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Python: [Durabletask] Update feature-durabletask-python branch with main (#3068)

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* Python: Add factory pattern to concurrent orchestration builder (#2738)

* Add factory pattern to concurrent orchestration builder

* Update readme

* Address AI comments

* Fix unit tests

* Fix import

* Prevent multiple calls to set participants or factories

* Add comments

* Mitigate warnings

* Fix mypy

* Address comments

* Address Copilot comments

* Fix tests

* Python: fix: GroupChat ManagerSelectionResponse JSON Schema for OpenAI Structured Outpu… (#2750)

* fix: ManagerSelectionResponse JSON Schema for OpenAI Structured Output Strict Mode

* refactor: install pre-commit then commit again

* Capture file IDs from code interpreter in streaming responses (#2741)

* .NET: [BREAKING] Prevent nulls in AIAgent property (#2719)

* prevent nulls in AIAgent property

* address feedback

* code ql sm04598 (#2723)

Co-authored-by: Mark Wallace <127216156+markwallace-microsoft@users.noreply.github.com>

* .NET: Add Conversation State Sample (Step05) (#2697)

* Initial plan

* Add Agent_OpenAI_Step05_Conversation sample for conversation state management

Co-authored-by: rogerbarreto <19890735+rogerbarreto@users.noreply.github.com>

* Update Program.cs comment to accurately describe the sample

Co-authored-by: rogerbarreto <19890735+rogerbarreto@users.noreply.github.com>

* Update the code to use the ConversationClient more in line with the samples in OpenAI

* Apply suggestions from code review

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Changing sample to use ChatClientAgent and conversationId in GetNewThread

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: rogerbarreto <19890735+rogerbarreto@users.noreply.github.com>
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* Bump AWSSDK.Extensions.Bedrock.MEAI from 4.0.4.7 to 4.0.4.11 (#2777)

---
updated-dependencies:
- dependency-name: AWSSDK.Extensions.Bedrock.MEAI
  dependency-version: 4.0.4.11
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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* Bump Azure.Identity from 1.17.0 to 1.17.1 (#2780)

---
updated-dependencies:
- dependency-name: Azure.Identity
  dependency-version: 1.17.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
- dependency-name: Azure.Identity
  dependency-version: 1.17.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
- dependency-name: Azure.Identity
  dependency-version: 1.17.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
- dependency-name: Azure.Identity
  dependency-version: 1.17.1
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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* Bump Azure.AI.AgentServer.AgentFramework from 1.0.0-beta.4 to 1.0.0-beta.5 (#2778)

---
updated-dependencies:
- dependency-name: Azure.AI.AgentServer.AgentFramework
  dependency-version: 1.0.0-beta.5
  dependency-type: direct:production
  update-type: version-update:semver-patch
- dependency-name: Azure.AI.AgentServer.AgentFramework
  dependency-version: 1.0.0-beta.5
  dependency-type: direct:production
  update-type: version-update:semver-patch
- dependency-name: Azure.AI.AgentServer.AgentFramework
  dependency-version: 1.0.0-beta.5
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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* Python: added more complete parsing for mcp tool arguments (#2756)

* added more complete parsing for mcp tool arguments

* fixed mypy

* added nonlocal model counter, and some fixes

* fixes in naming logic

* extracted json parsing function, added parametrized test and checked coverage

* Python: Updated package versions (#2784)

* Updated package versions

* Small fix

* Bump actions/checkout from 5 to 6 (#2404)

Bumps [actions/checkout](https://github.com/actions/checkout) from 5 to 6.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](https://github.com/actions/checkout/compare/v5...v6)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

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* .NET: adds support for labels in edges,  fixes rendering of labels in dot a… (#1507)

* adds support for labels in edges,  fixes rendering of labels in dot and mermaid, adds rendering of labels in edges

* Update dotnet/src/Microsoft.Agents.AI.Workflows/Visualization/WorkflowVisualizer.cs

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* escaping edge labels, adding tests for labels containing strange characters that would break the diagram and enabling the previous signature so the API has backwards compatibility.

* Unify label in EdgeData

* Edge API adjustments, removed useless "sanitizer"

* fixed test

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Jacob Alber <jaalber@microsoft.com>
Co-authored-by: Chris <66376200+crickman@users.noreply.github.com>

* Python: Added custom args and thread object to ai_function kwargs (#2769)

* Added an example of using kwargs in ai_function

* Added thread object to ai_function kwargs

* Updated docs

* Small fix

* Added thread parameter filtering

* Fix WorkflowAgent to include thread convo history. Enable checkpointing. (#2774)

* Update OpenAIResponses.yaml to match AgentSchema (#2598)

1. Update `connection` child types --  `kind: ApiKey` to `kind: key` otherwise schema will fail: https://microsoft.github.io/AgentSchema/reference/apikeyconnection/

2.  Update `outputSchema`'s `PropertySchema` to be `kind` instead of `type` otherwise schema will fail: https://microsoft.github.io/AgentSchema/reference/propertyschema/

* Python: Remove warnings from workflow builder on not using factories (#2808)

* Revert concurrent

* Fix comments

* Python: Filter framework kwargs from MCP tool invocations (#2870)

* Filter framework kwargs from MCP tool invocations

* Fixes

* Python: Fix WorkflowAgent to emit yield_output as agent response (#2866)

* Fix WorkflowAgent to emit yield_output as agent response

* use raw_representation

* Raw representation handling

* Python: Use agent description in HandoffBuilder auto-generated tools (#2713) (#2714)

## Summary
Enhanced `HandoffBuilder._apply_auto_tools` to use the target agent's
description when creating handoff tools, providing more informative tool
descriptions for LLMs.

## Changes
- Modified `_apply_auto_tools` to extract `description` from
  `AgentExecutor._agent` when available
- Updated iteration to use `.items()` for more efficient dict traversal
- Handoff tools now use agent descriptions instead of generic placeholders

## Example
Before: "Handoff to the refund_agent agent."
After: "You handle refund requests. Ask for order details and process refunds."

## Testing
- All handoff tests pass (20/20)
- No breaking changes to existing API

Fixes #2713

Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>

* Python: [BREAKING] Observability updates (#2782)

* fixes Python: Add env_file_path parameter to setup_observability() similar to AzureOpenAIChatClient
Fixes #2186

* WIP on updates using configure_azure_monitor

* improved setup and clarity

* fixed root .env.example

* revert changes

* updated files

* updated sample

* updated zero code

* test fixes and fixed links

* fix devui

* removed planning docs

* added enable method and updated readme and samples

* clarified docstring

* add return annotation

* updated naming

* update capatilized version

* updated readme and some fixes

* updated decorator name inline with the rest

* feedback from comments addressed

* Python: Fix middleware terminate flag to exit function calling loop immediately (#2868)

* Fix middleware terminate flag to exit function calling loop immediately

* Eliminating duck typing

* Improve function exec result handling

* Fix race condition

* Fix mypy issues

* Python: Fix context duplication in handoff workflows when restoring from checkpoint (#2867)

* Fix context duplication in handoff workflows when restoring from checkpoint

* Address Copilot PR review

* .NET: Update to latest Azure.AI.*, OpenAI, and M.E.AI* (#2850)

* Update to latest Azure.AI.*, OpenAI, and M.E.AI*

Absorb breaking changes in Responses surface area

* Update dotnet/samples/AgentWebChat/AgentWebChat.AgentHost/Utilities/ChatClientExtensions.cs

* Update dotnet/samples/AgentWebChat/AgentWebChat.AgentHost/Utilities/ChatClientExtensions.cs

* Update dotnet/samples/AgentWebChat/AgentWebChat.AgentHost/Utilities/ChatClientExtensions.cs

* Update dotnet/samples/GettingStarted/AgentWithOpenAI/Agent_OpenAI_Step04_CreateFromOpenAIResponseClient/Program.cs

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Using patch to remove the model is necessary, updated the response client to actually use the the ForAgent

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com>

* Bump actions/download-artifact from 6 to 7 (#2862)

Bumps [actions/download-artifact](https://github.com/actions/download-artifact) from 6 to 7.
- [Release notes](https://github.com/actions/download-artifact/releases)
- [Commits](https://github.com/actions/download-artifact/compare/v6...v7)

---
updated-dependencies:
- dependency-name: actions/download-artifact
  dependency-version: '7'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

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* Bump actions/cache from 4 to 5 (#2861)

Bumps [actions/cache](https://github.com/actions/cache) from 4 to 5.
- [Release notes](https://github.com/actions/cache/releases)
- [Changelog](https://github.com/actions/cache/blob/main/RELEASES.md)
- [Commits](https://github.com/actions/cache/compare/v4...v5)

---
updated-dependencies:
- dependency-name: actions/cache
  dependency-version: '5'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

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* Bump actions/upload-artifact from 5 to 6 (#2860)

Bumps [actions/upload-artifact](https://github.com/actions/upload-artifact) from 5 to 6.
- [Release notes](https://github.com/actions/upload-artifact/releases)
- [Commits](https://github.com/actions/upload-artifact/compare/v5...v6)

---
updated-dependencies:
- dependency-name: actions/upload-artifact
  dependency-version: '6'
  dependency-type: direct:production
  update-type: version-update:semver-major
...

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* Python : Ollama Connector for Agent Framework (#1104)

* Initial Commit for Olama Connector

* Added Olama Sample

* Add Sample & Fixed Open Telemetry

* Fixed Spelling from Olama to Ollama

* remove"opentelemetry-semantic-conventions-ai ~=0.4.13" since its handled in a different pr

* Added Tool Calling

* Finalizing test cases

* Adjust samples to be more reliable

* Update python/packages/ollama/agent_framework_ollama/_chat_client.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update python/packages/ollama/pyproject.toml

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update python/packages/ollama/tests/test_ollama_chat_client.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Update python/packages/ollama/agent_framework_ollama/_chat_client.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Improved Docstrings & Sample

* Update python/packages/ollama/agent_framework_ollama/_chat_client.py

Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>

* Integrate PR Feedback
- Divided Streaming and Non-Streaming into independent Methods
- Catch Ollama Validation Error
- Add OTEL Provider Name
- Checked Ollama Messages
- Add Usage Statistics

* Revert setting, so it can be none

* Validate Message formatting between AF and Ollama

* Catch Ollama Error and raise a ServiceResponse Error

* Fix mypy error

* remove .vscode comma

* Add Reasoning support & adjust to new structure

* Add Ollama Multimodality and Reasoning

* Add test cases for reasoning

* Add Tests for Error Handling in Ollama Client

* Update python/samples/getting_started/multimodal_input/ollama_chat_multimodal.py

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Integrated Copilot Feedback

* Implement first PR Feedback

* Adjust Readme files for examples

* Adjust argument passing via additional chat options

* Implemented PR Feedback

* Removing Ollama Package from Core and moving samples

* Fix Link & Adding Samples to Main Sample Readme

* Fixing Links in Readme

* Moved Multimodal and Chat Example

* Fixed Link in ChatClient to Ollama

* Fix AgentFramework Links in Ollama Project

* Fix observability breaking change

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>

* Skip failing IT (#2904)

* .NET: Cosmos DB UT Fast Skip (For Non-Configured Local envs) (#2906)

* Cosmos DB UT Fast Skip (Non-Configured Local envs) + Long running UT skip in pipeline when no CosmosDB changes happened

* Force a CosmosDB source code change to trigger the pipeline

* Address possible string boolean mismatch

* Add debug

* Enabling emulator always when running IT

* .NET: Add TTLs to durable agent sessions (#2679)

* .NET: Add TTLs to durable agent sessions

* Remove unnecessary async

* PR feedback: clarify UTC

* PR feedback: limit minimum signal delay to <= 5 minutes

* PR feedback: Fix TTL disablement

* Linter: use auto-property

* Fix build break from OpenAI SDK change

* Updated CHANGELOG.md

* PR feedback

* Reduce default TTL to 14 days to work around DTS bug

* Python:  Update Mem0Provider to use v2 search API `filters` parameter (#2766)

* short fix to move id parameters to filters object

* added tests

* small fix

* mem0 dependency update

* Updated package versions (#2913)

* .NET: Switch to new "Run" method name. (#2843)

* Switch to new "RunAgent" method name.

* Try to disable false positive naming warning.

* Add comment about disabled warnings.

* Rename `RunAgent` to just `Run`.

* Update CHANGELOG.

* Python: Switch to new "run" method name. (#2890)

* Switch to `run` method.

* Add support for deprecated `run_agent`.

* Fix entity method name.

* Fix method name and improve tests.

* Update comment.

* Update Python CHANGELOG.

* [BREAKING] Python: Add factory pattern to handoff orchestration builder (#2844)

* WIP: Factory pattern to handoff

* Add factory pattern to concurrent orchestration builder; Next: tests and sample verification

* Add tests and improve comments

* Fix mypy

* Simplify handoff_simple.py

* Simplify handoff_autonoumous.py and bug fix

* Update readme

* Address Copilot comments

* Python: Flow custom kwargs to agents via Workflow SharedState (#2894)

* Flow custom kwargs to agents via SharedState

* Address Copilot feedback

* Improve sample typing

* Fix test

* Fix Pydantic error when using Literal type for tool params (#2893)

* Updated Ollama package version (#2920)

* Python: Azure AI Agent with Bing Grounding Citations Sample (#2892)

* bing grounding sample with citations

* small fix

* fix

* .NET: Make DelegatingAIAgent abstract (#2797)

* Initial plan

* Make DelegatingAIAgent abstract

Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com>

---------

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Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com>

* Added additional arguments for Azure AI agent (#2922)

* Python: Correction of MCP image type conversion in  _mcp.py (#2901)

* Correction of MCP image type conversion in  _mcp.py

* Added a new overload to the init function of the DataContent() type of the Agent Framework, edited the test case to correctly test the usage of the data and uri fields while using DataContent()

* Fixed tests related to the changes of the DataContent type, added testing for both string and byte representations

* Pass kwargs into subworkflows (#2923)

* Python: Move ollama samples to samples getting started dir (#2921)

* Move ollama samples to samples getting started dir

* Address feedback

* Python: fix: correct BadRequestError when using Pydantic model in response_fo… (#1843)

* fix: correct BadRequestError when using Pydantic model in response_format

* Fix lint

---------

Co-authored-by: Evan Mattson <evan.mattson@microsoft.com>

* .NET: [Breaking] Delete display name property (#2758)

* delete the AIAgent.DisplayName property

* use agent name as a first value for activity display name

* Update dotnet/src/Microsoft.Agents.AI.Workflows/Specialized/HandoffAgentExecutor.cs

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Python: cleanup and refactoring of chat clients (#2937)

* refactoring and unifying naming schemes of internal methods of chat clients

* set tool_choice to auto

* fix for mypy

* added note on naming and fix #2951

* fix responses

* fixes in azure ai agents client

* Python: Workflow add option to visualize internal executors (#2917)

* Workflow add option to visualize internal executors

* Address Copilot comments

* Python: Fixes Run ID and Thread ID casing to align with AG-UI Typescript SDK (#2948)

* added camelCase input to run id and thread id aligning with @ag-ui/core

* fixed per copilot suggestions

* Python: Add workflow cancellation sample (#2732)

* Add workflow cancellation sample

Add sample demonstrating how to cancel a running workflow using asyncio
tasks. Shows both cancellation mid-execution and normal completion paths.
Useful for implementing timeouts, graceful shutdown, or A2A executors.

* update docstring

* .NET: Update Anthropic package to version 12.0.0 (#2914)

* Initial plan

* Update Anthropic package to version 12.0.0

Co-authored-by: stephentoub <2642209+stephentoub@users.noreply.github.com>

---------

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Co-authored-by: stephentoub <2642209+stephentoub@users.noreply.github.com>

* Python: Add Azure Managed Redis Support with Credential Provider (#2887)

* azure redis support

* small fixes

* azure managed redis sample

* fixes

* Bump CommunityToolkit.Aspire.OllamaSharp from 13.0.0-beta.440 to 13.0.0 (#2856)

---
updated-dependencies:
- dependency-name: CommunityToolkit.Aspire.OllamaSharp
  dependency-version: 13.0.0
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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* Bump AWSSDK.Extensions.Bedrock.MEAI from 4.0.4.11 to 4.0.5 (#2853)

---
updated-dependencies:
- dependency-name: AWSSDK.Extensions.Bedrock.MEAI
  dependency-version: 4.0.5
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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* Bump Azure.AI.AgentServer.AgentFramework from 1.0.0-beta.4 to 1.0.0-beta.5 (#2854)

---
updated-dependencies:
- dependency-name: Azure.AI.AgentServer.AgentFramework
  dependency-version: 1.0.0-beta.5
  dependency-type: direct:production
  update-type: version-update:semver-patch
- dependency-name: Azure.AI.AgentServer.AgentFramework
  dependency-version: 1.0.0-beta.5
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

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* Python: Fix WorkflowAgent event handling and kwargs forwarding (#2946)

* Fix kwargs propagation through workflow.as_agent()

* Fix WorkflowAgent to respect AgentExecutor output_response setting

* .NET: Use GrpcEntityRunner instead of TaskEntityDispatcher (#2759)

* Use GrpcEntityRunner instead of TaskEntityDispatcher

* Pin to Durable worker 1.11.0

* Set the invocation result

* Update all Durable packages

* Update changelog, rename dispatcher to encondedEntityRequest

* Python: Bump Py version to 1.0.0b251218 for a release. Update CHANGELOG (#2968)

* Bump Py version to 1.0.0b251218 for a release. Update CHANGELOG

* update lock

* Fix formatting

* Fix ChatKit typing

* Python: Introducing Foundry Local Chat Clients (#2915)

* redo foundry local chat client

* fix mypy and spelling

* better docstring, updated sample

* fixed tests and added tests

* small sample update

* Updated package versions (#2978)

* Python: Added GitHub MCP sample with PAT (#2967)

* added github mcp sample with PAT

* addressed copilot fixes

* env fix

* Python: Preserve reasoning blocks with OpenRouter (#2950)

* Preserve reasoning blocks with OpenRouter

* Put encrypted reasoning in TextReasoningContent

* Remove unneccessary change

* Fix docs

* Support streaming

* Fix handling None in TextReasoningContent.text

* Python: Added response.created and response.in_progress event process to OpenAIBaseResponseClient (#2975)

* added response.created and response.in_progress to include response.id

* better doc string

* added tests for the new streaming event types

* Python: Introducing support for Bedrock-hosted models (Anthropic, Cohere, etc.) (#2610)

* Pushing the bedrock related changes to the new branch after addressing the review comments

* 2524 Addressed the second round review comments

* 2524 Addressed few more minor comments on the PR

* resolving the merge conflict

* 2524 resolved the uv.lock conflicts

* 2524 addressed more comments

* 2524 removed the print statement to fix the checks failure

* 2524 resolved the CI failure issues

* 2524 fixing the CI breaks

* 2524 Addressed the review comment

* 2524 resolved conflict

---------

Co-authored-by: Sunil Dutta <sunil.dutta@penske.com>
Co-authored-by: budgetboardingai <apurva.sharma31@gmail.com>

* .NET: [Durable Agents] Reliable streaming sample (#2942)

* .NET: [Durable Agents] Reliable streaming sample

* Add automated validation for new sample

* Address Copilot PR feedback

* Fix typo in README.md about agent definitions (#2634)

* Fix typo in README.md about agent definitions

* Update agent-samples/README.md

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* Python: latency improvements (#3014)

* latency improvements

* fixed mypy, added coding standards and instructions

* slight logic improvement

* Python: Updated package versions (#3024)

* Updated package versions

* Updated changelog

* Python: add powerfx safe mode (#3028)

* add powerfx safe mode

* improved docstring and aligned env_file loading

* ensured test uses reset

* .NET: [Breaking] Introduce RunCoreAsync/RunCoreStreamingAsync delegation pattern in AIAgent (#2749)

* Initial plan

* Refactor AIAgent: Make RunAsync and RunStreamingAsync non-abstract, add RunCoreAsync and RunCoreStreamingAsync

Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com>

* Fix infinite recursion in test implementations

Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com>

* Make RunAsync and RunStreamingAsync non-virtual as requested

Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com>

* Fix DelegatingAIAgent subclasses to use RunCoreAsync/RunCoreStreamingAsync

Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com>

* Fix XML documentation references in AnonymousDelegatingAIAgent

Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com>

* Restore <see cref> tags with proper qualified signatures in AnonymousDelegatingAIAgent

Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com>

* Rollback unnecessary XML documentation changes in AnonymousDelegatingAIAgent

Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com>

* Remove pragma and update crefs to RunCoreAsync/RunCoreStreamingAsync

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* Fix EntityAgentWrapper to call base.RunCoreAsync/RunCoreStreamingAsync

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This commit is contained in:
Laveesh Rohra
2026-01-02 13:13:37 -08:00
committed by GitHub
Unverified
parent a02527f00a
commit a5b36dc379
182 changed files with 7454 additions and 2462 deletions
Download Patch File Download Diff File Expand all files Collapse all files
python/packages/core/tests/azure/test_azure_chat_client.py
+7 -7
View File
@@ -193,7 +193,7 @@ async def test_cmc(
mock_create.assert_awaited_once_with(
model=azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
stream=False,
messages=azure_chat_client._prepare_chat_history_for_request(chat_history), # type: ignore
messages=azure_chat_client._prepare_messages_for_openai(chat_history), # type: ignore
)
@@ -216,7 +216,7 @@ async def test_cmc_with_logit_bias(
mock_create.assert_awaited_once_with(
model=azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
messages=azure_chat_client._prepare_chat_history_for_request(chat_history), # type: ignore
messages=azure_chat_client._prepare_messages_for_openai(chat_history), # type: ignore
stream=False,
logit_bias=token_bias,
)
@@ -241,7 +241,7 @@ async def test_cmc_with_stop(
mock_create.assert_awaited_once_with(
model=azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
messages=azure_chat_client._prepare_chat_history_for_request(chat_history), # type: ignore
messages=azure_chat_client._prepare_messages_for_openai(chat_history), # type: ignore
stream=False,
stop=stop,
)
@@ -311,7 +311,7 @@ async def test_azure_on_your_data(
mock_create.assert_awaited_once_with(
model=azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
messages=azure_chat_client._prepare_chat_history_for_request(messages_out), # type: ignore
messages=azure_chat_client._prepare_messages_for_openai(messages_out), # type: ignore
stream=False,
extra_body=expected_data_settings,
)
@@ -381,7 +381,7 @@ async def test_azure_on_your_data_string(
mock_create.assert_awaited_once_with(
model=azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
messages=azure_chat_client._prepare_chat_history_for_request(messages_out), # type: ignore
messages=azure_chat_client._prepare_messages_for_openai(messages_out), # type: ignore
stream=False,
extra_body=expected_data_settings,
)
@@ -438,7 +438,7 @@ async def test_azure_on_your_data_fail(
mock_create.assert_awaited_once_with(
model=azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
messages=azure_chat_client._prepare_chat_history_for_request(messages_out), # type: ignore
messages=azure_chat_client._prepare_messages_for_openai(messages_out), # type: ignore
stream=False,
extra_body=expected_data_settings,
)
@@ -584,7 +584,7 @@ async def test_get_streaming(
mock_create.assert_awaited_once_with(
model=azure_openai_unit_test_env["AZURE_OPENAI_CHAT_DEPLOYMENT_NAME"],
stream=True,
messages=azure_chat_client._prepare_chat_history_for_request(chat_history), # type: ignore
messages=azure_chat_client._prepare_messages_for_openai(chat_history), # type: ignore
# NOTE: The `stream_options={"include_usage": True}` is explicitly enforced in
# `OpenAIChatCompletionBase._inner_get_streaming_response`.
# To ensure consistency, we align the arguments here accordingly.
python/packages/core/tests/core/test_mcp.py
+26 -26
View File
@@ -24,14 +24,14 @@ from agent_framework import (
)
from agent_framework._mcp import (
MCPTool,
_ai_content_to_mcp_types,
_chat_message_to_mcp_types,
_get_input_model_from_mcp_prompt,
_get_input_model_from_mcp_tool,
_mcp_call_tool_result_to_ai_contents,
_mcp_prompt_message_to_chat_message,
_mcp_type_to_ai_content,
_normalize_mcp_name,
_parse_content_from_mcp,
_parse_contents_from_mcp_tool_result,
_parse_message_from_mcp,
_prepare_content_for_mcp,
_prepare_message_for_mcp,
)
from agent_framework.exceptions import ToolException, ToolExecutionException
@@ -60,7 +60,7 @@ def test_normalize_mcp_name():
def test_mcp_prompt_message_to_ai_content():
"""Test conversion from MCP prompt message to AI content."""
mcp_message = types.PromptMessage(role="user", content=types.TextContent(type="text", text="Hello, world!"))
ai_content = _mcp_prompt_message_to_chat_message(mcp_message)
ai_content = _parse_message_from_mcp(mcp_message)
assert isinstance(ai_content, ChatMessage)
assert ai_content.role.value == "user"
@@ -70,7 +70,7 @@ def test_mcp_prompt_message_to_ai_content():
assert ai_content.raw_representation == mcp_message
def test_mcp_call_tool_result_to_ai_contents():
def test_parse_contents_from_mcp_tool_result():
"""Test conversion from MCP tool result to AI contents."""
mcp_result = types.CallToolResult(
content=[
@@ -79,7 +79,7 @@ def test_mcp_call_tool_result_to_ai_contents():
types.ImageContent(type="image", data=b"abc", mimeType="image/webp"),
]
)
ai_contents = _mcp_call_tool_result_to_ai_contents(mcp_result)
ai_contents = _parse_contents_from_mcp_tool_result(mcp_result)
assert len(ai_contents) == 3
assert isinstance(ai_contents[0], TextContent)
@@ -100,7 +100,7 @@ def test_mcp_call_tool_result_with_meta_error():
_meta={"isError": True, "errorCode": "TOOL_ERROR", "errorMessage": "Tool execution failed"},
)
ai_contents = _mcp_call_tool_result_to_ai_contents(mcp_result)
ai_contents = _parse_contents_from_mcp_tool_result(mcp_result)
assert len(ai_contents) == 1
assert isinstance(ai_contents[0], TextContent)
@@ -131,7 +131,7 @@ def test_mcp_call_tool_result_with_meta_arbitrary_data():
},
)
ai_contents = _mcp_call_tool_result_to_ai_contents(mcp_result)
ai_contents = _parse_contents_from_mcp_tool_result(mcp_result)
assert len(ai_contents) == 1
assert isinstance(ai_contents[0], TextContent)
@@ -153,7 +153,7 @@ def test_mcp_call_tool_result_with_meta_merging_existing_properties():
text_content = types.TextContent(type="text", text="Test content")
mcp_result = types.CallToolResult(content=[text_content], _meta={"newField": "newValue", "isError": False})
ai_contents = _mcp_call_tool_result_to_ai_contents(mcp_result)
ai_contents = _parse_contents_from_mcp_tool_result(mcp_result)
assert len(ai_contents) == 1
content = ai_contents[0]
@@ -169,7 +169,7 @@ def test_mcp_call_tool_result_with_meta_none():
mcp_result = types.CallToolResult(content=[types.TextContent(type="text", text="No meta test")])
# No _meta field set
ai_contents = _mcp_call_tool_result_to_ai_contents(mcp_result)
ai_contents = _parse_contents_from_mcp_tool_result(mcp_result)
assert len(ai_contents) == 1
assert isinstance(ai_contents[0], TextContent)
@@ -191,7 +191,7 @@ def test_mcp_call_tool_result_regression_successful_workflow():
]
)
ai_contents = _mcp_call_tool_result_to_ai_contents(mcp_result)
ai_contents = _parse_contents_from_mcp_tool_result(mcp_result)
# Verify basic conversion still works correctly
assert len(ai_contents) == 2
@@ -213,7 +213,7 @@ def test_mcp_call_tool_result_regression_successful_workflow():
def test_mcp_content_types_to_ai_content_text():
"""Test conversion of MCP text content to AI content."""
mcp_content = types.TextContent(type="text", text="Sample text")
ai_content = _mcp_type_to_ai_content(mcp_content)[0]
ai_content = _parse_content_from_mcp(mcp_content)[0]
assert isinstance(ai_content, TextContent)
assert ai_content.text == "Sample text"
@@ -224,7 +224,7 @@ def test_mcp_content_types_to_ai_content_image():
"""Test conversion of MCP image content to AI content."""
mcp_content = types.ImageContent(type="image", data="abc", mimeType="image/jpeg")
mcp_content = types.ImageContent(type="image", data=b"abc", mimeType="image/jpeg")
ai_content = _mcp_type_to_ai_content(mcp_content)[0]
ai_content = _parse_content_from_mcp(mcp_content)[0]
assert isinstance(ai_content, DataContent)
assert ai_content.uri == "data:image/jpeg;base64,abc"
@@ -235,7 +235,7 @@ def test_mcp_content_types_to_ai_content_image():
def test_mcp_content_types_to_ai_content_audio():
"""Test conversion of MCP audio content to AI content."""
mcp_content = types.AudioContent(type="audio", data="def", mimeType="audio/wav")
ai_content = _mcp_type_to_ai_content(mcp_content)[0]
ai_content = _parse_content_from_mcp(mcp_content)[0]
assert isinstance(ai_content, DataContent)
assert ai_content.uri == "data:audio/wav;base64,def"
@@ -251,7 +251,7 @@ def test_mcp_content_types_to_ai_content_resource_link():
name="test_resource",
mimeType="application/json",
)
ai_content = _mcp_type_to_ai_content(mcp_content)[0]
ai_content = _parse_content_from_mcp(mcp_content)[0]
assert isinstance(ai_content, UriContent)
assert ai_content.uri == "https://example.com/resource"
@@ -267,7 +267,7 @@ def test_mcp_content_types_to_ai_content_embedded_resource_text():
text="Embedded text content",
)
mcp_content = types.EmbeddedResource(type="resource", resource=text_resource)
ai_content = _mcp_type_to_ai_content(mcp_content)[0]
ai_content = _parse_content_from_mcp(mcp_content)[0]
assert isinstance(ai_content, TextContent)
assert ai_content.text == "Embedded text content"
@@ -283,7 +283,7 @@ def test_mcp_content_types_to_ai_content_embedded_resource_blob():
blob="data:application/octet-stream;base64,dGVzdCBkYXRh",
)
mcp_content = types.EmbeddedResource(type="resource", resource=blob_resource)
ai_content = _mcp_type_to_ai_content(mcp_content)[0]
ai_content = _parse_content_from_mcp(mcp_content)[0]
assert isinstance(ai_content, DataContent)
assert ai_content.uri == "data:application/octet-stream;base64,dGVzdCBkYXRh"
@@ -294,7 +294,7 @@ def test_mcp_content_types_to_ai_content_embedded_resource_blob():
def test_ai_content_to_mcp_content_types_text():
"""Test conversion of AI text content to MCP content."""
ai_content = TextContent(text="Sample text")
mcp_content = _ai_content_to_mcp_types(ai_content)
mcp_content = _prepare_content_for_mcp(ai_content)
assert isinstance(mcp_content, types.TextContent)
assert mcp_content.type == "text"
@@ -304,7 +304,7 @@ def test_ai_content_to_mcp_content_types_text():
def test_ai_content_to_mcp_content_types_data_image():
"""Test conversion of AI data content to MCP content."""
ai_content = DataContent(uri="data:image/png;base64,xyz", media_type="image/png")
mcp_content = _ai_content_to_mcp_types(ai_content)
mcp_content = _prepare_content_for_mcp(ai_content)
assert isinstance(mcp_content, types.ImageContent)
assert mcp_content.type == "image"
@@ -315,7 +315,7 @@ def test_ai_content_to_mcp_content_types_data_image():
def test_ai_content_to_mcp_content_types_data_audio():
"""Test conversion of AI data content to MCP content."""
ai_content = DataContent(uri="data:audio/mpeg;base64,xyz", media_type="audio/mpeg")
mcp_content = _ai_content_to_mcp_types(ai_content)
mcp_content = _prepare_content_for_mcp(ai_content)
assert isinstance(mcp_content, types.AudioContent)
assert mcp_content.type == "audio"
@@ -329,7 +329,7 @@ def test_ai_content_to_mcp_content_types_data_binary():
uri="data:application/octet-stream;base64,xyz",
media_type="application/octet-stream",
)
mcp_content = _ai_content_to_mcp_types(ai_content)
mcp_content = _prepare_content_for_mcp(ai_content)
assert isinstance(mcp_content, types.EmbeddedResource)
assert mcp_content.type == "resource"
@@ -340,7 +340,7 @@ def test_ai_content_to_mcp_content_types_data_binary():
def test_ai_content_to_mcp_content_types_uri():
"""Test conversion of AI URI content to MCP content."""
ai_content = UriContent(uri="https://example.com/resource", media_type="application/json")
mcp_content = _ai_content_to_mcp_types(ai_content)
mcp_content = _prepare_content_for_mcp(ai_content)
assert isinstance(mcp_content, types.ResourceLink)
assert mcp_content.type == "resource_link"
@@ -348,7 +348,7 @@ def test_ai_content_to_mcp_content_types_uri():
assert mcp_content.mimeType == "application/json"
def test_chat_message_to_mcp_types():
def test_prepare_message_for_mcp():
message = ChatMessage(
role="user",
contents=[
@@ -356,7 +356,7 @@ def test_chat_message_to_mcp_types():
DataContent(uri="data:image/png;base64,xyz", media_type="image/png"),
],
)
mcp_contents = _chat_message_to_mcp_types(message)
mcp_contents = _prepare_message_for_mcp(message)
assert len(mcp_contents) == 2
assert isinstance(mcp_contents[0], types.TextContent)
assert isinstance(mcp_contents[1], types.ImageContent)
python/packages/core/tests/openai/test_openai_assistants_client.py
+16 -16
View File
@@ -463,9 +463,9 @@ async def test_openai_assistants_client_process_stream_events_requires_action(mo
"""Test _process_stream_events with thread.run.requires_action event."""
chat_client = create_test_openai_assistants_client(mock_async_openai)
# Mock the _create_function_call_contents method to return test content
# Mock the _parse_function_calls_from_assistants method to return test content
test_function_content = FunctionCallContent(call_id="call-123", name="test_func", arguments={"arg": "value"})
chat_client._create_function_call_contents = MagicMock(return_value=[test_function_content]) # type: ignore
chat_client._parse_function_calls_from_assistants = MagicMock(return_value=[test_function_content]) # type: ignore
# Create a mock Run object
mock_run = MagicMock(spec=Run)
@@ -498,8 +498,8 @@ async def test_openai_assistants_client_process_stream_events_requires_action(mo
assert update.contents[0] == test_function_content
assert update.raw_representation == mock_run
# Verify _create_function_call_contents was called correctly
chat_client._create_function_call_contents.assert_called_once_with(mock_run, None) # type: ignore
# Verify _parse_function_calls_from_assistants was called correctly
chat_client._parse_function_calls_from_assistants.assert_called_once_with(mock_run, None) # type: ignore
async def test_openai_assistants_client_process_stream_events_run_step_created(mock_async_openai: MagicMock) -> None:
@@ -585,8 +585,8 @@ async def test_openai_assistants_client_process_stream_events_run_completed_with
assert update.raw_representation == mock_run
def test_openai_assistants_client_create_function_call_contents_basic(mock_async_openai: MagicMock) -> None:
"""Test _create_function_call_contents with a simple function call."""
def test_openai_assistants_client_parse_function_calls_from_assistants_basic(mock_async_openai: MagicMock) -> None:
"""Test _parse_function_calls_from_assistants with a simple function call."""
chat_client = create_test_openai_assistants_client(mock_async_openai)
@@ -605,7 +605,7 @@ def test_openai_assistants_client_create_function_call_contents_basic(mock_async
# Call the method
response_id = "response_456"
contents = chat_client._create_function_call_contents(mock_run, response_id) # type: ignore
contents = chat_client._parse_function_calls_from_assistants(mock_run, response_id) # type: ignore
# Test that one function call content was created
assert len(contents) == 1
@@ -825,24 +825,24 @@ def test_openai_assistants_client_prepare_options_with_image_content(mock_async_
assert message["content"][0]["image_url"]["url"] == "https://example.com/image.jpg"
def test_openai_assistants_client_convert_function_results_to_tool_output_empty(mock_async_openai: MagicMock) -> None:
"""Test _convert_function_results_to_tool_output with empty list."""
def test_openai_assistants_client_prepare_tool_outputs_for_assistants_empty(mock_async_openai: MagicMock) -> None:
"""Test _prepare_tool_outputs_for_assistants with empty list."""
chat_client = create_test_openai_assistants_client(mock_async_openai)
run_id, tool_outputs = chat_client._convert_function_results_to_tool_output([]) # type: ignore
run_id, tool_outputs = chat_client._prepare_tool_outputs_for_assistants([]) # type: ignore
assert run_id is None
assert tool_outputs is None
def test_openai_assistants_client_convert_function_results_to_tool_output_valid(mock_async_openai: MagicMock) -> None:
"""Test _convert_function_results_to_tool_output with valid function results."""
def test_openai_assistants_client_prepare_tool_outputs_for_assistants_valid(mock_async_openai: MagicMock) -> None:
"""Test _prepare_tool_outputs_for_assistants with valid function results."""
chat_client = create_test_openai_assistants_client(mock_async_openai)
call_id = json.dumps(["run-123", "call-456"])
function_result = FunctionResultContent(call_id=call_id, result="Function executed successfully")
run_id, tool_outputs = chat_client._convert_function_results_to_tool_output([function_result]) # type: ignore
run_id, tool_outputs = chat_client._prepare_tool_outputs_for_assistants([function_result]) # type: ignore
assert run_id == "run-123"
assert tool_outputs is not None
@@ -851,10 +851,10 @@ def test_openai_assistants_client_convert_function_results_to_tool_output_valid(
assert tool_outputs[0].get("output") == "Function executed successfully"
def test_openai_assistants_client_convert_function_results_to_tool_output_mismatched_run_ids(
def test_openai_assistants_client_prepare_tool_outputs_for_assistants_mismatched_run_ids(
mock_async_openai: MagicMock,
) -> None:
"""Test _convert_function_results_to_tool_output with mismatched run IDs."""
"""Test _prepare_tool_outputs_for_assistants with mismatched run IDs."""
chat_client = create_test_openai_assistants_client(mock_async_openai)
# Create function results with different run IDs
@@ -863,7 +863,7 @@ def test_openai_assistants_client_convert_function_results_to_tool_output_mismat
function_result1 = FunctionResultContent(call_id=call_id1, result="Result 1")
function_result2 = FunctionResultContent(call_id=call_id2, result="Result 2")
run_id, tool_outputs = chat_client._convert_function_results_to_tool_output([function_result1, function_result2]) # type: ignore
run_id, tool_outputs = chat_client._prepare_tool_outputs_for_assistants([function_result1, function_result2]) # type: ignore
# Should only process the first one since run IDs don't match
assert run_id == "run-123"
python/packages/core/tests/openai/test_openai_chat_client.py
+21 -21
View File
@@ -182,12 +182,12 @@ def test_unsupported_tool_handling(openai_unit_test_env: dict[str, str]) -> None
unsupported_tool.__class__.__name__ = "UnsupportedAITool"
# This should ignore the unsupported ToolProtocol and return empty list
result = client._chat_to_tool_spec([unsupported_tool]) # type: ignore
result = client._prepare_tools_for_openai([unsupported_tool]) # type: ignore
assert result == []
# Also test with a non-ToolProtocol that should be converted to dict
dict_tool = {"type": "function", "name": "test"}
result = client._chat_to_tool_spec([dict_tool]) # type: ignore
result = client._prepare_tools_for_openai([dict_tool]) # type: ignore
assert result == [dict_tool]
@@ -637,7 +637,7 @@ def test_chat_response_content_order_text_before_tool_calls(openai_unit_test_env
)
client = OpenAIChatClient()
response = client._create_chat_response(mock_response, ChatOptions())
response = client._parse_response_from_openai(mock_response, ChatOptions())
# Verify we have both text and tool call content
assert len(response.messages) == 1
@@ -658,7 +658,7 @@ def test_function_result_falsy_values_handling(openai_unit_test_env: dict[str, s
# Test with empty list (falsy but not None)
message_with_empty_list = ChatMessage(role="tool", contents=[FunctionResultContent(call_id="call-123", result=[])])
openai_messages = client._openai_chat_message_parser(message_with_empty_list)
openai_messages = client._prepare_message_for_openai(message_with_empty_list)
assert len(openai_messages) == 1
assert openai_messages[0]["content"] == "[]" # Empty list should be JSON serialized
@@ -667,14 +667,14 @@ def test_function_result_falsy_values_handling(openai_unit_test_env: dict[str, s
role="tool", contents=[FunctionResultContent(call_id="call-456", result="")]
)
openai_messages = client._openai_chat_message_parser(message_with_empty_string)
openai_messages = client._prepare_message_for_openai(message_with_empty_string)
assert len(openai_messages) == 1
assert openai_messages[0]["content"] == "" # Empty string should be preserved
# Test with False (falsy but not None)
message_with_false = ChatMessage(role="tool", contents=[FunctionResultContent(call_id="call-789", result=False)])
openai_messages = client._openai_chat_message_parser(message_with_false)
openai_messages = client._prepare_message_for_openai(message_with_false)
assert len(openai_messages) == 1
assert openai_messages[0]["content"] == "false" # False should be JSON serialized
@@ -695,7 +695,7 @@ def test_function_result_exception_handling(openai_unit_test_env: dict[str, str]
],
)
openai_messages = client._openai_chat_message_parser(message_with_exception)
openai_messages = client._prepare_message_for_openai(message_with_exception)
assert len(openai_messages) == 1
assert openai_messages[0]["content"] == "Error: Function failed."
assert openai_messages[0]["tool_call_id"] == "call-123"
@@ -708,8 +708,8 @@ def test_prepare_function_call_results_string_passthrough():
assert isinstance(result, str)
def test_openai_content_parser_data_content_image(openai_unit_test_env: dict[str, str]) -> None:
"""Test _openai_content_parser converts DataContent with image media type to OpenAI format."""
def test_prepare_content_for_openai_data_content_image(openai_unit_test_env: dict[str, str]) -> None:
"""Test _prepare_content_for_openai converts DataContent with image media type to OpenAI format."""
client = OpenAIChatClient()
# Test DataContent with image media type
@@ -718,7 +718,7 @@ def test_openai_content_parser_data_content_image(openai_unit_test_env: dict[str
media_type="image/png",
)
result = client._openai_content_parser(image_data_content) # type: ignore
result = client._prepare_content_for_openai(image_data_content) # type: ignore
# Should convert to OpenAI image_url format
assert result["type"] == "image_url"
@@ -727,7 +727,7 @@ def test_openai_content_parser_data_content_image(openai_unit_test_env: dict[str
# Test DataContent with non-image media type should use default model_dump
text_data_content = DataContent(uri="data:text/plain;base64,SGVsbG8gV29ybGQ=", media_type="text/plain")
result = client._openai_content_parser(text_data_content) # type: ignore
result = client._prepare_content_for_openai(text_data_content) # type: ignore
# Should use default model_dump format
assert result["type"] == "data"
@@ -740,7 +740,7 @@ def test_openai_content_parser_data_content_image(openai_unit_test_env: dict[str
media_type="audio/wav",
)
result = client._openai_content_parser(audio_data_content) # type: ignore
result = client._prepare_content_for_openai(audio_data_content) # type: ignore
# Should convert to OpenAI input_audio format
assert result["type"] == "input_audio"
@@ -751,7 +751,7 @@ def test_openai_content_parser_data_content_image(openai_unit_test_env: dict[str
# Test DataContent with MP3 audio
mp3_data_content = DataContent(uri="data:audio/mp3;base64,//uQAAAAWGluZwAAAA8AAAACAAACcQ==", media_type="audio/mp3")
result = client._openai_content_parser(mp3_data_content) # type: ignore
result = client._prepare_content_for_openai(mp3_data_content) # type: ignore
# Should convert to OpenAI input_audio format with mp3
assert result["type"] == "input_audio"
@@ -760,8 +760,8 @@ def test_openai_content_parser_data_content_image(openai_unit_test_env: dict[str
assert result["input_audio"]["format"] == "mp3"
def test_openai_content_parser_document_file_mapping(openai_unit_test_env: dict[str, str]) -> None:
"""Test _openai_content_parser converts document files (PDF, DOCX, etc.) to OpenAI file format."""
def test_prepare_content_for_openai_document_file_mapping(openai_unit_test_env: dict[str, str]) -> None:
"""Test _prepare_content_for_openai converts document files (PDF, DOCX, etc.) to OpenAI file format."""
client = OpenAIChatClient()
# Test PDF without filename - should omit filename in OpenAI payload
@@ -770,7 +770,7 @@ def test_openai_content_parser_document_file_mapping(openai_unit_test_env: dict[
media_type="application/pdf",
)
result = client._openai_content_parser(pdf_data_content) # type: ignore
result = client._prepare_content_for_openai(pdf_data_content) # type: ignore
# Should convert to OpenAI file format without filename
assert result["type"] == "file"
@@ -787,7 +787,7 @@ def test_openai_content_parser_document_file_mapping(openai_unit_test_env: dict[
additional_properties={"filename": "report.pdf"},
)
result = client._openai_content_parser(pdf_with_filename) # type: ignore
result = client._prepare_content_for_openai(pdf_with_filename) # type: ignore
# Should use custom filename
assert result["type"] == "file"
@@ -820,7 +820,7 @@ def test_openai_content_parser_document_file_mapping(openai_unit_test_env: dict[
media_type=case["media_type"],
)
result = client._openai_content_parser(doc_content) # type: ignore
result = client._prepare_content_for_openai(doc_content) # type: ignore
# All application/* types should now be mapped to file format
assert result["type"] == "file"
@@ -834,7 +834,7 @@ def test_openai_content_parser_document_file_mapping(openai_unit_test_env: dict[
additional_properties={"filename": case["filename"]},
)
result = client._openai_content_parser(doc_with_filename) # type: ignore
result = client._prepare_content_for_openai(doc_with_filename) # type: ignore
# Should now use file format with filename
assert result["type"] == "file"
@@ -848,7 +848,7 @@ def test_openai_content_parser_document_file_mapping(openai_unit_test_env: dict[
additional_properties={},
)
result = client._openai_content_parser(pdf_empty_props) # type: ignore
result = client._prepare_content_for_openai(pdf_empty_props) # type: ignore
assert result["type"] == "file"
assert "filename" not in result["file"]
@@ -860,7 +860,7 @@ def test_openai_content_parser_document_file_mapping(openai_unit_test_env: dict[
additional_properties={"filename": None},
)
result = client._openai_content_parser(pdf_none_filename) # type: ignore
result = client._prepare_content_for_openai(pdf_none_filename) # type: ignore
assert result["type"] == "file"
assert "filename" not in result["file"] # None filename should be omitted
python/packages/core/tests/openai/test_openai_chat_client_base.py
+10 -10
View File
@@ -76,7 +76,7 @@ async def test_cmc(
mock_create.assert_awaited_once_with(
model=openai_unit_test_env["OPENAI_CHAT_MODEL_ID"],
stream=False,
messages=openai_chat_completion._prepare_chat_history_for_request(chat_history), # type: ignore
messages=openai_chat_completion._prepare_messages_for_openai(chat_history), # type: ignore
)
@@ -97,7 +97,7 @@ async def test_cmc_chat_options(
mock_create.assert_awaited_once_with(
model=openai_unit_test_env["OPENAI_CHAT_MODEL_ID"],
stream=False,
messages=openai_chat_completion._prepare_chat_history_for_request(chat_history), # type: ignore
messages=openai_chat_completion._prepare_messages_for_openai(chat_history), # type: ignore
)
@@ -120,7 +120,7 @@ async def test_cmc_no_fcc_in_response(
mock_create.assert_awaited_once_with(
model=openai_unit_test_env["OPENAI_CHAT_MODEL_ID"],
stream=False,
messages=openai_chat_completion._prepare_chat_history_for_request(orig_chat_history), # type: ignore
messages=openai_chat_completion._prepare_messages_for_openai(orig_chat_history), # type: ignore
)
@@ -167,7 +167,7 @@ async def test_scmc_chat_options(
model=openai_unit_test_env["OPENAI_CHAT_MODEL_ID"],
stream=True,
stream_options={"include_usage": True},
messages=openai_chat_completion._prepare_chat_history_for_request(chat_history), # type: ignore
messages=openai_chat_completion._prepare_messages_for_openai(chat_history), # type: ignore
)
@@ -203,7 +203,7 @@ async def test_cmc_additional_properties(
mock_create.assert_awaited_once_with(
model=openai_unit_test_env["OPENAI_CHAT_MODEL_ID"],
stream=False,
messages=openai_chat_completion._prepare_chat_history_for_request(chat_history), # type: ignore
messages=openai_chat_completion._prepare_messages_for_openai(chat_history), # type: ignore
reasoning_effort="low",
)
@@ -246,7 +246,7 @@ async def test_get_streaming(
model=openai_unit_test_env["OPENAI_CHAT_MODEL_ID"],
stream=True,
stream_options={"include_usage": True},
messages=openai_chat_completion._prepare_chat_history_for_request(orig_chat_history), # type: ignore
messages=openai_chat_completion._prepare_messages_for_openai(orig_chat_history), # type: ignore
)
@@ -285,7 +285,7 @@ async def test_get_streaming_singular(
model=openai_unit_test_env["OPENAI_CHAT_MODEL_ID"],
stream=True,
stream_options={"include_usage": True},
messages=openai_chat_completion._prepare_chat_history_for_request(orig_chat_history), # type: ignore
messages=openai_chat_completion._prepare_messages_for_openai(orig_chat_history), # type: ignore
)
@@ -349,7 +349,7 @@ async def test_get_streaming_no_fcc_in_response(
model=openai_unit_test_env["OPENAI_CHAT_MODEL_ID"],
stream=True,
stream_options={"include_usage": True},
messages=openai_chat_completion._prepare_chat_history_for_request(orig_chat_history), # type: ignore
messages=openai_chat_completion._prepare_messages_for_openai(orig_chat_history), # type: ignore
)
@@ -399,7 +399,7 @@ def test_chat_response_created_at_uses_utc(openai_unit_test_env: dict[str, str])
)
client = OpenAIChatClient()
response = client._create_chat_response(mock_response, ChatOptions())
response = client._parse_response_from_openai(mock_response, ChatOptions())
# Verify that created_at is correctly formatted as UTC
assert response.created_at is not None
@@ -431,7 +431,7 @@ def test_chat_response_update_created_at_uses_utc(openai_unit_test_env: dict[str
)
client = OpenAIChatClient()
response_update = client._create_chat_response_update(mock_chunk)
response_update = client._parse_response_update_from_openai(mock_chunk)
# Verify that created_at is correctly formatted as UTC
assert response_update.created_at is not None
python/packages/core/tests/openai/test_openai_responses_client.py
+141 -76
View File
@@ -368,16 +368,43 @@ async def test_response_format_parse_path() -> None:
mock_parsed_response.output_parsed = None
mock_parsed_response.usage = None
mock_parsed_response.finish_reason = None
mock_parsed_response.conversation = None # No conversation object
with patch.object(client.client.responses, "parse", return_value=mock_parsed_response):
response = await client.get_response(
messages=[ChatMessage(role="user", text="Test message")], response_format=OutputStruct, store=True
)
assert response.response_id == "parsed_response_123"
assert response.conversation_id == "parsed_response_123"
assert response.model_id == "test-model"
async def test_response_format_parse_path_with_conversation_id() -> None:
"""Test get_response response_format parsing path with set conversation ID."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
# Mock successful parse response
mock_parsed_response = MagicMock()
mock_parsed_response.id = "parsed_response_123"
mock_parsed_response.text = "Parsed response"
mock_parsed_response.model = "test-model"
mock_parsed_response.created_at = 1000000000
mock_parsed_response.metadata = {}
mock_parsed_response.output_parsed = None
mock_parsed_response.usage = None
mock_parsed_response.finish_reason = None
mock_parsed_response.conversation = MagicMock()
mock_parsed_response.conversation.id = "conversation_456"
with patch.object(client.client.responses, "parse", return_value=mock_parsed_response):
response = await client.get_response(
messages=[ChatMessage(role="user", text="Test message")], response_format=OutputStruct, store=True
)
assert response.response_id == "parsed_response_123"
assert response.conversation_id == "conversation_456"
assert response.model_id == "test-model"
async def test_bad_request_error_non_content_filter() -> None:
"""Test get_response BadRequestError without content_filter."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
@@ -454,7 +481,7 @@ async def test_get_streaming_response_with_all_parameters() -> None:
def test_response_content_creation_with_annotations() -> None:
"""Test _create_response_content with different annotation types."""
"""Test _parse_response_from_openai with different annotation types."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
# Create a mock response with annotated text content
@@ -485,7 +512,7 @@ def test_response_content_creation_with_annotations() -> None:
mock_response.output = [mock_message_item]
with patch.object(client, "_get_metadata_from_response", return_value={}):
response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore
response = client._parse_response_from_openai(mock_response, chat_options=ChatOptions()) # type: ignore
assert len(response.messages[0].contents) >= 1
assert isinstance(response.messages[0].contents[0], TextContent)
@@ -494,7 +521,7 @@ def test_response_content_creation_with_annotations() -> None:
def test_response_content_creation_with_refusal() -> None:
"""Test _create_response_content with refusal content."""
"""Test _parse_response_from_openai with refusal content."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
# Create a mock response with refusal content
@@ -516,7 +543,7 @@ def test_response_content_creation_with_refusal() -> None:
mock_response.output = [mock_message_item]
response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore
response = client._parse_response_from_openai(mock_response, chat_options=ChatOptions()) # type: ignore
assert len(response.messages[0].contents) == 1
assert isinstance(response.messages[0].contents[0], TextContent)
@@ -524,7 +551,7 @@ def test_response_content_creation_with_refusal() -> None:
def test_response_content_creation_with_reasoning() -> None:
"""Test _create_response_content with reasoning content."""
"""Test _parse_response_from_openai with reasoning content."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
# Create a mock response with reasoning content
@@ -546,7 +573,7 @@ def test_response_content_creation_with_reasoning() -> None:
mock_response.output = [mock_reasoning_item]
response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore
response = client._parse_response_from_openai(mock_response, chat_options=ChatOptions()) # type: ignore
assert len(response.messages[0].contents) == 2
assert isinstance(response.messages[0].contents[0], TextReasoningContent)
@@ -554,7 +581,7 @@ def test_response_content_creation_with_reasoning() -> None:
def test_response_content_creation_with_code_interpreter() -> None:
"""Test _create_response_content with code interpreter outputs."""
"""Test _parse_response_from_openai with code interpreter outputs."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
@@ -582,7 +609,7 @@ def test_response_content_creation_with_code_interpreter() -> None:
mock_response.output = [mock_code_interpreter_item]
response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore
response = client._parse_response_from_openai(mock_response, chat_options=ChatOptions()) # type: ignore
assert len(response.messages[0].contents) == 2
assert isinstance(response.messages[0].contents[0], TextContent)
@@ -593,7 +620,7 @@ def test_response_content_creation_with_code_interpreter() -> None:
def test_response_content_creation_with_function_call() -> None:
"""Test _create_response_content with function call content."""
"""Test _parse_response_from_openai with function call content."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
# Create a mock response with function call
@@ -614,7 +641,7 @@ def test_response_content_creation_with_function_call() -> None:
mock_response.output = [mock_function_call_item]
response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore
response = client._parse_response_from_openai(mock_response, chat_options=ChatOptions()) # type: ignore
assert len(response.messages[0].contents) == 1
assert isinstance(response.messages[0].contents[0], FunctionCallContent)
@@ -624,7 +651,7 @@ def test_response_content_creation_with_function_call() -> None:
assert function_call.arguments == '{"location": "Seattle"}'
def test_tools_to_response_tools_with_hosted_mcp() -> None:
def test_prepare_tools_for_openai_with_hosted_mcp() -> None:
"""Test that HostedMCPTool is converted to the correct response tool dict."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
@@ -638,7 +665,7 @@ def test_tools_to_response_tools_with_hosted_mcp() -> None:
additional_properties={"custom": "value"},
)
resp_tools = client._tools_to_response_tools([tool])
resp_tools = client._prepare_tools_for_openai([tool])
assert isinstance(resp_tools, list)
assert len(resp_tools) == 1
mcp = resp_tools[0]
@@ -654,7 +681,7 @@ def test_tools_to_response_tools_with_hosted_mcp() -> None:
assert "require_approval" in mcp
def test_create_response_content_with_mcp_approval_request() -> None:
def test_parse_response_from_openai_with_mcp_approval_request() -> None:
"""Test that a non-streaming mcp_approval_request is parsed into FunctionApprovalRequestContent."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
@@ -675,7 +702,7 @@ def test_create_response_content_with_mcp_approval_request() -> None:
mock_response.output = [mock_item]
response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore
response = client._parse_response_from_openai(mock_response, chat_options=ChatOptions()) # type: ignore
assert isinstance(response.messages[0].contents[0], FunctionApprovalRequestContent)
req = response.messages[0].contents[0]
@@ -716,7 +743,7 @@ def test_responses_client_created_at_uses_utc(openai_unit_test_env: dict[str, st
mock_response.output = [mock_message_item]
with patch.object(client, "_get_metadata_from_response", return_value={}):
response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore
response = client._parse_response_from_openai(mock_response, chat_options=ChatOptions()) # type: ignore
# Verify that created_at is correctly formatted as UTC
assert response.created_at is not None
@@ -730,7 +757,7 @@ def test_responses_client_created_at_uses_utc(openai_unit_test_env: dict[str, st
)
def test_tools_to_response_tools_with_raw_image_generation() -> None:
def test_prepare_tools_for_openai_with_raw_image_generation() -> None:
"""Test that raw image_generation tool dict is handled correctly with parameter mapping."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
@@ -744,7 +771,7 @@ def test_tools_to_response_tools_with_raw_image_generation() -> None:
"background": "transparent",
}
resp_tools = client._tools_to_response_tools([tool])
resp_tools = client._prepare_tools_for_openai([tool])
assert isinstance(resp_tools, list)
assert len(resp_tools) == 1
@@ -759,7 +786,7 @@ def test_tools_to_response_tools_with_raw_image_generation() -> None:
assert image_tool["output_compression"] == 75
def test_tools_to_response_tools_with_raw_image_generation_openai_responses_params() -> None:
def test_prepare_tools_for_openai_with_raw_image_generation_openai_responses_params() -> None:
"""Test raw image_generation tool with OpenAI-specific parameters."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
@@ -773,7 +800,7 @@ def test_tools_to_response_tools_with_raw_image_generation_openai_responses_para
"partial_images": 2, # Should be integer 0-3
}
resp_tools = client._tools_to_response_tools([tool])
resp_tools = client._prepare_tools_for_openai([tool])
assert isinstance(resp_tools, list)
assert len(resp_tools) == 1
@@ -791,14 +818,14 @@ def test_tools_to_response_tools_with_raw_image_generation_openai_responses_para
assert tool_dict["partial_images"] == 2
def test_tools_to_response_tools_with_raw_image_generation_minimal() -> None:
def test_prepare_tools_for_openai_with_raw_image_generation_minimal() -> None:
"""Test raw image_generation tool with minimal configuration."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
# Test with minimal parameters (just type)
tool = {"type": "image_generation"}
resp_tools = client._tools_to_response_tools([tool])
resp_tools = client._prepare_tools_for_openai([tool])
assert isinstance(resp_tools, list)
assert len(resp_tools) == 1
@@ -809,7 +836,7 @@ def test_tools_to_response_tools_with_raw_image_generation_minimal() -> None:
assert len(image_tool) == 1
def test_create_streaming_response_content_with_mcp_approval_request() -> None:
def test_parse_chunk_from_openai_with_mcp_approval_request() -> None:
"""Test that a streaming mcp_approval_request event is parsed into FunctionApprovalRequestContent."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
chat_options = ChatOptions()
@@ -825,7 +852,7 @@ def test_create_streaming_response_content_with_mcp_approval_request() -> None:
mock_item.server_label = "My_MCP"
mock_event.item = mock_item
update = client._create_streaming_response_content(mock_event, chat_options, function_call_ids)
update = client._parse_chunk_from_openai(mock_event, chat_options, function_call_ids)
assert any(isinstance(c, FunctionApprovalRequestContent) for c in update.contents)
fa = next(c for c in update.contents if isinstance(c, FunctionApprovalRequestContent))
assert fa.id == "approval-stream-1"
@@ -901,7 +928,7 @@ async def test_end_to_end_mcp_approval_flow(span_exporter) -> None:
def test_usage_details_basic() -> None:
"""Test _usage_details_from_openai without cached or reasoning tokens."""
"""Test _parse_usage_from_openai without cached or reasoning tokens."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
mock_usage = MagicMock()
@@ -911,7 +938,7 @@ def test_usage_details_basic() -> None:
mock_usage.input_tokens_details = None
mock_usage.output_tokens_details = None
details = client._usage_details_from_openai(mock_usage) # type: ignore
details = client._parse_usage_from_openai(mock_usage) # type: ignore
assert details is not None
assert details.input_token_count == 100
assert details.output_token_count == 50
@@ -919,7 +946,7 @@ def test_usage_details_basic() -> None:
def test_usage_details_with_cached_tokens() -> None:
"""Test _usage_details_from_openai with cached input tokens."""
"""Test _parse_usage_from_openai with cached input tokens."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
mock_usage = MagicMock()
@@ -930,14 +957,14 @@ def test_usage_details_with_cached_tokens() -> None:
mock_usage.input_tokens_details.cached_tokens = 25
mock_usage.output_tokens_details = None
details = client._usage_details_from_openai(mock_usage) # type: ignore
details = client._parse_usage_from_openai(mock_usage) # type: ignore
assert details is not None
assert details.input_token_count == 200
assert details.additional_counts["openai.cached_input_tokens"] == 25
def test_usage_details_with_reasoning_tokens() -> None:
"""Test _usage_details_from_openai with reasoning tokens."""
"""Test _parse_usage_from_openai with reasoning tokens."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
mock_usage = MagicMock()
@@ -948,7 +975,7 @@ def test_usage_details_with_reasoning_tokens() -> None:
mock_usage.output_tokens_details = MagicMock()
mock_usage.output_tokens_details.reasoning_tokens = 30
details = client._usage_details_from_openai(mock_usage) # type: ignore
details = client._parse_usage_from_openai(mock_usage) # type: ignore
assert details is not None
assert details.output_token_count == 80
assert details.additional_counts["openai.reasoning_tokens"] == 30
@@ -975,7 +1002,7 @@ def test_get_metadata_from_response() -> None:
def test_streaming_response_basic_structure() -> None:
"""Test that _create_streaming_response_content returns proper structure."""
"""Test that _parse_chunk_from_openai returns proper structure."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
chat_options = ChatOptions(store=True)
function_call_ids: dict[int, tuple[str, str]] = {}
@@ -983,7 +1010,7 @@ def test_streaming_response_basic_structure() -> None:
# Test with a basic mock event to ensure the method returns proper structure
mock_event = MagicMock()
response = client._create_streaming_response_content(mock_event, chat_options, function_call_ids) # type: ignore
response = client._parse_chunk_from_openai(mock_event, chat_options, function_call_ids) # type: ignore
# Should get a valid ChatResponseUpdate structure
assert isinstance(response, ChatResponseUpdate)
@@ -993,6 +1020,44 @@ def test_streaming_response_basic_structure() -> None:
assert response.raw_representation is mock_event
def test_streaming_response_created_type() -> None:
"""Test streaming response with created type"""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
chat_options = ChatOptions()
function_call_ids: dict[int, tuple[str, str]] = {}
mock_event = MagicMock()
mock_event.type = "response.created"
mock_event.response = MagicMock()
mock_event.response.id = "resp_1234"
mock_event.response.conversation = MagicMock()
mock_event.response.conversation.id = "conv_5678"
response = client._parse_chunk_from_openai(mock_event, chat_options, function_call_ids)
assert response.response_id == "resp_1234"
assert response.conversation_id == "conv_5678"
def test_streaming_response_in_progress_type() -> None:
"""Test streaming response with in_progress type"""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
chat_options = ChatOptions()
function_call_ids: dict[int, tuple[str, str]] = {}
mock_event = MagicMock()
mock_event.type = "response.in_progress"
mock_event.response = MagicMock()
mock_event.response.id = "resp_1234"
mock_event.response.conversation = MagicMock()
mock_event.response.conversation.id = "conv_5678"
response = client._parse_chunk_from_openai(mock_event, chat_options, function_call_ids)
assert response.response_id == "resp_1234"
assert response.conversation_id == "conv_5678"
def test_streaming_annotation_added_with_file_path() -> None:
"""Test streaming annotation added event with file_path type extracts HostedFileContent."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
@@ -1008,7 +1073,7 @@ def test_streaming_annotation_added_with_file_path() -> None:
"index": 42,
}
response = client._create_streaming_response_content(mock_event, chat_options, function_call_ids)
response = client._parse_chunk_from_openai(mock_event, chat_options, function_call_ids)
assert len(response.contents) == 1
content = response.contents[0]
@@ -1035,7 +1100,7 @@ def test_streaming_annotation_added_with_file_citation() -> None:
"index": 15,
}
response = client._create_streaming_response_content(mock_event, chat_options, function_call_ids)
response = client._parse_chunk_from_openai(mock_event, chat_options, function_call_ids)
assert len(response.contents) == 1
content = response.contents[0]
@@ -1064,7 +1129,7 @@ def test_streaming_annotation_added_with_container_file_citation() -> None:
"end_index": 50,
}
response = client._create_streaming_response_content(mock_event, chat_options, function_call_ids)
response = client._parse_chunk_from_openai(mock_event, chat_options, function_call_ids)
assert len(response.contents) == 1
content = response.contents[0]
@@ -1091,7 +1156,7 @@ def test_streaming_annotation_added_with_unknown_type() -> None:
"url": "https://example.com",
}
response = client._create_streaming_response_content(mock_event, chat_options, function_call_ids)
response = client._parse_chunk_from_openai(mock_event, chat_options, function_call_ids)
# url_citation should not produce HostedFileContent
assert len(response.contents) == 0
@@ -1137,8 +1202,8 @@ def test_get_streaming_response_with_response_format() -> None:
asyncio.run(run_streaming())
def test_openai_content_parser_image_content() -> None:
"""Test _openai_content_parser with image content variations."""
def test_prepare_content_for_openai_image_content() -> None:
"""Test _prepare_content_for_openai with image content variations."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
# Test image content with detail parameter and file_id
@@ -1147,7 +1212,7 @@ def test_openai_content_parser_image_content() -> None:
media_type="image/jpeg",
additional_properties={"detail": "high", "file_id": "file_123"},
)
result = client._openai_content_parser(Role.USER, image_content_with_detail, {}) # type: ignore
result = client._prepare_content_for_openai(Role.USER, image_content_with_detail, {}) # type: ignore
assert result["type"] == "input_image"
assert result["image_url"] == "https://example.com/image.jpg"
assert result["detail"] == "high"
@@ -1155,47 +1220,47 @@ def test_openai_content_parser_image_content() -> None:
# Test image content without additional properties (defaults)
image_content_basic = UriContent(uri="https://example.com/basic.png", media_type="image/png")
result = client._openai_content_parser(Role.USER, image_content_basic, {}) # type: ignore
result = client._prepare_content_for_openai(Role.USER, image_content_basic, {}) # type: ignore
assert result["type"] == "input_image"
assert result["detail"] == "auto"
assert result["file_id"] is None
def test_openai_content_parser_audio_content() -> None:
"""Test _openai_content_parser with audio content variations."""
def test_prepare_content_for_openai_audio_content() -> None:
"""Test _prepare_content_for_openai with audio content variations."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
# Test WAV audio content
wav_content = UriContent(uri="data:audio/wav;base64,abc123", media_type="audio/wav")
result = client._openai_content_parser(Role.USER, wav_content, {}) # type: ignore
result = client._prepare_content_for_openai(Role.USER, wav_content, {}) # type: ignore
assert result["type"] == "input_audio"
assert result["input_audio"]["data"] == "data:audio/wav;base64,abc123"
assert result["input_audio"]["format"] == "wav"
# Test MP3 audio content
mp3_content = UriContent(uri="data:audio/mp3;base64,def456", media_type="audio/mp3")
result = client._openai_content_parser(Role.USER, mp3_content, {}) # type: ignore
result = client._prepare_content_for_openai(Role.USER, mp3_content, {}) # type: ignore
assert result["type"] == "input_audio"
assert result["input_audio"]["format"] == "mp3"
def test_openai_content_parser_unsupported_content() -> None:
"""Test _openai_content_parser with unsupported content types."""
def test_prepare_content_for_openai_unsupported_content() -> None:
"""Test _prepare_content_for_openai with unsupported content types."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
# Test unsupported audio format
unsupported_audio = UriContent(uri="data:audio/ogg;base64,ghi789", media_type="audio/ogg")
result = client._openai_content_parser(Role.USER, unsupported_audio, {}) # type: ignore
result = client._prepare_content_for_openai(Role.USER, unsupported_audio, {}) # type: ignore
assert result == {}
# Test non-media content
text_uri_content = UriContent(uri="https://example.com/document.txt", media_type="text/plain")
result = client._openai_content_parser(Role.USER, text_uri_content, {}) # type: ignore
result = client._prepare_content_for_openai(Role.USER, text_uri_content, {}) # type: ignore
assert result == {}
def test_create_streaming_response_content_code_interpreter() -> None:
"""Test _create_streaming_response_content with code_interpreter_call."""
def test_parse_chunk_from_openai_code_interpreter() -> None:
"""Test _parse_chunk_from_openai with code_interpreter_call."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
chat_options = ChatOptions()
function_call_ids: dict[int, tuple[str, str]] = {}
@@ -1211,15 +1276,15 @@ def test_create_streaming_response_content_code_interpreter() -> None:
mock_item_image.code = None
mock_event_image.item = mock_item_image
result = client._create_streaming_response_content(mock_event_image, chat_options, function_call_ids) # type: ignore
result = client._parse_chunk_from_openai(mock_event_image, chat_options, function_call_ids) # type: ignore
assert len(result.contents) == 1
assert isinstance(result.contents[0], UriContent)
assert result.contents[0].uri == "https://example.com/plot.png"
assert result.contents[0].media_type == "image"
def test_create_streaming_response_content_reasoning() -> None:
"""Test _create_streaming_response_content with reasoning content."""
def test_parse_chunk_from_openai_reasoning() -> None:
"""Test _parse_chunk_from_openai with reasoning content."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
chat_options = ChatOptions()
function_call_ids: dict[int, tuple[str, str]] = {}
@@ -1234,7 +1299,7 @@ def test_create_streaming_response_content_reasoning() -> None:
mock_item_reasoning.summary = ["Problem analysis summary"]
mock_event_reasoning.item = mock_item_reasoning
result = client._create_streaming_response_content(mock_event_reasoning, chat_options, function_call_ids) # type: ignore
result = client._parse_chunk_from_openai(mock_event_reasoning, chat_options, function_call_ids) # type: ignore
assert len(result.contents) == 1
assert isinstance(result.contents[0], TextReasoningContent)
assert result.contents[0].text == "Analyzing the problem step by step..."
@@ -1242,8 +1307,8 @@ def test_create_streaming_response_content_reasoning() -> None:
assert result.contents[0].additional_properties["summary"] == "Problem analysis summary"
def test_openai_content_parser_text_reasoning_comprehensive() -> None:
"""Test _openai_content_parser with TextReasoningContent all additional properties."""
def test_prepare_content_for_openai_text_reasoning_comprehensive() -> None:
"""Test _prepare_content_for_openai with TextReasoningContent all additional properties."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
# Test TextReasoningContent with all additional properties
@@ -1255,7 +1320,7 @@ def test_openai_content_parser_text_reasoning_comprehensive() -> None:
"encrypted_content": "secure_data_456",
},
)
result = client._openai_content_parser(Role.ASSISTANT, comprehensive_reasoning, {}) # type: ignore
result = client._prepare_content_for_openai(Role.ASSISTANT, comprehensive_reasoning, {}) # type: ignore
assert result["type"] == "reasoning"
assert result["summary"]["text"] == "Comprehensive reasoning summary"
assert result["status"] == "in_progress"
@@ -1280,7 +1345,7 @@ def test_streaming_reasoning_text_delta_event() -> None:
)
with patch.object(client, "_get_metadata_from_response", return_value={}) as mock_metadata:
response = client._create_streaming_response_content(event, chat_options, function_call_ids) # type: ignore
response = client._parse_chunk_from_openai(event, chat_options, function_call_ids) # type: ignore
assert len(response.contents) == 1
assert isinstance(response.contents[0], TextReasoningContent)
@@ -1305,7 +1370,7 @@ def test_streaming_reasoning_text_done_event() -> None:
)
with patch.object(client, "_get_metadata_from_response", return_value={"test": "data"}) as mock_metadata:
response = client._create_streaming_response_content(event, chat_options, function_call_ids) # type: ignore
response = client._parse_chunk_from_openai(event, chat_options, function_call_ids) # type: ignore
assert len(response.contents) == 1
assert isinstance(response.contents[0], TextReasoningContent)
@@ -1331,7 +1396,7 @@ def test_streaming_reasoning_summary_text_delta_event() -> None:
)
with patch.object(client, "_get_metadata_from_response", return_value={}) as mock_metadata:
response = client._create_streaming_response_content(event, chat_options, function_call_ids) # type: ignore
response = client._parse_chunk_from_openai(event, chat_options, function_call_ids) # type: ignore
assert len(response.contents) == 1
assert isinstance(response.contents[0], TextReasoningContent)
@@ -1356,7 +1421,7 @@ def test_streaming_reasoning_summary_text_done_event() -> None:
)
with patch.object(client, "_get_metadata_from_response", return_value={"custom": "meta"}) as mock_metadata:
response = client._create_streaming_response_content(event, chat_options, function_call_ids) # type: ignore
response = client._parse_chunk_from_openai(event, chat_options, function_call_ids) # type: ignore
assert len(response.contents) == 1
assert isinstance(response.contents[0], TextReasoningContent)
@@ -1392,8 +1457,8 @@ def test_streaming_reasoning_events_preserve_metadata() -> None:
)
with patch.object(client, "_get_metadata_from_response", return_value={"test": "metadata"}):
text_response = client._create_streaming_response_content(text_event, chat_options, function_call_ids) # type: ignore
reasoning_response = client._create_streaming_response_content(reasoning_event, chat_options, function_call_ids) # type: ignore
text_response = client._parse_chunk_from_openai(text_event, chat_options, function_call_ids) # type: ignore
reasoning_response = client._parse_chunk_from_openai(reasoning_event, chat_options, function_call_ids) # type: ignore
# Both should preserve metadata
assert text_response.additional_properties == {"test": "metadata"}
@@ -1404,7 +1469,7 @@ def test_streaming_reasoning_events_preserve_metadata() -> None:
assert isinstance(reasoning_response.contents[0], TextReasoningContent)
def test_create_response_content_image_generation_raw_base64():
def test_parse_response_from_openai_image_generation_raw_base64():
"""Test image generation response parsing with raw base64 string."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
@@ -1428,7 +1493,7 @@ def test_create_response_content_image_generation_raw_base64():
mock_response.output = [mock_item]
with patch.object(client, "_get_metadata_from_response", return_value={}):
response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore
response = client._parse_response_from_openai(mock_response, chat_options=ChatOptions()) # type: ignore
# Verify the response contains DataContent with proper URI and media_type
assert len(response.messages[0].contents) == 1
@@ -1438,7 +1503,7 @@ def test_create_response_content_image_generation_raw_base64():
assert content.media_type == "image/png"
def test_create_response_content_image_generation_existing_data_uri():
def test_parse_response_from_openai_image_generation_existing_data_uri():
"""Test image generation response parsing with existing data URI."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
@@ -1461,7 +1526,7 @@ def test_create_response_content_image_generation_existing_data_uri():
mock_response.output = [mock_item]
with patch.object(client, "_get_metadata_from_response", return_value={}):
response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore
response = client._parse_response_from_openai(mock_response, chat_options=ChatOptions()) # type: ignore
# Verify the response contains DataContent with proper media_type parsed from URI
assert len(response.messages[0].contents) == 1
@@ -1471,7 +1536,7 @@ def test_create_response_content_image_generation_existing_data_uri():
assert content.media_type == "image/webp"
def test_create_response_content_image_generation_format_detection():
def test_parse_response_from_openai_image_generation_format_detection():
"""Test different image format detection from base64 data."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
@@ -1493,7 +1558,7 @@ def test_create_response_content_image_generation_format_detection():
mock_response_jpeg.output = [mock_item_jpeg]
with patch.object(client, "_get_metadata_from_response", return_value={}):
response_jpeg = client._create_response_content(mock_response_jpeg, chat_options=ChatOptions()) # type: ignore
response_jpeg = client._parse_response_from_openai(mock_response_jpeg, chat_options=ChatOptions()) # type: ignore
content_jpeg = response_jpeg.messages[0].contents[0]
assert isinstance(content_jpeg, DataContent)
assert content_jpeg.media_type == "image/jpeg"
@@ -1517,14 +1582,14 @@ def test_create_response_content_image_generation_format_detection():
mock_response_webp.output = [mock_item_webp]
with patch.object(client, "_get_metadata_from_response", return_value={}):
response_webp = client._create_response_content(mock_response_webp, chat_options=ChatOptions()) # type: ignore
response_webp = client._parse_response_from_openai(mock_response_webp, chat_options=ChatOptions()) # type: ignore
content_webp = response_webp.messages[0].contents[0]
assert isinstance(content_webp, DataContent)
assert content_webp.media_type == "image/webp"
assert "data:image/webp;base64," in content_webp.uri
def test_create_response_content_image_generation_fallback():
def test_parse_response_from_openai_image_generation_fallback():
"""Test image generation with invalid base64 falls back to PNG."""
client = OpenAIResponsesClient(model_id="test-model", api_key="test-key")
@@ -1547,7 +1612,7 @@ def test_create_response_content_image_generation_fallback():
mock_response.output = [mock_item]
with patch.object(client, "_get_metadata_from_response", return_value={}):
response = client._create_response_content(mock_response, chat_options=ChatOptions()) # type: ignore
response = client._parse_response_from_openai(mock_response, chat_options=ChatOptions()) # type: ignore
# Verify it falls back to PNG format for unrecognized binary data
assert len(response.messages[0].contents) == 1
@@ -1563,21 +1628,21 @@ async def test_prepare_options_store_parameter_handling() -> None:
test_conversation_id = "test-conversation-123"
chat_options = ChatOptions(store=True, conversation_id=test_conversation_id)
options = await client.prepare_options(messages, chat_options)
options = await client._prepare_options(messages, chat_options) # type: ignore
assert options["store"] is True
assert options["previous_response_id"] == test_conversation_id
chat_options = ChatOptions(store=False, conversation_id="")
options = await client.prepare_options(messages, chat_options)
options = await client._prepare_options(messages, chat_options) # type: ignore
assert options["store"] is False
chat_options = ChatOptions(store=None, conversation_id=None)
options = await client.prepare_options(messages, chat_options)
options = await client._prepare_options(messages, chat_options) # type: ignore
assert "store" not in options
assert "previous_response_id" not in options
chat_options = ChatOptions()
options = await client.prepare_options(messages, chat_options)
options = await client._prepare_options(messages, chat_options) # type: ignore
assert "store" not in options
assert "previous_response_id" not in options
python/packages/core/tests/workflow/test_workflow_agent.py
+180
View File
@@ -1,11 +1,13 @@
# Copyright (c) Microsoft. All rights reserved.
import uuid
from collections.abc import AsyncIterable
from typing import Any
import pytest
from agent_framework import (
AgentProtocol,
AgentRunResponse,
AgentRunResponseUpdate,
AgentRunUpdateEvent,
@@ -422,6 +424,48 @@ class TestWorkflowAgent:
assert isinstance(updates[2].raw_representation, CustomData)
assert updates[2].raw_representation.value == 42
async def test_workflow_as_agent_yield_output_with_list_of_chat_messages(self) -> None:
"""Test that yield_output with list[ChatMessage] extracts contents from all messages.
Note: TextContent items are coalesced by _finalize_response, so multiple text contents
become a single merged TextContent in the final response.
"""
@executor
async def list_yielding_executor(messages: list[ChatMessage], ctx: WorkflowContext) -> None:
# Yield a list of ChatMessages (as SequentialBuilder does)
msg_list = [
ChatMessage(role=Role.USER, contents=[TextContent(text="first message")]),
ChatMessage(role=Role.ASSISTANT, contents=[TextContent(text="second message")]),
ChatMessage(
role=Role.ASSISTANT,
contents=[TextContent(text="third"), TextContent(text="fourth")],
),
]
await ctx.yield_output(msg_list)
workflow = WorkflowBuilder().set_start_executor(list_yielding_executor).build()
agent = workflow.as_agent("list-msg-agent")
# Verify streaming returns the update with all 4 contents before coalescing
updates: list[AgentRunResponseUpdate] = []
async for update in agent.run_stream("test"):
updates.append(update)
assert len(updates) == 1
assert len(updates[0].contents) == 4
texts = [c.text for c in updates[0].contents if isinstance(c, TextContent)]
assert texts == ["first message", "second message", "third", "fourth"]
# Verify run() coalesces text contents (expected behavior)
result = await agent.run("test")
assert isinstance(result, AgentRunResponse)
assert len(result.messages) == 1
# TextContent items are coalesced into one
assert len(result.messages[0].contents) == 1
assert result.messages[0].text == "first messagesecond messagethirdfourth"
async def test_thread_conversation_history_included_in_workflow_run(self) -> None:
"""Test that conversation history from thread is included when running WorkflowAgent.
@@ -521,6 +565,142 @@ class TestWorkflowAgent:
checkpoints = await checkpoint_storage.list_checkpoints(workflow.id)
assert len(checkpoints) > 0, "Checkpoints should have been created when checkpoint_storage is provided"
async def test_agent_executor_output_response_false_filters_streaming_events(self):
"""Test that AgentExecutor with output_response=False does not surface streaming events."""
class MockAgent(AgentProtocol):
"""Mock agent for testing."""
def __init__(self, name: str, response_text: str) -> None:
self._name = name
self._response_text = response_text
self._description: str | None = None
@property
def name(self) -> str | None:
return self._name
@property
def description(self) -> str | None:
return self._description
def get_new_thread(self) -> AgentThread:
return AgentThread()
async def run(self, messages: Any, *, thread: AgentThread | None = None, **kwargs: Any) -> AgentRunResponse:
return AgentRunResponse(
messages=[ChatMessage(role=Role.ASSISTANT, text=self._response_text)],
text=self._response_text,
)
async def run_stream(
self, messages: Any, *, thread: AgentThread | None = None, **kwargs: Any
) -> AsyncIterable[AgentRunResponseUpdate]:
for word in self._response_text.split():
yield AgentRunResponseUpdate(
contents=[TextContent(text=word + " ")],
role=Role.ASSISTANT,
author_name=self._name,
)
@executor
async def start_executor(messages: list[ChatMessage], ctx: WorkflowContext) -> None:
from agent_framework import AgentExecutorRequest
await ctx.yield_output("Start output")
await ctx.send_message(AgentExecutorRequest(messages=messages, should_respond=True))
# Build workflow: start -> agent1 (no output) -> agent2 (output_response=True)
workflow = (
WorkflowBuilder()
.register_executor(lambda: start_executor, "start")
.register_agent(lambda: MockAgent("agent1", "Agent1 output - should NOT appear"), "agent1")
.register_agent(
lambda: MockAgent("agent2", "Agent2 output - SHOULD appear"), "agent2", output_response=True
)
.set_start_executor("start")
.add_edge("start", "agent1")
.add_edge("agent1", "agent2")
.build()
)
agent = WorkflowAgent(workflow=workflow, name="Test Agent")
result = await agent.run("Test input")
# Collect all message texts
texts = [msg.text for msg in result.messages if msg.text]
# Start output should appear (from yield_output)
assert any("Start output" in t for t in texts), "Start output should appear"
# Agent1 output should NOT appear (output_response=False)
assert not any("Agent1" in t for t in texts), "Agent1 output should NOT appear"
# Agent2 output should appear (output_response=True)
assert any("Agent2" in t for t in texts), "Agent2 output should appear"
async def test_agent_executor_output_response_no_duplicate_from_workflow_output_event(self):
"""Test that AgentExecutor with output_response=True does not duplicate content."""
class MockAgent(AgentProtocol):
"""Mock agent for testing."""
def __init__(self, name: str, response_text: str) -> None:
self._name = name
self._response_text = response_text
self._description: str | None = None
@property
def name(self) -> str | None:
return self._name
@property
def description(self) -> str | None:
return self._description
def get_new_thread(self) -> AgentThread:
return AgentThread()
async def run(self, messages: Any, *, thread: AgentThread | None = None, **kwargs: Any) -> AgentRunResponse:
return AgentRunResponse(
messages=[ChatMessage(role=Role.ASSISTANT, text=self._response_text)],
text=self._response_text,
)
async def run_stream(
self, messages: Any, *, thread: AgentThread | None = None, **kwargs: Any
) -> AsyncIterable[AgentRunResponseUpdate]:
yield AgentRunResponseUpdate(
contents=[TextContent(text=self._response_text)],
role=Role.ASSISTANT,
author_name=self._name,
)
@executor
async def start_executor(messages: list[ChatMessage], ctx: WorkflowContext) -> None:
from agent_framework import AgentExecutorRequest
await ctx.send_message(AgentExecutorRequest(messages=messages, should_respond=True))
# Build workflow with single agent that has output_response=True
workflow = (
WorkflowBuilder()
.register_executor(lambda: start_executor, "start")
.register_agent(lambda: MockAgent("agent", "Unique response text"), "agent", output_response=True)
.set_start_executor("start")
.add_edge("start", "agent")
.build()
)
agent = WorkflowAgent(workflow=workflow, name="Test Agent")
result = await agent.run("Test input")
# Count occurrences of the unique response text
unique_text_count = sum(1 for msg in result.messages if msg.text and "Unique response text" in msg.text)
# Should appear exactly once (not duplicated from both streaming and WorkflowOutputEvent)
assert unique_text_count == 1, f"Response should appear exactly once, but appeared {unique_text_count} times"
class TestWorkflowAgentMergeUpdates:
"""Test cases specifically for the WorkflowAgent.merge_updates static method."""
python/packages/core/tests/workflow/test_workflow_builder.py
+4 -2
View File
@@ -245,7 +245,8 @@ def test_register_multiple_executors():
# Build workflow with edges using registered names
workflow = (
builder.set_start_executor("ExecutorA")
builder
.set_start_executor("ExecutorA")
.add_edge("ExecutorA", "ExecutorB")
.add_edge("ExecutorB", "ExecutorC")
.build()
@@ -426,7 +427,8 @@ def test_register_with_fan_in_edges():
# Add fan-in edges using registered names
# Both Source1 and Source2 need to be reachable, so connect Source1 to Source2
workflow = (
builder.set_start_executor("Source1")
builder
.set_start_executor("Source1")
.add_edge("Source1", "Source2")
.add_fan_in_edges(["Source1", "Source2"], "Aggregator")
.build()
python/packages/core/tests/workflow/test_workflow_kwargs.py
+263
View File
@@ -490,3 +490,266 @@ async def test_magentic_kwargs_stored_in_shared_state() -> None:
# endregion
# region WorkflowAgent (as_agent) kwargs Tests
async def test_workflow_as_agent_run_propagates_kwargs_to_underlying_agent() -> None:
"""Test that kwargs passed to workflow_agent.run() flow through to the underlying agents."""
agent = _KwargsCapturingAgent(name="inner_agent")
workflow = SequentialBuilder().participants([agent]).build()
workflow_agent = workflow.as_agent(name="TestWorkflowAgent")
custom_data = {"endpoint": "https://api.example.com", "version": "v1"}
user_token = {"user_name": "alice", "access_level": "admin"}
_ = await workflow_agent.run(
"test message",
custom_data=custom_data,
user_token=user_token,
)
# Verify inner agent received kwargs
assert len(agent.captured_kwargs) >= 1, "Inner agent should have been invoked at least once"
received = agent.captured_kwargs[0]
assert "custom_data" in received, "Inner agent should receive custom_data kwarg"
assert "user_token" in received, "Inner agent should receive user_token kwarg"
assert received["custom_data"] == custom_data
assert received["user_token"] == user_token
async def test_workflow_as_agent_run_stream_propagates_kwargs_to_underlying_agent() -> None:
"""Test that kwargs passed to workflow_agent.run_stream() flow through to the underlying agents."""
agent = _KwargsCapturingAgent(name="inner_agent")
workflow = SequentialBuilder().participants([agent]).build()
workflow_agent = workflow.as_agent(name="TestWorkflowAgent")
custom_data = {"session_id": "xyz123"}
api_token = "secret-token"
async for _ in workflow_agent.run_stream(
"test message",
custom_data=custom_data,
api_token=api_token,
):
pass
# Verify inner agent received kwargs
assert len(agent.captured_kwargs) >= 1, "Inner agent should have been invoked at least once"
received = agent.captured_kwargs[0]
assert "custom_data" in received, "Inner agent should receive custom_data kwarg"
assert "api_token" in received, "Inner agent should receive api_token kwarg"
assert received["custom_data"] == custom_data
assert received["api_token"] == api_token
async def test_workflow_as_agent_propagates_kwargs_to_multiple_agents() -> None:
"""Test that kwargs flow to all agents when using workflow.as_agent()."""
agent1 = _KwargsCapturingAgent(name="agent1")
agent2 = _KwargsCapturingAgent(name="agent2")
workflow = SequentialBuilder().participants([agent1, agent2]).build()
workflow_agent = workflow.as_agent(name="MultiAgentWorkflow")
custom_data = {"batch_id": "batch-001"}
_ = await workflow_agent.run("test message", custom_data=custom_data)
# Both agents should have received kwargs
assert len(agent1.captured_kwargs) >= 1, "First agent should be invoked"
assert len(agent2.captured_kwargs) >= 1, "Second agent should be invoked"
assert agent1.captured_kwargs[0].get("custom_data") == custom_data
assert agent2.captured_kwargs[0].get("custom_data") == custom_data
async def test_workflow_as_agent_kwargs_with_none_values() -> None:
"""Test that kwargs with None values are passed through correctly via as_agent()."""
agent = _KwargsCapturingAgent(name="none_test_agent")
workflow = SequentialBuilder().participants([agent]).build()
workflow_agent = workflow.as_agent(name="NoneTestWorkflow")
_ = await workflow_agent.run("test", optional_param=None, other_param="value")
assert len(agent.captured_kwargs) >= 1
received = agent.captured_kwargs[0]
assert "optional_param" in received
assert received["optional_param"] is None
assert received["other_param"] == "value"
async def test_workflow_as_agent_kwargs_with_complex_nested_data() -> None:
"""Test that complex nested data structures flow through correctly via as_agent()."""
agent = _KwargsCapturingAgent(name="nested_agent")
workflow = SequentialBuilder().participants([agent]).build()
workflow_agent = workflow.as_agent(name="NestedDataWorkflow")
complex_data = {
"level1": {
"level2": {
"level3": ["a", "b", "c"],
"number": 42,
},
"list": [1, 2, {"nested": True}],
},
}
_ = await workflow_agent.run("test", complex_data=complex_data)
assert len(agent.captured_kwargs) >= 1
received = agent.captured_kwargs[0]
assert received.get("complex_data") == complex_data
# endregion
# region SubWorkflow (WorkflowExecutor) Tests
async def test_subworkflow_kwargs_propagation() -> None:
"""Test that kwargs are propagated to subworkflows.
Verifies kwargs passed to parent workflow.run_stream() flow through to agents
in subworkflows wrapped by WorkflowExecutor.
"""
from agent_framework._workflows._workflow_executor import WorkflowExecutor
# Create an agent inside the subworkflow that captures kwargs
inner_agent = _KwargsCapturingAgent(name="inner_agent")
# Build the inner (sub) workflow with the agent
inner_workflow = SequentialBuilder().participants([inner_agent]).build()
# Wrap the inner workflow in a WorkflowExecutor so it can be used as a subworkflow
subworkflow_executor = WorkflowExecutor(workflow=inner_workflow, id="subworkflow_executor")
# Build the outer (parent) workflow containing the subworkflow
outer_workflow = SequentialBuilder().participants([subworkflow_executor]).build()
# Define kwargs that should propagate to subworkflow
custom_data = {"api_key": "secret123", "endpoint": "https://api.example.com"}
user_token = {"user_name": "alice", "access_level": "admin"}
# Run the outer workflow with kwargs
async for event in outer_workflow.run_stream(
"test message for subworkflow",
custom_data=custom_data,
user_token=user_token,
):
if isinstance(event, WorkflowStatusEvent) and event.state == WorkflowRunState.IDLE:
break
# Verify that the inner agent was called
assert len(inner_agent.captured_kwargs) >= 1, "Inner agent in subworkflow should have been invoked"
received_kwargs = inner_agent.captured_kwargs[0]
# Verify kwargs were propagated from parent workflow to subworkflow agent
assert "custom_data" in received_kwargs, (
f"Subworkflow agent should receive 'custom_data' kwarg. Received keys: {list(received_kwargs.keys())}"
)
assert "user_token" in received_kwargs, (
f"Subworkflow agent should receive 'user_token' kwarg. Received keys: {list(received_kwargs.keys())}"
)
assert received_kwargs.get("custom_data") == custom_data, (
f"Expected custom_data={custom_data}, got {received_kwargs.get('custom_data')}"
)
assert received_kwargs.get("user_token") == user_token, (
f"Expected user_token={user_token}, got {received_kwargs.get('user_token')}"
)
async def test_subworkflow_kwargs_accessible_via_shared_state() -> None:
"""Test that kwargs are accessible via SharedState within subworkflow.
Verifies that WORKFLOW_RUN_KWARGS_KEY is populated in the subworkflow's SharedState
with kwargs from the parent workflow.
"""
from agent_framework import Executor, WorkflowContext, handler
from agent_framework._workflows._workflow_executor import WorkflowExecutor
captured_kwargs_from_state: list[dict[str, Any]] = []
class _SharedStateReader(Executor):
"""Executor that reads kwargs from SharedState for verification."""
@handler
async def read_kwargs(self, msgs: list[ChatMessage], ctx: WorkflowContext[list[ChatMessage]]) -> None:
kwargs_from_state = await ctx.get_shared_state(WORKFLOW_RUN_KWARGS_KEY)
captured_kwargs_from_state.append(kwargs_from_state or {})
await ctx.send_message(msgs)
# Build inner workflow with SharedState reader
state_reader = _SharedStateReader(id="state_reader")
inner_workflow = SequentialBuilder().participants([state_reader]).build()
# Wrap as subworkflow
subworkflow_executor = WorkflowExecutor(workflow=inner_workflow, id="subworkflow")
# Build outer workflow
outer_workflow = SequentialBuilder().participants([subworkflow_executor]).build()
# Run with kwargs
async for event in outer_workflow.run_stream(
"test",
my_custom_kwarg="should_be_propagated",
another_kwarg=42,
):
if isinstance(event, WorkflowStatusEvent) and event.state == WorkflowRunState.IDLE:
break
# Verify the state reader was invoked
assert len(captured_kwargs_from_state) >= 1, "SharedState reader should have been invoked"
kwargs_in_subworkflow = captured_kwargs_from_state[0]
assert kwargs_in_subworkflow.get("my_custom_kwarg") == "should_be_propagated", (
f"Expected 'my_custom_kwarg' in subworkflow SharedState, got: {kwargs_in_subworkflow}"
)
assert kwargs_in_subworkflow.get("another_kwarg") == 42, (
f"Expected 'another_kwarg'=42 in subworkflow SharedState, got: {kwargs_in_subworkflow}"
)
async def test_nested_subworkflow_kwargs_propagation() -> None:
"""Test kwargs propagation through multiple levels of nested subworkflows.
Verifies kwargs flow through 3 levels:
- Outer workflow
- Middle subworkflow (WorkflowExecutor)
- Inner subworkflow (WorkflowExecutor) with agent
"""
from agent_framework._workflows._workflow_executor import WorkflowExecutor
# Innermost agent
inner_agent = _KwargsCapturingAgent(name="deeply_nested_agent")
# Build inner workflow
inner_workflow = SequentialBuilder().participants([inner_agent]).build()
inner_executor = WorkflowExecutor(workflow=inner_workflow, id="inner_executor")
# Build middle workflow containing inner
middle_workflow = SequentialBuilder().participants([inner_executor]).build()
middle_executor = WorkflowExecutor(workflow=middle_workflow, id="middle_executor")
# Build outer workflow containing middle
outer_workflow = SequentialBuilder().participants([middle_executor]).build()
# Run with kwargs
async for event in outer_workflow.run_stream(
"deeply nested test",
deep_kwarg="should_reach_inner",
):
if isinstance(event, WorkflowStatusEvent) and event.state == WorkflowRunState.IDLE:
break
# Verify inner agent was called
assert len(inner_agent.captured_kwargs) >= 1, "Deeply nested agent should be invoked"
received = inner_agent.captured_kwargs[0]
assert received.get("deep_kwarg") == "should_reach_inner", (
f"Deeply nested agent should receive 'deep_kwarg'. Got: {received}"
)
# endregion