fix(optimize): add TARGET fallback + enrich score feedback for GEPA
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benchmark.sh: fall back to  when ATLAS_OPTIMIZE_TARGET unset
score.py: track find_optimal_crossing and SA direct as separate
  scorecard examples with diagnostic context for reflector
gate.sh: add positional-arg fallback for ATLAS_OPTIMIZE_TARGET

Build: N/A (config & Python shims only)
This commit is contained in:
allaun 2026-07-07 00:49:07 -05:00
parent 006e8b1876
commit 180bf43cce
3 changed files with 55 additions and 46 deletions

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@ -14,7 +14,8 @@ OUT="$(mktemp)"
# --- the repo's run command (auto-detected) --------------------------------
# Edit this line if the campaign should run something different.
( python3 "$ATLAS_OPTIMIZE_TARGET" ) >"$OUT" 2>&1
TARGET="${ATLAS_OPTIMIZE_TARGET:-$1}"
( python3 "$TARGET" ) >"$OUT" 2>&1
RC=$?
# ---------------------------------------------------------------------------

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@ -8,7 +8,7 @@
# rewrites tracked files (checkpoints, logs, and .atlas/ are already ignored).
set -uo pipefail
WT="${1:-$PWD}"
TARGET="${2:-${ATLAS_OPTIMIZE_TARGET:-}}"
TARGET="${ATLAS_OPTIMIZE_TARGET:-$2}"
REL="${TARGET#"$WT"/}"
IGNORE_RE='^(outputs/|out/|checkpoints/|runs/|wandb/|\.atlas/|.*\.log$|.*\.ckpt$|.*\.pt$|.*\.bin$|.*\.safetensors$)'
CHANGED="$(git -C "$WT" status --porcelain --untracked-files=no 2>/dev/null \

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@ -1,65 +1,73 @@
#!/usr/bin/env python3
"""Generated by `atlas autoresearch`. Parse one metric out of a run's output
into the Atlas benchmark contract.
EDIT the METRIC line if the wrong number is being read, or rewrite parse() for
a richer evaluator (per-example feedback is what makes GEPA converge see
.atlas/benchmark-contract or the atlas-optimize skill)."""
import argparse
import json
import os
import re
import sys
# autoresearch guessed this metric name from your --goal.
METRIC = "find_optimal_crossing" # <-- EDIT ME if this is the wrong metric
HIGHER_IS_BETTER = False
# Matches "<metric> = 0.74", "<metric>: 0.74", "<metric> 0.74".
PATTERN = re.compile(
re.escape(METRIC) + r"\s*[:=]?\s*([+-]?[0-9]*\.?[0-9]+(?:[eE][+-]?[0-9]+)?)"
)
import argparse, json, os, re, sys
METRICS = {
"find_optimal_crossing": False,
"SA direct": False,
}
def parse(text):
matches = PATTERN.findall(text)
if not matches:
return None
return float(matches[-1]) # last occurrence == final epoch / final eval
results = {}
for name, higher in METRICS.items():
pat = re.compile(re.escape(name) + r"\s*[:=]?\s*([+-]?[0-9]*\.?[0-9]+)")
for m in pat.finditer(text):
raw = m.group(0).strip()
val = float(m.group(1))
line_before = text[max(0, m.start()-80):m.start()].split("\n")[-1].strip()
results[name] = (val, higher, raw, line_before)
return results
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--stdout", required=True, help="file holding the run's captured output")
ap.add_argument("--stdout", required=True)
args = ap.parse_args()
text = open(args.stdout, encoding="utf-8", errors="replace").read()
score = parse(text)
if score is None:
sys.stderr.write(
f"[score] could not find metric '{METRIC}' in the run output.\n"
" Fix: edit .atlas/score.py (METRIC=...), or pass an explicit\n"
" --benchmark to 'atlas autoresearch'.\n"
)
parsed = parse(text)
if "find_optimal_crossing" not in parsed:
sys.stderr.write(f"[score] could not find metric in output.\n")
sys.exit(3)
direction = "higher is better" if HIGHER_IS_BETTER else "lower is better"
primary_name = "find_optimal_crossing"
primary_val, _, primary_raw, ctx = parsed[primary_name]
direction = "lower is better"
examples = [{
"id": primary_name,
"score": primary_val,
"pass": True,
"feedback": f"{primary_raw} | context: {ctx}" if ctx else primary_raw,
}]
if "SA direct" in parsed:
sa_val, _, sa_raw, sa_ctx = parsed["SA direct"]
examples.append({
"id": "SA direct",
"score": sa_val,
"pass": sa_val < 100,
"feedback": f"{sa_raw} | context: {sa_ctx}" if sa_ctx else sa_raw,
})
diag_lines = []
for line in text.strip().split("\n"):
stripped = line.strip()
if "find_optimal_crossing" in stripped or "SA direct" in stripped:
diag_lines.append(stripped)
diagnostic = "; ".join(diag_lines) if diag_lines else primary_raw
result = {
"score": score,
"examples": [{
"id": METRIC,
"score": score,
"pass": True,
"feedback": f"{METRIC} = {score} (parsed from run output; {direction})",
}],
"feedback": f"Final {METRIC} = {score}.",
"score": primary_val,
"examples": examples,
"feedback": f"find_optimal_crossing={primary_val} ({direction}) | {diagnostic}",
}
out = os.environ.get("ATLAS_OPTIMIZE_RESULT")
payload = json.dumps(result)
if out:
with open(out, "w", encoding="utf-8") as fh:
with open(out, "w") as fh:
fh.write(payload)
else:
sys.stdout.write(payload)
if __name__ == "__main__":
main()