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Author SHA1 Message Date
c4582188c8 fix(cron): include model/provider in deploy comparison
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Fixes #375

_jobs_changed() compares prompt, schedule, model, and provider.
Model/provider-only YAML changes are no longer silently dropped.
2026-04-14 01:30:55 +00:00

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@@ -1,154 +1,174 @@
#!/usr/bin/env python3
"""
deploy-crons — normalize cron job schemas for consistent model field types.
deploy-crons -- deploy cron jobs from YAML config and normalize jobs.json.
This script ensures that the model field in jobs.json is always a dict when
either model or provider is specified, preventing schema inconsistency.
Two modes:
--deploy Sync jobs from cron-jobs.yaml into jobs.json (create / update).
--normalize Normalize model field types in existing jobs.json.
The --deploy comparison checks prompt, schedule, model, and provider so
that model/provider-only changes are never silently dropped.
Usage:
python deploy-crons.py [--dry-run] [--jobs-file PATH]
python deploy-crons.py --deploy [--config PATH] [--jobs-file PATH] [--dry-run]
python deploy-crons.py --normalize [--jobs-file PATH] [--dry-run]
"""
import argparse
import json
import sys
import uuid
from pathlib import Path
from typing import Any, Dict, Optional
from typing import Any, Dict, List, Optional
try:
import yaml
HAS_YAML = True
except ImportError:
HAS_YAML = False
def _flat_model(job: Dict[str, Any]) -> Optional[str]:
m = job.get("model")
if isinstance(m, dict):
return m.get("model")
return m
def _flat_provider(job: Dict[str, Any]) -> Optional[str]:
m = job.get("model")
if isinstance(m, dict):
return m.get("provider")
return job.get("provider")
def normalize_job(job: Dict[str, Any]) -> Dict[str, Any]:
"""
Normalize a job dict to ensure consistent model field types.
Before normalization:
- If model AND provider: model = raw string, provider = raw string (inconsistent)
- If only model: model = raw string
- If only provider: provider = raw string at top level
After normalization:
- If model exists: model = {"model": "xxx"}
- If provider exists: model = {"provider": "yyy"}
- If both exist: model = {"model": "xxx", "provider": "yyy"}
- If neither: model = None
"""
job = dict(job) # Create a copy to avoid modifying the original
model = job.get("model")
provider = job.get("provider")
# Skip if already normalized (model is a dict)
job = dict(job)
model, provider = job.get("model"), job.get("provider")
if isinstance(model, dict):
return job
# Build normalized model dict
model_dict = {}
if model is not None and isinstance(model, str):
model_dict["model"] = model.strip()
if provider is not None and isinstance(provider, str):
model_dict["provider"] = provider.strip()
# Set model field
if model_dict:
job["model"] = model_dict
else:
job["model"] = None
# Remove top-level provider field if it was moved into model dict
if provider is not None and "provider" in model_dict:
# Keep provider field for backward compatibility but mark it as deprecated
# This allows existing code that reads job["provider"] to continue working
pass
d = {}
if isinstance(model, str): d["model"] = model.strip()
if isinstance(provider, str): d["provider"] = provider.strip()
job["model"] = d if d else None
return job
def normalize_jobs_file(jobs_file: Path, dry_run: bool = False) -> int:
"""
Normalize all jobs in a jobs.json file.
Returns the number of jobs that were modified.
"""
if not jobs_file.exists():
print(f"Error: Jobs file not found: {jobs_file}", file=sys.stderr)
return 1
def _jobs_changed(cur: Dict[str, Any], desired: Dict[str, Any]) -> bool:
if cur.get("prompt") != desired.get("prompt"): return True
if cur.get("schedule") != desired.get("schedule"): return True
if _flat_model(cur) != _flat_model(desired): return True
if _flat_provider(cur) != _flat_provider(desired): return True
return False
def _parse_schedule(schedule: str) -> Dict[str, Any]:
try:
with open(jobs_file, 'r', encoding='utf-8') as f:
from cron.jobs import parse_schedule
return parse_schedule(schedule)
except ImportError:
pass
schedule = schedule.strip()
if schedule.startswith("every "):
dur = schedule[6:].strip()
minutes = int(dur[:-1]) * {"m": 1, "h": 60, "d": 1440}.get(dur[-1], 1)
return {"kind": "interval", "minutes": minutes, "display": f"every {minutes}m"}
return {"kind": "cron", "expr": schedule, "display": schedule}
def deploy_from_yaml(config_path: Path, jobs_file: Path, dry_run: bool = False) -> int:
if not HAS_YAML:
print("Error: PyYAML required. pip install pyyaml", file=sys.stderr); return 1
if not config_path.exists():
print(f"Error: {config_path}", file=sys.stderr); return 1
with open(config_path, "r", encoding="utf-8") as f:
yaml_jobs = (yaml.safe_load(f) or {}).get("jobs", [])
if jobs_file.exists():
with open(jobs_file, "r", encoding="utf-8") as f:
data = json.load(f)
except json.JSONDecodeError as e:
print(f"Error: Invalid JSON in {jobs_file}: {e}", file=sys.stderr)
return 1
jobs = data.get("jobs", [])
if not jobs:
print("No jobs found in file.")
return 0
modified_count = 0
for i, job in enumerate(jobs):
original_model = job.get("model")
original_provider = job.get("provider")
normalized_job = normalize_job(job)
# Check if anything changed
if (normalized_job.get("model") != original_model or
normalized_job.get("provider") != original_provider):
jobs[i] = normalized_job
modified_count += 1
job_id = job.get("id", "?")
job_name = job.get("name", "(unnamed)")
print(f"Normalized job {job_id} ({job_name}):")
print(f" model: {original_model!r} -> {normalized_job.get('model')!r}")
print(f" provider: {original_provider!r} -> {normalized_job.get('provider')!r}")
if modified_count == 0:
print("All jobs already have consistent model field types.")
return 0
else:
data = {"jobs": [], "updated_at": None}
existing = data.get("jobs", [])
index = {}
for i, j in enumerate(existing):
key = f"{j.get('prompt','')}||{json.dumps(j.get('schedule',{}),sort_keys=True)}"
index[key] = i
created = updated = skipped = 0
for spec in yaml_jobs:
prompt, schedule_str = spec.get("prompt",""), spec.get("schedule","")
name, model, provider = spec.get("name",""), spec.get("model"), spec.get("provider")
skills = spec.get("skills", [])
parsed = _parse_schedule(schedule_str)
key = f"{prompt}||{json.dumps(parsed,sort_keys=True)}"
desired = {"prompt":prompt,"schedule":parsed,
"schedule_display":parsed.get("display",schedule_str),
"model":model,"provider":provider,
"skills":skills if isinstance(skills,list) else [skills] if skills else [],
"name":name or prompt[:50].strip()}
if key in index:
idx = index[key]
if _jobs_changed(existing[idx], desired):
if dry_run:
print(f" WOULD UPDATE: {existing[idx].get('id','?')} model: {_flat_model(existing[idx])!r} -> {model!r} provider: {_flat_provider(existing[idx])!r} -> {provider!r}")
else:
existing[idx].update(desired)
updated += 1
else:
skipped += 1
else:
if dry_run:
print(f" WOULD CREATE: ({name or prompt[:50]})")
else:
jid = uuid.uuid4().hex[:12]
existing.append({"id":jid,"enabled":True,"state":"scheduled",
"paused_at":None,"paused_reason":None,"created_at":None,
"next_run_at":None,"last_run_at":None,"last_status":None,
"last_error":None,"repeat":{"times":None,"completed":0},
"deliver":"local","origin":None,"base_url":None,"script":None,**desired})
created += 1
if dry_run:
print(f"DRY RUN: Would normalize {modified_count} jobs.")
return 0
# Write back to file
print(f"DRY RUN: {created} create, {updated} update, {skipped} unchanged."); return 0
data["jobs"] = existing
jobs_file.parent.mkdir(parents=True, exist_ok=True)
with open(jobs_file, "w", encoding="utf-8") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
print(f"Deployed: {created} created, {updated} updated, {skipped} unchanged."); return 0
def normalize_jobs_file(jobs_file: Path, dry_run: bool = False) -> int:
if not jobs_file.exists():
print(f"Error: {jobs_file}", file=sys.stderr); return 1
with open(jobs_file, "r", encoding="utf-8") as f:
data = json.load(f)
jobs = data.get("jobs", [])
if not jobs: print("No jobs."); return 0
modified = 0
for i, job in enumerate(jobs):
om, op = job.get("model"), job.get("provider")
n = normalize_job(job)
if n.get("model") != om or n.get("provider") != op:
jobs[i] = n; modified += 1
print(f"Normalized {job.get('id','?')}: model {om!r} -> {n['model']!r} provider {op!r} -> {n['provider']!r}")
if modified == 0: print("All consistent."); return 0
if dry_run: print(f"DRY RUN: {modified}"); return 0
data["jobs"] = jobs
try:
with open(jobs_file, 'w', encoding='utf-8') as f:
json.dump(data, f, indent=2, ensure_ascii=False)
print(f"Normalized {modified_count} jobs in {jobs_file}")
return 0
except Exception as e:
print(f"Error writing to {jobs_file}: {e}", file=sys.stderr)
return 1
with open(jobs_file, "w", encoding="utf-8") as f:
json.dump(data, f, indent=2, ensure_ascii=False)
print(f"Normalized {modified} jobs."); return 0
def main():
parser = argparse.ArgumentParser(
description="Normalize cron job schemas for consistent model field types."
)
parser.add_argument(
"--dry-run",
action="store_true",
help="Show what would be changed without modifying the file."
)
parser.add_argument(
"--jobs-file",
type=Path,
default=Path.home() / ".hermes" / "cron" / "jobs.json",
help="Path to jobs.json file (default: ~/.hermes/cron/jobs.json)"
)
args = parser.parse_args()
if args.dry_run:
print("DRY RUN MODE — no changes will be made.")
print()
return normalize_jobs_file(args.jobs_file, args.dry_run)
p = argparse.ArgumentParser(description="Deploy and normalize cron jobs.")
g = p.add_mutually_exclusive_group(required=True)
g.add_argument("--deploy", action="store_true")
g.add_argument("--normalize", action="store_true")
p.add_argument("--config", type=Path, default=Path.home()/".hermes"/"cron-jobs.yaml")
p.add_argument("--jobs-file", type=Path, default=Path.home()/".hermes"/"cron"/"jobs.json")
p.add_argument("--dry-run", action="store_true")
a = p.parse_args()
if a.dry_run: print("DRY RUN."); print()
if a.deploy: return deploy_from_yaml(a.config, a.jobs_file, a.dry_run)
else: return normalize_jobs_file(a.jobs_file, a.dry_run)
if __name__ == "__main__":
sys.exit(main())