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"""
Sentence-transformer embeddings shared across all MCP tools.
"""
from sentence_transformers import SentenceTransformer
# Load MiniLM model (384-dimensional embeddings)
model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
def embed_text(text: str):
"""
Generate sentence embedding for use with pgvector.
Args:
text (str): Input text
Returns:
List[float]: 384-dimensional embedding vector
"""
vector = model.encode(text)
return vector.tolist()
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