0b901cf2f9
Generic Constructor-Pattern agent kit for Claude Code. Zero personal data, fully English, MIT-licensed. Contents: - 34 reusable blocks (baseline, rules, stack/deploy/domain/api/scraper) - 14 cross-project agent manifests (code/ml/infra/researcher/critic/...) - 6 portable skills (/new-agent, /research, /test-gen, /debug-deep, /pr-review, /refactor) - Rust assembler (single binary, ~500 KB) - 3 hooks (auto-reassemble, pre-commit validate, no-hand-edit) - install.sh (idempotent, cargo-builds on first run) - MIT LICENSE All 6 sanity greps pass: 0 Russian text, 0 specific project names, 0 incident numbers, 0 user paths, 0 hardcoded IPs, 0 API keys. cargo check + assemble --validate: both pass on 14 manifests. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
26 lines
1.8 KiB
Markdown
26 lines
1.8 KiB
Markdown
# DEPLOY — Modal (GPU compute)
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A real cost-overrun incident (tens of dollars lost to unchecked runs) and a real KILL-GUARD incident (over an hour of training killed for a non-critical bug) shape every rule below.
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**Pre-launch 10-step checklist (all ticks before `modal run`):**
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1. `modal app list` — verify no collisions/duplicates
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2. GPU compat: A10G torch ≥ 2.0 (~$1.10/hr), H100 torch ≥ 2.1 (~$4.50/hr), B200 torch ≥ 2.6 (~$8/hr)
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3. `cat` the script — confirm file edits actually landed
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4. Cost estimate in dollars, verified on live https://modal.com/pricing (NOT from memory)
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5. Volume + `vol.commit()` after each write
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6. Checkpoints every 500 steps saving `state_dict` (not just JSON metrics)
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7. `retries=modal.Retries(max_retries=1)` minimum
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8. `.spawn()` for batches — NEVER `.map()` (cascade-kill on single failure)
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9. `flush=True` on every print; progress every 250 steps
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10. Single-variant smoke run BEFORE fanning out to N variants
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**Cost tiers:** AUTO < $5 · WARN $5-$20 (daily cap $20) · STOP > $20 (explicit user "yes, launch").
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**KILL GUARD (no exception):**
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- NEVER `modal app stop`, `modal app kill`, `kill <pid>`, `pkill -f modal` without literal user phrase "yes, stop it".
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- Before any stop: `modal app list` → show user what is running, how long in, how much remaining, current checkpoint state.
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- A bug in the launching script is NOT a reason to kill a running training run.
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**Volume persistence:** results survive only inside `modal.Volume` with explicit `vol.commit()`. Stdout is ephemeral — checkpoints in volume, metrics in volume, logs to volume.
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**Forbidden:** guessed prices from memory; `.map(return_exceptions=False)` for batches; `print()` without `flush=True`; launching N variants before one verified single-variant; restarting "for cleanliness" when checkpoints are flowing; stopping a run to fix the launching script.
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