feat(fimi): Fundament Counter-Disinformation-Match (Embedding + LLM-Verifikation)

Zweistufiger Abgleich von Monitor-Artikeln gegen den EUvsDisinfo-
Falschbehauptungsbestand, vollstaendig im Monitor (kein Vigil-Call):

- services/embeddings.py: SentenceTransformer-Singleton (paraphrase-
  multilingual-MiniLM-L12-v2), Modell-Cache mit Vigil geteilt.
- fimi_claims-Tabelle + scripts/import_fimi_claims.py: Einmal-/Sync-Import
  der 19.629 EUvsDisinfo-Claims inkl. Embedding-BLOB und Case-URL.
- services/fimi_matcher.py: Stufe 1 Embedding-Vorfilter (numpy-Matrix im RAM,
  Kosinus), Stufe 2 Haiku-Verifikation (verbreitet vs. berichtet/widerlegt),
  speichert nur bestaetigte Verbreitungen + woertliches Zitat.
- article_fimi_matches-Tabelle + fimi_checked_at-Marker auf articles.
- requirements.txt: torch, sentence-transformers, transformers, numpy.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

scripts/import_fimi_claims.py

@@ -0,0 +1,116 @@
+#!/usr/bin/env python3
+"""Einmal-/Sync-Import des EUvsDisinfo-Falschbehauptungsbestands in den Monitor.
+
+Kopiert die Claims (Text, Verdict, Widerlegung, Quell-Referenz, Embedding-BLOB)
+aus der Vigil-Datenbank in die Monitor-Tabelle fimi_claims. Die Embeddings
+werden als BLOB 1:1 uebernommen (384-dim float32, L2-normalisiert) und im
+Monitor mit demselben Modell (paraphrase-multilingual-MiniLM-L12-v2) gematcht.
+
+Idempotent: UPSERT auf der stabilen Vigil-claim.id. Bestehende Treffer in
+article_fimi_matches bleiben dadurch gueltig.
+
+Aufruf (Staging):
+  python scripts/import_fimi_claims.py \
+      --vigil-db /home/claude-dev/vigil-data/vigil.db \
+      --osint-db /home/claude-dev/AegisSight-Monitor-staging/data/osint.db
+"""
+from __future__ import annotations
+
+import argparse
+import sqlite3
+import sys
+
+EUVSDISINFO_REPORT_BASE = "https://euvsdisinfo.eu/report/"
+
+
+def case_url_from_source_ref(source_ref: str | None) -> str | None:
+    """Leitet die EUvsDisinfo-Case-URL aus 'euvsdisinfo:<slug>' ab."""
+    if not source_ref:
+        return None
+    prefix = "euvsdisinfo:"
+    if source_ref.startswith(prefix):
+        slug = source_ref[len(prefix):].strip().strip("/")
+        if slug:
+            return f"{EUVSDISINFO_REPORT_BASE}{slug}/"
+    return None
+
+
+def main() -> int:
+    ap = argparse.ArgumentParser(description=__doc__)
+    ap.add_argument("--vigil-db", required=True, help="Pfad zur Vigil-SQLite-DB (Quelle)")
+    ap.add_argument("--osint-db", required=True, help="Pfad zur Monitor-SQLite-DB (Ziel)")
+    ap.add_argument("--limit", type=int, default=0, help="Optional: nur N Claims importieren (Test)")
+    args = ap.parse_args()
+
+    src = sqlite3.connect(args.vigil_db)
+    src.row_factory = sqlite3.Row
+    q = (
+        "SELECT id, text, text_normalized, language, verdict, verdict_summary, "
+        "source_id, embedding, first_seen_at FROM claims WHERE embedding IS NOT NULL"
+    )
+    if args.limit:
+        q += f" LIMIT {int(args.limit)}"
+    rows = src.execute(q).fetchall()
+    src.close()
+    print(f"Vigil: {len(rows)} Claims mit Embedding gelesen", flush=True)
+
+    dst = sqlite3.connect(args.osint_db)
+    dst.execute("PRAGMA busy_timeout=10000")
+
+    # Sicherstellen, dass die Zieltabelle existiert (falls Skript vor init_db laeuft)
+    dst.execute(
+        """CREATE TABLE IF NOT EXISTS fimi_claims (
+            id INTEGER PRIMARY KEY,
+            text TEXT NOT NULL,
+            text_normalized TEXT,
+            language TEXT,
+            verdict TEXT NOT NULL DEFAULT 'false',
+            verdict_summary TEXT,
+            source_ref TEXT,
+            case_url TEXT,
+            embedding BLOB,
+            first_seen_at TIMESTAMP,
+            imported_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+        )"""
+    )
+    dst.execute("CREATE INDEX IF NOT EXISTS idx_fimi_claims_source_ref ON fimi_claims(source_ref)")
+
+    inserted = 0
+    with_url = 0
+    for r in rows:
+        case_url = case_url_from_source_ref(r["source_id"])
+        if case_url:
+            with_url += 1
+        dst.execute(
+            """INSERT INTO fimi_claims
+                   (id, text, text_normalized, language, verdict, verdict_summary,
+                    source_ref, case_url, embedding, first_seen_at, imported_at)
+               VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, CURRENT_TIMESTAMP)
+               ON CONFLICT(id) DO UPDATE SET
+                   text=excluded.text,
+                   text_normalized=excluded.text_normalized,
+                   language=excluded.language,
+                   verdict=excluded.verdict,
+                   verdict_summary=excluded.verdict_summary,
+                   source_ref=excluded.source_ref,
+                   case_url=excluded.case_url,
+                   embedding=excluded.embedding,
+                   first_seen_at=excluded.first_seen_at,
+                   imported_at=CURRENT_TIMESTAMP""",
+            (
+                r["id"], r["text"], r["text_normalized"], r["language"],
+                r["verdict"] or "false", r["verdict_summary"], r["source_id"],
+                case_url, r["embedding"], r["first_seen_at"],
+            ),
+        )
+        inserted += 1
+    dst.commit()
+    total = dst.execute("SELECT COUNT(*) FROM fimi_claims").fetchone()[0]
+    dst.close()
+    print(f"Monitor: {inserted} Claims upserted ({with_url} mit Case-URL), "
+          f"fimi_claims enthaelt jetzt {total} Eintraege", flush=True)
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())