feat(nlp-service): wire NLP_FUZZY_THRESHOLD env var with 0-100 validation

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

nlp-service/main.py

@@ -9,10 +9,23 @@ from fastapi import FastAPI, HTTPException
 
 logger = logging.getLogger(__name__)
 
-from extractor import extract, get_person_matcher, set_person_matcher
+from extractor import extract, get_person_matcher, set_fuzzy_threshold, set_person_matcher
 from models import ParseRequest, ParseResponse
 from person_matcher import PersonMatcher
 
+_DEFAULT_FUZZY_THRESHOLD = 80
+
+
+def _parse_fuzzy_threshold(val: str) -> int:
+    """Parse and validate NLP_FUZZY_THRESHOLD — must be integer in [0, 100]."""
+    try:
+        n = int(val)
+    except ValueError:
+        raise ValueError(f"NLP_FUZZY_THRESHOLD must be an integer, got: {val!r}")
+    if not (0 <= n <= 100):
+        raise ValueError(f"NLP_FUZZY_THRESHOLD must be between 0 and 100, got: {n}")
+    return n
+
 
 def _load_persons_from_db(db_url: str) -> list[tuple[str | None, str | None]]:
     import psycopg2  # deferred — not available in test environments without a DB
@@ -28,6 +41,10 @@ def _load_persons_from_db(db_url: str) -> list[tuple[str | None, str | None]]:
 
 @asynccontextmanager
 async def lifespan(app: FastAPI):
+    threshold_raw = os.environ.get("NLP_FUZZY_THRESHOLD", str(_DEFAULT_FUZZY_THRESHOLD))
+    threshold = _parse_fuzzy_threshold(threshold_raw)
+    set_fuzzy_threshold(threshold)
+
     # Only initialise the matcher when nothing was pre-seeded (e.g., by tests).
     if get_person_matcher() is None:
         m = PersonMatcher()