* WIP: with_output_from
* Add with_output_from to other modules; next: workflow as agent
* WIP: remove agent run events
* orchestrations
* WIP: update samples; next start at guessing_game_With_human_input.py
* Update all samples
* WIP: consolidate workflow as agent streaming vs non-streaming
* Consolidate workflow as agent streaming vs non-streaming
* Move request info event processing to a share method
* Final pass on the samples
* Fix mypy
* Fix mypy
* Comments
---------
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
* Replace Role and FinishReason classes with NewType + Literal
- Remove EnumLike metaclass from _types.py
- Replace Role class with NewType('Role', str) + RoleLiteral
- Replace FinishReason class with NewType('FinishReason', str) + FinishReasonLiteral
- Update all usages across codebase to use string literals
- Remove .value access patterns (direct string comparison now works)
- Add backward compatibility for legacy dict serialization format
- Update tests to reflect new string-based types
Addresses #3591, #3615
* Simplify ChatResponse and AgentResponse type hints (#3592)
- Remove overloads from ChatResponse.__init__
- Remove text parameter from ChatResponse.__init__
- Remove | dict[str, Any] from finish_reason and usage_details params
- Remove **kwargs from AgentResponse.__init__
- Both now accept ChatMessage | Sequence[ChatMessage] | None for messages
- Update docstrings and examples to reflect changes
- Fix tests that were using removed kwargs
- Fix Role type hint usage in ag-ui utils
* Remove text parameter from ChatResponseUpdate and AgentResponseUpdate (#3597)
- Remove text parameter from ChatResponseUpdate.__init__
- Remove text parameter from AgentResponseUpdate.__init__
- Remove **kwargs from both update classes
- Simplify contents parameter type to Sequence[Content] | None
- Update all usages to use contents=[Content.from_text(...)] pattern
- Fix imports in test files
- Update docstrings and examples
* Rename from_chat_response_updates to from_updates (#3593)
- ChatResponse.from_chat_response_updates → ChatResponse.from_updates
- ChatResponse.from_chat_response_generator → ChatResponse.from_update_generator
- AgentResponse.from_agent_run_response_updates → AgentResponse.from_updates
* Remove try_parse_value method from ChatResponse and AgentResponse (#3595)
- Remove try_parse_value method from ChatResponse
- Remove try_parse_value method from AgentResponse
- Remove try_parse_value calls from from_updates and from_update_generator methods
- Update samples to use try/except with response.value instead
- Update tests to use response.value pattern
- Users should now use response.value with try/except for safe parsing
* Add agent_id to AgentResponse and clarify author_name documentation (#3596)
- Add agent_id parameter to AgentResponse class
- Document that author_name is on ChatMessage objects, not responses
- Update ChatResponse docstring with author_name note
- Update AgentResponse docstring with author_name note
* Simplify ChatMessage.__init__ signature (#3618)
- Make contents a positional argument accepting Sequence[Content | str]
- Auto-convert strings in contents to TextContent
- Remove overloads, keep text kwarg for backward compatibility with serialization
- Update _parse_content_list to handle string items
- Update all usages across codebase to use new format: ChatMessage("role", ["text"])
* Allow Content as input on run and get_response
- Update prepare_messages and normalize_messages to accept Content
- Update type signatures in _agents.py and _clients.py
- Add tests for Content input handling
* Fix ChatMessage usage across packages and samples
Update all remaining ChatMessage(role=..., text=...) to use new
ChatMessage('role', ['text']) signature.
* Fix Role string usage and response format parsing
- Fix redis provider: remove .value access on string literals
- Fix durabletask ensure_response_format: set _response_format before accessing .value
* Fix ollama .value and ai_model_id issues, handle None in content list
- Fix ollama _chat_client: remove .value on string literals
- Fix ollama _chat_client: rename ai_model_id to model_id
- Fix _parse_content_list: skip None values gracefully
* Fix A2AAgent type signature to include Content
* Fix Role/FinishReason NewType dict annotations and improve test coverage to 95%
* Fix mypy errors for Role/FinishReason NewType usage
* Fix Role.TOOL and Role.ASSISTANT usage in _orchestrator_helpers.py
* Fix Role NewType usage in durabletask _models.py
Eduard van Valkenburg
·
2026-02-04 10:13:23 +00:00
* fix(claude): preserve $defs in JSON schema for nested Pydantic models
- Preserve $defs section from Pydantic JSON schema when converting FunctionTool to SDK MCP tool
- This fixes tools with nested Pydantic models that use $ref references
- Add test for nested type schema preservation
Fixes#3654
* Adjust shared state import
* Fix MCP tool kwargs serialization bug
---------
Co-authored-by: Evan Mattson <evan.mattson@microsoft.com>
* Support specifying types via handler and executor decorators
* Add handling for string types
* Fix typing
* Address PR feedback
* All or nothing for handler typing approach
* Fix mypy issues
* type support for request info
* Fix naming issue
* Fix mypy
* Python: Add coverage threshold gate for PR checks (#3392)
- Add python-check-coverage.py script to enforce coverage threshold on specific modules
- Modify python-test-coverage.yml to run coverage check after tests
- Initial enforced module: agent_framework_azure_ai at 85% threshold
- Other modules are reported for visibility but don't block merges
* Fail if module not found
* Force unit test job to run
* Comment 1
* Fix coverage check to use full package paths for submodule support
* Update report format
* Add core utilities unit tests to improve coverage (#3356)
* Address PR comments: remove redundant imports and fix misleading test
* Refactor tests to use module-level mock class instead of inline classes
* Remove unnecessary tests for trivial base class implementations
* Restore base class tests with module-level helper class
* changed AIFunction to FunctionTool and @ai_function to @tool
* test and mypy fixes
* mypy fix
* switch function tool to always_require
* fix noop
* fix github copilot imports
* test fixes
* fix ollama test
* fixes for tests
* fix tests
* reverted change to always_require and extended timeout
* fix test
Eduard van Valkenburg
·
2026-01-28 14:53:53 +00:00
* Fix: Add system_instructions to ChatClient LLM span tracing
- Add system_instructions parameter to _capture_messages() calls in
_trace_get_response() and _trace_get_streaming_response()
- Extract instructions from chat_options in kwargs
- Add unit tests to verify system_instructions are captured correctly
When using ChatClient with ChatOptions.instructions, the OpenTelemetry
LLM span was missing system messages in gen_ai.input.messages and the
gen_ai.system_instructions attribute was not being set.
This fix aligns the ChatClient-level tracing with the Agent-level
tracing which already correctly passes system_instructions.
Fixes#3163
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* Add edge case tests for system_instructions
- Add test for empty string instructions (should not set attribute)
- Add test for list-type instructions (verify multiple items captured)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
* Simplify: use options.get('instructions') directly instead of kwargs.get('chat_options')
Addresses reviewer feedback:
- Removed unnecessary chat_options variable from kwargs
- Directly access instructions from the options parameter
- Updated tests to use dict syntax for options (TypedDict convention)
---------
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
* Group chat refactoring Part 1; Next: HIL and handoff
* Add agent approval flow; next samples
* WIP: samples
* WIP: HIL samples
* Group chat HIL working; next: handoff
* Fix group chat tool approval sample
* WIP: refactor handoff; next handoff handling
* Handoff done; next handoff samples and concurrent and sequential
* Handoff samples, concurrent, and sequential done; next Magentic
* WIP: magentic; next test with samples + HIL
* Magentic Working; next fix all samples and tests
* Fix handoff samples; next tests
* WIP: fixing tests; some orchestration as agent samples are failing
* Group chat unit tests done
* Handoff unit tests done
* Remove old orchestration_request_info and fix related tests
* Magentic unit tests done
* Fix samples
* Fix test
* Fix test 2
* mypy
* Address comments
* Update readme
* Address comments
* Address comments 2
* Replace display name
* removed display_name, renamed context_providers, middleware and AggregateContextProvider
* fixes
* fixed test
* testfix
* removed mistakenly put back test
* updated new test
* rename middlewares to middleware
* middleware fixes
Eduard van Valkenburg
·
2026-01-13 02:24:07 +00:00
* Fix MCP tool result serialization for list[TextContent]
When MCP tools return results containing list[TextContent], they were
incorrectly serialized to object repr strings like:
'[<agent_framework._types.TextContent object at 0x...>]'
This fix properly extracts text content from list items by:
1. Checking if items have a 'text' attribute (TextContent)
2. Using model_dump() for items that support it
3. Falling back to str() for other types
4. Joining single items as plain text, multiple items as JSON array
Fixes#2509
* Address PR review feedback for MCP tool result serialization
- Extract serialize_content_result() to shared _utils.py
- Fix logic: use texts[0] instead of join for single item
- Add type annotation: texts: list[str] = []
- Return empty string for empty list instead of '[]'
- Move import json to file top level
- Add comprehensive unit tests for serialization
* Address PR review feedback: fix type checking and double serialization
- Add isinstance(item.text, str) check to ensure text attribute is a string
- Fix double-serialization issue by keeping model_dump results as dicts
until final json.dumps (removes escaped JSON strings in arrays)
- Improve docstring with detailed return value documentation
- Add test for non-string text attribute handling
- Add tests for list type tool results in _events.py path
* Simplify PR: minimal changes to fix MCP tool result serialization
Addresses reviewer feedback about excessive refactoring:
- Reset _events.py to original structure
- Only add import and use serialize_content_result in one location
- All review comments addressed in serialize_content_result():
- Added isinstance(item.text, str) check
- Use model_dump(mode="json") to avoid double-serialization
- Improved docstring with explicit return value documentation
- Empty list returns "" instead of "[]"
* Refactor: Move MCP TextContent serialization to core prepare_function_call_results
Per reviewer feedback, moved the TextContent serialization logic from
ag-ui's serialize_content_result to the core package's
prepare_function_call_results function.
Changes:
- Added handling for objects with 'text' attribute (like MCP TextContent)
in _prepare_function_call_results_as_dumpable
- Removed serialize_content_result from ag-ui/_utils.py
- Updated _events.py and _message_adapters.py to use
prepare_function_call_results from core package
- Updated tests to match the core function's behavior
* Fix failing tests for prepare_function_call_results behavior
- test_tool_result_with_none: Update expected value to 'null' (JSON serialization of None)
- test_tool_result_with_model_dump_objects: Use Pydantic BaseModel instead of plain class
* Fix B903 linter error: Convert MockTextContent to dataclass
The ruff linter was reporting B903 (class could be dataclass or namedtuple)
for the MockTextContent test helper classes. This commit converts them to
dataclasses to satisfy the linter check.
* 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
Eduard van Valkenburg
·
2025-12-18 12:02:23 +00:00
* 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