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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/azure-ai/agent_framework_azure_ai/_chat_client.py
+190 -141
View File
@@ -278,22 +278,13 @@ class AzureAIAgentClient(BaseChatClient):
chat_options: ChatOptions,
**kwargs: Any,
) -> AsyncIterable[ChatResponseUpdate]:
# Extract necessary state from messages and options
run_options, required_action_results = await self._create_run_options(messages, chat_options, **kwargs)
# Get the thread ID
thread_id: str | None = (
chat_options.conversation_id
if chat_options.conversation_id is not None
else run_options.get("conversation_id", self.thread_id)
)
# Determine which agent to use and create if needed
# prepare
run_options, required_action_results = await self._prepare_options(messages, chat_options, **kwargs)
agent_id = await self._get_agent_id_or_create(run_options)
# Process and yield each update from the stream
# execute and process
async for update in self._process_stream(
*(await self._create_agent_stream(thread_id, agent_id, run_options, required_action_results))
*(await self._create_agent_stream(agent_id, run_options, required_action_results))
):
yield update
@@ -342,7 +333,6 @@ class AzureAIAgentClient(BaseChatClient):
async def _create_agent_stream(
self,
thread_id: str | None,
agent_id: str,
run_options: dict[str, Any],
required_action_results: list[FunctionResultContent | FunctionApprovalResponseContent] | None,
@@ -352,14 +342,14 @@ class AzureAIAgentClient(BaseChatClient):
Returns:
tuple: (stream, final_thread_id)
"""
thread_id = run_options.pop("thread_id", None)
# Get any active run for this thread
thread_run = await self._get_active_thread_run(thread_id)
stream: AsyncAgentRunStream[AsyncAgentEventHandler[Any]] | AsyncAgentEventHandler[Any]
handler: AsyncAgentEventHandler[Any] = AsyncAgentEventHandler()
tool_run_id, tool_outputs, tool_approvals = self._convert_required_action_to_tool_output(
required_action_results
)
tool_run_id, tool_outputs, tool_approvals = self._prepare_tool_outputs_for_azure_ai(required_action_results)
if (
thread_run is not None
@@ -421,19 +411,11 @@ class AzureAIAgentClient(BaseChatClient):
# No thread ID was provided, so create a new thread.
thread = await self.agents_client.threads.create(
tool_resources=run_options.get("tool_resources"), metadata=run_options.get("metadata")
tool_resources=run_options.get("tool_resources"),
metadata=run_options.get("metadata"),
messages=run_options.get("additional_messages"),
)
thread_id = thread.id
# workaround for: https://github.com/Azure/azure-sdk-for-python/issues/42805
# this occurs when otel is enabled
# once fixed, in the function above, readd:
# `messages=run_options.pop("additional_messages")`
for msg in run_options.pop("additional_messages", []):
await self.agents_client.messages.create(
thread_id=thread_id, role=msg.role, content=msg.content, metadata=msg.metadata
)
# and remove until here.
return thread_id
return thread.id
def _extract_url_citations(
self, message_delta_chunk: MessageDeltaChunk, azure_search_tool_calls: list[dict[str, Any]]
@@ -611,7 +593,7 @@ class AzureAIAgentClient(BaseChatClient):
"submit_tool_outputs",
"submit_tool_approval",
]:
function_call_contents = self._create_function_call_contents(
function_call_contents = self._parse_function_calls_from_azure_ai(
event_data, response_id
)
if function_call_contents:
@@ -753,8 +735,8 @@ class AzureAIAgentClient(BaseChatClient):
except Exception as ex:
logger.debug(f"Failed to capture Azure AI Search tool call: {ex}")
def _create_function_call_contents(self, event_data: ThreadRun, response_id: str | None) -> list[Contents]:
"""Create function call contents from a tool action event."""
def _parse_function_calls_from_azure_ai(self, event_data: ThreadRun, response_id: str | None) -> list[Contents]:
"""Parse function call contents from an Azure AI tool action event."""
if isinstance(event_data, ThreadRun) and event_data.required_action is not None:
if isinstance(event_data.required_action, SubmitToolOutputsAction):
return [
@@ -815,117 +797,197 @@ class AzureAIAgentClient(BaseChatClient):
chat_options.tool_choice = chat_tool_mode
async def _create_run_options(
async def _prepare_options(
self,
messages: MutableSequence[ChatMessage],
chat_options: ChatOptions | None,
chat_options: ChatOptions,
**kwargs: Any,
) -> tuple[dict[str, Any], list[FunctionResultContent | FunctionApprovalResponseContent] | None]:
run_options: dict[str, Any] = {**kwargs}
agent_definition = await self._load_agent_definition_if_needed()
if chat_options is not None:
run_options["max_completion_tokens"] = chat_options.max_tokens
if chat_options.model_id is not None:
run_options["model"] = chat_options.model_id
else:
run_options["model"] = self.model_id
run_options["top_p"] = chat_options.top_p
run_options["temperature"] = chat_options.temperature
run_options["parallel_tool_calls"] = chat_options.allow_multiple_tool_calls
# Use to_dict with exclusions for properties handled separately
run_options: dict[str, Any] = chat_options.to_dict(
exclude={
"type",
"instructions", # handled via messages
"tools", # handled separately
"tool_choice", # handled separately
"response_format", # handled separately
"additional_properties", # handled separately
"frequency_penalty", # not supported
"presence_penalty", # not supported
"user", # not supported
"stop", # not supported
"logit_bias", # not supported
"seed", # not supported
"store", # not supported
}
)
tool_definitions: list[ToolDefinition | dict[str, Any]] = []
# Translation between ChatOptions and Azure AI Agents API
translations = {
"model_id": "model",
"allow_multiple_tool_calls": "parallel_tool_calls",
"max_tokens": "max_completion_tokens",
}
for old_key, new_key in translations.items():
if old_key in run_options and old_key != new_key:
run_options[new_key] = run_options.pop(old_key)
# Add tools from existing agent
if agent_definition is not None:
# Don't include function tools, since they will be passed through chat_options.tools
agent_tools = [tool for tool in agent_definition.tools if not isinstance(tool, FunctionToolDefinition)]
if agent_tools:
tool_definitions.extend(agent_tools)
if agent_definition.tool_resources:
run_options["tool_resources"] = agent_definition.tool_resources
# model id fallback
if not run_options.get("model"):
run_options["model"] = self.model_id
if chat_options.tool_choice is not None:
if chat_options.tool_choice != "none" and chat_options.tools:
# Add run tools
tool_definitions.extend(await self._prep_tools(chat_options.tools, run_options))
# tools and tool_choice
if tool_definitions := await self._prepare_tool_definitions_and_resources(
chat_options, agent_definition, run_options
):
run_options["tools"] = tool_definitions
# Handle MCP tool resources for approval mode
mcp_tools = [tool for tool in chat_options.tools if isinstance(tool, HostedMCPTool)]
if mcp_tools:
mcp_resources = []
for mcp_tool in mcp_tools:
server_label = mcp_tool.name.replace(" ", "_")
mcp_resource: dict[str, Any] = {"server_label": server_label}
if tool_choice := self._prepare_tool_choice_mode(chat_options):
run_options["tool_choice"] = tool_choice
# Add headers if they exist
if mcp_tool.headers:
mcp_resource["headers"] = mcp_tool.headers
if mcp_tool.approval_mode is not None:
match mcp_tool.approval_mode:
case str():
# Map agent framework approval modes to Azure AI approval modes
approval_mode = (
"always" if mcp_tool.approval_mode == "always_require" else "never"
)
mcp_resource["require_approval"] = approval_mode
case _:
if "always_require_approval" in mcp_tool.approval_mode:
mcp_resource["require_approval"] = {
"always": mcp_tool.approval_mode["always_require_approval"]
}
elif "never_require_approval" in mcp_tool.approval_mode:
mcp_resource["require_approval"] = {
"never": mcp_tool.approval_mode["never_require_approval"]
}
mcp_resources.append(mcp_resource)
# Add MCP resources to tool_resources
if "tool_resources" not in run_options:
run_options["tool_resources"] = {}
run_options["tool_resources"]["mcp"] = mcp_resources
if chat_options.tool_choice == "none":
run_options["tool_choice"] = AgentsToolChoiceOptionMode.NONE
elif chat_options.tool_choice == "auto":
run_options["tool_choice"] = AgentsToolChoiceOptionMode.AUTO
elif (
isinstance(chat_options.tool_choice, ToolMode)
and chat_options.tool_choice == "required"
and chat_options.tool_choice.required_function_name is not None
):
run_options["tool_choice"] = AgentsNamedToolChoice(
type=AgentsNamedToolChoiceType.FUNCTION,
function=FunctionName(name=chat_options.tool_choice.required_function_name),
)
if tool_definitions:
run_options["tools"] = tool_definitions
if chat_options.response_format is not None:
run_options["response_format"] = ResponseFormatJsonSchemaType(
json_schema=ResponseFormatJsonSchema(
name=chat_options.response_format.__name__,
schema=chat_options.response_format.model_json_schema(),
)
# response format
if chat_options.response_format is not None:
run_options["response_format"] = ResponseFormatJsonSchemaType(
json_schema=ResponseFormatJsonSchema(
name=chat_options.response_format.__name__,
schema=chat_options.response_format.model_json_schema(),
)
)
# messages
additional_messages, instructions, required_action_results = self._prepare_messages(messages)
if additional_messages:
run_options["additional_messages"] = additional_messages
# Add instruction from existing agent at the beginning
if (
agent_definition is not None
and agent_definition.instructions
and agent_definition.instructions not in instructions
):
instructions.insert(0, agent_definition.instructions)
if instructions:
run_options["instructions"] = "\n".join(instructions)
# thread_id resolution (conversation_id takes precedence, then kwargs, then instance default)
run_options["thread_id"] = chat_options.conversation_id or kwargs.get("conversation_id") or self.thread_id
return run_options, required_action_results
def _prepare_tool_choice_mode(
self, chat_options: ChatOptions
) -> AgentsToolChoiceOptionMode | AgentsNamedToolChoice | None:
"""Prepare the tool choice mode for Azure AI Agents API."""
if chat_options.tool_choice is None:
return None
if chat_options.tool_choice == "none":
return AgentsToolChoiceOptionMode.NONE
if chat_options.tool_choice == "auto":
return AgentsToolChoiceOptionMode.AUTO
if (
isinstance(chat_options.tool_choice, ToolMode)
and chat_options.tool_choice == "required"
and chat_options.tool_choice.required_function_name is not None
):
return AgentsNamedToolChoice(
type=AgentsNamedToolChoiceType.FUNCTION,
function=FunctionName(name=chat_options.tool_choice.required_function_name),
)
return None
async def _prepare_tool_definitions_and_resources(
self,
chat_options: ChatOptions,
agent_definition: Agent | None,
run_options: dict[str, Any],
) -> list[ToolDefinition | dict[str, Any]]:
"""Prepare tool definitions and resources for the run options."""
tool_definitions: list[ToolDefinition | dict[str, Any]] = []
# Add tools from existing agent (exclude function tools - passed via chat_options.tools)
if agent_definition is not None:
agent_tools = [tool for tool in agent_definition.tools if not isinstance(tool, FunctionToolDefinition)]
if agent_tools:
tool_definitions.extend(agent_tools)
if agent_definition.tool_resources:
run_options["tool_resources"] = agent_definition.tool_resources
# Add run tools if tool_choice allows
if chat_options.tool_choice is not None and chat_options.tool_choice != "none" and chat_options.tools:
tool_definitions.extend(await self._prepare_tools_for_azure_ai(chat_options.tools, run_options))
# Handle MCP tool resources
mcp_resources = self._prepare_mcp_resources(chat_options.tools)
if mcp_resources:
if "tool_resources" not in run_options:
run_options["tool_resources"] = {}
run_options["tool_resources"]["mcp"] = mcp_resources
return tool_definitions
def _prepare_mcp_resources(
self, tools: Sequence["ToolProtocol | MutableMapping[str, Any]"]
) -> list[dict[str, Any]]:
"""Prepare MCP tool resources for approval mode configuration."""
mcp_tools = [tool for tool in tools if isinstance(tool, HostedMCPTool)]
if not mcp_tools:
return []
mcp_resources: list[dict[str, Any]] = []
for mcp_tool in mcp_tools:
server_label = mcp_tool.name.replace(" ", "_")
mcp_resource: dict[str, Any] = {"server_label": server_label}
if mcp_tool.headers:
mcp_resource["headers"] = mcp_tool.headers
if mcp_tool.approval_mode is not None:
match mcp_tool.approval_mode:
case str():
# Map agent framework approval modes to Azure AI approval modes
approval_mode = "always" if mcp_tool.approval_mode == "always_require" else "never"
mcp_resource["require_approval"] = approval_mode
case _:
if "always_require_approval" in mcp_tool.approval_mode:
mcp_resource["require_approval"] = {
"always": mcp_tool.approval_mode["always_require_approval"]
}
elif "never_require_approval" in mcp_tool.approval_mode:
mcp_resource["require_approval"] = {
"never": mcp_tool.approval_mode["never_require_approval"]
}
mcp_resources.append(mcp_resource)
return mcp_resources
def _prepare_messages(
self, messages: MutableSequence[ChatMessage]
) -> tuple[
list[ThreadMessageOptions] | None,
list[str],
list[FunctionResultContent | FunctionApprovalResponseContent] | None,
]:
"""Prepare messages for Azure AI Agents API.
System/developer messages are turned into instructions, since there is no such message roles in Azure AI.
All other messages are added 1:1, treating assistant messages as agent messages
and everything else as user messages.
Returns:
Tuple of (additional_messages, instructions, required_action_results)
"""
instructions: list[str] = []
required_action_results: list[FunctionResultContent | FunctionApprovalResponseContent] | None = None
additional_messages: list[ThreadMessageOptions] | None = None
# System/developer messages are turned into instructions, since there is no such message roles in Azure AI.
# All other messages are added 1:1, treating assistant messages as agent messages
# and everything else as user messages.
for chat_message in messages:
if chat_message.role.value in ["system", "developer"]:
for text_content in [content for content in chat_message.contents if isinstance(content, TextContent)]:
instructions.append(text_content.text)
continue
message_contents: list[MessageInputContentBlock] = []
@@ -942,7 +1004,7 @@ class AzureAIAgentClient(BaseChatClient):
elif isinstance(content.raw_representation, MessageInputContentBlock):
message_contents.append(content.raw_representation)
if len(message_contents) > 0:
if message_contents:
if additional_messages is None:
additional_messages = []
additional_messages.append(
@@ -952,26 +1014,12 @@ class AzureAIAgentClient(BaseChatClient):
)
)
if additional_messages is not None:
run_options["additional_messages"] = additional_messages
return additional_messages, instructions, required_action_results
# Add instruction from existing agent at the beginning
if (
agent_definition is not None
and agent_definition.instructions
and agent_definition.instructions not in instructions
):
instructions.insert(0, agent_definition.instructions)
if len(instructions) > 0:
run_options["instructions"] = "".join(instructions)
return run_options, required_action_results
async def _prep_tools(
async def _prepare_tools_for_azure_ai(
self, tools: Sequence["ToolProtocol | MutableMapping[str, Any]"], run_options: dict[str, Any] | None = None
) -> list[ToolDefinition | dict[str, Any]]:
"""Prepare tool definitions for the run options."""
"""Prepare tool definitions for the Azure AI Agents API."""
tool_definitions: list[ToolDefinition | dict[str, Any]] = []
for tool in tools:
match tool:
@@ -1044,10 +1092,11 @@ class AzureAIAgentClient(BaseChatClient):
raise ServiceInitializationError(f"Unsupported tool type: {type(tool)}")
return tool_definitions
def _convert_required_action_to_tool_output(
def _prepare_tool_outputs_for_azure_ai(
self,
required_action_results: list[FunctionResultContent | FunctionApprovalResponseContent] | None,
) -> tuple[str | None, list[ToolOutput] | None, list[ToolApproval] | None]:
"""Prepare function results and approvals for submission to the Azure AI API."""
run_id: str | None = None
tool_outputs: list[ToolOutput] | None = None
tool_approvals: list[ToolApproval] | None = None
python/packages/azure-ai/agent_framework_azure_ai/_client.py
+40 -58
View File
@@ -28,10 +28,6 @@ from azure.ai.projects.models import (
)
from azure.core.credentials_async import AsyncTokenCredential
from azure.core.exceptions import ResourceNotFoundError
from openai.types.responses.parsed_response import (
ParsedResponse,
)
from openai.types.responses.response import Response as OpenAIResponse
from pydantic import BaseModel, ValidationError
from ._shared import AzureAISettings
@@ -41,6 +37,11 @@ if sys.version_info >= (3, 11):
else:
from typing_extensions import Self # pragma: no cover
if sys.version_info >= (3, 12):
from typing import override # type: ignore # pragma: no cover
else:
from typing_extensions import override # type: ignore[import] # pragma: no cover
logger = get_logger("agent_framework.azure")
@@ -368,7 +369,38 @@ class AzureAIClient(OpenAIBaseResponsesClient):
if self._should_close_client:
await self.project_client.close()
def _prepare_input(self, messages: MutableSequence[ChatMessage]) -> tuple[list[ChatMessage], str | None]:
@override
async def _prepare_options(
self,
messages: MutableSequence[ChatMessage],
chat_options: ChatOptions,
**kwargs: Any,
) -> dict[str, Any]:
"""Take ChatOptions and create the specific options for Azure AI."""
prepared_messages, instructions = self._prepare_messages_for_azure_ai(messages)
run_options = await super()._prepare_options(prepared_messages, chat_options, **kwargs)
if not self._is_application_endpoint:
# Application-scoped response APIs do not support "agent" property.
agent_reference = await self._get_agent_reference_or_create(run_options, instructions)
run_options["extra_body"] = {"agent": agent_reference}
# Remove properties that are not supported on request level
# but were configured on agent level
exclude = ["model", "tools", "response_format", "temperature", "top_p"]
for property in exclude:
run_options.pop(property, None)
return run_options
@override
def _get_current_conversation_id(self, chat_options: ChatOptions, **kwargs: Any) -> str | None:
"""Get the current conversation ID from chat options or kwargs."""
return chat_options.conversation_id or kwargs.get("conversation_id") or self.conversation_id
def _prepare_messages_for_azure_ai(
self, messages: MutableSequence[ChatMessage]
) -> tuple[list[ChatMessage], str | None]:
"""Prepare input from messages and convert system/developer messages to instructions."""
result: list[ChatMessage] = []
instructions_list: list[str] = []
@@ -387,44 +419,7 @@ class AzureAIClient(OpenAIBaseResponsesClient):
return result, instructions
async def prepare_options(
self,
messages: MutableSequence[ChatMessage],
chat_options: ChatOptions,
**kwargs: Any,
) -> dict[str, Any]:
"""Take ChatOptions and create the specific options for Azure AI."""
prepared_messages, instructions = self._prepare_input(messages)
run_options = await super().prepare_options(prepared_messages, chat_options, **kwargs)
if not self._is_application_endpoint:
# Application-scoped response APIs do not support "agent" property.
agent_reference = await self._get_agent_reference_or_create(run_options, instructions)
run_options["extra_body"] = {"agent": agent_reference}
conversation_id = chat_options.conversation_id or self.conversation_id
# Handle different conversation ID formats
if conversation_id:
if conversation_id.startswith("resp_"):
# For response IDs, set previous_response_id and remove conversation property
run_options.pop("conversation", None)
run_options["previous_response_id"] = conversation_id
elif conversation_id.startswith("conv_"):
# For conversation IDs, set conversation and remove previous_response_id property
run_options.pop("previous_response_id", None)
run_options["conversation"] = conversation_id
# Remove properties that are not supported on request level
# but were configured on agent level
exclude = ["model", "tools", "response_format", "temperature", "top_p"]
for property in exclude:
run_options.pop(property, None)
return run_options
async def initialize_client(self) -> None:
async def _initialize_client(self) -> None:
"""Initialize OpenAI client."""
self.client = self.project_client.get_openai_client() # type: ignore
@@ -442,7 +437,8 @@ class AzureAIClient(OpenAIBaseResponsesClient):
if description and not self.agent_description:
self.agent_description = description
def get_mcp_tool(self, tool: HostedMCPTool) -> Any:
@staticmethod
def _prepare_mcp_tool(tool: HostedMCPTool) -> MCPTool: # type: ignore[override]
"""Get MCP tool from HostedMCPTool."""
mcp = MCPTool(server_label=tool.name.replace(" ", "_"), server_url=str(tool.url))
@@ -460,17 +456,3 @@ class AzureAIClient(OpenAIBaseResponsesClient):
mcp["require_approval"] = {"never": {"tool_names": list(never_require_approvals)}}
return mcp
def get_conversation_id(
self, response: OpenAIResponse | ParsedResponse[BaseModel], store: bool | None
) -> str | None:
"""Get the conversation ID from the response if store is True."""
if store is False:
return None
# If conversation ID exists, it means that we operate with conversation
# so we use conversation ID as input and output.
if response.conversation and response.conversation.id:
return response.conversation.id
# If conversation ID doesn't exist, we operate with responses
# so we use response ID as input and output.
return response.id
python/packages/azure-ai/pyproject.toml
+8 -1
View File
@@ -4,7 +4,7 @@ description = "Azure AI Foundry integration for Microsoft Agent Framework."
authors = [{ name = "Microsoft", email = "af-support@microsoft.com"}]
readme = "README.md"
requires-python = ">=3.10"
version = "1.0.0b251216"
version = "1.0.0b251223"
license-files = ["LICENSE"]
urls.homepage = "https://aka.ms/agent-framework"
urls.source = "https://github.com/microsoft/agent-framework/tree/main/python"
@@ -83,6 +83,13 @@ include = "../../shared_tasks.toml"
mypy = "mypy --config-file $POE_ROOT/pyproject.toml agent_framework_azure_ai"
test = "pytest --cov=agent_framework_azure_ai --cov-report=term-missing:skip-covered tests"
[tool.poe.tasks.integration-tests]
cmd = """
pytest --import-mode=importlib
-n logical --dist loadfile --dist worksteal
tests
"""
[build-system]
requires = ["flit-core >= 3.11,<4.0"]
build-backend = "flit_core.buildapi"
python/packages/azure-ai/tests/test_azure_ai_agent_client.py
+95 -89
View File
@@ -367,33 +367,33 @@ async def test_azure_ai_chat_client_get_agent_id_or_create_missing_model(
await chat_client._get_agent_id_or_create() # type: ignore
async def test_azure_ai_chat_client_create_run_options_basic(mock_agents_client: MagicMock) -> None:
"""Test _create_run_options with basic ChatOptions."""
async def test_azure_ai_chat_client_prepare_options_basic(mock_agents_client: MagicMock) -> None:
"""Test _prepare_options with basic ChatOptions."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
messages = [ChatMessage(role=Role.USER, text="Hello")]
chat_options = ChatOptions(max_tokens=100, temperature=0.7)
run_options, tool_results = await chat_client._create_run_options(messages, chat_options) # type: ignore
run_options, tool_results = await chat_client._prepare_options(messages, chat_options) # type: ignore
assert run_options is not None
assert tool_results is None
async def test_azure_ai_chat_client_create_run_options_no_chat_options(mock_agents_client: MagicMock) -> None:
"""Test _create_run_options with no ChatOptions."""
async def test_azure_ai_chat_client_prepare_options_no_chat_options(mock_agents_client: MagicMock) -> None:
"""Test _prepare_options with default ChatOptions."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
messages = [ChatMessage(role=Role.USER, text="Hello")]
run_options, tool_results = await chat_client._create_run_options(messages, None) # type: ignore
run_options, tool_results = await chat_client._prepare_options(messages, ChatOptions()) # type: ignore
assert run_options is not None
assert tool_results is None
async def test_azure_ai_chat_client_create_run_options_with_image_content(mock_agents_client: MagicMock) -> None:
"""Test _create_run_options with image content."""
async def test_azure_ai_chat_client_prepare_options_with_image_content(mock_agents_client: MagicMock) -> None:
"""Test _prepare_options with image content."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
@@ -403,7 +403,7 @@ async def test_azure_ai_chat_client_create_run_options_with_image_content(mock_a
image_content = UriContent(uri="https://example.com/image.jpg", media_type="image/jpeg")
messages = [ChatMessage(role=Role.USER, contents=[image_content])]
run_options, _ = await chat_client._create_run_options(messages, None) # type: ignore
run_options, _ = await chat_client._prepare_options(messages, ChatOptions()) # type: ignore
assert "additional_messages" in run_options
assert len(run_options["additional_messages"]) == 1
@@ -412,11 +412,11 @@ async def test_azure_ai_chat_client_create_run_options_with_image_content(mock_a
assert len(message.content) == 1
def test_azure_ai_chat_client_convert_function_results_to_tool_output_none(mock_agents_client: MagicMock) -> None:
"""Test _convert_required_action_to_tool_output with None input."""
def test_azure_ai_chat_client_prepare_tool_outputs_for_azure_ai_none(mock_agents_client: MagicMock) -> None:
"""Test _prepare_tool_outputs_for_azure_ai with None input."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
run_id, tool_outputs, tool_approvals = chat_client._convert_required_action_to_tool_output(None) # type: ignore
run_id, tool_outputs, tool_approvals = chat_client._prepare_tool_outputs_for_azure_ai(None) # type: ignore
assert run_id is None
assert tool_outputs is None
@@ -484,8 +484,8 @@ def test_azure_ai_chat_client_update_agent_name_and_description_with_none_input(
assert chat_client.agent_description is None
async def test_azure_ai_chat_client_create_run_options_with_messages(mock_agents_client: MagicMock) -> None:
"""Test _create_run_options with different message types."""
async def test_azure_ai_chat_client_prepare_options_with_messages(mock_agents_client: MagicMock) -> None:
"""Test _prepare_options with different message types."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
# Test with system message (becomes instruction)
@@ -494,7 +494,7 @@ async def test_azure_ai_chat_client_create_run_options_with_messages(mock_agents
ChatMessage(role=Role.USER, text="Hello"),
]
run_options, _ = await chat_client._create_run_options(messages, None) # type: ignore
run_options, _ = await chat_client._prepare_options(messages, ChatOptions()) # type: ignore
assert "instructions" in run_options
assert "You are a helpful assistant" in run_options["instructions"]
@@ -565,8 +565,8 @@ async def test_azure_ai_chat_client_prepare_thread_cancels_active_run(mock_agent
mock_agents_client.runs.cancel.assert_called_once_with("test-thread", "run_123")
def test_azure_ai_chat_client_create_function_call_contents_basic(mock_agents_client: MagicMock) -> None:
"""Test _create_function_call_contents with basic function call."""
def test_azure_ai_chat_client_parse_function_calls_from_azure_ai_basic(mock_agents_client: MagicMock) -> None:
"""Test _parse_function_calls_from_azure_ai with basic function call."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
mock_tool_call = MagicMock(spec=RequiredFunctionToolCall)
@@ -580,7 +580,7 @@ def test_azure_ai_chat_client_create_function_call_contents_basic(mock_agents_cl
mock_event_data = MagicMock(spec=ThreadRun)
mock_event_data.required_action = mock_submit_action
result = chat_client._create_function_call_contents(mock_event_data, "response_123") # type: ignore
result = chat_client._parse_function_calls_from_azure_ai(mock_event_data, "response_123") # type: ignore
assert len(result) == 1
assert isinstance(result[0], FunctionCallContent)
@@ -588,22 +588,24 @@ def test_azure_ai_chat_client_create_function_call_contents_basic(mock_agents_cl
assert result[0].call_id == '["response_123", "call_123"]'
def test_azure_ai_chat_client_create_function_call_contents_no_submit_action(mock_agents_client: MagicMock) -> None:
"""Test _create_function_call_contents when required_action is not SubmitToolOutputsAction."""
def test_azure_ai_chat_client_parse_function_calls_from_azure_ai_no_submit_action(
mock_agents_client: MagicMock,
) -> None:
"""Test _parse_function_calls_from_azure_ai when required_action is not SubmitToolOutputsAction."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
mock_event_data = MagicMock(spec=ThreadRun)
mock_event_data.required_action = MagicMock()
result = chat_client._create_function_call_contents(mock_event_data, "response_123") # type: ignore
result = chat_client._parse_function_calls_from_azure_ai(mock_event_data, "response_123") # type: ignore
assert result == []
def test_azure_ai_chat_client_create_function_call_contents_non_function_tool_call(
def test_azure_ai_chat_client_parse_function_calls_from_azure_ai_non_function_tool_call(
mock_agents_client: MagicMock,
) -> None:
"""Test _create_function_call_contents with non-function tool call."""
"""Test _parse_function_calls_from_azure_ai with non-function tool call."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
mock_tool_call = MagicMock()
@@ -614,37 +616,37 @@ def test_azure_ai_chat_client_create_function_call_contents_non_function_tool_ca
mock_event_data = MagicMock(spec=ThreadRun)
mock_event_data.required_action = mock_submit_action
result = chat_client._create_function_call_contents(mock_event_data, "response_123") # type: ignore
result = chat_client._parse_function_calls_from_azure_ai(mock_event_data, "response_123") # type: ignore
assert result == []
async def test_azure_ai_chat_client_create_run_options_with_none_tool_choice(
async def test_azure_ai_chat_client_prepare_options_with_none_tool_choice(
mock_agents_client: MagicMock,
) -> None:
"""Test _create_run_options with tool_choice set to 'none'."""
"""Test _prepare_options with tool_choice set to 'none'."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
chat_options = ChatOptions()
chat_options.tool_choice = "none"
run_options, _ = await chat_client._create_run_options([], chat_options) # type: ignore
run_options, _ = await chat_client._prepare_options([], chat_options) # type: ignore
from azure.ai.agents.models import AgentsToolChoiceOptionMode
assert run_options["tool_choice"] == AgentsToolChoiceOptionMode.NONE
async def test_azure_ai_chat_client_create_run_options_with_auto_tool_choice(
async def test_azure_ai_chat_client_prepare_options_with_auto_tool_choice(
mock_agents_client: MagicMock,
) -> None:
"""Test _create_run_options with tool_choice set to 'auto'."""
"""Test _prepare_options with tool_choice set to 'auto'."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
chat_options = ChatOptions()
chat_options.tool_choice = "auto"
run_options, _ = await chat_client._create_run_options([], chat_options) # type: ignore
run_options, _ = await chat_client._prepare_options([], chat_options) # type: ignore
from azure.ai.agents.models import AgentsToolChoiceOptionMode
@@ -669,10 +671,10 @@ async def test_azure_ai_chat_client_prepare_tool_choice_none_string(
assert chat_options.tool_choice == ToolMode.NONE.mode
async def test_azure_ai_chat_client_create_run_options_tool_choice_required_specific_function(
async def test_azure_ai_chat_client_prepare_options_tool_choice_required_specific_function(
mock_agents_client: MagicMock,
) -> None:
"""Test _create_run_options with ToolMode.REQUIRED specifying a specific function name."""
"""Test _prepare_options with ToolMode.REQUIRED specifying a specific function name."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
required_tool_mode = ToolMode.REQUIRED("specific_function_name")
@@ -682,7 +684,7 @@ async def test_azure_ai_chat_client_create_run_options_tool_choice_required_spec
chat_options = ChatOptions(tools=[dict_tool], tool_choice=required_tool_mode)
messages = [ChatMessage(role=Role.USER, text="Hello")]
run_options, _ = await chat_client._create_run_options(messages, chat_options) # type: ignore
run_options, _ = await chat_client._prepare_options(messages, chat_options) # type: ignore
# Verify tool_choice is set to the specific named function
assert "tool_choice" in run_options
@@ -692,10 +694,10 @@ async def test_azure_ai_chat_client_create_run_options_tool_choice_required_spec
assert tool_choice.function.name == "specific_function_name" # type: ignore
async def test_azure_ai_chat_client_create_run_options_with_response_format(
async def test_azure_ai_chat_client_prepare_options_with_response_format(
mock_agents_client: MagicMock,
) -> None:
"""Test _create_run_options with response_format configured."""
"""Test _prepare_options with response_format configured."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
class TestResponseModel(BaseModel):
@@ -704,7 +706,7 @@ async def test_azure_ai_chat_client_create_run_options_with_response_format(
chat_options = ChatOptions()
chat_options.response_format = TestResponseModel
run_options, _ = await chat_client._create_run_options([], chat_options) # type: ignore
run_options, _ = await chat_client._prepare_options([], chat_options) # type: ignore
assert "response_format" in run_options
response_format = run_options["response_format"]
@@ -720,8 +722,8 @@ def test_azure_ai_chat_client_service_url_method(mock_agents_client: MagicMock)
assert url == "https://test-endpoint.com/"
async def test_azure_ai_chat_client_prep_tools_ai_function(mock_agents_client: MagicMock) -> None:
"""Test _prep_tools with AIFunction tool."""
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_ai_function(mock_agents_client: MagicMock) -> None:
"""Test _prepare_tools_for_azure_ai with AIFunction tool."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
@@ -729,28 +731,28 @@ async def test_azure_ai_chat_client_prep_tools_ai_function(mock_agents_client: M
mock_ai_function = MagicMock(spec=AIFunction)
mock_ai_function.to_json_schema_spec.return_value = {"type": "function", "function": {"name": "test_function"}}
result = await chat_client._prep_tools([mock_ai_function]) # type: ignore
result = await chat_client._prepare_tools_for_azure_ai([mock_ai_function]) # type: ignore
assert len(result) == 1
assert result[0] == {"type": "function", "function": {"name": "test_function"}}
mock_ai_function.to_json_schema_spec.assert_called_once()
async def test_azure_ai_chat_client_prep_tools_code_interpreter(mock_agents_client: MagicMock) -> None:
"""Test _prep_tools with HostedCodeInterpreterTool."""
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_code_interpreter(mock_agents_client: MagicMock) -> None:
"""Test _prepare_tools_for_azure_ai with HostedCodeInterpreterTool."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
code_interpreter_tool = HostedCodeInterpreterTool()
result = await chat_client._prep_tools([code_interpreter_tool]) # type: ignore
result = await chat_client._prepare_tools_for_azure_ai([code_interpreter_tool]) # type: ignore
assert len(result) == 1
assert isinstance(result[0], CodeInterpreterToolDefinition)
async def test_azure_ai_chat_client_prep_tools_mcp_tool(mock_agents_client: MagicMock) -> None:
"""Test _prep_tools with HostedMCPTool."""
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_mcp_tool(mock_agents_client: MagicMock) -> None:
"""Test _prepare_tools_for_azure_ai with HostedMCPTool."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
@@ -762,7 +764,7 @@ async def test_azure_ai_chat_client_prep_tools_mcp_tool(mock_agents_client: Magi
mock_mcp_tool.definitions = [{"type": "mcp", "name": "test_mcp"}]
mock_mcp_tool_class.return_value = mock_mcp_tool
result = await chat_client._prep_tools([mcp_tool]) # type: ignore
result = await chat_client._prepare_tools_for_azure_ai([mcp_tool]) # type: ignore
assert len(result) == 1
assert result[0] == {"type": "mcp", "name": "test_mcp"}
@@ -774,8 +776,8 @@ async def test_azure_ai_chat_client_prep_tools_mcp_tool(mock_agents_client: Magi
assert set(call_args["allowed_tools"]) == {"tool1", "tool2"}
async def test_azure_ai_chat_client_create_run_options_mcp_never_require(mock_agents_client: MagicMock) -> None:
"""Test _create_run_options with HostedMCPTool having never_require approval mode."""
async def test_azure_ai_chat_client_prepare_options_mcp_never_require(mock_agents_client: MagicMock) -> None:
"""Test _prepare_options with HostedMCPTool having never_require approval mode."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
mcp_tool = HostedMCPTool(name="Test MCP Tool", url="https://example.com/mcp", approval_mode="never_require")
@@ -784,12 +786,12 @@ async def test_azure_ai_chat_client_create_run_options_mcp_never_require(mock_ag
chat_options = ChatOptions(tools=[mcp_tool], tool_choice="auto")
with patch("agent_framework_azure_ai._chat_client.McpTool") as mock_mcp_tool_class:
# Mock _prep_tools to avoid actual tool preparation
# Mock _prepare_tools_for_azure_ai to avoid actual tool preparation
mock_mcp_tool_instance = MagicMock()
mock_mcp_tool_instance.definitions = [{"type": "mcp", "name": "test_mcp"}]
mock_mcp_tool_class.return_value = mock_mcp_tool_instance
run_options, _ = await chat_client._create_run_options(messages, chat_options) # type: ignore
run_options, _ = await chat_client._prepare_options(messages, chat_options) # type: ignore
# Verify tool_resources is created with correct MCP approval structure
assert "tool_resources" in run_options, (
@@ -803,8 +805,8 @@ async def test_azure_ai_chat_client_create_run_options_mcp_never_require(mock_ag
assert mcp_resource["require_approval"] == "never"
async def test_azure_ai_chat_client_create_run_options_mcp_with_headers(mock_agents_client: MagicMock) -> None:
"""Test _create_run_options with HostedMCPTool having headers."""
async def test_azure_ai_chat_client_prepare_options_mcp_with_headers(mock_agents_client: MagicMock) -> None:
"""Test _prepare_options with HostedMCPTool having headers."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client)
# Test with headers
@@ -817,12 +819,12 @@ async def test_azure_ai_chat_client_create_run_options_mcp_with_headers(mock_age
chat_options = ChatOptions(tools=[mcp_tool], tool_choice="auto")
with patch("agent_framework_azure_ai._chat_client.McpTool") as mock_mcp_tool_class:
# Mock _prep_tools to avoid actual tool preparation
# Mock _prepare_tools_for_azure_ai to avoid actual tool preparation
mock_mcp_tool_instance = MagicMock()
mock_mcp_tool_instance.definitions = [{"type": "mcp", "name": "test_mcp"}]
mock_mcp_tool_class.return_value = mock_mcp_tool_instance
run_options, _ = await chat_client._create_run_options(messages, chat_options) # type: ignore
run_options, _ = await chat_client._prepare_options(messages, chat_options) # type: ignore
# Verify tool_resources is created with headers
assert "tool_resources" in run_options
@@ -835,8 +837,10 @@ async def test_azure_ai_chat_client_create_run_options_mcp_with_headers(mock_age
assert mcp_resource["headers"] == headers
async def test_azure_ai_chat_client_prep_tools_web_search_bing_grounding(mock_agents_client: MagicMock) -> None:
"""Test _prep_tools with HostedWebSearchTool using Bing Grounding."""
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_web_search_bing_grounding(
mock_agents_client: MagicMock,
) -> None:
"""Test _prepare_tools_for_azure_ai with HostedWebSearchTool using Bing Grounding."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
@@ -856,7 +860,7 @@ async def test_azure_ai_chat_client_prep_tools_web_search_bing_grounding(mock_ag
mock_bing_tool.definitions = [{"type": "bing_grounding"}]
mock_bing_grounding.return_value = mock_bing_tool
result = await chat_client._prep_tools([web_search_tool]) # type: ignore
result = await chat_client._prepare_tools_for_azure_ai([web_search_tool]) # type: ignore
assert len(result) == 1
assert result[0] == {"type": "bing_grounding"}
@@ -868,10 +872,10 @@ async def test_azure_ai_chat_client_prep_tools_web_search_bing_grounding(mock_ag
assert "connection_id" in call_args
async def test_azure_ai_chat_client_prep_tools_web_search_bing_grounding_with_connection_id(
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_web_search_bing_grounding_with_connection_id(
mock_agents_client: MagicMock,
) -> None:
"""Test _prep_tools with HostedWebSearchTool using Bing Grounding with connection_id (no HTTP call)."""
"""Test _prepare_tools_... with HostedWebSearchTool using Bing Grounding with connection_id (no HTTP call)."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
@@ -888,15 +892,17 @@ async def test_azure_ai_chat_client_prep_tools_web_search_bing_grounding_with_co
mock_bing_tool.definitions = [{"type": "bing_grounding"}]
mock_bing_grounding.return_value = mock_bing_tool
result = await chat_client._prep_tools([web_search_tool]) # type: ignore
result = await chat_client._prepare_tools_for_azure_ai([web_search_tool]) # type: ignore
assert len(result) == 1
assert result[0] == {"type": "bing_grounding"}
mock_bing_grounding.assert_called_once_with(connection_id="direct-connection-id", count=3)
async def test_azure_ai_chat_client_prep_tools_web_search_custom_bing(mock_agents_client: MagicMock) -> None:
"""Test _prep_tools with HostedWebSearchTool using Custom Bing Search."""
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_web_search_custom_bing(
mock_agents_client: MagicMock,
) -> None:
"""Test _prepare_tools_for_azure_ai with HostedWebSearchTool using Custom Bing Search."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
@@ -914,16 +920,16 @@ async def test_azure_ai_chat_client_prep_tools_web_search_custom_bing(mock_agent
mock_custom_tool.definitions = [{"type": "bing_custom_search"}]
mock_custom_bing.return_value = mock_custom_tool
result = await chat_client._prep_tools([web_search_tool]) # type: ignore
result = await chat_client._prepare_tools_for_azure_ai([web_search_tool]) # type: ignore
assert len(result) == 1
assert result[0] == {"type": "bing_custom_search"}
async def test_azure_ai_chat_client_prep_tools_file_search_with_vector_stores(
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_file_search_with_vector_stores(
mock_agents_client: MagicMock,
) -> None:
"""Test _prep_tools with HostedFileSearchTool using vector stores."""
"""Test _prepare_tools_for_azure_ai with HostedFileSearchTool using vector stores."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
@@ -938,7 +944,7 @@ async def test_azure_ai_chat_client_prep_tools_file_search_with_vector_stores(
mock_file_search.return_value = mock_file_tool
run_options = {}
result = await chat_client._prep_tools([file_search_tool], run_options) # type: ignore
result = await chat_client._prepare_tools_for_azure_ai([file_search_tool], run_options) # type: ignore
assert len(result) == 1
assert result[0] == {"type": "file_search"}
@@ -973,7 +979,7 @@ async def test_azure_ai_chat_client_create_agent_stream_submit_tool_approvals(
with patch("azure.ai.agents.models.AsyncAgentEventHandler", return_value=mock_handler):
stream, final_thread_id = await chat_client._create_agent_stream( # type: ignore
"test-thread", "test-agent", {}, [approval_response]
"test-agent", {"thread_id": "test-thread"}, [approval_response]
)
# Verify the approvals path was taken
@@ -987,26 +993,26 @@ async def test_azure_ai_chat_client_create_agent_stream_submit_tool_approvals(
assert call_args["tool_approvals"][0].approve is True
async def test_azure_ai_chat_client_prep_tools_dict_tool(mock_agents_client: MagicMock) -> None:
"""Test _prep_tools with dictionary tool definition."""
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_dict_tool(mock_agents_client: MagicMock) -> None:
"""Test _prepare_tools_for_azure_ai with dictionary tool definition."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
dict_tool = {"type": "custom_tool", "config": {"param": "value"}}
result = await chat_client._prep_tools([dict_tool]) # type: ignore
result = await chat_client._prepare_tools_for_azure_ai([dict_tool]) # type: ignore
assert len(result) == 1
assert result[0] == dict_tool
async def test_azure_ai_chat_client_prep_tools_unsupported_tool(mock_agents_client: MagicMock) -> None:
"""Test _prep_tools with unsupported tool type."""
async def test_azure_ai_chat_client_prepare_tools_for_azure_ai_unsupported_tool(mock_agents_client: MagicMock) -> None:
"""Test _prepare_tools_for_azure_ai with unsupported tool type."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
unsupported_tool = "not_a_tool"
with pytest.raises(ServiceInitializationError, match="Unsupported tool type: <class 'str'>"):
await chat_client._prep_tools([unsupported_tool]) # type: ignore
await chat_client._prepare_tools_for_azure_ai([unsupported_tool]) # type: ignore
async def test_azure_ai_chat_client_get_active_thread_run_with_active_run(mock_agents_client: MagicMock) -> None:
@@ -1072,16 +1078,16 @@ async def test_azure_ai_chat_client_service_url(mock_agents_client: MagicMock) -
assert result == "https://test-endpoint.com/"
async def test_azure_ai_chat_client_convert_required_action_to_tool_output_function_result(
async def test_azure_ai_chat_client_prepare_tool_outputs_for_azure_ai_function_result(
mock_agents_client: MagicMock,
) -> None:
"""Test _convert_required_action_to_tool_output with FunctionResultContent."""
"""Test _prepare_tool_outputs_for_azure_ai with FunctionResultContent."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
# Test with simple result
function_result = FunctionResultContent(call_id='["run_123", "call_456"]', result="Simple result")
run_id, tool_outputs, tool_approvals = chat_client._convert_required_action_to_tool_output([function_result]) # type: ignore
run_id, tool_outputs, tool_approvals = chat_client._prepare_tool_outputs_for_azure_ai([function_result]) # type: ignore
assert run_id == "run_123"
assert tool_approvals is None
@@ -1092,7 +1098,7 @@ async def test_azure_ai_chat_client_convert_required_action_to_tool_output_funct
async def test_azure_ai_chat_client_convert_required_action_invalid_call_id(mock_agents_client: MagicMock) -> None:
"""Test _convert_required_action_to_tool_output with invalid call_id format."""
"""Test _prepare_tool_outputs_for_azure_ai with invalid call_id format."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
@@ -1100,19 +1106,19 @@ async def test_azure_ai_chat_client_convert_required_action_invalid_call_id(mock
function_result = FunctionResultContent(call_id="invalid_json", result="result")
with pytest.raises(json.JSONDecodeError):
chat_client._convert_required_action_to_tool_output([function_result]) # type: ignore
chat_client._prepare_tool_outputs_for_azure_ai([function_result]) # type: ignore
async def test_azure_ai_chat_client_convert_required_action_invalid_structure(
mock_agents_client: MagicMock,
) -> None:
"""Test _convert_required_action_to_tool_output with invalid call_id structure."""
"""Test _prepare_tool_outputs_for_azure_ai with invalid call_id structure."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
# Valid JSON but invalid structure (missing second element)
function_result = FunctionResultContent(call_id='["run_123"]', result="result")
run_id, tool_outputs, tool_approvals = chat_client._convert_required_action_to_tool_output([function_result]) # type: ignore
run_id, tool_outputs, tool_approvals = chat_client._prepare_tool_outputs_for_azure_ai([function_result]) # type: ignore
# Should return None values when structure is invalid
assert run_id is None
@@ -1123,7 +1129,7 @@ async def test_azure_ai_chat_client_convert_required_action_invalid_structure(
async def test_azure_ai_chat_client_convert_required_action_serde_model_results(
mock_agents_client: MagicMock,
) -> None:
"""Test _convert_required_action_to_tool_output with BaseModel results."""
"""Test _prepare_tool_outputs_for_azure_ai with BaseModel results."""
class MockResult(SerializationMixin):
def __init__(self, name: str, value: int):
@@ -1136,7 +1142,7 @@ async def test_azure_ai_chat_client_convert_required_action_serde_model_results(
mock_result = MockResult(name="test", value=42)
function_result = FunctionResultContent(call_id='["run_123", "call_456"]', result=mock_result)
run_id, tool_outputs, tool_approvals = chat_client._convert_required_action_to_tool_output([function_result]) # type: ignore
run_id, tool_outputs, tool_approvals = chat_client._prepare_tool_outputs_for_azure_ai([function_result]) # type: ignore
assert run_id == "run_123"
assert tool_approvals is None
@@ -1151,7 +1157,7 @@ async def test_azure_ai_chat_client_convert_required_action_serde_model_results(
async def test_azure_ai_chat_client_convert_required_action_multiple_results(
mock_agents_client: MagicMock,
) -> None:
"""Test _convert_required_action_to_tool_output with multiple results."""
"""Test _prepare_tool_outputs_for_azure_ai with multiple results."""
class MockResult(SerializationMixin):
def __init__(self, data: str):
@@ -1164,7 +1170,7 @@ async def test_azure_ai_chat_client_convert_required_action_multiple_results(
results_list = [mock_basemodel, {"key": "value"}, "string_result"]
function_result = FunctionResultContent(call_id='["run_123", "call_456"]', result=results_list)
run_id, tool_outputs, tool_approvals = chat_client._convert_required_action_to_tool_output([function_result]) # type: ignore
run_id, tool_outputs, tool_approvals = chat_client._prepare_tool_outputs_for_azure_ai([function_result]) # type: ignore
assert run_id == "run_123"
assert tool_outputs is not None
@@ -1184,7 +1190,7 @@ async def test_azure_ai_chat_client_convert_required_action_multiple_results(
async def test_azure_ai_chat_client_convert_required_action_approval_response(
mock_agents_client: MagicMock,
) -> None:
"""Test _convert_required_action_to_tool_output with FunctionApprovalResponseContent."""
"""Test _prepare_tool_outputs_for_azure_ai with FunctionApprovalResponseContent."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
# Test with approval response - need to provide required fields
@@ -1194,7 +1200,7 @@ async def test_azure_ai_chat_client_convert_required_action_approval_response(
approved=True,
)
run_id, tool_outputs, tool_approvals = chat_client._convert_required_action_to_tool_output([approval_response]) # type: ignore
run_id, tool_outputs, tool_approvals = chat_client._prepare_tool_outputs_for_azure_ai([approval_response]) # type: ignore
assert run_id == "run_123"
assert tool_outputs is None
@@ -1204,10 +1210,10 @@ async def test_azure_ai_chat_client_convert_required_action_approval_response(
assert tool_approvals[0].approve is True
async def test_azure_ai_chat_client_create_function_call_contents_approval_request(
async def test_azure_ai_chat_client_parse_function_calls_from_azure_ai_approval_request(
mock_agents_client: MagicMock,
) -> None:
"""Test _create_function_call_contents with approval action."""
"""Test _parse_function_calls_from_azure_ai with approval action."""
chat_client = create_test_azure_ai_chat_client(mock_agents_client, agent_id="test-agent")
# Mock SubmitToolApprovalAction with RequiredMcpToolCall
@@ -1222,7 +1228,7 @@ async def test_azure_ai_chat_client_create_function_call_contents_approval_reque
mock_event_data = MagicMock(spec=ThreadRun)
mock_event_data.required_action = mock_approval_action
result = chat_client._create_function_call_contents(mock_event_data, "response_123") # type: ignore
result = chat_client._parse_function_calls_from_azure_ai(mock_event_data, "response_123") # type: ignore
assert len(result) == 1
assert isinstance(result[0], FunctionApprovalRequestContent)
@@ -1312,7 +1318,7 @@ async def test_azure_ai_chat_client_create_agent_stream_submit_tool_outputs(
with patch("azure.ai.agents.models.AsyncAgentEventHandler", return_value=mock_handler):
stream, final_thread_id = await chat_client._create_agent_stream( # type: ignore
thread_id="test-thread", agent_id="test-agent", run_options={}, required_action_results=[function_result]
agent_id="test-agent", run_options={"thread_id": "test-thread"}, required_action_results=[function_result]
)
# Should call submit_tool_outputs_stream since we have matching run ID
python/packages/azure-ai/tests/test_azure_ai_client.py
+28 -114
View File
@@ -249,10 +249,10 @@ async def test_azure_ai_client_get_agent_reference_missing_model(
await client._get_agent_reference_or_create({}, None) # type: ignore
async def test_azure_ai_client_prepare_input_with_system_messages(
async def test_azure_ai_client_prepare_messages_for_azure_ai_with_system_messages(
mock_project_client: MagicMock,
) -> None:
"""Test _prepare_input converts system/developer messages to instructions."""
"""Test _prepare_messages_for_azure_ai converts system/developer messages to instructions."""
client = create_test_azure_ai_client(mock_project_client)
messages = [
@@ -261,7 +261,7 @@ async def test_azure_ai_client_prepare_input_with_system_messages(
ChatMessage(role=Role.ASSISTANT, contents=[TextContent(text="System response")]),
]
result_messages, instructions = client._prepare_input(messages) # type: ignore
result_messages, instructions = client._prepare_messages_for_azure_ai(messages) # type: ignore
assert len(result_messages) == 2
assert result_messages[0].role == Role.USER
@@ -269,10 +269,10 @@ async def test_azure_ai_client_prepare_input_with_system_messages(
assert instructions == "You are a helpful assistant."
async def test_azure_ai_client_prepare_input_no_system_messages(
async def test_azure_ai_client_prepare_messages_for_azure_ai_no_system_messages(
mock_project_client: MagicMock,
) -> None:
"""Test _prepare_input with no system/developer messages."""
"""Test _prepare_messages_for_azure_ai with no system/developer messages."""
client = create_test_azure_ai_client(mock_project_client)
messages = [
@@ -280,7 +280,7 @@ async def test_azure_ai_client_prepare_input_no_system_messages(
ChatMessage(role=Role.ASSISTANT, contents=[TextContent(text="Hi there!")]),
]
result_messages, instructions = client._prepare_input(messages) # type: ignore
result_messages, instructions = client._prepare_messages_for_azure_ai(messages) # type: ignore
assert len(result_messages) == 2
assert instructions is None
@@ -294,14 +294,14 @@ async def test_azure_ai_client_prepare_options_basic(mock_project_client: MagicM
chat_options = ChatOptions()
with (
patch.object(client.__class__.__bases__[0], "prepare_options", return_value={"model": "test-model"}),
patch.object(client.__class__.__bases__[0], "_prepare_options", return_value={"model": "test-model"}),
patch.object(
client,
"_get_agent_reference_or_create",
return_value={"name": "test-agent", "version": "1.0", "type": "agent_reference"},
),
):
run_options = await client.prepare_options(messages, chat_options)
run_options = await client._prepare_options(messages, chat_options)
assert "extra_body" in run_options
assert run_options["extra_body"]["agent"]["name"] == "test-agent"
@@ -329,14 +329,14 @@ async def test_azure_ai_client_prepare_options_with_application_endpoint(
chat_options = ChatOptions()
with (
patch.object(client.__class__.__bases__[0], "prepare_options", return_value={"model": "test-model"}),
patch.object(client.__class__.__bases__[0], "_prepare_options", return_value={"model": "test-model"}),
patch.object(
client,
"_get_agent_reference_or_create",
return_value={"name": "test-agent", "version": "1", "type": "agent_reference"},
),
):
run_options = await client.prepare_options(messages, chat_options)
run_options = await client._prepare_options(messages, chat_options)
if expects_agent:
assert "extra_body" in run_options
@@ -369,14 +369,14 @@ async def test_azure_ai_client_prepare_options_with_application_project_client(
chat_options = ChatOptions()
with (
patch.object(client.__class__.__bases__[0], "prepare_options", return_value={"model": "test-model"}),
patch.object(client.__class__.__bases__[0], "_prepare_options", return_value={"model": "test-model"}),
patch.object(
client,
"_get_agent_reference_or_create",
return_value={"name": "test-agent", "version": "1", "type": "agent_reference"},
),
):
run_options = await client.prepare_options(messages, chat_options)
run_options = await client._prepare_options(messages, chat_options)
if expects_agent:
assert "extra_body" in run_options
@@ -386,13 +386,13 @@ async def test_azure_ai_client_prepare_options_with_application_project_client(
async def test_azure_ai_client_initialize_client(mock_project_client: MagicMock) -> None:
"""Test initialize_client method."""
"""Test _initialize_client method."""
client = create_test_azure_ai_client(mock_project_client)
mock_openai_client = MagicMock()
mock_project_client.get_openai_client = MagicMock(return_value=mock_openai_client)
await client.initialize_client()
await client._initialize_client()
assert client.client is mock_openai_client
mock_project_client.get_openai_client.assert_called_once()
@@ -727,7 +727,7 @@ async def test_azure_ai_client_prepare_options_excludes_response_format(
with (
patch.object(
client.__class__.__bases__[0],
"prepare_options",
"_prepare_options",
return_value={"model": "test-model", "response_format": ResponseFormatModel},
),
patch.object(
@@ -736,7 +736,7 @@ async def test_azure_ai_client_prepare_options_excludes_response_format(
return_value={"name": "test-agent", "version": "1.0", "type": "agent_reference"},
),
):
run_options = await client.prepare_options(messages, chat_options)
run_options = await client._prepare_options(messages, chat_options)
# response_format should be excluded from final run options
assert "response_format" not in run_options
@@ -745,94 +745,8 @@ async def test_azure_ai_client_prepare_options_excludes_response_format(
assert run_options["extra_body"]["agent"]["name"] == "test-agent"
async def test_azure_ai_client_prepare_options_with_resp_conversation_id(
mock_project_client: MagicMock,
) -> None:
"""Test prepare_options with conversation ID starting with 'resp_'."""
client = create_test_azure_ai_client(mock_project_client, agent_name="test-agent", agent_version="1.0")
messages = [ChatMessage(role=Role.USER, contents=[TextContent(text="Hello")])]
chat_options = ChatOptions(conversation_id="resp_12345")
with (
patch.object(
client.__class__.__bases__[0],
"prepare_options",
return_value={"model": "test-model", "previous_response_id": "old_value", "conversation": "old_conv"},
),
patch.object(
client,
"_get_agent_reference_or_create",
return_value={"name": "test-agent", "version": "1.0", "type": "agent_reference"},
),
):
run_options = await client.prepare_options(messages, chat_options)
# Should set previous_response_id and remove conversation property
assert run_options["previous_response_id"] == "resp_12345"
assert "conversation" not in run_options
async def test_azure_ai_client_prepare_options_with_conv_conversation_id(
mock_project_client: MagicMock,
) -> None:
"""Test prepare_options with conversation ID starting with 'conv_'."""
client = create_test_azure_ai_client(mock_project_client, agent_name="test-agent", agent_version="1.0")
messages = [ChatMessage(role=Role.USER, contents=[TextContent(text="Hello")])]
chat_options = ChatOptions(conversation_id="conv_67890")
with (
patch.object(
client.__class__.__bases__[0],
"prepare_options",
return_value={"model": "test-model", "previous_response_id": "old_value", "conversation": "old_conv"},
),
patch.object(
client,
"_get_agent_reference_or_create",
return_value={"name": "test-agent", "version": "1.0", "type": "agent_reference"},
),
):
run_options = await client.prepare_options(messages, chat_options)
# Should set conversation and remove previous_response_id property
assert run_options["conversation"] == "conv_67890"
assert "previous_response_id" not in run_options
async def test_azure_ai_client_prepare_options_with_client_conversation_id(
mock_project_client: MagicMock,
) -> None:
"""Test prepare_options using client's default conversation ID when chat options don't have one."""
client = create_test_azure_ai_client(
mock_project_client, agent_name="test-agent", agent_version="1.0", conversation_id="resp_client_default"
)
messages = [ChatMessage(role=Role.USER, contents=[TextContent(text="Hello")])]
chat_options = ChatOptions() # No conversation_id specified
with (
patch.object(
client.__class__.__bases__[0],
"prepare_options",
return_value={"model": "test-model", "previous_response_id": "old_value", "conversation": "old_conv"},
),
patch.object(
client,
"_get_agent_reference_or_create",
return_value={"name": "test-agent", "version": "1.0", "type": "agent_reference"},
),
):
run_options = await client.prepare_options(messages, chat_options)
# Should use client's default conversation_id and set previous_response_id
assert run_options["previous_response_id"] == "resp_client_default"
assert "conversation" not in run_options
def test_get_conversation_id_with_store_true_and_conversation_id() -> None:
"""Test get_conversation_id returns conversation ID when store is True and conversation exists."""
"""Test _get_conversation_id returns conversation ID when store is True and conversation exists."""
client = create_test_azure_ai_client(MagicMock())
# Mock OpenAI response with conversation
@@ -842,13 +756,13 @@ def test_get_conversation_id_with_store_true_and_conversation_id() -> None:
mock_conversation.id = "conv_67890"
mock_response.conversation = mock_conversation
result = client.get_conversation_id(mock_response, store=True)
result = client._get_conversation_id(mock_response, store=True)
assert result == "conv_67890"
def test_get_conversation_id_with_store_true_and_no_conversation() -> None:
"""Test get_conversation_id returns response ID when store is True and no conversation exists."""
"""Test _get_conversation_id returns response ID when store is True and no conversation exists."""
client = create_test_azure_ai_client(MagicMock())
# Mock OpenAI response without conversation
@@ -856,13 +770,13 @@ def test_get_conversation_id_with_store_true_and_no_conversation() -> None:
mock_response.id = "resp_12345"
mock_response.conversation = None
result = client.get_conversation_id(mock_response, store=True)
result = client._get_conversation_id(mock_response, store=True)
assert result == "resp_12345"
def test_get_conversation_id_with_store_true_and_empty_conversation_id() -> None:
"""Test get_conversation_id returns response ID when store is True and conversation ID is empty."""
"""Test _get_conversation_id returns response ID when store is True and conversation ID is empty."""
client = create_test_azure_ai_client(MagicMock())
# Mock OpenAI response with conversation but empty ID
@@ -872,13 +786,13 @@ def test_get_conversation_id_with_store_true_and_empty_conversation_id() -> None
mock_conversation.id = ""
mock_response.conversation = mock_conversation
result = client.get_conversation_id(mock_response, store=True)
result = client._get_conversation_id(mock_response, store=True)
assert result == "resp_12345"
def test_get_conversation_id_with_store_false() -> None:
"""Test get_conversation_id returns None when store is False."""
"""Test _get_conversation_id returns None when store is False."""
client = create_test_azure_ai_client(MagicMock())
# Mock OpenAI response with conversation
@@ -888,13 +802,13 @@ def test_get_conversation_id_with_store_false() -> None:
mock_conversation.id = "conv_67890"
mock_response.conversation = mock_conversation
result = client.get_conversation_id(mock_response, store=False)
result = client._get_conversation_id(mock_response, store=False)
assert result is None
def test_get_conversation_id_with_parsed_response_and_store_true() -> None:
"""Test get_conversation_id works with ParsedResponse when store is True."""
"""Test _get_conversation_id works with ParsedResponse when store is True."""
client = create_test_azure_ai_client(MagicMock())
# Mock ParsedResponse with conversation
@@ -904,13 +818,13 @@ def test_get_conversation_id_with_parsed_response_and_store_true() -> None:
mock_conversation.id = "conv_parsed_67890"
mock_response.conversation = mock_conversation
result = client.get_conversation_id(mock_response, store=True)
result = client._get_conversation_id(mock_response, store=True)
assert result == "conv_parsed_67890"
def test_get_conversation_id_with_parsed_response_no_conversation() -> None:
"""Test get_conversation_id returns response ID with ParsedResponse when no conversation exists."""
"""Test _get_conversation_id returns response ID with ParsedResponse when no conversation exists."""
client = create_test_azure_ai_client(MagicMock())
# Mock ParsedResponse without conversation
@@ -918,7 +832,7 @@ def test_get_conversation_id_with_parsed_response_no_conversation() -> None:
mock_response.id = "resp_parsed_12345"
mock_response.conversation = None
result = client.get_conversation_id(mock_response, store=True)
result = client._get_conversation_id(mock_response, store=True)
assert result == "resp_parsed_12345"