feat: Add Update Skill method for Vertex AI Skill Registry SDK

tests/unit/vertexai/genai/replays/test_skills_create.py

@@ -0,0 +1,78 @@
+# 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.
+#
+"""Tests the skills.create() method against the Vertex AI endpoint using replays."""
+
+import io
+import os
+import tempfile
+import zipfile
+
+from tests.unit.vertexai.genai.replays import pytest_helper
+from vertexai._genai import types
+
+# MANDATORY: Initialize the replay test framework for this module
+pytestmark = pytest_helper.setup(
+    file=__file__,
+    globals_for_file=globals(),
+)
+
+
+def test_create_skill(client):
+  """Tests the creation of a skill using `client.skills.create()`."""
+  client._api_client._http_options.base_url = (
+      "https://us-central1-aiplatform.googleapis.com"
+  )
+
+  with tempfile.TemporaryDirectory() as tmpdir:
+    # Create a dummy skill structure (SKILL.md is required by the spec)
+    with open(os.path.join(tmpdir, "SKILL.md"), "w") as f:
+      f.write("# My Replay Skill\nThis is a test skill for replay tests.")
+
+    skill = client.skills.create(
+        display_name="My Replay Skill",
+        description="My Replay Skill Description",
+        config=types.CreateSkillConfig(
+            local_path=tmpdir, wait_for_completion=True
+        ),
+    )
+
+    assert skill.name is not None
+    assert skill.display_name == "My Replay Skill"
+    assert skill.description == "My Replay Skill Description"
+
+
+def test_create_skill_with_prezipped_bytes(client):
+  """Tests the creation of a skill with pre-zipped bytes."""
+  client._api_client._http_options.base_url = (
+      "https://us-central1-aiplatform.googleapis.com"
+  )
+
+  zip_buffer = io.BytesIO()
+  zinfo = zipfile.ZipInfo("SKILL.md", date_time=(1980, 1, 1, 0, 0, 0))
+  with zipfile.ZipFile(zip_buffer, "w") as zip_file:
+    zip_file.writestr(zinfo, "# My Zipped Replay Skill\nThis is a test.")
+  zipped_bytes = zip_buffer.getvalue()
+
+  skill = client.skills.create(
+      display_name="My Zipped Replay Skill",
+      description="My Zipped Replay Skill Description",
+      config=types.CreateSkillConfig(
+          zipped_filesystem=zipped_bytes, wait_for_completion=True
+      ),
+  )
+
+  assert skill.name is not None
+  assert skill.display_name == "My Zipped Replay Skill"
+  assert skill.description == "My Zipped Replay Skill Description"

tests/unit/vertexai/genai/replays/test_skills_update.py

@@ -0,0 +1,113 @@
+# 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.
+#
+"""Tests the skills.update() method against the Vertex AI endpoint using replays."""
+
+import io
+import os
+import random
+import tempfile
+import zipfile
+
+from tests.unit.vertexai.genai.replays import pytest_helper
+from vertexai._genai import types
+
+# MANDATORY: Initialize the replay test framework for this module
+pytestmark = pytest_helper.setup(
+    file=__file__,
+    globals_for_file=globals(),
+)
+
+PROJECT_ID = os.environ.get("GOOGLE_CLOUD_PROJECT", "srbai-testing")
+REGION = "us-central1"
+
+
+def test_update_skill(client):
+  """Tests the update of a skill using `client.skills.update()` (metadata only)."""
+  # Target the autopush sandbox endpoint for the Skill Registry API
+  client._api_client._http_options.base_url = (
+      "https://us-central1-autopush-aiplatform.sandbox.googleapis.com"
+  )
+
+  # 1. Create a fresh unique skill first
+  skill_id = f"update_meta_test_skill_{random.randint(10000, 99999)}"
+  with tempfile.TemporaryDirectory() as tmpdir:
+    with open(os.path.join(tmpdir, "SKILL.md"), "w") as f:
+      f.write("# Test Skill\nInitial content.")
+
+    created_skill = client.skills.create(
+        display_name="Original Skill",
+        description="Original Description",
+        config=types.CreateSkillConfig(
+            local_path=tmpdir, skill_id=skill_id, wait_for_completion=True
+        ),
+    )
+
+  # 2. Perform the metadata-only update on the new skill
+  updated_skill = client.skills.update(
+      name=created_skill.name,
+      config=types.UpdateSkillConfig(
+          display_name="My Updated Replay Skill",
+          description="My Updated Replay Skill Description",
+          wait_for_completion=True,
+      ),
+  )
+
+  assert updated_skill.name == created_skill.name
+  assert updated_skill.display_name == "My Updated Replay Skill"
+  assert updated_skill.description == "My Updated Replay Skill Description"
+
+
+def test_update_skill_with_zipped_bytes(client):
+  """Tests the update of a skill with zipped bytes filesystem."""
+  # Target the autopush sandbox endpoint for the Skill Registry API
+  client._api_client._http_options.base_url = (
+      "https://us-central1-autopush-aiplatform.sandbox.googleapis.com"
+  )
+
+  # 1. Create a fresh unique skill first
+  skill_id = f"update_zip_test_skill_{random.randint(10000, 99999)}"
+  with tempfile.TemporaryDirectory() as tmpdir:
+    with open(os.path.join(tmpdir, "SKILL.md"), "w") as f:
+      f.write("# Test Skill\nInitial content.")
+
+    created_skill = client.skills.create(
+        display_name="Original Skill",
+        description="Original Description",
+        config=types.CreateSkillConfig(
+            local_path=tmpdir, skill_id=skill_id, wait_for_completion=True
+        ),
+    )
+
+  # 2. Prepare zipped bytes for update
+  zip_buffer = io.BytesIO()
+  zinfo = zipfile.ZipInfo("SKILL.md", date_time=(1980, 1, 1, 0, 0, 0))
+  with zipfile.ZipFile(zip_buffer, "w") as zip_file:
+    zip_file.writestr(
+        zinfo, "# My Updated Zipped Replay Skill\nThis is updated."
+    )
+  zipped_bytes = zip_buffer.getvalue()
+
+  # 3. Update the skill with new zipped bytes
+  updated_skill = client.skills.update(
+      name=created_skill.name,
+      config=types.UpdateSkillConfig(
+          zipped_filesystem=zipped_bytes, wait_for_completion=True
+      ),
+  )
+
+  assert updated_skill.name == created_skill.name
+  assert (
+      updated_skill.display_name == "Original Skill"
+  )  # Display name remains unchanged

vertexai/_genai/_skills_utils.py

@@ -0,0 +1,116 @@
+# 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.
+#
+"""Utility functions for Skills."""
+
+import asyncio
+import base64
+import io
+import os
+import time
+from typing import Any, Awaitable, Callable
+import zipfile
+
+
+def zip_directory(directory_path: str) -> bytes:
+  """Zips a directory into memory and returns the bytes.
+
+  Args:
+      directory_path (str): Required. The local path to the directory.
+
+  Returns:
+      bytes: The zipped directory content.
+  """
+  if not os.path.isdir(directory_path):
+    raise ValueError(f"Path is not a directory: {directory_path}")
+
+  zip_buffer = io.BytesIO()
+  with zipfile.ZipFile(zip_buffer, "w", zipfile.ZIP_DEFLATED) as zip_file:
+    for root, _, files in os.walk(directory_path):
+      for file in files:
+        file_path = os.path.join(root, file)
+        arcname = os.path.relpath(file_path, directory_path)
+
+        # Read actual file data
+        with open(file_path, "rb") as f:
+          file_data = f.read()
+
+        # Use deterministic ZipInfo (mtime: 1980-01-01 00:00:00)
+        zinfo = zipfile.ZipInfo(arcname, date_time=(1980, 1, 1, 0, 0, 0))
+        zinfo.compress_type = zipfile.ZIP_DEFLATED
+        zinfo.external_attr = 0o644 << 16  # Constant file permissions
+
+        zip_file.writestr(zinfo, file_data)
+  return zip_buffer.getvalue()
+
+
+def get_zipped_filesystem_payload(directory_path: str) -> str:
+  """Zips a directory and base64-encodes the result to a UTF-8 string.
+
+  Args:
+      directory_path (str): Required. The local path to the directory.
+
+  Returns:
+      str: The base64-encoded zipped directory.
+  """
+  zip_bytes = zip_directory(directory_path)
+  return base64.b64encode(zip_bytes).decode("utf-8")
+
+
+def await_operation(
+    *,
+    operation_name: str,
+    get_operation_fn: Callable[..., Any],
+    poll_interval_seconds: float = 10.0,
+) -> Any:
+  """Waits for a long running operation to complete.
+
+  Args:
+      operation_name (str): Required. The name of the operation.
+      get_operation_fn (Callable): Required. Function to get the operation
+        status.
+      poll_interval_seconds (float): The interval between polls in seconds.
+
+  Returns:
+      Any: The completed operation.
+  """
+  operation = get_operation_fn(operation_name=operation_name)
+  while not operation.done:
+    time.sleep(poll_interval_seconds)
+    operation = get_operation_fn(operation_name=operation.name)
+  return operation
+
+
+async def await_operation_async(
+    *,
+    operation_name: str,
+    get_operation_fn: Callable[..., Awaitable[Any]],
+    poll_interval_seconds: float = 10.0,
+) -> Any:
+  """Waits for a long running operation to complete asynchronously.
+
+  Args:
+      operation_name (str): Required. The name of the operation.
+      get_operation_fn (Callable): Required. Async function to get the operation
+        status.
+      poll_interval_seconds (float): The interval between polls in seconds.
+
+  Returns:
+      Any: The completed operation.
+  """
+  operation = await get_operation_fn(operation_name=operation_name)
+  while not operation.done:
+    await asyncio.sleep(poll_interval_seconds)
+    operation = await get_operation_fn(operation_name=operation.name)
+  return operation