feat(genai): Multiple updates to improve samples quality, consistency and readability (#13157)

* feat(genai): Update Gen AI SDK Samples for Consistency/Readability

- Updated to latest SDK version
- Added Typing and consistent imports
- Changed all GA Samples to include `HttpOptions` for `v1` endpoint
- Updated Gemini 2.0 Exp to Gemini 2.0 Flash GA
- Updated Batch Prediction to Gemini 2.0 GA

* Fix issue with PIL Image load

* Rename BatchPredict Files

Author: holtskinner

genai/batch_prediction/submit_with_bq.py …batch_prediction/batchpredict_with_bq.pygenai/batch_prediction/submit_with_bq.py renamed to genai/batch_prediction/batchpredict_with_bq.py genai/batch_prediction/submit_with_bq.py renamed to genai/batch_prediction/batchpredict_with_bq.py

@@ -18,17 +18,17 @@ def generate_content(output_uri: str) -> str:
     import time
 
     from google import genai
+    from google.genai.types import CreateBatchJobConfig, JobState, HttpOptions
+
+    client = genai.Client(http_options=HttpOptions(api_version="v1"))
 
-    client = genai.Client()
     # TODO(developer): Update and un-comment below line
     # output_uri = f"bq://your-project.your_dataset.your_table"
 
     job = client.batches.create(
-        model="gemini-1.5-pro-002",
+        model="gemini-2.0-flash-001",
         src="bq://storage-samples.generative_ai.batch_requests_for_multimodal_input",
-        config={
-            "dest": output_uri
-        }
+        config=CreateBatchJobConfig(dest=output_uri),
     )
     print(f"Job name: {job.name}")
     print(f"Job state: {job.state}")
@@ -37,12 +37,13 @@ def generate_content(output_uri: str) -> str:
     # Job state: JOB_STATE_PENDING
 
     # See the documentation: https://googleapis.github.io/python-genai/genai.html#genai.types.BatchJob
-    completed_states = [
-        "JOB_STATE_SUCCEEDED",
-        "JOB_STATE_FAILED",
-        "JOB_STATE_CANCELLED",
-        "JOB_STATE_PAUSED",
-    ]
+    completed_states = {
+        JobState.JOB_STATE_SUCCEEDED,
+        JobState.JOB_STATE_FAILED,
+        JobState.JOB_STATE_CANCELLED,
+        JobState.JOB_STATE_PAUSED,
+    }
+
     while job.state not in completed_states:
         time.sleep(30)
         job = client.batches.get(name=job.name)
@@ -59,6 +60,4 @@ def generate_content(output_uri: str) -> str:
 
 
 if __name__ == "__main__":
-    generate_content(
-        output_uri="bq://your-project.your_dataset.your_table"
-    )
+    generate_content(output_uri="bq://your-project.your_dataset.your_table")

genai/batch_prediction/submit_with_gcs.py …atch_prediction/batchpredict_with_gcs.pygenai/batch_prediction/submit_with_gcs.py renamed to genai/batch_prediction/batchpredict_with_gcs.py genai/batch_prediction/submit_with_gcs.py renamed to genai/batch_prediction/batchpredict_with_gcs.py

@@ -18,19 +18,18 @@ def generate_content(output_uri: str) -> str:
     import time
 
     from google import genai
+    from google.genai.types import CreateBatchJobConfig, JobState, HttpOptions
 
-    client = genai.Client()
+    client = genai.Client(http_options=HttpOptions(api_version="v1"))
     # TODO(developer): Update and un-comment below line
     # output_uri = "gs://your-bucket/your-prefix"
 
     # See the documentation: https://googleapis.github.io/python-genai/genai.html#genai.batches.Batches.create
     job = client.batches.create(
-        model="gemini-1.5-pro-002",
+        model="gemini-2.0-flash-001",
         # Source link: https://storage.cloud.google.com/cloud-samples-data/batch/prompt_for_batch_gemini_predict.jsonl
         src="gs://cloud-samples-data/batch/prompt_for_batch_gemini_predict.jsonl",
-        config={
-            "dest": output_uri
-        }
+        config=CreateBatchJobConfig(dest=output_uri),
     )
     print(f"Job name: {job.name}")
     print(f"Job state: {job.state}")
@@ -39,12 +38,13 @@ def generate_content(output_uri: str) -> str:
     # Job state: JOB_STATE_PENDING
 
     # See the documentation: https://googleapis.github.io/python-genai/genai.html#genai.types.BatchJob
-    completed_states = [
-        "JOB_STATE_SUCCEEDED",
-        "JOB_STATE_FAILED",
-        "JOB_STATE_CANCELLED",
-        "JOB_STATE_PAUSED",
-    ]
+    completed_states = {
+        JobState.JOB_STATE_SUCCEEDED,
+        JobState.JOB_STATE_FAILED,
+        JobState.JOB_STATE_CANCELLED,
+        JobState.JOB_STATE_PAUSED,
+    }
+
     while job.state not in completed_states:
         time.sleep(30)
         job = client.batches.get(name=job.name)
@@ -61,6 +61,4 @@ def generate_content(output_uri: str) -> str:
 
 
 if __name__ == "__main__":
-    generate_content(
-        output_uri="gs://your-bucket/your-prefix"
-    )
+    generate_content(output_uri="gs://your-bucket/your-prefix")

genai/batch_prediction/requirements.txt

@@ -1 +1 @@
-google-genai==0.8.0
+google-genai==1.2.0

genai/batch_prediction/test_batch_predict.py

@@ -20,8 +20,8 @@
 
 import pytest
 
-import submit_with_bq
-import submit_with_gcs
+import batchpredict_with_bq
+import batchpredict_with_gcs
 
 
 os.environ["GOOGLE_GENAI_USE_VERTEXAI"] = "True"
@@ -57,10 +57,10 @@ def gcs_output_uri():
 
 
 def test_batch_prediction_with_bq(bq_output_uri) -> None:
-    response = submit_with_bq.generate_content(output_uri=bq_output_uri)
+    response = batchpredict_with_bq.generate_content(output_uri=bq_output_uri)
     assert response == JobState.JOB_STATE_SUCCEEDED
 
 
 def test_batch_prediction_with_gcs(gcs_output_uri) -> None:
-    response = submit_with_gcs.generate_content(output_uri=gcs_output_uri)
+    response = batchpredict_with_gcs.generate_content(output_uri=gcs_output_uri)
     assert response == JobState.JOB_STATE_SUCCEEDED

genai/controlled_generation/ctrlgen_with_class_schema.py

@@ -16,23 +16,27 @@
 def generate_content() -> str:
     # [START googlegenaisdk_ctrlgen_with_class_schema]
     from google import genai
+    from google.genai.types import GenerateContentConfig, HttpOptions
+
     from pydantic import BaseModel
 
     class Recipe(BaseModel):
         recipe_name: str
         ingredients: list[str]
 
-    client = genai.Client()
+    client = genai.Client(http_options=HttpOptions(api_version="v1"))
     response = client.models.generate_content(
         model="gemini-2.0-flash-001",
         contents="List a few popular cookie recipes.",
-        config={
-            "response_mime_type": "application/json",
-            "response_schema": list[Recipe],
-        },
+        config=GenerateContentConfig(
+            response_mime_type="application/json",
+            response_schema=list[Recipe],
+        ),
     )
     # Use the response as a JSON string.
     print(response.text)
+    # Use the response as an object
+    print(response.parsed)
 
     # Example output:
     # [Recipe(recipe_name='Chocolate Chip Cookies', ingredients=['2 1/4 cups all-purpose flour'

genai/controlled_generation/ctrlgen_with_enum_schema.py

@@ -16,18 +16,19 @@
 def generate_content() -> str:
     # [START googlegenaisdk_ctrlgen_with_enum_schema]
     from google import genai
+    from google.genai.types import GenerateContentConfig, HttpOptions
 
-    client = genai.Client()
+    client = genai.Client(http_options=HttpOptions(api_version="v1"))
     response = client.models.generate_content(
         model="gemini-2.0-flash-001",
         contents="What type of instrument is an oboe?",
-        config={
-            "response_mime_type": "text/x.enum",
-            "response_schema": {
+        config=GenerateContentConfig(
+            response_mime_type="text/x.enum",
+            response_schema={
                 "type": "STRING",
                 "enum": ["Percussion", "String", "Woodwind", "Brass", "Keyboard"],
             },
-        },
+        ),
     )
 
     print(response.text)

genai/controlled_generation/ctrlgen_with_nested_class_schema.py

@@ -15,9 +15,11 @@
 
 def generate_content() -> str:
     # [START googlegenaisdk_ctrlgen_with_nested_class_schema]
+    import enum
+
     from google import genai
+    from google.genai.types import GenerateContentConfig, HttpOptions
 
-    import enum
     from pydantic import BaseModel
 
     class Grade(enum.Enum):
@@ -32,14 +34,14 @@ class Recipe(BaseModel):
         recipe_name: str
         rating: Grade
 
-    client = genai.Client()
+    client = genai.Client(http_options=HttpOptions(api_version="v1"))
     response = client.models.generate_content(
         model="gemini-2.0-flash-001",
         contents="List about 10 home-baked cookies and give them grades based on tastiness.",
-        config={
-            "response_mime_type": "application/json",
-            "response_schema": list[Recipe],
-        },
+        config=GenerateContentConfig(
+            response_mime_type="application/json",
+            response_schema=list[Recipe],
+        ),
     )
 
     print(response.text)

genai/controlled_generation/ctrlgen_with_nullable_schema.py

@@ -16,6 +16,7 @@
 def generate_content() -> str:
     # [START googlegenaisdk_ctrlgen_with_nullable_schema]
     from google import genai
+    from google.genai.types import GenerateContentConfig, HttpOptions
 
     response_schema = {
         "type": "OBJECT",
@@ -48,14 +49,14 @@ def generate_content() -> str:
         Finally, Saturday rounds off the week with sunny skies, a temperature of 80°F, and a humidity level of 40%. Winds will be gentle at 8 km/h.
     """
 
-    client = genai.Client()
+    client = genai.Client(http_options=HttpOptions(api_version="v1"))
     response = client.models.generate_content(
         model="gemini-2.0-flash-001",
         contents=prompt,
-        config={
-            "response_mime_type": "application/json",
-            "response_schema": response_schema,
-        },
+        config=GenerateContentConfig(
+            response_mime_type="application/json",
+            response_schema=response_schema,
+        ),
     )
 
     print(response.text)

genai/controlled_generation/requirements.txt

@@ -0,0 +1 @@
+google-genai==1.2.0

genai/text_generation/requirements.txt

@@ -1 +1 @@
-google-genai==1.0.0
+google-genai==1.2.0