Fix studio setup: venv isolation, centralized .venv_t5, uv targeting
- All platforms (including Colab) now create ~/.unsloth/studio/.venv with --without-pip fallback for broken ensurepip environments - Add --python sys.executable to uv pip install in install_python_stack.py so uv targets the correct venv instead of system Python - Centralize .venv_t5 bootstrap in transformers_version.py with proper validation (checks required packages exist, not just non-empty dir) - Replace ~150 lines of duplicated install code across 3 worker files with calls to the shared _ensure_venv_t5_exists() helper - Use uv-if-present with pip fallback; do not install uv at runtime - Add site.addsitedir() shim in colab.py so notebook cells can import studio packages from the venv without system-Python double-install - Update .venv_t5 packages: huggingface_hub 1.3.0->1.7.1, add hf_xet - Bump transformers pin 4.57.1->4.57.6 in requirements + constraints - Add Fast-Install helper to setup.ps1 with uv+pip fallback - Keep Colab-specific completion banner in setup.sh
This commit is contained in:
Daniel Han
parent
f43091bf34
commit
fc2d577d0d
10 changed files with 239 additions and 224 deletions
102
studio/setup.sh
102
studio/setup.sh
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@ -240,50 +240,73 @@ install_python_stack() {
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python "$SCRIPT_DIR/install_python_stack.py"
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}
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if [ "$IS_COLAB" = true ]; then
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# Colab: install packages directly without venv
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install_python_stack
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else
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# Local: create venv under ~/.unsloth/studio/ (shared location, not in repo)
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STUDIO_HOME="$HOME/.unsloth/studio"
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VENV_DIR="$STUDIO_HOME/.venv"
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VENV_T5_DIR="$STUDIO_HOME/.venv_t5"
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mkdir -p "$STUDIO_HOME"
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# Create venv under ~/.unsloth/studio/ (shared location, not in repo).
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# All platforms (including Colab) use the same isolated venv so that
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# studio dependencies are never installed into the system Python.
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STUDIO_HOME="$HOME/.unsloth/studio"
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VENV_DIR="$STUDIO_HOME/.venv"
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VENV_T5_DIR="$STUDIO_HOME/.venv_t5"
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mkdir -p "$STUDIO_HOME"
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# Clean up legacy in-repo venvs if they exist
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[ -d "$REPO_ROOT/.venv" ] && rm -rf "$REPO_ROOT/.venv"
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[ -d "$REPO_ROOT/.venv_overlay" ] && rm -rf "$REPO_ROOT/.venv_overlay"
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[ -d "$REPO_ROOT/.venv_t5" ] && rm -rf "$REPO_ROOT/.venv_t5"
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# Clean up legacy in-repo venvs if they exist
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[ -d "$REPO_ROOT/.venv" ] && rm -rf "$REPO_ROOT/.venv"
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[ -d "$REPO_ROOT/.venv_overlay" ] && rm -rf "$REPO_ROOT/.venv_overlay"
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[ -d "$REPO_ROOT/.venv_t5" ] && rm -rf "$REPO_ROOT/.venv_t5"
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rm -rf "$VENV_DIR"
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rm -rf "$VENV_T5_DIR"
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"$BEST_PY" -m venv "$VENV_DIR"
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rm -rf "$VENV_DIR"
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rm -rf "$VENV_T5_DIR"
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# Try creating venv with pip; fall back to --without-pip + bootstrap
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# (some environments like Colab have broken ensurepip)
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if ! "$BEST_PY" -m venv "$VENV_DIR" 2>/dev/null; then
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"$BEST_PY" -m venv --without-pip "$VENV_DIR"
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source "$VENV_DIR/bin/activate"
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cd "$SCRIPT_DIR"
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install_python_stack
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curl -sS https://bootstrap.pypa.io/get-pip.py | python > /dev/null
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else
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source "$VENV_DIR/bin/activate"
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fi
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# ── 6b. Pre-install transformers 5.x into .venv_t5/ ──
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# Models like GLM-4.7-Flash need transformers>=5.3.0. Instead of pip-installing
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# at runtime (slow, ~10-15s), we pre-install into a separate directory.
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# The training subprocess just prepends .venv_t5/ to sys.path — instant switch.
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echo ""
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echo " Pre-installing transformers 5.x for newer model support..."
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mkdir -p "$VENV_T5_DIR"
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run_quiet "pip install transformers 5.x" pip install --target "$VENV_T5_DIR" --no-deps "transformers==5.3.0"
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run_quiet "pip install huggingface_hub for t5" pip install --target "$VENV_T5_DIR" --no-deps "huggingface_hub==1.3.0"
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echo "✅ Transformers 5.x pre-installed to $VENV_T5_DIR/"
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# ── Ensure uv is available (much faster than pip) ──
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USE_UV=false
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if command -v uv &>/dev/null; then
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USE_UV=true
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elif curl -LsSf https://astral.sh/uv/install.sh | sh > /dev/null 2>&1; then
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export PATH="$HOME/.local/bin:$PATH"
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command -v uv &>/dev/null && USE_UV=true
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fi
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# ── 7. WSL: pre-install GGUF build dependencies ──
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# On WSL, sudo requires a password and can't be entered during GGUF export
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# (runs in a non-interactive subprocess). Install build deps here instead.
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if grep -qi microsoft /proc/version 2>/dev/null; then
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echo ""
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echo "⚠️ WSL detected — installing build dependencies for GGUF export..."
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echo " You may be prompted for your password."
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sudo apt-get update -y
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sudo apt-get install -y build-essential cmake curl git libcurl4-openssl-dev
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echo "✅ GGUF build dependencies installed"
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# Helper: install a package, preferring uv with pip fallback
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fast_install() {
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if [ "$USE_UV" = true ]; then
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uv pip install --python "$(command -v python)" "$@" && return 0
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fi
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python -m pip install "$@"
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}
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cd "$SCRIPT_DIR"
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install_python_stack
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# ── 6b. Pre-install transformers 5.x into .venv_t5/ ──
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# Models like GLM-4.7-Flash need transformers>=5.3.0. Instead of pip-installing
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# at runtime (slow, ~10-15s), we pre-install into a separate directory.
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# The training subprocess just prepends .venv_t5/ to sys.path -- instant switch.
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echo ""
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echo " Pre-installing transformers 5.x for newer model support..."
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mkdir -p "$VENV_T5_DIR"
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run_quiet "install transformers 5.x" fast_install --target "$VENV_T5_DIR" --no-deps "transformers==5.3.0"
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run_quiet "install huggingface_hub for t5" fast_install --target "$VENV_T5_DIR" --no-deps "huggingface_hub==1.7.1"
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run_quiet "install hf_xet for t5" fast_install --target "$VENV_T5_DIR" --no-deps "hf_xet==1.4.2"
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echo "✅ Transformers 5.x pre-installed to $VENV_T5_DIR/"
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# ── 7. WSL: pre-install GGUF build dependencies ──
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# On WSL, sudo requires a password and can't be entered during GGUF export
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# (runs in a non-interactive subprocess). Install build deps here instead.
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if grep -qi microsoft /proc/version 2>/dev/null; then
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echo ""
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echo "⚠️ WSL detected -- installing build dependencies for GGUF export..."
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echo " You may be prompted for your password."
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sudo apt-get update -y
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sudo apt-get install -y build-essential cmake curl git libcurl4-openssl-dev
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echo "✅ GGUF build dependencies installed"
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fi
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# ── 8. Build llama.cpp binaries for GGUF inference + export ──
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@ -422,6 +445,9 @@ if [ "$IS_COLAB" = true ]; then
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echo "╠══════════════════════════════════════╣"
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echo "║ Unsloth Studio is ready to start ║"
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echo "║ in your Colab notebook! ║"
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echo "║ ║"
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echo "║ from colab import start ║"
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echo "║ start() ║"
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echo "╚══════════════════════════════════════╝"
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else
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echo "╔══════════════════════════════════════╗"
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