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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 closes #3144
54 lines
1.7 KiB
Python
54 lines
1.7 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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"""Shared fixtures for batches provider unit tests."""
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import tempfile
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from pathlib import Path
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from unittest.mock import AsyncMock
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import pytest
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from llama_stack.providers.inline.batches.reference.batches import ReferenceBatchesImpl
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from llama_stack.providers.inline.batches.reference.config import ReferenceBatchesImplConfig
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from llama_stack.providers.utils.kvstore import kvstore_impl
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from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
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@pytest.fixture
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async def provider():
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"""Create a test provider instance with temporary database."""
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with tempfile.TemporaryDirectory() as tmpdir:
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db_path = Path(tmpdir) / "test_batches.db"
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kvstore_config = SqliteKVStoreConfig(db_path=str(db_path))
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config = ReferenceBatchesImplConfig(kvstore=kvstore_config)
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# Create kvstore and mock APIs
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kvstore = await kvstore_impl(config.kvstore)
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mock_inference = AsyncMock()
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mock_files = AsyncMock()
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mock_models = AsyncMock()
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provider = ReferenceBatchesImpl(config, mock_inference, mock_files, mock_models, kvstore)
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await provider.initialize()
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# unit tests should not require background processing
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provider.process_batches = False
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yield provider
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await provider.shutdown()
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@pytest.fixture
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def sample_batch_data():
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"""Sample batch data for testing."""
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return {
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"input_file_id": "file_abc123",
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"endpoint": "/v1/chat/completions",
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"completion_window": "24h",
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"metadata": {"test": "true", "priority": "high"},
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}
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