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f4533f6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 | """Validate and execute a YAML-defined doc2harness run.
A run must name an executable production backend in ``executor.command`` (or
through ``SBH_PRODUCTION_EXECUTOR``); there is no built-in stand-in that would
let a misconfigured run look like it scored something. ``--dry-run`` validates
the complete plan and writes no model result; without it, each configured model
is invoked through the declared executor, respecting the configured concurrency
limit.
"""
from __future__ import annotations
import argparse
import json
import os
import shlex
import subprocess
import sys
from concurrent.futures import ThreadPoolExecutor, as_completed
from pathlib import Path
from typing import Any
class RunConfigError(ValueError):
"""Raised when a run configuration is incomplete or unsafe."""
def _load_yaml(path: Path) -> dict[str, Any]:
try:
import yaml # type: ignore[import-not-found]
except ImportError as exc: # pragma: no cover - environment dependent
raise RunConfigError(
"PyYAML is required for YAML run configs; install the run requirements"
) from exc
try:
value = yaml.safe_load(path.read_text(encoding="utf-8"))
except (OSError, yaml.YAMLError) as exc:
raise RunConfigError(f"cannot read YAML config {path}: {exc}") from exc
if not isinstance(value, dict):
raise RunConfigError("top-level YAML value must be a mapping")
return value
def _mapping(value: Any, name: str) -> dict[str, Any]:
if not isinstance(value, dict):
raise RunConfigError(f"{name} must be a mapping")
return value
def _nonempty_string(value: Any, name: str) -> str:
if not isinstance(value, str) or not value.strip():
raise RunConfigError(f"{name} must be a non-empty string")
return value.strip()
def _repo_path(repo_root: Path, value: Any, name: str) -> Path:
raw = Path(_nonempty_string(value, name)).expanduser()
return raw if raw.is_absolute() else repo_root / raw
def _catalog_ids(repo_root: Path) -> tuple[str, ...]:
from doc2harness.benchmark.catalog import (
load_catalog_sources,
parse_catalog_root,
)
package = repo_root / "src" / "doc2harness"
benchmark = package / "benchmark"
root = parse_catalog_root((benchmark / "catalog_root.toml").read_bytes())
resources = {
root.taxonomy_resource: (benchmark / "taxonomy.toml").read_bytes(),
**{
shard.resource: (package / Path(*shard.resource.segments)).read_bytes()
for shard in root.shards
},
}
definitions = load_catalog_sources(
root,
resources,
lambda module, export: __import__(module, fromlist=[export]).__dict__[export],
)
return tuple(item.scenario_id for item in definitions)
def _expand(value: str) -> str:
return os.path.expandvars(value)
def _command(executor: dict[str, Any], *, allow_missing: bool) -> list[str]:
configured = executor.get("command")
if configured is None or configured == []:
env_command = os.environ.get("SBH_PRODUCTION_EXECUTOR", "").strip()
if not env_command:
if allow_missing:
return []
raise RunConfigError(
"executor.command is missing; set a production executor explicitly "
"(SBH_PRODUCTION_EXECUTOR may provide one)"
)
configured = shlex.split(env_command)
if isinstance(configured, str):
configured = shlex.split(configured)
if not isinstance(configured, list) or not configured or not all(
isinstance(item, str) and item.strip() for item in configured
):
raise RunConfigError("executor.command must be a non-empty string/list command")
return [_expand(item) for item in configured]
def _validate(
repo_root: Path,
config_path: Path,
document: dict[str, Any],
required_models: tuple[str, ...] = (),
required_count: int | None = None,
) -> dict[str, Any]:
if document.get("schema") != "doc2harness.run-config/1":
raise RunConfigError("schema must be doc2harness.run-config/1")
run = _mapping(document.get("run"), "run")
selection = _mapping(document.get("selection"), "selection")
executor = _mapping(document.get("executor"), "executor")
models_value = document.get("models")
if not isinstance(models_value, list) or not models_value:
raise RunConfigError("models must be a non-empty list")
catalog = _catalog_ids(repo_root)
requested = selection.get("mode", "all")
if requested == "all":
selected = catalog
elif requested == "ids_file":
ids_file = _repo_path(repo_root, selection.get("ids_file"), "selection.ids_file")
try:
selected = tuple(
line.strip()
for line in ids_file.read_text(encoding="utf-8").splitlines()
if line.strip() and not line.lstrip().startswith("#")
)
except OSError as exc:
raise RunConfigError(f"cannot read selection.ids_file: {ids_file}") from exc
else:
raise RunConfigError("selection.mode must be all or ids_file")
if not selected or len(selected) != len(set(selected)):
raise RunConfigError("selection must contain unique non-empty scenario IDs")
if required_count is not None and len(selected) != required_count:
raise RunConfigError(
f"selection must contain exactly {required_count} scenario IDs, found {len(selected)}"
)
unknown = sorted(set(selected) - set(catalog))
if unknown:
raise RunConfigError(f"selection contains unknown scenario IDs: {unknown[:5]}")
if required_models:
names = tuple(_nonempty_string(_mapping(item, "model").get("id"), "model.id") for item in models_value)
if names != required_models:
raise RunConfigError(f"models must be exactly {list(required_models)}, found {list(names)}")
command = _command(executor, allow_missing=bool(document.get("_dry_run")))
output_dir = _repo_path(repo_root, run.get("output_dir", "run-results"), "run.output_dir")
if not output_dir.is_relative_to(repo_root):
raise RunConfigError("run.output_dir must remain inside the repository")
concurrency = run.get("concurrency", 1)
if type(concurrency) is not int or concurrency < 1:
raise RunConfigError("run.concurrency must be a positive integer")
return {
"repo_root": str(repo_root),
"config_path": str(config_path),
"run": run,
"selection": {"mode": requested, "count": len(selected), "ids": selected},
"models": models_value,
"executor": {"command": command, "output_dir": str(output_dir)},
}
def _execute(plan: dict[str, Any], *, dry_run: bool) -> int:
output_dir = Path(plan["executor"]["output_dir"])
output_dir.mkdir(parents=True, exist_ok=True)
manifest = output_dir / "run-plan.json"
manifest.write_text(json.dumps(plan, ensure_ascii=False, indent=2) + "\n", encoding="utf-8")
selection_file = output_dir / "selected-scenarios.txt"
selection_file.write_text(
"".join(f"{scenario_id}\n" for scenario_id in plan["selection"]["ids"]),
encoding="utf-8",
)
if dry_run:
print(json.dumps({"status": "VALID", "selection_count": plan["selection"]["count"], "models": [item["id"] for item in plan["models"]]}, ensure_ascii=False))
return 0
command = plan["executor"]["command"]
if not command:
raise RunConfigError(
"no production executor configured; set executor.command or "
"SBH_PRODUCTION_EXECUTOR before a real run"
)
def run_model(model: Any) -> tuple[str, int]:
model_map = _mapping(model, "model")
model_id = _nonempty_string(model_map.get("id"), "model.id")
environment = os.environ.copy()
environment.update(
{
str(key): _expand(str(value))
for key, value in _mapping(model_map.get("env", {}), "model.env").items()
}
)
environment["SBH_RUN_CONFIG"] = plan["config_path"]
environment["SBH_MODEL_ID"] = model_id
environment["SBH_SCENARIO_COUNT"] = str(plan["selection"]["count"])
environment["SBH_IDS_FILE"] = str(selection_file)
environment["SBH_RUN_OUTPUT_DIR"] = plan["executor"]["output_dir"]
environment["SBH_CATALOG_CONCURRENCY"] = str(
plan["run"].get("catalog_concurrency", 1)
)
environment["SBH_CATALOG_TIMEOUT"] = str(
plan["run"].get("catalog_timeout", 900)
)
print(
f"[doc2harness] starting model={model_id} "
f"scenarios={plan['selection']['count']}",
flush=True,
)
result = subprocess.run(command, cwd=Path(plan["repo_root"]), env=environment, check=False)
return model_id, result.returncode
concurrency = min(int(plan["run"].get("concurrency", 1)), len(plan["models"]))
with ThreadPoolExecutor(max_workers=concurrency) as pool:
futures = [pool.submit(run_model, model) for model in plan["models"]]
for future in as_completed(futures):
model_id, returncode = future.result()
if returncode != 0:
print(
f"[doc2harness] executor failed model={model_id} rc={returncode}",
file=sys.stderr,
)
return returncode
print(json.dumps({"status": "COMPLETED", "selection_count": plan["selection"]["count"], "models": [item["id"] for item in plan["models"]]}, ensure_ascii=False))
return 0
def main() -> int:
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--repo-root", type=Path, required=True)
parser.add_argument("--config", type=Path, required=True)
parser.add_argument("--dry-run", action="store_true")
parser.add_argument("--require-models", default="")
parser.add_argument("--require-count", type=int)
args = parser.parse_args()
try:
repo_root = args.repo_root.resolve()
config_path = args.config.resolve()
sys.path.insert(0, str(repo_root / "src"))
document = _load_yaml(config_path)
document["_dry_run"] = args.dry_run
plan = _validate(
repo_root,
config_path,
document,
tuple(item for item in args.require_models.split(",") if item),
args.require_count,
)
return _execute(plan, dry_run=args.dry_run)
except (OSError, RunConfigError, ImportError) as exc:
print(f"error[SBH-RUN-CONFIG]: {exc}", file=sys.stderr)
return 4
if __name__ == "__main__":
raise SystemExit(main())
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