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app/core/retriever.py aktualisiert
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Lars 2025-12-04 15:55:39 +01:00
parent a571c41c61
commit 9d9239b11e
1 changed files with 16 additions and 10 deletions
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app/core/retriever.py
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@ -14,7 +14,7 @@ import app.core.graph_adapter as ga
try: try:
import yaml # type: ignore[import] import yaml # type: ignore[import]
except Exception: # pragma: no cover - Fallback falls PyYAML nicht installiert ist except Exception: # pragma: no cover - Fallback, falls PyYAML nicht installiert ist
yaml = None # type: ignore[assignment] yaml = None # type: ignore[assignment]
@ -77,7 +77,13 @@ def _get_query_vector(req: QueryRequest) -> List[float]:
settings = get_settings() settings = get_settings()
model_name = settings.MODEL_NAME model_name = settings.MODEL_NAME
return ec.embed_text(req.query, model_name=model_name)
# Kompatibel mit Fakes in Unit-Tests (ohne model_name-Parameter)
try:
return ec.embed_text(req.query, model_name=model_name) # type: ignore[call-arg]
except TypeError:
# Fallback: einfache Signatur embed_text(text)
return ec.embed_text(req.query) # type: ignore[call-arg]
def _semantic_hits( def _semantic_hits(
@ -90,15 +96,15 @@ def _semantic_hits(
"""Führt eine semantische Suche über mindnet_chunks aus und liefert Roh-Treffer. """Führt eine semantische Suche über mindnet_chunks aus und liefert Roh-Treffer.
Rückgabeformat: Liste von (point_id, score, payload) Rückgabeformat: Liste von (point_id, score, payload)
Erwartetes Format von qp.search_chunks_by_vector:
List[Tuple[str, float, dict]]
""" """
flt = filters or None flt = filters or None
hits = qp.search_chunks_by_vector(client, prefix, vector, top=top_k, filters=flt) raw_hits = qp.search_chunks_by_vector(client, prefix, vector, top=top_k, filters=flt)
results: List[Tuple[str, float, Dict[str, Any]]] = [] results: List[Tuple[str, float, Dict[str, Any]]] = []
for point in hits: for pid, score, payload in raw_hits:
pid = str(point.id) results.append((str(pid), float(score), dict(payload or {})))
score = float(point.score)
payload = dict(point.payload or {})
results.append((pid, score, payload))
return results return results
@ -150,7 +156,7 @@ def _extract_expand_options(req: QueryRequest) -> Tuple[int, List[str] | None]:
return 0, None return 0, None
depth = 1 depth = 1
edge_types = None edge_types: List[str] | None = None
# Pydantic-Modell oder Objekt mit Attributen # Pydantic-Modell oder Objekt mit Attributen
if hasattr(expand, "depth") or hasattr(expand, "edge_types"): if hasattr(expand, "depth") or hasattr(expand, "edge_types"):
@ -279,7 +285,7 @@ def hybrid_retrieve(req: QueryRequest) -> QueryResponse:
if depth and depth > 0: if depth and depth > 0:
# Seeds: stabile IDs aus dem Payload (chunk_id bevorzugt, sonst note_id) # Seeds: stabile IDs aus dem Payload (chunk_id bevorzugt, sonst note_id)
seed_ids: List[str] = [] seed_ids: List[str] = []
for _, _score, payload in hits: for _pid, _score, payload in hits:
key = payload.get("chunk_id") or payload.get("note_id") key = payload.get("chunk_id") or payload.get("note_id")
if key and key not in seed_ids: if key and key not in seed_ids:
seed_ids.append(key) seed_ids.append(key)