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feat(weave): Add basic support for OpenAI Responses #3886
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WalkthroughThe changes introduce new functions in the OpenAI SDK to handle streaming responses more effectively. The modifications include functions for padding output, accumulating responses, and creating both synchronous and asynchronous response wrappers. New settings and patcher updates have been added to integrate these capabilities. Additionally, several YAML cassette files and expanded test cases have been added to simulate various API interactions, including response streaming, synchronous/asynchronous calls, and tool calling. These updates enhance the response handling workflow and test coverage for OpenAI API interactions. Changes
Sequence Diagram(s)sequenceDiagram
participant Client
participant Wrapper
participant Accumulator
participant OpenAIApi
Client->>Wrapper: Initiate API request (sync/async)
Wrapper->>OpenAIApi: Send request
OpenAIApi-->>Accumulator: Stream response events (created, delta, completed)
Accumulator->>Accumulator: Update response state (_pad_output, accumulate deltas)
Accumulator->>Wrapper: Return accumulated response
Wrapper->>Client: Deliver final response
Suggested reviewers
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Actionable comments posted: 0
🧹 Nitpick comments (3)
weave/integrations/openai/openai_sdk.py (3)
389-427
: Consider validating or logging unexpected event types.
Currently, ifvalue
is not an instance ofResponseCreatedEvent
,ResponseTextDeltaEvent
, orResponseCompletedEvent
, the code silently returnsacc
. This could obscure errors in upstream code. Consider raising an error or logging a warning for unexpected event types.
433-455
: Reduce duplicated logic with existing wrappers.
create_wrapper_responses_sync
is highly similar tocreate_wrapper_sync
. Consider centralizing or parameterizing common logic to keep code DRY.
457-477
: Async wrapper code overlaps with existing async logic.
create_wrapper_responses_async
also duplicates patterns fromcreate_wrapper_async
. A single parametrized function could handle both scenarios, improving maintainability.
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weave/integrations/openai/openai_sdk.py
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`**/*.py`: Focus on pythonic code patterns. Check for proper...
**/*.py
: Focus on pythonic code patterns.
Check for proper exception handling.
Verify type hints usage where applicable.
Look for potential performance improvements.
Don't comment on formatting if black/isort is configured.
Check for proper dependency injection patterns.
Verify proper async handling if applicable.
weave/integrations/openai/openai_sdk.py
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🔇 Additional comments (4)
weave/integrations/openai/openai_sdk.py (4)
15-20
: Imports look good.
These imports within theif TYPE_CHECKING:
block are correct and consistent with Pythonic best practices.
429-431
: Unify streaming-logic checks withshould_use_accumulator
.
This function always returnsTrue
whenstream
is set toTrue
, unlikeshould_use_accumulator
, which also checks other conditions (e.g.,X-Stainless-Raw-Response
). Verify if you need consistent logic for both accumulators.
520-525
: Configuration updates look good.
The additionalresponses_create_settings
andasync_responses_create_settings
are straightforward clones of the base settings with a renamed operation. This approach seems consistent with existing patterns.
573-584
:❓ Verification inconclusive
Confirm module availability for
"openai.resources.responses"
.
This patcher referencesopenai.resources.responses
, which may vary by OpenAI Python library version.Use the script below to verify that the relevant module is present:
🏁 Script executed:
#!/bin/bash # Check references to openai.resources.responses in the codebase and confirm existence rg "openai.resources.responses" -A 3Length of output: 801
Module Compatibility Check for
openai.resources.responses
The search confirms that the file correctly references the module with the following snippet:
SymbolPatcher( lambda: importlib.import_module("openai.resources.responses"), "Responses.create", create_wrapper_responses_sync(settings=responses_create_settings), ), SymbolPatcher( lambda: importlib.import_module("openai.resources.responses"), "AsyncResponses.create", create_wrapper_responses_async( settings=async_responses_create_settings ), ),However, since the OpenAI Python SDK can vary between versions, please verify that the
openai.resources.responses
module (and specifically itsResponses.create
andAsyncResponses.create
methods) is present in all supported versions of the library. This additional check will help prevent potential runtime issues if a user’s environment uses a different SDK version.
Preview this PR with FeatureBee: https://beta.wandb.ai/?betaVersion=d6d4753dd14173b2ec8f64592b6d331d32362b2a |
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Actionable comments posted: 1
🧹 Nitpick comments (2)
weave/integrations/openai/openai_sdk.py (2)
384-388
: Guard against invalid or negativeoutput_index
.
This helper ensures the output list is large enough to append deltas atvalue.output_index
. However, consider handling potential edge cases (e.g., negative or very large indices) with a warning or defensive check, preventing unexpected list growth or index errors.def _pad_output(acc: Response, value: ResponseStreamEvent) -> Response: + if value.output_index < 0: + # Optionally log, raise, or clamp + return acc while len(acc.output) <= value.output_index: acc.output.append("") return acc
551-553
: Potential duplication of logic withshould_use_accumulator
.
This function is nearly identical in logic to the existingshould_use_accumulator
, apart from referencing different event types. Consider extracting the common logic or unify them if feasible to reduce duplication.
📜 Review details
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📒 Files selected for processing (1)
weave/integrations/openai/openai_sdk.py
(4 hunks)
🧰 Additional context used
📓 Path-based instructions (1)
`**/*.py`: Focus on pythonic code patterns. Check for proper exception handling. Verify type hints usage where applicable. Look for potential performance improvements. Don't commen...
**/*.py
: Focus on pythonic code patterns.
Check for proper exception handling.
Verify type hints usage where applicable.
Look for potential performance improvements.
Don't comment on formatting if black/isort is configured.
Check for proper dependency injection patterns.
Verify proper async handling if applicable.
weave/integrations/openai/openai_sdk.py
🧬 Code Definitions (1)
weave/integrations/openai/openai_sdk.py (1)
weave/integrations/patcher.py (1) (1)
SymbolPatcher
(63:121)
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- GitHub Check: Legacy (Query Service) Python unit tests (1)
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- GitHub Check: Trace nox tests (3, 9, pandas-test)
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- GitHub Check: Legacy (Query Service) Python unit tests (1)
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- GitHub Check: Trace nox tests (3, 13, pandas-test)
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- GitHub Check: Trace nox tests (3, 12, pandas-test)
- GitHub Check: Trace nox tests (3, 12, scorers)
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- GitHub Check: Trace nox tests (3, 11, pandas-test)
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- GitHub Check: Trace nox tests (3, 10, pandas-test)
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- GitHub Check: Trace nox tests (3, 10, trace_server)
- GitHub Check: Trace nox tests (3, 10, trace)
- GitHub Check: Trace nox tests (3, 9, pandas-test)
- GitHub Check: Trace nox tests (3, 9, scorers)
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- GitHub Check: Trace nox tests (3, 9, llamaindex)
- GitHub Check: Trace nox tests (3, 9, litellm)
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- GitHub Check: Legacy (Query Service) Python unit tests (1)
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- GitHub Check: Trace nox tests (3, 13, pandas-test)
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- GitHub Check: Trace nox tests (3, 13, langchain)
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- GitHub Check: Trace nox tests (3, 13, groq)
- GitHub Check: Trace nox tests (3, 13, cerebras)
- GitHub Check: Trace nox tests (3, 13, trace_server)
- GitHub Check: Trace nox tests (3, 13, trace)
- GitHub Check: Trace nox tests (3, 12, pandas-test)
- GitHub Check: Trace nox tests (3, 12, scorers)
- GitHub Check: Trace nox tests (3, 12, vertexai)
- GitHub Check: Trace nox tests (3, 12, openai)
- GitHub Check: Trace nox tests (3, 12, notdiamond)
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- GitHub Check: Trace nox tests (3, 11, pandas-test)
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- GitHub Check: Trace nox tests (3, 10, pandas-test)
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- GitHub Check: Trace nox tests (3, 10, trace_server)
- GitHub Check: Trace nox tests (3, 10, trace)
- GitHub Check: Trace nox tests (3, 9, pandas-test)
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- GitHub Check: Legacy (Query Service) Python unit tests (0)
- GitHub Check: Trace nox tests (3, 13, pandas-test)
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- GitHub Check: Trace nox tests (3, 12, pandas-test)
- GitHub Check: Trace nox tests (3, 12, scorers)
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- GitHub Check: Trace nox tests (3, 11, huggingface)
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- GitHub Check: Trace nox tests (3, 10, pandas-test)
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- GitHub Check: Trace nox tests (3, 9, pandas-test)
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- GitHub Check: Legacy (Query Service) Python unit tests (0)
- GitHub Check: Trace nox tests (3, 13, pandas-test)
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- GitHub Check: Trace nox tests (3, 12, pandas-test)
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🔇 Additional comments (5)
weave/integrations/openai/openai_sdk.py (5)
15-15
: New import usage is consistent with the subsequent streaming accumulator logic.
This import is used by the new_pad_output
andresponses_accumulator
functions, aligning with the additions below.
555-577
: Wrapper logic mirrors existing patterns effectively.
This synchronous wrapper properly sets up the accumulator for streaming responses. Looks consistent and follows the existing approach without introducing new complexity.
579-601
: Well-structured async wrapper.
This async version closely parallels the synchronous approach and aligns with the codebase patterns for streaming accumulators. No obvious concurrency issues.
642-647
: New settings for response creation are properly introduced.
Bothresponses_create_settings
andasync_responses_create_settings
follow the same pattern as other*_create_settings
definitions, maintaining naming and configuration consistency.
695-706
: SymbolPatchers for synchronous and async responses integrate seamlessly.
Registering new patchers forResponses.create
andAsyncResponses.create
is consistent with the existing patcher structure. This is a clean extension.
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Actionable comments posted: 0
🧹 Nitpick comments (8)
tests/integrations/openai/cassettes/test_openai_responses/test_openai_tool_calling_async_stream.yaml (1)
39-797
: Comprehensive Streaming Response Simulation:
The response section meticulously outlines a sequence of streamed events—including initial creation, progress updates, multiple text delta events, annotations, and final completion. This level of detail is excellent for validating the streaming response-handling of the SDK. For long-term maintainability, consider adding inline documentation (perhaps as YAML comments) to describe the purpose of each event type.tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart_stream.yaml (1)
39-345
: Detailed Streaming Response and Delta Updates:
The response section simulates a realistic streaming interaction by detailing a series of delta events that combine to form the final message. Each event—from"response.created"
to successive"response.output_text.delta"
segments, and finally"response.completed"
—is presented in a clear sequence. For future updates, consider adding an inline summary comment within the YAML to document the intended final message structure, which can improve maintainability.weave/integrations/openai/openai_sdk.py (1)
385-387
: Guard against large or unexpected output indices.
You might consider checking whethervalue.output_index
can grow extremely large or become negative in edge cases. Otherwise, the logic here is straightforward.tests/integrations/openai/test_openai_responses.py (5)
210-210
: Remove debug print statements.There are debug print statements left in the tool calling tests which should be removed before committing.
- print(f"{output=}")
Also applies to: 268-268, 325-325, 385-385
27-27
: Consider adding proper type annotations instead of using type ignore.The code uses
# type: ignore
comments when comparing timestamps, suggesting there are type annotation issues that could be fixed.Consider updating type definitions for
call.started_at
andcall.ended_at
in their respective classes instead of using type ignore comments.Also applies to: 72-72, 116-116, 163-163, 207-207, 265-265, 322-322, 382-382
64-64
: Improve streaming test implementation.The synchronous streaming tests consume the stream with
list(stream)
but don't verify the individual chunks.Consider verifying properties of individual chunks or the accumulated content:
- res = list(stream) + chunks = list(stream) + # Verify proper chunking behavior + assert len(chunks) > 1 + # Verify that all chunks are of the expected type + for chunk in chunks: + assert hasattr(chunk, 'model')Also applies to: 257-257
154-155
: Improve async streaming test implementation.The async streaming tests iterate through the stream with empty loops without verifying the chunks.
Consider collecting and verifying properties of individual chunks:
- async for chunk in response: - pass + chunks = [] + async for chunk in response: + chunks.append(chunk) + + # Verify proper chunking behavior + assert len(chunks) > 1 + # Verify that all chunks are of the expected type + for chunk in chunks: + assert hasattr(chunk, 'model')Also applies to: 373-374
1-416
: Consider refactoring to reduce code duplication.The test file contains significant repetition across the eight test functions with similar patterns and assertions.
Consider using pytest's parametrization to reduce duplication:
@pytest.mark.parametrize( "is_async,is_stream,use_tools", [ (False, False, False), # sync, non-stream, no tools (False, True, False), # sync, stream, no tools (True, False, False), # async, non-stream, no tools (True, True, False), # async, stream, no tools (False, False, True), # sync, non-stream, with tools (False, True, True), # sync, stream, with tools (True, False, True), # async, non-stream, with tools (True, True, True), # async, stream, with tools ], ) @pytest.mark.skip_clickhouse_client @pytest.mark.vcr( filter_headers=["authorization"], allowed_hosts=["api.wandb.ai", "localhost"], ) @pytest.mark.asyncio async def test_openai_responses(client: WeaveClient, is_async: bool, is_stream: bool, use_tools: bool) -> None: # Test implementation with conditional logic based on parameters # This would replace the eight separate test functions
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tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart.yaml
(1 hunks)tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart_async.yaml
(1 hunks)tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart_async_stream.yaml
(1 hunks)tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart_stream.yaml
(1 hunks)tests/integrations/openai/cassettes/test_openai_responses/test_openai_tool_calling.yaml
(1 hunks)tests/integrations/openai/cassettes/test_openai_responses/test_openai_tool_calling_async.yaml
(1 hunks)tests/integrations/openai/cassettes/test_openai_responses/test_openai_tool_calling_async_stream.yaml
(1 hunks)tests/integrations/openai/cassettes/test_openai_responses/test_openai_tool_calling_stream.yaml
(1 hunks)tests/integrations/openai/test_openai_responses.py
(1 hunks)weave/integrations/openai/openai_sdk.py
(4 hunks)
✅ Files skipped from review due to trivial changes (1)
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`**/*.{yaml,yml,json,tf}`: Check for security best practices. Verify environment-specific configurations. Look for hardcoded credentials or sensitive data. Ensure proper resource l...
**/*.{yaml,yml,json,tf}
: Check for security best practices.
Verify environment-specific configurations.
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Ensure proper resource limits and requests.
Verify proper versioning of dependencies.
Check for infrastructure best practices.
tests/integrations/openai/cassettes/test_openai_responses/test_openai_tool_calling_async.yaml
tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart.yaml
tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart_async_stream.yaml
tests/integrations/openai/cassettes/test_openai_responses/test_openai_tool_calling_async_stream.yaml
tests/integrations/openai/cassettes/test_openai_responses/test_openai_tool_calling_stream.yaml
tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart_async.yaml
tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart_stream.yaml
`**/*.py`: Focus on pythonic code patterns. Check for proper exception handling. Verify type hints usage where applicable. Look for potential performance improvements. Don't commen...
**/*.py
: Focus on pythonic code patterns.
Check for proper exception handling.
Verify type hints usage where applicable.
Look for potential performance improvements.
Don't comment on formatting if black/isort is configured.
Check for proper dependency injection patterns.
Verify proper async handling if applicable.
weave/integrations/openai/openai_sdk.py
tests/integrations/openai/test_openai_responses.py
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🔇 Additional comments (17)
tests/integrations/openai/cassettes/test_openai_responses/test_openai_tool_calling_async.yaml (1)
1-109
: Overall Structure and Validity of Asynchronous Tool Calling Test:
This new cassette file is well-structured for verifying asynchronous tool-calling behavior. The request section correctly supplies the JSON payload (including the input, model "gpt-4o-08-06", and appropriate headers like"AsyncOpenAI/Python 1.66.3"
and"x-stainless-async": ["async:asyncio"]
) and the response section accurately simulates a typical API reply with gzip-encoded binary data and comprehensive metadata.tests/integrations/openai/cassettes/test_openai_responses/test_openai_tool_calling_async_stream.yaml (1)
1-38
: Request Payload for Asynchronous Streaming Tool Calling:
The request payload here properly includes the"stream": true
flag alongside the input parameters and essential headers. The custom fields (like"x-stainless-async"
,"user-agent"
, etc.) are set correctly to facilitate asynchronous operations.tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart_async.yaml (1)
1-94
: Quickstart Asynchronous Interaction Cassette:
This cassette captures a quickstart asynchronous request effectively. The JSON body, headers, and binary-encoded gzip response all align with expectations for testing asynchronous response handling. The structure is consistent with similar test cases.tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart.yaml (1)
1-94
: Standard Quickstart Interaction Cassette:
This file simulates a synchronous conversation with the OpenAI API. The request’s JSON payload (asking for a one-sentence bedtime story) and corresponding headers are well formed, and the compressed binary response is as expected. It might be worthwhile to periodically verify that the"content-length"
value remains accurate if any modifications are made to the payload.tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart_stream.yaml (1)
1-38
: Streaming Quickstart Request Definition:
The request segment here properly signals that the response should be streamed by including"stream": true
. It is complemented by the necessary headers and JSON payload. Notably, the custom header"x-stainless-async"
is set to'false'
here, which fits within this test’s context.tests/integrations/openai/cassettes/test_openai_responses/test_openai_quickstart_async_stream.yaml (1)
1-318
: No detection of hardcoded secrets or credentials.This test cassette file appears to store only request/response data without including any sensitive information. Everything looks safe to merge.
tests/integrations/openai/cassettes/test_openai_responses/test_openai_tool_calling_stream.yaml (1)
1-1547
: Verified no security issues or PII in the cassette data.These lines only capture typical HTTP request/response data for testing. No concerns found regarding secrets or credentials.
weave/integrations/openai/openai_sdk.py (7)
15-15
: Imported classes are utilized correctly.
This new import fromopenai.types.responses
is properly referenced later in the code.
390-552
: Handle unimplemented events to aid debugging.
There are placeholder sections for events likeResponseContentPartAddedEvent
andResponseOutputItemAddedEvent
. Consider logging or raising a descriptive exception for completeness.
554-556
: Simple and effective check.
This helper cleanly verifies if streaming is requested.
558-578
: Synchronous responses wrapper looks good.
The accumulator usage aligns well with your streaming approach.
582-604
: Async responses wrapper is on point.
Implementation is consistent with the sync version, ensuring streaming support.
645-650
: Dedicated response settings.
Extracting these settings helps keep the architecture modular for the new “responses” endpoint.
699-709
: Seamless integration for new endpoints.
Patching the newResponses.create
andAsyncResponses.create
is a clean addition to your existing design.tests/integrations/openai/test_openai_responses.py (3)
1-6
: LGTM - Proper imports and type hints.The imports are appropriate and the function signatures correctly use type hints.
8-49
: Well-structured test with comprehensive assertions.The test case properly validates the operation name, timing, output structure, and usage statistics. Good job on thorough testing!
51-94
: Well-structured test coverage for different OpenAI API modes.The test suite thoroughly covers all combinations of synchronous/asynchronous and streaming/non-streaming modes for both basic responses and tool-based responses. This provides excellent coverage for the new feature.
Also applies to: 96-138, 140-185, 187-241, 243-299, 301-356, 358-416
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Actionable comments posted: 0
🧹 Nitpick comments (1)
tests/integrations/openai/cassettes/openai_test/test_openai_responses_tool_calling_stream.yaml (1)
39-1547
: Review Comment: Comprehensive Streaming Response SimulationThe response block simulates a full streaming interaction by capturing a detailed sequence of events (including
response.created
,response.in_progress
,response.output_item.added
, and multipleresponse.output_text.delta
events) that eventually culminates with aresponse.completed
event. This level of detail supports robust testing of the SDK’s streaming response handling.
• Consider reviewing periodically that the growing volume of delta events remains maintainable.
• Ensure that the test harness correctly aggregates the incremental text to form the final output.
📜 Review details
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Review profile: CHILL
Plan: Pro
📒 Files selected for processing (9)
tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart.yaml
(1 hunks)tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart_async.yaml
(1 hunks)tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart_async_stream.yaml
(1 hunks)tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart_stream.yaml
(1 hunks)tests/integrations/openai/cassettes/openai_test/test_openai_responses_tool_calling.yaml
(1 hunks)tests/integrations/openai/cassettes/openai_test/test_openai_responses_tool_calling_async.yaml
(1 hunks)tests/integrations/openai/cassettes/openai_test/test_openai_responses_tool_calling_async_stream.yaml
(1 hunks)tests/integrations/openai/cassettes/openai_test/test_openai_responses_tool_calling_stream.yaml
(1 hunks)tests/integrations/openai/openai_test.py
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✅ Files skipped from review due to trivial changes (2)
- tests/integrations/openai/cassettes/openai_test/test_openai_responses_tool_calling_async_stream.yaml
- tests/integrations/openai/cassettes/openai_test/test_openai_responses_tool_calling_async.yaml
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`**/*.{yaml,yml,json,tf}`: Check for security best practices. Verify environment-specific configurations. Look for hardcoded credentials or sensitive data. Ensure proper resource l...
**/*.{yaml,yml,json,tf}
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Ensure proper resource limits and requests.
Verify proper versioning of dependencies.
Check for infrastructure best practices.
tests/integrations/openai/cassettes/openai_test/test_openai_responses_tool_calling.yaml
tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart.yaml
tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart_async_stream.yaml
tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart_async.yaml
tests/integrations/openai/cassettes/openai_test/test_openai_responses_tool_calling_stream.yaml
tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart_stream.yaml
`**/*.py`: Focus on pythonic code patterns. Check for proper exception handling. Verify type hints usage where applicable. Look for potential performance improvements. Don't commen...
**/*.py
: Focus on pythonic code patterns.
Check for proper exception handling.
Verify type hints usage where applicable.
Look for potential performance improvements.
Don't comment on formatting if black/isort is configured.
Check for proper dependency injection patterns.
Verify proper async handling if applicable.
tests/integrations/openai/openai_test.py
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🔇 Additional comments (13)
tests/integrations/openai/cassettes/openai_test/test_openai_responses_tool_calling_stream.yaml (1)
1-38
: Review Comment: Request Block ValidationThe request segment is well-structured. It includes a valid JSON body—with the input question, model version, and the stream flag set—and provides comprehensive headers. No sensitive data is exposed, and the header values (such as host, user-agent, and custom x-stainless-* fields) adhere to expected standards for testing.
tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart.yaml (2)
1-38
: Review Comment: Quickstart Request Block ReviewThe request block is correctly set up for the quickstart scenario. The JSON payload—instructing the creation of a one-sentence bedtime story—is clear, and the headers (including content-length, content-type, and various x-stainless fields) are appropriate for simulating a synchronous API call.
39-94
: Review Comment: Quickstart Response ValidationThe response section encodes the content as binary (using the YAML !!binary tag) and provides realistic header metadata (e.g., content-encoding, date, server). The status (200 OK) and version information are as expected for a successful quickstart interaction.
tests/integrations/openai/cassettes/openai_test/test_openai_responses_tool_calling.yaml (2)
1-38
: Review Comment: Tool Calling Request BlockThe request for the tool-calling scenario is clearly defined. The JSON body includes the required "tools" parameter with an entry of type
"web_search_preview"
, and the supporting headers are complete and consistent with other request cassettes.
39-103
: Review Comment: Tool Calling Response SimulationThe response section is structured in line with the other cassette files. The binary-encoded response body and accompanying headers simulate realistic output for a tool-calling request. This cassette should adequately support tests that rely on tool call responses.
tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart_async.yaml (2)
1-38
: Review Comment: Async Quickstart Request BlockThe asynchronous request block is well-formed. Notice that the user agent now reflects an async client (
AsyncOpenAI/Python 1.66.3
) and thex-stainless-async
header indicates asynchronous processing (usingasync:asyncio
), which is appropriate for testing async responses. All other JSON and header settings are consistent and correct.
39-94
: Review Comment: Async Quickstart Response BlockThe response block for the async cassette uses a binary string to store the payload and provides all expected HTTP headers. The metadata (status, date, openai-version, etc.) is consistent with a successful asynchronous API call.
tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart_stream.yaml (2)
1-38
: Review Comment: Streaming Quickstart Request BlockThe request block for the streaming scenario is configured correctly. The JSON payload includes the
"stream": true
flag along with the standard fields, and all headers are provided appropriately to simulate a streaming request. The configuration is consistent with our goal of testing streaming behavior.
39-345
: Review Comment: Streaming Quickstart Response SequenceThis cassette accurately mimics a streaming response scenario by outlining a sequence of events—including initial creation, in-progress updates, multiple incremental output (
delta
) events, and final completion. The detailed simulation ensures that the SDK can be rigorously tested against real-time, partial response updates.
• The sequence and structure are complete; please keep an eye on future expansions to avoid undue complexity in a single cassette.tests/integrations/openai/cassettes/openai_test/test_openai_responses_quickstart_async_stream.yaml (1)
1-317
: No security or data concerns identified.This YAML file appears to be a standard VCR cassette capturing the request/response cycle for testing asynchronous streaming. No sensitive tokens or credentials are exposed, and the response data is typical for mocking the OpenAI API.
tests/integrations/openai/openai_test.py (3)
8-8
: Import ofWeaveClient
looks good.The addition of this import is consistent with other usage across the file.
18-20
: Test signature update is consistent.Updating the function signature to accept a
WeaveClient
parameter aligns with the rest of the file’s approach for recording API calls.
1043-1454
: Extensive new tests for theresponses
feature appear well-structured.
- The new test methods thoroughly cover synchronous, asynchronous, streaming, and tool-calling scenarios for the
responses
API.- Usage assertions (input/output tokens, request counts, etc.) are properly validated.
- Consider verifying that the stable text outputs remain valid over time if the model version changes or if the test cassettes are re-recorded.
Overall, the coverage and clarity are excellent.
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LGTM
https://wandb.atlassian.net/browse/WB-23858
The response output is quite verbose
In future, we should make a decision RE: where to put the full response output data (some of it would fit under metadata/attributes, others output, etc.)
Summary by CodeRabbit
Summary by CodeRabbit