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"""
"""
from PIL import Image
from sentence_transformers import SentenceTransformer
from config import settings
# --- Global Singleton for Embedding Model ---
_embedding_model = None
def get_embedding_model():
"""
Initializes and returns the SentenceTransformer model (singleton pattern).
"""
global _embedding_model
if _embedding_model is None:
print("Initializing embedding model...")
_embedding_model = SentenceTransformer(settings.EMBEDDING_MODEL_ID)
print(f"✓ Embedding model initialized ({settings.EMBEDDING_MODEL_ID})")
return _embedding_model
def get_image_embedding(image_path: str) -> list[float]:
"""
Generates a CLIP embedding for a given image file.
Args:
image_path (str): The path to the image file.
Returns:
list[float]: The image embedding as a list of floats.
"""
model = get_embedding_model()
img = Image.open(image_path).convert("RGB")
embedding = model.encode(img, convert_to_numpy=True)
return embedding.tolist()
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