mirror of
https://github.com/harvard-edge/cs249r_book.git
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d456a5a962
Every other vol1 chapter folder name matches its qmd slug; this aligns the last outlier so folder == qmd stem across the volume. Also matches the slides folder name (slides/vol1/10_model_compression). - git mv contents/vol1/optimizations → contents/vol1/model_compression - Update path refs in 4 quarto configs (html, pdf, pdf-copyedit, epub) - Update path refs in index_prune_candidates.yml, build_locator_bins.py, format_tables.py, learning_objectives_bolding_parallel.sh - Update chapter-id refs (vol1/optimizations → vol1/model_compression) in vol2 quiz integration strings (ops_scale, robust_ai, sustainable_ai) - Update CHAPTER_DIRS, READING_ORDER, and stale "outlier" docstrings in fix_abbreviations.py, build_prior_vocab.py, build_audit_context.py, generate_quizzes.py (fallback logic kept as defensive code) - Rename _audit/optimizations_audit.json → model_compression_audit.json and fix its stale source_file/chapter fields - Update vol1/README.md chapter table
93 lines
4.2 KiB
Bash
Executable File
93 lines
4.2 KiB
Bash
Executable File
#!/usr/bin/env bash
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# Learning Objectives Bolding: Run Gemini CLI in parallel across all chapters
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#
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# Usage: From repo root, run:
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# ./book/tools/scripts/learning_objectives_bolding_parallel.sh
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#
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# Requires: Gemini CLI installed (npm install -g @google/gemini-cli or brew install gemini-cli)
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# Rate limits: Free tier is 60 req/min. Default MAX_PARALLEL=8 to stay under limit.
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# Adjust with: MAX_PARALLEL=4 ./book/tools/scripts/learning_objectives_bolding_parallel.sh
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set -e
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# Repo root (script lives at book/tools/scripts/)
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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REPO_ROOT="$(cd "$SCRIPT_DIR/../../.." && pwd)"
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cd "$REPO_ROOT"
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# Limit concurrent Gemini invocations to avoid rate limits (60/min free tier)
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MAX_PARALLEL="${MAX_PARALLEL:-2}"
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# All chapters with Learning Objectives (exclude compute_infrastructure_expanded—draft)
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CHAPTERS=(
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"book/quarto/contents/vol1/introduction/introduction.qmd"
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"book/quarto/contents/vol1/ml_systems/ml_systems.qmd"
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"book/quarto/contents/vol1/data_engineering/data_engineering.qmd"
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"book/quarto/contents/vol1/data_selection/data_selection.qmd"
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"book/quarto/contents/vol1/nn_architectures/nn_architectures.qmd"
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"book/quarto/contents/vol1/nn_computation/nn_computation.qmd"
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"book/quarto/contents/vol1/training/training.qmd"
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"book/quarto/contents/vol1/hw_acceleration/hw_acceleration.qmd"
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"book/quarto/contents/vol1/model_compression/model_compression.qmd"
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"book/quarto/contents/vol1/frameworks/frameworks.qmd"
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"book/quarto/contents/vol1/benchmarking/benchmarking.qmd"
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"book/quarto/contents/vol1/ml_ops/ml_ops.qmd"
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"book/quarto/contents/vol1/model_serving/model_serving.qmd"
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"book/quarto/contents/vol1/responsible_engr/responsible_engr.qmd"
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"book/quarto/contents/vol1/ml_workflow/ml_workflow.qmd"
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"book/quarto/contents/vol1/conclusion/conclusion.qmd"
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"book/quarto/contents/vol1/backmatter/appendix_algorithm.qmd"
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"book/quarto/contents/vol1/backmatter/appendix_data.qmd"
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"book/quarto/contents/vol1/backmatter/appendix_machine.qmd"
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"book/quarto/contents/vol1/backmatter/appendix_dam.qmd"
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"book/quarto/contents/vol1/backmatter/appendix_assumptions.qmd"
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"book/quarto/contents/vol2/introduction/introduction.qmd"
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"book/quarto/contents/vol2/compute_infrastructure/compute_infrastructure.qmd"
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"book/quarto/contents/vol2/network_fabrics/network_fabrics.qmd"
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"book/quarto/contents/vol2/data_storage/data_storage.qmd"
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"book/quarto/contents/vol2/distributed_training/distributed_training.qmd"
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"book/quarto/contents/vol2/collective_communication/collective_communication.qmd"
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"book/quarto/contents/vol2/fault_tolerance/fault_tolerance.qmd"
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"book/quarto/contents/vol2/fleet_orchestration/fleet_orchestration.qmd"
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"book/quarto/contents/vol2/inference/inference.qmd"
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"book/quarto/contents/vol2/edge_intelligence/edge_intelligence.qmd"
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"book/quarto/contents/vol2/ops_scale/ops_scale.qmd"
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"book/quarto/contents/vol2/performance_engineering/performance_engineering.qmd"
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"book/quarto/contents/vol2/sustainable_ai/sustainable_ai.qmd"
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"book/quarto/contents/vol2/responsible_ai/responsible_ai.qmd"
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"book/quarto/contents/vol2/robust_ai/robust_ai.qmd"
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"book/quarto/contents/vol2/security_privacy/security_privacy.qmd"
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"book/quarto/contents/vol2/conclusion/conclusion.qmd"
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)
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run_chapter() {
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local file="$1"
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local prompt="Read the instructions at .claude/docs/learning-objectives-gemini-instructions.md, then edit this chapter file to add bolding to Learning Objectives: $file"
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echo "[$(date +%H:%M:%S)] Starting: $file"
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if gemini -p "$prompt" --include-directories "book/quarto/contents,.claude/docs"; then
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echo "[$(date +%H:%M:%S)] Done: $file"
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else
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echo "[$(date +%H:%M:%S)] FAILED: $file" >&2
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return 1
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fi
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}
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export -f run_chapter
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export MAX_PARALLEL
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echo "Learning Objectives Bolding: Running Gemini CLI on ${#CHAPTERS[@]} chapters (max $MAX_PARALLEL parallel)"
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echo "Instructions: .claude/docs/learning-objectives-gemini-instructions.md"
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echo ""
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# Run in parallel with semaphore
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for ch in "${CHAPTERS[@]}"; do
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while [ "$(jobs -r 2>/dev/null | wc -l | tr -d ' ')" -ge "$MAX_PARALLEL" ]; do
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sleep 2
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done
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run_chapter "$ch" &
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done
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wait
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echo ""
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echo "All chapters processed. Review changes with: git diff book/quarto/contents/"
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