Datasets:
Download bench/bench.py from WithinUsAI/Genesis_AI_Code_100k: direct link, hf CLI and curl.
- Browser
- Download file 4.93 kB
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https://huggingface.co/datasets/WithinUsAI/Genesis_AI_Code_100k/resolve/main/bench/bench.py
- Command line
-
hf download hf://datasets/WithinUsAI/Genesis_AI_Code_100k/bench/bench.py
-
curl -L -o bench.py https://huggingface.co/datasets/WithinUsAI/Genesis_AI_Code_100k/resolve/main/bench/bench.py
4.93 kB
| \ | |
| #!/usr/bin/env python3 | |
| from __future__ import annotations | |
| import argparse | |
| import json | |
| from pathlib import Path | |
| from typing import Any, Dict, Iterable, Tuple | |
| REQUIRED_FIELDS = {"id","created","topic","task_type","difficulty","instruction","input","output","metadata","hash"} | |
| def iter_jsonl(path: Path, max_rows: int | None) -> Iterable[Dict[str, Any]]: | |
| n = 0 | |
| with path.open("r", encoding="utf-8") as f: | |
| for line in f: | |
| line = line.strip() | |
| if not line: | |
| continue | |
| try: | |
| obj = json.loads(line) | |
| except Exception: | |
| yield {"__parse_error__": True} | |
| n += 1 | |
| if max_rows and n >= max_rows: | |
| return | |
| continue | |
| yield obj | |
| n += 1 | |
| if max_rows and n >= max_rows: | |
| return | |
| def is_tool_trace_valid(out: Any) -> bool: | |
| # Accept either a parsed list OR a JSON string representing a list | |
| if isinstance(out, str): | |
| s = out.strip() | |
| if not s: | |
| return False | |
| try: | |
| out = json.loads(s) | |
| except Exception: | |
| return False | |
| if not isinstance(out, list) or len(out) == 0: | |
| return False | |
| for step in out: | |
| if not isinstance(step, dict): | |
| return False | |
| if "tool" not in step or "args" not in step: | |
| return False | |
| if not isinstance(step["tool"], str) or not isinstance(step["args"], dict): | |
| return False | |
| return True | |
| def is_patch_diff_valid(out: Any) -> bool: | |
| if not isinstance(out, str): | |
| return False | |
| s = out.strip() | |
| if "```diff" in s: | |
| # fenced diff | |
| return ("-" in s and "+" in s) | |
| # also allow plain diff-like strings | |
| return s.startswith("-") or s.startswith("diff") or ("- " in s and "+ " in s) | |
| def is_self_grade_valid(out: Any) -> bool: | |
| if isinstance(out, str): | |
| try: | |
| out = json.loads(out) | |
| except Exception: | |
| return False | |
| if not isinstance(out, dict): | |
| return False | |
| score = out.get("score") | |
| conf = out.get("confidence") | |
| notes = out.get("notes") | |
| if not (isinstance(score, int) and 0 <= score <= 10): | |
| return False | |
| if not (isinstance(conf, (int, float)) and 0.0 <= float(conf) <= 1.0): | |
| return False | |
| if not (isinstance(notes, str) and len(notes) >= 3): | |
| return False | |
| return True | |
| def main() -> int: | |
| ap = argparse.ArgumentParser(description="Genesis AI Code Bench (Within Us AI)") | |
| ap.add_argument("--jsonl", required=True, help="Path to JSONL file") | |
| ap.add_argument("--max_rows", type=int, default=5000) | |
| args = ap.parse_args() | |
| path = Path(args.jsonl) | |
| total = 0 | |
| format_valid = 0 | |
| required_ok = 0 | |
| tool_ok = tool_total = 0 | |
| diff_ok = diff_total = 0 | |
| grade_ok = grade_total = 0 | |
| gov_ok = 0 | |
| econ_ok = 0 | |
| hashes = set() | |
| hash_total = 0 | |
| for obj in iter_jsonl(path, args.max_rows): | |
| total += 1 | |
| if obj.get("__parse_error__"): | |
| continue | |
| format_valid += 1 | |
| keys = set(obj.keys()) | |
| if REQUIRED_FIELDS.issubset(keys): | |
| required_ok += 1 | |
| # hash / uniqueness | |
| h = obj.get("hash") | |
| if isinstance(h, str) and h: | |
| hash_total += 1 | |
| hashes.add(h) | |
| # governance + economics (metadata) | |
| md = obj.get("metadata", {}) | |
| if isinstance(md, dict): | |
| if md.get("audit_required") is True: | |
| gov_ok += 1 | |
| if isinstance(md.get("cost_budget"), int) and isinstance(md.get("latency_ms_target"), int): | |
| econ_ok += 1 | |
| # task-specific validity | |
| task = obj.get("task_type") | |
| out = obj.get("output") | |
| if task == "tool_trace": | |
| tool_total += 1 | |
| if is_tool_trace_valid(out): | |
| tool_ok += 1 | |
| elif task == "patch_diff": | |
| diff_total += 1 | |
| if is_patch_diff_valid(out): | |
| diff_ok += 1 | |
| elif task == "self_grade": | |
| grade_total += 1 | |
| if is_self_grade_valid(out): | |
| grade_ok += 1 | |
| def rate(num: int, den: int) -> float: | |
| return 0.0 if den == 0 else round(num / den, 4) | |
| report = { | |
| "rows_scanned": total, | |
| "format_valid_rate": rate(format_valid, total), | |
| "required_fields_rate": rate(required_ok, total), | |
| "tool_trace_valid_rate": rate(tool_ok, tool_total), | |
| "patch_diff_valid_rate": rate(diff_ok, diff_total), | |
| "self_grade_valid_rate": rate(grade_ok, grade_total), | |
| "governance_present_rate": rate(gov_ok, total), | |
| "economics_present_rate": rate(econ_ok, total), | |
| "uniqueness_rate": rate(len(hashes), hash_total), | |
| } | |
| print(json.dumps(report, indent=2)) | |
| return 0 | |
| if __name__ == "__main__": | |
| raise SystemExit(main()) | |