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feat(genai/embeddings): migrate lower dimension embeddings to genai #14512

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b164972
feat(genai/embeddings): migrate lower dimension embeddings to genai
XrossFox Aug 14, 2026
23af44e
Fixed region: required to be global.
XrossFox Aug 14, 2026
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67 changes: 67 additions & 0 deletions genai/embeddings/generate_embeddings_with_lower_dimension.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,67 @@
# Copyright 2026 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# [START aiplatform_genai_embeddings_specify_lower_dimension]
import os

from google import genai

# TODO (Developer) Set environment variables
PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
LOCATION_ID = "global"

# Supported dimensions: 128, 256, 512, 1408 (or up to 3072 for gemini-embedding-2)
EMBEDDING_DIMENSION = 128
IMAGE_URI = "gs://cloud-samples-data/vertex-ai/llm/prompts/landmark1.png"
EMBEDDING_MODEL = "gemini-embedding-2"
CONTEXTUAL_TEXT = "Colosseum"


def generate_embeddings_with_lower_dimension() -> genai.types.EmbedContentResponse:
"""Generates multimodal embeddings (image + text) with custom lower dimensionality

using the modern google-genai SDK.
"""

client = genai.Client(
vertexai=True,
project=PROJECT_ID,
location=LOCATION_ID,
)
Comment on lines +37 to +41

@gemini-code-assist gemini-code-assist Bot Aug 14, 2026

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critical

The google-genai SDK uses the vertexai parameter to initialize the client for Vertex AI, rather than enterprise. Using enterprise=True will result in a TypeError at runtime.

Suggested change
client = genai.Client(
enterprise=True,
project=PROJECT_ID,
location=LOCATION_ID,
)
client = genai.Client(
vertexai=True,
project=PROJECT_ID,
location=LOCATION_ID,
)

@XrossFox XrossFox Aug 14, 2026

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It does not, tested locally.


image_part = genai.types.Part.from_uri(
file_uri=IMAGE_URI,
mime_type="image/png",
)

text_part = genai.types.Part.from_text(text=CONTEXTUAL_TEXT)

@gemini-code-assist gemini-code-assist Bot Aug 14, 2026

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critical

The google-genai SDK's Part class does not have a from_text classmethod. To create a text part, you should instantiate Part directly with the text parameter.

Suggested change
text_part = genai.types.Part.from_text(text=CONTEXTUAL_TEXT)
text_part = genai.types.Part(text=CONTEXTUAL_TEXT)

@XrossFox XrossFox Aug 14, 2026

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Tested locally, it does.


contents = genai.types.Content(parts=[image_part, text_part])

config = genai.types.EmbedContentConfig(output_dimensionality=EMBEDDING_DIMENSION)

response = client.models.embed_content(
model=EMBEDDING_MODEL,
contents=[contents],
config=config,
)

embeddings = response.embeddings[0].values

print(f"Embeddings (dim={len(embeddings)}): {embeddings[:3]}...")

return response


# [END aiplatform_genai_embeddings_specify_lower_dimension]
5 changes: 5 additions & 0 deletions genai/embeddings/test_embeddings_examples.py
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Expand Up @@ -20,6 +20,7 @@

import code_retrieval_example
import embeddings_docretrieval_with_txt
import generate_embeddings_with_lower_dimension
import model_tuning_example

os.environ["GOOGLE_GENAI_USE_ENTERPRISE"] = "True"
Expand All @@ -40,3 +41,7 @@ def test_code_retrieval_example() -> None:
def test_model_tuning_example() -> None:
response = model_tuning_example.tune_embedding_model()
assert response

def test_generate_embeddings_with_lower_dimension() -> None:
response = generate_embeddings_with_lower_dimension.generate_embeddings_with_lower_dimension()
assert response