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7d23582e2b5a94366ca08fc74562b1a5317f05aa
288
Commits
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7d23582e2b |
Python: fix: prevent MCP message_handler deadlock on notification reload (#4866)
* fix(python): prevent MCP message_handler deadlock on notification reload When an MCP server sends a notifications/tools/list_changed or notifications/prompts/list_changed notification, the message_handler previously awaited load_tools()/load_prompts() directly. Since the handler runs on the MCP SDK's single-threaded receive loop, this caused a deadlock: load_tools() sends a list_tools request and waits for its response, but the receive loop cannot deliver that response while blocked in the handler. This manifested as a timeout in call_tool(), which then surfaced as "Error: Function failed." to the model instead of the real tool output. The MATLAB MCP server reliably triggers this because it sends a tools/list_changed notification during tool execution. Fix: schedule reloads as background asyncio.Tasks via a new _schedule_reload() helper, freeing the receive loop immediately. Fixes #4828 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback: fix exc_info, coalesce reloads, shutdown cleanup, tests - Fix exc_info=exc -> exc_info=True in _schedule_reload and message_handler - Tighten _schedule_reload param type from Any to Coroutine[Any, Any, None] - Coalesce reloads: cancel-and-replace per reload kind to prevent unbounded growth - Cancel pending reload tasks in _close_on_owner before tearing down session - Re-raise CancelledError in _safe_reload to respect task cancellation - Replace flaky asyncio.sleep(0) with asyncio.wait_for/gather in tests - Add caplog assertions to verify reload failure is actually logged - Assert _pending_reload_tasks cleanup on error path Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: address review comments on MCP reload handling - Fix exc_info=True -> exc_info=message in message_handler error logging, since the handler is not called from an except block - Await cancelled reload tasks in _close_on_owner before tearing down the session to avoid 'Task was destroyed but pending' warnings - Add cancel-and-replace test verifying duplicate notifications cancel the first reload task and only keep one in flight Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: remove Task.cancelling() call for Python 3.10 compat Task.cancelling() was added in Python 3.11. Replace with awaiting the task and checking cancelled() instead. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add debug log when cancelling superseded reload task Log at DEBUG level when a new notification cancels an in-flight reload task, improving observability of the cancel-and-replace behavior. 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> |
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1d94518f37 |
Python: Add ClassSkill for class-based skill definitions (#5678)
* Python: Add ClassSkill for class-based skill definitions Add ClassSkill abstract base class with decorator-based resource and script discovery, porting .NET's AgentClassSkill (PRs #5027 and #5183) to Python. - Add ClassSkill(Skill, ABC) with instructions abstract property, cached content/resources/scripts properties - Add @ClassSkill.resource and @ClassSkill.script static method decorators for auto-discovery of methods and properties - Extract _build_skill_content() and _create_resource_element() shared helpers from InlineSkill for reuse - Add _discover_marked_members() for scanning class hierarchies - Add _make_method_name() for Python-to-skill name conversion - Add class_based_skill sample (UnitConverterSkill) - Update mixed_skills sample with TemperatureConverterSkill - Add 58 new tests covering ClassSkill, decorator discovery, property resources, inheritance, kwargs forwarding, and duplicate detection - Export ClassSkill from agent_framework public API Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: replace try/except/continue with assignment to satisfy bandit B112 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * address PR review feedback - Walk cls.__mro__ in _discover_marked_members for inherited property resources - Use inspect.getattr_static for MRO-aware is_property check - Return defensive copies from resources/scripts properties - Raise TypeError on wrong decorator stacking order (@resource above @property) - Log warning instead of silently swallowing descriptor errors during discovery - Validate explicit name= at decoration time via _validate_member_name - Add tests for all of the above Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix temperature converter skill: make resource necessary for script Refactor TemperatureConverterSkill so the agent must read the formulas resource (factor/offset) before calling the script, aligning with the volume-converter pattern. - Resource: numeric factor/offset table instead of symbolic formulas - Script: generic linear transform (value * factor + offset) - Instructions: updated to reflect new workflow Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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2a9b68d1bd |
Python: Fix MCPStreamableHTTPTool leaking asyncio.CancelledError when MCP server is unreachable (#5687)
* fix: wrap asyncio.CancelledError in ToolException in _connect_on_owner (#5667) asyncio.CancelledError is a BaseException (not Exception) in Python 3.8+. When an MCP server is unreachable, the MCP library's internal anyio task group raises CancelledError, which escaped all three 'except Exception' handlers in _connect_on_owner(). This propagated through _run_lifecycle_owner -> _run_on_lifecycle_owner -> connect -> __aenter__, bypassing user except Exception blocks entirely. Fix: change the three except-Exception clauses in _connect_on_owner to 'except (Exception, asyncio.CancelledError)' so spurious CancelledErrors from the MCP transport layer are caught and wrapped in ToolException, consistent with the method's documented contract. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(mcp): propagate genuine task CancelledError in connect() (#5667) On Python >= 3.11, check task.cancelling() > 0 before wrapping CancelledError as ToolException in the three except blocks inside _connect_on_owner(). When the current task is being cancelled by its caller, the CancelledError now propagates after cleanup, consistent with the existing pattern at _mcp.py:560-564 and _runner.py:115-120. On Python < 3.11 task.cancelling() is unavailable, so MCP-internal CancelledErrors still cannot be reliably distinguished from caller-driven cancellation; they continue to be wrapped as ToolException with a comment documenting the trade-off. Tests: - Add cleanup assertion to transport-creation CancelledError test - Add MCPStdioTool variants exercising the 'command' message branches for both transport-creation and initialize CancelledError paths - Add Python 3.11+-gated tests verifying genuine task cancellation propagates (and still cleans up) for transport and initialize stages Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(mcp): log CancelledError with exc_info before wrapping in ToolException (#5667) CancelledError inherits from BaseException (not Exception) on Python >= 3.8, so the 'inner_exception=ex if isinstance(ex, Exception) else None' guard always yields None for CancelledError. This means ToolException.__init__ calls logger.log(level, message, exc_info=None), dropping the traceback. Add an explicit logger.debug(error_msg, exc_info=ex) before each raise ToolException(...) in the three CancelledError handlers so the full traceback is preserved in debug logs when MCP-internal cancellation is wrapped rather than propagated. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #5667: Python: [Bug]: Error Handling Issue regarding Python MCPStreamableHTTPTool Class * refactor(_mcp): extract cancellation helper, fix session error msg and exc_info - Extract _should_propagate_cancelled_error() helper to eliminate duplicated genuine-cancellation detection logic across the three connect() except blocks - Fix session-creation ToolException message to include exception details (e.g. 'Failed to create MCP session: <ex>') matching the transport and initialize failure paths - Change exc_info=ex to exc_info=True in all three logger.debug() calls for idiomatic logging - Add tests for _should_propagate_cancelled_error helper - Add regression test asserting session error message includes exception text - Add test verifying logger.debug is called with exc_info=True Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor: factor out _close_and_check_cancelled helper in _connect_on_owner Addresses review comment on PR #5687: 1. Add _close_and_check_cancelled() helper method that combines _safe_close_exit_stack() + _should_propagate_cancelled_error() into a single await-able call. This eliminates the duplicated close-then-check pattern that appeared identically in all three connect phases (transport, session, initialize), reducing future drift risk. 2. Comments 2 and 3 (missing {ex} in session error message and non-idiomatic exc_info=ex) were already addressed in the current code: all error messages include {ex} and all logger.debug calls use exc_info=True. 3. Add test_connect_genuine_cancellation_during_session_creation_propagates to cover the previously untested genuine-cancellation path in the session-creation phase (transport and initialize phases already had tests). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #5667: review comment fixes --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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8bb4692678 |
Python: Add base_url parameter to AnthropicClient and RawAnthropicClient (#5685)
* feat(anthropic): add base_url parameter to AnthropicClient and RawAnthropicClient Add base_url support to AnthropicSettings TypedDict, RawAnthropicClient, and AnthropicClient so users can point the client at Foundry or other Anthropic-compatible endpoints without having to construct AsyncAnthropic manually. - Add base_url field to AnthropicSettings (resolved from ANTHROPIC_BASE_URL env var) - Add base_url parameter to RawAnthropicClient.__init__ and pass it to AsyncAnthropic - Add base_url parameter to AnthropicClient.__init__ and forward to super - Add unit tests for base_url on both client classes Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Add `base_url` parameter to `AnthropicClient` and `RawAnthropicClient` Fixes #5683 * test: add ANTHROPIC_BASE_URL env fallback tests for issue #5683 Add unit tests verifying that both AnthropicClient and RawAnthropicClient pick up base_url from the ANTHROPIC_BASE_URL environment variable via load_settings when base_url is not passed explicitly as a constructor arg. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * test(anthropic): explicit base_url kwarg beats ANTHROPIC_BASE_URL env var (#5683) Add regression tests asserting that when both ANTHROPIC_BASE_URL is set in the environment *and* an explicit base_url kwarg is passed to AnthropicClient / RawAnthropicClient, the explicit kwarg wins. This closes the priority-ordering contract (explicit arg > env var) that the existing tests left implicit. 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> |
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a95493a909 |
Python: Core: notify agent of external AgentModeProvider mode changes (#5650)
When the operating mode is changed externally (e.g. via a slash-command handler calling set_agent_mode), the agent's chat history still shows the prior set_mode tool call near the end. Updating only the system instructions is insufficient — models tend to anchor on the recent tool call and ignore the new mode. Mirror the .NET AgentModeProvider behavior: when set_agent_mode detects an actual mode change, record the previous mode in provider state. On the next before_run, the provider pops that flag and injects a user-role notification message announcing the switch, so the most recent context unambiguously reflects the current mode. The agent-driven set_mode tool path bypasses this so it does not trigger a redundant notification on its own change. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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be8d2619e4 |
Python: [Breaking] Restructure agent skills to use multi-source architecture (#5584)
* migrate skills to multi source architecture * Fix ruff lint errors in skills module (ASYNC240, SIM108, E501) - Use anyio.Path for async file I/O in _FileSkillResource.read() - Use noqa: ASYNC240 for pure string os.path calls in async context - Restore pre-commit if/else pattern in InlineSkillScript.run() - Break long lines to fit 120-char limit in _skills.py and test_skills.py Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: collapse multi-line lambdas to single lines to fix pyright errors The pyright ignore comments only suppress errors on the same line, so multi-line lambdas left arguments on continuation lines uncovered. Collapse both lambdas to single lines matching the existing load_skill lambda pattern. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: replace untyped lambdas with typed inner functions to fix pyright errors Python lambdas cannot have type annotations, so pyright reports reportUnknownLambdaType and reportUnknownArgumentType errors that cannot be suppressed with inline ignore comments. Replace the lambdas for read_skill_resource and run_skill_script with typed inner async functions. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: address PR review feedback on docs and prompt template - Update with_prompt_template() docstring to document the {resource_instructions} placeholder requirement - Remove stray backslashes after {resource_instructions} and {runner_instructions} in DEFAULT_SKILLS_INSTRUCTION_PROMPT - Update subprocess_script_runner docstring to reflect FileSkillScript.full_path usage Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor: replace dict[str, Skill] with Sequence[Skill] in SkillsProvider Replace internal dict-based skills storage with Sequence[Skill] to eliminate silent duplicate overwrites and simplify the code. Add _find_skill helper for case-insensitive linear lookup. Also fix pyright errors in tests by adding isinstance assertions before accessing .function on SkillResource/SkillScript base types. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor: add read-time resource path validation in _FileSkillsSource Move security validation (path-traversal and symlink guards) for file-based skill resources into _FileSkillsSource, restoring the read-time checks that existed in main via _read_file_skill_resource. - Add _get_validated_resource_path static method on _FileSkillsSource that validates containment, existence, and symlink safety - _FileSkillsSource.get_skills() validates resource paths at discovery time via _get_validated_resource_path before passing to _FileSkillResource - Move _normalize_resource_path, _is_path_within_directory, and _has_symlink_in_path from module-level into _FileSkillsSource as static methods (only used there) - _FileSkillResource remains a simple path-to-content reader - Add tests for _get_validated_resource_path security checks Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: reject str/Path in SkillsProvider constructor to prevent str-as-Sequence ambiguity Since str is a Sequence, passing a path string to the source parameter would silently be treated as a sequence of characters instead of a file source. Add an explicit TypeError with a helpful message pointing callers to SkillsProvider.from_paths(). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR #5584 review feedback - Remove .NET reference from _FileSkillResource docstring - Fix inconsistent resource name example (references/FAQ.md -> references/FAQ) - Simplify SkillsProvider usage in code_defined_skill sample (pass single skill directly) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * remove skillsproviderbuilder * Update python/packages/core/agent_framework/_skills.py Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> * fix: remove dead code and fix sync function call in InlineSkillResource.read() - Change await self.function() to self.function() for sync functions without **kwargs; async results are handled by inspect.isawaitable() - Remove unreachable raise ValueError since __init__ already validates Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * remove full_path unnecessary property * replace anyio with asyncio.to_thread for file I/O in _FileSkillResource Replace anyio.Path usage with asyncio.to_thread + pathlib.Path since anyio is not a direct dependency of core (transitive via mcp). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * simplify awaitable check to return directly Use 'return await result' instead of assigning then returning. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * address PR review feedback for skills refactoring - Replace anyio with asyncio.to_thread + pathlib.Path for file I/O - Simplify awaitable check to return directly - Remove unnecessary function None guard in InlineSkillResource.read() - Add assert for type narrowing on self.function Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * address PR review feedback for skills refactoring - Replace anyio with asyncio.to_thread + pathlib.Path for file I/O - Simplify awaitable checks to return directly - Remove unnecessary function None guard in InlineSkillResource.read() - Use typing.cast instead of assert for type narrowing - Add caching behavior note to SkillsProvider docstring Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor: move name/description from abstract properties to Skill.__init__ Replace abstract properties for name and description on the Skill ABC with a base __init__ that validates and stores them as regular attributes. This simplifies custom Skill subclasses (only content remains abstract) and centralizes validation in the base class, consistent with SkillResource and SkillScript base classes. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> |
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ddfbdf5c7a |
Python: information-flow control prompt injection defense (#5331)
* Python: Information-flow control based prompt injection defense (#5024) * fides integration * documentation * documentation * documentation * human-approval on policy violation * numenous hyena 'works' * IFC based implementation * minor edits in documentation * rebasing the branch and running the email example * Add security tests for IFC middleware * Fix Role.TOOL NameError in approval handling * tiered labelling scheme * 3 tier labelling scheme in middleware * Adapt security middleware to list[Content] tool results * Refactor SecureAgentConfig as context provider and address Copilot review comments * Update FIDES docs to reflect context provider pattern and update code for ContextProvider rename * Fix security examples: use OpenAIChatClient instead of non-existent AzureOpenAIChatClient * Address PR review: consolidate security modules, remove ContentLineage, update docs * remove unrelated files * remove comment from _tools.py and rename decision file * Fix CI failures: Bandit B110, broken md links, hosted approval passthrough * apply template to decision doc 0024 * minor fixes to decision doc 0024 --------- Co-authored-by: Aashish <t-akolluri@microsoft.com> * Python: follow up FIDES security flow (#5330) * Python: follow up FIDES security flow Refine the secure approval path, mark the security classes with the FIDES experimental feature label, and clean up the related docs/tests. Also fix workspace-level validation regressions uncovered while running the full Python check suite. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: remove FIDES GitHub MCP sample Drop the GitHub MCP security sample from the FIDES follow-up branch while keeping the remaining security docs and samples intact. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: fix paths and update FIDES implementation (#5352) * Python: updated import naming and comment from review (#5421) * updated import naming and comment from review * Add approval replay None call-id test Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Address PR 5331 comments and track sesssion while calling Agent in email_security_example (#5446) * Address PR review: fix paths and update FIDES implementation * Address PR comments and add session tracking in email example in samples * Fix session creation and resolve merge conflict in docstring example * Resolve merge conflict in docstring example * Python: add test for empty-message pruning in approval result replacement (#5617) Adds test coverage for the second-pass logic in `_replace_approval_contents_with_results` that removes messages whose `contents` list becomes empty after first-pass content removal. Addresses review comment on PR #5331: https://github.com/microsoft/agent-framework/pull/5331#discussion_r3129039445 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: shrutitople <shruti.tople@gmail.com> Co-authored-by: Aashish <t-akolluri@microsoft.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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d7ca9c8f16 |
Python: Core: add experimental session-mode harness context provider (#5611)
* Python: Core: add experimental session-mode harness context provider Introduces the _harness namespace and the first context provider: SessionModeContextProvider, with get_session_mode / set_session_mode helpers and a DEFAULT_MODE_SOURCE_ID constant. Behind @experimental(ExperimentalFeature.HARNESS). Also folds in a small _sessions.py cleanup (try/except ImportError -> contextlib.suppress) touched while developing the harness. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: align session-mode harness with .NET AgentModeProvider Mirror the default mode descriptions and instruction template used by the .NET AgentModeProvider so the cross-language harness UX is consistent. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: address review feedback on session-mode harness - json.dumps tool outputs to stay valid for arbitrary mode names - normalize configured mode keys (lower+strip) so custom-cased configs work - raise TypeError instead of silently replacing non-dict session state - mark get_session_mode/set_session_mode as @experimental(HARNESS) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: rename SessionModeContextProvider to AgentModeProvider Match the .NET AgentModeProvider class name for cross-language consistency. Helpers renamed accordingly: get_session_mode -> get_agent_mode, set_session_mode -> set_agent_mode. The default source_id is now "agent_mode". Construction pattern stays Pythonic (kwargs, not an options object). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: address AgentModeProvider review feedback - default_mode now defaults to None and falls back to the first configured mode, decoupling the kwarg from the built-in 'plan'/'execute' set. - get_agent_mode catches ValueError when a previously persisted mode is no longer in available_modes and resets to the default mode (matching the non-string recovery branch). Added regression coverage for both behaviors. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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57c901a245 |
Python: Fix hyperlight WasmSandbox cross-thread Drop and harden hosted-agent sample (#5603)
* update hyperlight to beta and move samples, add hosted agent sample * Python: Fix hyperlight WasmSandbox cross-thread Drop and harden sample Root cause: when a worker-side closure raised, the exception's __traceback__ retained frame locals that included the partially constructed PyO3 sandbox. Future.result() re-raised that exception on the caller thread, and when the caller's exception was eventually GC'd the frame locals were released off-thread, dec_ref'ing the unsendable sandbox from the wrong thread and tripping the PyO3 panic '_native_wasm::WasmSandbox is unsendable, but is being dropped on another thread'. Fix: * Add _SandboxWorker._run_on_worker which catches every exception on the worker, drops __traceback__ there, deletes the original exception, and re-raises a fresh instance on the caller thread. initialize and execute route through it; dispose keeps its bare-submit semantics. * Add an opt-in diagnostic module _drop_diagnostic (no-op unless HYPERLIGHT_TRACE_DROPS=1) that installs a sys.unraisablehook and dumps owner-thread + per-thread stacks on any future cross-thread unsendable Drop. Useful for triaging similar PyO3 regressions. * Tests: cross-thread invocation, traceback-leak isolation, _SandboxEntry attribute-shape check, and a stale-reference stress test driven through asyncio.to_thread. Sample (samples/04-hosting/foundry-hosted-agents/responses/06_hyperlight_codeact): * Dockerfile installs agent-framework-* from in-tree source with python/ as build context so unreleased fixes can be validated end-to-end. * call_server.py pins the Responses API version. * main.py enables include_detailed_errors=True so future tool failures surface the actual exception text instead of a bare 'Error: Function failed.' string. * README.md documents the in-tree-package build and the Hyperlight hypervisor requirement (/dev/kvm on Linux, MSHV on Windows). Hosted environments without hypervisor passthrough surface 'No Hypervisor was found for Sandbox'; this is a hosting constraint, not a hyperlight bug. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: remove _drop_diagnostic from hyperlight package The diagnostic module was useful while bisecting the cross-thread Drop bug, but it is no longer needed now that _SandboxWorker._run_on_worker prevents the panic at the source. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: address PR review feedback on hyperlight - Use lazy agent_framework.hyperlight import in sample main.py. - Env-driven endpoint (FOUNDRY_AGENT_ENDPOINT) in call_server.py; remove personal URLs. - Align agent.yaml model deployment with manifest (gpt-4.1-mini). - Tighten Dockerfile requirements guard; drop dangling deploy.ps1 reference. - Preserve exception args when sanitizing tracebacks in _run_on_worker. - Add public _SandboxWorker.is_alive(); update test to avoid private attr. - Add namespace coverage tests for agent_framework.hyperlight lazy loader. - Add prominent note: Foundry hosted-agent runtime does not yet support Hyperlight (no hypervisor exposed); container works locally with /dev/kvm. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: bump hyperlight-sandbox dependencies to 0.4.x Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: renumber hyperlight codeact sample to 08 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Coerce worker exception args to strings for cross-thread safety Stringify exc.args on the worker thread before propagating, so any PyO3 unsendable object captured in args (e.g. via a caller-supplied callback or underlying SDK) cannot be Dropped on the calling thread. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * moved sample --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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550209fe6e |
Python: Core: add experimental todo-list harness context provider (#5612)
* Python: Core: add experimental todo-list harness context provider Adds TodoListContextProvider with pluggable TodoStore backends: TodoSessionStore (in-session) and TodoFileStore (JSONL on disk). Public types: TodoItem, TodoInput. Behind @experimental(ExperimentalFeature.HARNESS). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: align todo harness instructions with .NET TodoProvider Reformat DEFAULT_TODO_INSTRUCTIONS to mirror the .NET TodoProvider DefaultInstructions wording and structure, and bring the class docstring closer to the .NET XML <remarks> block. Keeps Python tool names in snake_case. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: address review feedback on todo harness - mark TodoStore as @experimental(HARNESS) for surface consistency - TodoSessionStore.load_state now raises ValueError on malformed items - TodoFileStore now namespaces persisted state by source_id - TodoFileStore now safely encodes session_id/owner and verifies path containment (matches FileHistoryProvider pattern) - per-(session, source_id) asyncio.Lock around read-modify-write to avoid races Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: rename TodoListContextProvider to TodoProvider Match the .NET TodoProvider class name for cross-language consistency. Other public types (TodoStore, TodoSessionStore, TodoFileStore, TodoItem, TodoInput) are unchanged. Construction stays Pythonic (kwargs, not an options object). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: address TodoProvider review feedback - TodoStore.load_state/save_state are now async; TodoFileStore performs disk I/O via asyncio.to_thread so the event loop is no longer blocked while the per-session mutation lock is held. - TodoSessionStore now raises ValueError for malformed top-level state (non-dict / non-list 'items' / non-int 'next_id') to match the TodoFileStore contract instead of silently re-defaulting. - Both stores now clamp next_id to max(item.id) + 1 after load to make ID collisions impossible after recovery or reconfiguration. - TodoFileStore writes atomically by writing a sibling temp file and os.replace-ing it so a crash mid-write cannot truncate the state file. - TodoFileStore.load_state no longer creates parent directories for sessions that never write; mkdir is deferred to save_state. - TodoProvider mutation locks now live in a weakref.WeakKeyDictionary keyed by AgentSession, so locks for GC'd sessions are evicted instead of leaking in long-running services. Tests cover each change including a TodoFileStore-backed end-to-end provider flow, atomic-write recovery, and lock GC eviction. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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4a2da953ca |
Python: Core: add experimental memory harness context provider (#5613)
* Python: Core: add experimental memory harness context provider Adds MemoryContextProvider with topic-indexed long-term memory and chat-driven compaction. Pluggable MemoryStore backends include MemoryFileStore. Public types: MemoryIndexEntry, MemoryTopicRecord. Behind @experimental(ExperimentalFeature.HARNESS). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: address review feedback on memory harness - mark MemoryStore as @experimental(HARNESS) for surface consistency - safely encode owner id and verify path containment (matches FileHistoryProvider pattern) - namespace MemoryFileStore on-disk layout by source_id to avoid cross-provider collisions - before_run computes index_entries once and only rewrites MEMORY.md when content changes - asyncio locks around topic/state read-modify-write to avoid concurrent-write races Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR feedback: harden memory store IO + consolidation behavior - Atomic writes via os.replace + temp sibling for topic, state, and index files so crashes/disk-full failures cannot leave a truncated half-written file. - Stop creating directories on read paths: list_topics/read_state/search_transcripts and get_messages return empty when nothing has been written. mkdir is deferred to the actual save path (write_topic/write_state/save_messages). - Escape lines that look like markdown headings on render and unescape them on parse, so a memory or summary containing '## Summary'/'## Memories' cannot tamper with the topic file structure. - Narrow extraction/consolidation chat-client failure handling to ChatClientException, asyncio.TimeoutError, and OSError. Programmer errors (AttributeError, TypeError, ...) now propagate so misconfigured clients fail loudly. - Log a payload-prefix preview for every silent shape branch in _extract_memories and _consolidate_topic so unparsable extractor output is debuggable instead of invisible. - Restructure _run_consolidation: read maintenance state and topic snapshot under the state lock, run the LLM consolidation loop without holding the state lock, and only advance last_consolidated_at/sessions_since_consolidation if at least one topic succeeded. Transient consolidation failures now leave the maintenance window in place so the next after_run retries instead of silently sliding forward. - Add regression tests for: markdown-marker round-trip, atomic-write recovery on os.replace failure, no-mkdir on pure read paths, transient consolidation failure preserves state, and propagation of programmer errors. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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570a4d54c2 |
Python: Support OpenAI and Gemini allowed_tools tool choice (#5322)
* Support OpenAI allowed_tools in ToolMode (#5309) Add allowed_tools field to ToolMode TypedDict, enabling users to restrict which tools the model may call via the OpenAI allowed_tools tool_choice type. This preserves prompt caching by keeping all tools in the tools list while limiting which ones the model can invoke. - Add allowed_tools: list[str] to ToolMode TypedDict - Add validation in validate_tool_mode() (only valid when mode == "auto") - Convert to OpenAI API format in _prepare_options() - Add tests for validation and API payload generation Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Support OpenAI `allowed_tools` tool choice in Python SDK Fixes #5309 * Fix #5309: Validate allowed_tools shape and add Chat Completions client support - validate_tool_mode now checks allowed_tools is a non-string sequence of strings and normalizes to list[str], raising ContentError for invalid types - Add missing allowed_tools branch in _chat_completion_client._prepare_options so allowed_tools is emitted as the OpenAI allowed_tools wire format instead of being silently dropped - Add tests for invalid allowed_tools types (string, int, mixed), empty list, tuple normalization, and Chat Completions client payload generation Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: support allowed_tools with mode 'required' in addition to 'auto' OpenAI's allowed_tools tool_choice type supports both mode 'auto' and 'required'. Update validation, client conversion, and tests to allow both modes instead of restricting to 'auto' only. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: use Gemini VALIDATED mode for allowed_tools, warn in unsupported providers - Use FunctionCallingConfigMode.VALIDATED instead of ANY when allowed_tools is set with auto mode in Gemini, preserving optional tool-call semantics. - Handle allowed_tools in required mode with required_function_name precedence. - Fix allowed_names guard to use identity check (is not None) so empty lists are preserved. - Bump google-genai minimum to >=1.32.0 (VALIDATED added in that version). - Add warnings in Anthropic and Bedrock when allowed_tools is set but not supported. - Add Gemini unit tests for allowed_tools with auto, required, empty list, and required_function_name precedence scenarios. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Chat Completions API does not support allowed_tools, add integration tests - Chat Completions API (_chat_completion_client.py) now warns and falls back to plain mode when allowed_tools is set, since the /chat/completions endpoint does not support the allowed_tools type. - Add allowed_tools integration test param to both OpenAIChatClient (Responses API) and OpenAIChatCompletionClient parametrized option tests. - Update Chat Completions unit tests to reflect the warn-and-fallback behavior. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: remove unused walrus operator variable in chat completion client Remove assigned-but-never-used variable 'allowed' flagged by ruff F841. 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> |
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 Tao ChenandGitHub
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03e47b5232 |
Python: Fix spans not correctly nested when using streaming (#5552)
* Fix spans not correctly nested when using streaming * fix pre commit * Address comments |
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8b71f9459a |
Python: Feature/hosted dwf (#5531)
* Fix declarative Workflow.as_agent() by accepting list[Message] in start executor The declarative start executor (JoinExecutor) only advertised dict and str in its input_types, so WorkflowAgent.__init__ rejected it with 'Workflow's start executor cannot handle list[Message]'. Add list[Message] to the JoinExecutor handler annotation and add a matching branch in DeclarativeActionExecutor._ensure_state_initialized that extracts the last user-message text and falls through to the string-input initialization path, so =System.LastMessageText works end-to-end via as_agent(). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Populate Conversation.messages from list[Message] trigger When Workflow.as_agent() is invoked with a list[Message], the start executor now populates Conversation.messages / Conversation.history / System.conversations.{id}.messages with prior turns only (excluding the latest user message), and surfaces the latest user message via Inputs.input and System.LastMessage*. This matches InvokeAzureAgent's contract that the messages binding holds prior turns and the executor itself appends the new user input before invoking, avoiding double-append of the trailing user turn while preserving full history (incl. assistant/system/tool roles and multi-modal content) for downstream actions. * Coerce Enum values when serializing PowerFx symbols MessageRole and other str-subclass Enums passed isinstance(v, str) and were forwarded to pythonnet unchanged. pythonnet then raised 'MessageRole value cannot be converted to System.String' for every PowerFx primitive when ConditionGroup/Expr eval walked the symbol table containing Conversation.messages. Reduce Enum members to their underlying value before the primitive check so eval sees plain strings/ints. * Foundry hosting: pass full conversation history to workflow agents _handle_inner_workflow only forwarded the latest user turn to WorkflowAgent.run, even though _handle_inner_agent already prepends history fetched from Foundry storage to the messages it sends a regular agent. Declarative workflows reset Conversation.messages on every run (state.initialize), so checkpoint replay alone does not give them prior turns - the host has to pass them in, the same way it does for non-workflow agents. Mirror that contract: fetch context.get_history() and pass [*history, *input_messages] to the workflow agent. * feat(workflows): support combined message + checkpoint_id for multi-turn continuation Allow Workflow.run(message=..., checkpoint_id=...) so callers can restore prior workflow state from a checkpoint AND deliver a new message to the start executor in a single call. The existing reset_context logic already preserves shared state when checkpoint_id is set, so this gives us 'fresh start executor invocation with prior state intact' - exactly what hosted multi-turn declarative workflows need. - _workflow.py: drop the message+checkpoint_id mutual exclusion and update _execute_with_message_or_checkpoint to do both (restore then execute) when both are provided. - _agent.py: in _run_core's checkpoint branch, also forward input_messages so WorkflowAgent.run(messages, checkpoint_id=...) works end-to-end. Falls back to the legacy 'restore only' behavior when messages are absent. - _declarative_base.py: detect continuation in _ensure_state_initialized by checking whether DECLARATIVE_STATE_KEY already exists in shared state; if so, refresh inputs/LastMessage* and append non-user trigger messages instead of calling state.initialize() (which would wipe Conversation/Local/System). - foundry_hosting/_responses.py: collapse the host's two-call pattern (restore-only, then fresh run) into a single combined call now that the underlying APIs support it. - tests: drop the assertion that combined message+checkpoint_id raises. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Pivot: preserve workflow state across run() calls Replace the prior 'combined message + checkpoint_id in one run()' approach with a cleaner default: Workflow.run no longer wipes shared state or runner- context messages between calls. Iteration counting and per-run kwargs still reset on a fresh-message run; checkpoint and responses runs are continuations that preserve everything. This lets a WorkflowAgent be invoked repeatedly on the same instance and maintain multi-turn context (e.g. accumulated Conversation.messages) without asking developers to opt in. Hosted-agent multi-turn pattern becomes two explicit calls: restore-from-checkpoint (drive to idle), then run-with-message. Key changes: - _workflow.py: drop _state.clear() and reset_for_new_run() from run(). Reset iteration count and run kwargs on fresh-message runs only. Restore 'Cannot provide both message and checkpoint_id' validation. Add async guard: fresh-message run with un-drained pending executor messages from a prior run is invalid. - _runner.py: clear _state before import_state in restore_from_checkpoint so restore is authoritative (import_state merges, not replaces). - _agent.py: revert checkpoint branch to restore-only (no message forward). - _responses.py (foundry_hosting): two-call host pattern - restore checkpoint silently, then run with new user input. - tests: state-preservation is the new default; rebuild Workflow for clean slate. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix CI lint and mypy issues from prior pivot commit - _workflow.py: collapse nested if (SIM102), drop redundant assignment (RET504) - _declarative_base.py: remove unused last_user_msg = tail assignment whose Message | None type clashed with the prior Message-typed branch Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: fix Inputs.input update and checkpoint storage path - _declarative_base.py: continuation branch was writing 'Inputs.input' via state.set, which routes to the Custom namespace and never updates the PowerFx-visible Workflow.Inputs.input. Update state_data['Inputs'] in place via get_state_data / set_state_data so =Workflow.Inputs.input and =inputs.input see the new turn's user text on continuation. - _declarative_base.py: refresh docstring to clarify that on a list[Message] trigger, Conversation.messages excludes the current user message at the start of the turn (agent executors append it before invoking the inner agent). - _responses.py: when previous_response_id is supplied (no conversation_id), the prior checkpoint lives under <storage>/<previous_response_id> but new checkpoints must land under <storage>/<current_response_id> for the next turn to find them. Hold onto restore_storage from the get_latest lookup and pass it to the restore-only run; pass write_storage (current id) to the message-delivery run and to checkpoint cleanup. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright errors in _declarative_base.py for CI - Replace state._state.get(...) protected access with new public is_initialized() method on DeclarativeWorkflowState (also clearer intent for the continuation detection use case). - Add narrow pyright ignores for the Any-typed trigger paths that pyright cannot fully narrow (the list[Message] isinstance loop and the fallback-DefaultTransform branch). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address Copilot review batch: tests + Workflow.reset escape hatch * Add Workflow.reset() public method as recovery escape hatch when an in-flight run aborted (e.g. WorkflowConvergenceException) and the workflow is not checkpointed. Update the in-flight messages guard's error message to point callers at it. * Add test_workflow_run_inflight_messages_guard exercising both the guard (sync + streaming) and the reset() recovery path. * Add test_workflow_reset_rejects_concurrent_runs to lock down the in-progress guard on reset. * Add test_as_agent_continuation_preserves_prior_state covering the is_continuation branch in _ensure_state_initialized: stamps a marker between calls and asserts it survives, while Inputs.input and System.LastMessageText refresh to the new turn. * Add test_powerfx_safe.py regression tests for the Enum branch in _make_powerfx_safe (str-subclass, int-subclass, plain Enum, and Enums nested in dict/list). * Drop redundant @pytest.mark.asyncio on test_as_agent_round_trip_with_last_message_text (asyncio_mode='auto'). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Skip restore-only pre-pass when checkpoint has pending request_info Address Copilot review on _responses.py: the restore-only checkpoint replay populates self._agent.pending_requests for any request_info events captured in the checkpoint. The follow-up run(input_messages) call would then route through WorkflowAgent._process_pending_requests, which expects function-response content and rejects plain text input as 'unexpected content while awaiting request info responses'. Workflows resumed from a checkpoint that was idle-with-pending-requests would therefore fail every subsequent plain-text user turn. Inspect the loaded checkpoint and skip the pre-pass when its pending_request_info_events dict is non-empty. Workflows that don't use request_info (the current sample set) are unaffected; workflows that do will fall through to a fresh-message run rather than silently corrupting the routing state. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Loosen azure-ai-agentserver-* pins to major version The exact-version pins on azure-ai-agentserver-{core,responses,invocations} forced foundry-hosting consumers to upgrade in lockstep with every beta bump from upstream. Switch to '>=current,<next-major' so we pick up patch and feature updates within the same major series without a coordinated release. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Drop Workflow.reset(); checkpointing is the recovery path The in-flight-messages guard prevented silent misbehavior, but the companion Workflow.reset() escape hatch only cleared _messages while leaving iteration count, executor-local state, and shared State mutations in an indeterminate condition after a mid-run failure. That gave a false sense of recovery. Recovery from a mid-run failure is supported only via checkpoint restoration. Keep the guard and reframe its error message accordingly; remove reset() and its tests. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address Tao's review on PR 5531 - Rename Workflow._run_workflow_with_tracing parameter is_fresh_message_run -> is_continuation (default False, inverted). Fresh-message turns reset per-run accounting; continuations (checkpoint restores, responses replays) preserve it. - Simplify the in-flight-messages guard: _validate_run_params already enforces that 'message' is mutually exclusive with 'checkpoint_id' and 'responses', so the additional checks were dead code. - foundry_hosting _responses: move the restore-only pre-pass above emit_created/emit_in_progress; restore is preparation, not run progress. Drop the skip-restore gate (state preservation requires unconditional restore) and instead clear agent.pending_requests after the restore-only call. Collapse over-conditioned check. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Don't clear pending_requests after restore-only pre-pass Pending requests in the restored checkpoint represent genuinely outstanding HITL requests. The next user input may carry function responses (Responses API `function_call_output` items become FunctionResultContent / FunctionApprovalResponseContent), which `WorkflowAgent._process_pending_requests` correctly extracts and matches against the populated `pending_requests`. Clearing them after restore would silently drop that state and force the next turn to be treated as a fresh input even when the caller is responding to the outstanding requests. 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: Evan Mattson <35585003+moonbox3@users.noreply.github.com> |
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866a325b48 |
Python: [BREAKING] Standardize orchestration terminal outputs as AgentResponse (#5301)
* Fix orchestration outputs so as_agent() returns the final answer only. Align other orchestration outputs * Fix orchestration output issues from review comments 1. Sample cleanup: Remove commented-out FoundryChatClient block and update prerequisites to reference OPENAI_CHAT_MODEL_ID instead of FOUNDRY_* vars. 2. Sequential approval output: Change _EndWithConversation.end_with_agent_executor_response from a no-op sink to yield response.agent_response. When the last participant is AgentApprovalExecutor (via with_request_info), _EndWithConversation is the output executor so the yield produces the terminal answer. When the last participant is a regular AgentExecutor, _EndWithConversation is not in output_executors so the yield is silently filtered out. 3. Forward data events through WorkflowExecutor: _process_workflow_result now also forwards 'data' events from sub-workflows so that emit_intermediate_data=True on AgentExecutor works correctly when wrapped in AgentApprovalExecutor. 4. Concurrent docstring: Update _AggregateAgentConversations docstring to say 'deterministic participant order' instead of 'completion order'. 5. Add test_concurrent_intermediate_outputs_emits_data_events verifying that ConcurrentBuilder(intermediate_outputs=True) emits per-participant data events alongside the single aggregated output event. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add tests for sequential workflow with_request_info and intermediate_outputs (#5301) Address PR review comments 2, 3, and 5: - Add test_sequential_request_info_last_participant_emits_output: Verifies that when the last participant is wrapped via with_request_info() (AgentApprovalExecutor), the workflow still emits a terminal output after approval, exercising the _EndWithConversation.end_with_agent_executor_response fallback path. - Add test_sequential_request_info_with_intermediate_outputs_emits_data_events: Verifies that emit_intermediate_data=True works correctly through AgentApprovalExecutor wrapping—WorkflowExecutor._process_result already forwards data events from sub-workflows, so intermediate agent responses surface as data events in the parent workflow. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright type errors from AgentResponse output refactor (#5301) Update cast() calls in _group_chat.py and _magentic.py to use WorkflowContext[Never, AgentResponse] instead of the old WorkflowContext[Never, list[Message]], matching the updated method signatures in _base_group_chat_orchestrator.py. Fix _sequential.py _EndWithConversation.end_with_agent_executor_response to declare WorkflowContext[Any, AgentResponse] so yield_output accepts AgentResponse[None]. Fix _workflow_executor.py data event forwarding to handle nullable executor_id. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright reportUnknownVariableType in _agent.py (#5301) Extract event.data into a typed local variable before the isinstance check to avoid pyright narrowing it to AgentResponse[Unknown]. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright reportMissingImports for orjson in file history samples (#5301) Add pyright: ignore[reportMissingImports] to orjson imports that are already guarded by try/except ImportError, matching the existing pattern used elsewhere in the samples. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #5301: review comment fixes * Address review feedback for #5301: review comment fixes * Revert sequential_workflow_as_agent sample to FoundryChatClient Reverts the mistaken switch from FoundryChatClient to OpenAIChatClient in the sequential workflow as agent sample. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address ultrareview feedback: emit_data_events rename + WorkflowAgent reasoning conversion Layered on top of the prior review-feedback work in this branch. Renames: - AgentExecutor.emit_intermediate_data -> emit_data_events (mechanical rename; orchestration semantics live at the orchestration layer, not the general-purpose executor). Forwarded through MagenticAgentExecutor, AgentApprovalExecutor, and all orchestration call sites. - HandoffAgentExecutor._check_terminate_and_yield -> _should_terminate (pure predicate; no longer yields anything). HandoffBuilder docstring rewritten to describe the new per-agent AgentResponse output contract. WorkflowAgent reasoning-content conversion: - Add _rewrite_text_to_reasoning(contents) and _msg_as_reasoning(msg) helpers; the as_agent() path now reframes text content from data events as text_reasoning Content blocks before merging into the AgentResponse. - Consumers iterate msg.contents and branch on content.type — same path they already use for Claude thinking and OpenAI reasoning. No new field on Message/AgentResponse/WorkflowEvent. - Streaming branch constructs fresh AgentResponseUpdate instances instead of mutating shared payloads (regression test added). - Helper _msg_maybe_reasoning consolidates the conditional rewrite at three call sites in the non-streaming conversion. Tests: - TestWorkflowAgentReasoningHelpers + TestWorkflowAgentDataEventReasoningConversion add 9 new tests covering helpers, non-streaming, streaming, mixed content, already-reasoning passthrough, and mutation-safety regression. - Updated test_sequential_as_agent_with_intermediate_outputs_includes_chain to assert text_reasoning content for intermediate agents. * Fix pyright: widen event.data to Any to avoid partial-unknown narrowing The streaming conversion path narrowed event.data via isinstance against generic AgentResponse, producing AgentResponse[Unknown] and tripping reportUnknownVariableType/reportUnknownMemberType. Binding data: Any before the check keeps runtime behavior identical while restoring a fully known type for downstream access. * Clean up design * Scope to agent output semantics only * yield AgentResponseUpdate streaming, AgentResponse non-streaming * Fix mypy/pyright: widen cast types at GroupChat callsites Eight callsites in _group_chat.py still cast to WorkflowContext[Never, AgentResponse] but the base orchestrator methods now accept the wider WorkflowContext[Never, AgentResponse | AgentResponseUpdate] (mode-aware yields). W_OutT is invariant, so the narrower cast is not assignable. Magentic was widened in the same commit; this catches the GroupChat callsites that were missed. * Python: skip flaky Foundry / Foundry Hosting integration tests (#5553) These two integration tests have been failing in the merge queue across multiple unrelated PRs (5301, 5531). Both are marked `@pytest.mark.flaky` with 3 retries, but all attempts fail back-to-back. Skipping both with a reason pointing to #5553 so they can be fixed properly without continuing to block unrelated merges. - packages/foundry_hosting/tests/test_responses_int.py::TestOptions::test_temperature_and_max_tokens - packages/foundry/tests/foundry/test_foundry_embedding_client.py::TestFoundryEmbeddingIntegration::test_text_embedding_live Also includes a one-line uv.lock specifier-ordering normalization auto-applied by the poe-check pre-commit hook. --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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9b22ecd119 |
Python: Add requirements.txt and .env.example to the a2a/ sample for pip-based setup (#5510)
* Add requirements.txt and .env.example to a2a sample Beginners following the a2a/ sample had no pip-based install path: the directory lacked requirements.txt and .env.example, unlike every other 04-hosting/ sample. - Add requirements.txt with editable local package paths matching the pattern used in azure_functions/ and similar hosting samples - Add .env.example documenting FOUNDRY_PROJECT_ENDPOINT, FOUNDRY_MODEL, and A2A_AGENT_HOST - Update README Quick Start to cover both pip (.venv) and uv workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Add `requirements.txt` and `.env.example` to the `a2a/` sample for pip-based setup Fixes #5395 * fix(a2a-sample): address PR review feedback for issue #5395 - Remove 'from repo root' wording from Option B uv heading in README to avoid contradicting the 'run from this directory' instruction - Fix A2A_AGENT_HOST default in .env.example from 5001 to 5000 to match function-tools flow; add clarifying comments about port usage - Add note for pip users explaining they can replace 'uv run python' with 'python' once the virtual environment is activated Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #5395: Python: [Samples][Python] a2a/ sample missing requirements.txt — beginners cannot install dependencies --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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 bahtyarandGitHub
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dad3652f46 |
Python: fix: prevent inner_exception from being lost in AgentFrameworkException (#5167)
* fix: prevent inner_exception from being lost in AgentFrameworkException The __init__ method unconditionally called super().__init__() after the conditional call with inner_exception, effectively overwriting the exception args and losing the inner_exception reference. Add else branch so super().__init__() is only called once with the correct arguments. Fixes #5155 Signed-off-by: bahtya <bahtyar153@qq.com> * test: add explicit tests for AgentFrameworkException inner_exception handling - test_exception_with_inner_exception: verifies args include inner exception - test_exception_without_inner_exception: verifies args only contain message - test_exception_inner_exception_none_explicit: verifies explicit None Covers both branches of the if/else in __init__. * fix: export AgentFrameworkException from package Bahtya --------- Signed-off-by: bahtya <bahtyar153@qq.com> |
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da32e8cf80 |
Python: (core): Add functional workflow API (#4238)
* Add functional workflow api * cleanup * More cleanup * address copilot feedback * Address PR feedbacK * updates * PR feedback * Address review comments on functional workflow samples - Swap 05/06 get-started samples: agent workflow first (motivates why workflows exist), simple text workflow second - Rename text_pipeline → text_workflow, poem_pipeline → poem_workflow - Add @step to agent workflow sample (05) to demonstrate caching - Switch agent samples to AzureOpenAIResponsesClient with Foundry - Remove .as_agent() from agent_integration.py to focus on the key difference between inline agent calls vs @step-cached calls - Add commented-out Agent.run example in hitl_review.py - Add clarifying comment in _functional.py that event streaming is buffered (not true per-token streaming) - Add naive_group_chat.py functional sample: round-robin group chat as a plain Python loop - Update READMEs to reflect new file names and group chat sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright type errors * Address PR review comments on functional workflow API 1. Allow request_info inside @step: Auto-inject RunContext into step functions that declare a RunContext parameter (by type or name 'ctx'), and expose get_run_context() for programmatic access. 2. Handle None responses: Log a warning when a response value is None, and document the behavior in request_info docstring. 3. Add executor_bypassed event type: Replace executor_invoked + executor_completed with a single executor_bypassed event when a step replays from cache, making cached vs live execution explicit. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add regression tests for PR review comments on functional workflow API The three review comments (request_info in @step, None response handling, executor_bypassed event type) were already addressed in 7da7db4e. This commit adds cross-cutting regression tests that exercise the interactions between these features: - HITL in step with caching: preceding step bypassed on resume - Full checkpoint lifecycle with HITL step (interrupt -> resume -> restore) - None response inside step-level request_info logs warning - WorkflowInterrupted from step does not emit executor_failed Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR #4238 review comments on functional workflow API Comment 1 (request_info in @step): Already supported. Added comment in StepWrapper.__call__ explaining why WorkflowInterrupted (BaseException) safely bypasses the except Exception handler. Comment 2 (None response): Added docstring to _get_response clarifying the (found, value) return tuple semantics and None handling. Comment 3 (bypass event type): executor_bypassed is already a dedicated event type in WorkflowEventType. Updated comment at the bypass site to make the deliberate event type choice explicit. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add experimental API warnings to functional workflow module Mark all public classes and decorators (workflow, step, RunContext, FunctionalWorkflow, StepWrapper, FunctionalWorkflowAgent) as experimental and subject to change or removal. * Address PR #4238 review comments from @eavanvalkenburg - RunContext docstring leads with purpose (opt-in handle for HITL, custom events, state) so readers importing it from the public surface understand its role before the mechanics (#2993513452). - Rename `06_first_functional_workflow.py` to `06_functional_workflow_basics.py`; the previous filename was confusing since it followed `05_functional_workflow_with_agents.py` (#2993531979). - Simplify `05_functional_workflow_with_agents.py` to call agents directly without a @step wrapper; the step-vs-no-step contrast lives in `03-workflows/functional/agent_integration.py`, keeping the get-started sample minimal (#2993525532). - Switch functional samples to `FoundryChatClient` for consistency with the rest of 01-get-started and 03-workflows (follow-up on #2876988570). - Use walrus in `hitl_review.py` final-state assertion (#2993572182). - Add expected-output block to `basic_streaming_pipeline.py` (#2993557609). - Clarify in `parallel_pipeline.py` that `@step` composes with `asyncio.gather` (#2993597282). - `naive_group_chat.py` threads `list[Message]` between turns instead of stringifying the transcript, preserving role/authorship (#2993583231). Drive-by: pre-commit hook sorts an unrelated import block in `samples/04-hosting/foundry-hosted-agents/responses/02_local_tools/main.py`. * Fix 10 functional-workflow API bugs from /ultrareview pass - bug_001: `ctx.request_info()` without an explicit `request_id` now derives a deterministic `auto::<index>` id from the call-counter, so HITL resume works correctly on the documented default path. A uuid was regenerated on every replay, making resume impossible. - bug_002: `StepWrapper.__call__` no longer deepcopies arguments on the cache-hit replay branch. The copy is only performed on the live-execution path (for the event log) and falls back to the original mapping if deepcopy fails, so steps whose args aren't deepcopyable (locks, sockets, sessions) can still resume from checkpoint. - bug_007: `_set_responses` now prunes each resolved `request_id` from `_pending_requests`, and the cache-hit branch in `request_info` does the same. Previously, answered requests were re-serialized into every subsequent checkpoint and the final checkpoint falsely claimed pending requests even after the workflow completed. - bug_008: `_compute_signature_hash` now mixes the function's `co_code` and `co_names` into the checkpoint signature, so changes to the workflow body invalidate older checkpoints even when steps are accessed via module / class attributes (which `_discover_step_names` can't see statically). `RunContext._record_observed_step` records observed step names for diagnostics. - bug_010: `FunctionalWorkflow.run()` docstring corrected — says "at least one of message/responses/checkpoint_id" and explicitly notes `responses` may be combined with `checkpoint_id` (the validator already allowed this). - bug_013: `FunctionalWorkflowAgent` now surfaces `request_info` events as `FunctionApprovalRequestContent` items (mirroring graph `WorkflowAgent`), threads `responses=` and `checkpoint_id=` through to the underlying workflow, and exposes `pending_requests`. Previously `.as_agent()` returned empty `AgentResponse` for HITL workflows — effectively unusable. - bug_014: `FunctionalWorkflow` now clears `_last_message`, `_last_step_cache`, and `_last_pending_request_ids` on clean completion. `run()` validates that `responses=` keys intersect the currently-pending request set (or raises with a clear error) instead of silently replaying against stale singleton state from a prior run. - bug_015: `FunctionalWorkflow.as_agent` signature now matches graph `Workflow.as_agent`: accepts `name`, `description`, `context_providers`, and `**kwargs`. `FunctionalWorkflowAgent` stores the overrides. - bug_017: `RunContext.set_state` raises `ValueError` for underscore- prefixed keys (the framework's `_step_cache` / `_original_message` keys would silently clobber user state on checkpoint save and user underscore-prefixed state was dropped on restore). Docstring documents the reserved prefix. - merged_bug_003: Workflow function arity is validated at decoration time. Multiple non-ctx parameters raise `ValueError` immediately (previously every arg past the first was silently dropped at call time). Passing a non-None `message` to a ctx-only workflow raises `ValueError` instead of silently discarding the message. Test coverage: +18 regression tests covering every fix. Full workflow suite now 766 passed, 1 skipped, 2 xfailed; full core suite 2338 passed. * Deslop functional.py fix commit - Remove dead instrumentation added in the prior commit that was never consumed: `RunContext._observed_step_names`, `RunContext._record_observed_step`, `FunctionalWorkflow._runtime_step_names`, and `FunctionalWorkflowAgent._extra_kwargs`. The signature hash relies on `co_code` alone, which covers the attribute-access case without the collection-scaffolding. - Trim over-explanatory comments that restated what the code does or what it no longer does. Keep only the comments that answer "why" for the non-obvious bits (deterministic id contract, defensive deepcopy, stale replay guard). - Compress the `_compute_signature_hash` and FunctionalWorkflow `__init__` block docstrings without losing the user-facing reasoning. Net -49 lines. Regression lock preserved (766 passed, 1 skipped, 2 xfailed). * Fix functional workflow review feedback --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Copilot <copilot@github.com> |
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Tao ChenandGitHub
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0989e68d1c |
Python: Fix user agent prefix (#5455)
* Fix hosting user agent missing * Fix other providers * Add more tests * comments * Fix tests |
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58ff4ad3a9 |
Python: Hyperlight: thread-confine sandbox, skip parsing on host callbacks, schema/tool cleanup (#5424)
* improved parsing of tool call results and tweaks * Address PR review: skip_parsing flag, broader registry close, comment fix - FunctionTool.invoke now takes a boolean skip_parsing flag instead of the SKIP_PARSING sentinel; the sentinel is still accepted as result_parser at construction time to opt out of parsing for every call. The two paths are equivalent. - _SandboxRegistry.close now invokes any sandbox close/shutdown hook on the entry's own worker thread (PyO3 unsendable), then shuts the worker down, then cleans up the per-entry temporary directories. - Clarified the _SandboxWorker.shutdown comment to describe the actual ThreadPoolExecutor.shutdown(wait=False, cancel_futures=False) semantics. - Hyperlight host callback uses skip_parsing=True (the new flag). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Drop redundant 'is not SKIP_PARSING' guard that mypy 1.x flags After callable(configured_parser) the sentinel is already excluded; the extra identity check tripped mypy's non-overlapping identity warning. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixed sandbox working on copy of tool --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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b6b191ad9c |
Python: Add second approval-required tool (set_stop_loss) to concurrent_builder_tool_approval sample (#4875)
* Add set_stop_loss tool to concurrent_builder_tool_approval sample Add a second approval-gated tool (set_stop_loss) to the concurrent workflow tool approval sample to demonstrate handling approval requests for different tools in the same concurrent workflow. Changes: - Add set_stop_loss(symbol, stop_price) with approval_mode='always_require' - Include new tool in both agents' tool lists - Update agent instructions and prompt to encourage stop-loss usage - Update docstring to reflect two approval-gated tools - Update sample output to show mixed approval requests Fixes #4874 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Print tool name and arguments in concurrent sample's process_event_stream (#4874) Align process_event_stream in concurrent_builder_tool_approval.py to print the tool name and arguments when collecting approval requests, matching the sample output comment and the sequential_builder_tool_approval.py pattern. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add None-guard for function_call access in tool approval sample (#4874) Add explicit None-checks before accessing function_call.name and function_call.arguments in concurrent_builder_tool_approval.py. The function_call field is typed Content | None, so direct attribute access without a guard could raise AttributeError and required type: ignore comments. The None-guard is consistent with the pattern used in _agent_run.py and removes the suppression comments. Also add a regression test verifying that function_call defaults to None and that the None-guard pattern is safe. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Apply same function_call None-guard to sibling tool-approval samples (#4874) Apply the same fix to sequential_builder_tool_approval.py and group_chat_builder_tool_approval.py, which had the identical pattern of accessing function_call.name/arguments without a None-guard. 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> |
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ce8b6305d8 |
Python: Foundry hosted agent V2 (#5379)
* Python: Wrapper + Samples 1st (#5177) * Experiment * Update dependency and add non streaming * Add more samples * Rename samples * Add invocations * Comments 1 * Comments 2 * Comments 3 * Improve README * Add local shell sample * WIP: Add eval and memory samples * Update user agent prefix * Update user agent prefix doc * Update dependency (#5215) * Add tests and more content types (#5235) * Add tests * fix tests and sample * Fix formatting * Remove function approval contents * Python: Refine samples and upgrade packages (#5261) * Refine samples and upgrade pacakges * Upgrade to a new package that fixes a bug * Update model env var * Move samples (#5281) * Python: Upgrade agentserver packages (#5284) * Upgrade agentserver packages * Fix new types * Python: Add special handling for workflows (#5298) * Add special handling for workflows * Address comments * Improve samples (#5372) * Python: Add more types (#5378) * Add more type supports * Upgrade packages * Remove TODOs in README * Fix README * Comments and mypy * User agent scoped * Fix README * Fix pre commit * Fix pre commit 2 * Fix pre commit 3 * Fix pre commit 4 * Fix pre commit 5 * Fix pre commit 6 * Add azure-monitor-opentelemetry to dev deps Fixes Samples & Markdown CI failure. The PR's new transitive dep on azure-monitor-opentelemetry-exporter (via azure-ai-agentserver-core) makes pyright resolve the azure.monitor.opentelemetry namespace, flipping the check_md_code_blocks diagnostic for `configure_azure_monitor` from reportMissingImports (filtered) to reportAttributeAccessIssue (not filtered). Installing the umbrella azure-monitor-opentelemetry package in dev makes pyright resolve the symbol correctly, matching the install guidance the observability README already gives users. --------- Co-authored-by: Evan Mattson <evan.mattson@microsoft.com> |
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04aaf0c1fe |
Python: Add support for Foundry Toolboxes (#5346)
* Add support for the Foundry Toolbox in MAF Introduces a Foundry Toolbox integration: FoundryChatClient gains a get_toolbox() helper plus select_toolbox_tools(), normalize_tools in the core package flattens tool-collection wrappers (ToolboxVersionObject and generic iterables, while leaving Pydantic BaseModel instances alone), and the new agent_framework.foundry namespace re-exports the toolbox helpers. Ships with unit tests, a sample, and a design doc. azure-ai-projects is pinned to the public >=2.0.0,<3.0 range and the lockfile resolves from public PyPI. The toolbox test module skips when Toolbox* types are unavailable so CI stays green until the public 2.1.0 SDK lands. OMC tooling directories (.omc/, .omx/) are gitignored. * Update to latest azure ai projects package * Improve sample * Rename ADR to 0025 * Update ADR * Apply suggestion from @alliscode Co-authored-by: Ben Thomas <ben.thomas@microsoft.com> * Improve samples * Update test --------- Co-authored-by: Ben Thomas <ben.thomas@microsoft.com> |
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 L. Elaine DazzioandGitHub
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91e34358eb |
Python: Feat: Add finish_reason support to AgentResponse and AgentResponseUpdate (#5211)
* feat: add finish_reason support to AgentResponse and AgentResponseUpdate Add finish_reason field to AgentResponse and AgentResponseUpdate classes, propagate it through _process_update() and map_chat_to_agent_update(), and add comprehensive unit tests. Fixes #4622 * feat: add finish_reason to AgentResponse and AgentResponseUpdate * style: add copyright header to test_finish_reason.py * docs: add finish_reason to AgentResponse and AgentResponseUpdate docstrings * refactor: move finish_reason tests into test_types.py per review feedback Move all finish_reason test cases from the separate test_finish_reason.py file into test_types.py as requested by eavanvalkenburg. Tests are placed in a new '# region finish_reason' section at the end of the file. * fix: use model instead of model_id in _process_update Address PR review feedback from @eavanvalkenburg — ChatResponse and ChatResponseUpdate both use 'model', not 'model_id'. * fix: resolve SIM102 lint error in _process_update Combine nested if statements for AgentResponse finish_reason check to satisfy ruff SIM102 rule, with line wrapping to stay under 120 chars. * fix: resolve pyright reportArgumentType in map_chat_to_agent_update Add type: ignore[arg-type] for FinishReason NewType widening when passing ChatResponseUpdate.finish_reason to AgentResponseUpdate. Matches existing patterns in the codebase (40+ similar ignores). |
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90a633967c |
Python: Fix Gemini client support for Gemini API and Vertex AI (#5258)
* Add Gemini and Vertex AI client support Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address Gemini PR review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * removed sample run readme part --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com> |
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d20f9b5f97 |
Add AgentExecutorResponse.with_text() to preserve conversation history through custom executors (#5255)
Fixes #5246 When a custom @executor transforms agent output and sends a plain str, the downstream AgentExecutor.from_str handler loses the full conversation context. This adds a with_text() helper that creates a new AgentExecutorResponse with replaced text while preserving the prior conversation chain, so AgentExecutor.from_response is invoked instead. - Add with_text(text) method to AgentExecutorResponse dataclass - Add 3 regression tests in test_full_conversation.py Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com> |
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Tao ChenandGitHub
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8f7fd9525d |
Python: Add OpenAI types to default checkpoint encoding allow list (#5297)
* Add OpenAI types to default checkpoint encoding allow list * Address comments |
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69697065ab |
Python: Add context_providers and description to workflow.as_agent() (#4651)
* Add context_providers and description to `workflow.as_agent()` * Add default workflow name and description * Positional * Move import --------- Co-authored-by: Tao Chen <taochen@microsoft.com> Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com> |
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ff05c22c58 |
Python: add experimental file history provider (#5248)
* add experimental file history provider * Improve file history provider writes Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * typo * cleanup * cleanup * fix in readme * added security messages * Refine file history provider locking Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * added additional sample --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Tao ChenandGitHub
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7bb0feca59 |
Python: Move InMemory history provider injection to the first invocation (#5236)
* Move InMemory history provider injection to the first invocation * Add tests |
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b89adb280b |
Python: skill name validation improvements (#4530)
* Initial plan * Port .NET validation improvements to Python skills: reject consecutive hyphens and enforce directory name match Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com> * Fix E501 lint error: split long error message string in _validate_skill_metadata Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: SergeyMenshykh <68852919+SergeyMenshykh@users.noreply.github.com> |
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4dbe696e0e |
Python: Restrict persisted checkpoint deserialization by default (#4941)
* Harden Python checkpoint persistence defaults Add RestrictedUnpickler to _checkpoint_encoding.py that limits which types may be instantiated during pickle deserialization. By default FileCheckpointStorage now uses the restricted unpickler, allowing only: - Built-in Python value types (primitives, datetime, uuid, decimal, collections, etc.) - All agent_framework.* internal types - Additional types specified via the new allowed_checkpoint_types parameter on FileCheckpointStorage This narrows the default type surface area for persisted checkpoints while keeping framework-owned scenarios working without extra configuration. Developers can extend the allowed set by passing "module:qualname" strings to allowed_checkpoint_types. The decode_checkpoint_value function retains backward-compatible unrestricted behavior when called without the new allowed_types kwarg. Fixes #4894 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: resolve mypy no-any-return error in checkpoint encoding Add explicit type annotation for super().find_class() return value to satisfy mypy's no-any-return check. Fixes #4894 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Simplify find_class return in _RestrictedUnpickler (#4894) Remove unnecessary intermediate variable and apply # noqa: S301 # nosec directly on the super().find_class() call, matching the established pattern used on the pickle.loads() call in the same file. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4894: Python: Harden Python checkpoint persistence defaults * Restore # noqa: S301 on line 102 of _checkpoint_encoding.py (#4894) The review feedback correctly identified that removing the # noqa: S301 suppression from the find_class return statement would cause a ruff S301 lint failure, since the project enables bandit ("S") rules. This restores consistency with lines 82 and 246 in the same file. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4894: Python: Harden Python checkpoint persistence defaults * Address PR review comments on checkpoint encoding (#4894) - Move module docstring to proper position after __future__ import - Fix find_class return type annotation to type[Any] - Add missing # noqa: S301 pragma on find_class return - Improve error message to reference both allowed_types param and FileCheckpointStorage.allowed_checkpoint_types - Add -> None return annotation to FileCheckpointStorage.__init__ - Replace tempfile.mktemp with TemporaryDirectory in test - Replace contextlib.suppress with pytest.raises for precise assertion - Remove unused contextlib import Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR #4941 review comments: fix docstring position and return type - Move module docstring before 'from __future__' import so it populates __doc__ (comment #4) - Change find_class return annotation from type[Any] to type to avoid misleading callers about non-type returns like copyreg._reconstructor (comment #2) Comments #1, #3, #5, #6, #7, #8 were already addressed in the current code. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4894: review comment fixes * fix: use pickle.UnpicklingError in RestrictedUnpickler and improve docstring (#4894) - Change _RestrictedUnpickler.find_class to raise pickle.UnpicklingError instead of WorkflowCheckpointException, since it is pickle-level concern that gets wrapped by the caller in _base64_to_unpickle. - Remove now-unnecessary WorkflowCheckpointException re-raise in _base64_to_unpickle (pickle.UnpicklingError is caught by the generic except Exception handler and wrapped). - Expand decode_checkpoint_value docstring to show a concrete example of the module:qualname format with a user-defined class. - Add regression test verifying find_class raises pickle.UnpicklingError. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: address PR #4941 review comments for checkpoint encoding - Comment 1 (line 103): Already resolved in prior commit — _RestrictedUnpickler now raises pickle.UnpicklingError instead of WorkflowCheckpointException. - Comment 2 (line 140): Add concrete usage examples to decode_checkpoint_value docstring showing both direct allowed_types usage and FileCheckpointStorage allowed_checkpoint_types usage. Rename 'SafeState' to 'MyState' across all docstrings for consistency, making it clear this is a user-defined class name. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: replace deprecated 'builtin' repo with pre-commit-hooks in pre-commit config pre-commit 4.x no longer supports 'repo: builtin'. Merge those hooks into the existing pre-commit-hooks repo entry. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * style: apply pyupgrade formatting to docstring example Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: resolve pre-commit hook paths for monorepo git root The poe-check and bandit hooks referenced paths relative to python/ but pre-commit runs hooks from the git root (monorepo root). Fix poe-check entry to cd into python/ first, and update bandit config path to python/pyproject.toml. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pre-commit config paths for prek --cd python execution Revert bandit config path from 'python/pyproject.toml' to 'pyproject.toml' and poe-check entry from explicit 'cd python' wrapper to direct invocation, since prek --cd python already sets the working directory to python/. Also apply ruff formatting fixes to cosmos checkpoint storage files. Fixes #4894 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: add builtins:getattr to checkpoint deserialization allowlist Pickle uses builtins:getattr to reconstruct enum members (e.g., WorkflowMessage.type which is a MessageType enum). Without it in the allowlist, checkpoint roundtrip tests fail with WorkflowCheckpointException. Fixes #4894 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4894: review comment fixes --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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f94a75daa5 |
Python: Fix response_format crash on background polling with empty text (#5146)
* Guard against empty text in _parse_structured_response_value (#5145) When using response_format with background=True (Responses API), polling an in-progress response produces empty text. _parse_structured_response_value unconditionally passed this to model_validate_json/json.loads, causing ValidationError or JSONDecodeError. Add an early return of None when text is empty, matching the existing guard for response_format=None. This allows .value to safely return None for in-progress background responses. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix `response_format` crash on background polling with empty text Fixes #5145 --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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36cafe4e5a |
Python: Raise clear handler registration error for unresolved TypeVar annotations (#4944)
* Raise clear handler registration error for unresolved TypeVar (#4943) Detect unresolved TypeVar in message parameter annotations during handler registration in both _validate_handler_signature (Executor) and _validate_function_signature (FunctionExecutor). Raises a ValueError with an actionable message recommending @handler(input=..., output=...) or @executor(input=..., output=...) instead of letting TypeVar leak through to a confusing TypeCompatibilityError during workflow edge validation. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4943: reorder checks and harden function executor - Move TypeVar check before validate_workflow_context_annotation in _executor.py so users see the more actionable error first - Wrap get_type_hints in try/except in _function_executor.py matching the defensive pattern in _executor.py - Repurpose duplicate test to cover bounded TypeVar rejection - Add test_function_executor_allows_concrete_types for test symmetry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Narrow get_type_hints except clause and add missing tests (#4943) - Narrow `except Exception` to `except (NameError, AttributeError, RecursionError)` in both _executor.py and _function_executor.py so unexpected failures in get_type_hints are not silently swallowed. - Add test_handler_unresolvable_annotation_raises to test_function_executor_future.py exercising the except branch of get_type_hints in the function executor path. - Add test_function_executor_rejects_bounded_typevar_in_message_annotation to test_function_executor.py for parity with the Executor bounded TypeVar test. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add error ordering test for TypeVar vs WorkflowContext priority (#4943) Add test_handler_typevar_error_takes_priority_over_context_error to verify that when a handler has both a TypeVar message and an unannotated ctx, the TypeVar error is raised first (the more actionable issue). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix image content serialization sending null file_id to Foundry API Omit file_id from input_image dict when not present instead of including it as null, which Azure AI Foundry's stricter schema validation rejects. * Python: Fix Foundry API rejecting rich content in function_call_output Azure AI Foundry does not support list-format output in function_call_output items. Add SUPPORTS_RICH_FUNCTION_OUTPUT flag (default True) to RawOpenAIChatClient, set to False in RawFoundryChatClient so Foundry falls back to string output for tool results with images/files. Also omit file_id from input_image dicts when not set, since Foundry rejects explicit nulls. * Python: Surface rich tool content as user message when Foundry lacks support When SUPPORTS_RICH_FUNCTION_OUTPUT is False, image/file items from tool results are injected as a follow-up user message so the model can still process the visual content via Foundry's supported user message format. * Xfail Foundry image integration test for the meantime --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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3446eb8d5d |
Python: [BREAKING] update to v1.0.0 (#5062)
* updates to final deprecated pieces and versions * fix mypy * fix readme links |
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Eduard van ValkenburgandGitHub
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95fd5ec658 |
Python: [BREAKING] Python: move Azure AI embeddings to Foundry (#5056)
* renamed AzureAIINferenceEmbeddings and lazy load azure-cosmos and env var rename * updated coverage * fix readme |
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Tao ChenandGitHub
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62595b233f |
[BREAKING] Python: Refactor workflows kwargs (#5010)
* Refactor workflows kwargs usage * Update sample * Add tests * Update samples * Fix formatting * Comments * Comments 2 * Comments 3 * Fix test and typing |
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 hashwnathandGitHub
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7e8e9e3074 |
Python: Fix duplicate system message from instructions (#5049) (#5051)
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 |
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Eduard van ValkenburgandGitHub
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519bb0cb2b |
Python: updated declarative samples and handling of non-pydantic response formats (#5022)
* updated declarative samples and handling of non-pydantic response formats * fixed from comments * update docstring |
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6acab3d1d6 |
Python: [BREAKING] Standardize model selection on model (#4999)
* 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> |
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b065a4ce51 |
Python: [BREAKING] update context provider APIs, middleware, and per-service-call history persistence (#4992)
* Rename provider base APIs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Allow provider-added chat and function middleware Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Simulate service-stored history per model call Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix typing regressions in CI Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix response ID suppression review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Rename per-service-call history persistence APIs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address context persistence review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize markdown sample docs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Persist service continuation state per call Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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651e317907 |
Python: Fix _add_text_reasoning_content to preserve id during coalescing (#4862)
* 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> |
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55b6e7a9f4 |
Python: Add Python feature lifecycle decorators for released APIs (#4975)
* Add Python feature lifecycle decorators Introduce reusable experimental and release-candidate decorators for released packages, migrate the Skills APIs to the new staged metadata and warning system, and add lifecycle guidance plus samples. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Python CI follow-ups Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Preserve protocol runtime checks Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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9c57680f00 |
Python: Add header_provider to Streamable HTTP MCP servers (#4849)
* 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> |
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35adfdb318 |
Python: Foundry Evals integration for Python (#4750)
* 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> |
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b1b528e4a8 |
Python: [BREAKING] Remove deprecated kwargs compatibility paths (#4858)
* [BREAKING] Remove deprecated kwargs compatibility paths Remove the deprecated kwargs compatibility shims across core agents, clients, tools, middleware, and telemetry. Keep workflow kwargs behavior intact in this branch and follow up separately in #4850. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix PR CI fallout for kwargs removal Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updates * Fix Azure AI CI fallout Remove the stale _get_current_conversation_id override from the Azure AI client after the OpenAI base helper was deleted. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixed new classes * Fix Assistants deprecated import gating Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix integration replay regressions Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Switch multi-agent hosting samples to Azure chat completions Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Simplify Azure multi-agent sample config Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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efb14cedb1 |
Python: Support structuredContent in MCP tool results and fix sampling options type (#4763)
* 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> |
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Eduard van ValkenburgandGitHub
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c012aac5f2 |
Python: [BREAKING] Reduce core dependencies and simplify optional integrations (#4904)
* improved dependencies and some fixes * fix for mypy * improve mcp |
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5e056b672e |
Python: [BREAKING] Python: Provider-leading client design & OpenAI package extraction (#4818)
* Python: Provider-leading client design & OpenAI package extraction Major refactoring of the Python Agent Framework client architecture: - Extract OpenAI clients into new `agent-framework-openai` package - Core package no longer depends on openai, azure-identity, azure-ai-projects - Rename clients for discoverability: OpenAIResponsesClient → OpenAIChatClient, OpenAIChatClient → OpenAIChatCompletionClient - Unify `model_id`/`deployment_name`/`model_deployment_name` → `model` param - New FoundryChatClient for Azure AI Foundry Responses API - New FoundryAgent/FoundryAgentClient for connecting to pre-configured Foundry agents - Remove OpenAIBase/OpenAIConfigMixin from non-deprecated client MRO - Deprecate AzureOpenAI* clients, AzureAIClient, OpenAIAssistantsClient - Reorganize samples: azure_openai+azure_ai+azure_ai_agent → azure/ - ADR-0020: Provider-Leading Client Design Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: missing Agent imports in samples, .model_id → .model in foundry_local sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: CI failures — mypy errors, coverage targets, sample imports - azure-ai mypy: add type ignores for TypedDict total=, model arg, forward ref - Coverage: replace core.azure/openai targets with openai package target - project_provider: add type annotation for opts dict Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: populate openai .pyi stub, fix broken README links, coverage targets Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixes * updated observabilitty * reset azure init.pyi * fix errors * updated adr number * fix foundry local * fixed not renamed docstrings and comments, and added deprecated markers to old classes * fix tests and pyprojects * fix test vars * updated function tests * update durable * updated test setup for functions * Fix Foundry auth in workflow samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize Python integration workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update hosting samples for Foundry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger full CI rerun Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger CI rerun again Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * trigger rerun * trigger rerun * fix for litellm * undo durabletask changes * Move Foundry APIs into foundry namespace Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Foundry pyproject formatting Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Split provider samples by Foundry surface Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Restore hosting sample requirements Also fix the Foundry Local sample link after the provider sample move. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated tests * udpated foundry integration tests * removed dist from azurefunctions tests * Use separate Foundry clients for concurrent agents Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix client setup in azfunc and durable * disabled two tests * updated setup for some function and durable tests * improved azure openai setup with new clients * ignore deprecated * fixes * skip 11 * remove openai assistants int tests --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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cb96347c95 |
Python: Fix PydanticSchemaGenerationError when using from __future__ import annotations with @tool (#4822)
* 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> |