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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)
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3 changed files with 55 additions and 46 deletions
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@ -14,7 +14,8 @@ OUT="$(mktemp)"
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# --- the repo's run command (auto-detected) --------------------------------
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# Edit this line if the campaign should run something different.
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( python3 "$ATLAS_OPTIMIZE_TARGET" ) >"$OUT" 2>&1
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TARGET="${ATLAS_OPTIMIZE_TARGET:-$1}"
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( python3 "$TARGET" ) >"$OUT" 2>&1
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RC=$?
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# ---------------------------------------------------------------------------
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@ -8,7 +8,7 @@
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# rewrites tracked files (checkpoints, logs, and .atlas/ are already ignored).
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set -uo pipefail
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WT="${1:-$PWD}"
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TARGET="${2:-${ATLAS_OPTIMIZE_TARGET:-}}"
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TARGET="${ATLAS_OPTIMIZE_TARGET:-$2}"
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REL="${TARGET#"$WT"/}"
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IGNORE_RE='^(outputs/|out/|checkpoints/|runs/|wandb/|\.atlas/|.*\.log$|.*\.ckpt$|.*\.pt$|.*\.bin$|.*\.safetensors$)'
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CHANGED="$(git -C "$WT" status --porcelain --untracked-files=no 2>/dev/null \
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@ -1,65 +1,73 @@
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#!/usr/bin/env python3
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"""Generated by `atlas autoresearch`. Parse one metric out of a run's output
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into the Atlas benchmark contract.
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EDIT the METRIC line if the wrong number is being read, or rewrite parse() for
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a richer evaluator (per-example feedback is what makes GEPA converge — see
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.atlas/benchmark-contract or the atlas-optimize skill)."""
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import argparse
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import json
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import os
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import re
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import sys
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# autoresearch guessed this metric name from your --goal.
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METRIC = "find_optimal_crossing" # <-- EDIT ME if this is the wrong metric
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HIGHER_IS_BETTER = False
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# Matches "<metric> = 0.74", "<metric>: 0.74", "<metric> 0.74".
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PATTERN = re.compile(
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re.escape(METRIC) + r"\s*[:=]?\s*([+-]?[0-9]*\.?[0-9]+(?:[eE][+-]?[0-9]+)?)"
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)
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import argparse, json, os, re, sys
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METRICS = {
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"find_optimal_crossing": False,
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"SA direct": False,
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}
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def parse(text):
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matches = PATTERN.findall(text)
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if not matches:
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return None
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return float(matches[-1]) # last occurrence == final epoch / final eval
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results = {}
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for name, higher in METRICS.items():
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pat = re.compile(re.escape(name) + r"\s*[:=]?\s*([+-]?[0-9]*\.?[0-9]+)")
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for m in pat.finditer(text):
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raw = m.group(0).strip()
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val = float(m.group(1))
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line_before = text[max(0, m.start()-80):m.start()].split("\n")[-1].strip()
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results[name] = (val, higher, raw, line_before)
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return results
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def main():
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ap = argparse.ArgumentParser()
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ap.add_argument("--stdout", required=True, help="file holding the run's captured output")
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ap.add_argument("--stdout", required=True)
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args = ap.parse_args()
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text = open(args.stdout, encoding="utf-8", errors="replace").read()
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score = parse(text)
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if score is None:
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sys.stderr.write(
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f"[score] could not find metric '{METRIC}' in the run output.\n"
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" Fix: edit .atlas/score.py (METRIC=...), or pass an explicit\n"
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" --benchmark to 'atlas autoresearch'.\n"
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)
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parsed = parse(text)
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if "find_optimal_crossing" not in parsed:
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sys.stderr.write(f"[score] could not find metric in output.\n")
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sys.exit(3)
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direction = "higher is better" if HIGHER_IS_BETTER else "lower is better"
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primary_name = "find_optimal_crossing"
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primary_val, _, primary_raw, ctx = parsed[primary_name]
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direction = "lower is better"
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examples = [{
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"id": primary_name,
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"score": primary_val,
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"pass": True,
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"feedback": f"{primary_raw} | context: {ctx}" if ctx else primary_raw,
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}]
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if "SA direct" in parsed:
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sa_val, _, sa_raw, sa_ctx = parsed["SA direct"]
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examples.append({
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"id": "SA direct",
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"score": sa_val,
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"pass": sa_val < 100,
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"feedback": f"{sa_raw} | context: {sa_ctx}" if sa_ctx else sa_raw,
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})
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diag_lines = []
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for line in text.strip().split("\n"):
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stripped = line.strip()
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if "find_optimal_crossing" in stripped or "SA direct" in stripped:
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diag_lines.append(stripped)
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diagnostic = "; ".join(diag_lines) if diag_lines else primary_raw
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result = {
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"score": score,
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"examples": [{
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"id": METRIC,
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"score": score,
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"pass": True,
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"feedback": f"{METRIC} = {score} (parsed from run output; {direction})",
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}],
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"feedback": f"Final {METRIC} = {score}.",
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"score": primary_val,
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"examples": examples,
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"feedback": f"find_optimal_crossing={primary_val} ({direction}) | {diagnostic}",
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}
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out = os.environ.get("ATLAS_OPTIMIZE_RESULT")
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payload = json.dumps(result)
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if out:
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with open(out, "w", encoding="utf-8") as fh:
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with open(out, "w") as fh:
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fh.write(payload)
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else:
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sys.stdout.write(payload)
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if __name__ == "__main__":
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main()
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