- docker-publish smoke + docker_confirm.sh probe Jupyter /login, not /api: the launcher always configures a password hash so /api returns 403 and curl -f would never flip the health flag (false build failure). - entrypoint.sh CPU messaging: CPU mode covers Jupyter, GGUF tooling and llama.cpp (GGUF) Studio chat; training AND loading an Unsloth model (FastLanguageModel) still need a GPU, since from_pretrained runs CUDA probes. - install_llama_prebuilt.py: rollback/activation moves used bare os.replace, which fails with EXDEV across overlayfs in a Docker build and fell back to a broken source build (no nvcc). Add is_cross_device_error + move_install_dir_aside (os.replace fast path, copy+remove on EXDEV; busy errors still re-raise). - notebooks: %pip / %uv line magics and the `!python -m pip` form bypassed the PATH pip/uv shim and could overwrite the baked cu128 torch/vLLM stack. Add unsloth_nb_pip_magic.py to re-point them at the shim, wired via the IPython startup hook and installed into the venv site-packages. |
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|---|---|---|
| .. | ||
| backend | ||
| frontend | ||
| src-tauri | ||
| __init__.py | ||
| install_llama_prebuilt.py | ||
| install_node_prebuilt.py | ||
| install_python_stack.py | ||
| LICENSE.AGPL-3.0 | ||
| node_prebuilt_pins.json | ||
| package-lock.json | ||
| package.json | ||
| setup.bat | ||
| setup.ps1 | ||
| setup.sh | ||
| Unsloth_Studio_Colab.ipynb | ||