Python Setup

Several Lite Suite apps rely on Python for AI inference, scripting, and backend services. Rather than requiring you to manage Python installations yourself, Lite Suite creates and maintains a shared virtual environment automatically.

How It Works

During installation, Lite Suite:

1. Detects your system Python installation (Python 3.10+ required).
2. Creates a shared virtual environment at <install-dir>\.venv.
3. Installs the Python dependencies each selected app needs into that venv.

All Python-based apps share this single venv. This avoids duplicate installs of large packages like PyTorch, which can be several gigabytes.

Apps That Require Python

The following apps depend on the Python environment:

| App | What Python Does | |-----|-----------------| | LiteImage | Runs Flux, SDXL, Stable Diffusion, and video generation models locally; includes face swap and enhancement | | LiteMCP | Python-based MCP server providing 13 tool domains | | LiteBench | Orchestrates LLM benchmark runs and result analysis | | LiteCLI | Universal MCP CLI and Skill Compiler | | LiteTUI | TUI + CLI code generation framework |

If you only install apps that do not require Python (like LiteCore, LiteEditor, or LiteTerminal), no Python environment is created.

Configuring the Python Path

By default, Lite Suite searches for Python in the standard locations:

• python and python3 on your system PATH
• Common install locations (C:\Python3*, %LOCALAPPDATA%\Programs\Python\*)

To override this and point to a specific Python installation:

1. Open LiteCore and go to Settings.
2. Under Python, enter the full path to your Python executable (e.g., C:\Python312\python.exe).
3. Click Apply. Lite Suite will recreate the venv using the specified interpreter.

You can also set the LITE_PYTHON environment variable before running the installer:

set LITE_PYTHON=C:\Python312\python.exe
LiteSuiteInstaller.exe

GPU Acceleration

For AI apps (LiteImage, LiteBench), GPU acceleration dramatically improves performance. Lite Suite installs the CUDA-enabled version of PyTorch by default if an NVIDIA GPU is detected.

Requirements for GPU acceleration:

• NVIDIA GPU with CUDA support
• NVIDIA drivers version 525.0 or later
• At least 6 GB of VRAM (8+ GB recommended for image generation)

If no compatible GPU is found, Lite Suite falls back to CPU-only PyTorch. This still works but is significantly slower for inference tasks.

Troubleshooting

"Python not found" during installation

Lite Suite requires Python 3.10 or later. Install it from python.org and make sure to check "Add Python to PATH" during the Python installer.

After installing Python, restart the Lite Suite installer.

Venv creation fails

Common causes:

• Antivirus interference -- some antivirus software blocks .pyd and .dll files from being created in the venv. Add your Lite Suite install directory to your antivirus exclusions.
• Long path issues -- if your install path is very deep, Windows path length limits (260 characters) can cause failures. Install to a short path like C:\LiteSuite.
• Corrupted Python install -- try running python -m venv test_env manually. If that fails, reinstall Python.

Package install errors

If a specific package fails to install:

1. Open a terminal in your Lite Suite directory.
2. Activate the venv: .venv\Scripts\activate
3. Try installing the package manually: pip install <package-name>
4. Check the error output -- common issues include missing Visual C++ Build Tools (required for some packages) or incompatible Python versions.

Resetting the Python environment

If the venv gets into a broken state, you can reset it:

1. Close all running Lite Suite apps.
2. Delete the .venv folder in your Lite Suite install directory.
3. Open LiteCore -- it will detect the missing venv and offer to recreate it.