Run memory-safe frozen V121 semantic residual #4

	name: Trace Ace V121 Local Bootstrap

	on:
	pull_request:
	branches: [agent/trace-ace-mastery-events, agent/v111-runner]
	paths:
	- '.github/workflows/trace-ace-v121-local-bootstrap.yml'
	workflow_dispatch:

	jobs:
	bootstrap:
	runs-on: ubuntu-24.04
	timeout-minutes: 10
	permissions:
	contents: read
	steps:
	- uses: actions/checkout@v4
	- uses: actions/setup-python@v5
	with:
	python-version: '3.13'
	- name: Download Python 3.13 wheelhouse
	run: \|
	mkdir -p wheelhouse
	python -m pip download --only-binary=:all: --dest wheelhouse fastembed==0.8.0
	- name: Install FastEmbed and fetch exact Jina model
	run: \|
	python -m pip install --no-index --find-links wheelhouse fastembed==0.8.0
	python - <<'PY'
	from fastembed import TextEmbedding
	m = TextEmbedding(model_name='jinaai/jina-embeddings-v2-small-en')
	print('model_ready', type(m).__name__)
	PY
	mkdir -p model_cache
	for p in "$HOME/.cache/fastembed" "$HOME/.cache/huggingface"; do
	if [ -d "$p" ]; then cp -a "$p" model_cache/; fi
	done
	find model_cache -maxdepth 4 -type f -printf '%p %s\n' \| head -100
	- uses: actions/upload-artifact@v4
	with:
	name: v121-python313-wheelhouse
	path: wheelhouse/
	retention-days: 2
	compression-level: 0
	- uses: actions/upload-artifact@v4
	with:
	name: v121-jina-model-cache
	path: model_cache/
	retention-days: 2
	compression-level: 0

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