Repository Utilities¶
These utilities are the stable entrypoints for contributors, agents, notebooks, and CI. Prefer them over ad hoc shell commands so every workflow hits the same package code.
Core Commands¶
make utility-summary: list the supported user-facing utility surfaces.make files-sync: regenerate the tracked-file inventory surfacesFILES.mdandFILES.csv.make ask QUESTION="...": answer a repository-grounded question with the baseline RAG flow, printing deterministicQuestion:,Answer:, andEvidence:sections.make ask-dspy QUESTION="...": answer through the DSPy runtime path, optionally loading a saved compiled program, and automatically reusing the latest saved one when no explicit program path is provided.make ask-live QUESTION="...": retrieve repository evidence locally, then synthesize the answer through Azure OpenAI or Azure AI Inference.make dspy-train DSPY_RUN_NAME=...: compile and persist a repository-grounded DSPy program underartifacts/dspy/.make dspy-artifacts: inspect the saved DSPy runs, latest program path, and recorded benchmark summaries.make exploratorium-sync: regenerate the bilingual publication inventory of files, links, and fetch state.make retrieval-eval: evaluate retrieval quality across a top-k sweep with source recall, precision, reciprocal-rank metrics, and per-tag benchmark summaries.make discover-mcp: inspect repository-local MCP candidates.make smoke-test: exercise answer generation, MCP discovery, and Azure manifest output together.make azure-openai-probe: validate the Azure OpenAI runtime contract and run a minimal live round trip.make azure-inference-probe: validate and normalize the Azure AI Inference runtime contract and run a minimal live round trip.make todo-sync: regenerate the shared TODO backlog table for bothTODO.MDand the publication PDF source.make exploratorium-build: build the committed bilingual exploratorium translation PDF.make verify-surfaces: validate the Makefile and notebook contract.make notebook-report: execute all tracked notebooks with monitored progress and report artifacts.make gh-runs: list the latest GitHub Actions runs withgh.make gh-watch: watch the latest or selected GitHub Actions run and exit with its status.make gh-failed-logs: show failed job logs for the latest or selected run.make azure-manifest MODEL_ID=... DEPLOYMENT_NAME=...: write Azure deployment metadata.uv run repo-rag ...: call the packaged CLI directly inside the lockeduvenvironment.make build: build the wheel and source distribution throughuv build.- Notebooks reuse
src/repo_rag_lab/notebook_scaffolding.pyandsrc/repo_rag_lab/notebook_support.pyfor sample validation, benchmark assertions, tuning metadata, latest compiled-program inspection, and notebook-run logging. - Batch notebook runs also use
src/repo_rag_lab/notebook_runner.pyto stream progress, capture raw logs, and write JSON plus Markdown reports underartifacts/notebook_runs/.
Why The Repository Uses These Surfaces¶
- Keep notebooks, tests, automation, and manual runs aligned.
- Give agents one preferred command vocabulary.
- Focus verification on behavior users actually invoke.
- Keep local Azure runtime validation on the same package entrypoints as the docs and notebooks.
- Keep local execution, CI, and publishing on the same
uv-managed toolchain.