test: use gemini-2.5-pro for ai accessor doctests (googleapis#17354)

Fixes #<519296335> 🦕

Author: shuoweil

packages/bigframes/bigframes/operations/ai.py

@@ -50,7 +50,7 @@ def filter(
             >>> bpd.options.compute.ai_ops_confirmation_threshold = 25
 
             >>> import bigframes.ml.llm as llm
-            >>> model = llm.GeminiTextGenerator(model_name="gemini-2.0-flash-001")
+            >>> model = llm.GeminiTextGenerator(model_name="gemini-2.5-pro")
 
             >>> df = bpd.DataFrame({"country": ["USA", "Germany"], "city": ["Seattle", "Berlin"]})
             >>> df.ai.filter("{city} is the capital of {country}", model)
@@ -119,7 +119,7 @@ def map(
             >>> bpd.options.compute.ai_ops_confirmation_threshold = 25
 
             >>> import bigframes.ml.llm as llm
-            >>> model = llm.GeminiTextGenerator(model_name="gemini-2.0-flash-001")
+            >>> model = llm.GeminiTextGenerator(model_name="gemini-2.5-pro")
 
             >>> df = bpd.DataFrame({"ingredient_1": ["Burger Bun", "Soy Bean"], "ingredient_2": ["Beef Patty", "Bittern"]})
             >>> df.ai.map("What is the food made from {ingredient_1} and {ingredient_2}? One word only.", model=model, output_schema={"food": "string"})
@@ -137,7 +137,7 @@ def map(
             >>> bpd.options.compute.ai_ops_confirmation_threshold = 25
 
             >>> import bigframes.ml.llm as llm
-            >>> model = llm.GeminiTextGenerator(model_name="gemini-2.0-flash-001")
+            >>> model = llm.GeminiTextGenerator(model_name="gemini-2.5-pro")
 
             >>> df = bpd.DataFrame({"text": ["Elmo lives at 123 Sesame Street."]})
             >>> df.ai.map("{text}", model=model, output_schema={"person": "string", "address": "string"})
@@ -268,7 +268,7 @@ def classify(
             >>> bpd.options.compute.ai_ops_confirmation_threshold = 25
 
             >>> import bigframes.ml.llm as llm
-            >>> model = llm.GeminiTextGenerator(model_name="gemini-2.0-flash-001")
+            >>> model = llm.GeminiTextGenerator(model_name="gemini-2.5-pro")
 
             >>> df = bpd.DataFrame({
             ...     "feedback_text": [
@@ -357,7 +357,7 @@ def join(
             >>> bpd.options.compute.ai_ops_confirmation_threshold = 25
 
             >>> import bigframes.ml.llm as llm
-            >>> model = llm.GeminiTextGenerator(model_name="gemini-2.0-flash-001")
+            >>> model = llm.GeminiTextGenerator(model_name="gemini-2.5-pro")
 
             >>> cities = bpd.DataFrame({'city': ['Seattle', 'Ottawa', 'Berlin', 'Shanghai', 'New Delhi']})
             >>> continents = bpd.DataFrame({'continent': ['North America', 'Africa', 'Asia']})