refactor: Rename the Google API based bigquery sample agent

This change renames the sample agent based on the Google API based tools to reflect the larger purpose and avoid confusion with the built-in BigQuery tools. In addition, it also renames the root agent in the BigQuery sample agent to "bigquery_agent"

PiperOrigin-RevId: 775655226

Author: google-genai-bot

contributing/samples/bigquery/agent.py

@@ -60,7 +60,7 @@
 # debug CLI
 root_agent = llm_agent.Agent(
     model="gemini-2.0-flash",
-    name="hello_agent",
+    name="bigquery_agent",
     description=(
         "Agent to answer questions about BigQuery data and models and execute"
         " SQL queries."

contributing/samples/bigquery_agent/README.md renamed to contributing/samples/google_api/README.md

@@ -1,45 +1,40 @@
-# BigQuery Sample
+# Google API Tools Sample
 
 ## Introduction
 
-This sample tests and demos the BigQuery support in ADK via two tools:
+This sample tests and demos Google API tools available in the
+`google.adk.tools.google_api_tool` module. We pick the following BigQuery API
+tools for this sample agent:
 
-* 1. bigquery_datasets_list:
+1. `bigquery_datasets_list`: List user's datasets.
 
-    List user's datasets.
+2. `bigquery_datasets_get`: Get a dataset's details.
 
-* 2. bigquery_datasets_get:
-    Get a dataset's details.
+3. `bigquery_datasets_insert`: Create a new dataset.
 
-* 3. bigquery_datasets_insert:
-    Create a new dataset.
+4. `bigquery_tables_list`: List all tables in a dataset.
 
-* 4. bigquery_tables_list:
-    List all tables in a dataset.
+5. `bigquery_tables_get`: Get a table's details.
 
-* 5. bigquery_tables_get:
-    Get a table's details.
-
-* 6. bigquery_tables_insert:
-    Insert a new table into a dataset.
+6. `bigquery_tables_insert`: Insert a new table into a dataset.
 
 ## How to use
 
-* 1. Follow https://developers.google.com/identity/protocols/oauth2#1.-obtain-oauth-2.0-credentials-from-the-dynamic_data.setvar.console_name. to get your client id and client secret.
+1. Follow https://developers.google.com/identity/protocols/oauth2#1.-obtain-oauth-2.0-credentials-from-the-dynamic_data.setvar.console_name. to get your client id and client secret.
   Be sure to choose "web" as your client type.
 
-* 2. Configure your `.env` file to add two variables:
+2. Configure your `.env` file to add two variables:
 
   * OAUTH_CLIENT_ID={your client id}
   * OAUTH_CLIENT_SECRET={your client secret}
 
   Note: don't create a separate `.env` file , instead put it to the same `.env` file that stores your Vertex AI or Dev ML credentials
 
-* 3. Follow https://developers.google.com/identity/protocols/oauth2/web-server#creatingcred to add http://localhost/dev-ui/ to "Authorized redirect URIs".
+3. Follow https://developers.google.com/identity/protocols/oauth2/web-server#creatingcred to add http://localhost/dev-ui/ to "Authorized redirect URIs".
 
   Note: localhost here is just a hostname that you use to access the dev ui, replace it with the actual hostname you use to access the dev ui.
 
-* 4. For 1st run, allow popup for localhost in Chrome.
+4. For 1st run, allow popup for localhost in Chrome.
 
 ## Sample prompt
 

contributing/samples/bigquery_agent/__init__.py renamed to contributing/samples/google_api/__init__.py

@@ -40,7 +40,7 @@
 
 root_agent = Agent(
     model="gemini-2.0-flash",
-    name="bigquery_agent",
+    name="google_api_bigquery_agent",
     instruction="""
       You are a helpful Google BigQuery agent that help to manage users' data on Google BigQuery.
       Use the provided tools to conduct various operations on users' data in Google BigQuery.