* Fix PydanticSchemaGenerationError with PEP 563 annotations in @tool
_resolve_input_model used raw param.annotation from inspect.signature(),
which returns string annotations when 'from __future__ import annotations'
is active (PEP 563). This caused Pydantic's create_model to fail for
complex types like Optional[int] or FunctionInvocationContext.
Use typing.get_type_hints() to resolve annotations to actual types before
passing them to create_model, matching the approach already used by
_discover_injected_parameters.
Fixes#4809
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Remove reproduction report and unused test imports
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(tests): strengthen PEP 563 regression tests per review feedback (#4809)
- Verify type correctness in schema assertions (not just key presence)
- Fix ctx annotation to FunctionInvocationContext | None for type consistency
- Add test for Optional[CustomType] pattern (original bug trigger)
- Add test for get_type_hints() fallback with unresolvable forward refs
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Address review feedback for #4809: Python: [Bug]: PydanticSchemaGenerationError in FunctionInvocationContext
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: avoid duplicate agent response telemetry
* Python: conditionally suppress duplicate agent telemetry
* Simplify telemetry ownership tracking
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Aggregate token usage from inner chat spans on invoke_agent span
The invoke_agent span now carries the aggregated input/output token
counts from all inner chat completion spans that occur during an agent
run. Previously, when inner ChatTelemetryLayer spans captured usage,
the outer AgentTelemetryLayer skipped setting usage entirely to avoid
duplication. Now a new INNER_ACCUMULATED_USAGE context variable tracks
cumulative usage across all inner completions, and the agent span
always reports the total.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* [BREAKING] Refactor middleware layering and raw clients
Reorder chat client layers so function invocation wraps chat middleware, and chat middleware stays outside telemetry while still running for each inner model call. Add middleware pipeline caching, refresh docs and samples, and split Anthropic into raw and public clients to match the standard layering model.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Tighten typing ignores in ancillary modules
Add targeted typing ignores in workflow visualization and lab modules so pyright stays clean alongside the middleware refactor work.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix categorize_middleware to unpack tuple/Sequence and use relative MRO assertions
- Broaden isinstance check in categorize_middleware from list to Sequence
so tuples and other Sequence types are properly unpacked instead of
being appended as a single item.
- Replace fragile hardcoded MRO index assertions in anthropic test with
relative ordering via mro.index().
- Add regression tests for categorize_middleware with tuple, list, and
None inputs.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix middleware string decomposition, add middleware param to FunctionInvocationLayer, and add tests (#4710)
- Guard categorize_middleware Sequence check against str/bytes to prevent
character-by-character decomposition of accidentally passed strings
- Add explicit middleware parameter to FunctionInvocationLayer.get_response
and merge it into client_kwargs before categorization, fixing the
inconsistency where only OpenAIChatClient supported this parameter
- Add assertions that RawAnthropicClient does not inherit convenience layers
- Add chat middleware cache test with non-empty base middleware
- Add tests for single unwrapped middleware item and string input
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Apply pre-commit auto-fixes
* Address review feedback for #4710: review comment fixes
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <copilot@github.com>
* Support detail field in OpenAI image_url payload (#4616)
Include the optional 'detail' field from Content.additional_properties
when building image_url payloads for the OpenAI Chat API, matching the
existing pattern used for 'filename' in document file payloads.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Remove reproduction report
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Simplify detail extraction from additional_properties (#4616)
- Remove unnecessary hasattr check; additional_properties is always
initialized as a dict on Content instances.
- Use 'is not None' instead of truthy check to be more precise.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Remove detail allowlist in chat client to align with responses client
Replace the strict allowlist check ('low', 'high', 'auto') with an
isinstance(detail, str) check so that any valid string detail value is
passed through to OpenAI. This aligns the chat client behavior with the
responses client, which passes detail through unconditionally.
Also add test coverage for:
- Future/unknown string detail values being passed through
- Data URI images (covering the 'data' branch of the match)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix zero-argument MCP tool schema missing 'properties' key (#4540)
MCP servers for zero-argument tools (e.g. matlab-mcp-core-server's
detect_matlab_toolboxes) declare inputSchema as {"type": "object"}
without a "properties" key. OpenAI's API requires "properties" to
be present on object schemas, causing a 400 invalid_request_error.
Normalize inputSchema at MCP ingestion in load_tools() to inject an
empty "properties": {} when it is missing from object-type schemas.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4540: improve test robustness and add defensive guard
- Look up loaded functions by name instead of index to avoid brittle
ordering assumptions
- Add negative-path test cases: non-object schema (type: string) and
empty schema ({}) to verify guard clause skips them correctly
- Assert original inputSchema dicts are not mutated by load_tools()
- Add defensive guard for tool.inputSchema being None
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4540: Python: [Bug]: Local stdio MCP works for calculator but fails for official matlab-mcp-core-server on LM Studio /v1/responses
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix invoke_agent span to aggregate token usage across LLM calls (#4062)
The FunctionInvocationLayer._get_response() loop was overwriting the
response on each iteration, so usage_details only reflected the last
chat completion call. Now tracks aggregated_usage across all iterations
using add_usage_details() and sets it on the returned response.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Remove reproduction report artifact
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Apply pre-commit auto-fixes
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated automation tasks and commands, with alias for the time being
* Restore aggregate test exclusions
Preserve the legacy all-tests scope for test --all by excluding lab and devui from the default aggregate sweep, while still allowing explicit package selection. Also ignore hidden/generated test directories such as .mypy_cache during aggregate discovery.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated versions in pre-commit
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Re-read env vars in configure_otel_providers and enable_instrumentation (#4119)
Fix ENABLE_SENSITIVE_DATA and VS_CODE_EXTENSION_PORT env vars being ignored
when load_dotenv() runs after module import. The module-level
OBSERVABILITY_SETTINGS singleton cached env state at import time, and
configure_otel_providers() / enable_instrumentation() never re-read from
os.environ when parameters were None.
Both functions now construct a fresh ObservabilitySettings() to pick up
current env vars when explicit parameters are not provided, matching the
existing behavior of the env_file_path branch.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review feedback for #4119: avoid throwaway ObservabilitySettings
- Add _read_bool_env/_read_int_env helpers to read env vars without
constructing a full ObservabilitySettings (which calls create_resource())
- Replace ObservabilitySettings() in enable_instrumentation() and
configure_otel_providers() else-branch with direct env reads
- Add enable_console_exporters parameter to configure_otel_providers()
for override parity with enable_sensitive_data and vs_code_extension_port
- Propagate _resource and _executed_setup in the non-env_file_path branch
- Make existing tests hermetic (clear VS_CODE_EXTENSION_PORT and
ENABLE_CONSOLE_EXPORTERS env vars)
- Add tests: enable_console_exporters env refresh, explicit param overrides
for both enable_instrumentation() and configure_otel_providers()
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address remaining review feedback for #4119
- Refresh enable_console_exporters in enable_instrumentation() for
consistency with configure_otel_providers(), so env var changes
after import are picked up by both public API functions
- Make test_configure_otel_providers_reads_env_vs_code_port hermetic
by clearing ENABLE_CONSOLE_EXPORTERS from the environment
- Add test_enable_instrumentation_reads_env_console_exporters to
cover the new refresh behavior
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove unconditional enable_console_exporters overwrite from enable_instrumentation() (#4119)
enable_instrumentation() is documented as not configuring exporters, so
managing enable_console_exporters there was a leaky abstraction. The
unconditional _read_bool_env call silently reset the value to False when
ENABLE_CONSOLE_EXPORTERS was absent from env, clobbering any value
previously set by configure_otel_providers(enable_console_exporters=True).
- Remove the unconditional overwrite line from enable_instrumentation()
- Replace test_enable_instrumentation_reads_env_console_exporters with
test_enable_instrumentation_does_not_touch_console_exporters
- Add regression test: enable_instrumentation() does not clobber a
previously configured enable_console_exporters value
- Add test: explicit enable_sensitive_data param still leaves
enable_console_exporters untouched
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix Content serialization in DurableAgentStateUnknownContent (#4719)
DurableAgentStateUnknownContent.from_unknown_content() stored raw Content
objects without converting them to dicts, causing json.dumps to fail in
Azure Durable Functions' entity state serialization. This affected content
types not explicitly handled (e.g., mcp_server_tool_call/result).
The fix converts Content objects to dicts via to_dict() when storing in
DurableAgentStateUnknownContent, and restores them via Content.from_dict()
in to_ai_content().
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add to_json and from_json methods to Content class (#4719)
Add to_json() and from_json() methods to the Content class to match the
serialization interface provided by SerializationMixin on other model classes.
Also fix pre-existing pyright type errors in durabletask's
DurableAgentStateUnknownContent.to_ai_content().
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review: add type guard, remove to_json, add fallback, and tests
- Remove Content.to_json() per reviewer request (comment 3)
- Add type guard in Content.from_json() for non-dict JSON (comments 1, 4)
- Wrap json.JSONDecodeError as ValueError for consistent exception contract
- Add try/except fallback in to_ai_content() for invalid Content dicts (comment 5)
- Add test_content_to_dict_exclude_none and test_content_to_dict_exclude_fields (comment 2)
- Add test_unknown_content_to_ai_content_fallback_on_invalid_type_dict (comment 5)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Address review feedback for #4719: review comment fixes
* Remove Content.from_json, move logic to consuming code (#4719)
Remove the from_json convenience method from Content class per review
feedback. This is the same trivial json.loads + from_dict wrapper as
to_json which was already removed. Consumers should call json.loads
and Content.from_dict directly.
Update tests to use Content.from_dict(json.loads(...)) pattern and
remove from_json-specific error handling tests (those errors are
already covered by json.loads and Content.from_dict).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: clean up kwargs across agents, chat clients, tools, and sessions (#3642)
Audit and refactor public **kwargs usage across core agents, chat clients,
tools, sessions, and provider packages per the migration strategy codified
in CODING_STANDARD.md.
Key changes:
- Add explicit runtime buckets: function_invocation_kwargs and client_kwargs
on RawAgent.run() and chat client get_response() layers.
- Refactor FunctionTool to prefer explicit ctx: FunctionInvocationContext
injection; legacy **kwargs tools still work via _forward_runtime_kwargs.
- Refactor Agent.as_tool() to use direct JSON schema, always-streaming
wrapper, approval_mode parameter, and UserInputRequiredException
propagation (integrates PR #4568 behavior).
- Remove implicit session bleeding into FunctionInvocationContext; tools
that need a session must receive it via function_invocation_kwargs.
- Lower chat-client layers after FunctionInvocationLayer accept only
compatibility **kwargs (client_kwargs flattened, function_invocation_kwargs
ignored).
- Add layered docstring composition from Raw... implementations via
_docstrings.py helper.
- Clean up provider constructors to use explicit additional_properties.
- Deprecation warnings on legacy direct kwargs paths.
- Update samples, tests, and typing across all 23 packages.
Resolves#3642
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* clarified docstring
* feedback fixes
* Add unit tests for _docstrings.py build/apply helpers
Tests cover: no docstring source, no extra kwargs, appending to existing
Keyword Args section, inserting after Args, inserting in plain docstrings,
multiline descriptions, ordering, and apply_layered_docstring.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add test for propagate_session TypeError on non-AgentSession values
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add tests for multi-content and empty UserInputRequiredException propagation
Cover the branching logic in _try_execute_function_calls for:
- Multiple user_input_request items in a single exception (extra_user_input_contents path)
- Empty contents list (fallback function_result path)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add tests for DurableAIAgent.get_session forwarding service_session_id
Verifies get_session correctly forwards service_session_id and session_id
to the executor's get_new_session, replacing the removed kwargs test.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Simplify ag-ui test stub to read session from client_kwargs only
Remove dual-mode detection (client_kwargs vs raw kwargs fallback) from
the test mock. Session is now read exclusively from client_kwargs,
matching the settled public calling convention.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated create and get sessions in durable
* fixed docstrings
* fix test
* updated session handling
* updated from main
* updated tests
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* feat(python): allow @tool functions to return rich content (images, audio)
Add support for tool functions to return Content objects that the model can perceive natively. Closes#4272
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Anthropic logging + mypy fix
* Address PR review: fix MCP ordering, fold helper into from_function_result, fix Chat client
- Preserve original content order in MCP tool results instead of text-first
- Move _build_function_result logic into Content.from_function_result()
- Chat Completions: inject user message for rich items (API only supports string tool content)
- Update tests for ordering and new from_function_result behavior
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Use native Responses API multi-part output, warn+omit for Chat client
- Responses client: put rich items directly in function_call_output's
output field as list (native API support) instead of user message injection
- Chat client: warn and omit rich items (API doesn't support multi-part
tool results), matching Ollama/Bedrock pattern
- Unify test image: use sample_image.jpg across all integration tests
- Add Azure OpenAI Responses integration test
- Assert model describes house image to verify perception
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix lint: remove print statement, wrap long line
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback: bug fixes, single-pass MCP, unit tests
- Add isinstance guard in from_function_result for non-Content lists
- Fix Anthropic empty tool_content fallback to string result
- Fix Content(type='text', text=None) edge case in parse_result
- Rewrite MCP _parse_tool_result_from_mcp as single-pass (no index counters)
- Add Anthropic unit tests: data image, uri image, unsupported media, all-unsupported
- Add OpenAI Chat unit test: rich items warning and omission
- Add OpenAI Responses unit tests: function_result with/without items
- Add test_types tests: only-rich-items list, non-Content list fallback
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix pyright errors: add type ignore comments for Any list iteration
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix mypy/pyright: ensure ToolExecutionException receives str
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix lint: remove duplicate test_prepare_options_excludes_conversation_id
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* refactor: unify all tool results into Content items
* addressed copilot comments
* pyright fix
* small fix
* comments
* fix: address Copilot review - warnings, blob safety, dedup
- Add warning logs when rich content is dropped in Claude agent and
MCP server handlers (matching Chat/Bedrock/Ollama pattern)
- Defensive blob URI construction: wrap plain base64 in data: prefix
- Simplify Chat client _prepare_content_for_openai to use content.result
- Simplify Responses client text-only path, remove redundant nesting
- Add test for plain base64 blob without data: prefix
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix token double-counting in compaction and address review comments
- Exclude items from _serialize_content() to prevent double-counting
tokens when items mirrors result in function_result content
- Add rich content warning in GitHub Copilot agent tool handler
- Replace raw Content debug log with concise item count/type summary
- Update stale test comments about FunctionTool.invoke return type
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Implement annotation-based context compaction
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Handle missing compaction attributes in BaseChatClient
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix CI typing and bandit issues
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Optimize incremental compaction annotation pass
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* refinement
* Python: add ToolResultCompactionStrategy and CompactionProvider
Add ToolResultCompactionStrategy that collapses older tool-call groups
into short summary messages (e.g. [Tool calls: get_weather]) while
keeping the most recent groups verbatim. This mirrors the .NET
ToolResultCompactionStrategy from PR #4533.
Add CompactionProvider as a context-provider that auto-applies compaction
before each agent turn and stores compacted history in session state
after each turn.
Includes tests and samples for both features.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* refinement and alignment with dotnet PR
* updated tool result compaction
* updated tool result compaction
* Python: add ToolResultCompactionStrategy, CompactionProvider, and skip_excluded
- ToolResultCompactionStrategy collapses older tool-call groups into
[Tool results: func_name: result] summaries with bidirectional tracing
(same pattern as SummarizationStrategy).
- CompactionProvider as BaseContextProvider with separate before_strategy
and after_strategy parameters. before_strategy compacts loaded context;
after_strategy compacts stored history via history_source_id.
- InMemoryHistoryProvider gains skip_excluded flag to filter out messages
marked as excluded by compaction strategies.
- Tests, samples, and exports updated.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fixed checks
* fix mypy
* Fix: ensure summary messages from both strategies get full compaction annotations
SummarizationStrategy was not calling annotate_message_groups after
inserting its summary message, so the summary lacked core group
annotations (id, kind, index, has_reasoning, _excluded). Added the
missing call. ToolResultCompactionStrategy already had it.
Added tests verifying both strategies produce fully annotated summaries.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated propagation
* fix mypy
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* support skill scripts execution
* fix mixed line endings
* address comments and fix syntax issues
* use few try/except instead of one
* change samples
* validate either script path or script resource is set not both
* fix: separate LLM args from runtime kwargs in skill script execution
* address pr review comments
* address PR review comments
* Update python/packages/core/agent_framework/_skills.py
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update python/packages/core/agent_framework/_skills.py
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Update python/packages/core/agent_framework/_skills.py
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* 1. Fixing the caching bug where parameters_schema would re-inspect on every call when the result was None
2. Updating the arguments tool description to be more generic (not CLI-specific)
* fix failing tests
* address pr review comments
* address pr review comments
* allow resource function returning any instead of sting
* address PR review comments
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Python: Fix `executor_completed` event with non-copyable raw_representation in mixed workflows
Fixes#4455
* fix(#4455): use class-level sets for deepcopy field exclusion
- SerializationMixin.__deepcopy__: check type(self).DEFAULT_EXCLUDE
instead of hardcoding 'raw_representation'
- Content.__deepcopy__: add _SHALLOW_COPY_FIELDS class variable and
check against it instead of hardcoding
- Fix tautological assertion in test (was always True)
- Add second excluded field to test to verify DEFAULT_EXCLUDE is
respected generically
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Decouple __deepcopy__ from DEFAULT_EXCLUDE in SerializationMixin (#4455)
Introduce _SHALLOW_COPY_FIELDS class variable in SerializationMixin to
separate deep-copy semantics from serialization semantics. Previously,
__deepcopy__ used DEFAULT_EXCLUDE to decide which fields to shallow-copy,
conflating 'not serialized' with 'not safe to deep-copy'. A field added
to DEFAULT_EXCLUDE purely for serialization (e.g. additional_properties)
would be silently shared between original and copy.
- Add _SHALLOW_COPY_FIELDS (default {'raw_representation'}) to
SerializationMixin, matching the pattern already used by Content
- Update __deepcopy__ to read from _SHALLOW_COPY_FIELDS instead of
DEFAULT_EXCLUDE
- Add test verifying DEFAULT_EXCLUDE fields are deep-copied unless
also in _SHALLOW_COPY_FIELDS
- Add test for Content._SHALLOW_COPY_FIELDS identity preservation
- Add test for ChatResponse deep-copying additional_properties
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add test for _SHALLOW_COPY_FIELDS and DEFAULT_EXCLUDE independence
Add test_deepcopy_shallow_copy_fields_override_default_exclude to verify
that a field in both DEFAULT_EXCLUDE and _SHALLOW_COPY_FIELDS is
shallow-copied (controlled by _SHALLOW_COPY_FIELDS), while a field in
DEFAULT_EXCLUDE only is still deep-copied. This addresses review comment
#11 ensuring the two class variables control independent concerns.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove unnecessary local variable in __deepcopy__
Inline cls._SHALLOW_COPY_FIELDS directly in the loop check instead of
assigning to a local variable first, per review feedback.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add multi-turn streaming sample and rename multi-turn samples
- Rename 03_multi_turn.py to 03a_multi_turn.py
- Add 03b_multi_turn_streaming.py showing streaming with session history
- The new sample demonstrates calling get_final_response() after
iterating the stream to persist conversation history
- Update READMEs to reflect the new file names
Closes#4447
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Auto-finalize ResponseStream on iteration completion
When a ResponseStream is fully consumed via async iteration,
automatically trigger finalization (finalizer + result hooks).
This ensures session history is persisted in streaming multi-turn
conversations without requiring an explicit get_final_response() call.
- Add auto-finalize call in __anext__ on StopAsyncIteration
- Guard inner stream finalization to prevent double-execution
- Re-check _finalized after iteration in get_final_response()
- Add tests for auto-finalization and streaming session history
- Revert sample file renames from previous commit
Closes#4447
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* README fix
* Fix SIM102 lint: combine nested if statements
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Exclude conversation_id from chat completions options (#4315)
When a session with service_session_id is passed to an agent using the
Chat Completions client, conversation_id leaked through _prepare_options()
into AsyncCompletions.create(), causing an 'unexpected keyword argument'
error. The Responses client already excluded conversation_id but the Chat
Completions client did not.
Added conversation_id to the exclusion set in _prepare_options().
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Remove reproduction report artifact
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix#4305: Handle dict chat_options in _update_conversation_id
_update_conversation_id assumed chat_options had attribute access, but
ChatOptions is a TypedDict (dict). When a dict was passed, setting
.conversation_id raised AttributeError. Now checks isinstance(dict) and
uses key access for dicts, falling back to attribute access for objects.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR feedback: use Mapping ABC and add missing tests (#4305)
- Use collections.abc.Mapping instead of dict for isinstance check in
_update_conversation_id, making it more robust for non-dict mapping types.
- Add test for object-style chat_options with optional options dict parameter.
- Add test verifying existing conversation_id gets overwritten (idempotent).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove unnecessary Mapping check in _update_conversation_id (#4305)
chat_options is always a dict, so the isinstance(chat_opts, Mapping)
check and the else branch for attribute-style access are dead code.
Simplify to direct dict key assignment and remove object-style tests.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Prepare azure-ai-projects 2.0 GA compatibility
Add allow_preview support for internal AIProjectClient creation, keep backward compatibility for renamed SDK model classes, and align Azure AI/core paths and tests for GA validation workflows.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* upgrade to ai-project==2.0.0
* Python: remove azure-ai-projects keyword-guard paths
Assume azure-ai-projects 2.0+ in Azure AI client/provider/responses code paths by removing _supports_keyword_argument gating and related fallback branching.
Also fix pyright typing in FoundryMemoryProvider memory store calls by using ResponseInputItemParam-typed items.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* check fixes
* Python: remove unsupported foundry_features option
Drop foundry_features from Azure AI client and provider surfaces because azure-ai-projects 2.0.0 does not expose that create_version parameter.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: add allow_preview to Foundry memory provider
Propagate allow_preview when FoundryMemoryProvider constructs an AIProjectClient and update tests accordingly.
Also finish wiring allow_preview through AzureAIClient-facing surfaces and related docs.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* aligning docstrings
* udpated lock
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Update github_copilot package for github-copilot-sdk>=0.1.32 (#4549)
- Update requires-python from >=3.10 to >=3.11
- Remove Python 3.10 classifier
- Update mypy python_version to 3.11
- Update dependency to github-copilot-sdk>=0.1.32
- Fix ToolResult API: use snake_case kwargs (text_result_for_llm,
result_type) instead of camelCase (textResultForLlm, resultType)
- Update test assertions to use attribute access on ToolResult
- Add ToolResult type assertions to tool handler tests
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix tests to use ToolInvocation dataclass instead of plain dict (#4549)
Update test_github_copilot_agent.py to pass ToolInvocation objects to tool
handlers instead of plain dicts, matching the github-copilot-sdk>=0.1.32 API
where ToolInvocation is a dataclass with an .arguments attribute.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add regression tests for ToolInvocation contract (#4549)
Add tests to lock in the new ToolInvocation-based calling convention:
- test_tool_handler_rejects_raw_dict_invocation: verifies passing a raw
dict (old calling convention) raises TypeError/AttributeError
- test_tool_handler_with_empty_arguments: verifies ToolInvocation with
empty arguments works correctly for no-arg tools
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Revert requires-python to >=3.10 to avoid breaking CI (#4549)
The repo CI runs with Python 3.10 (uv sync --all-packages) and all other
packages require >=3.10. Raising this package to >=3.11 would break the
shared install flow. The SDK dependency version constraint (>=0.1.32) will
enforce any Python version requirement from the SDK itself.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix min Python version for github_copilot package to >=3.11
github-copilot-sdk>=0.1.32 requires Python>=3.11, which conflicts
with the package's declared >=3.10 minimum, breaking uv sync.
* Bump py version for GH workflows to 3.11, exclude GHCP sdk from 3.10 items
* Fix uv command
* Fixes
* Update samples
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix Python pyright package scoping and typing remediation
Implements issue #4407 by removing the root pyright include, adding package-level pyright includes, and resolving pyright/mypy typing issues across Python packages. Also cleans unnecessary casts and applies line-level, rule-specific ignores where external libraries are too dynamic.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Reduce pyright cost in handoff cloning
Simplify cloned_options construction in HandoffAgentExecutor to avoid expensive TypedDict narrowing/inference in _handoff.py, which was causing pyright to spend a long time in orchestrations.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix types
* Fix lint and type-check regressions
Resolve current Python package check failures across lint, pyright, and mypy after recent code changes, including purview/declarative pyright issues and multiple ruff simplification findings.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fixed hooks
* Stabilize package tests and test tasks
Resolve cross-package non-integration test failures, simplify streaming type flow, harden locale/culture handling, and standardize package test poe tasks to exclude integration tests where applicable.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* lots of small fixes
* Fix current Python test regressions
Address current failing unit tests in azure-ai, bedrock, and azure-cosmos while keeping Bedrock parsing logic inline (no new static helper methods).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* small fixes
* small fixes
* removed pydantic from json
* final updates
* fix core
* fix tests
* fix obser
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Add propagate_session parameter to as_tool() for session sharing
Add opt-in session propagation in agent-as-tool scenarios. When
propagate_session=True, the parent agent's AgentSession is forwarded
to the sub-agent's run() call, allowing both agents to share session
state (history, metadata, session_id).
- Add propagate_session parameter to BaseAgent.as_tool() (default False)
- Include session in additional_function_arguments so it flows to tools
- Add 3 tests for propagation on/off and shared state verification
- Add sample showing session propagation with observability middleware
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Clarify propagate_session docstring per review feedback
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix MCP tools duplicated on second turn when runtime tools are present
When AG-UI's collect_server_tools pre-expands MCP functions on turn 2
(after the MCP server is connected), _prepare_run_context unconditionally
appends them again from self.mcp_tools, duplicating every MCP tool.
Skip MCP functions whose names already exist in the final tool list,
following the same name-based dedup pattern used in _merge_options.
Fixes#4381
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* mypy fix
* Remove issue-specific references from test docstring
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix: Parse oauth_consent_request events in Azure AI client (#3950)
When Azure AI Agent Service returns an oauth_consent_request output item
for OAuth-protected MCP tools, the base OpenAI responses parser drops it
(hits case _ default branch). This causes agent runs to complete silently
with zero content.
Changes:
- Add oauth_consent_request ContentType and Content.from_oauth_consent_request()
factory with consent_link field and user_input_request=True
- Override _parse_response_from_openai and _parse_chunk_from_openai in
RawAzureAIClient to intercept Azure-specific oauth_consent_request items
- Add _emit_oauth_consent helper in AG-UI to emit CustomEvent for frontends
- Add tests proving base parser drops the event and Azure AI override catches it
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* addressed comment
* addressed comments
* addressed comments
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Add OpenTelemetry instrumentation to ClaudeAgent (#4278)
Add inline telemetry to ClaudeAgent.run() so that enable_instrumentation()
emits invoke_agent spans and metrics. Covers both streaming and
non-streaming paths using the same observability helpers as
AgentTelemetryLayer. Adds 5 unit tests for telemetry behavior.
Co-Authored-By: amitmukh <amimukherjee@microsoft.com>
* Address PR review feedback for ClaudeAgent telemetry
- Add justification comment for private observability API imports
- Pass system_instructions to capture_messages for system prompt capture
- Use monkeypatch instead of try/finally for test global state isolation
Co-Authored-By: amitmukh <amitmukh@users.noreply.github.com>
Co-Authored-By: Claude <noreply@anthropic.com>
* Adopt AgentTelemetryLayer instead of inline telemetry
Restructure ClaudeAgent to inherit from AgentTelemetryLayer via a
_ClaudeAgentRunImpl mixin, eliminating duplicated telemetry code and
private API imports.
MRO: ClaudeAgent → AgentTelemetryLayer → _ClaudeAgentRunImpl → BaseAgent
- Remove inline _run_with_telemetry / _run_with_telemetry_stream methods
- Remove private observability helper imports (_capture_messages, etc.)
- Add default_options property mapping system_prompt → instructions
- Net -105 lines by reusing core telemetry layer
Co-Authored-By: amitmukh <amitmukh@users.noreply.github.com>
Co-Authored-By: Claude <noreply@anthropic.com>
* Fix mypy: align _ClaudeAgentRunImpl.run() signature with AgentTelemetryLayer.run()
Remove explicit `options` parameter from mixin's run() signature and
extract it from **kwargs to match AgentTelemetryLayer's signature.
Also align overload return types (ResponseStream, Awaitable) to match.
Co-Authored-By: Claude <noreply@anthropic.com>
* Introduce RawClaudeAgent following framework's RawAgent/Agent pattern
Replace private _ClaudeAgentRunImpl mixin with public RawClaudeAgent
class that contains all core logic (init, run, lifecycle, tools).
ClaudeAgent becomes a thin wrapper that adds AgentTelemetryLayer.
- RawClaudeAgent(BaseAgent): full implementation without telemetry
- ClaudeAgent(AgentTelemetryLayer, RawClaudeAgent): adds OTel tracing
- Export RawClaudeAgent from package __init__.py
Users who want to skip telemetry or provide their own can use
RawClaudeAgent directly.
Co-Authored-By: Claude <noreply@anthropic.com>
* Address review nits: trim RawClaudeAgent docstring, fix import paths
- Simplify RawClaudeAgent docstring to a single basic example (not the
primary entry point for most users)
- Use agent_framework.anthropic import path in docstrings instead of
direct agent_framework_claude path
- Add RawClaudeAgent to agent_framework.anthropic lazy re-exports
Co-Authored-By: Claude <noreply@anthropic.com>
---------
Co-authored-by: Amit Mukherjee <amimukherjee@microsoft.com>
Co-authored-by: amitmukh <amitmukh@users.noreply.github.com>
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
* Added shell tool
* Fixed CI error
* Add ShellTool support for OpenAI and Anthropic providers
- Add shell_tool_call, shell_tool_result, and shell_command_output content types
- Add ShellTool class and shell_tool decorator to core
- Add get_hosted_shell_tool() to OpenAI Responses client
- Handle shell_call and shell_call_output parsing in OpenAI (sync and streaming)
- Map ShellTool to Anthropic bash tool API format
- Parse bash_code_execution_tool_result as shell_tool_result in Anthropic
- Add unit tests for all new functionality
- Add sample scripts for hosted and local shell execution
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Addressed comments
* Reverted ruff change
* Fixed tests
* Addressed comments
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix IndexError when reasoning models return no text content (#4384)
In _prepare_message_for_openai(), the text_reasoning case unconditionally
accessed all_messages[-1] to attach reasoning_details. When a reasoning
model (e.g. gpt-5-mini) returns reasoning_details without text content,
all_messages is empty, causing an IndexError.
Guard the access by initializing all_messages with the current args dict
when it is empty, so reasoning_details can be safely attached.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review: buffer reasoning details for valid message payloads (#4384)
- Buffer pending reasoning details and attach to the next message with
content/tool_calls, avoiding standalone reasoning-only messages.
- When reasoning is the only content, emit a message with empty content
to satisfy Chat Completions schema requirements.
- Strengthen test assertions to verify text+reasoning co-location and
that all messages with reasoning_details also have content or tool_calls.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix text_reasoning handling: always buffer and tighten tests (#4384)
- Always buffer reasoning into pending_reasoning instead of conditionally
attaching to the previous message via fragile all_messages emptiness check
- Attach buffered reasoning to last message at end-of-loop when no subsequent
content consumed it
- Assert exact content values (content == '' not in ('', None))
- Assert exact list lengths (== 1 not >= 1) for stronger regression guards
- Add test for reasoning before FunctionCallContent
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: handle thread.message.completed event in Assistants API streaming
Previously, `thread.message.completed` events fell through to the
catch-all `else` branch and yielded empty `ChatResponseUpdate` objects,
silently discarding fully-resolved annotation data (file citations,
file paths, and their character-offset regions).
This commit adds a dedicated handler for `thread.message.completed`
that:
- Walks the completed ThreadMessage.content array
- Extracts text blocks with their fully-resolved annotations
- Maps FileCitationAnnotation and FilePathAnnotation to the
framework's Annotation type with proper TextSpanRegion data
- Yields a ChatResponseUpdate containing the complete text and
annotations
Fixes#4322
* test: add tests for thread.message.completed annotation handling
Tests cover:
- File citation annotation extraction
- File path annotation extraction
- Multiple annotations on a single text block
- Text-only messages (no annotations)
- Non-text blocks are skipped
- Mixed content blocks (text + image)
- Conversation ID propagation
* fix: address Copilot review - add quote field and log unrecognized annotations
- Include `quote` from `annotation.file_citation.quote` in
`additional_properties` for FileCitationAnnotation, preserving the
exact cited text snippet from the source file
- Add `else` clause to log unrecognized annotation types at debug level,
consistent with the pattern in `_responses_client.py`
- Add `import logging` and module-level logger
* test: add coverage for quote field and unrecognized annotation logging
- test_message_completed_with_file_citation_quote: verifies quote is
included in additional_properties
- test_message_completed_with_file_citation_no_quote: verifies quote
is omitted when None
- test_message_completed_unrecognized_annotation_logged: verifies
unknown annotation types are logged at debug level and skipped
* fix: address reviewer nits — logger name convention + annotation type string
Per @giles17's review:
- Use logging.getLogger('agent_framework.openai') to match module convention
- Simplify debug message to use annotation.type instead of type().__name__
* refactor: move message.completed tests into consolidated test file
Per @giles17's review: moved all tests from test_assistants_message_completed.py
into test_openai_assistants_client.py and deleted the standalone file.
* fix: resolve mypy no-redef and ruff RET504 lint errors
- Remove duplicate type annotation for 'ann' variable (no-redef)
- Return directly from fixture instead of unnecessary assignment (RET504)
* fix: rename annotation variable in completed block to fix mypy type conflict
The 'annotation' loop variable in thread.message.completed has type
FileCitationAnnotation | FilePathAnnotation, which conflicts with the
delta block's 'annotation' of type FileCitationDeltaAnnotation |
FilePathDeltaAnnotation. Renamed to 'completed_annotation' to avoid
mypy 'Incompatible types in assignment' error.
* fix: remove quote field from FileCitationAnnotation handling
---------
Co-authored-by: Giles Odigwe <79032838+giles17@users.noreply.github.com>
* Fix walrus operator precedence for model_id in AzureOpenAIResponsesClient (#4299)
Add parentheses around the walrus assignment so model_id receives the
actual string value instead of the boolean result of
`kwargs.pop(...) and not deployment_name`.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review: replace walrus with explicit None check, add edge-case tests (#4299)
- Replace walrus operator with explicit assignment and 'is not None'
check to avoid boolean-coercion pitfalls (empty string now correctly
surfaces as ValueError instead of silently falling back)
- Add test: deployment_name takes precedence over model_id kwarg
- Add test: model_id='' raises ValueError
- Add test: model_id=None falls back to env var
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add explicit validation for empty model_id in AzureOpenAIResponsesClient
Reject empty or whitespace-only model_id with ValueError instead of
silently passing an empty deployment name downstream. This ensures the
test_init_model_id_kwarg_empty_string test correctly validates behavior
defined in production code rather than relying on downstream validation.
Addresses PR review feedback for #4299.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Simplify model_id handling using walrus operator
Addresses review comment on PR #4310.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Restore explicit model_id validation to fix test failures (#4299)
The walrus operator refactor silently dropped the empty-string validation,
causing test_init_model_id_kwarg_empty_string to fail. Restore the explicit
None check and ValueError raise for empty model_id.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Revert "Restore explicit model_id validation to fix test failures (#4299)"
This reverts commit 1d2965fff6.
* Revert to walrus operator fix per review feedback
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Fix Executor handler type checking with __future__ annotations (#3898)
Use typing.get_type_hints() in _validate_handler_signature to resolve
string annotations from `from __future__ import annotations`. This
mirrors the fix applied to FunctionExecutor in #2308.
When __future__ annotations are enabled, type annotations are stored as
strings. The handler decorator was passing these strings directly to
validate_workflow_context_annotation, which uses typing.get_origin and
returns None for strings, causing a ValueError.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review feedback for #3898: improve error handling and test coverage
- Wrap typing.get_type_hints() in try/except to provide a descriptive
ValueError mentioning the handler name when annotations cannot be resolved
- Strengthen bare context test to assert output_types and workflow_output_types
- Add test for @handler(input=..., output=...) with future annotations
covering the skip_message_annotation branch
- Add test for union-type context annotations with future annotations
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Narrow exception catch and add test for unresolvable annotations (#3898)
- Narrow except clause from bare Exception to (NameError, AttributeError,
TypeError) to avoid masking unexpected errors.
- Add test_handler_unresolvable_annotation_raises to verify that a handler
with a forward-reference to a non-existent type raises ValueError with
the expected message.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix#3898: fall back to raw annotations when get_type_hints fails
When typing.get_type_hints(func) raises NameError (unresolvable forward
ref), AttributeError, RecursionError, or any other exception, fall back
to the raw parameter annotations instead of raising a ValueError.
This matches the suggestion from @moonbox3 on PR #4317.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix test to match new fallback behavior when get_type_hints fails (#3898)
The code now falls back to raw string annotations instead of raising
'Failed to resolve type annotations'. A ValueError is still raised when
the raw string ctx annotation is not a valid WorkflowContext type, so
update the test to match on ValueError without checking the message.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pyupgrade: remove unnecessary string annotation quote
* Add noqa for intentionally undefined name in annotation test
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix _merge_options dropping dict-defined tools (#4303)
_merge_options used getattr(tool, 'name', None) to de-duplicate tools,
which returns None for dict-style tool definitions. This caused all
override dict tools to be treated as duplicates of each other and of any
base dict tools, silently dropping them.
Add _get_tool_name() helper that extracts the name from both object-style
tools (via .name attribute) and dict-style tools (via tool['function']['name']).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review: fix None dedup bug and add comprehensive tests (#4303)
- Exclude None from existing_names set so nameless/malformed tools are
not silently deduplicated against each other
- Add test for cross-type dedup (dict tool + object tool with same name)
- Add test verifying nameless tools are preserved (not falsely deduped)
- Add unit tests for _get_tool_name edge cases: missing function key,
non-dict function value, missing name, no name attribute, non-dict
inputs, and valid dict/object tools
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix OpenAIResponsesClient mishandling single-tool inputs (#4304)
Use normalize_tools() in _prepare_tools_for_openai to wrap single tools
(FunctionTool or dict) in a list before iteration, consistent with the
chat client implementation.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review feedback for #4304
- Use precise type annotation matching normalize_tools/OpenAIChatClient signature
instead of collapsed Sequence[Any] | Any | None
- Move emptiness guard after normalize_tools() call so single falsy tool
objects are not silently swallowed
- Import ToolTypes for the type annotation
- Expand test_prepare_tools_for_openai_single_function_tool assertions to
verify parameters, strict, and parameter schema fields
- Add test_prepare_tools_for_openai_none to verify None input returns []
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Tao ChenandGitHub
Evan MattsonandGitHub
Dmytro StrukandGitHub
