| Full | Yes | No | pip install -e -v . |
| Full | Yes | Yes | pip install -e -v ".[cuda]" |
| Full | No | No | pip wheel -v -w dist . && pip install dist/*.whl --force-reinstall |
| Full | No | Yes | pip wheel -v -w dist . && pip install dist/*.whl --force-reinstall && pip install "pymllm[cuda]" |
| Fast | Yes | No | SKBUILD_WHEEL_CMAKE=false pip install -e . |
| Fast | Yes | Yes | SKBUILD_WHEEL_CMAKE=false pip install -e ".[cuda]" |
| Fast | No | No | SKBUILD_WHEEL_CMAKE=false pip wheel -v -w dist . && pip install dist/*.whl --force-reinstall |
| Fast | No | Yes | SKBUILD_WHEEL_CMAKE=false pip wheel -v -w dist . && pip install dist/*.whl --force-reinstall && pip install "pymllm[cuda]" |
Step 5: Post-install for editable + full build
If the user chose editable + full build, the compiled .so files live in a build directory (e.g. build/bin/), not in the source tree. The Python code at pymllm/__init__.py looks for libraries at pymllm/lib/MllmFFIExtension.so. A symlink is needed to bridge this gap.
Invoke the /link-pymllm-lib skill to help the user set up the symlink.
Important Notes
- The project root must contain
pyproject.tomlwithscikit-build-coreas the build backend. - The
wheel.cmake = trueflag inpyproject.tomlcontrols whether CMake runs. The env varSKBUILD_WHEEL_CMAKE=falseoverrides it at install time without modifying the file. - For non-editable full builds, the
.sofiles are bundled inside the wheel automatically — no symlink needed. - For fast installs,
pymllm.is_mobile_available()will returnFalsesince no C++ libraries are present. This is expected. - The
[cuda]optional dependencies are defined inpyproject.tomlunder[project.optional-dependencies].