feat(quality): add L0 quality layer (Track A1 + A2 of dev plan)

L0 quality detection layer to catch translation failures BEFORE they
reach users. Pure Python/TypeScript, zero new dependencies, no API calls.

Backend (Python — services/quality/):
  - Script detection: 145 langs mapped to 23 scripts (Latin, Cyrillic,
    Greek, Arabic, Hebrew, CJK, Hangul, Kana, Devanagari, Bengali, etc.)
  - Language confusion detection (e.g. Arabic text for French target)
  - Arabic-script variant discrimination (Persian/Urdu/Pashto/Kurdish
    confusion — e.g. Persian text returned when Arabic was requested)
  - Length sanity check (with numeric/short-source exemptions)
  - Prompt leak detection (Translation: / Voici la traduction: / 翻译:)
  - Repetition hallucination detection (token + character level)
  - File text extraction for .docx/.xlsx/.pptx/.pdf (no translator
    changes needed)
  - Defensive pipeline that never raises (L0 must NEVER break a job)

Frontend (TypeScript — wordly.art---traduction-de-documents/src/utils/):
  - Exact 1:1 mirror of the Python module
  - Zero dependencies, works in browser AND Node.js
  - Native Unicode regex (\\p{L}/u) and codePoint iteration
  - 63 tests using Node's built-in test runner

Integration:
  - Feature-flagged: QUALITY_L0_ENABLED=false (default)
  - Observation only: logs structured events, never modifies files
  - try/except wrapped: impossible to break a translation job
  - Lazy imports: only loaded when flag is on
  - Zero impact on existing tests / behavior

Tests:
  - 111 Python tests covering all paths (config, script, length, leak,
    pipeline, file_extractor) — 100% pass
  - 63 TypeScript tests (Node --test) — 100% pass
  - 174/174 total tests for the L0 layer

Bug fixes in script mapping:
  - yi (Yiddish) -> hebrew (was incorrectly mapped to arabic)
  - dv (Maldivian) -> thaana (was incorrectly mapped to arabic)
  - ja (Japanese) -> hiragana_katakana (distinguishes from Chinese CJK)

Phase 1 (backend) + Phase 2 (frontend) of Track A complete.
Next: Track B1 (Word/Excel format preservation quick wins).

Closes Track A phase 1+2 of the dev plan.

services/quality/pipeline.py

@@ -0,0 +1,75 @@
+"""
+Quality pipeline — defensive wrapper around the L0 checks.
+
+The pipeline is the integration point for the route. It:
+  1. Catches all exceptions (L0 must NEVER break a translation job)
+  2. Adds timing
+  3. Emits a single structured log line per job
+
+The actual checks live in `script_detector`, `length_checker`, `pattern_leak`.
+This module is the orchestration / safety layer.
+"""
+
+from __future__ import annotations
+
+import time
+from typing import List, Optional
+
+from core.logging import get_logger
+
+from .script_detector import evaluate_document, DocumentQualityResult
+
+logger = get_logger(__name__)
+
+
+def run_l0_check(
+    source_chunks: List[str],
+    translated_chunks: List[str],
+    target_lang: Optional[str],
+    job_id: Optional[str] = None,
+    file_extension: Optional[str] = None,
+) -> DocumentQualityResult:
+    """
+    Run the L0 quality checks defensively. Never raises.
+
+    Returns an empty/neutral DocumentQualityResult on internal error
+    so the calling route can log and continue without affecting the
+    translation job outcome.
+    """
+    start = time.time()
+    empty = DocumentQualityResult(
+        passed=True,
+        score=0.0,
+        chunk_count=0,
+        failed_chunk_count=0,
+        issues={"internal_error": 1},
+    )
+
+    try:
+        result = evaluate_document(source_chunks, translated_chunks, target_lang)
+    except Exception as e:
+        elapsed_ms = round((time.time() - start) * 1000, 2)
+        logger.warning(
+            "quality_l0_check_failed",
+            job_id=job_id,
+            file_extension=file_extension,
+            error=str(e)[:200],
+            error_type=type(e).__name__,
+            elapsed_ms=elapsed_ms,
+        )
+        return empty
+
+    elapsed_ms = round((time.time() - start) * 1000, 2)
+    logger.info(
+        "quality_l0_check",
+        job_id=job_id,
+        file_extension=file_extension,
+        target_lang=target_lang,
+        chunk_count=result.chunk_count,
+        failed_chunk_count=result.failed_chunk_count,
+        score=result.score,
+        passed=result.passed,
+        issues=result.issues,
+        elapsed_ms=elapsed_ms,
+    )
+    return result