install-pymllm

name	install-pymllm
description	Install the pymllm Python package. Asks the user whether to do a full build (with CMake C++ compilation) or a fast install (Python-only, skip CMake). Use when the user asks to install, set up, or reinstall pymllm.

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 .py files 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.toml with scikit-build-core as the build backend.
• The wheel.cmake = true flag in pyproject.toml controls whether CMake runs. The env var SKBUILD_WHEEL_CMAKE=false overrides it at install time without modifying the file.
• For non-editable full builds, the .so files are bundled inside the wheel automatically — no symlink needed.
• For fast installs, pymllm.is_mobile_available() will return False since no C++ libraries are present. This is expected.
• The [cuda] optional dependencies are defined in pyproject.toml under [project.optional-dependencies].