davide
85ae95bf8d
Nuovi check bloccanti: - prefisso malformato ([ senza ] o contenuto vuoto) - corpo vuoto dopo prefisso valido Nuovi warning: - tabelle Markdown senza riga separatore |---| - chunk con corpo identico (duplicati da overlap/merge) Output migliorato: - istogramma ASCII con marcatori ← MIN / ← MAX - top 5 sezioni per volume di chunk - mediana (p50) nelle statistiche di lunghezza report.json arricchito: p50_chars, sections, malformed_prefix, body_empty, broken_tables, duplicate_bodies. PUNCT_END esteso con \d[\d.,/]*$ per numeri, anni, riferimenti normativi. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
482 lines
19 KiB
Python
482 lines
19 KiB
Python
#!/usr/bin/env python3
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"""
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Verifica chunk
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Analizza chunks/<stem>/chunks.json e segnala ogni anomalia che potrebbe
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degradare la qualità del retrieval. Non modifica nulla.
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Input: chunks/<stem>/chunks.json
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Output: report a schermo + chunks/<stem>/report.json + exit code (0 = OK, 1 = problemi)
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Uso:
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python chunks/verify_chunks.py --stem documento
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python chunks/verify_chunks.py # tutti i documenti in chunks/
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python chunks/verify_chunks.py --min 200 --max 800
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"""
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import argparse
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import json
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import re
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import sys
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from collections import Counter
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from pathlib import Path
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_HERE = Path(__file__).resolve().parent
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if str(_HERE) not in sys.path:
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sys.path.insert(0, str(_HERE))
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import config as cfg
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# ─── Soglie ───────────────────────────────────────────────────────────────────
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MIN_CHARS = cfg.MIN_CHARS
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MAX_CHARS = cfg.MAX_CHARS
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PUNCT_END = re.compile(
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r"[.!?\xbb)\]'’\"“”‘—–…]$"
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r"|/$" # URL che finisce con /
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r"|\|$" # riga di tabella Markdown
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r"|;$" # fine clausola legale
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r"|:$" # introduzione a lista o formula
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r"|\d[\d.,/]*$" # numero, anno, versione, riferimento normativo
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)
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_HEX_END = re.compile(r"[0-9a-fA-F]{8,}$")
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_URL_TAIL = re.compile(r"(https?://|www\.)\S+(\s+\S+){0,3}$")
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_MATH_SYMS = re.compile(r"[∈∑≤≥≠∀∃∫√∞∂±×÷→←↔⊂⊃⊆⊇∩∪·°]")
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_ROMAN_END = re.compile(r"\b(I{1,3}|IV|VI{0,3}|IX|XI{0,2}|XIV|XV|XVI{0,2}|XIX|XX{0,2})$")
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_TABLE_SEP = re.compile(r"^\s*\|[\s\-|:]+\|\s*$")
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def _load_thresholds(stem_dir: Path) -> tuple[int, int]:
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meta = stem_dir / "meta.json"
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if meta.exists():
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m = json.loads(meta.read_text(encoding="utf-8"))
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return m["min_chars"], m["max_chars"]
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return MIN_CHARS, MAX_CHARS
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def _strip_prefix(text: str) -> str:
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text = text.lstrip()
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if text.startswith("["):
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end = text.find("]")
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if end != -1:
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return text[end + 1:].lstrip("\n")
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return text
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# ─── Checks ───────────────────────────────────────────────────────────────────
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def is_empty(chunk: dict) -> bool:
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return not chunk.get("text", "").strip()
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def has_prefix(chunk: dict) -> bool:
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return chunk.get("text", "").lstrip().startswith("[")
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def is_prefix_malformed(chunk: dict) -> bool:
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"""Inizia con [ ma il prefisso non chiude con ] o ha contenuto vuoto."""
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text = chunk.get("text", "").lstrip()
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if not text.startswith("["):
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return False
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first_line = text.split("\n")[0]
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end = first_line.find("]")
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if end == -1:
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return True
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return len(first_line[1:end].strip()) == 0
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def is_body_empty(chunk: dict) -> bool:
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"""Prefisso valido ma nessun testo nel corpo."""
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text = chunk.get("text", "").lstrip()
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if not text.startswith("["):
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return False
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end = text.find("]")
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if end == -1:
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return False
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return len(text[end + 1:].strip()) == 0
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def is_too_short(chunk: dict, min_chars: int) -> bool:
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return chunk.get("n_chars", 0) < min_chars
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def is_too_long(chunk: dict, max_chars: int) -> bool:
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return chunk.get("n_chars", 0) > max_chars
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def ends_incomplete(chunk: dict) -> bool:
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text = chunk.get("text", "").rstrip()
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if not text:
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return False
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text_check = re.sub(r"[_*]+$", "", text).rstrip()
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if not text_check:
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return False
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if PUNCT_END.search(text_check):
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return False
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if _HEX_END.search(text_check):
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return False
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if _ROMAN_END.search(text_check):
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return False
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if _URL_TAIL.search(text_check[-200:]):
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return False
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return True
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def is_math_incomplete(chunk: dict) -> bool:
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return ends_incomplete(chunk) and len(_MATH_SYMS.findall(chunk.get("text", ""))) >= cfg.MATH_SYMS_MIN
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def is_table_broken(chunk: dict) -> bool:
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"""Tabella Markdown (≥2 righe con |) senza riga separatore |---|."""
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text = chunk.get("text", "")
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pipe_lines = [l for l in text.splitlines() if "|" in l and l.strip().startswith("|")]
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if len(pipe_lines) < 2:
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return False
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return not any(_TABLE_SEP.match(l) for l in pipe_lines)
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def find_duplicate_bodies(chunks: list[dict]) -> list[dict]:
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"""Chunk con testo body identico (prefisso escluso). Ignora corpi < 30 char."""
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seen: dict[str, str] = {}
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dupes = []
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for c in chunks:
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body = _strip_prefix(c.get("text", "")).strip()
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if len(body) < 30:
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continue
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cid = c["chunk_id"]
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if body in seen:
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dupes.append({
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"chunk_id": cid,
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"duplicate_of": seen[body],
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"sezione": c.get("sezione", ""),
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"titolo": c.get("titolo", ""),
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"n_chars": c.get("n_chars", 0),
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"last_text": body[:120],
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})
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else:
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seen[body] = cid
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return dupes
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# ─── Istogramma ───────────────────────────────────────────────────────────────
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def _ascii_histogram(lengths: list[int], min_t: int, max_t: int,
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n_bins: int = 10, bar_width: int = 28) -> list[str]:
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if not lengths:
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return []
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lo, hi = min(lengths), max(lengths)
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if lo == hi:
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return [f" {lo:>5}–{hi:<5} │{'█' * bar_width}│ {len(lengths)}"]
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step = (hi - lo) / n_bins
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bins = [0] * n_bins
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for l in lengths:
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idx = min(int((l - lo) / step), n_bins - 1)
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bins[idx] += 1
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max_count = max(bins) or 1
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lines = []
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for i, count in enumerate(bins):
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lo_b = int(lo + i * step)
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hi_b = int(lo + (i + 1) * step)
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bar = "█" * round(count / max_count * bar_width)
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note = ""
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if lo_b <= min_t < hi_b:
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note = " ← MIN"
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elif lo_b <= max_t < hi_b:
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note = " ← MAX"
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lines.append(f" {lo_b:>5}–{hi_b:<5} │{bar:<{bar_width}}│ {count}{note}")
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return lines
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# ─── Helpers output ───────────────────────────────────────────────────────────
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def _fmt_chunk(c: dict) -> str:
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cid = c.get("chunk_id", "?")
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n = c.get("n_chars", 0)
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preview = c.get("text", "")[:60].replace("\n", " ")
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return f" [{cid}] ({n} char) «{preview}»"
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def _chunk_entry(c: dict) -> dict:
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return {
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"chunk_id": c.get("chunk_id", ""),
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"sezione": c.get("sezione", ""),
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"titolo": c.get("titolo", ""),
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"n_chars": c.get("n_chars", 0),
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"last_text": c.get("text", "").rstrip().split("\n")[-1][-120:],
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}
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def _print_list(items: list[dict], limit: int = 5) -> None:
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for c in items[:limit]:
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print(_fmt_chunk(c))
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if len(items) > limit:
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print(f" ... e altri {len(items) - limit}")
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# ─── Core ─────────────────────────────────────────────────────────────────────
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def verify_stem(stem: str, project_root: Path, min_chars: int, max_chars: int) -> bool:
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stem_dir = project_root / "chunks" / stem
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chunks_path = stem_dir / "chunks.json"
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min_chars, max_chars = _load_thresholds(stem_dir)
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print(f"\nDocumento: {stem}")
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if not chunks_path.exists():
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print(f" ✗ chunks/{stem}/chunks.json non trovato")
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print(f" Esegui prima: python chunks/chunker.py --stem {stem}")
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return False
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chunks: list[dict] = json.loads(chunks_path.read_text(encoding="utf-8"))
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if not chunks:
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print(f" ✗ chunks.json è vuoto")
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return False
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# ── Raccogli problemi ──────────────────────────────────────────────────────
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empty_chunks = [c for c in chunks if is_empty(c)]
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no_prefix = [c for c in chunks if not is_empty(c) and not has_prefix(c)]
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malformed_prefix = [c for c in chunks
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if not is_empty(c) and has_prefix(c) and is_prefix_malformed(c)]
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body_empty = [c for c in chunks
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if not is_empty(c) and has_prefix(c)
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and not is_prefix_malformed(c) and is_body_empty(c)]
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too_short = [c for c in chunks if is_too_short(c, min_chars)]
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too_long = [c for c in chunks if is_too_long(c, max_chars)]
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_incomplete_all = [c for c in chunks if not is_empty(c) and ends_incomplete(c)]
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incomplete_math = [c for c in _incomplete_all if is_math_incomplete(c)]
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incomplete = [c for c in _incomplete_all if not is_math_incomplete(c)]
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broken_tables = [c for c in chunks if is_table_broken(c)]
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duplicates = find_duplicate_bodies(chunks)
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# ── Statistiche ───────────────────────────────────────────────────────────
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lengths = [c.get("n_chars", 0) for c in chunks]
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n_total = len(chunks)
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blocker_ids = set(
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c["chunk_id"]
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for lst in [empty_chunks, no_prefix, malformed_prefix, body_empty, incomplete]
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for c in lst
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)
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n_ok = n_total - len(blocker_ids)
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min_l = min(lengths)
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max_l = max(lengths)
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avg_l = int(sum(lengths) / n_total)
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p50 = sorted(lengths)[n_total // 2]
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n_under = sum(1 for l in lengths if l < min_chars)
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n_norm = sum(1 for l in lengths if min_chars <= l <= max_chars)
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n_over = sum(1 for l in lengths if l > max_chars)
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section_counts = Counter(c.get("sezione", "—") or "—" for c in chunks)
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# ── Output statistiche ────────────────────────────────────────────────────
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print(f" Totale: {n_total} | ✅ OK: {n_ok}")
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print()
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print(f" Lunghezze — min {min_l} p50 {p50} media {avg_l} max {max_l}")
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print(f" Fasce — <{min_chars}: {n_under} | {min_chars}–{max_chars}: {n_norm} | >{max_chars}: {n_over}")
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print()
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print(" Istogramma:")
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for line in _ascii_histogram(lengths, min_chars, max_chars):
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print(line)
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print()
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print(" Top sezioni:")
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for sezione, count in section_counts.most_common(5):
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bar = "▪" * min(count, 35)
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print(f" {bar} {count:>4} {sezione[:65]}")
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# ── Blockers ──────────────────────────────────────────────────────────────
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if empty_chunks:
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print(f"\n 🔴 {len(empty_chunks)} chunk VUOTI:")
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for c in empty_chunks[:5]:
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print(f" [{c.get('chunk_id', '?')}]")
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if len(empty_chunks) > 5:
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print(f" ... e altri {len(empty_chunks) - 5}")
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if no_prefix:
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print(f"\n 🔴 {len(no_prefix)} chunk SENZA PREFISSO DI CONTESTO:")
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_print_list(no_prefix)
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print(f" → Causa probabile: heading mancanti nel clean.md")
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if malformed_prefix:
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print(f"\n 🔴 {len(malformed_prefix)} chunk con PREFISSO MALFORMATO ([ senza ] o vuoto):")
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_print_list(malformed_prefix)
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print(f" → Causa probabile: heading con caratteri speciali nel clean.md")
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if body_empty:
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print(f"\n 🔴 {len(body_empty)} chunk con CORPO VUOTO (solo prefisso):")
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_print_list(body_empty)
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print(f" → Causa probabile: sezioni senza testo nel clean.md")
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if incomplete:
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print(f"\n 🔴 {len(incomplete)} chunk con FRASE SPEZZATA:")
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for c in incomplete[:5]:
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last_line = c.get("text", "").rstrip().split("\n")[-1][-80:]
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print(f" [{c.get('chunk_id', '?')}] ...{last_line!r}")
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if len(incomplete) > 5:
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print(f" ... e altri {len(incomplete) - 5}")
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print(f" → Soluzione: python chunks/fix_chunks.py --stem {stem}")
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# ── Warnings ──────────────────────────────────────────────────────────────
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if too_short:
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print(f"\n 🟡 {len(too_short)} chunk SOTTO MIN_CHARS ({min_chars}):")
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_print_list(too_short)
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if too_long:
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print(f"\n 🟡 {len(too_long)} chunk SOPRA MAX ({max_chars}):")
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_print_list(too_long)
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print(f" → Causa: frasi non suddivisibili o blocchi atomici (tabelle/liste)")
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if incomplete_math:
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print(f"\n 🟡 {len(incomplete_math)} chunk MATEMATICI senza punteggiatura finale:")
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for c in incomplete_math[:3]:
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last_line = c.get("text", "").rstrip().split("\n")[-1][-80:]
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print(f" [{c.get('chunk_id', '?')}] ...{last_line!r}")
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if len(incomplete_math) > 3:
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print(f" ... e altri {len(incomplete_math) - 3}")
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if broken_tables:
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print(f"\n 🟡 {len(broken_tables)} TABELLE senza riga separatore |---|:")
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_print_list(broken_tables, limit=3)
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print(f" → Le tabelle potrebbero non renderizzarsi nel retrieval")
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if duplicates:
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print(f"\n 🟡 {len(duplicates)} DUPLICATI (corpo identico):")
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for e in duplicates[:5]:
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print(f" [{e['chunk_id']}] ≡ [{e['duplicate_of']}] «{e['last_text'][:60]}»")
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if len(duplicates) > 5:
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print(f" ... e altri {len(duplicates) - 5}")
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print(f" → Causa probabile: fix_chunks merge multipli o sezioni ripetute")
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# ── Report.json ───────────────────────────────────────────────────────────
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blockers = empty_chunks + no_prefix + malformed_prefix + body_empty + incomplete
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warnings = too_short + too_long + incomplete_math + broken_tables
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verdict = "blocked" if blockers else ("warnings_only" if (warnings or duplicates) else "ok")
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report = {
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"stem": stem,
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"verdict": verdict,
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"stats": {
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"total": n_total,
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"ok": n_ok,
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"min_chars": min_l,
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"max_chars": max_l,
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"avg_chars": avg_l,
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"p50_chars": p50,
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"under_min": n_under,
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"in_range": n_norm,
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"over_max": n_over,
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"sections": [{"sezione": s, "n_chunks": n}
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for s, n in section_counts.most_common()],
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},
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"thresholds": {
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"min_chars": min_chars,
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"max_chars": max_chars,
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"target_chars": cfg.MAX_CHARS,
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},
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"blockers": {
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"empty": [_chunk_entry(c) for c in empty_chunks],
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"no_prefix": [_chunk_entry(c) for c in no_prefix],
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"malformed_prefix": [_chunk_entry(c) for c in malformed_prefix],
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"body_empty": [_chunk_entry(c) for c in body_empty],
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"incomplete": [_chunk_entry(c) for c in incomplete],
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},
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"warnings": {
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"too_short": [_chunk_entry(c) for c in too_short],
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"too_long": [_chunk_entry(c) for c in too_long],
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"incomplete_math": [_chunk_entry(c) for c in incomplete_math],
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"broken_tables": [_chunk_entry(c) for c in broken_tables],
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"duplicate_bodies": duplicates,
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},
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}
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out_dir = project_root / "chunks" / stem
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out_dir.mkdir(parents=True, exist_ok=True)
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(out_dir / "report.json").write_text(
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json.dumps(report, ensure_ascii=False, indent=2), encoding="utf-8"
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)
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print(f"\n report.json → chunks/{stem}/")
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# ── Prossimi passi ────────────────────────────────────────────────────────
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print(f"\n {'─' * 50}")
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print(f" Verdict: {verdict.upper()}")
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print(f" {'─' * 50}")
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if verdict == "ok":
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print(f" ✅ Tutto OK — procedi alla vettorizzazione:")
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print(f" python ingestion/ingest.py --stem {stem}")
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elif verdict == "warnings_only":
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print(f" 🟡 Solo avvisi — puoi procedere alla vettorizzazione:")
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print(f" python ingestion/ingest.py --stem {stem}")
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if too_short or too_long:
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print()
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print(f" Per ottimizzare prima:")
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print(f" python chunks/fix_chunks.py --stem {stem} --dry-run")
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print(f" python chunks/fix_chunks.py --stem {stem}")
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else:
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print(f" 🔴 {len(blockers)} problemi bloccanti — correggi prima di procedere:")
|
||
if empty_chunks or body_empty:
|
||
print(f" • chunk vuoti/senza corpo → controlla sources/{stem}/auto/{stem}_clean.md")
|
||
if no_prefix or malformed_prefix:
|
||
print(f" • prefisso mancante/malformato → controlla gli heading in {stem}_clean.md")
|
||
if incomplete:
|
||
print(f" • frasi spezzate → python chunks/fix_chunks.py --stem {stem}")
|
||
print()
|
||
print(f" Dopo le correzioni:")
|
||
print(f" python chunks/chunker.py --stem {stem} --force")
|
||
print(f" python chunks/verify_chunks.py --stem {stem}")
|
||
if warnings:
|
||
print()
|
||
print(f" 🟡 Hai anche {len(warnings)} avvisi — affrontali dopo aver risolto i 🔴.")
|
||
|
||
return not blockers
|
||
|
||
|
||
# ─── Entry point ──────────────────────────────────────────────────────────────
|
||
|
||
if __name__ == "__main__":
|
||
project_root = Path(__file__).parent.parent
|
||
|
||
parser = argparse.ArgumentParser(description="Verifica chunk")
|
||
parser.add_argument("--stem", help="Nome del documento (sottocartella di chunks/)")
|
||
parser.add_argument(
|
||
"--min", type=int, default=cfg.MIN_CHARS,
|
||
help=f"Soglia minima caratteri (default: {cfg.MIN_CHARS})"
|
||
)
|
||
parser.add_argument(
|
||
"--max", type=int, default=cfg.MAX_CHARS,
|
||
help=f"Soglia massima caratteri (default: {cfg.MAX_CHARS})"
|
||
)
|
||
args = parser.parse_args()
|
||
|
||
if args.stem:
|
||
stems = [args.stem]
|
||
else:
|
||
chunks_dir = project_root / "chunks"
|
||
if not chunks_dir.exists():
|
||
print(f"Errore: cartella chunks/ non trovata in {project_root}")
|
||
sys.exit(1)
|
||
stems = sorted(
|
||
p.name for p in chunks_dir.iterdir()
|
||
if p.is_dir() and (p / "chunks.json").exists()
|
||
)
|
||
if not stems:
|
||
print("Errore: nessun chunks.json trovato in chunks/")
|
||
sys.exit(1)
|
||
|
||
results = [verify_stem(s, project_root, args.min, args.max) for s in stems]
|
||
|
||
ok = sum(results)
|
||
total = len(results)
|
||
print(f"\n{'✅' if all(results) else '⚠️ '} {ok}/{total} documenti senza problemi bloccanti")
|
||
sys.exit(0 if all(results) else 1)
|