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

PiperOrigin-RevId: 911930424

Author: vertex-sdk-bot

tests/unit/vertexai/genai/replays/test_skills_create.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.
+#
+"""Tests the skills.create() method against the Vertex AI endpoint using replays."""
+
+import io
+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, tmp_path):
+    client._api_client._http_options.base_url = (
+        "https://us-central1-aiplatform.googleapis.com"
+    )
+
+    # Create a dummy skill structure (SKILL.md is required by the spec)
+    with open(tmp_path / "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=str(tmp_path), 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"

vertexai/_genai/_skills_utils.py

@@ -0,0 +1,147 @@
+# 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 datetime
+import io
+import os
+import pathlib
+import time
+from typing import Any, Awaitable, Callable
+import zipfile
+
+
+def zip_directory(directory_path: pathlib.Path | str) -> bytes:
+    """Zips a directory into memory and returns the bytes.
+
+    Args:
+        directory_path (pathlib.Path | str): Required. The local path to the
+          directory.
+
+    Returns:
+        bytes: The zipped directory content.
+    """
+    directory_str = os.fspath(directory_path)
+    if not os.path.isdir(directory_str):
+        raise ValueError(f"Path is not a directory: {directory_str}")
+
+    zip_buffer = io.BytesIO()
+    with zipfile.ZipFile(zip_buffer, "w", zipfile.ZIP_DEFLATED) as zip_file:
+        for root, _, files in os.walk(directory_str):
+            for file in files:
+                file_path = os.path.join(root, file)
+                arcname = os.path.relpath(file_path, directory_str)
+
+                # 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: pathlib.Path | str) -> str:
+    """Zips a directory and base64-encodes the result to a UTF-8 string.
+
+    Args:
+        directory_path (pathlib.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: datetime.timedelta | float = 10.0,
+    timeout_seconds: float = 300.0,
+) -> 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 (datetime.timedelta | float): The interval between polls.
+        timeout_seconds (float): The maximum wait duration in seconds.
+
+    Returns:
+        Any: The completed operation.
+    """
+    if isinstance(poll_interval, datetime.timedelta):
+        poll_seconds = poll_interval.total_seconds()
+    else:
+        poll_seconds = float(poll_interval)
+
+    start_time = time.time()
+    operation = get_operation_fn(operation_name=operation_name)
+    while not operation.done:
+        if (time.time() - start_time) > timeout_seconds:
+            raise TimeoutError(
+                f"Operation {operation_name} did not complete within the timeout "
+                f"of {timeout_seconds} seconds."
+            )
+        time.sleep(poll_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: datetime.timedelta | float = 10.0,
+    timeout_seconds: float = 300.0,
+) -> 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 (datetime.timedelta | float): The interval between polls.
+        timeout_seconds (float): The maximum wait duration in seconds.
+
+    Returns:
+        Any: The completed operation.
+    """
+    if isinstance(poll_interval, datetime.timedelta):
+        poll_seconds = poll_interval.total_seconds()
+    else:
+        poll_seconds = float(poll_interval)
+
+    start_time = time.time()
+    operation = await get_operation_fn(operation_name=operation_name)
+    while not operation.done:
+        if (time.time() - start_time) > timeout_seconds:
+            raise TimeoutError(
+                f"Operation {operation_name} did not complete within the timeout "
+                f"of {timeout_seconds} seconds."
+            )
+        await asyncio.sleep(poll_seconds)
+        operation = await get_operation_fn(operation_name=operation.name)
+    return operation