Merge branch 'main' into feature/ollama-llm

Author: ayman3000

.github/workflows/triage.yml

@@ -17,8 +17,7 @@ jobs:
     if: >-
       github.repository == 'google/adk-python' && (
         github.event_name == 'schedule' ||
-        github.event.action == 'opened' ||
-        github.event.label.name == 'planned'
+        github.event.action == 'opened'
       )
     permissions:
       issues: write

contributing/samples/adk_triaging_agent/agent.py

@@ -42,6 +42,14 @@
     "workflow": "DeanChensj",
 }
 
+
+LABEL_TO_GTECH = [
+    "klateefa",
+    "llalitkumarrr",
+    "surajksharma07",
+    "sanketpatil06",
+]
+
 LABEL_GUIDELINES = """
       Label rubric and disambiguation rules:
       - "documentation": Tutorials, README content, reference docs, or samples.
@@ -121,15 +129,13 @@ def list_untriaged_issues(issue_count: int) -> dict[str, Any]:
 
     existing_component_labels = issue_labels & component_labels
     has_component = bool(existing_component_labels)
-    has_planned = "planned" in issue_labels
 
     # Determine what actions are needed
     needs_component_label = not has_component
-    needs_owner = has_planned and not assignees
+    needs_owner = not assignees
 
     # Include issue if it needs any action
     if needs_component_label or needs_owner:
-      issue["has_planned_label"] = has_planned
       issue["has_component_label"] = has_component
       issue["existing_component_label"] = (
           list(existing_component_labels)[0]
@@ -146,7 +152,6 @@ def list_untriaged_issues(issue_count: int) -> dict[str, Any]:
 
 def add_label_to_issue(issue_number: int, label: str) -> dict[str, Any]:
   """Add the specified component label to the given issue number.
-
   Args:
     issue_number: issue number of the GitHub issue.
     label: label to assign
@@ -177,37 +182,30 @@ def add_label_to_issue(issue_number: int, label: str) -> dict[str, Any]:
   }
 
 
-def add_owner_to_issue(issue_number: int, label: str) -> dict[str, Any]:
-  """Assign an owner to the issue based on the component label.
+def assign_gtech_owner_to_issue(issue_number: int) -> dict[str, Any]:
+  """Assign an owner from the GTech team to the given issue number.
 
-  This should only be called for issues that have the 'planned' label.
+  This is go to option irrespective of component label or planned label,
+  as long as the issue needs an owner.
+
+  All unassigned issues will be considered for GTech ownership. Unassigned
+  issues will seperated in two categories: issues with type "Bug" and issues
+  with type "Feature". Then bug issues and feature issues will be equally
+  assigned to the Gtech members in such a way that every day all members get
+  equal number of bug and feature issues.
 
   Args:
     issue_number: issue number of the GitHub issue.
-    label: component label that determines the owner to assign
 
   Returns:
     The status of this request, with the assigned owner when successful.
   """
-  print(
-      f"Attempting to assign owner for label '{label}' to issue #{issue_number}"
-  )
-  if label not in LABEL_TO_OWNER:
-    return error_response(
-        f"Error: Label '{label}' is not a valid component label."
-    )
-
-  owner = LABEL_TO_OWNER.get(label, None)
-  if not owner:
-    return {
-        "status": "warning",
-        "message": f"Label '{label}' does not have an owner. Will not assign.",
-    }
-
+  print(f"Attempting to assign GTech owner to issue #{issue_number}")
+  gtech_assignee = LABEL_TO_GTECH[issue_number % len(LABEL_TO_GTECH)]
   assignee_url = (
       f"{GITHUB_BASE_URL}/repos/{OWNER}/{REPO}/issues/{issue_number}/assignees"
   )
-  assignee_payload = {"assignees": [owner]}
+  assignee_payload = {"assignees": [gtech_assignee]}
 
   try:
     response = post_request(assignee_url, assignee_payload)
@@ -217,7 +215,7 @@ def add_owner_to_issue(issue_number: int, label: str) -> dict[str, Any]:
   return {
       "status": "success",
       "message": response,
-      "assigned_owner": owner,
+      "assigned_owner": gtech_assignee,
   }
 
 
@@ -259,7 +257,7 @@ def change_issue_type(issue_number: int, issue_type: str) -> dict[str, Any]:
 
       Each issue will have flags indicating what actions are needed:
       - `needs_component_label`: true if the issue needs a component label
-      - `needs_owner`: true if the issue needs an owner assigned (has 'planned' label but no assignee)
+      - `needs_owner`: true if the issue needs an owner assigned
 
       For each issue, perform ONLY the required actions based on the flags:
 
@@ -271,8 +269,8 @@ def change_issue_type(issue_number: int, issue_type: str) -> dict[str, Any]:
            - Otherwise → do not change the issue type
 
       2. **If `needs_owner` is true**:
-         - Use `add_owner_to_issue` to assign an owner based on the component label
-         - Note: If the issue already has a component label (`has_component_label: true`), use that existing label to determine the owner
+         - Use `assign_gtech_owner_to_issue` to assign an owner.
+
 
       Do NOT add a component label if `needs_component_label` is false.
       Do NOT assign an owner if `needs_owner` is false.
@@ -282,19 +280,18 @@ def change_issue_type(issue_number: int, issue_type: str) -> dict[str, Any]:
         placeholders (never output text like "[fill in later]").
       - Justify the chosen label with a short explanation referencing the issue
         details.
-      - Mention the assigned owner only when you actually assign one (i.e., when
-        the issue has the 'planned' label).
+      - Mention the assigned owner only when you actually assign one.
       - If no label is applied, clearly state why.
 
       Present the following in an easy to read format highlighting issue number and your label.
       - the issue summary in a few sentence
       - your label recommendation and justification
-      - the owner of the label if you assign the issue to an owner (only for planned issues)
+      - the owner, if you assign the issue to an owner
     """,
     tools=[
         list_untriaged_issues,
         add_label_to_issue,
-        add_owner_to_issue,
+        assign_gtech_owner_to_issue,
         change_issue_type,
     ],
 )

contributing/samples/adk_triaging_agent/main.py

@@ -57,7 +57,7 @@ async def fetch_specific_issue_details(issue_number: int):
 
     # Determine what actions are needed
     needs_component_label = not has_component
-    needs_owner = has_planned and not has_assignee
+    needs_owner = not has_assignee
 
     if needs_component_label or needs_owner:
       print(

contributing/samples/agent_registry_agent/agent.py

@@ -18,6 +18,7 @@
 
 from google.adk.agents.llm_agent import LlmAgent
 from google.adk.integrations.agent_registry import AgentRegistry
+from google.adk.models.google_llm import Gemini
 
 # Project and location can be set via environment variables:
 # GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION
@@ -27,6 +28,8 @@
 # Initialize Agent Registry client
 registry = AgentRegistry(project_id=project_id, location=location)
 
+# List agents, MCP servers, and endpoints resource names from the registry.
+# They can be used to initialize the agent, toolset, and model below.
 print(f"Listing agents in {project_id}/{location}...")
 agents = registry.list_agents()
 for agent in agents.get("agents", []):
@@ -37,6 +40,11 @@
 for server in mcp_servers.get("mcpServers", []):
   print(f"- MCP Server: {server.get('displayName')} ({server.get('name')})")
 
+print(f"\nListing endpoints in {project_id}/{location}...")
+endpoints = registry.list_endpoints()
+for endpoint in endpoints.get("endpoints", []):
+  print(f"- Endpoint: {endpoint.get('displayName')} ({endpoint.get('name')})")
+
 # Example of using a specific agent or MCP server from the registry:
 # (Note: These names should be full resource names as returned by list methods)
 
@@ -52,8 +60,19 @@
     f"projects/{project_id}/locations/{location}/mcpServers/MCP_SERVER_NAME"
 )
 
+# 3. Getting a specific model endpoint configuration
+# This returns a string like:
+# "projects/adk12345/locations/us-central1/publishers/google/models/gemini-2.5-flash"
+# TODO: Replace ENDPOINT_NAME with your endpoint name
+model_name = registry.get_model_name(
+    f"projects/{project_id}/locations/{location}/endpoints/ENDPOINT_NAME"
+)
+
+# Initialize the model using the resolved model name from registry.
+gemini_model = Gemini(model=model_name)
+
 root_agent = LlmAgent(
-    model="gemini-2.5-flash",
+    model=gemini_model,
     name="discovery_agent",
     instruction=(
         "You have access to tools and sub-agents discovered via Registry."

contributing/samples/agent_tool_with_grounding_metadata/__init__.py

@@ -0,0 +1,15 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from . import agent

contributing/samples/agent_tool_with_grounding_metadata/agent.py

@@ -0,0 +1,74 @@
+# Copyright 2026 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import random
+
+from dotenv import load_dotenv
+from google.adk import Agent
+from google.adk.tools.agent_tool import AgentTool
+from google.adk.tools.tool_context import ToolContext
+from google.adk.tools.vertex_ai_search_tool import VertexAiSearchTool
+
+load_dotenv(override=True)
+
+VERTEXAI_DATASTORE_ID = os.getenv("VERTEXAI_DATASTORE_ID")
+if not VERTEXAI_DATASTORE_ID:
+  raise ValueError("VERTEXAI_DATASTORE_ID environment variable not set")
+
+
+def roll_die(sides: int, tool_context: ToolContext) -> int:
+  """Roll a die and return the rolled result.
+
+  Args:
+    sides: The integer number of sides the die has.
+
+  Returns:
+    An integer of the result of rolling the die.
+  """
+  result = random.randint(1, sides)
+  if "rolls" not in tool_context.state:
+    tool_context.state["rolls"] = []
+
+  tool_context.state["rolls"] = tool_context.state["rolls"] + [result]
+  return result
+
+
+vertex_ai_search_agent = Agent(
+    model="gemini-3-flash-preview",
+    name="vertex_ai_search_agent",
+    description="An agent for performing Vertex AI search.",
+    tools=[
+        VertexAiSearchTool(
+            data_store_id=VERTEXAI_DATASTORE_ID,
+        )
+    ],
+)
+
+root_agent = Agent(
+    model="gemini-3.1-pro-preview",
+    name="hello_world_agent",
+    description="A hello world agent with multiple tools.",
+    instruction="""
+      You are a helpful assistant which can help user to roll dice and search for information.
+      - Use `roll_die` tool to roll dice.
+      - Use `vertex_ai_search_agent` to search for Google Agent Development Kit (ADK) information in the datastore.
+    """,
+    tools=[
+        roll_die,
+        AgentTool(
+            agent=vertex_ai_search_agent, propagate_grounding_metadata=True
+        ),
+    ],
+)

contributing/samples/bigquery/agent.py

@@ -21,6 +21,7 @@
 from google.adk.tools.bigquery.config import BigQueryToolConfig
 from google.adk.tools.bigquery.config import WriteMode
 import google.auth
+import google.auth.transport.requests
 
 # Define the desired credential type.
 # By default use Application Default Credentials (ADC) from the local
@@ -57,6 +58,8 @@
   # service account key file
   # https://cloud.google.com/iam/docs/service-account-creds#user-managed-keys
   creds, _ = google.auth.load_credentials_from_file("service_account_key.json")
+  if not creds.valid:
+    creds.refresh(google.auth.transport.requests.Request())
   credentials_config = BigQueryCredentialsConfig(credentials=creds)
 elif CREDENTIALS_TYPE == AuthCredentialTypes.HTTP:
   # Initialize the tools to use the externally provided access token. One such
@@ -73,6 +76,10 @@
   # Initialize the tools to use the application default credentials.
   # https://cloud.google.com/docs/authentication/provide-credentials-adc
   application_default_credentials, _ = google.auth.default()
+  if not application_default_credentials.valid:
+    application_default_credentials.refresh(
+        google.auth.transport.requests.Request()
+    )
   credentials_config = BigQueryCredentialsConfig(
       credentials=application_default_credentials
   )

contributing/samples/data_agent/agent.py

@@ -51,6 +51,10 @@
   # Initialize the tools to use the application default credentials.
   # https://cloud.google.com/docs/authentication/provide-credentials-adc
   application_default_credentials, _ = google.auth.default()
+  if not application_default_credentials.valid:
+    application_default_credentials.refresh(
+        google.auth.transport.requests.Request()
+    )
   credentials_config = DataAgentCredentialsConfig(
       credentials=application_default_credentials
   )

contributing/samples/hello_world/main.py

@@ -48,8 +48,15 @@ async def run_prompt(session: Session, new_message: str):
         session_id=session.id,
         new_message=content,
     ):
-      if event.content.parts and event.content.parts[0].text:
-        print(f'** {event.author}: {event.content.parts[0].text}')
+      if event.content.parts:
+        for part in event.content.parts:
+          if part.text:
+            print(f'** {event.author}: {part.text}')
+          if part.function_call:
+            print(
+                f'** {event.author} calls tool: {part.function_call.name} with'
+                f' args {part.function_call.args}'
+            )
 
   async def run_prompt_bytes(session: Session, new_message: str):
     content = types.Content(
@@ -74,6 +81,7 @@ async def check_rolls_in_state(rolls_size: int):
     session = await runner.session_service.get_session(
         app_name=app_name, user_id=user_id_1, session_id=session_11.id
     )
+    print('** session.state:', session.state)
     assert len(session.state['rolls']) == rolls_size
     for roll in session.state['rolls']:
       assert roll > 0 and roll <= 100
@@ -82,9 +90,9 @@ async def check_rolls_in_state(rolls_size: int):
   print('Start time:', start_time)
   print('------------------------------------')
   await run_prompt(session_11, 'Hi')
-  await run_prompt(session_11, 'Roll a die with 100 sides')
+  await run_prompt(session_11, 'Roll a dice with 100 sides')
   await check_rolls_in_state(1)
-  await run_prompt(session_11, 'Roll a die again with 100 sides.')
+  await run_prompt(session_11, 'Roll a dice again with 100 sides.')
   await check_rolls_in_state(2)
   await run_prompt(session_11, 'What numbers did I got?')
   await run_prompt_bytes(session_11, 'Hi bytes')