feat(import): Abgabeverträge (DOCX) auswerten und Tiere/Kontakte anreichern

Neuer Parser extract_contracts.py liest die ~1,4k Abgabevertrags-DOCX
(\truenas\…\Verträge): er extrahiert aus dem Dokument-Body (zuverlässiger als
die Dateinamen) Käufer, Tier(e), Farbschlag, Abgabedatum und Preis — robust
gegen Word-Run-Splits (z. B. „F r au"/„3 0,00"); überspringt Vorlage,
Abstammungsnachweise und als .docx getarnte .doc.

enrich_from_contracts() in merge_and_resolve.py: Käufer werden als Kontakte
(IsReceiver) angelegt/zusammengeführt; Tiere werden KONSERVATIV per Rufname
(+ DOB-Jahr bei Mehrdeutigkeit) auf eigene Bestandstiere gematcht und erhalten
ReceiverContactId, GoHomeDate und Status „abgegeben" — nur wo nicht bereits
gesetzt; Konflikte werden geloggt, nicht überschrieben. Jede Übernahme bekommt
eine Herkunfts-Zeile („Abgabe an … aus Vertrag … übernommen.").

Ergebnis: 1095 Verträge → 783 Tier-Treffer (400 mehrdeutige übersprungen),
274 neue Abnehmer-Kontakte, 153 Tiere mit Abnehmer, 49 mit Abgabedatum,
23 neu „abgegeben". Keine Backend-/Frontend-Änderung nötig (Akte zeigt Abnehmer/
Abgabedatum/Herkunft bereits). SaleContract-Records bewusst nicht erzeugt
(bräuchte Migration + ingest-sichere Id — späterer Schritt).

Tests: test_extract_contracts.py (Dateiname/Body/Run-Split/Skip-Regeln) + alle
bestehenden grün; dotnet 212.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

tools/import/README.md

@@ -51,12 +51,25 @@ preserving everything: `genotype.mapped8locus`, `genotype.rawGenotype` (verbatim
 
 ```sh
 cd tools/import
-python extract.py                       # uses the default source paths
+python extract.py                       # xlsx → animals.json / litters.json
 python extract.py --stammbaeume "<dir>" --wurfchronik "<file.xlsx>"
+python extract_docx.py                  # Wurfchronik-Detail.docx → docx_*.json
+python extract_contracts.py             # Abgabeverträge (.docx) → contracts.json
+python merge_and_resolve.py             # → resolved_import.json (DB-ready)
 ```
 
-Requires Python 3. **Re-runnable / idempotent** — re-run when more files arrive
+Requires Python 3 (zero third-party deps). **Re-runnable / idempotent** — re-run
-(Wurfchronik `Teil2+`, or new charts).
+when more files arrive (Wurfchronik `Teil2+`, new charts, or new contracts).
+
+`extract_contracts.py` scans the breeder's sale-contract share
+(`\\truenas\…\Verträge`, ~1.4k `.docx`) and emits one record per contract
+(buyer, animal call-names, Farbschlag, dates, price, source filename). It skips
+the blank template, `Abstammungsnachweis`/`Geburtsurkunde` documents, and any
+file that is not a readable `.docx`. `merge_and_resolve.py` then conservatively
+folds contracts into the resolved data: buyers become receiver `Contacts`, and
+unambiguously matched gerbils get `ReceiverContactId` / `GoHomeDate` /
+`Status=GivenAway` (only where not already set), with a provenance history line.
+Ambiguous / unmatched animals are counted and skipped, never guessed.
 
 ## Output (`tools/import/output/`, git-ignored except the report)
 
@@ -64,6 +77,9 @@ Requires Python 3. **Re-runnable / idempotent** — re-run when more files arriv
 |---|---|
 | `animals.json` | deduped animals with genotype, parentRefs, photos, sourceFiles |
 | `litters.json` | litters from the Wurfchronik |
+| `docx_animals.json` / `docx_litters.json` | Wurfchronik-Detail.docx rows |
+| `contracts.json` | one record per Abgabevertrag (buyer, animals, dates, price) |
+| `resolved_import.json` | merged DB-ready payload consumed by `IngestResolvedService` |
 | `photos/<slug>/…` | extracted, anchor-mapped images |
 | `review-report.md` | **human review deliverable** (committed) |
 

tools/import/extract_contracts.py

@@ -0,0 +1,446 @@
+#!/usr/bin/env python3
+"""FEAT-Contracts Stage 1 — Abgabeverträge (.docx) extrahieren.
+
+Liest die Sammlung der Vermittlungs-/Abgabeverträge ("Zucht der kleinen
+Chaoten _ … (Tier.Namen) - <Käufer>_.docx") vom Netzlaufwerk und erzeugt:
+  output/contracts.json  — strukturierte Vertrags-Datensätze
+
+Reines stdlib-Python (kein pip), nach Vorbild von extract_docx.py: .docx ist
+ein ZIP mit word/document.xml; daraus werden die "Label: Wert"-Zeilen des
+Vertragskörpers gelesen. Der Dateiname dient als Zusatz-Signal für die
+Tier-Rufnamen und den Farbschlag, wenn der Körper sie nicht hergibt.
+
+Zuverlässig extrahierbar (beobachtete Abdeckung über 250er-Stichprobe):
+  Name (Tier):     100 %   — Body-Label "Name:"
+  Geschlecht:      100 %   — Body-Label "Geschlecht:"
+  Geburtsdatum:     98 %   — Body-Label "Geburtsdatum:"
+  Abgabedatum:      78 %   — Body-Label "Abgabedatum:"
+  Preis:            78 %   — "Gesamtpreis/Schutzgebühr/Kaufpreis"
+  Käufer (Body):    79 %   — Block "Abnehmer/Empfänger" → "Name:"
+  Farbschlag(Body): 13 %   — Body-Label "Farbschlag:" (oft im Dateinamen)
+
+Übersprungen werden:
+  * die Vorlage  "Vertrags mustter new.docx"
+  * Abstammungsnachweise / Geburtsurkunden (kein Verkauf, eigener Doc-Typ)
+  * Dateien, die kein lesbares ZIP sind (alte .doc als .docx getarnt)
+
+Ausführung: python extract_contracts.py [--dir PFAD] [--limit N]
+Idempotent: mehrfaches Ausführen überschreibt output/contracts.json.
+"""
+import os
+import re
+import sys
+import json
+import zipfile
+import argparse
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+DEFAULT_DIR = r"\\truenas\Datengrab\Rennmäuse\Verträge"
+OUT = os.path.join(HERE, "output")
+
+TEMPLATE_MARKERS = ("mustter", "muster new")
+# Doc types that are NOT sale contracts (skip):
+NON_CONTRACT_MARKERS = ("Abstammungsnachweis", "Geburtsurkunde")
+
+# --- Body label regexes (work on whitespace-collapsed plain text) ----------
+# Generic "Label: value up to next known label or end".
+_KNOWN_LABELS = (
+    r"Name|Geburtsdatum|Geschlecht|Farbschlag|Farbe|Abgabedatum|Abgabe\s*am|"
+    r"Gesamtpreis|Schutzgeb\w+|Kaufpreis|Preis|Zuchtname|Zuchtbuchnummer|"
+    r"Stra\w+e|Wohnort|Fon|Festnetz|Handy|Handynummer|Telefon|E-?Mail|Homepage|"
+    r"Facebook|Mutter|Vater|Linie|Wurf|Bemerkung|Z\w+chter\w*|Abnehmer|Empf\w+nger"
+)
+
+
+def _norm_date(d: str) -> str:
+    """German DD.MM.YY[YY] → ISO YYYY-MM-DD (or '' if unparseable)."""
+    if not d:
+        return ""
+    m = re.search(r"(\d{1,2})\.(\d{1,2})\.(\d{2,4})", d)
+    if not m:
+        return ""
+    day, mon, yr = m.group(1), m.group(2), m.group(3)
+    if len(yr) == 2:
+        yr = "20" + yr
+    try:
+        di, mi, yi = int(day), int(mon), int(yr)
+        if not (1 <= di <= 31 and 1 <= mi <= 12 and 1900 <= yi <= 2100):
+            return ""
+    except ValueError:
+        return ""
+    return f"{yi:04d}-{mi:02d}-{di:02d}"
+
+
+def _unescape(t: str) -> str:
+    for a, b in (("&amp;", "&"), ("&lt;", "<"), ("&gt;", ">"),
+                 ("&apos;", "'"), ("&quot;", '"'), ("&#160;", " ")):
+        t = t.replace(a, b)
+    return t
+
+
+def _para_text(p_xml: str) -> str:
+    """Plain text of one <w:p>.
+
+    IMPORTANT: Word frequently splits a single word across multiple <w:r>/<w:t>
+    runs (formatting/spell-check artefacts). Run boundaries are NOT word
+    boundaries, so we concatenate <w:t> contents directly (no separator) and
+    only turn explicit tabs/breaks into spaces. This avoids mangling
+    "Frau"→"F r au" or "30,00"→"3 0,00".
+    """
+    p_xml = re.sub(r"<w:tab\b[^>]*/?>", " ", p_xml)
+    p_xml = re.sub(r"<w:br\b[^>]*/?>", " ", p_xml)
+    texts = re.findall(r"<w:t\b[^>]*>(.*?)</w:t>", p_xml, re.DOTALL)
+    t = _unescape("".join(texts))
+    return re.sub(r"\s+", " ", t).strip()
+
+
+def _full_text(docx_path: str) -> str:
+    """Return whitespace-collapsed plain text of the document body.
+
+    Paragraphs (and table cells, also wrapped in <w:p>) are joined by a single
+    space so adjacent labels stay separable.
+    """
+    with zipfile.ZipFile(docx_path) as z:
+        xml = z.read("word/document.xml").decode("utf-8", errors="replace")
+    paras = [_para_text(p) for p in re.findall(r"<w:p[ >].*?</w:p>", xml, re.DOTALL)]
+    return re.sub(r"\s+", " ", " ".join(p for p in paras if p)).strip()
+
+
+def _paragraphs(docx_path: str) -> list[str]:
+    """Return per-paragraph plain text (preserves the Label/value line breaks)."""
+    with zipfile.ZipFile(docx_path) as z:
+        xml = z.read("word/document.xml").decode("utf-8", errors="replace")
+    out = []
+    for p in re.findall(r"<w:p[ >].*?</w:p>", xml, re.DOTALL):
+        t = _para_text(p)
+        if t:
+            out.append(t)
+    return out
+
+
+def _label_value(text: str, label_rx: str) -> str:
+    """Find 'Label: value' in collapsed text; stop at the next known label."""
+    rx = re.compile(
+        rf"(?:{label_rx})\s*:\s*(.+?)(?=\s*(?:{_KNOWN_LABELS})\s*:|$)",
+        re.IGNORECASE,
+    )
+    m = rx.search(text)
+    return m.group(1).strip() if m else ""
+
+
+def _clean_money(raw: str) -> str:
+    """'27,50 Euro (Überweisung)' → '27,50'. Returns '' if no number."""
+    m = re.search(r"(\d+(?:[.,]\d{1,2})?)", raw)
+    if not m:
+        return ""
+    return m.group(1).replace(".", ",")
+
+
+def parse_filename(fname: str) -> dict:
+    """Best-effort structured pieces from the contract filename.
+
+    Returns dict with keys: color, animals (list of call-names), buyer
+    (may be empty). Robust to the many messy variants observed.
+    """
+    base = re.sub(r"\.docx$", "", fname, flags=re.IGNORECASE)
+    # Strip the leading cattery prefix and the leading/trailing underscores.
+    base = re.sub(r"^\s*(?:Zucht der kleinen Chaoten|Clan[^_]*Chaoten)\s*",
+                  "", base, flags=re.IGNORECASE)
+    base = base.strip().strip("_").strip()
+
+    color = ""
+    animals: list[str] = []
+    buyer = ""
+
+    # Animals are inside the (…) group, dot-separated call-names.
+    pm = re.search(r"\(([^)]*)\)", base)
+    if pm:
+        inner = pm.group(1).strip()
+        # split on dot (call-name separator) but keep multi-word names
+        animals = [a.strip() for a in inner.split(".") if a.strip()]
+        # color = text before "("
+        color = base[:pm.start()].strip(" -–_")
+        # buyer = text after ")"
+        after = base[pm.end():].strip()
+        bm = re.match(r"\s*[-–]\s*(.+)", after)
+        if bm:
+            buyer = bm.group(1).strip().strip("_").strip()
+    else:
+        # No parens. Two shapes:
+        #   "<token> - <Buyer>"   (token is animal-name or color)
+        #   "<AnimalName>"        (just a name)
+        dm = re.split(r"\s*[-–]\s*", base, maxsplit=1)
+        if len(dm) == 2 and dm[1].strip():
+            color = ""  # ambiguous; treat the left token as an animal name
+            animals = [dm[0].strip().strip("_")] if dm[0].strip() else []
+            buyer = dm[1].strip().strip("_").strip()
+        else:
+            tok = base.strip().strip("_").strip()
+            # comma list like "Speedy,Agouti" → first is the name
+            if tok:
+                animals = [tok.split(",")[0].strip()]
+
+    # Clean buyer: drop trailing numbering "2", file-version noise
+    buyer = re.sub(r"\s*\(?\d+\)?$", "", buyer).strip() if buyer else ""
+    return {"color": color, "animals": animals, "buyer": buyer}
+
+
+# Seller is always the breeder Drazena Rimac (the cattery owner); never a buyer.
+_SELLER_RX = re.compile(r"^(?:(?:Herr|Frau|Familie)\s+)?Drazena\b", re.IGNORECASE)
+_ADDR_STOP = r"Stra\w+e|Wohnort|Fon|E-?Mail|Handy|Festnetz|Telefon|Homepage|Zuchtname|Facebook"
+
+
+_BUYER_REJECT_RX = re.compile(
+    r"^(?:Stra\w+e|Wohnort|Fon|E-?Mail|Handy|Festnetz|Telefon|Homepage|"
+    r"Zuchtname|Facebook|Name)\s*:?\s*$|^[\d\s/]+$",
+    re.IGNORECASE,
+)
+
+
+def _clean_person(name: str) -> str:
+    name = re.sub(r"\s+", " ", name).strip().strip(",").strip()
+    # Reject label leakage / non-person artefacts (e.g. "Straße:", phone runs).
+    if _BUYER_REJECT_RX.match(name):
+        return ""
+    return name
+
+
+def _extract_buyer(text: str, paras: list[str]) -> str:
+    """Buyer (Abnehmer/Empfänger) name from the body.
+
+    Two document layouts exist:
+      A) Side-by-side columns (two table cells): "Name:<seller>" and
+         "Name:<buyer>" appear as two separate runs in the full text.
+      B) Stacked blocks: a "Empfänger/Abnehmer:" header precedes the buyer's
+         "Name:".
+    Strategy: collect every "Name:" value that looks like a person and is not
+    the seller (Drazena Rimac). The buyer is such a value.
+    """
+    # Layout B: explicit Abnehmer/Empfänger header followed by Name:.
+    bm = re.search(
+        r"(?:Empf\w+nger|Abnehmer)[^:]*:\s*(?:[^:]*?\s)?Name\s*:\s*"
+        rf"(.+?)(?=\s*(?:{_ADDR_STOP})\s*:|$)",
+        text, re.IGNORECASE,
+    )
+    if bm:
+        cand = _clean_person(bm.group(1))
+        if cand and not _SELLER_RX.match(cand):
+            return cand
+
+    # Layout A / fallback: scan all Name: values; pick the first non-seller one.
+    for m in re.finditer(
+        rf"Name\s*:\s*(.+?)(?=\s*(?:{_ADDR_STOP})\s*:|\s*Name\s*:|$)",
+        text, re.IGNORECASE,
+    ):
+        cand = _clean_person(m.group(1))
+        if not cand or _SELLER_RX.match(cand):
+            continue
+        # Skip the animal block: animal Name is immediately followed by
+        # Geburtsdatum/Geschlecht/Farbschlag.
+        tail = text[m.end():m.end() + 40]
+        if re.match(r"\s*(?:Geburtsdatum|Geschlecht|Farbschlag)\s*:", tail, re.IGNORECASE):
+            continue
+        return cand
+    return ""
+
+
+def parse_contract(docx_path: str) -> dict | None:
+    """Parse one .docx. Returns a contract record or None if not a contract."""
+    fname = os.path.basename(docx_path)
+    try:
+        text = _full_text(docx_path)
+        paras = _paragraphs(docx_path)
+    except (zipfile.BadZipFile, KeyError, OSError):
+        return None  # unreadable / not a real docx
+
+    if any(m in text for m in NON_CONTRACT_MARKERS):
+        return None  # Abstammungsnachweis / Geburtsurkunde — not a sale contract
+
+    fn = parse_filename(fname)
+
+    # --- animal block (body) ---
+    body_name = _label_value(text, r"Name")
+    # The first "Name:" in the body could be the seller's. The animal's name
+    # appears under "Tierdaten:". Prefer the Name that directly precedes
+    # Geburtsdatum/Geschlecht (the animal block).
+    animal_name = ""
+    # The animal block is headed by "Tierdaten:" (when present) and its Name is
+    # the LAST "Name:" before "Geburtsdatum:". Anchor on Tierdaten if present,
+    # then take the closest Name: to Geburtsdatum.
+    scope = text
+    ti = re.search(r"Tierdaten\s*:", text, re.IGNORECASE)
+    if ti:
+        scope = text[ti.end():]
+    am = re.search(
+        r"Name\s*:\s*(.*?)\s*Geburtsdatum\s*:",
+        scope, re.IGNORECASE,
+    )
+    if am:
+        cand = am.group(1).strip()
+        # Greedy guard: if it still spans multiple labels, keep only the tail
+        # after the last embedded "Name:".
+        if "Name:" in cand or re.search(r"Name\s*:", cand):
+            cand = re.split(r"Name\s*:", cand)[-1].strip()
+        # Drop any leading address-block leftovers.
+        cand = re.split(rf"\s*(?:{_ADDR_STOP})\s*:", cand)[-1].strip()
+        animal_name = cand
+    # Body animal name is often blank (the call-name lives in the filename).
+    if not animal_name or len(animal_name) > 40:
+        animal_name = ""
+
+    dob = _norm_date(_label_value(text, r"Geburtsdatum"))
+    gender_raw = _label_value(text, r"Geschlecht").lower()
+    if gender_raw.startswith("m"):
+        gender = "Male"
+    elif gender_raw.startswith("w"):
+        gender = "Female"
+    else:
+        gender = ""
+
+    color = _label_value(text, r"Farbschlag") or _label_value(text, r"Farbe")
+    color = color.strip()
+    if not color and fn["color"]:
+        color = fn["color"]
+
+    handover = _norm_date(
+        _label_value(text, r"Abgabedatum") or _label_value(text, r"Abgabe\s*am")
+    )
+
+    price = ""
+    for lab in (r"Gesamtpreis", r"Schutzgeb\w+", r"Kaufpreis", r"Preis"):
+        raw = _label_value(text, lab)
+        if raw:
+            price = _clean_money(raw)
+            if price:
+                break
+
+    # contract date: trailing "Ort, [den ]DD.MM.YYYY" near signature line
+    contract_date = ""
+    cm = re.findall(r"[A-Za-zÄÖÜäöü.\- ]+,\s*(?:den\s*)?(\d{1,2}\.\d{1,2}\.\d{2,4})",
+                    text)
+    if cm:
+        contract_date = _norm_date(cm[-1])
+
+    buyer = _extract_buyer(text, paras)
+    if not buyer and fn["buyer"]:
+        buyer = fn["buyer"]
+
+    # Animal call-names: prefer filename (the call-names the breeder filed by),
+    # fall back to body animal name.
+    animals = list(fn["animals"])
+    if not animals and animal_name:
+        animals = [animal_name]
+
+    # Reject if we have neither a buyer nor any animal name — useless record.
+    if not buyer and not animals:
+        return None
+
+    return {
+        "sourceFile": fname,
+        "buyer": buyer,
+        "animals": animals,
+        "animalNameBody": animal_name,
+        "color": color,
+        "gender": gender,
+        "dob": dob,
+        "handoverDate": handover,
+        "contractDate": contract_date,
+        "price": price,
+    }
+
+
+def scan(dir_path: str, limit: int | None = None):
+    """Walk the share, parse every .docx. Returns (records, stats)."""
+    records = []
+    stats = {
+        "files_seen": 0, "template_skipped": 0, "non_contract_skipped": 0,
+        "unreadable": 0, "parsed": 0, "unparseable": 0,
+        "with_buyer": 0, "with_handover": 0, "with_price": 0,
+        "with_color": 0, "with_dob": 0, "with_animals": 0,
+    }
+    for root, _, files in os.walk(dir_path):
+        for f in sorted(files):
+            if not f.lower().endswith(".docx"):
+                continue
+            stats["files_seen"] += 1
+            low = f.lower()
+            if any(m in low for m in TEMPLATE_MARKERS):
+                stats["template_skipped"] += 1
+                continue
+            path = os.path.join(root, f)
+            try:
+                rec = parse_contract(path)
+            except Exception:  # never let one bad file kill the run
+                rec = None
+            if rec is None:
+                # Distinguish unreadable vs non-contract vs genuinely unparseable
+                try:
+                    _ = _full_text(path)
+                    txt = _
+                    if any(m in txt for m in NON_CONTRACT_MARKERS):
+                        stats["non_contract_skipped"] += 1
+                    else:
+                        stats["unparseable"] += 1
+                except Exception:
+                    stats["unreadable"] += 1
+                continue
+            stats["parsed"] += 1
+            if rec["buyer"]:
+                stats["with_buyer"] += 1
+            if rec["handoverDate"]:
+                stats["with_handover"] += 1
+            if rec["price"]:
+                stats["with_price"] += 1
+            if rec["color"]:
+                stats["with_color"] += 1
+            if rec["dob"]:
+                stats["with_dob"] += 1
+            if rec["animals"]:
+                stats["with_animals"] += 1
+            records.append(rec)
+            if limit and len(records) >= limit:
+                return records, stats
+    return records, stats
+
+
+def main():
+    try:
+        sys.stdout.reconfigure(encoding="utf-8", errors="replace")
+    except Exception:
+        pass
+
+    ap = argparse.ArgumentParser(description="Abgabevertrag-Extraktor")
+    ap.add_argument("--dir", default=DEFAULT_DIR, help="Verträge-Ordner")
+    ap.add_argument("--limit", type=int, default=None,
+                    help="Nur die ersten N Verträge (Stichprobe)")
+    args = ap.parse_args()
+
+    if not os.path.isdir(args.dir):
+        print(f"Fehler: Ordner nicht gefunden: {args.dir}", file=sys.stderr)
+        sys.exit(1)
+
+    os.makedirs(OUT, exist_ok=True)
+    print(f"Scanne: {args.dir}")
+    records, stats = scan(args.dir, args.limit)
+
+    out_path = os.path.join(OUT, "contracts.json")
+    with open(out_path, "w", encoding="utf-8") as f:
+        json.dump(records, f, ensure_ascii=False, indent=2)
+
+    print(f"Dateien gesehen:        {stats['files_seen']}")
+    print(f"  Vorlage übersprungen: {stats['template_skipped']}")
+    print(f"  Nicht-Vertrag (AN):   {stats['non_contract_skipped']}")
+    print(f"  unlesbar (kein ZIP):  {stats['unreadable']}")
+    print(f"  unparsbar:            {stats['unparseable']}")
+    print(f"Verträge geparst:       {stats['parsed']}")
+    print(f"  mit Käufer:           {stats['with_buyer']}")
+    print(f"  mit Tier(en):         {stats['with_animals']}")
+    print(f"  mit Geburtsdatum:     {stats['with_dob']}")
+    print(f"  mit Abgabedatum:      {stats['with_handover']}")
+    print(f"  mit Preis:            {stats['with_price']}")
+    print(f"  mit Farbschlag:       {stats['with_color']}")
+    print(f"Ausgabe: {out_path}")
+
+
+if __name__ == "__main__":
+    main()

tools/import/merge_and_resolve.py

@@ -944,6 +944,168 @@ def _format_discard(d):
     return DISCARD_MARK + line + "."
 
 
+def _append_history(prov_json, line):
+    """Append one history line to an existing Provenance JSON string and add the
+    contract source file. Returns the updated JSON string."""
+    try:
+        prov = json.loads(prov_json) if prov_json else {}
+    except (ValueError, TypeError):
+        prov = {}
+    prov.setdefault("history", [])
+    if line not in prov["history"]:
+        prov["history"].append(line)
+    return json.dumps(prov, ensure_ascii=False)
+
+
+def enrich_from_contracts(contracts, resolved_gerbils, contact_by_norm_name,
+                          contact_id_map):
+    """Conservatively fold Abgabevertrag data into the resolved gerbils.
+
+    For every parsed contract we (a) ensure the buyer exists as a (receiver)
+    contact, reusing the existing contact dedup/normalisation, and (b) try to
+    match each animal call-name to exactly one resolved gerbil that the breeder
+    bred ("…Chaoten"). On a confident match we set ReceiverContactId /
+    GoHomeDate / Status=GivenAway — but only where not already set differently —
+    and add a provenance history line. Ambiguous or absent matches are logged,
+    never guessed.
+
+    Returns a stats dict. Mutates resolved_gerbils + contact_by_norm_name in
+    place. New buyer contacts are appended via contact_by_norm_name so the later
+    IsReceiver-flag pass picks them up automatically.
+    """
+    stats = {
+        "contracts": len(contracts), "buyers_created": 0, "buyers_existing": 0,
+        "matched": 0, "ambiguous_skipped": 0, "no_match_skipped": 0,
+        "receiver_set": 0, "gohome_set": 0, "status_givenaway": 0,
+        "conflicts": 0,
+    }
+    if not contracts:
+        return stats
+
+    # Index breeder-owned gerbils by dedup name key. Contracts only ever sell
+    # animals the breeder bred, so restrict candidates to her own stock to avoid
+    # colliding with same-named foreign-bred animals.
+    def is_own(g):
+        ob = (g.get("OriginBreeder") or "").lower()
+        return ("chaoten" in ob) or (g.get("OriginBreeder") is None)
+
+    index = {}
+    for g in resolved_gerbils:
+        if not is_own(g):
+            continue
+        key = get_dedup_name_key(get_call_name(g.get("Name", "")))
+        if key:
+            index.setdefault(key, []).append(g)
+
+    def year_of(iso):
+        return iso[:4] if iso else None
+
+    # Reject buyer values that are obviously label leakage / non-person noise
+    # (defends against any stale contracts.json produced before the parser fix).
+    _buyer_junk = re.compile(
+        r"^(?:stra\w+e|wohnort|fon|e-?mail|handy|festnetz|telefon|homepage|"
+        r"zuchtname|facebook|name)\s*:?\s*$|^[\d\s/]+$", re.IGNORECASE)
+
+    for c in contracts:
+        fname = c.get("sourceFile", "")
+        buyer_raw = (c.get("buyer") or "").strip()
+        if buyer_raw and _buyer_junk.match(buyer_raw):
+            buyer_raw = ""
+
+        # --- buyer contact (reuse curated normalisation/dedup) ---
+        buyer_global_id = None
+        if buyer_raw:
+            canon, keep = get_normalized_contact_name(buyer_raw)
+            if keep and canon:
+                norm = normalize_name(canon)
+                if norm in contact_by_norm_name:
+                    gc = contact_by_norm_name[norm]
+                    gc.setdefault("_source_files", set()).add(fname)
+                    gc["_merged_count"] = gc.get("_merged_count", 1) + 1
+                    stats["buyers_existing"] += 1
+                else:
+                    gid = generate_guid(f"contact-{norm}")
+                    contact_by_norm_name[norm] = {
+                        "Id": gid, "Name": canon, "Email": None, "Phone": None,
+                        "Address": None, "Notes": None, "NameSuffix": None,
+                        "_source_files": {fname}, "_merged_count": 1,
+                    }
+                    stats["buyers_created"] += 1
+                buyer_global_id = contact_by_norm_name[norm]["Id"]
+
+        # --- match each animal call-name to a resolved gerbil ---
+        handover = parse_date(c.get("handoverDate"))
+        c_year = year_of(parse_date(c.get("dob"))) if c.get("dob") else None
+        c_color = (c.get("color") or "").strip().lower()
+
+        for call in (c.get("animals") or []):
+            key = get_dedup_name_key(get_call_name(call))
+            if not key:
+                continue
+            cands = index.get(key, [])
+            if not cands:
+                stats["no_match_skipped"] += 1
+                continue
+
+            # Corroborate when more than one candidate shares the call-name.
+            chosen = None
+            if len(cands) == 1:
+                chosen = cands[0]
+            else:
+                scored = []
+                for g in cands:
+                    score = 0
+                    g_year = year_of(g.get("DateOfBirth"))
+                    if c_year and g_year and c_year == g_year:
+                        score += 2
+                    if c_color and g.get("ColorVarietyId"):
+                        # color match is corroboration; we don't have the name
+                        # here, so only DOB drives disambiguation strongly.
+                        pass
+                    scored.append((score, g))
+                scored.sort(key=lambda t: t[0], reverse=True)
+                if scored[0][0] >= 2 and (len(scored) == 1 or scored[0][0] > scored[1][0]):
+                    chosen = scored[0][1]
+                else:
+                    stats["ambiguous_skipped"] += 1
+                    continue
+
+            stats["matched"] += 1
+
+            # --- set receiver, only if not already set differently ---
+            if buyer_global_id:
+                cur = chosen.get("ReceiverContactId")
+                if not cur:
+                    chosen["ReceiverContactId"] = buyer_global_id
+                    stats["receiver_set"] += 1
+                    chosen["Provenance"] = _append_history(
+                        chosen.get("Provenance"),
+                        f"Abgabe an „{buyer_raw}“ aus Vertrag {_quote_file(fname)} übernommen.")
+                elif cur != buyer_global_id:
+                    stats["conflicts"] += 1
+                    chosen["Provenance"] = _append_history(
+                        chosen.get("Provenance"),
+                        f"Vertrag {_quote_file(fname)} nennt anderen Abnehmer „{buyer_raw}“ "
+                        f"— bestehende Zuordnung beibehalten.")
+
+            # --- set go-home date, only if empty ---
+            if handover and not chosen.get("GoHomeDate"):
+                chosen["GoHomeDate"] = handover
+                stats["gohome_set"] += 1
+                chosen["Provenance"] = _append_history(
+                    chosen.get("Provenance"),
+                    f"Abgabedatum {handover} aus Vertrag {_quote_file(fname)} übernommen.")
+
+            # --- status: derive GivenAway if we set a receiver and it isn't
+            # already a stronger state (Deceased). ---
+            if chosen.get("ReceiverContactId") and chosen.get("Status") not in (
+                    "Deceased", "GivenAway"):
+                chosen["Status"] = "GivenAway"
+                stats["status_givenaway"] += 1
+
+    return stats
+
+
 def main():
     print("Loading color variety seeds...")
     variety_map = {}
@@ -1176,6 +1338,17 @@ def main():
     else:
         print(f"Warning: docx_litters.json not found at {docx_litters_path}")
 
+    # Abgabevertrag-Datensätze (aus extract_contracts.py). Optional: wenn die
+    # Datei fehlt, läuft der Import ohne Vertrags-Anreicherung normal weiter.
+    contracts = []
+    contracts_path = os.path.join(OUTPUT_DIR, "contracts.json")
+    if os.path.exists(contracts_path):
+        with open(contracts_path, "r", encoding="utf-8") as f:
+            contracts = json.load(f)
+        print(f"Loaded {len(contracts)} Abgabeverträge.")
+    else:
+        print(f"Info: contracts.json not found at {contracts_path} (Vertrags-Anreicherung übersprungen)")
+
     # Extract docx buyer contacts and add to raw_contacts
     for da in docx_animals:
         o_name = (da.get("owner") or "").strip()
@@ -2685,6 +2858,28 @@ def main():
     if n_discards:
         print(f"Datenherkunft: recorded {n_discards} discard line(s) across gerbils.")
 
+    # Abgabevertrag-Anreicherung: Käufer als Abnehmer-Kontakte anlegen und —
+    # konservativ — auf eindeutig passende Tiere ReceiverContactId/GoHomeDate/
+    # Status=GivenAway setzen (nur falls noch nicht gesetzt). Provenance-
+    # Historie wird ergänzt. Neue Käuferkontakte landen in contact_by_norm_name
+    # und werden danach automatisch als IsReceiver markiert.
+    cstats = enrich_from_contracts(
+        contracts, resolved_gerbils, contact_by_norm_name, contact_id_map)
+    if contracts:
+        print("Abgabeverträge: "
+              f"{cstats['contracts']} geladen, {cstats['matched']} Tier-Treffer, "
+              f"{cstats['ambiguous_skipped']} mehrdeutig übersprungen, "
+              f"{cstats['no_match_skipped']} ohne Treffer.")
+        print("  Kontakte: "
+              f"{cstats['buyers_created']} neu, {cstats['buyers_existing']} bestehend.")
+        print("  Gesetzt: "
+              f"ReceiverContactId={cstats['receiver_set']}, "
+              f"GoHomeDate={cstats['gohome_set']}, "
+              f"Status=GivenAway={cstats['status_givenaway']}, "
+              f"Konflikte={cstats['conflicts']}.")
+    # Re-materialise contacts so freshly created buyer contacts are exported.
+    resolved_contacts = list(contact_by_norm_name.values())
+
     # Datenherkunft for litters: which source files contributed, whether this is
     # a Wurfchronik litter vs a Stammbaum-reconstructed ("virtual") litter, how
     # many raw records merged into it, plus human-readable notes. Accumulators

tools/import/test_extract_contracts.py

@@ -0,0 +1,189 @@
+"""Tests for extract_contracts.py — run: python test_extract_contracts.py
+
+Zero third-party deps (mirrors test_extract_docx.py). Builds tiny in-memory
+.docx files (a zip with word/document.xml) so the tests run without the
+network share. Covers: filename parsing, run-splitting de-mangling, both body
+layouts (side-by-side / stacked), price/date normalisation, and skip rules.
+"""
+import io
+import os
+import sys
+import zipfile
+
+try:
+    sys.stdout.reconfigure(encoding="utf-8", errors="replace")
+except Exception:
+    pass
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+import extract_contracts as ec
+
+failed = 0
+
+
+def check(name, cond):
+    global failed
+    print(("ok:   " if cond else "FAIL: ") + name)
+    if not cond:
+        failed += 1
+
+
+def make_docx(paragraphs):
+    """paragraphs: list of lists of run-strings → bytes of a .docx zip."""
+    body = []
+    for runs in paragraphs:
+        rs = "".join(f"<w:r><w:t>{r}</w:t></w:r>" for r in runs)
+        body.append(f"<w:p>{rs}</w:p>")
+    xml = ('<?xml version="1.0"?><w:document xmlns:w="x"><w:body>'
+           + "".join(body) + "</w:body></w:document>")
+    buf = io.BytesIO()
+    with zipfile.ZipFile(buf, "w") as z:
+        z.writestr("word/document.xml", xml)
+    return buf.getvalue()
+
+
+def write_tmp(name, data):
+    d = os.path.join(os.path.dirname(os.path.abspath(__file__)), "_test_tmp")
+    os.makedirs(d, exist_ok=True)
+    p = os.path.join(d, name)
+    with open(p, "wb") as f:
+        f.write(data)
+    return p
+
+
+# --- _norm_date -----------------------------------------------------------
+check("date 4-digit year", ec._norm_date("18.02.2014") == "2014-02-18")
+check("date 2-digit year", ec._norm_date("09.12.14") == "2014-12-09")
+check("date embedded", ec._norm_date("Bonn, 20.09.2014") == "2014-09-20")
+check("date invalid", ec._norm_date("99.99.9999") == "")
+check("date empty", ec._norm_date("") == "")
+
+# --- _clean_money ---------------------------------------------------------
+check("money comma", ec._clean_money("27,50 Euro (Überweisung)") == "27,50")
+check("money dot→comma", ec._clean_money("25.00 €") == "25,00")
+check("money plain", ec._clean_money("28 Euro") == "28")
+check("money none", ec._clean_money("kostenlos") == "")
+
+# --- parse_filename -------------------------------------------------------
+fn = ec.parse_filename(
+    "Zucht der kleinen Chaoten _ Agouti (Kathlin.Baxter) - Stephan Füchsle_.docx")
+check("fn color", fn["color"] == "Agouti")
+check("fn animals", fn["animals"] == ["Kathlin", "Baxter"])
+check("fn buyer", fn["buyer"] == "Stephan Füchsle")
+
+fn2 = ec.parse_filename(
+    "Zucht der kleinen Chaoten _ dd Polar Sp (Velvet.Vance Jr.)- Alexandra Wendler_.docx")
+check("fn multiword color", fn2["color"] == "dd Polar Sp")
+check("fn multiword animal", fn2["animals"] == ["Velvet", "Vance Jr"])
+check("fn buyer 2", fn2["buyer"] == "Alexandra Wendler")
+
+fn3 = ec.parse_filename("Zucht der kleinen Chaoten _ Ethan - Stefanie Stoica_.docx")
+check("fn no-paren animal", fn3["animals"] == ["Ethan"])
+check("fn no-paren buyer", fn3["buyer"] == "Stefanie Stoica")
+
+fn4 = ec.parse_filename("Zucht der kleinen Chaoten _Azrael_.docx")
+check("fn name-only animal", fn4["animals"] == ["Azrael"])
+check("fn name-only no buyer", fn4["buyer"] == "")
+
+# --- run-splitting de-mangling (the core text-extraction fix) -------------
+data = make_docx([["Name:", "F", "r", "au Josephin Kiefer"]])
+p = write_tmp("split.docx", data)
+check("run-split joins to 'Frau Josephin Kiefer'",
+      ec._full_text(p) == "Name:Frau Josephin Kiefer")
+
+money = make_docx([["Schutzgebühr: ", "3", "0,00 €"]])
+p = write_tmp("money.docx", money)
+check("run-split price intact",
+      ec._clean_money(ec._label_value(ec._full_text(p), r"Schutzgeb\w+")) == "30,00")
+
+# --- full contract: stacked layout (B) ------------------------------------
+stacked = make_docx([
+    ["Vermittlungsvertrag"],
+    ["Abgebender/Züchter:"],
+    ["Name:", "Frau Drazena Rimac"],
+    ["Straße:", "New-York-Str. 30"],
+    ["Empfänger/Abnehmer:"],
+    ["Name:", "Familie Tanja und Thorsten Kurz"],
+    ["Straße:", "Ebelstraße 2"],
+    ["Tierdaten:"],
+    ["Name:", "Einstein"],
+    ["Geburtsdatum:", "10.08.2019"],
+    ["Geschlecht:", "männlich"],
+    ["Farbschlag: ", "Schwarz"],
+    ["Abgabedatum:", "31.12.2019"],
+    ["Schutzgebühr: ", "25,00 €"],
+    ["Butzbach, den 31.12.2019"],
+])
+p = write_tmp("stacked.docx",
+              make_docx_b := stacked)
+rec = ec.parse_contract(p)
+check("stacked buyer", rec["buyer"] == "Familie Tanja und Thorsten Kurz")
+check("stacked not seller", rec["buyer"] != "Frau Drazena Rimac")
+check("stacked animal name", rec["animalNameBody"] == "Einstein")
+check("stacked dob", rec["dob"] == "2019-08-10")
+check("stacked gender", rec["gender"] == "Male")
+check("stacked color", rec["color"] == "Schwarz")
+check("stacked handover", rec["handoverDate"] == "2019-12-31")
+check("stacked price", rec["price"] == "25,00")
+check("stacked contract date", rec["contractDate"] == "2019-12-31")
+
+# --- full contract: side-by-side columns (A) ------------------------------
+# Two columns render as separate paragraphs (table cells).
+sidebyside = make_docx([
+    ["Vermittlungsvertrag"],
+    ["Züchter:"], ["Abnehmer:"],
+    ["Name:", "Drazena Rimac"], ["Name:", "Andrea Thesing"],
+    ["Straße:", "Alten-Busecker-Str. 57"], ["Straße:", "Veilchenweg 32"],
+    ["Tierdaten:"],
+    ["Name:", "Sally"],
+    ["Geburtsdatum:", "03.02.2014"],
+    ["Geschlecht:", "weiblich"],
+    ["Farbschlag:", "Kohlfuchs-hell"],
+    ["Abgabedatum:", "20.09.2014"],
+    ["Gesamtpreis: ", "27,00 Euro (Überweisung)"],
+    ["Bonn, 20.09.2014"],
+])
+p = write_tmp("sidebyside.docx", sidebyside)
+rec = ec.parse_contract(p)
+check("sbs buyer is Andrea Thesing", rec["buyer"] == "Andrea Thesing")
+check("sbs buyer not seller", rec["buyer"] != "Drazena Rimac")
+check("sbs animal", rec["animalNameBody"] == "Sally")
+check("sbs gender female", rec["gender"] == "Female")
+check("sbs price", rec["price"] == "27,00")
+
+# --- skip rules -----------------------------------------------------------
+abstammung = make_docx([
+    ["Abstammungsnachweis"],
+    ["Name:"], ["Grace"],
+    ["Geburtsdatum:", "04.10.2015"],
+])
+p = write_tmp("abst.docx", abstammung)
+check("Abstammungsnachweis skipped", ec.parse_contract(p) is None)
+
+# bad zip
+badp = write_tmp("bad.docx", b"not a zip")
+check("bad zip → None", ec.parse_contract(badp) is None)
+
+# --- filename color fallback when body has no Farbschlag ------------------
+nocolor = make_docx([
+    ["Vermittlungsvertrag"], ["Abnehmer:"], ["Name:", "Max Mustermann"],
+    ["Tierdaten:"], ["Name:", "Bello"],
+    ["Geburtsdatum:", "01.01.2020"], ["Geschlecht:", "männlich"],
+    ["Gesamtpreis: ", "20,00 €"],
+])
+p = write_tmp("Zucht der kleinen Chaoten _ Agouti (Bello)- Max Mustermann_.docx",
+              nocolor)
+rec = ec.parse_contract(p)
+check("color falls back to filename", rec["color"] == "Agouti")
+check("animals from filename", rec["animals"] == ["Bello"])
+
+# cleanup tmp
+import shutil
+shutil.rmtree(os.path.join(os.path.dirname(os.path.abspath(__file__)), "_test_tmp"),
+              ignore_errors=True)
+
+print()
+if failed:
+    print(f"{failed} test(s) FAILED")
+    sys.exit(1)
+print("All extract_contracts tests passed.")