* feat(ag-ui): Add Pydantic request model and OpenAPI tags support
- Add AGUIRequest Pydantic model in _types.py with field descriptions
- Update add_agent_framework_fastapi_endpoint() to accept tags parameter
- Use AGUIRequest model for automatic validation and OpenAPI schema generation
- Export AGUIRequest and DEFAULT_TAGS in __init__.py
- Update test_endpoint.py to expect 422 for invalid requests
- Add tests for OpenAPI schema, default tags, custom tags, and validation
Benefits:
- Better API documentation with complete request schema in Swagger UI
- Automatic request validation with Pydantic
- Organized endpoints under 'AG-UI' tag instead of 'default'
- Improved developer experience and type safety
Fixes #<issue-number>
* test(ag-ui): Add test for internal error handling to achieve 100% coverage
- Add test_endpoint_internal_error_handling() to cover exception handling code
- Mock copy.deepcopy to simulate internal error during default_state processing
- Add type: ignore for FastAPI tags parameter (known pyright compatibility issue)
- Achieves 100% test coverage for _endpoint.py (previously missing lines 103-105)
When processing `input_json_delta` events, the Anthropic client was
passing the tool name from the previous `tool_use` event. This caused
ag-ui's `_handle_function_call_content` to emit a `ToolCallStartEvent`
for every streaming chunk (since it triggers on `if content.name:`).
This fix changes the behavior to pass an empty string for `name` in
`input_json_delta` events, matching OpenAI's behavior where streaming
argument chunks have `name=""`. The initial `tool_use` event still
provides the tool name, so only one `ToolCallStartEvent` is emitted.
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
* fix Python: kwargs are not passed to _prepare_thread_and_messages in ChatAgent.run
Fixes#3118
* fix Python: [Bug]: model_id versus model_deployment_name is confusing in Azure AI Agents
Fixes#3147
* add types
* fixed type and docstring
* fix(ag-ui): execute tools after approval in human-in-the-loop flow
* Fix shared state bug
* Bug fix finalized
* Refactoring to clean up code
* Code cleanup
* More fixes
* More code cleanup
* Add version detection in __init__.py to ruff ignore list
* fix: Expose WorkflowErrorEvent as ErrorContent
When hosted using .AsAgent(), Workflows were not exposing inner errors coming as Exceptions (through the WorkflowErrorEvent)
The fix is to convert their message to an ErrorContent on the way out, rather than rely on the default "empty update" to collect the raw event.
* feat: Add a way to show/suppress exception information
* save input messages and stream updates to the continuation token to be able to use them in the last successful stream resumption call.
* Update dotnet/src/Microsoft.Agents.AI/ChatClient/ChatClientAgentContinuationToken.cs
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update dotnet/src/Microsoft.Agents.AI/ChatClient/ChatClientAgentContinuationToken.cs
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update dotnet/tests/Microsoft.Agents.AI.UnitTests/ChatClient/ChatClientAgent_BackgroundResponsesTests.cs
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update dotnet/src/Microsoft.Agents.AI/ChatClient/ChatClientAgentContinuationToken.cs
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update dotnet/src/Microsoft.Agents.AI/ChatClient/ChatClientAgentContinuationToken.cs
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* fix typo
* init continuation token from chat response
* remove unnecessary types for source generation
* remove check for continuation token passed at initial run
* remove check for continuation token pass at initial run
* centralize continuation token parsing
* update xml comments
* use readonly collection instead of enumerable
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* map additional props from agent run options to a2a request metadata
* small touches
* add unit tests for new extension methods
* Sort using
* add unit test
* add additiona unit tests
* special case json element to avoid unnecessary serialization
* Improve DevUI, add Context Inspector view as new tab under traces
* fix mypy errors
* fix: Handle stale MCP connections in DevUI executor
MCP tools can become stale when HTTP streaming responses end - the underlying
stdio streams close but `is_connected` remains True. This causes subsequent
requests to fail with `ClosedResourceError`.
Add `_ensure_mcp_connections()` to detect and reconnect stale MCP tools before
agent execution. This is a workaround for an upstream Agent Framework issue
where connection state isn't properly tracked.
Fixes MCP tools failing on second HTTP request in DevUI.
fixes #1476#1515#2865
* fix#1572 report import dependency errors more clearly
* Ensure there is streaming toggle where users can select streaming vs non streaming mode in devui . Fixes .NET: [Python] DevUI tool call rendering in non-streaming mode?
* remove unused dead code
* improve ux - workflows with agents show a chat component in execution timelien, also ensure magentic final output shows correctly
* update ui build
* update devui to use instrumentation instead of tracing, other instrumentation and type/instance check fixes
* 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.
* Refactor ChatMessageStore methods to be similar to AIContextProvider
* Fix file encoding
* Ensure that AIContextProvider messages area also persisted.
* Update formatting and seal context classes
* Improve formatting
* Remove optional messages from constructor and add unit test
* Add ChatMessageStore filtering via a decorator
* Update sample and cosmos message store to store AIContextProvider messages in right order. Fix unit tests.
* Update Workflowmessage store to use aicontext provider messages.
* Apply suggestions from code review
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com>
* Improve xml docs messaging
* Address code review comments.
* Also notify message store on failure
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com>
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