106 lines
3.8 KiB
Makefile
106 lines
3.8 KiB
Makefile
.PHONY: kind tilt-up tilt-down seed seed-fetch seed-push recon evals test \
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run-log run-logs \
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compose-up compose-down compose-clean compose-seed compose-recon compose-evals \
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docs-graphs
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COMPOSE := docker compose -f ctrl/docker-compose.yml
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KCTX := --context kind-nvi
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KNS := -n nvi
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# ── kind + Tilt (primary path) ─────────────────────────────
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kind:
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bash ctrl/kind-config.sh
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tilt-up:
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cd ctrl && tilt up $(KCTX)
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tilt-down:
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cd ctrl && tilt down $(KCTX)
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seed-fetch:
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bash ctrl/seed/download.sh
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# Copy the downloaded SQLite into the api pod. The file is excluded from the
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# docker build context (.dockerignore) to keep the image small, so we push
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# it explicitly the first time.
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seed-push:
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@POD=$$(kubectl $(KCTX) $(KNS) get pod -l app=api -o jsonpath='{.items[0].metadata.name}'); \
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echo "pushing financial.sqlite → $$POD"; \
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kubectl $(KCTX) $(KNS) exec $$POD -- mkdir -p /app/seed/data; \
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kubectl $(KCTX) $(KNS) cp ctrl/seed/data/financial.sqlite $$POD:/app/seed/data/financial.sqlite
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seed: seed-fetch seed-push
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kubectl $(KCTX) $(KNS) exec deploy/api -- uv run python -m seed.load_bird
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# Rebuild api/datasets/<name>/{extracted_schema,recon}.json from the YAML +
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# live warehouse introspection. Runs inside the api pod (needs Postgres
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# access), then copies the artefacts back to the host so they appear next
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# to the source YAMLs.
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recon:
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@POD=$$(kubectl $(KCTX) $(KNS) get pod -l app=api -o jsonpath='{.items[0].metadata.name}'); \
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kubectl $(KCTX) $(KNS) exec $$POD -- uv run python -m api.recon.build; \
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for ds in $$(ls api/datasets); do \
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[ -d "api/datasets/$$ds" ] || continue; \
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case "$$ds" in __*|.*) continue ;; esac; \
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for f in extracted_schema.json recon.json; do \
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kubectl $(KCTX) $(KNS) cp $$POD:/app/api/datasets/$$ds/$$f api/datasets/$$ds/$$f 2>/dev/null \
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&& echo " → api/datasets/$$ds/$$f" || true; \
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done; \
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done
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evals:
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kubectl $(KCTX) $(KNS) exec deploy/api -- uv run python -m api.evals.run_evals
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# Pull a run's JSONL transcript from the api pod to the host. The api writes
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# every published event into /app/.data/logs/<RUN>.jsonl inside the pod;
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# this target copies it next to .data/logs/ on the host so it's easy to
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# share / grep / paste a path to.
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# Usage: make run-log RUN=<run_id>
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run-log:
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@[ -n "$(RUN)" ] || { echo "usage: make run-log RUN=<run_id>" >&2; exit 1; }
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@mkdir -p .data/logs
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@POD=$$(kubectl $(KCTX) $(KNS) get pod -l app=api -o jsonpath='{.items[0].metadata.name}'); \
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kubectl $(KCTX) $(KNS) cp $$POD:/app/.data/logs/$(RUN).jsonl .data/logs/$(RUN).jsonl \
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&& echo "→ .data/logs/$(RUN).jsonl"
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# List the runs the api currently has log files for (most recent first).
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run-logs:
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@POD=$$(kubectl $(KCTX) $(KNS) get pod -l app=api -o jsonpath='{.items[0].metadata.name}'); \
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kubectl $(KCTX) $(KNS) exec $$POD -- sh -c 'ls -1t /app/.data/logs 2>/dev/null || echo "(no logs yet)"'
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# Unit tests run on the host venv (no postgres/llm calls needed).
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# Ensures dev extras are installed first; uv is idempotent on no-ops.
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test:
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uv sync --extra dev
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uv run pytest -q
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# ── docker-compose (alternative path) ──────────────────────
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compose-up:
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$(COMPOSE) up -d --build
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compose-down:
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$(COMPOSE) down
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compose-clean:
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$(COMPOSE) down -v
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compose-seed: seed-fetch
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$(COMPOSE) exec api uv run python -m seed.load_bird
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compose-recon:
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$(COMPOSE) exec api uv run python -m api.recon.build
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compose-evals:
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$(COMPOSE) exec api uv run python -m api.evals.run_evals
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# ── docs ───────────────────────────────────────────────────
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docs-graphs:
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@for f in docs/graphs/*.dot; do \
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out=$${f%.dot}.svg; \
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echo " graphviz $$f → $$out"; \
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dot -Tsvg $$f -o $$out; \
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done
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