feat: add Gemini 1.5 stable models support (#945)

* feat: add Gemini 1.5 stable models support

* add to loader

Author: GarrettWu

bigframes/ml/llm.py

@@ -55,10 +55,14 @@
 _GEMINI_PRO_ENDPOINT = "gemini-pro"
 _GEMINI_1P5_PRO_PREVIEW_ENDPOINT = "gemini-1.5-pro-preview-0514"
 _GEMINI_1P5_PRO_FLASH_PREVIEW_ENDPOINT = "gemini-1.5-flash-preview-0514"
+_GEMINI_1P5_PRO_001_ENDPOINT = "gemini-1.5-pro-001"
+_GEMINI_1P5_FLASH_001_ENDPOINT = "gemini-1.5-flash-001"
 _GEMINI_ENDPOINTS = (
     _GEMINI_PRO_ENDPOINT,
     _GEMINI_1P5_PRO_PREVIEW_ENDPOINT,
     _GEMINI_1P5_PRO_FLASH_PREVIEW_ENDPOINT,
+    _GEMINI_1P5_PRO_001_ENDPOINT,
+    _GEMINI_1P5_FLASH_001_ENDPOINT,
 )
 
 _CLAUDE_3_SONNET_ENDPOINT = "claude-3-sonnet"
@@ -728,7 +732,7 @@ class GeminiTextGenerator(base.BaseEstimator):
 
     Args:
         model_name (str, Default to "gemini-pro"):
-            The model for natural language tasks. Accepted values are "gemini-pro", "gemini-1.5-pro-preview-0514" and "gemini-1.5-flash-preview-0514". Default to "gemini-pro".
+            The model for natural language tasks. Accepted values are "gemini-pro", "gemini-1.5-pro-preview-0514", "gemini-1.5-flash-preview-0514", "gemini-1.5-pro-001" and "gemini-1.5-flash-001". Default to "gemini-pro".
 
         .. note::
             "gemini-1.5-pro-preview-0514" and "gemini-1.5-flash-preview-0514" is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the
@@ -750,7 +754,11 @@ def __init__(
         self,
         *,
         model_name: Literal[
-            "gemini-pro", "gemini-1.5-pro-preview-0514", "gemini-1.5-flash-preview-0514"
+            "gemini-pro",
+            "gemini-1.5-pro-preview-0514",
+            "gemini-1.5-flash-preview-0514",
+            "gemini-1.5-pro-001",
+            "gemini-1.5-flash-001",
         ] = "gemini-pro",
         session: Optional[bigframes.Session] = None,
         connection_name: Optional[str] = None,

bigframes/ml/loader.py

@@ -63,6 +63,8 @@
         llm._GEMINI_PRO_ENDPOINT: llm.GeminiTextGenerator,
         llm._GEMINI_1P5_PRO_PREVIEW_ENDPOINT: llm.GeminiTextGenerator,
         llm._GEMINI_1P5_PRO_FLASH_PREVIEW_ENDPOINT: llm.GeminiTextGenerator,
+        llm._GEMINI_1P5_PRO_001_ENDPOINT: llm.GeminiTextGenerator,
+        llm._GEMINI_1P5_FLASH_001_ENDPOINT: llm.GeminiTextGenerator,
         llm._CLAUDE_3_HAIKU_ENDPOINT: llm.Claude3TextGenerator,
         llm._CLAUDE_3_SONNET_ENDPOINT: llm.Claude3TextGenerator,
         llm._CLAUDE_3_5_SONNET_ENDPOINT: llm.Claude3TextGenerator,

tests/system/small/ml/test_llm.py

@@ -324,7 +324,7 @@ def test_create_load_text_embedding_generator_model(
     ("text-embedding-004", "text-multilingual-embedding-002"),
 )
 @pytest.mark.flaky(retries=2)
-def test_gemini_text_embedding_generator_predict_default_params_success(
+def test_text_embedding_generator_predict_default_params_success(
     llm_text_df, model_name, session, bq_connection
 ):
     text_embedding_model = llm.TextEmbeddingGenerator(
@@ -340,7 +340,13 @@ def test_gemini_text_embedding_generator_predict_default_params_success(
 
 @pytest.mark.parametrize(
     "model_name",
-    ("gemini-pro", "gemini-1.5-pro-preview-0514", "gemini-1.5-flash-preview-0514"),
+    (
+        "gemini-pro",
+        "gemini-1.5-pro-preview-0514",
+        "gemini-1.5-flash-preview-0514",
+        "gemini-1.5-pro-001",
+        "gemini-1.5-flash-001",
+    ),
 )
 def test_create_load_gemini_text_generator_model(
     dataset_id, model_name, session, bq_connection
@@ -362,7 +368,13 @@ def test_create_load_gemini_text_generator_model(
 
 @pytest.mark.parametrize(
     "model_name",
-    ("gemini-pro", "gemini-1.5-pro-preview-0514", "gemini-1.5-flash-preview-0514"),
+    (
+        "gemini-pro",
+        "gemini-1.5-pro-preview-0514",
+        "gemini-1.5-flash-preview-0514",
+        "gemini-1.5-pro-001",
+        "gemini-1.5-flash-001",
+    ),
 )
 @pytest.mark.flaky(retries=2)
 def test_gemini_text_generator_predict_default_params_success(
@@ -379,7 +391,13 @@ def test_gemini_text_generator_predict_default_params_success(
 
 @pytest.mark.parametrize(
     "model_name",
-    ("gemini-pro", "gemini-1.5-pro-preview-0514", "gemini-1.5-flash-preview-0514"),
+    (
+        "gemini-pro",
+        "gemini-1.5-pro-preview-0514",
+        "gemini-1.5-flash-preview-0514",
+        "gemini-1.5-pro-001",
+        "gemini-1.5-flash-001",
+    ),
 )
 @pytest.mark.flaky(retries=2)
 def test_gemini_text_generator_predict_with_params_success(