chore: deprecated Claude 3.5 sonnet for TextGenerator

Author: sycai

bigframes/ml/llm.py

@@ -877,7 +877,7 @@ class Claude3TextGenerator(base.RetriableRemotePredictor):
             The model for natural language tasks. Possible values are "claude-3-sonnet", "claude-3-haiku", "claude-3-5-sonnet" and "claude-3-opus".
             "claude-3-sonnet" (deprecated) is Anthropic's dependable combination of skills and speed. It is engineered to be dependable for scaled AI deployments across a variety of use cases.
             "claude-3-haiku" is Anthropic's fastest, most compact vision and text model for near-instant responses to simple queries, meant for seamless AI experiences mimicking human interactions.
-            "claude-3-5-sonnet" is Anthropic's most powerful AI model and maintains the speed and cost of Claude 3 Sonnet, which is a mid-tier model.
+            "claude-3-5-sonnet" (deprecated) is Anthropic's most powerful AI model and maintains the speed and cost of Claude 3 Sonnet, which is a mid-tier model.
             "claude-3-opus" (deprecated) is Anthropic's second-most powerful AI model, with strong performance on highly complex tasks.
             https://cloud.google.com/vertex-ai/generative-ai/docs/partner-models/use-claude#available-claude-models
             If no setting is provided, "claude-3-sonnet" will be used by default

tests/system/load/test_llm.py

@@ -98,18 +98,10 @@ def test_llm_gemini_w_ground_with_google_search(llm_remote_text_df):
 
 
 # (b/366290533): Claude models are of extremely low capacity. The tests should reside in small tests. Moving these here just to protect BQML's shared capacity(as load test only runs once per day.) and make sure we still have minimum coverage.
-@pytest.mark.parametrize(
-    "model_name",
-    ("claude-3-haiku", "claude-3-5-sonnet"),
-)
 @pytest.mark.flaky(retries=3, delay=120)
-def test_claude3_text_generator_create_load(
-    dataset_id, model_name, session, session_us_east5, bq_connection
-):
-    if model_name in ("claude-3-5-sonnet",):
-        session = session_us_east5
+def test_claude3_text_generator_create_load(dataset_id, session, bq_connection):
     claude3_text_generator_model = llm.Claude3TextGenerator(
-        model_name=model_name, connection_name=bq_connection, session=session
+        model_name="claude-3-haiku", connection_name=bq_connection, session=session
     )
     assert claude3_text_generator_model is not None
     assert claude3_text_generator_model._bqml_model is not None
@@ -120,40 +112,28 @@ def test_claude3_text_generator_create_load(
     )
     assert f"{dataset_id}.temp_text_model" == reloaded_model._bqml_model.model_name
     assert reloaded_model.connection_name == bq_connection
-    assert reloaded_model.model_name == model_name
+    assert reloaded_model.model_name == "claude-3-haiku"
 
 
-@pytest.mark.parametrize(
-    "model_name",
-    ("claude-3-haiku", "claude-3-5-sonnet"),
-)
 @pytest.mark.flaky(retries=3, delay=120)
 def test_claude3_text_generator_predict_default_params_success(
-    llm_text_df, model_name, session, session_us_east5, bq_connection
+    llm_text_df, session, bq_connection
 ):
-    if model_name in ("claude-3-5-sonnet",):
-        session = session_us_east5
     claude3_text_generator_model = llm.Claude3TextGenerator(
-        model_name=model_name, connection_name=bq_connection, session=session
+        model_name="claude-3-haiku", connection_name=bq_connection, session=session
     )
     df = claude3_text_generator_model.predict(llm_text_df).to_pandas()
     utils.check_pandas_df_schema_and_index(
         df, columns=utils.ML_GENERATE_TEXT_OUTPUT, index=3, col_exact=False
     )
 
 
-@pytest.mark.parametrize(
-    "model_name",
-    ("claude-3-haiku", "claude-3-5-sonnet"),
-)
 @pytest.mark.flaky(retries=3, delay=120)
 def test_claude3_text_generator_predict_with_params_success(
-    llm_text_df, model_name, session, session_us_east5, bq_connection
+    llm_text_df, session, bq_connection
 ):
-    if model_name in ("claude-3-5-sonnet",):
-        session = session_us_east5
     claude3_text_generator_model = llm.Claude3TextGenerator(
-        model_name=model_name, connection_name=bq_connection, session=session
+        model_name="claude-3-haiku", connection_name=bq_connection, session=session
     )
     df = claude3_text_generator_model.predict(
         llm_text_df, max_output_tokens=100, top_k=20, top_p=0.5
@@ -163,20 +143,14 @@ def test_claude3_text_generator_predict_with_params_success(
     )
 
 
-@pytest.mark.parametrize(
-    "model_name",
-    ("claude-3-haiku", "claude-3-5-sonnet"),
-)
 @pytest.mark.flaky(retries=3, delay=120)
 def test_claude3_text_generator_predict_multi_col_success(
-    llm_text_df, model_name, session, session_us_east5, bq_connection
+    llm_text_df, session, bq_connection
 ):
-    if model_name in ("claude-3-5-sonnet",):
-        session = session_us_east5
 
     llm_text_df["additional_col"] = 1
     claude3_text_generator_model = llm.Claude3TextGenerator(
-        model_name=model_name, connection_name=bq_connection, session=session
+        model_name="claude-3-haiku", connection_name=bq_connection, session=session
     )
     df = claude3_text_generator_model.predict(llm_text_df).to_pandas()
     utils.check_pandas_df_schema_and_index(