Trainer_LLM/docker/qdrant/search_qdrant.py

25 lines
580 B
Python

from sentence_transformers import SentenceTransformer
from qdrant_client import QdrantClient
# Modell laden
model = SentenceTransformer("all-MiniLM-L6-v2")
# Qdrant-Client initialisieren
qdrant = QdrantClient(host="localhost", port=6333)
# Suchabfrage
query = "Wie wird Mae-geri korrekt ausgeführt?"
query_vector = model.encode(query).tolist()
# Suche durchführen
results = qdrant.search(
collection_name="karate-doku",
query_vector=query_vector,
limit=3
)
# Ergebnisse ausgeben
for r in results:
print(f"Score: {r.score:.3f} - Text: {r.payload['text']}")