import tempfile
from pathlib import Path
import lancedb
from lancedb.embeddings import get_registry
from lancedb.pydantic import LanceModel, Vector
db = lancedb.connect(str(Path(tempfile.mkdtemp()) / "ollama-demo"))
func = get_registry().get("ollama").create(name="nomic-embed-text")
class Words(LanceModel):
text: str = func.SourceField()
vector: Vector(func.ndims()) = func.VectorField()
table = db.create_table("words", schema=Words, mode="overwrite")
table.add(
[
{"text": "hello world"},
{"text": "goodbye world"},
]
)
query = "greetings"
actual = table.search(query).limit(1).to_pydantic(Words)[0]
print(actual.text)
