llama-stack-mirror/tests/unit/providers/batches/conftest.py
Matthew Farrellee 68877f331e feat: Add optional idempotency support to batches API
Implements optional idempotency for batch creation using `idem_tok` parameter:

* **Core idempotency**: Same token + parameters returns existing batch
* **Conflict detection**: Same token + different parameters raises HTTP 409 ConflictError
* **Metadata order independence**: Different key ordering doesn't affect idempotency

**API changes:**
- Add optional `idem_tok` parameter to `create_batch()` method
- Enhanced API documentation with idempotency extensions

**Implementation:**
- Reference provider supports idempotent batch creation
- ConflictError for proper HTTP 409 status code mapping
- Comprehensive parameter validation

**Testing:**
- Unit tests: focused tests covering core scenarios with parametrized conflict detection
- Integration tests: tests validating real OpenAI client behavior

This enables client-side retry safety and prevents duplicate batch creation
when using the same idempotency token, following REST API
2025-08-08 08:08:08 -04:00

54 lines
1.7 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
"""Shared fixtures for batches provider unit tests."""
import tempfile
from pathlib import Path
from unittest.mock import AsyncMock
import pytest
from llama_stack.providers.inline.batches.reference.batches import ReferenceBatchesImpl
from llama_stack.providers.inline.batches.reference.config import ReferenceBatchesImplConfig
from llama_stack.providers.utils.kvstore import kvstore_impl
from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
@pytest.fixture
async def provider():
"""Create a test provider instance with temporary database."""
with tempfile.TemporaryDirectory() as tmpdir:
db_path = Path(tmpdir) / "test_batches.db"
kvstore_config = SqliteKVStoreConfig(db_path=str(db_path))
config = ReferenceBatchesImplConfig(kvstore=kvstore_config)
# Create kvstore and mock APIs
kvstore = await kvstore_impl(config.kvstore)
mock_inference = AsyncMock()
mock_files = AsyncMock()
mock_models = AsyncMock()
provider = ReferenceBatchesImpl(config, mock_inference, mock_files, mock_models, kvstore)
await provider.initialize()
# unit tests should not require background processing
provider.process_batches = False
yield provider
await provider.shutdown()
@pytest.fixture
def sample_batch_data():
"""Sample batch data for testing."""
return {
"input_file_id": "file_abc123",
"endpoint": "/v1/chat/completions",
"completion_window": "24h",
"metadata": {"test": "true", "priority": "high"},
}