From b4ae6e731caa60d910cc339de853a8097c297eb2 Mon Sep 17 00:00:00 2001 From: Krishna Chaithanya Movva Date: Sat, 11 May 2024 11:04:19 +0530 Subject: [PATCH] Standardize the location parameter (#11745) * adds the location fixes * Updated variable name REGION to LOCATION * fixed issue in comments * fixes linter issues * Update gemini_tuning.py convert LOCATION to location * Update generative_ai/multimodal_embedding_video.py --------- Co-authored-by: rohith-egen Co-authored-by: nileshspringml Co-authored-by: Holt Skinner <13262395+holtskinner@users.noreply.github.com> --- generative_ai/gemini_tuning.py | 2 ++ generative_ai/gemini_tuning_test.py | 7 ++++--- generative_ai/inference/inference_api_test.py | 9 ++++----- .../inference/non_stream_multimodality_basic.py | 4 ++-- generative_ai/inference/non_stream_text_basic.py | 4 ++-- generative_ai/inference/stream_multimodality_basic.py | 4 ++-- generative_ai/inference/stream_text_basic.py | 4 ++-- generative_ai/multimodal_embedding_image.py | 6 ++---- generative_ai/multimodal_embedding_image_test.py | 2 -- generative_ai/multimodal_embedding_image_video_text.py | 5 ++--- .../multimodal_embedding_image_video_text_test.py | 2 -- generative_ai/multimodal_embedding_video.py | 5 ++--- generative_ai/multimodal_embedding_video_test.py | 2 -- 13 files changed, 24 insertions(+), 32 deletions(-) diff --git a/generative_ai/gemini_tuning.py b/generative_ai/gemini_tuning.py index c5a5b6de7f2a..ad133398b2e0 100644 --- a/generative_ai/gemini_tuning.py +++ b/generative_ai/gemini_tuning.py @@ -21,6 +21,7 @@ def gemini_tuning_basic(project_id: str) -> sft.SupervisedTuningJob: # [START generativeaionvertexai_tuning_basic] import time + import vertexai from vertexai.preview.tuning import sft @@ -51,6 +52,7 @@ def gemini_tuning_advanced(project_id: str) -> sft.SupervisedTuningJob: # [START generativeaionvertexai_tuning_advanced] import time + import vertexai from vertexai.preview.tuning import sft diff --git a/generative_ai/gemini_tuning_test.py b/generative_ai/gemini_tuning_test.py index 2931fcd888a3..f2b074a5bada 100644 --- a/generative_ai/gemini_tuning_test.py +++ b/generative_ai/gemini_tuning_test.py @@ -19,7 +19,7 @@ import gemini_tuning PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT") -REGION = "us-central1" +LOCATION = "us-central1" MODEL_ID = "gemini-1.5-pro-preview-0409" TUNING_JOB_ID = "4982013113894174720" @@ -34,7 +34,8 @@ def test_gemini_tuning() -> None: def test_get_tuning_job() -> None: - response = gemini_tuning.get_tuning_job(PROJECT_ID, REGION, TUNING_JOB_ID) + response = gemini_tuning.get_tuning_job( + PROJECT_ID, LOCATION, TUNING_JOB_ID) assert response @@ -45,4 +46,4 @@ def test_list_tuning_jobs() -> None: @pytest.mark.skip(reason="Skip due to tuning taking a long time.") def test_cancel_tuning_job() -> None: - gemini_tuning.cancel_tuning_job(PROJECT_ID, REGION, TUNING_JOB_ID) + gemini_tuning.cancel_tuning_job(PROJECT_ID, LOCATION, TUNING_JOB_ID) diff --git a/generative_ai/inference/inference_api_test.py b/generative_ai/inference/inference_api_test.py index 903c2f2b29c0..bfed57026593 100644 --- a/generative_ai/inference/inference_api_test.py +++ b/generative_ai/inference/inference_api_test.py @@ -21,29 +21,28 @@ PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT") -REGION = "us-central1" MODEL_ID = "gemini-1.5-pro-preview-0409" def test_non_stream_text_basic() -> None: - response = non_stream_text_basic.generate_content(PROJECT_ID, REGION, MODEL_ID) + response = non_stream_text_basic.generate_content(PROJECT_ID, MODEL_ID) assert response def test_non_stream_multi_modality_basic() -> None: response = non_stream_multimodality_basic.generate_content( - PROJECT_ID, REGION, MODEL_ID + PROJECT_ID, MODEL_ID ) assert response def test_stream_text_basic() -> None: - responses = stream_text_basic.generate_content(PROJECT_ID, REGION, MODEL_ID) + responses = stream_text_basic.generate_content(PROJECT_ID, MODEL_ID) assert responses def test_stream_multi_modality_basic() -> None: responses = stream_multimodality_basic.generate_content( - PROJECT_ID, REGION, MODEL_ID + PROJECT_ID, MODEL_ID ) assert responses diff --git a/generative_ai/inference/non_stream_multimodality_basic.py b/generative_ai/inference/non_stream_multimodality_basic.py index 29eb2597c480..705e239aa691 100644 --- a/generative_ai/inference/non_stream_multimodality_basic.py +++ b/generative_ai/inference/non_stream_multimodality_basic.py @@ -13,13 +13,13 @@ # limitations under the License. -def generate_content(PROJECT_ID: str, REGION: str, MODEL_ID: str) -> object: +def generate_content(PROJECT_ID: str, MODEL_ID: str) -> object: # [START generativeaionvertexai_non_stream_multimodality_basic] import vertexai from vertexai.generative_models import GenerativeModel, Part - vertexai.init(project=PROJECT_ID, location=REGION) + vertexai.init(project=PROJECT_ID, location="us-central1") model = GenerativeModel(MODEL_ID) response = model.generate_content( diff --git a/generative_ai/inference/non_stream_text_basic.py b/generative_ai/inference/non_stream_text_basic.py index 71326208ddc1..1da43d5420bf 100644 --- a/generative_ai/inference/non_stream_text_basic.py +++ b/generative_ai/inference/non_stream_text_basic.py @@ -13,13 +13,13 @@ # limitations under the License. -def generate_content(PROJECT_ID: str, REGION: str, MODEL_ID: str) -> object: +def generate_content(PROJECT_ID: str, MODEL_ID: str) -> object: # [START generativeaionvertexai_non_stream_text_basic] import vertexai from vertexai.generative_models import GenerativeModel - vertexai.init(project=PROJECT_ID, location=REGION) + vertexai.init(project=PROJECT_ID, location="us-central1") model = GenerativeModel(MODEL_ID) response = model.generate_content("Write a story about a magic backpack.") diff --git a/generative_ai/inference/stream_multimodality_basic.py b/generative_ai/inference/stream_multimodality_basic.py index b79afc9a0f7e..f2025d609684 100644 --- a/generative_ai/inference/stream_multimodality_basic.py +++ b/generative_ai/inference/stream_multimodality_basic.py @@ -13,13 +13,13 @@ # limitations under the License. -def generate_content(PROJECT_ID: str, REGION: str, MODEL_ID: str) -> object: +def generate_content(PROJECT_ID: str, MODEL_ID: str) -> object: # [START generativeaionvertexai_stream_multimodality_basic] import vertexai from vertexai.generative_models import GenerativeModel, Part - vertexai.init(project=PROJECT_ID, location=REGION) + vertexai.init(project=PROJECT_ID, location="us-central1") model = GenerativeModel(MODEL_ID) responses = model.generate_content( diff --git a/generative_ai/inference/stream_text_basic.py b/generative_ai/inference/stream_text_basic.py index be3cab645807..f1a4c9a3502d 100644 --- a/generative_ai/inference/stream_text_basic.py +++ b/generative_ai/inference/stream_text_basic.py @@ -13,13 +13,13 @@ # limitations under the License. -def generate_content(PROJECT_ID: str, REGION: str, MODEL_ID: str) -> object: +def generate_content(PROJECT_ID: str, MODEL_ID: str) -> object: # [START generativeaionvertexai_stream_text_basic] import vertexai from vertexai.generative_models import GenerativeModel - vertexai.init(project=PROJECT_ID, location=REGION) + vertexai.init(project=PROJECT_ID, location="us-central1") model = GenerativeModel(MODEL_ID) responses = model.generate_content( diff --git a/generative_ai/multimodal_embedding_image.py b/generative_ai/multimodal_embedding_image.py index ab56daef0b2b..b960b4f6c2d0 100644 --- a/generative_ai/multimodal_embedding_image.py +++ b/generative_ai/multimodal_embedding_image.py @@ -19,7 +19,6 @@ def get_image_embeddings( project_id: str, - location: str, image_path: str, contextual_text: Optional[str] = None, ) -> MultiModalEmbeddingResponse: @@ -27,7 +26,6 @@ def get_image_embeddings( Args: project_id: Google Cloud Project ID, used to initialize vertexai - location: Google Cloud Region, used to initialize vertexai image_path: Path to image (local or Google Cloud Storage) to generate embeddings for. contextual_text: Text to generate embeddings for. """ @@ -35,8 +33,8 @@ def get_image_embeddings( import vertexai from vertexai.vision_models import Image, MultiModalEmbeddingModel - # TODO(developer): Update values for project_id, location, image_path & contextual_text - vertexai.init(project=project_id, location=location) + # TODO(developer): Update values for project_id, image_path & contextual_text + vertexai.init(project=project_id, location="us-central1") model = MultiModalEmbeddingModel.from_pretrained("multimodalembedding") image = Image.load_from_file(image_path) diff --git a/generative_ai/multimodal_embedding_image_test.py b/generative_ai/multimodal_embedding_image_test.py index 335c7b56cada..9743ddc48836 100644 --- a/generative_ai/multimodal_embedding_image_test.py +++ b/generative_ai/multimodal_embedding_image_test.py @@ -19,14 +19,12 @@ import multimodal_embedding_image _PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT") -_LOCATION = "us-central1" @backoff.on_exception(backoff.expo, ResourceExhausted, max_time=10) def test_multimodal_embedding_image() -> None: embeddings = multimodal_embedding_image.get_image_embeddings( project_id=_PROJECT_ID, - location=_LOCATION, image_path="gs://cloud-samples-data/vertex-ai/llm/prompts/landmark1.png", contextual_text="Colosseum", ) diff --git a/generative_ai/multimodal_embedding_image_video_text.py b/generative_ai/multimodal_embedding_image_video_text.py index fabba2b86174..91a70abf22f0 100644 --- a/generative_ai/multimodal_embedding_image_video_text.py +++ b/generative_ai/multimodal_embedding_image_video_text.py @@ -19,7 +19,6 @@ def get_image_video_text_embeddings( project_id: str, - location: str, image_path: str, video_path: str, contextual_text: Optional[str] = None, @@ -44,9 +43,9 @@ def get_image_video_text_embeddings( from vertexai.vision_models import Image, MultiModalEmbeddingModel, Video - # TODO(developer): Update values for project_id, location, + # TODO(developer): Update values for project_id, # image_path, video_path, contextual_text, video_segment_config - vertexai.init(project=project_id, location=location) + vertexai.init(project=project_id, location="us-central1") model = MultiModalEmbeddingModel.from_pretrained("multimodalembedding") image = Image.load_from_file(image_path) diff --git a/generative_ai/multimodal_embedding_image_video_text_test.py b/generative_ai/multimodal_embedding_image_video_text_test.py index 2b0e41ba4598..313a530426d0 100644 --- a/generative_ai/multimodal_embedding_image_video_text_test.py +++ b/generative_ai/multimodal_embedding_image_video_text_test.py @@ -19,14 +19,12 @@ import multimodal_embedding_image_video_text _PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT") -_LOCATION = "us-central1" @backoff.on_exception(backoff.expo, ResourceExhausted, max_time=10) def test_multimodal_embedding_image_video_text() -> None: embeddings = multimodal_embedding_image_video_text.get_image_video_text_embeddings( project_id=_PROJECT_ID, - location=_LOCATION, image_path="gs://cloud-samples-data/vertex-ai/llm/prompts/landmark1.png", video_path="gs://cloud-samples-data/vertex-ai-vision/highway_vehicles.mp4", contextual_text="Cars on Highway", diff --git a/generative_ai/multimodal_embedding_video.py b/generative_ai/multimodal_embedding_video.py index 04338b10f446..62de144dbbca 100644 --- a/generative_ai/multimodal_embedding_video.py +++ b/generative_ai/multimodal_embedding_video.py @@ -19,7 +19,6 @@ def get_video_embeddings( project_id: str, - location: str, video_path: str, contextual_text: Optional[str] = None, dimension: Optional[int] = 1408, @@ -42,9 +41,9 @@ def get_video_embeddings( from vertexai.vision_models import MultiModalEmbeddingModel, Video - # TODO(developer): Update values for project_id, location, + # TODO(developer): Update values for project_id, # video_path, contextual_text, dimension, video_segment_config - vertexai.init(project=project_id, location=location) + vertexai.init(project=project_id, location="us-central1") model = MultiModalEmbeddingModel.from_pretrained("multimodalembedding") video = Video.load_from_file(video_path) diff --git a/generative_ai/multimodal_embedding_video_test.py b/generative_ai/multimodal_embedding_video_test.py index 42550e3c6c19..d57eac5573ef 100644 --- a/generative_ai/multimodal_embedding_video_test.py +++ b/generative_ai/multimodal_embedding_video_test.py @@ -19,14 +19,12 @@ import multimodal_embedding_video _PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT") -_LOCATION = "us-central1" @backoff.on_exception(backoff.expo, ResourceExhausted, max_time=10) def test_multimodal_embedding_video() -> None: embeddings = multimodal_embedding_video.get_video_embeddings( project_id=_PROJECT_ID, - location=_LOCATION, video_path="gs://cloud-samples-data/vertex-ai-vision/highway_vehicles.mp4", contextual_text="Cars on Highway", )