* Fix GitHubCopilotAgent not calling context provider hooks (#3984)
GitHubCopilotAgent accepted context_providers in its constructor but
never called before_run()/after_run() on them in _run_impl() or
_stream_updates(), silently ignoring all context providers.
Add _run_before_providers() helper to create SessionContext and invoke
before_run on each provider. Both _run_impl() and _stream_updates() now
run the full provider lifecycle: before_run before sending the prompt
(with provider instructions prepended) and after_run after receiving the
response. This follows the same pattern used by A2AAgent.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Fix GitHubCopilotAgent to invoke context provider before_run/after_run hooks
Fixes#3984
* fix(#3984): address review feedback for context provider integration
- Build prompt from session_context.get_messages(include_input=True) so
provider-injected context_messages are included in both non-streaming
and streaming paths (review comments #1, #2)
- Preserve timeout in opts (use get instead of pop) so providers can
observe it via context.options (review comment #3)
- Eliminate streaming double-buffer: move after_run invocation to a
ResponseStream result_hook (matching Agent class pattern) instead of
maintaining a separate updates list in the generator (review comment #4)
- Improve _run_before_providers docstring
Add tests for:
- Context messages included in prompt (non-streaming + streaming)
- Error path: after_run NOT called when send_and_wait/streaming raises
- Multiple providers: forward before_run, reverse after_run ordering
- BaseHistoryProvider with load_messages=False is skipped
- Streaming after_run response contains aggregated updates
- Streaming with no updates still sets empty response
- Timeout preserved in session context options for providers
Note: _run_before_providers remains on GitHubCopilotAgent for now. A
follow-up PR should extract it to BaseAgent so subclasses can reuse it
without duplicating the provider iteration logic.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #3984: Python: [Bug]: GitHubCopilotAgent Memory Example
* refactor(#3984): promote _run_before_providers to BaseAgent
Move _run_before_providers from GitHubCopilotAgent into BaseAgent,
mirroring the existing _run_after_providers helper. Agent's
_prepare_session_and_messages now delegates to the shared base method,
eliminating the near-duplicate provider iteration logic that could
drift as the provider contract evolves.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #3984: Python: [Bug]: GitHubCopilotAgent Memory Example
* revert: keep _run_before_providers in GitHubCopilotAgent only
Undo the promotion of _run_before_providers to BaseAgent. The method
stays in GitHubCopilotAgent where it is needed, and _agents.py
retains its original inline provider iteration in RawAgent.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: replace deprecated BaseContextProvider/BaseHistoryProvider with ContextProvider/HistoryProvider
Update imports and usages in GitHubCopilotAgent and its tests to use
the new non-deprecated class names from the core package.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: address review feedback - reorder providers before session, wrap streaming after_run in try/except, assert after_run on skipped HistoryProvider
- Move _run_before_providers before _get_or_create_session so provider
contributions can affect session configuration
- Wrap _run_after_providers in try/except in streaming _after_run_hook
to prevent provider errors from replacing successful responses
- Add after_run assertion to test_history_provider_skip_when_load_messages_false
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>
Add deduplication to `prepend_instructions_to_messages()` to skip
instructions that are already present as leading messages with the
same role and text. This prevents duplicate system messages when
instructions are injected by multiple layers (e.g. Agent + chat client).
Fixes#5049
* Python: Fix broken samples and add missing READMEs
- simple_context_provider: move instructions kwarg into options dict
- suspend_resume_session: use OpenAIChatCompletionClient for in-memory demo
- foundry_chat_client_with_hosted_mcp: move store kwarg into options dict
- Add README.md for context_providers and conversations sample folders
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Fix additional sample issues in context_providers
- mem0_basic: send preferences query before sleep so Mem0 can learn them,
print result from new session recall
- mem0_sessions: add session for multi-turn conversation in agent-scoped
example, remove user_id from agent-scoped provider (Mem0 API stores
memories without user_id when agent_id is provided), use single message
for storing preferences
- redis_basics: print retrieved context messages instead of raw object
- redis_sessions: add missing load_dotenv() call
- redis_basics/redis_sessions: fix docstrings referencing wrong client type
- azure_redis_conversation: replace duplicate copyright with load_dotenv()
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Fix broken link in declarative README
openai_responses_agent.py was renamed to openai_agent.py
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Refactor Anthropic model option and provider clients
Rename the Anthropic client model option from model_id to model, add provider-specific Anthropic wrappers for Foundry, Bedrock, and Vertex, and expose them through the Anthropic, Foundry, Amazon, and Google namespaces. Update core option handling, docs, samples, and tests accordingly.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix Anthropic skills sample typing
Cast the Anthropic beta client to Any in the skills sample so the pre-commit sample pyright check no longer fails on beta skills and files endpoints that are not exposed by the current SDK stubs.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* undo sample mypy
* Retry CI after transient external failures
Retrigger PR validation after an unrelated Copilot review workflow SAML failure and a transient external tau2 git fetch failure in the Windows Python test setup.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback on model option merging
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address Anthropic compatibility review feedback
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* moved all to `model`
* fixes for azure ai search
* Python: standardize remaining sample env var names
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: fix foundry-local pyright compatibility
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated env vars in cicd
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Eduard van Valkenburg
·
2026-04-01 19:00:18 +00:00
* Fix agent_with_hosted_mcp sample to use AzureOpenAIResponsesClient (#4861)
The agent_with_hosted_mcp sample used AzureOpenAIChatClient with an MCP tool
dict, but the Chat Completions API only supports 'function' and 'custom' tool
types, not 'mcp'. This caused a 400 error at runtime.
Switch the sample to AzureOpenAIResponsesClient which natively supports MCP
tools via the Responses API. Use get_mcp_tool() to construct the tool config.
Changes:
- main.py: Replace AzureOpenAIChatClient with AzureOpenAIResponsesClient
- requirements.txt: Update azure-ai-agentserver-agentframework to 1.0.0b16
and use agent-framework-azure-ai package
- agent.yaml: Use AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME env var
- Add regression test documenting chat client MCP tool passthrough behavior
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Fix agent_with_hosted_mcp sample to use Responses API client for MCP tools
Fixes#4861
* Remove REPRODUCTION_REPORT.md investigation artifact (#4861)
Remove the reproduction report markdown file from the test directory.
Investigation notes belong in the GitHub issue or PR description,
not as committed files in the source tree. The regression test in
test_openai_chat_client.py already provides automated verification.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add MCP tool API rejection regression test (#4861)
Add test_mcp_tool_dict_causes_api_rejection to verify that MCP tool
dicts passed through to the Chat Completions API result in a clear
ChatClientException rather than being silently dropped. This completes
the regression test coverage requested in code review.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* small fix
* Revert deletion of dotnet local.settings.json files
Restore the two local.settings.json files that were accidentally deleted in this PR.
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 _add_text_reasoning_content dropping id during coalescing (#4852)
Preserve the id field (rs_* identifier) when coalescing text_reasoning
Content objects by passing id=self.id or other.id to the Content
constructor. This fixes the encrypted reasoning round-trip where the
missing id prevented _prepare_content_for_openai from including it in
the serialized reasoning item.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Fix `_add_text_reasoning_content` to preserve `id` during coalescing
Fixes#4852
* Raise AdditionItemMismatch on conflicting text_reasoning ids (#4852)
Detect when both operands have different non-empty ids during
text_reasoning Content coalescing and raise AdditionItemMismatch
instead of silently keeping one. This prevents mis-associating
encrypted_content during round-trips.
Also adds tests for conflicting ids and the neither-has-id edge case.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4852: Python: [Bug]: Content._add_text_reasoning_content drops id during coalescing, breaking encrypted reasoning round-trip
* test fix
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Remove unsupported memory scoping params from samples and docs
Fixes#4353
The `Mem0ContextProvider` and `RedisContextProvider` no longer support
`thread_id` or `scope_to_per_operation_thread_id` parameters. This commit
updates the affected samples and READMEs to use only the currently
supported API (`user_id`, `agent_id`, `application_id`).
Changes:
- mem0_sessions.py: Remove `thread_id` and
`scope_to_per_operation_thread_id` from examples 1 and 2, rewrite to
demonstrate user-scoped and agent-scoped memory patterns
- redis_sessions.py: Update module docstring to remove references to
removed thread scoping params
- mem0/README.md: Update Memory Scoping docs to reflect current API
- redis/README.md: Remove `thread_id` and
`scope_to_per_operation_thread_id` references from docs
* Address Copilot review: rename thread_scope functions, fix docstring
- Rename `example_global_thread_scope` -> `example_global_memory_scope`
- Rename `example_per_operation_thread_scope` -> `example_agent_scoped_memory`
- Update example 2 docstring to mention `application_id` alongside
`user_id` and `agent_id` since it's set in the provider config
- Update module docstring scenario 2 to include `application_id`
* fix: rebase onto main, address giles17 review feedback
- Resolve merge conflicts by rebasing all 4 original files onto current main
- Address giles17's agent review suggestions:
- mem0_basic.py: update comment to remove thread_id from scoping list
- mem0_oss.py: update comment to remove thread_id from scoping list
- redis_sessions.py: rename Example 2 from "Agent-Scoped Memory" to
"Hybrid Vector Search" to accurately describe what it demonstrates
- redis/README.md: update Example 2 description to match renamed example
---------
Co-authored-by: Tao Chen <taochen@microsoft.com>
Co-authored-by: Giles Odigwe <79032838+giles17@users.noreply.github.com>
* Add Python A2A agent-as-function-tools sample
Port of the .NET A2AAgent_AsFunctionTools sample to Python.
Resolves a remote A2A agent card, converts each skill to a
FunctionTool via as_tool(), and registers them with a host agent
using AzureOpenAIResponsesClient.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Sanitize A2A skill names before passing to as_tool()
as_tool() only auto-sanitizes when name is omitted. Since we pass
skill.name explicitly, we need to strip special characters ourselves.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Add header_provider to MCPStreamableHTTPTool (#4808)
Add a header_provider callback parameter to MCPStreamableHTTPTool that
enables injecting dynamic per-request HTTP headers from runtime kwargs
(originating from FunctionInvocationContext.kwargs set in agent middleware).
The implementation uses contextvars and httpx event hooks to ensure headers
are task-local and safe for concurrent tool calls:
- header_provider receives the runtime kwargs dict and returns headers
- call_tool sets a ContextVar before delegating to MCPTool.call_tool
- An httpx request event hook reads from the ContextVar and injects headers
Example usage:
mcp_tool = MCPStreamableHTTPTool(
name="web-api",
url="https://api.example.com/mcp",
header_provider=lambda kwargs: {
"X-Auth-Token": kwargs.get("auth_token", ""),
},
)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4808: Python: [Bug]: Unable to pass AgentContext to MCPStreamableHTTPTool
* Add test for header_provider via FunctionTool.invoke with FunctionInvocationContext
Addresses PR review comment: exercises the full pipeline from
FunctionInvocationContext.kwargs through FunctionTool.invoke to
MCPStreamableHTTPTool.call_tool and header_provider, rather than
testing call_tool in isolation.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4808: review comment fixes
* Fix streamable MCP transport defaults
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix Azure AI test client mocks
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix MCP runtime kwarg regressions
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Stabilize MCP tool runtime kwargs
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Use context kwargs in MCP wrappers
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated mcp samples
* fix link
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Eduard van Valkenburg
·
2026-03-31 17:23:49 +00:00
* Fix sample bugs: incorrect API params, wrong client types, and invalid options
- typed_options.py: Fix AnthropicClient model->model_id, wrap raw strings in Message objects for get_response(), fix reasoning_effort->reasoning dict, fix budget_tokens minimum (1024), use OpenAIChatClient not FoundryChatClient, remove unused import
- client_reasoning.py: Fix deprecated model_id to model param
- client_with_hosted_mcp.py: Remove invalid store=True kwarg from Agent.run()
- code_defined_skill.py: Fix precision kwarg to use function_invocation_kwargs
- Various other samples: Fix deprecated API usage and incorrect params
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review comments
- client_with_hosted_mcp.py: Fix remaining store=True kwarg on line 68 to use options dict
- client_with_session.py: Change store=True to store=False to match in-memory persistence demo intent
- typed_options.py: Remove non-existent import and model key from docstring example
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* new sample fixes
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Foundry Evals integration for Python
Merged and refactored eval module per Eduard's PR review:
- Merge _eval.py + _local_eval.py into single _evaluation.py
- Convert EvalItem from dataclass to regular class
- Rename to_dict() to to_eval_data()
- Convert _AgentEvalData to TypedDict
- Simplify check system: unified async pattern with isawaitable
- Parallelize checks and evaluators with asyncio.gather
- Add all/any mode to tool_called_check
- Fix bool(passed) truthy bug in _coerce_result
- Remove deprecated function_evaluator/async_function_evaluator aliases
- Remove _MinimalAgent, tighten evaluate_agent signature
- Set self.name in __init__ (LocalEvaluator, FoundryEvals)
- Limit FoundryEvals to AsyncOpenAI only
- Type project_client as AIProjectClient
- Remove NotImplementedError continuous eval code
- Add evaluation samples in 02-agents/ and 03-workflows/
- Update all imports and tests (167 passing)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: resolve mypy redundant-cast errors while keeping pyright happy
Use cast(list[Any], x) with type: ignore[redundant-cast] comments to
satisfy both mypy (which considers casting Any redundant) and pyright
strict mode (which needs explicit casts to narrow Unknown types).
Also fix evaluator decorator check_name type annotation to be
explicitly str, resolving mypy str|Any|None mismatch.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: CI failures — pyupgrade, evaluator overloads, sample API, reset attr
- Apply pyupgrade: Sequence from collections.abc, remove forward-ref quotes
- Add @overload signatures to evaluator() for proper @evaluator usage
- Fix evaluate_workflow sample to use WorkflowBuilder(start_executor=) API
- Fix _workflow.py executor.reset() to use getattr pattern for pyright
- Remove unused EvalResults forward-ref string in default_factory lambda
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: skip gRPC-dependent observability test
The test_configure_otel_providers_with_env_file_and_vs_code_port test
triggers gRPC OTLP exporter creation, but the grpc dependency is
optional and not installed by default. Add skipif decorator matching
the pattern used by all other gRPC exporter tests in the same file.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: add nosec B101 for bandit assert check
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* style: align eval samples with repo conventions
- Move module docstrings before imports (after copyright header)
- Add -> None return type to all main() and helper functions
- Fix line-too-long in multiturn sample conversation data
- Add Workflow import for typed return in all_patterns_sample
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review feedback: async fixes, sample bugs, deprecation warnings
- Simplify _ensure_async_result to direct await (async-only clients)
- Replace get_event_loop() with get_running_loop()
- Narrow _fetch_output_items exception handling to specific types
- Add warning log when _filter_tool_evaluators falls back to defaults
- Add DeprecationWarning to options alias in Agent.__init__
- Add DeprecationWarning to evaluate_response()
- Rename raw key to _raw_arguments in convert_message fallback
- Fix evaluate_agent_sample.py: replace evals.select() with FoundryEvals()
- Fix evaluate_multiturn_sample.py: use Message/Content/FunctionTool types
- Fix evaluate_workflow_sample.py: replace evals.select() with FoundryEvals()
- Update test mocks to use AsyncMock for awaited API calls
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add test coverage for review feedback items
- Add num_repetitions=2 positive test verifying 2×items and 4 agent calls
- Add _poll_eval_run tests: timeout, failed, and canceled paths
- Add evaluate_traces tests: validation error, response_ids path, trace_ids path
- Add evaluate_foundry_target happy-path test with target/query verification
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix ruff ISC004 lint error and apply formatter
- Wrap implicit string concatenation in parens in evaluate_multiturn_sample.py
- Apply ruff formatter to 6 other files with minor formatting drift
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove core type changes (extracted to fix/workflow-stale-session branch)
Reverts changes to _agents.py, _agent_executor.py, and _workflow.py
back to upstream/main. These fixes are now in a separate PR.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review round 2: bugs, tests, and architecture
Code fixes:
- Fix _normalize_queries inverted condition (single query now replicates
to match expected_count)
- Fix substring match bug: 'end' in 'backend' matched; use exact set
lookup for executor ID filtering
- Fix used_available_tools sample: tool_definitions→tools param, use
FunctionTool attribute access instead of dict .get()
- Add None-check in _resolve_openai_client for misconfigured project
- Add Returns section to evaluate_workflow docstring
- Cache inspect.signature in @evaluator wrapper (avoid per-item reflection)
Architecture:
- Extract _evaluate_via_responses as module-level helper; evaluate_traces
now calls it directly instead of creating a FoundryEvals instance
- Move Foundry-specific typed-content conversion out of core to_eval_data;
core now returns plain role/content dicts, FoundryEvals applies
AgentEvalConverter in _evaluate_via_dataset
Tests:
- evaluate_response() deprecation warning emission and delegation
- num_repetitions > 1 with expected_output and expected_tool_calls
- Mock output_items.list in test_evaluate_calls_evals_api
- Update to_eval_data assertions for plain-dict format
- Unknown param error now raised at @evaluator decoration time
Skipped (separate PR): executor reset loop, xfail removal, options alias
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix CI: revert test_full_conversation, fix pyright errors
- Revert test_full_conversation.py to upstream/main (the session
preservation test was incorrectly changed to assert clearing)
- Fix pyright reportUnnecessaryComparison on get_openai_client() None
check by adding ignore comment
- Fix pyright reportPrivateUsage: add public EvalItem.split_messages()
method and use it in FoundryEvals._evaluate_via_dataset instead of
accessing private _split_conversation
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review round 3: reliability, test gaps, cleanup
- Add try/except guard for non-numeric score in _coerce_result
- Add poll_interval minimum bound (0.1s) to prevent tight loops
- Add runtime async client check in _resolve_openai_client
- Remove _ensure_async_result wrapper (10 call sites → direct await)
- Better error message when queries provided without agent
- Import-time asserts for evaluator set consistency
- Remove 28 redundant @pytest.mark.asyncio decorators
- Add doc note about _raw_arguments sensitive data
- Tests: tool_called_check mode=any, _normalize_queries branches,
_extract_result_counts paths, _extract_per_evaluator, bare check
via evaluate_agent, output_items assertion, modulo wrapping,
async client check, queries-without-agent error
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix CI: ruff S101 assert, pyright and mypy arg-type errors
- Replace module-level assert with if/raise for evaluator set
consistency checks (ruff S101 disallows bare assert)
- Add type: ignore[arg-type] and pyright: ignore[reportArgumentType]
on OpenAI SDK evals API calls that pass dicts where typed params
are expected (SDK accepts dicts at runtime)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review round 4: bugs, reliability, test fixes
- Fix all_passed ignoring parent result_counts when sub_results present
- Fix _extract_tool_calls: parse string arguments via json.loads before
falling back to None (real LLM responses use string arguments)
- Sanitize _raw_arguments to '[unparseable]' to avoid leaking sensitive
tool-call data to external evaluation services
- Add NOTE comment on to_eval_data message serialization dropping
non-text content (tool calls, results)
- Eliminate double conversation split in _evaluate_via_dataset: build
JSONL dicts directly from split_messages + AgentEvalConverter
- Raise poll_interval floor from 0.1s to 1.0s to prevent rate-limit
exhaustion
- Fix MagicMock(name=...) bug in test: sets display name not .name attr
- Fix mock_output_item.sample: use MagicMock object instead of dict so
_fetch_output_items exercises error/usage/input/output extraction
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review round 5: reliability, docs, test coverage
Code fixes:
- Move import-time RuntimeError checks to unit tests (avoids breaking
imports for all users on developer set-drift mistake)
- _filter_tool_evaluators now raises ValueError when all evaluators
require tools but no items have tools (was silently substituting)
- Add poll_interval upper bound (60s) to prevent single-iteration sleep
- Log exc_info=True in _fetch_output_items for debugging API changes
- Fix evaluate() docstring: remove claim about Responses API optimization
- Validate target dict has 'type' key in evaluate_foundry_target
- Document to_eval_data() limitation: non-text content is omitted
Tests:
- TestEvaluatorSetConsistency: verify _AGENT/_TOOL subsets of _BUILTIN
- TestEvaluateTracesAgentId: agent_id-only path with lookback_hours
- TestFilterToolEvaluatorsRaises: ValueError on all-tool no-items
- TestEvaluateFoundryTargetValidation: target without 'type' key
- Assert items==[] on failed/canceled poll results
- Mock output_items.list in response_ids test for full flow
- TestAllPassedSubResults: result_counts=None + sub_results delegation
and parent failures override sub_results
- TestBuildOverallItemEmpty: empty workflow outputs returns None
Skipped r5-07 (_raw_arguments length hint): marginal debugging value,
could leak content size information.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix error message: evaluate_responses() → evaluate_traces(response_ids=...)
The referenced function doesn't exist; the correct API is
evaluate_traces(response_ids=...) from the azure-ai package.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove dead to_eval_data() method, fix docstring claims
- Remove to_eval_data() from EvalItem (dead code after r4-05 JSONL refactor)
- Migrate 15 tests from to_eval_data() to split_messages()
- Update sample to use split_messages() + Message properties
- Remove unimplemented Responses API optimization docstring claim
- Update split_messages() docstring to not reference removed method
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Reduce default eval timeout from 600s to 180s (3 minutes)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove dead _evaluate_via_responses method from FoundryEvals
The method was never called — evaluate() uses _evaluate_via_dataset,
and evaluate_traces() calls _evaluate_via_responses_impl directly.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Revert unrelated formatting changes to get-started samples
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix pyright: remove phantom FoundryMemoryProvider import, apply ruff format
- Remove import of non-existent _foundry_memory_provider module
(incorrectly kept during rebase conflict resolution)
- Apply ruff formatter to test_local_eval.py and get-started samples
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix eval samples: use FoundryChatClient for Agent()
The upstream provider-leading client refactor (#4818) made client=
a required parameter on Agent(). Update the three getting-started
eval samples to use FoundryChatClient with FOUNDRY_PROJECT_ENDPOINT,
matching the standard pattern from 01-get-started samples.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Simplify self-reflection sample using FoundryEvals
Replace ~80 lines of manual OpenAI evals API code (create_eval,
run_eval, manual polling, raw JSONL params) with FoundryEvals:
- evaluate_groundedness() uses FoundryEvals.evaluate() with EvalItem
- Remove create_openai_client(), create_eval(), run_eval() functions
- Remove openai SDK type imports (DataSourceConfigCustom, etc.)
- run_self_reflection_batch creates FoundryEvals instance once,
reuses it for all iterations across all prompts
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Update eval samples to FoundryChatClient and FOUNDRY_PROJECT_ENDPOINT
- Migrate all foundry_evals samples from AzureOpenAIResponsesClient to FoundryChatClient
- Update env var from AZURE_AI_PROJECT_ENDPOINT to FOUNDRY_PROJECT_ENDPOINT
- Use AzureCliCredential consistently across all samples
- Fix README.md: correct function names (evaluate_dataset -> FoundryEvals.evaluate, evaluate_responses -> evaluate_traces)
- Update self_reflection .env.example and README.md
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix lint errors in eval samples (E501, ASYNC240, formatting)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove evaluate_all_patterns_sample.py (redundant with focused samples)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix async credential mismatch: use azure.identity.aio for async AIProjectClient
AIProjectClient from azure.ai.projects.aio requires an async credential.
Switch all foundry_evals samples from azure.identity.AzureCliCredential
to azure.identity.aio.AzureCliCredential. Also pass project_client to
FoundryChatClient instead of duplicating endpoint+credential.
Close credential in self_reflection sample to avoid resource leak.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Revert test_observability.py to upstream/main (not our test)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address moonbox3 review: sphinx docstrings, pagination, isinstance check
- Convert all Example:: / Typical usage:: code blocks to .. code-block:: python
format matching codebase convention (both _evaluation.py and _foundry_evals.py)
- Add async pagination in _fetch_output_items via async for (handles large result sets)
- Replace hasattr(__aenter__) with isinstance(client, AsyncOpenAI) in _resolve_openai_client
- Move AsyncOpenAI import from TYPE_CHECKING to runtime (needed for isinstance)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix test failures and address remaining moonbox3 review comments
- Fix tests: use MagicMock(spec=AsyncOpenAI) for project_client mocks
(isinstance check now requires proper type, not duck-typing)
- Fix tests: replace mock_page.__iter__ with _AsyncPage helper for async for
- Fix evaluate_response: auto-extract queries from response messages when
query is not provided (previously always raised ValueError)
- Add debug logging when skipping internal _-prefixed executor IDs
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address Tao's PR review comments on Foundry Evals
- T1: Add comment explaining builtin.* pass-through in _resolve_evaluator
- T2: Add comment referencing OpenAI evals API for testing_criteria dict
- T3: Document Mustache-style {{item.*}} template placeholders
- T4: Document poll loop 60s sleep upper bound rationale
- T5: Narrow run type to RunRetrieveResponse, use typed field access
instead of vars()/getattr dance in _extract_result_counts and
_extract_per_evaluator; use run.error and run.report_url directly
- T6: Clarify openai_client docstring re: Azure Foundry endpoint
- T8: Remove misleading empty expected_tool_calls from sample
- Update tests to match real SDK PerTestingCriteriaResult shape
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove unnecessary Any union from run type annotations
RunRetrieveResponse is the correct type — no backward compat needed
for a brand new feature.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Accept FoundryChatClient instead of raw AsyncOpenAI
FoundryEvals now takes client: FoundryChatClient as its primary
parameter instead of openai_client: AsyncOpenAI. The builtin.*
evaluators require a Foundry endpoint, so the type should reflect that.
- FoundryEvals.__init__: client: FoundryChatClient replaces openai_client
- evaluate_traces / evaluate_foundry_target: same change
- _resolve_openai_client: extracts .client from FoundryChatClient
- project_client fallback retained for standalone functions
- All samples updated to construct FoundryChatClient and pass as client=
- Tests updated (openai_client= → client=)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove implicit 60s upper bound on poll interval
If a developer sets a higher poll_interval, respect it. Only clamp
to remaining time and enforce a 1s minimum for rate-limit protection.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove 1s floor on poll interval — let the developer control it
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Update python/samples/05-end-to-end/evaluation/foundry_evals/.env.example
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
* Update python/samples/02-agents/evaluation/evaluate_agent.py
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
* Address eavanvalkenburg review (round 2) on Python eval PR
- Rename model_deployment -> model across FoundryEvals and all samples
- Make model param optional, resolves from client.model
- Convert EvalResults from dataclass to regular class
- Remove deprecated evaluate_response() function
- Refactor splitters: BUILT_IN_SPLITTERS dict + standalone functions
- Change per_turn_items from classmethod to staticmethod
- Simplify EvalCheck type alias to use Awaitable[CheckResult]
- Remove errored property from EvalResults
- Remove default value from Evaluator protocol eval_name
- Rename assert_passed -> raise_for_status, add EvalNotPassedError
- Type agent param as SupportsAgentRun | None
- Fix Arguments docstring
- Update __init__.py exports
- Update all tests and samples
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Move FoundryEvals to foundry package, split tool eval sample
- Move _foundry_evals.py from azure-ai to foundry package
- Move test_foundry_evals.py to foundry/tests/
- Update lazy re-exports in agent_framework.foundry namespace
- Update .pyi type stubs
- All samples now import from agent_framework.foundry
- Split tool-call evaluation into evaluate_tool_calls_sample.py
- Fix all_passed to check errored count from result_counts
- Fix raise_for_status to include errored item details
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Auto-create FoundryChatClient from env vars when no client provided
FoundryEvals() now works zero-config when FOUNDRY_PROJECT_ENDPOINT and
FOUNDRY_MODEL environment variables are set. Auto-creates a FoundryChatClient
under the hood, matching the established env var pattern.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix pyright errors: remove dead _normalize_queries, suppress EvalAPIError check
- Remove unused _normalize_queries function and its tests
- Add pyright ignore for EvalAPIError None check (defensive guard)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Support multimodal image content in eval pipeline
Add image (data/uri) content handling to AgentEvalConverter.convert_message()
so that Content.from_data() and Content.from_uri() image payloads are
preserved as input_image parts in the Foundry evaluator format.
- Handle Content type='data' and type='uri' → emit input_image parts
- Add 6 unit tests for image content through convert_message/convert_messages
- Add integration test verifying images flow through EvalItem → JSONL path
- Add evaluate_multimodal.py sample demonstrating local image eval
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address remaining review comments
- Fix project_client docstring to say async-only (not sync/async)
- Add builtin evaluator name validation warning in _resolve_evaluator
- Replace getattr with typed attribute access in _poll_eval_run,
_extract_result_counts, _extract_per_evaluator, _fetch_output_items
- Remove cast import from _foundry_evals (no longer needed)
- Tighten _coerce_result: honour explicit 'passed' when both 'score'
and 'passed' are present; remove performative cast
- Fix self_reflection sample: add env file existence check
- Fix traces sample: correct Pattern 2 section label
- Update all Foundry eval samples to FoundryChatClient + FOUNDRY_MODEL
(remove AIProjectClient + AZURE_AI_MODEL_DEPLOYMENT_NAME pattern)
- Add eval_name and OpenAI client docs to FoundryEvals docstring
- Update test mocks to match typed SDK objects (_MockResultCounts)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix ruff lint errors (E501, SIM108, SIM102)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix pyright errors: type-narrow dict to dict[str, Any], add ignore comments
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Replace ConversationSplitter type alias with Protocol
ConversationSplitter is now a runtime-checkable Protocol with a named
'conversation' parameter, making the expected signature self-documenting.
ConversationSplit enum members gain a __call__ method so they satisfy
the protocol directly -- ConversationSplit.LAST_TURN(conversation) works.
This simplifies _split_conversation from an isinstance dispatch to a
single split(conversation) call.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Standardize on AZURE_AI_MODEL_DEPLOYMENT_NAME and fix Unicode in samples
- Replace FOUNDRY_MODEL with AZURE_AI_MODEL_DEPLOYMENT_NAME in all
eval samples to match repo convention
- Replace Unicode symbols with ASCII equivalents in all eval sample
print statements to avoid cp1252 encoding errors on Windows
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Update python/samples/03-workflows/evaluation/evaluate_workflow.py
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
* Rename ADR 0020 to 0023 (foundry evals integration)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: alliscode <bentho@microsoft.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
* Python: Fix broken samples for GitHub Copilot, declarative, and Responses API
- Add missing on_permission_request handler to github_copilot_basic and
github_copilot_with_session samples (required by copilot SDK)
- Increase timeout for remote MCP query in github_copilot_with_mcp sample
- Soften session isolation claim in github_copilot_with_session sample
- Fix inline_yaml sample: pass project_endpoint via client_kwargs instead
of relying on YAML connection block (AzureAIClient expects
project_endpoint, not endpoint)
- Handle raw JSON schemas in Responses client _convert_response_format
so declarative outputSchema works with the Responses API
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Improve raw JSON schema detection heuristic and add tests
- Broaden raw schema detection to handle anyOf, oneOf, allOf, $ref, $defs
keywords and JSON Schema primitive types, not just 'properties'
- Apply same raw schema handling to azure-ai _shared.py for consistency
- Add unit tests for both openai and azure-ai response_format conversion
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Move ag_ui_workflow_handoff demo to 05-end-to-end (#4895)
Move the AG-UI workflow handoff demo from python/samples/demos/ to
python/samples/05-end-to-end/ to follow the current folder structure
convention. Update README paths accordingly.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix review feedback: remove build artifacts, fix README paths (#4895)
- Add .gitignore to frontend/ to exclude *.tsbuildinfo, vite.config.js,
and vite.config.d.ts build artifacts from version control
- Remove the 4 tracked build artifact files from the tree
- Fix step 2 cd path in README to be relative after 'cd python'
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Clarify working directory context in README Step 2 (#4895)
Step 2 uses a python/-relative path (samples/...) which assumes the
user is still in the python/ directory from Step 1. Add a brief note
making this explicit.
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>
* Support MCP sampling tools capability (#4625)
Forward systemPrompt, tools, and toolChoice from MCP sampling requests
to the chat client's get_response() call. Also advertise the
sampling.tools capability to MCP servers when a client is configured.
- Pass SamplingCapability with tools support to ClientSession
- Convert systemPrompt to instructions in options
- Convert MCP Tool objects to FunctionTool instances for options
- Map MCP ToolChoice.mode to tool_choice in options
- Add tests for all new behaviors and update existing sampling tests
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix#4625: Support MCP sampling tool with proper typing and structured content
- Fix mypy error by typing sampling callback options as ChatOptions[None]
instead of dict[str, Any], and importing ChatOptions from _types
- Handle structuredContent from CallToolResult in _parse_tool_result_from_mcp,
serializing it as JSON text Content when present
- Add tests for structuredContent parsing (with and without regular content)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix lint: add author to TODO comment
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4625: remove default=str, add edge-case tests
- Remove default=str from json.dumps for structuredContent to fail fast
on non-JSON-serializable values instead of silently converting
- Add test for non-JSON-serializable structuredContent (TypeError)
- Add tests for empty systemPrompt ('') and empty tools list ([]) edge
cases in sampling callback
- Expand TODO comment noting list[Content] return type constraint for
future result_type support
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Sanitize sampling callback error to avoid leaking internals (#4625)
Log exception details at DEBUG level instead of including them in the
ErrorData message returned to the MCP server, which may be untrusted.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4625: move params to options, restore error info
- Remove stale TODO comment about response_format (ChatOptions already has it)
- Restore {ex} in sampling callback error message for useful debugging info
- Set structuredContent as additional_property on Content for structured access
- Move temperature, max_tokens, stop into options dict (not top-level kwargs)
- Only set temperature when provided (not all models support it)
- Add tests for generation params in options and temperature omission
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix MCP sampling callback and structured content error handling (#4625)
- Guard max_tokens like temperature: only set when not None, so options
can properly evaluate to None when all params are absent
- Wrap json.dumps of structuredContent in try/except to fall back to
str() for non-serializable values instead of propagating TypeError
- Extract test_connect_sampling_capabilities_with_client into its own
test function so pytest can discover it independently
- Add test for max_tokens=None omission from options
- Update structured content non-serializable test to expect fallback
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4625: review comment fixes
* Fix MCP and Azure validation regressions
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>
Eduard van Valkenburg
·
2026-03-26 07:33:19 +00:00
* Include reasoning messages in MESSAGES_SNAPSHOT (#4843)
FlowState now tracks reasoning messages emitted during a run.
_emit_text_reasoning() persists reasoning (including encrypted_value)
into flow.reasoning_messages, and _build_messages_snapshot() appends
them to the final MESSAGES_SNAPSHOT event.
Changes:
- Add reasoning_messages field to FlowState
- Update _emit_text_reasoning() to accept optional flow parameter
- Include reasoning_messages in _build_messages_snapshot()
- Add 'reasoning' to ALLOWED_AGUI_ROLES so normalize_agui_role()
preserves the role through snapshot round-trips
- Skip reasoning messages in agui_messages_to_agent_framework() since
they are UI-only state and should not be forwarded to LLM providers
- Add regression tests for snapshot emission, encrypted value
preservation, and multi-turn round-trip with reasoning
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Include reasoning messages in MESSAGES_SNAPSHOT events
Fixes#4843
* Fix PR review feedback for reasoning persistence (#4843)
- Accumulate reasoning text per message_id (append deltas) instead of
storing only the current chunk, matching flow.accumulated_text pattern
- Use camelCase encryptedValue in snapshot JSON to match AG-UI protocol
conventions (toolCallId, encryptedValue)
- Normalize snake_case encrypted_value to encryptedValue in
agui_messages_to_snapshot_format for input compatibility
- Update normalize_agui_role docstring to include reasoning role
- Add tests for incremental reasoning accumulation and key normalization
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4843: Python: agent-framework-ag-ui: include reasoning messages in MESSAGES_SNAPSHOT
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix streaming path to deliver mcp_server_tool_result content (#4814)
Remove premature mcp_server_tool_result emission from the
response.output_item.added/mcp_call handler — at that point the MCP
server has not yet responded and output is always None.
Add a handler for response.mcp_call.completed that emits
mcp_server_tool_result with the actual tool output, matching the
non-streaming path behavior.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix streaming path to deliver mcp_server_tool_result content (#4814)
Stop eagerly emitting mcp_server_tool_result on response.output_item.added
(when output is always None). Instead, handle response.output_item.done for
mcp_call items, which carries the full McpCall with populated output.
This matches the non-streaming path which guards with 'if item.output is not
None' before emitting the result.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix test docstring to match actual implementation event name
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review: call_id fallback and raw_representation consistency (#4814)
- Add call_id fallback in response.output_item.done mcp_call handler to
match the output_item.added handler pattern
- Use done_item instead of event for raw_representation to keep
consistent with other output_item branches and non-streaming path
- Add test for call_id fallback when id attribute is missing
- Add raw_representation assertions to existing done handler tests
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review: call_id fallback for non-streaming path and test coverage (#4814)
- Apply defensive call_id fallback (getattr with id/call_id/empty) to
non-streaming mcp_call path for consistency with streaming path
- Add raw_representation assertion to call_id fallback test
- Add test for empty-string fallback when neither id nor call_id exist
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 A2AAgent dropping message content from in-progress TaskStatusUpdateEvents (#4783)
_updates_from_task() returned [] for working-state tasks when
background=False, silently discarding all intermediate message content
from task.status.message. Now extracts and yields message parts from
in-progress status updates during streaming.
Also fixed MockA2AClient.send_message to yield all queued responses
(enabling multi-event streaming tests) and added text parameter to
add_in_progress_task_response for tests that need status messages.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix: gate intermediate status updates behind emit_intermediate flag and add missing test coverage
- Add emit_intermediate parameter to _updates_from_task and _map_a2a_stream
- Thread stream flag from run() so only streaming callers see intermediate updates
- Add IN_PROGRESS_TASK_STATES guard to emit_intermediate condition
- Add role parameter to test helper add_in_progress_task_response
- Add clarifying comment on MockA2AClient.send_message batch semantics
- Add tests for user role mapping, background precedence, non-streaming behavior,
terminal task with no artifacts, and empty parts edge case
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 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>
Eduard van Valkenburg
·
2026-03-20 10:09:46 +00:00
Eduard van Valkenburg ·
perry ·
chetantoshniwal ·
Giles Odigwe ·
Tao Chen ·
Copilot ·
hashwnath ·
Christian Glessner ·
L. Elaine Dazzio ·
westey ·
Peter Ibekwe ·
Ben Thomas ·
dependabot[bot] ·
Evan Mattson ·