teleo-infrastructure/scripts/apply_worker.py
Fawaz 4de98b29fd
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feat(kb): apply-worker — auto-land approved proposals (stage 2 automation) (#36)
* feat(kb): apply-worker to auto-land approved proposals (stage 2 automation)

Event-driven worker that turns a HUMAN-approved kb_stage proposal into canonical
state, so an approval in Telegram surfaces in Leo's identity without Leo applying
its own work.

- Fires only on status='approved' (never pending_review) -> proposer != applier
  holds; the human approval stays the trigger. No auto-approve anywhere.
- Reuses scripts/apply_proposal.py verbatim as the sole apply path (same txn,
  rowcount=1 guard, FK stamp). Connects as the narrow kb_apply role, never
  superuser, never inside the hermes harness.
- Render hook (--render-cmd / KB_APPLY_RENDER_CMD) is inert until the SOUL
  renderer (PR2) is deployed; applying still works, rendered SOUL just lags.
- Ships INERT: report-only unless --enable / KB_APPLY_WORKER_ENABLED=1. systemd
  oneshot service + 5min timer, both shipped disabled.
- 10 unit tests; candidate query validated read-only vs prod (0 applyable today).

* fix(kb): apply-worker --max-per-tick cap + poison-pill retry ceiling

Fixer draft-exit items:
- --max-per-tick=1 (default): an enabled worker lands applies one-at-a-time
  and observably instead of draining the whole approved queue in one tick.
- --max-attempts=3 ceiling with a persisted failure-count state file: a
  deterministically-failing approved proposal is treated as a poison pill and
  skipped after N consecutive failures, instead of retrying every tick forever.
  State persists on disk because the worker runs oneshot per timer tick.

Both are inert until the worker is enabled; it still ships disabled.
2026-07-05 18:23:56 -04:00

303 lines
13 KiB
Python

#!/usr/bin/env python3
"""Event-driven worker that lands human-approved proposals into canonical state.
Stage 2-of-the-loop automation: Leo proposes -> HUMAN approves -> WORKER applies
-> renderer runs -> Leo reads the new self.
This is the "natural evolution" engine: it makes an approval in Telegram surface
in Leo's identity without Leo ever applying its own work. It does NOT think, does
NOT approve, and does NOT create proposals -- it only acts on proposals a human
has already moved to ``status='approved'``.
Governance boundary (why this is safe)
--------------------------------------
* Proposer != applier. The worker fires ONLY on ``status='approved'``; it never
touches ``pending_review`` and never auto-approves. The human approval stays the
trigger, so "Leo proposes but does not self-apply" holds.
* It connects as the narrow ``kb_apply`` role (never superuser, never Leo's creds)
and reuses ``apply_proposal.py`` verbatim as the apply path -- same transaction,
same ``rowcount=1`` concurrency guard, same FK stamp. No new write logic here.
* It runs as an operator-side systemd unit, NOT inside the hermes harness.
Safety posture
--------------
* Gated OFF by default. Without ``--enable`` (or ``KB_APPLY_WORKER_ENABLED=1``) the
worker only REPORTS what it would apply -- it performs no writes. Flip it on only
after the first apply has been proven by hand.
* The render step is a configurable hook (``--render-cmd`` / ``KB_APPLY_RENDER_CMD``).
Until the SOUL renderer (PR2) is deployed the hook is simply absent and the worker
logs that render was skipped -- applying still works, Leo's canonical is correct,
and the rendered SOUL.md just lags until the renderer exists.
"""
from __future__ import annotations
import argparse
import json
import os
import subprocess
import sys
from pathlib import Path
from typing import Any, Dict, List, Optional
HERE = Path(__file__).resolve().parent
sys.path.insert(0, str(HERE))
import apply_proposal as ap # noqa: E402 (sibling module, reused verbatim)
# Types the worker is willing to auto-apply. Deliberately the same set the engine
# supports; a proposal type outside this list is ignored (never applied).
WORKER_TYPES = ("revise_strategy", "add_edge", "attach_evidence")
# Only a revise_strategy changes an agent's identity spine, so only it triggers a
# SOUL re-render. Evidence/edge applies change the graph but not the rendered self.
RENDER_TYPES = ("revise_strategy",)
# --------------------------------------------------------------------------- #
# Pure helpers (unit-tested without a DB) #
# --------------------------------------------------------------------------- #
def build_candidate_query(types: tuple = WORKER_TYPES, limit: int = 20) -> str:
"""SELECT approved, applyable proposals that carry an apply_payload.
Filters on status='approved' at the DB level -- this is the structural
guarantee that the worker cannot act on anything a human has not approved.
"""
type_list = ", ".join(ap.sql_literal(t) for t in types)
return f"""select jsonb_build_object(
'id', id::text,
'proposal_type', proposal_type,
'agent_id', payload->'apply_payload'->>'agent_id')::text
from kb_stage.kb_proposals
where status = 'approved'
and proposal_type in ({type_list})
and payload ? 'apply_payload'
order by created_at asc
limit {int(limit)};"""
def parse_candidates(psql_output: str) -> List[Dict[str, Any]]:
"""Parse newline-delimited JSON rows from psql -At output."""
rows: List[Dict[str, Any]] = []
for line in psql_output.splitlines():
line = line.strip()
if line:
rows.append(json.loads(line))
return rows
def build_render_command(render_cmd: Optional[str], agent_id: Optional[str]) -> Optional[List[str]]:
"""Expand the render-hook template for one agent, or None if no hook configured.
``render_cmd`` is a shell-word template, e.g. ``python3 render_soul.py --agent-id {agent_id}``.
Returns a token list ready for subprocess, or None when unset (render skipped).
"""
if not render_cmd:
return None
if not agent_id:
return None
import shlex
return [tok.format(agent_id=agent_id) for tok in shlex.split(render_cmd)]
def load_failure_state(path: Optional[str]) -> Dict[str, int]:
"""Load the persisted {proposal_id: consecutive_failure_count} map.
The worker runs oneshot per timer tick, so in-memory failure counts do not
survive between ticks. A poison-pill proposal (deterministically failing but
stuck at 'approved') would otherwise be re-selected and re-attempted every
tick forever. Persisting the count on disk lets the ceiling actually bite.
Missing/corrupt file -> empty map (fail open to "no known failures").
"""
if not path:
return {}
p = Path(path)
if not p.is_file():
return {}
try:
data = json.loads(p.read_text(encoding="utf-8"))
return {str(k): int(v) for k, v in data.items()} if isinstance(data, dict) else {}
except Exception: # noqa: BLE001 -- a bad state file must never wedge the worker
return {}
def save_failure_state(path: Optional[str], state: Dict[str, int]) -> None:
if not path:
return
p = Path(path)
p.parent.mkdir(parents=True, exist_ok=True)
p.write_text(json.dumps(state, sort_keys=True), encoding="utf-8")
def partition_candidates(
candidates: List[Dict[str, Any]],
failure_counts: Dict[str, int],
max_attempts: int,
max_per_tick: int,
) -> Dict[str, List[Dict[str, Any]]]:
"""Split fetched candidates into what to apply now vs. skip.
- ``poisoned``: already at/over the failure ceiling -> never re-attempted,
surfaced loudly for the operator (needs a human fix, not another retry).
- ``to_apply``: the first ``max_per_tick`` non-poisoned candidates -> capped
so an enabled worker lands applies one-at-a-time and observably, rather
than draining the whole approved queue in a single unobserved tick.
"""
poisoned = [c for c in candidates if failure_counts.get(c["id"], 0) >= max_attempts]
eligible = [c for c in candidates if failure_counts.get(c["id"], 0) < max_attempts]
return {"poisoned": poisoned, "to_apply": eligible[: max(0, max_per_tick)]}
# --------------------------------------------------------------------------- #
# Side-effecting steps #
# --------------------------------------------------------------------------- #
def _psql_args(args: argparse.Namespace) -> argparse.Namespace:
"""Namespace shaped for ap.run_psql (reuses the kb_apply connection path)."""
return argparse.Namespace(
container=args.container, db=args.db, host=args.host, role=args.role
)
def fetch_candidates(args: argparse.Namespace, password: str) -> List[Dict[str, Any]]:
sql = build_candidate_query(limit=args.limit)
out = ap.run_psql(_psql_args(args), sql, password)
return parse_candidates(out)
def apply_one(args: argparse.Namespace, proposal_id: str) -> None:
"""Apply via the audited apply_proposal.py CLI -- same txn + rowcount guard."""
cmd = [
sys.executable, str(args.apply_script), proposal_id,
"--applied-by", args.applied_by,
"--secrets-file", args.secrets_file,
"--container", args.container, "--db", args.db,
"--host", args.host, "--role", args.role,
]
result = subprocess.run(cmd, text=True, capture_output=True, check=False)
if result.returncode != 0:
raise RuntimeError(
f"apply failed for {proposal_id}: {result.stdout.strip()} {result.stderr.strip()}"
)
def render_one(args: argparse.Namespace, agent_id: Optional[str]) -> str:
cmd = build_render_command(args.render_cmd, agent_id)
if cmd is None:
return "render skipped (no render-cmd configured; PR2 renderer not deployed)"
result = subprocess.run(cmd, text=True, capture_output=True, check=False)
if result.returncode != 0:
raise RuntimeError(
f"render failed for agent {agent_id}: {result.stdout.strip()} {result.stderr.strip()}"
)
return f"rendered agent {agent_id}"
# --------------------------------------------------------------------------- #
# Main #
# --------------------------------------------------------------------------- #
def run(args: argparse.Namespace) -> int:
password = ap.load_password(args.secrets_file)
candidates = fetch_candidates(args, password)
if not candidates:
print("no approved+applyable proposals; nothing to do")
return 0
failure_counts = load_failure_state(args.failure_state_file)
split = partition_candidates(candidates, failure_counts, args.max_attempts, args.max_per_tick)
for c in split["poisoned"]:
print(
f"SKIP poison-pill {c['id']} ({c['proposal_type']}): failed "
f"{failure_counts.get(c['id'], 0)}x >= max-attempts {args.max_attempts}; "
f"needs a human fix, not another retry",
file=sys.stderr,
)
enabled = args.enable or os.environ.get("KB_APPLY_WORKER_ENABLED") == "1"
if not enabled:
print(
f"[report-only] worker disabled; {len(split['to_apply'])} proposal(s) would apply "
f"this tick (cap {args.max_per_tick}):"
)
for c in split["to_apply"]:
print(f" would apply {c['id']} ({c['proposal_type']}) agent={c.get('agent_id')}")
print("enable with --enable or KB_APPLY_WORKER_ENABLED=1 after the first manual apply is proven")
return 0
failures = 0
for c in split["to_apply"]:
pid, ptype, agent_id = c["id"], c["proposal_type"], c.get("agent_id")
try:
apply_one(args, pid)
failure_counts.pop(pid, None) # success clears any prior failure count
print(f"applied {pid} ({ptype})")
if ptype in RENDER_TYPES:
print(" " + render_one(args, agent_id))
except Exception as exc: # noqa: BLE001 -- one bad proposal must not stop the batch
failures += 1
# Leave the proposal at 'approved' so a fixed one reapplies next tick
# (the rowcount=1 guard makes reapply safe), but bump its failure count
# so a deterministically-failing proposal hits the ceiling instead of
# retrying forever. Surface loudly for the operator.
failure_counts[pid] = failure_counts.get(pid, 0) + 1
print(f"ERROR applying {pid} ({ptype}) [attempt {failure_counts[pid]}/"
f"{args.max_attempts}]: {exc}", file=sys.stderr)
save_failure_state(args.failure_state_file, failure_counts)
return 1 if failures else 0
def parse_args(argv: List[str]) -> argparse.Namespace:
p = argparse.ArgumentParser(
description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
)
p.add_argument(
"--enable", action="store_true",
help="actually apply (default: report-only). Also honored via KB_APPLY_WORKER_ENABLED=1.",
)
p.add_argument("--limit", type=int, default=20, help="max candidates fetched per tick")
p.add_argument(
"--max-per-tick", type=int, default=1,
help="max proposals actually APPLIED per tick (default 1: applies land "
"one-at-a-time and observably, not a whole-queue drain)",
)
p.add_argument(
"--max-attempts", type=int, default=3,
help="consecutive apply failures before a proposal is treated as a "
"poison pill and skipped (needs a human fix, not endless retries)",
)
p.add_argument(
"--failure-state-file",
default=os.environ.get("KB_APPLY_WORKER_STATE", "/opt/teleo-eval/logs/kb-apply-worker-failures.json"),
help="persisted per-proposal failure counts (survives oneshot ticks so "
"the poison-pill ceiling actually bites)",
)
p.add_argument(
"--applied-by", default=ap.SERVICE_AGENT_HANDLE,
help="handle recorded as applied_by (default: the kb-apply service agent)",
)
p.add_argument(
"--apply-script", default=str(HERE / "apply_proposal.py"),
help="path to the apply_proposal.py engine (the sole apply path)",
)
p.add_argument(
"--render-cmd", default=os.environ.get("KB_APPLY_RENDER_CMD", ""),
help="render hook template, e.g. 'python3 render_soul.py --agent-id {agent_id}'. "
"Empty (default) skips render until the SOUL renderer is deployed.",
)
p.add_argument("--secrets-file", default=ap.DEFAULT_SECRETS_FILE)
p.add_argument("--container", default=ap.DEFAULT_CONTAINER)
p.add_argument("--db", default=ap.DEFAULT_DB)
p.add_argument("--host", default=ap.DEFAULT_HOST)
p.add_argument("--role", default=ap.DEFAULT_ROLE)
return p.parse_args(argv)
def main(argv: Optional[List[str]] = None) -> int:
return run(parse_args(sys.argv[1:] if argv is None else argv))
if __name__ == "__main__":
raise SystemExit(main())