* fix(foundry): reconcile toolbox hosted-tool payloads with Responses API
* docs(foundry): update create_sample_toolbox docstring to reflect all tools created
* Add support for the Foundry Toolbox in MAF
Introduces a Foundry Toolbox integration: FoundryChatClient gains a
get_toolbox() helper plus select_toolbox_tools(), normalize_tools in
the core package flattens tool-collection wrappers (ToolboxVersionObject
and generic iterables, while leaving Pydantic BaseModel instances
alone), and the new agent_framework.foundry namespace re-exports the
toolbox helpers. Ships with unit tests, a sample, and a design doc.
azure-ai-projects is pinned to the public >=2.0.0,<3.0 range and the
lockfile resolves from public PyPI. The toolbox test module skips when
Toolbox* types are unavailable so CI stays green until the public 2.1.0
SDK lands. OMC tooling directories (.omc/, .omx/) are gitignored.
* Update to latest azure ai projects package
* Improve sample
* Rename ADR to 0025
* Update ADR
* Apply suggestion from @alliscode
Co-authored-by: Ben Thomas <ben.thomas@microsoft.com>
* Improve samples
* Update test
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Co-authored-by: Ben Thomas <ben.thomas@microsoft.com>
_prepare_options() now removes tools, tool_choice, and parallel_tool_calls
from run_options after injecting agent_reference. The Foundry API rejects
requests containing both fields. FunctionTools are still invoked client-side
by the function invocation layer.
Fixes#5087
Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
* Raise clear handler registration error for unresolved TypeVar (#4943)
Detect unresolved TypeVar in message parameter annotations during handler
registration in both _validate_handler_signature (Executor) and
_validate_function_signature (FunctionExecutor). Raises a ValueError with
an actionable message recommending @handler(input=..., output=...) or
@executor(input=..., output=...) instead of letting TypeVar leak through
to a confusing TypeCompatibilityError during workflow edge validation.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4943: reorder checks and harden function executor
- Move TypeVar check before validate_workflow_context_annotation in
_executor.py so users see the more actionable error first
- Wrap get_type_hints in try/except in _function_executor.py matching
the defensive pattern in _executor.py
- Repurpose duplicate test to cover bounded TypeVar rejection
- Add test_function_executor_allows_concrete_types for test symmetry
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Narrow get_type_hints except clause and add missing tests (#4943)
- Narrow `except Exception` to `except (NameError, AttributeError, RecursionError)`
in both _executor.py and _function_executor.py so unexpected failures in
get_type_hints are not silently swallowed.
- Add test_handler_unresolvable_annotation_raises to test_function_executor_future.py
exercising the except branch of get_type_hints in the function executor path.
- Add test_function_executor_rejects_bounded_typevar_in_message_annotation to
test_function_executor.py for parity with the Executor bounded TypeVar test.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add error ordering test for TypeVar vs WorkflowContext priority (#4943)
Add test_handler_typevar_error_takes_priority_over_context_error to verify
that when a handler has both a TypeVar message and an unannotated ctx, the
TypeVar error is raised first (the more actionable issue).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Fix image content serialization sending null file_id to Foundry API
Omit file_id from input_image dict when not present instead of including
it as null, which Azure AI Foundry's stricter schema validation rejects.
* Python: Fix Foundry API rejecting rich content in function_call_output
Azure AI Foundry does not support list-format output in function_call_output
items. Add SUPPORTS_RICH_FUNCTION_OUTPUT flag (default True) to
RawOpenAIChatClient, set to False in RawFoundryChatClient so Foundry
falls back to string output for tool results with images/files.
Also omit file_id from input_image dicts when not set, since Foundry
rejects explicit nulls.
* Python: Surface rich tool content as user message when Foundry lacks support
When SUPPORTS_RICH_FUNCTION_OUTPUT is False, image/file items from tool
results are injected as a follow-up user message so the model can still
process the visual content via Foundry's supported user message format.
* Xfail Foundry image integration test for the meantime
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>