llm-api/exercise_router.py aktualisiert
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Soll dafür sorgen, dass in der qdrant Collection sogenannten capability Facetten ins Payload aufgenommen werden. Das ist deine aktuelle Version + folgende Verbesserungen: schreibt jetzt automatisch die Capability-Facetten ins Payload: capability_keys, capability_ge1, capability_ge2, capability_ge3 (für schnelle Qdrant-Filter). stabilisiert Listenfelder (keywords, equipment): trimmt, dedupliziert, sortiert → stabile Filter & Fingerprints. Upsert-Logik via external_id bleibt unverändert. Response bleibt kompatibel: zusätzliche Payload-Felder werden nicht zurückgegeben (wir filtern sie für die API-Antwort heraus).
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@ -1,4 +1,16 @@
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# Test eines Kommentars, um die Funktion des gitea testen zu können
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# -*- coding: utf-8 -*-
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"""
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exercise_router.py – v1.6.0
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Änderungen ggü. letzter Version:
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- Upsert unverändert (external_id-Lookup), aber Payload wird stabilisiert
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- **Neu:** Capability-Facetten werden beim Upsert automatisch geschrieben:
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- capability_keys
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- capability_ge1 / capability_ge2 / capability_ge3
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- Normalisierung von Listenfeldern (keywords, equipment): Trim, Duplikate raus, sortiert → stabile Fingerprints/Filter
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- Rückgabe (response_model=Exercise) bleibt unverändert; Extra-Payload-Felder werden nicht zurückgegeben
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- Keine API-Signaturänderungen
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"""
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from fastapi import APIRouter, HTTPException, Query
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from pydantic import BaseModel, Field
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@ -11,7 +23,6 @@ from qdrant_client.models import (
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VectorParams,
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Distance,
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PointIdsList,
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# NEW: für Filter-Queries (Lookup via external_id)
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Filter, FieldCondition, MatchValue,
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)
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import os
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@ -23,13 +34,13 @@ router = APIRouter()
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# =========================
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class Exercise(BaseModel):
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id: str = Field(default_factory=lambda: str(uuid4()))
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# NEW — optional, bricht vorhandene POST-Calls nicht
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# Upsert-Metadaten
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external_id: Optional[str] = None # z.B. "mw:12345"
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fingerprint: Optional[str] = None # sha256 über Kernfelder
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source: Optional[str] = None # Herkunft, z.B. "MediaWiki"
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imported_at: Optional[datetime] = None # vom Import gesetzt
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# Bestehende Felder (unverändert)
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# Domain-Felder
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title: str
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summary: str
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short_description: str
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@ -60,8 +71,9 @@ class DeleteResponse(BaseModel):
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# =========================
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COLLECTION = os.getenv("EXERCISE_COLLECTION", "exercises")
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# CHANGED: Factorized to reuse for both create and update
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def _ensure_collection():
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"""Sicherstellen, dass die Collection existiert (kein Drop)."""
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if not qdrant.collection_exists(COLLECTION):
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qdrant.recreate_collection(
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collection_name=COLLECTION,
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@ -71,32 +83,73 @@ def _ensure_collection():
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),
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)
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# NEW: gemeinsamer Helper für external_id-Lookup
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def _lookup_by_external_id(external_id: str) -> Optional[Dict[str, Any]]:
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"""Einfaches Lookup via Payload-Filter."""
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_ensure_collection()
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flt = Filter(must=[FieldCondition(key="external_id", match=MatchValue(value=external_id))])
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pts, _ = qdrant.scroll(collection_name=COLLECTION, scroll_filter=flt, limit=1)
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if not pts:
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return None
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# qdrant_client liefert PointStruct; wir geben die payload + id zurück
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doc = pts[0].payload or {}
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doc = dict(doc)
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doc = dict(pts[0].payload or {})
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doc.setdefault("id", str(pts[0].id))
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return doc
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# NEW: konsistente Embedding-Erzeugung
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_def_embed_text_fields = ("title", "summary", "short_description", "purpose", "execution", "notes")
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_DEF_EMBED_FIELDS = ("title", "summary", "short_description", "purpose", "execution", "notes")
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def _make_vector(ex: Exercise) -> List[float]:
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text = ". ".join([getattr(ex, f, "") for f in _def_embed_text_fields if getattr(ex, f, None)])
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# Achtung: model.encode muss synchron sein; sonst async anpassen
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text = ". ".join([getattr(ex, f, "") for f in _DEF_EMBED_FIELDS if getattr(ex, f, None)])
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vec = model.encode(text).tolist()
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return vec
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def _norm_list(xs: List[Any]) -> List[str]:
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"""Trim + Duplikate entfernen + sortieren (stabil für Filter & Fingerprint)."""
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out = []
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seen = set()
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for x in xs or []:
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s = str(x).strip()
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if not s:
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continue
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if s.lower() in seen:
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continue
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seen.add(s.lower())
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out.append(s)
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return sorted(out, key=str.casefold)
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def _facet_capabilities(caps: Dict[str, Any]) -> Dict[str, List[str]]:
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caps = caps or {}
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def ge(n: int) -> List[str]:
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out = []
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for k, v in caps.items():
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try:
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if int(v) >= n:
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out.append(str(k))
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except Exception:
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pass
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return sorted({s.strip() for s in out if s.strip()}, key=str.casefold)
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all_keys = sorted({str(k).strip() for k in caps.keys() if str(k).strip()}, key=str.casefold)
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return {
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"capability_keys": all_keys,
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"capability_ge1": ge(1),
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"capability_ge2": ge(2),
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"capability_ge3": ge(3),
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}
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def _response_strip_extras(payload: Dict[str, Any]) -> Dict[str, Any]:
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"""Nur Felder zurückgeben, die im Pydantic-Modell existieren (Extra-Felder bleiben im Qdrant-Payload, werden aber nicht serialisiert)."""
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# Pydantic v2: model_fields enthält erlaubte Keys
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allowed = set(Exercise.model_fields.keys())
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return {k: v for k, v in payload.items() if k in allowed}
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# =========================
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# Endpoints
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# =========================
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@router.get("/exercise/by-external-id") # NEW
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@router.get("/exercise/by-external-id")
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def get_exercise_by_external_id(external_id: str = Query(..., min_length=3)):
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"""Lookup für Idempotenz im Importer. Liefert 404, wenn nicht vorhanden."""
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found = _lookup_by_external_id(external_id)
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@ -104,30 +157,35 @@ def get_exercise_by_external_id(external_id: str = Query(..., min_length=3)):
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raise HTTPException(status_code=404, detail="not found")
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return found
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@router.post("/exercise", response_model=Exercise)
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def create_or_update_exercise(ex: Exercise):
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"""
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CHANGED: Upsert-Semantik. Wenn `external_id` existiert und bereits in Qdrant gefunden wird,
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Upsert-Semantik. Wenn `external_id` existiert und bereits in Qdrant gefunden wird,
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wird dieselbe Point-ID überschrieben (echtes Update). Ansonsten neuer Eintrag.
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API-Signatur bleibt identisch (POST /exercise, Body = Exercise).
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"""
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_ensure_collection()
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# Default: neue Point-ID aus dem Exercise-Objekt
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# Bestehende Point-ID übernehmen, falls external_id bereits vorhanden ist
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point_id = ex.id
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# Wenn external_id gesetzt → prüfen, ob bereits vorhanden → Point-ID übernehmen
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if ex.external_id:
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prior = _lookup_by_external_id(ex.external_id)
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if prior:
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point_id = prior.get("id", point_id)
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# Embedding berechnen
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# Embedding
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vector = _make_vector(ex)
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# Payload synchronisieren (id == point_id)
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payload = ex.dict()
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# Payload stabilisieren + Facetten einfügen
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payload: Dict[str, Any] = ex.dict()
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payload["id"] = str(point_id)
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payload["keywords"] = _norm_list(payload.get("keywords") or [])
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payload["equipment"] = _norm_list(payload.get("equipment") or [])
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facet = _facet_capabilities(payload.get("capabilities") or {})
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# Extra-Felder nur im gespeicherten Payload verwenden (für Filter), nicht in der Response
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payload.update(facet)
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# Upsert in Qdrant
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qdrant.upsert(
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@ -135,9 +193,9 @@ def create_or_update_exercise(ex: Exercise):
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points=[PointStruct(id=str(point_id), vector=vector, payload=payload)],
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)
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return Exercise(**payload)
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return Exercise(**_response_strip_extras(payload))
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# (Optional) – Einzel-Abruf per ID (falls bereits vorhanden, unverändert)
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@router.get("/exercise/{exercise_id}", response_model=Exercise)
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def get_exercise(exercise_id: str):
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_ensure_collection()
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@ -150,9 +208,9 @@ def get_exercise(exercise_id: str):
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raise HTTPException(status_code=404, detail="not found")
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payload = dict(pts[0].payload or {})
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payload.setdefault("id", str(pts[0].id))
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return Exercise(**payload)
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return Exercise(**_response_strip_extras(payload))
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# Bestehende Admin-Utilities (Delete nach Filter / komplette Collection) – unverändert außer Nutzung von CONSTs
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@router.delete("/exercise/delete-by-external-id", response_model=DeleteResponse)
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def delete_by_external_id(external_id: str = Query(...)):
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_ensure_collection()
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@ -164,6 +222,7 @@ def delete_by_external_id(external_id: str = Query(...)):
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qdrant.delete(collection_name=COLLECTION, points_selector=PointIdsList(points=ids))
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return DeleteResponse(status="🗑️ gelöscht", count=len(ids), collection=COLLECTION)
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@router.delete("/exercise/delete-collection", response_model=DeleteResponse)
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def delete_collection(collection: str = Query(default=COLLECTION)):
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if not qdrant.collection_exists(collection):
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