add predict tests

tests/system/conftest.py

@@ -550,6 +550,20 @@ def llm_fine_tune_df_default_index(
     return session.read_gbq(sql)
 
 
+@pytest.fixture(scope="session")
+def llm_remote_text_pandas_df():
+    """Additional data matching the penguins dataset, with a new index"""
+    return pd.DataFrame(
+        {
+            "prompt": [
+                "Please do sentiment analysis on the following text and only output a number from 0 to 5where 0 means sadness, 1 means joy, 2 means love, 3 means anger, 4 means fear, and 5 means surprise. Text: i feel beautifully emotional knowing that these women of whom i knew just a handful were holding me and my baba on our journey",
+                "Please do sentiment analysis on the following text and only output a number from 0 to 5 where 0 means sadness, 1 means joy, 2 means love, 3 means anger, 4 means fear, and 5 means surprise. Text: i was feeling a little vain when i did this one",
+                "Please do sentiment analysis on the following text and only output a number from 0 to 5 where 0 means sadness, 1 means joy, 2 means love, 3 means anger, 4 means fear, and 5 means surprise. Text: a father of children killed in an accident",
+            ],
+        }
+    )
+
+
 @pytest.fixture(scope="session")
 def time_series_df_default_index(
     time_series_table_id: str, session: bigframes.Session

tests/system/load/test_llm.py

@@ -15,7 +15,9 @@
 import bigframes.ml.llm
 
 
-def test_llm_palm_configure_fit(llm_fine_tune_df_default_index, dataset_id):
+def test_llm_palm_configure_fit(
+    llm_fine_tune_df_default_index, llm_remote_text_pandas_df
+):
     model = bigframes.ml.llm.PaLM2TextGenerator(
         model_name="text-bison", max_iterations=1, evaluation_task="CLASSIFICATION"
     )
@@ -25,12 +27,12 @@ def test_llm_palm_configure_fit(llm_fine_tune_df_default_index, dataset_id):
     y_train = df[["label"]]
     model.fit(X_train, y_train)
 
-    # save, load, check parameters to ensure configuration was kept
-    reloaded_model = model.to_gbq(
-        f"{dataset_id}.temp_configured_palm_model", replace=True
-    )
-    assert (
-        f"{dataset_id}.temp_configured_palm_model"
-        in reloaded_model._bqml_model.model_name
-    )
-    assert reloaded_model.evaluation_task == "CLASSIFICATION"
+    assert model is not None
+
+    df = model.predict(llm_remote_text_pandas_df).to_pandas()
+    assert df.shape == (3, 4)
+    assert "ml_generate_text_llm_result" in df.columns
+    series = df["ml_generate_text_llm_result"]
+    assert all(series.str.len() == 1)
+
+    # TODO(ashleyxu): After bqml rolled out version control: save, load, check parameters to ensure configuration was kept

tests/system/small/ml/conftest.py

@@ -232,18 +232,6 @@ def palm2_text_generator_model(session, bq_connection) -> llm.PaLM2TextGenerator
     return llm.PaLM2TextGenerator(session=session, connection_name=bq_connection)
 
 
-@pytest.fixture(scope="session")
-def palm2_text_generator_fine_tune_model(
-    session, bq_connection
-) -> llm.PaLM2TextGenerator:
-    return llm.PaLM2TextGenerator(
-        session=session,
-        connection_name=bq_connection,
-        max_iterations=300,
-        evaluation_task="TEXT_GENERATION",
-    )
-
-
 @pytest.fixture(scope="session")
 def palm2_text_generator_32k_model(session, bq_connection) -> llm.PaLM2TextGenerator:
     return llm.PaLM2TextGenerator(