test: disable deprecated embedding model tests (#1006)

* test: disable deprecated embedding models

* delete tests

Author: GarrettWu

tests/system/small/ml/test_llm.py

@@ -178,125 +178,6 @@ def test_text_generator_predict_with_params_success(
     )
 
 
-def test_create_embedding_generator_model(
-    palm2_embedding_generator_model, dataset_id, bq_connection
-):
-    # Model creation doesn't return error
-    assert palm2_embedding_generator_model is not None
-    assert palm2_embedding_generator_model._bqml_model is not None
-
-    # save, load to ensure configuration was kept
-    reloaded_model = palm2_embedding_generator_model.to_gbq(
-        f"{dataset_id}.temp_embedding_model", replace=True
-    )
-    assert f"{dataset_id}.temp_embedding_model" == reloaded_model._bqml_model.model_name
-    assert reloaded_model.model_name == "textembedding-gecko"
-    assert reloaded_model.connection_name == bq_connection
-
-
-def test_create_embedding_generator_model_002(
-    palm2_embedding_generator_model_002, dataset_id, bq_connection
-):
-    # Model creation doesn't return error
-    assert palm2_embedding_generator_model_002 is not None
-    assert palm2_embedding_generator_model_002._bqml_model is not None
-
-    # save, load to ensure configuration was kept
-    reloaded_model = palm2_embedding_generator_model_002.to_gbq(
-        f"{dataset_id}.temp_embedding_model", replace=True
-    )
-    assert f"{dataset_id}.temp_embedding_model" == reloaded_model._bqml_model.model_name
-    assert reloaded_model.model_name == "textembedding-gecko"
-    assert reloaded_model.version == "002"
-    assert reloaded_model.connection_name == bq_connection
-
-
-def test_create_embedding_generator_multilingual_model(
-    palm2_embedding_generator_multilingual_model,
-    dataset_id,
-    bq_connection,
-):
-    # Model creation doesn't return error
-    assert palm2_embedding_generator_multilingual_model is not None
-    assert palm2_embedding_generator_multilingual_model._bqml_model is not None
-
-    # save, load to ensure configuration was kept
-    reloaded_model = palm2_embedding_generator_multilingual_model.to_gbq(
-        f"{dataset_id}.temp_embedding_model", replace=True
-    )
-    assert f"{dataset_id}.temp_embedding_model" == reloaded_model._bqml_model.model_name
-    assert reloaded_model.model_name == "textembedding-gecko-multilingual"
-    assert reloaded_model.connection_name == bq_connection
-
-
-def test_create_text_embedding_generator_model_defaults(bq_connection):
-    import bigframes.pandas as bpd
-
-    # Note: This starts a thread-local session.
-    with bpd.option_context(
-        "bigquery.bq_connection",
-        bq_connection,
-        "bigquery.location",
-        "US",
-    ):
-        model = llm.PaLM2TextEmbeddingGenerator()
-        assert model is not None
-        assert model._bqml_model is not None
-
-
-def test_create_text_embedding_generator_multilingual_model_defaults(bq_connection):
-    import bigframes.pandas as bpd
-
-    # Note: This starts a thread-local session.
-    with bpd.option_context(
-        "bigquery.bq_connection",
-        bq_connection,
-        "bigquery.location",
-        "US",
-    ):
-        model = llm.PaLM2TextEmbeddingGenerator(
-            model_name="textembedding-gecko-multilingual"
-        )
-        assert model is not None
-        assert model._bqml_model is not None
-
-
-@pytest.mark.flaky(retries=2)
-def test_embedding_generator_predict_success(
-    palm2_embedding_generator_model, llm_text_df
-):
-    df = palm2_embedding_generator_model.predict(llm_text_df).to_pandas()
-    assert df.shape == (3, 4)
-    assert "text_embedding" in df.columns
-    series = df["text_embedding"]
-    value = series[0]
-    assert len(value) == 768
-
-
-@pytest.mark.flaky(retries=2)
-def test_embedding_generator_multilingual_predict_success(
-    palm2_embedding_generator_multilingual_model, llm_text_df
-):
-    df = palm2_embedding_generator_multilingual_model.predict(llm_text_df).to_pandas()
-    assert df.shape == (3, 4)
-    assert "text_embedding" in df.columns
-    series = df["text_embedding"]
-    value = series[0]
-    assert len(value) == 768
-
-
-@pytest.mark.flaky(retries=2)
-def test_embedding_generator_predict_series_success(
-    palm2_embedding_generator_model, llm_text_df
-):
-    df = palm2_embedding_generator_model.predict(llm_text_df["prompt"]).to_pandas()
-    assert df.shape == (3, 4)
-    assert "text_embedding" in df.columns
-    series = df["text_embedding"]
-    value = series[0]
-    assert len(value) == 768
-
-
 @pytest.mark.parametrize(
     "model_name",
     ("text-embedding-004", "text-multilingual-embedding-002"),