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feat: Add optional idempotency support to batches API (#3171)
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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
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7 changed files with 351 additions and 64 deletions
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@ -2,12 +2,15 @@
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## Overview
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## Overview
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Protocol for batch processing API operations.
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The Batches API enables efficient processing of multiple requests in a single operation,
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The Batches API enables efficient processing of multiple requests in a single operation,
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particularly useful for processing large datasets, batch evaluation workflows, and
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particularly useful for processing large datasets, batch evaluation workflows, and
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cost-effective inference at scale.
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cost-effective inference at scale.
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The API is designed to allow use of openai client libraries for seamless integration.
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This API provides the following extensions:
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- idempotent batch creation
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Note: This API is currently under active development and may undergo changes.
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Note: This API is currently under active development and may undergo changes.
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This section contains documentation for all available providers for the **batches** API.
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This section contains documentation for all available providers for the **batches** API.
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@ -29,12 +29,16 @@ class ListBatchesResponse(BaseModel):
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@runtime_checkable
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@runtime_checkable
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class Batches(Protocol):
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class Batches(Protocol):
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"""Protocol for batch processing API operations.
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"""
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The Batches API enables efficient processing of multiple requests in a single operation,
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The Batches API enables efficient processing of multiple requests in a single operation,
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particularly useful for processing large datasets, batch evaluation workflows, and
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particularly useful for processing large datasets, batch evaluation workflows, and
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cost-effective inference at scale.
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cost-effective inference at scale.
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The API is designed to allow use of openai client libraries for seamless integration.
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This API provides the following extensions:
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- idempotent batch creation
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Note: This API is currently under active development and may undergo changes.
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Note: This API is currently under active development and may undergo changes.
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"""
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"""
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@ -45,6 +49,7 @@ class Batches(Protocol):
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endpoint: str,
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endpoint: str,
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completion_window: Literal["24h"],
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completion_window: Literal["24h"],
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metadata: dict[str, str] | None = None,
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metadata: dict[str, str] | None = None,
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idempotency_key: str | None = None,
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) -> BatchObject:
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) -> BatchObject:
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"""Create a new batch for processing multiple API requests.
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"""Create a new batch for processing multiple API requests.
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@ -52,6 +57,7 @@ class Batches(Protocol):
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:param endpoint: The endpoint to be used for all requests in the batch.
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:param endpoint: The endpoint to be used for all requests in the batch.
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:param completion_window: The time window within which the batch should be processed.
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:param completion_window: The time window within which the batch should be processed.
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:param metadata: Optional metadata for the batch.
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:param metadata: Optional metadata for the batch.
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:param idempotency_key: Optional idempotency key. When provided, enables idempotent behavior.
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:returns: The created batch object.
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:returns: The created batch object.
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"""
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"""
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...
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...
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@ -5,6 +5,7 @@
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# the root directory of this source tree.
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# the root directory of this source tree.
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import asyncio
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import asyncio
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import hashlib
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import itertools
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import itertools
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import json
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import json
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import time
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import time
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@ -136,28 +137,45 @@ class ReferenceBatchesImpl(Batches):
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endpoint: str,
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endpoint: str,
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completion_window: Literal["24h"],
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completion_window: Literal["24h"],
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metadata: dict[str, str] | None = None,
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metadata: dict[str, str] | None = None,
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idempotency_key: str | None = None,
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) -> BatchObject:
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) -> BatchObject:
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"""
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"""
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Create a new batch for processing multiple API requests.
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Create a new batch for processing multiple API requests.
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Error handling by levels -
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This implementation provides optional idempotency: when an idempotency key
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0. Input param handling, results in 40x errors before processing, e.g.
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(idempotency_key) is provided, a deterministic ID is generated based on the input
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- Wrong completion_window
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parameters. If a batch with the same parameters already exists, it will be
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- Invalid metadata types
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returned instead of creating a duplicate. Without an idempotency key,
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- Unknown endpoint
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each request creates a new batch with a unique ID.
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-> no batch created
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1. Errors preventing processing, result in BatchErrors aggregated in process_batch, e.g.
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Args:
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- input_file_id missing
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input_file_id: The ID of an uploaded file containing requests for the batch.
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- invalid json in file
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endpoint: The endpoint to be used for all requests in the batch.
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- missing custom_id, method, url, body
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completion_window: The time window within which the batch should be processed.
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- invalid model
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metadata: Optional metadata for the batch.
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- streaming
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idempotency_key: Optional idempotency key for enabling idempotent behavior.
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-> batch created, validation sends to failed status
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2. Processing errors, result in error_file_id entries, e.g.
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Returns:
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- Any error returned from inference endpoint
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The created or existing batch object.
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-> batch created, goes to completed status
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"""
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"""
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# Error handling by levels -
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# 0. Input param handling, results in 40x errors before processing, e.g.
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# - Wrong completion_window
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# - Invalid metadata types
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# - Unknown endpoint
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# -> no batch created
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# 1. Errors preventing processing, result in BatchErrors aggregated in process_batch, e.g.
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# - input_file_id missing
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# - invalid json in file
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# - missing custom_id, method, url, body
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# - invalid model
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# - streaming
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# -> batch created, validation sends to failed status
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# 2. Processing errors, result in error_file_id entries, e.g.
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# - Any error returned from inference endpoint
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# -> batch created, goes to completed status
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# TODO: set expiration time for garbage collection
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# TODO: set expiration time for garbage collection
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if endpoint not in ["/v1/chat/completions"]:
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if endpoint not in ["/v1/chat/completions"]:
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@ -171,6 +189,35 @@ class ReferenceBatchesImpl(Batches):
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)
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)
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batch_id = f"batch_{uuid.uuid4().hex[:16]}"
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batch_id = f"batch_{uuid.uuid4().hex[:16]}"
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# For idempotent requests, use the idempotency key for the batch ID
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# This ensures the same key always maps to the same batch ID,
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# allowing us to detect parameter conflicts
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if idempotency_key is not None:
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hash_input = idempotency_key.encode("utf-8")
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hash_digest = hashlib.sha256(hash_input).hexdigest()[:24]
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batch_id = f"batch_{hash_digest}"
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try:
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existing_batch = await self.retrieve_batch(batch_id)
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if (
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existing_batch.input_file_id != input_file_id
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or existing_batch.endpoint != endpoint
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or existing_batch.completion_window != completion_window
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or existing_batch.metadata != metadata
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):
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raise ConflictError(
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f"Idempotency key '{idempotency_key}' was previously used with different parameters. "
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"Either use a new idempotency key or ensure all parameters match the original request."
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)
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logger.info(f"Returning existing batch with ID: {batch_id}")
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return existing_batch
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except ResourceNotFoundError:
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# Batch doesn't exist, continue with creation
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pass
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current_time = int(time.time())
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current_time = int(time.time())
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batch = BatchObject(
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batch = BatchObject(
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@ -185,6 +232,7 @@ class ReferenceBatchesImpl(Batches):
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)
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)
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await self.kvstore.set(f"batch:{batch_id}", batch.to_json())
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await self.kvstore.set(f"batch:{batch_id}", batch.to_json())
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logger.info(f"Created new batch with ID: {batch_id}")
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if self.process_batches:
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if self.process_batches:
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task = asyncio.create_task(self._process_batch(batch_id))
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task = asyncio.create_task(self._process_batch(batch_id))
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91
tests/integration/batches/test_batches_idempotency.py
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91
tests/integration/batches/test_batches_idempotency.py
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# 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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"""
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Integration tests for batch idempotency functionality using the OpenAI client library.
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This module tests the idempotency feature in the batches API using the OpenAI-compatible
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client interface. These tests verify that the idempotency key (idempotency_key) works correctly
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in a real client-server environment.
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Test Categories:
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1. Successful Idempotency: Same key returns same batch with identical parameters
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- test_idempotent_batch_creation_successful: Verifies that requests with the same
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idempotency key return identical batches, even with different metadata order
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2. Conflict Detection: Same key with conflicting parameters raises HTTP 409 errors
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- test_idempotency_conflict_with_different_params: Verifies that reusing an idempotency key
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with truly conflicting parameters (both file ID and metadata values) raises ConflictError
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"""
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import time
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import pytest
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from openai import ConflictError
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class TestBatchesIdempotencyIntegration:
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"""Integration tests for batch idempotency using OpenAI client."""
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def test_idempotent_batch_creation_successful(self, openai_client):
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"""Test that identical requests with same idempotency key return the same batch."""
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batch1 = openai_client.batches.create(
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input_file_id="bogus-id",
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endpoint="/v1/chat/completions",
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completion_window="24h",
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metadata={
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"test_type": "idempotency_success",
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"purpose": "integration_test",
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},
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extra_body={"idempotency_key": "test-idempotency-token-1"},
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)
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# sleep to ensure different timestamps
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time.sleep(1)
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batch2 = openai_client.batches.create(
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input_file_id="bogus-id",
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endpoint="/v1/chat/completions",
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completion_window="24h",
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metadata={
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"purpose": "integration_test",
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"test_type": "idempotency_success",
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}, # Different order
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extra_body={"idempotency_key": "test-idempotency-token-1"},
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)
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assert batch1.id == batch2.id
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assert batch1.input_file_id == batch2.input_file_id
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assert batch1.endpoint == batch2.endpoint
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assert batch1.completion_window == batch2.completion_window
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assert batch1.metadata == batch2.metadata
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assert batch1.created_at == batch2.created_at
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def test_idempotency_conflict_with_different_params(self, openai_client):
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"""Test that using same idempotency key with different params raises conflict error."""
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batch1 = openai_client.batches.create(
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input_file_id="bogus-id-1",
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endpoint="/v1/chat/completions",
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completion_window="24h",
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metadata={"test_type": "conflict_test_1"},
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extra_body={"idempotency_key": "conflict-token"},
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)
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with pytest.raises(ConflictError) as exc_info:
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openai_client.batches.create(
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input_file_id="bogus-id-2", # Different file ID
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endpoint="/v1/chat/completions",
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completion_window="24h",
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metadata={"test_type": "conflict_test_2"}, # Different metadata
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extra_body={"idempotency_key": "conflict-token"}, # Same token
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)
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assert exc_info.value.status_code == 409
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assert "conflict" in str(exc_info.value).lower()
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retrieved_batch = openai_client.batches.retrieve(batch1.id)
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assert retrieved_batch.id == batch1.id
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assert retrieved_batch.input_file_id == "bogus-id-1"
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54
tests/unit/providers/batches/conftest.py
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54
tests/unit/providers/batches/conftest.py
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# 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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@ -54,60 +54,17 @@ dependencies like inference, files, and models APIs.
|
||||||
"""
|
"""
|
||||||
|
|
||||||
import json
|
import json
|
||||||
import tempfile
|
|
||||||
from pathlib import Path
|
|
||||||
from unittest.mock import AsyncMock, MagicMock
|
from unittest.mock import AsyncMock, MagicMock
|
||||||
|
|
||||||
import pytest
|
import pytest
|
||||||
|
|
||||||
from llama_stack.apis.batches import BatchObject
|
from llama_stack.apis.batches import BatchObject
|
||||||
from llama_stack.apis.common.errors import ConflictError, ResourceNotFoundError
|
from llama_stack.apis.common.errors import ConflictError, ResourceNotFoundError
|
||||||
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.config import SqliteKVStoreConfig
|
|
||||||
|
|
||||||
|
|
||||||
class TestReferenceBatchesImpl:
|
class TestReferenceBatchesImpl:
|
||||||
"""Test the reference implementation of the Batches API."""
|
"""Test the reference implementation of the Batches API."""
|
||||||
|
|
||||||
@pytest.fixture
|
|
||||||
async def provider(self):
|
|
||||||
"""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
|
|
||||||
from unittest.mock import AsyncMock
|
|
||||||
|
|
||||||
from llama_stack.providers.utils.kvstore import kvstore_impl
|
|
||||||
|
|
||||||
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(self):
|
|
||||||
"""Sample batch data for testing."""
|
|
||||||
return {
|
|
||||||
"input_file_id": "file_abc123",
|
|
||||||
"endpoint": "/v1/chat/completions",
|
|
||||||
"completion_window": "24h",
|
|
||||||
"metadata": {"test": "true", "priority": "high"},
|
|
||||||
}
|
|
||||||
|
|
||||||
def _validate_batch_type(self, batch, expected_metadata=None):
|
def _validate_batch_type(self, batch, expected_metadata=None):
|
||||||
"""
|
"""
|
||||||
Helper function to validate batch object structure and field types.
|
Helper function to validate batch object structure and field types.
|
||||||
|
|
128
tests/unit/providers/batches/test_reference_idempotency.py
Normal file
128
tests/unit/providers/batches/test_reference_idempotency.py
Normal file
|
@ -0,0 +1,128 @@
|
||||||
|
# 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.
|
||||||
|
|
||||||
|
"""
|
||||||
|
Tests for idempotency functionality in the reference batches provider.
|
||||||
|
|
||||||
|
This module tests the optional idempotency feature that allows clients to provide
|
||||||
|
an idempotency key (idempotency_key) to ensure that repeated requests with the same key
|
||||||
|
and parameters return the same batch, while requests with the same key but different
|
||||||
|
parameters result in a conflict error.
|
||||||
|
|
||||||
|
Test Categories:
|
||||||
|
1. Core Idempotency: Same parameters with same key return same batch
|
||||||
|
2. Parameter Independence: Different parameters without keys create different batches
|
||||||
|
3. Conflict Detection: Same key with different parameters raises ConflictError
|
||||||
|
|
||||||
|
Tests by Category:
|
||||||
|
|
||||||
|
1. Core Idempotency:
|
||||||
|
- test_idempotent_batch_creation_same_params
|
||||||
|
- test_idempotent_batch_creation_metadata_order_independence
|
||||||
|
|
||||||
|
2. Parameter Independence:
|
||||||
|
- test_non_idempotent_behavior_without_key
|
||||||
|
- test_different_idempotency_keys_create_different_batches
|
||||||
|
|
||||||
|
3. Conflict Detection:
|
||||||
|
- test_same_idempotency_key_different_params_conflict (parametrized: input_file_id, metadata values, metadata None vs {})
|
||||||
|
|
||||||
|
Key Behaviors Tested:
|
||||||
|
- Idempotent batch creation when idempotency_key provided with identical parameters
|
||||||
|
- Metadata order independence for consistent batch ID generation
|
||||||
|
- Non-idempotent behavior when no idempotency_key provided (random UUIDs)
|
||||||
|
- Conflict detection for parameter mismatches with same idempotency key
|
||||||
|
- Deterministic ID generation based solely on idempotency key
|
||||||
|
- Proper error handling with detailed conflict messages including key and error codes
|
||||||
|
- Protection against idempotency key reuse with different request parameters
|
||||||
|
"""
|
||||||
|
|
||||||
|
import asyncio
|
||||||
|
|
||||||
|
import pytest
|
||||||
|
|
||||||
|
from llama_stack.apis.common.errors import ConflictError
|
||||||
|
|
||||||
|
|
||||||
|
class TestReferenceBatchesIdempotency:
|
||||||
|
"""Test suite for idempotency functionality in the reference implementation."""
|
||||||
|
|
||||||
|
async def test_idempotent_batch_creation_same_params(self, provider, sample_batch_data):
|
||||||
|
"""Test that creating batches with identical parameters returns the same batch when idempotency_key is provided."""
|
||||||
|
|
||||||
|
del sample_batch_data["metadata"]
|
||||||
|
|
||||||
|
batch1 = await provider.create_batch(
|
||||||
|
**sample_batch_data,
|
||||||
|
metadata={"test": "value1", "other": "value2"},
|
||||||
|
idempotency_key="unique-token-1",
|
||||||
|
)
|
||||||
|
|
||||||
|
# sleep for 1 second to allow created_at timestamps to be different
|
||||||
|
await asyncio.sleep(1)
|
||||||
|
|
||||||
|
batch2 = await provider.create_batch(
|
||||||
|
**sample_batch_data,
|
||||||
|
metadata={"other": "value2", "test": "value1"}, # Different order
|
||||||
|
idempotency_key="unique-token-1",
|
||||||
|
)
|
||||||
|
|
||||||
|
assert batch1.id == batch2.id
|
||||||
|
assert batch1.input_file_id == batch2.input_file_id
|
||||||
|
assert batch1.metadata == batch2.metadata
|
||||||
|
assert batch1.created_at == batch2.created_at
|
||||||
|
|
||||||
|
async def test_different_idempotency_keys_create_different_batches(self, provider, sample_batch_data):
|
||||||
|
"""Test that different idempotency keys create different batches even with same params."""
|
||||||
|
batch1 = await provider.create_batch(
|
||||||
|
**sample_batch_data,
|
||||||
|
idempotency_key="token-A",
|
||||||
|
)
|
||||||
|
|
||||||
|
batch2 = await provider.create_batch(
|
||||||
|
**sample_batch_data,
|
||||||
|
idempotency_key="token-B",
|
||||||
|
)
|
||||||
|
|
||||||
|
assert batch1.id != batch2.id
|
||||||
|
|
||||||
|
async def test_non_idempotent_behavior_without_key(self, provider, sample_batch_data):
|
||||||
|
"""Test that batches without idempotency key create unique batches even with identical parameters."""
|
||||||
|
batch1 = await provider.create_batch(**sample_batch_data)
|
||||||
|
|
||||||
|
batch2 = await provider.create_batch(**sample_batch_data)
|
||||||
|
|
||||||
|
assert batch1.id != batch2.id
|
||||||
|
assert batch1.input_file_id == batch2.input_file_id
|
||||||
|
assert batch1.endpoint == batch2.endpoint
|
||||||
|
assert batch1.completion_window == batch2.completion_window
|
||||||
|
assert batch1.metadata == batch2.metadata
|
||||||
|
|
||||||
|
@pytest.mark.parametrize(
|
||||||
|
"param_name,first_value,second_value",
|
||||||
|
[
|
||||||
|
("input_file_id", "file_001", "file_002"),
|
||||||
|
("metadata", {"test": "value1"}, {"test": "value2"}),
|
||||||
|
("metadata", None, {}),
|
||||||
|
],
|
||||||
|
)
|
||||||
|
async def test_same_idempotency_key_different_params_conflict(
|
||||||
|
self, provider, sample_batch_data, param_name, first_value, second_value
|
||||||
|
):
|
||||||
|
"""Test that same idempotency_key with different parameters raises conflict error."""
|
||||||
|
sample_batch_data["idempotency_key"] = "same-token"
|
||||||
|
|
||||||
|
sample_batch_data[param_name] = first_value
|
||||||
|
|
||||||
|
batch1 = await provider.create_batch(**sample_batch_data)
|
||||||
|
|
||||||
|
with pytest.raises(ConflictError, match="Idempotency key.*was previously used with different parameters"):
|
||||||
|
sample_batch_data[param_name] = second_value
|
||||||
|
await provider.create_batch(**sample_batch_data)
|
||||||
|
|
||||||
|
retrieved_batch = await provider.retrieve_batch(batch1.id)
|
||||||
|
assert retrieved_batch.id == batch1.id
|
||||||
|
assert getattr(retrieved_batch, param_name) == first_value
|
Loading…
Add table
Add a link
Reference in a new issue