merge: testing → main (reconcile 2-week divergence)
This commit is contained in:
421
decnet/realism/bodies.py
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421
decnet/realism/bodies.py
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"""Per-content-class body generators (deterministic templates).
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Stage 3 of the realism migration ships deterministic per-class
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templates — varied enough that two notes on the same decky aren't
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identical, formulaic enough that system-class files (cron logs,
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journal entries) look like cron actually wrote them.
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Stage 6 wires LLM enrichment for user-classes; the templates here
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remain the fallback path so the orchestrator tick never blocks on
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Ollama.
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Determinism: every namer/body takes a :class:`SystemRandom` (from
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:mod:`secrets`). Tests pin the RNG seed for reproducibility; the
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orchestrator passes a fresh RNG per tick so production picks are
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unpredictable.
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The factory mirrors :mod:`decnet.realism.naming`: caller passes a
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:class:`~decnet.realism.taxonomy.ContentClass`; we return the body
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generator registered for it. Email + canary classes raise —
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those bodies come from the email driver and canary cultivator
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respectively, not from realism.bodies.
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"""
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from __future__ import annotations
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import asyncio
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import secrets
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from datetime import datetime, timezone
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from typing import Callable, Optional
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from decnet.logging import get_logger
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from decnet.realism.taxonomy import ContentClass
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log = get_logger("realism.bodies")
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# ── User-class body generators ─────────────────────────────────────────────
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_NOTE_TEMPLATES: tuple[str, ...] = (
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"follow up with the team on this",
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"remember to ping the on-call",
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"ask about the staging migration timeline",
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"double-check the runbook before next shift",
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"todo: rotate keys; check on backup task",
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"meeting notes from yesterday — copy onto wiki when free",
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"this is broken in prod; talk to ops monday",
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"draft response to the auditor — keep it short",
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)
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def _body_note(persona: str, rng: secrets.SystemRandom) -> str:
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n = rng.randint(2, 5)
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lines = rng.sample(_NOTE_TEMPLATES, k=min(n, len(_NOTE_TEMPLATES)))
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return "\n".join(lines) + "\n"
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_TODO_VERBS: tuple[str, ...] = (
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"rotate keys", "review pr",
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"clean up logs", "update docs",
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"follow up on ticket",
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"test backup restore",
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"deploy to staging",
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"ack auditor email",
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"patch CVE backlog",
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)
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def _body_todo(persona: str, rng: secrets.SystemRandom) -> str:
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n = rng.randint(3, 7)
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items = rng.sample(_TODO_VERBS, k=min(n, len(_TODO_VERBS)))
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# Roughly a third pre-checked — looks like a list that's been
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# touched at least once.
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out = []
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for item in items:
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marker = "[x]" if rng.random() < 0.33 else "[ ]"
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out.append(f"- {marker} {item}")
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return "\n".join(out) + "\n"
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_DRAFT_PARAGRAPHS: tuple[str, ...] = (
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"Hi team,\n\nQuick update on the project. We're tracking ahead of schedule "
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"on the migration but the staging soak revealed a regression in the "
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"auth path. I'll have a fix in by end of week.\n\nThanks,\n",
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"Hi,\n\nFollowing up on yesterday's meeting. Action items below:\n\n"
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"- Engineering owns the deployment plan\n"
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"- Ops will draft the runbook update\n"
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"- We sync again Friday\n\n",
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"All,\n\nProposal attached. Key points:\n\n"
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"1. We are not changing the data model in this release\n"
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"2. The new endpoint is opt-in via feature flag\n"
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"3. Rollback path is one config flip\n\n"
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"Feedback by EOD?\n\n",
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)
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def _body_draft(persona: str, rng: secrets.SystemRandom) -> str:
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return rng.choice(_DRAFT_PARAGRAPHS)
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_SCRIPT_TEMPLATES: tuple[str, ...] = (
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"#!/usr/bin/env bash\nset -euo pipefail\n\n"
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"BACKUP_DIR=/var/backups\n"
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"STAMP=$(date +%Y%m%d-%H%M)\n"
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"echo \"backup start $STAMP\"\n"
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"tar czf \"$BACKUP_DIR/db-$STAMP.tar.gz\" /var/lib/mysql\n"
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"echo \"backup done\"\n",
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"#!/usr/bin/env bash\nset -e\n\n"
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"# clean up old logs\n"
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"find /var/log -name '*.log.*.gz' -mtime +30 -delete\n",
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"#!/usr/bin/env python3\n\"\"\"Quick fix for the reporting job.\"\"\"\n"
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"import sys\n\n"
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"def main():\n print('todo: real fix here')\n\n"
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"if __name__ == '__main__':\n sys.exit(main())\n",
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)
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def _body_script(persona: str, rng: secrets.SystemRandom) -> str:
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return rng.choice(_SCRIPT_TEMPLATES)
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# ── System-class body generators ───────────────────────────────────────────
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_CRON_COMMANDS: tuple[str, ...] = (
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"(root) CMD (run-parts /etc/cron.daily)",
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"(root) CMD (run-parts /etc/cron.hourly)",
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"(www-data) CMD (cd /var/www && /usr/bin/php artisan schedule:run)",
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"(backup) CMD (/usr/local/bin/backup.sh)",
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"(root) CMD (test -x /usr/sbin/anacron || ( cd / && run-parts --report /etc/cron.daily ))",
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)
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def _body_log_cron(persona: str, rng: secrets.SystemRandom) -> str:
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n = rng.randint(8, 24)
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base = datetime.now(timezone.utc)
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lines = []
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for i in range(n):
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hour = (base.hour - i) % 24
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minute = rng.randint(0, 59)
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pid = rng.randint(1000, 99999)
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cmd = rng.choice(_CRON_COMMANDS)
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# ISO-ish "Apr 27 09:13:44 host CRON[1234]: ..." cron syslog shape.
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date_s = base.strftime("%b %d")
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lines.append(
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f"{date_s} {hour:02d}:{minute:02d}:{rng.randint(0,59):02d} "
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f"hostname CRON[{pid}]: {cmd}"
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)
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return "\n".join(lines) + "\n"
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_DAEMON_LINES: tuple[str, ...] = (
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"systemd[1]: Started Daily apt download activities.",
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"systemd[1]: apt-daily.service: Succeeded.",
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"systemd[1]: Reached target Multi-User System.",
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"kernel: [UFW BLOCK] IN=eth0 OUT= MAC=…",
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"sshd[2103]: pam_unix(sshd:session): session opened for user admin by (uid=0)",
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"sshd[2103]: Received disconnect from 10.0.0.4 port 47282:11: disconnected by user",
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"CRON[1894]: pam_unix(cron:session): session closed for user root",
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)
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def _body_log_daemon(persona: str, rng: secrets.SystemRandom) -> str:
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n = rng.randint(10, 30)
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lines = []
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base = datetime.now(timezone.utc)
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for _ in range(n):
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lines.append(
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f"{base.strftime('%b %d %H:%M:%S')} hostname "
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f"{rng.choice(_DAEMON_LINES)}"
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)
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return "\n".join(lines) + "\n"
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def _body_cache_tmp(persona: str, rng: secrets.SystemRandom) -> str:
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# ~64-256 bytes of opaque session-ish payload — most /tmp/.cache-*
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# files in the wild are short binary or k=v dumps. We emit ASCII
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# so docker exec write paths don't need binary-safety acrobatics.
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nbytes = rng.randint(64, 256)
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chars = "abcdefghijklmnopqrstuvwxyz0123456789"
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return "session=" + "".join(rng.choice(chars) for _ in range(nbytes)) + "\n"
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def _body_email(persona: str, rng: secrets.SystemRandom) -> str:
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raise NotImplementedError(
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"email bodies come from the email driver, not realism.bodies"
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)
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def _body_canary(persona: str, rng: secrets.SystemRandom) -> str:
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raise NotImplementedError(
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"canary bodies come from the canary cultivator (stage 7), "
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"not realism.bodies"
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)
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# ── Dispatch ───────────────────────────────────────────────────────────────
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_BODIES: dict[ContentClass, Callable[[str, secrets.SystemRandom], str]] = {
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ContentClass.NOTE: _body_note,
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ContentClass.TODO: _body_todo,
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ContentClass.DRAFT: _body_draft,
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ContentClass.SCRIPT: _body_script,
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ContentClass.LOG_CRON: _body_log_cron,
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ContentClass.LOG_DAEMON: _body_log_daemon,
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ContentClass.CACHE_TMP: _body_cache_tmp,
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ContentClass.EMAIL: _body_email,
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ContentClass.CANARY_AWS_CREDS: _body_canary,
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ContentClass.CANARY_ENV_FILE: _body_canary,
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ContentClass.CANARY_GIT_CONFIG: _body_canary,
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ContentClass.CANARY_SSH_KEY: _body_canary,
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ContentClass.CANARY_HONEYDOC: _body_canary,
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ContentClass.CANARY_HONEYDOC_DOCX: _body_canary,
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ContentClass.CANARY_HONEYDOC_PDF: _body_canary,
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ContentClass.CANARY_MYSQL_DUMP: _body_canary,
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}
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def make_body(
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content_class: ContentClass,
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persona: str,
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*,
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rand: Optional[secrets.SystemRandom] = None,
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) -> str:
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"""Return deterministic body bytes (utf-8 string) for *content_class*.
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Stage 3 ships templates only. :func:`make_body_with_llm` is the
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LLM-aware variant added in stage 6 — kept on a separate name so
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the deterministic path stays trivially callable from tests and
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from the LLM fallback itself.
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"""
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rng = rand or secrets.SystemRandom()
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gen = _BODIES.get(content_class)
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if gen is None:
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raise KeyError(
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f"no body generator registered for content_class={content_class!r}"
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)
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return gen(persona, rng)
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async def make_body_with_llm(
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content_class: ContentClass,
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persona, # EmailPersona — typed loosely to avoid an import cycle
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*,
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llm=None, # LLMBackend | None
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breaker=None, # LLMCircuitBreaker | None
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timeout: float = 60.0,
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rand: Optional[secrets.SystemRandom] = None,
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) -> str:
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"""LLM-enriched body for user-classes; deterministic fallback otherwise.
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Falls back to :func:`make_body` whenever:
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* ``llm`` is None,
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* ``breaker.allow_call()`` returns False (sustained failure),
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* the LLM call times out or returns empty,
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* the content class isn't a user-class (system-class content
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should look formulaic, so we never invoke LLM there).
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Em-dash stripping runs on the LLM output as a belt-and-braces
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guard (see :mod:`decnet.realism.prompts._style`). The function
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is async because LLM calls are; the deterministic path returns
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immediately so the orchestrator's tick doesn't pay async overhead
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when LLM is disabled.
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"""
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rng = rand or secrets.SystemRandom()
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# System / canary / email classes never touch the LLM.
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if not content_class.is_user_class():
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return make_body(content_class, persona.name, rand=rng)
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if llm is None or (breaker is not None and not breaker.allow_call()):
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return make_body(content_class, persona.name, rand=rng)
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# Lazy imports keep the prompt + style modules out of the
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# deterministic path's import graph.
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from decnet.realism.llm.base import LLMTimeout
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from decnet.realism.prompts import filebody as _filebody
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from decnet.realism.prompts._style import strip_em_dashes
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prompt = _filebody.build(content_class, persona)
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try:
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result = await asyncio.wait_for(llm.generate(prompt), timeout=timeout)
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except (LLMTimeout, asyncio.TimeoutError):
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log.debug("realism.bodies LLM timeout class=%s persona=%s",
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content_class.value, persona.name)
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if breaker is not None:
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breaker.record_failure()
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return make_body(content_class, persona.name, rand=rng)
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except Exception as exc: # noqa: BLE001
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log.warning("realism.bodies LLM error class=%s persona=%s: %s",
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content_class.value, persona.name, exc)
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if breaker is not None:
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breaker.record_failure()
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return make_body(content_class, persona.name, rand=rng)
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if not result.success or not result.text.strip():
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if breaker is not None:
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breaker.record_failure()
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return make_body(content_class, persona.name, rand=rng)
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if breaker is not None:
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breaker.record_success()
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return strip_em_dashes(result.text.rstrip() + "\n", persona)
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# ── Edit-in-place mutators ─────────────────────────────────────────────────
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# Stage 3b: deterministic per-class mutations. The contract: take the
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# previous body bytes, return a plausible *next* iteration (append a
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# line, flip a checkbox, fix a typo). Append-only for logs; small
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# in-place edits for user content. LLM enrichment in stage 6 wires
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# next_iteration to ask "what would <persona> write next" with the
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# previous body in the prompt; the deterministic path stays as the
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# fallback.
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def _edit_todo(
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prev: str, persona: str, rng: secrets.SystemRandom,
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) -> str:
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"""Flip an unchecked box, append a new item, or both.
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Real TODO files evolve: items get checked off as work happens, new
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items get added, occasionally a sub-bullet appears under an
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existing one. We pick one of those mutations per call.
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"""
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lines = prev.splitlines()
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unchecked_indices = [
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i for i, ln in enumerate(lines) if ln.startswith("- [ ]")
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]
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op = rng.choice(("flip", "append", "both") if unchecked_indices else ("append",))
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if op in ("flip", "both") and unchecked_indices:
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idx = rng.choice(unchecked_indices)
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lines[idx] = lines[idx].replace("- [ ]", "- [x]", 1)
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if op in ("append", "both"):
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new_item = rng.choice(_TODO_VERBS)
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marker = "[x]" if rng.random() < 0.15 else "[ ]"
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lines.append(f"- {marker} {new_item}")
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return "\n".join(lines) + ("" if prev.endswith("\n") else "\n")
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def _edit_note(
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prev: str, persona: str, rng: secrets.SystemRandom,
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) -> str:
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"""Append one new note line or insert a follow-up under an existing one."""
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new_line = rng.choice(_NOTE_TEMPLATES)
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if prev.endswith("\n"):
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return prev + new_line + "\n"
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return prev + "\n" + new_line + "\n"
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def _edit_draft(
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prev: str, persona: str, rng: secrets.SystemRandom,
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) -> str:
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"""Append a new short paragraph to the existing draft."""
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addition = (
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"\nFollow-up: I'll send the deck once finance signs off on the numbers.\n",
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"\nP.S.: Looping in ops on the rollout sequence — they have context I don't.\n",
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"\nLet me know if any of this needs another pass.\n",
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)
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return prev.rstrip() + "\n" + rng.choice(addition)
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def _edit_script(
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prev: str, persona: str, rng: secrets.SystemRandom,
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) -> str:
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"""Append a comment line — scripts evolve via comments and small fixes."""
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comments = (
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"# TODO: handle the empty-input case\n",
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"# 2026-04-27: hardened error path after the prod incident\n",
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"# noqa: shellcheck disagrees but this is what the runbook says\n",
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)
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return prev.rstrip() + "\n" + rng.choice(comments)
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def _edit_log_cron(
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prev: str, persona: str, rng: secrets.SystemRandom,
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) -> str:
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"""Append one new cron syslog line — logs only ever grow."""
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extra = _body_log_cron(persona, rng)
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return prev.rstrip() + "\n" + extra.splitlines()[-1] + "\n"
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def _edit_log_daemon(
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prev: str, persona: str, rng: secrets.SystemRandom,
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) -> str:
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extra = _body_log_daemon(persona, rng)
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return prev.rstrip() + "\n" + extra.splitlines()[-1] + "\n"
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_EDITORS: dict[ContentClass, Callable[[str, str, secrets.SystemRandom], str]] = {
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ContentClass.NOTE: _edit_note,
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ContentClass.TODO: _edit_todo,
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ContentClass.DRAFT: _edit_draft,
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ContentClass.SCRIPT: _edit_script,
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ContentClass.LOG_CRON: _edit_log_cron,
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ContentClass.LOG_DAEMON: _edit_log_daemon,
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}
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def next_iteration(
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content_class: ContentClass,
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persona: str,
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previous_body: str,
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*,
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rand: Optional[secrets.SystemRandom] = None,
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) -> str:
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"""Return the next-iteration body for an edit-in-place mutation.
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Raises :class:`KeyError` for content classes that don't support
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editing (canary blobs, cache-tmp scratch files, email). The
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planner filters those out before producing an :class:`EditAction`,
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so reaching this branch with an unsupported class is a bug worth
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surfacing loudly.
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"""
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rng = rand or secrets.SystemRandom()
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editor = _EDITORS.get(content_class)
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if editor is None:
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raise KeyError(
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f"content_class={content_class!r} does not support edits"
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)
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return editor(previous_body, persona, rng)
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Block a user