168 lines
5.2 KiB
Python
168 lines
5.2 KiB
Python
"""Scorer: Weighted aggregate all judge scores → report"""
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import json, os
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from datetime import datetime
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import subprocess
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import numpy as np
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class NumpyEncoder(json.JSONEncoder):
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def default(self, obj):
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if isinstance(obj, (np.integer,)):
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return int(obj)
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if isinstance(obj, (np.floating,)):
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return float(obj)
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if isinstance(obj, (np.bool_,)):
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return bool(obj)
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if isinstance(obj, np.ndarray):
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return obj.tolist()
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return super().default(obj)
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OUTPUT_DIR = "/Users/accusys/momentry/output_dev"
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WEIGHTS = {
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"Gemma4": 0.35,
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"PaliGemma": 0.25,
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"YOLO": 0.15,
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"MaskFormer": 0.15,
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"GroundingDINO": 0.05,
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"FaceNet": 0.05,
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}
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def get_build_info():
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try:
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git_hash = subprocess.run(
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["git", "rev-parse", "--short", "HEAD"],
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capture_output=True, text=True, timeout=5,
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cwd=os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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).stdout.strip()
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except:
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git_hash = "unknown"
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return {
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"build_git_hash": git_hash,
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"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"version": "1.0.0"
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}
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def compute_scores(judge_results):
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"""Convert judge outputs to numeric scores."""
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scores = {}
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for jr in judge_results:
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agent = jr["agent"]
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s = jr.get("score")
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if s is None:
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s = 50 # default for non-numeric judges
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scores[agent] = s
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return scores
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def aggregate(scores):
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"""Weighted aggregate across all judges."""
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total_weight = 0
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weighted_sum = 0
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for agent, score in scores.items():
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w = WEIGHTS.get(agent, 0.1)
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if score is not None:
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weighted_sum += w * score
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total_weight += w
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return round(weighted_sum / total_weight) if total_weight > 0 else 0
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def generate_report(all_results, file_uuid):
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"""Generate qa_report.md + qa_report.json."""
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build = get_build_info()
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report_path = os.path.join(OUTPUT_DIR, "qa_report.md")
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json_path = os.path.join(OUTPUT_DIR, "qa_report.json")
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lines = []
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lines.append("# QA Self-Check Report")
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lines.append(f"")
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lines.append(f"**UUID**: `{file_uuid}`")
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lines.append(f"**Build**: {build['build_git_hash']}")
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lines.append(f"**Timestamp**: {build['timestamp']}")
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lines.append(f"**Version**: {build['version']}")
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lines.append("")
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lines.append("---")
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lines.append("")
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# Summary table
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total_queries = len(all_results)
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avg_scores = []
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by_type = {}
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for r in all_results:
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qtype = r["query"]["type"]
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qid = r["query"]["id"]
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# Collect all judge scores for this result
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scores = {}
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for jr in r.get("judge_results", []):
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s = jr.get("score")
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if s is not None:
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scores[jr["agent"]] = s
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final_score = aggregate(scores)
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avg_scores.append(final_score)
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by_type.setdefault(qtype, []).append(final_score)
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overall = round(sum(avg_scores) / len(avg_scores)) if avg_scores else 0
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lines.append("## Summary")
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lines.append("")
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lines.append(f"| Metric | Score |")
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lines.append(f"|--------|:----:|")
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lines.append(f"| **Overall** | **{overall}/100** |")
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for qtype in ["identity", "scene", "object"]:
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scores = by_type.get(qtype, [])
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if scores:
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avg = round(sum(scores) / len(scores))
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lines.append(f"| {qtype.capitalize()} queries | {avg}/100 |")
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lines.append("")
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# Per-query details
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lines.append("## Per-Query Details")
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lines.append("")
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for r in all_results:
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q = r["query"]
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lines.append(f"### {q['id']}: {q['prompt']}")
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lines.append(f"")
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lines.append(f"| Type: {q['type']} | Status: {r.get('status', 'ok')} |")
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lines.append(f"|-----------------|-------------------|")
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lines.append(f"")
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# Judges
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lines.append(f"| Judge | Score | Reasoning |")
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lines.append(f"|-------|:-----:|-----------|")
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for jr in r.get("judge_results", []):
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s = jr.get("score", "-")
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if s is None: s = "-"
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reasoning = jr.get("reasoning", "")[:80]
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lines.append(f"| {jr['agent']} | {s} | {reasoning} |")
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scores = {}
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for jr in r.get("judge_results", []):
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if jr.get("score") is not None:
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scores[jr["agent"]] = jr["score"]
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final = aggregate(scores)
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lines.append(f"| **Weighted** | **{final}** | |")
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lines.append(f"")
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lines.append("---")
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lines.append(f"*Report generated by M5 QA Agent — {build['timestamp']}*")
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report_text = "\n".join(lines)
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with open(report_path, "w") as f:
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f.write(report_text)
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# JSON output
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json_output = {
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"build": build,
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"file_uuid": file_uuid,
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"overall_score": overall,
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"by_type": {t: round(sum(s)/len(s)) for t, s in by_type.items() if s},
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"queries": all_results
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}
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with open(json_path, "w") as f:
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json.dump(json_output, f, indent=2, ensure_ascii=False, cls=NumpyEncoder)
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print(f"\n Report: {report_path}")
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print(f" JSON: {json_path}")
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print(f" Overall score: {overall}/100")
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