scripts/analyze_quality.py

#!/usr/bin/env python3
from __future__ import annotations

import argparse
import json
import re
from collections import Counter
from pathlib import Path
from typing import Any


def read_jsonl(path: Path) -> list[dict[str, Any]]:
    rows: list[dict[str, Any]] = []
    if not path.exists():
        return rows
    with path.open("r", encoding="utf-8") as handle:
        for line in handle:
            line = line.strip()
            if line:
                rows.append(json.loads(line))
    return rows


def word_count(text: Any) -> int:
    return len(re.findall(r"\b[\w'-]+\b", str(text)))


def avg(values: list[float]) -> float:
    return sum(values) / len(values) if values else 0.0


def main() -> None:
    parser = argparse.ArgumentParser(description="Summarize LifeStreamingCoT v0.4 quality metrics.")
    parser.add_argument("--data-dir", default="life_streaming_cot_dataset")
    args = parser.parse_args()

    data_dir = Path(args.data_dir) / "data"
    rows = read_jsonl(data_dir / "train.jsonl") + read_jsonl(data_dir / "eval.jsonl")
    hq_rows = read_jsonl(data_dir / "train_high_quality.jsonl") + read_jsonl(data_dir / "eval_high_quality.jsonl")
    total_chunks = sum(row.get("num_chunks", 0) for row in rows)
    skip_chunks = sum(len(row.get("skip_chunks", [])) for row in rows)

    print("Quality analysis")
    print(f"total rows: {len(rows)}")
    print(f"high-quality rows: {len(hq_rows)}")
    print(f"domains: {dict(sorted(Counter(row.get('domain') for row in rows).items()))}")
    print(f"quality flags: {dict(sorted(Counter(flag for row in rows for flag in row.get('quality_flags', [])).items()))}")
    print(f"average quality_score: {avg([float(row.get('quality_score', 0)) for row in rows]):.3f}")
    print(f"average streaming words: {avg([word_count(row.get('streaming_reasoning', '')) for row in rows]):.2f}")
    print(f"average deep words: {avg([word_count(row.get('deep_reasoning', '')) for row in rows]):.2f}")
    print(f"skip ratio: {skip_chunks / total_chunks if total_chunks else 0:.4f}")
    print(f"llm_augmented rows: {sum(1 for row in rows if row.get('llm_augmented'))}")


if __name__ == "__main__":
    main()