feat(genai): Add http_params to Text Generation doc samples (#13138)

* feat(genai): Add Tool examples

* Code execution example
* Function Calling example
* Grounding with Google Search example

* fix(genai): Linter suggestion

* feat(genai): Add region tags

* feat(genai): Update http flag for TextGeneration samples.

* Update genai/text_generation/requirements.txt

Co-authored-by: Holt Skinner <13262395+holtskinner@users.noreply.github.com>

* Update pillow package version

* Fixing bug from merge conflict

* update package version

---------

Co-authored-by: Holt Skinner <13262395+holtskinner@users.noreply.github.com>
Co-authored-by: Sita Lakshmi Sangameswaran <sitalakshmi@google.com>

Author: 3 people

genai/template_folder/requirements.txt

@@ -1,14 +1,14 @@
-pandas==1.3.5; python_version == '3.7'
-pandas==2.0.3; python_version == '3.8'
-pandas==2.1.4; python_version > '3.8'
-pillow==10.3.0; python_version < '3.8'
-pillow==10.3.0; python_version >= '3.8'
-google-cloud-aiplatform[all]==1.69.0
-sentencepiece==0.2.0
-google-auth==2.38.0
-anthropic[vertex]==0.28.0
-langchain-core==0.2.33
-langchain-google-vertexai==1.0.10
-numpy<2
-openai==1.30.5
-immutabledict==4.2.0
+# pandas==1.3.5; python_version == '3.7'
+# pandas==2.0.3; python_version == '3.8'
+# pandas==2.1.4; python_version > '3.8'
+# pillow==10.3.0; python_version < '3.8'
+# pillow==10.3.0; python_version >= '3.8'
+# google-cloud-aiplatform[all]==1.69.0
+# sentencepiece==0.2.0
+# google-auth==2.29.0
+# anthropic[vertex]==0.28.0
+# langchain-core==0.2.33
+# langchain-google-vertexai==1.0.10
+# numpy<2
+# openai==1.30.5
+# immutabledict==4.2.0

genai/text_generation/requirements.txt

@@ -1 +1 @@
-google-genai==0.8.0
+google-genai==1.0.0

genai/text_generation/textgen_chat_stream_with_txt.py

@@ -17,7 +17,7 @@ def generate_content() -> str:
     # [START googlegenaisdk_textgen_chat_stream_with_txt]
     from google import genai
 
-    client = genai.Client()
+    client = genai.Client(http_options={'api_version': 'v1'})
     chat = client.chats.create(model="gemini-2.0-flash-001")
     response_text = ""
 

genai/text_generation/textgen_chat_with_txt.py

@@ -18,7 +18,7 @@ def generate_content() -> str:
     from google import genai
     from google.genai.types import Content, Part
 
-    client = genai.Client()
+    client = genai.Client(http_options={'api_version': 'v1'})
     chat = client.chats.create(
         model="gemini-2.0-flash-001",
         history=[

genai/text_generation/textgen_config_with_txt.py

@@ -18,7 +18,7 @@ def generate_content() -> str:
     from google import genai
     from google.genai import types
 
-    client = genai.Client()
+    client = genai.Client(http_options={'api_version': 'v1'})
     response = client.models.generate_content(
         model="gemini-2.0-flash-001",
         contents="Why is the sky blue?",

genai/text_generation/textgen_sys_instr_with_txt.py

@@ -18,7 +18,7 @@ def generate_content() -> str:
     from google import genai
     from google.genai import types
 
-    client = genai.Client()
+    client = genai.Client(http_options={'api_version': 'v1'})
     response = client.models.generate_content(
         model="gemini-2.0-flash-001",
         contents="Why is the sky blue?",

genai/text_generation/textgen_transcript_with_gcs_audio.py

@@ -18,8 +18,7 @@ def generate_content() -> str:
     from google import genai
     from google.genai.types import Part
 
-    client = genai.Client()
-
+    client = genai.Client(http_options={'api_version': 'v1'})
     prompt = """
     Transcribe the interview, in the format of timecode, speaker, caption.
     Use speaker A, speaker B, etc. to identify speakers.

genai/text_generation/textgen_with_gcs_audio.py

@@ -18,8 +18,7 @@ def generate_content() -> str:
     from google import genai
     from google.genai.types import Part
 
-    client = genai.Client()
-
+    client = genai.Client(http_options={'api_version': 'v1'})
     prompt = """
     Provide the summary of the audio file.
     Summarize the main points of the audio concisely.

genai/text_generation/textgen_with_multi_img.py

@@ -18,7 +18,7 @@ def generate_content() -> str:
     from google import genai
     from google.genai.types import Part
 
-    client = genai.Client()
+    client = genai.Client(http_options={'api_version': 'v1'})
 
     # Read content from GCS
     gcs_file_img_path = "gs://cloud-samples-data/generative-ai/image/scones.jpg"
@@ -30,21 +30,20 @@ def generate_content() -> str:
     response = client.models.generate_content(
         model="gemini-2.0-flash-001",
         contents=[
-            "Write an advertising jingle based on the items in both images.",
+            "Generate a list of all the objects contained in both images.",
             Part.from_uri(
                 file_uri=gcs_file_img_path,
-                mime_type="image/jpeg",
+                mime_type="image/jpeg"
             ),
             Part.from_bytes(
                 data=local_file_img_bytes,
-                mime_type="image/jpeg",
-            ),
-        ],
+                mime_type="image/jpeg"
+            )
+        ]
     )
     print(response.text)
     # Example response:
-    # Okay, here's an advertising jingle based on the blueberry scones, coffee, and
-    #  flowers from the first image, and the cake and latte in the second image:
+    # Okay, here's the list of objects present in both images:
     # ...
     # [END googlegenaisdk_textgen_with_multi_img]
     return response.text

genai/text_generation/textgen_with_multi_local_img.py

@@ -18,8 +18,7 @@ def generate_content(image_path_1: str, image_path_2: str) -> str:
     from google import genai
     from google.genai.types import Part
 
-    client = genai.Client()
-
+    client = genai.Client(http_options={'api_version': 'v1'})
     # TODO(Developer): Update the below file paths to your images
     # image_path_1 = "path/to/your/image1.jpg"
     # image_path_2 = "path/to/your/image2.jpg"