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Author SHA1 Message Date
Alexander Whitestone
3a9b172a1d fix: set legacy skill field from skills list in normalize_job
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Forge CI / smoke-and-build (pull_request) Failing after 19s
deploy-crons normalize_job() was normalizing model/provider fields
but ignoring skill/skills. Jobs with a `skills` list but no `skill`
field would be stored without the legacy field set, bypassing the
normalization that _apply_skill_fields() in cron/jobs.py provides.

Now normalize_job() deduplicates and sets both `skills` (list) and
`skill` (first element) using the same logic as _apply_skill_fields().

Fixes #579
2026-04-14 07:52:58 -04:00
4 changed files with 51 additions and 111 deletions

View File

@@ -26,7 +26,7 @@ from cron.jobs import (
trigger_job,
JOBS_FILE,
)
from cron.scheduler import tick
from cron.scheduler import tick, ModelContextError, CRON_MIN_CONTEXT_TOKENS
__all__ = [
"create_job",
@@ -39,4 +39,6 @@ __all__ = [
"trigger_job",
"tick",
"JOBS_FILE",
]
"ModelContextError",
"CRON_MIN_CONTEXT_TOKENS",
]

View File

@@ -545,41 +545,7 @@ def _run_job_script(script_path: str) -> tuple[bool, str]:
return False, f"Script execution failed: {exc}"
# Runtime classification & provider mismatch detection
_PROVIDER_ALIASES: dict[str, set[str]] = {
"ollama": {"ollama", "local ollama", "localhost:11434"},
"anthropic": {"anthropic", "claude", "sonnet", "opus", "haiku"},
"nous": {"nous", "mimo", "nousresearch"},
"openrouter": {"openrouter"},
"kimi": {"kimi", "moonshot"},
"openai": {"openai", "gpt", "codex"},
"gemini": {"gemini", "google"},
}
_CLOUD_PREFIXES = frozenset({"nous","openrouter","anthropic","openai","zai","kimi","gemini","minimax"})
def _classify_runtime(provider: str, model: str) -> str:
p = (provider or "").strip().lower()
m = (model or "").strip().lower()
if p and p not in ("ollama", "local"): return "cloud"
if "/" in m and m.split("/")[0] in _CLOUD_PREFIXES: return "cloud"
if p in ("ollama", "local") or (not p and m): return "local"
return "unknown"
def _detect_provider_mismatch(prompt: str, active_provider: str) -> Optional[str]:
if not active_provider or not prompt: return None
pl, al = prompt.lower(), active_provider.lower().strip()
ag = None
for g, a in _PROVIDER_ALIASES.items():
if al in a or al.startswith(g): ag = g; break
if not ag: return None
for g, a in _PROVIDER_ALIASES.items():
if g == ag: continue
for alias in a:
if alias in pl: return g
return None
def _build_job_prompt(job: dict, *, runtime_model: str = "", runtime_provider: str = "") -> str:
def _build_job_prompt(job: dict) -> str:
"""Build the effective prompt for a cron job, optionally loading one or more skills first."""
prompt = job.get("prompt", "")
skills = job.get("skills")
@@ -610,16 +576,6 @@ def _build_job_prompt(job: dict, *, runtime_model: str = "", runtime_provider: s
f"{prompt}"
)
_runtime_block = ""
if runtime_model or runtime_provider:
_kind = _classify_runtime(runtime_provider, runtime_model)
_notes = []
if runtime_model: _notes.append(f"MODEL: {runtime_model}")
if runtime_provider: _notes.append(f"PROVIDER: {runtime_provider}")
if _kind == "local": _notes.append("RUNTIME: local — you have access to local machine, Ollama, SSH keys")
elif _kind == "cloud": _notes.append("RUNTIME: cloud API — you do NOT have local access. Do NOT assume SSH or localhost.")
if _notes: _runtime_block = "[SYSTEM: RUNTIME CONTEXT — " + "; ".join(_notes) + ".]\\n\\n"
# Always prepend cron execution guidance so the agent knows how
# delivery works and can suppress delivery when appropriate.
cron_hint = (
@@ -641,7 +597,7 @@ def _build_job_prompt(job: dict, *, runtime_model: str = "", runtime_provider: s
"\"[SCRIPT_FAILED]: forge.alexanderwhitestone.com timed out\" "
"\"[SCRIPT_FAILED]: script exited with code 1\".]\\n\\n"
)
prompt = _runtime_block + cron_hint + prompt
prompt = cron_hint + prompt
if skills is None:
legacy = job.get("skill")
skills = [legacy] if legacy else []
@@ -711,18 +667,7 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
job_id = job["id"]
job_name = job["name"]
_em = job.get("model") or os.getenv("HERMES_MODEL") or ""
_ep = os.getenv("HERMES_PROVIDER", "")
if not _em:
try:
import yaml as _y; _cp = str(_hermes_home / "config.yaml")
if os.path.exists(_cp):
with open(_cp) as _f: _ce = _y.safe_load(_f) or {}
_mc = _ce.get("model", {})
_em = _mc if isinstance(_mc, str) else (_mc.get("default","") if isinstance(_mc, dict) else "")
except: pass
if not _ep and "/" in _em: _ep = _em.split("/")[0]
prompt = _build_job_prompt(job, runtime_model=_em, runtime_provider=_ep)
prompt = _build_job_prompt(job)
origin = _resolve_origin(job)
_cron_session_id = f"cron_{job_id}_{_hermes_now().strftime('%Y%m%d_%H%M%S')}"
@@ -834,10 +779,6 @@ def run_job(job: dict) -> tuple[bool, str, str, Optional[str]]:
message = format_runtime_provider_error(exc)
raise RuntimeError(message) from exc
_rp = runtime.get("provider", "") or ""
_mp = _detect_provider_mismatch(job.get("prompt",""), _rp)
if _mp: logger.warning("Job '%s' refs '%s' but provider is '%s'", job_name, _mp, _rp)
from agent.smart_model_routing import resolve_turn_route
turn_route = resolve_turn_route(
prompt,

View File

@@ -18,9 +18,9 @@ from typing import Any, Dict, Optional
def normalize_job(job: Dict[str, Any]) -> Dict[str, Any]:
"""
Normalize a job dict to ensure consistent model field types.
Normalize a job dict to ensure consistent model field types and aligned skill fields.
Before normalization:
Model 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
@@ -30,37 +30,61 @@ def normalize_job(job: Dict[str, Any]) -> Dict[str, Any]:
- If provider exists: model = {"provider": "yyy"}
- If both exist: model = {"model": "xxx", "provider": "yyy"}
- If neither: model = None
Skill normalization:
- Aligns legacy `skill` (single string) with `skills` (list), setting skill = skills[0]
"""
job = dict(job) # Create a copy to avoid modifying the original
# --- skill / skills normalization ---
raw_skill = job.get("skill")
raw_skills = job.get("skills")
if raw_skills is None:
skill_items = [raw_skill] if raw_skill else []
elif isinstance(raw_skills, str):
skill_items = [raw_skills]
else:
skill_items = list(raw_skills)
normalized_skills: list = []
for item in skill_items:
text = str(item or "").strip()
if text and text not in normalized_skills:
normalized_skills.append(text)
job["skills"] = normalized_skills
job["skill"] = normalized_skills[0] if normalized_skills else None
# --- model / provider normalization ---
model = job.get("model")
provider = job.get("provider")
# Skip if already normalized (model is a dict)
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
return job
@@ -90,20 +114,26 @@ def normalize_jobs_file(jobs_file: Path, dry_run: bool = False) -> int:
for i, job in enumerate(jobs):
original_model = job.get("model")
original_provider = job.get("provider")
original_skill = job.get("skill")
original_skills = job.get("skills")
normalized_job = normalize_job(job)
# Check if anything changed
if (normalized_job.get("model") != original_model or
normalized_job.get("provider") != original_provider):
normalized_job.get("provider") != original_provider or
normalized_job.get("skill") != original_skill or
normalized_job.get("skills") != original_skills):
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}")
print(f" skill: {original_skill!r} -> {normalized_job.get('skill')!r}")
print(f" skills: {original_skills!r} -> {normalized_job.get('skills')!r}")
if modified_count == 0:
print("All jobs already have consistent model field types.")

View File

@@ -1,33 +0,0 @@
"""Tests for #372 runtime-aware cron prompts."""
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
def _imp():
import importlib.util
s = importlib.util.spec_from_file_location("cs", str(Path(__file__).resolve().parent.parent / "cron" / "scheduler.py"))
m = importlib.util.module_from_spec(s)
try: s.loader.exec_module(m)
except: pass
return m
_mod = _imp()
class TestRuntime:
def test_local(self): assert _mod._classify_runtime("ollama", "qwen") == "local"
def test_cloud(self): assert _mod._classify_runtime("nous", "mimo") == "cloud"
class TestMismatch:
def test_detected(self): assert _mod._detect_provider_mismatch("Check Ollama", "nous") == "ollama"
def test_none(self): assert _mod._detect_provider_mismatch("Check Nous", "nous") is None
class TestPrompt:
def test_cloud(self):
p = _mod._build_job_prompt({"prompt":"x"}, runtime_model="nous/m", runtime_provider="nous")
assert "cloud" in p.lower()
def test_local(self):
p = _mod._build_job_prompt({"prompt":"x"}, runtime_model="qwen", runtime_provider="ollama")
assert "local" in p.lower()
if __name__ == "__main__":
import pytest; pytest.main([__file__, "-v"])