init

python/test.py

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+import requests
+from lancedb.pydantic import LanceModel, Vector
+import importlib
+import io
+import os
+
+import lancedb
+import numpy as np
+import pandas as pd
+import pyarrow as pa
+import pytest
+from lancedb.embeddings import get_registry
+from lancedb.pydantic import LanceModel, Vector, MultiVector
+
+db = lancedb.connect("~/.db")
+registry = get_registry()
+func = registry.get("multimodal-late-interaction").create(
+    model_name="vidore/colQwen2.5-v0.2",
+    device="auto",
+    batch_size=1,
+)
+
+class MediaItems(LanceModel):
+    text: str
+    image_uri: str = func.SourceField()
+    image_bytes: bytes = func.SourceField()
+    image_vectors: MultiVector(func.ndims()) = func.VectorField()
+
+table = db.create_table("media", schema=MediaItems, mode="overwrite")
+
+texts = [
+    "a cute cat playing with yarn",
+    "a puppy in a flower field",
+    "a red sports car on the highway",
+]
+
+uris = [
+    "http://farm1.staticflickr.com/53/167798175_7c7845bbbd_z.jpg",
+    "http://farm1.staticflickr.com/134/332220238_da527d8140_z.jpg",
+    "http://farm5.staticflickr.com/4092/5017326486_1f46057f5f_z.jpg",
+]
+
+image_bytes = [requests.get(uri).content for uri in uris]
+
+table.add(
+    pd.DataFrame({"text": texts, "image_uri": uris, "image_bytes": image_bytes})
+)
+
+result = (
+    table.search("fluffy companion", vector_column_name="image_vectors")
+    .limit(1)
+    .to_pydantic(MediaItems)[0]
+)
+assert any(keyword in result.text.lower() for keyword in ("cat", "puppy"))
+
+first_row = table.to_arrow().to_pylist()[0]
+assert len(first_row["image_vectors"]) > 1
+assert len(first_row["image_vectors"][0]) == func.ndims()