From 95b018a57ffd73b29911fd097a4c6e26d6ff51dd Mon Sep 17 00:00:00 2001 From: Shuowei Li Date: Tue, 2 Jun 2026 22:08:49 +0000 Subject: [PATCH] test: use gemini-2.5-pro for ai accessor doctests --- packages/bigframes/bigframes/operations/ai.py | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/packages/bigframes/bigframes/operations/ai.py b/packages/bigframes/bigframes/operations/ai.py index c5cc08ae976f..c1c5164e9065 100644 --- a/packages/bigframes/bigframes/operations/ai.py +++ b/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']})