chore: split Multimodal snippets (#1683)

Author: GarrettWu

samples/snippets/multimodal_test.py

@@ -77,7 +77,7 @@ def test_multimodal_dataframe(gcs_dst_bucket: str) -> None:
     df_image
     # [END bigquery_dataframes_multimodal_dataframe_image_transform]
 
-    # [START bigquery_dataframes_multimodal_dataframe_ai]
+    # [START bigquery_dataframes_multimodal_dataframe_ml_text]
     from bigframes.ml import llm
 
     gemini = llm.GeminiTextGenerator(model_name="gemini-1.5-flash-002")
@@ -89,7 +89,9 @@ def test_multimodal_dataframe(gcs_dst_bucket: str) -> None:
     df_image = df_image.head(2)
     answer = gemini.predict(df_image, prompt=["what item is it?", df_image["image"]])
     answer[["ml_generate_text_llm_result", "image"]]
+    # [END bigquery_dataframes_multimodal_dataframe_ml_text]
 
+    # [START bigquery_dataframes_multimodal_dataframe_ml_text_alt]
     # Ask different questions
     df_image["question"] = [  # type: ignore
         "what item is it?",
@@ -99,12 +101,14 @@ def test_multimodal_dataframe(gcs_dst_bucket: str) -> None:
         df_image, prompt=[df_image["question"], df_image["image"]]
     )
     answer_alt[["ml_generate_text_llm_result", "image"]]
+    # [END bigquery_dataframes_multimodal_dataframe_ml_text_alt]
 
+    # [START bigquery_dataframes_multimodal_dataframe_ml_embed]
     # Generate embeddings on images
     embed_model = llm.MultimodalEmbeddingGenerator()
     embeddings = embed_model.predict(df_image["image"])
     embeddings
-    # [END bigquery_dataframes_multimodal_dataframe_ai]
+    # [END bigquery_dataframes_multimodal_dataframe_ml_embed]
 
     # [START bigquery_dataframes_multimodal_dataframe_pdf_chunk]
     # PDF chunking