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Python: Adding AgentFileStore and FileAccessProvider to support file access operations. (#6099)
* Adding AgentFileStore and FileAccessProvider to support file ased operations for agents. * Address PR review feedback on FileAccessProvider - Probe symlinks on the unresolved candidate path so in-root symlinks cannot silently pass and out-of-root symlinks surface the correct error message. - Validate matching_lines elements in FileSearchResult.from_dict and raise a clean ValueError for non-mapping entries. - Cap search regex pattern length (256 chars) via a new _compile_search_regex helper to mitigate ReDoS, and surface the cap in the file_access_search_files tool description. - Skip non-UTF-8 files during filesystem search instead of aborting the entire directory walk. - Replace the module-scope trailing string in the data-processing sample with comments to avoid Ruff B018. - Remove the checked-in working/region_totals.md sample artifact so the save flow works from a clean checkout. - Expand the Windows stdout reconfiguration comment in task_runner.py for clarity. - Add tests for invalid/oversize regex, non-UTF-8 file search, and in-root symlink rejection. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix mypy redundant-cast in FileSearchResult.from_dict Use cast(list[object], ...) instead of cast(list[Any], ...) so the cast represents a real type change (lists are invariant) and is no longer flagged by mypy as redundant, while still satisfying pyright's reportUnknownVariableType. Matches the existing pattern in _memory.py. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Tighten path normalization and directory resolution in FileAccess - _normalize_relative_path now strips surrounding whitespace up front so leading/trailing spaces never leak into file segments, and rejects trailing path separators for file paths so 'foo/' is no longer silently coerced to 'foo'. - FileSystemAgentFileStore._resolve_safe_directory_path normalizes with is_directory=True and maps an empty normalized result to the root. This matches InMemoryAgentFileStore so whitespace-only directory inputs resolve to the root instead of raising. - Added tests for whitespace stripping, trailing-separator rejection, and whitespace-only directory listing on the filesystem store. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Harden FileAccess search and atomic save in store API - Add wall-clock timeout (10s) around regex scans so a pathological pattern (e.g. `(a+)+`) below the length cap cannot stall the event loop. - Offload the InMemoryAgentFileStore regex scan to a worker thread, matching the filesystem store. - Fail closed when `Path.is_symlink` raises during the safe-path probe so a permission error cannot silently bypass the symlink/reparse-point rejection. - Add `overwrite: bool = True` to `AgentFileStore.write_file`; the in-memory store performs the check under the existing lock and the filesystem store uses `open(mode='x')` so concurrent callers cannot race past `overwrite=False`. - `file_access_save_file` now relies on the atomic store call instead of a separate `file_exists` round-trip. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Python 3.10 timeout handling and add directory arg to list/search tools - Catch asyncio.TimeoutError in _run_search_with_timeout. In Python 3.10 asyncio.wait_for raises asyncio.exceptions.TimeoutError, which is distinct from the builtin TimeoutError (the two were unified in 3.11). Catching the asyncio alias works on every supported version. - Add an optional directory parameter to file_access_list_files and file_access_search_files so agents can enumerate / scope searches to nested folders, not just the store root. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address FileAccess review feedback: case, errors, signal, TOCTOU - InMemoryAgentFileStore now stores (display_name, content) so list_files and search_files return the original-case names callers wrote, matching the behaviour of FileSystemAgentFileStore on case-preserving filesystems and removing the silent in-memory vs. on-disk contract divergence. - FileSystemAgentFileStore.read_file raises ValueError instead of letting UnicodeDecodeError bubble for binary / non-UTF-8 input, restoring symmetry with search_files (which still skips) and giving the tool layer a recoverable type to translate. - Tool wrappers now catch ValueError and OSError around every operation and surface them as readable strings, so 'you used ..' and 'the file already exists' are both reported to the model the same way instead of the former crashing out as an unhandled exception. - _search_files_sync logs per skipped non-UTF-8 file at WARNING and an aggregate INFO summary so operators can distinguish 'no matches' from 'half the corpus was unreadable'. - FileSystemAgentFileStore softens its docstrings to acknowledge the inherent probe-then-open TOCTOU window. On POSIX both read and write now pass O_NOFOLLOW so the kernel refuses if the leaf segment becomes a symlink between the probe and the open. Windows has no equivalent flag; the limitation is documented. - Tests cover: case preservation on list/search, ValueError on non-UTF-8 read at the store and tool layer, tool-layer string responses for path-traversal and oversized-regex inputs, search-skip log output, symlink rejection on delete/search/list, and symlinked intermediate directory rejection. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address FileAccess nit comments: docstrings, enumerate, opt-in delete approval - Expand FileSearchMatch/FileSearchResult.to_dict docstrings to explain why the override is needed (__slots__ defeats the mixin's __dict__ iteration) and why exclude/exclude_none are accepted-but-ignored (mixin signature compatibility for callers like to_json). - Use enumerate(lines, start=1) in _search_file_content so the +1 below is no longer needed; rename loop variable to line_number for clarity. - Add opt-in require_delete_approval: bool = False on FileAccessProvider. When True, file_access_delete_file is registered with approval_mode 'always_require' so the host must approve every delete. Default False preserves current behaviour and matches the .NET reference, but deployments that want a safer-by-default posture can enable it. - Add tests covering both delete approval modes. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * FileAccess: require delete approval by default Flip the default for FileAccessProvider(require_delete_approval=...) from False to True so destructive deletes are gated by host approval out of the box. Callers that want the previous autonomous behaviour (which matches the .NET reference) can pass require_delete_approval=False. Tests updated accordingly. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fixing linkinspector by installing Chrome for puppeteer first. --------- Co-authored-by: Ben Thomas <25218250+alliscode@users.noreply.github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Ben Thomas ·
2026-05-28 20:09:50 +00:00 -
Tao Chen ·
2026-05-28 20:03:46 +00:00 -
Python: [Breaking] Refactor Skill API to async resource and script lookup (#6135)
Port of .NET commit
08541ee5a9. Replace property-based Skill.content/resources/scripts with async by-name lookup methods: - content property -> async get_content() -> str - resources property -> async get_resource(name) -> SkillResource | None - scripts property -> async get_script(name) -> SkillScript | None SkillsProvider now always includes all three tools (load_skill, read_skill_resource, run_skill_script) and both instruction blocks regardless of whether any skills have resources or scripts. ClassSkill retains resources/scripts properties as overridable hooks for subclass reflection-based discovery. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>semenshi-m ·
2026-05-28 15:54:20 +00:00 -
Bump Python package versions for 1.7.0 release (#6142)
Bumps the released 1.6.0 packages agent-framework, agent-framework-core, agent-framework-foundry, and agent-framework-openai to 1.7.0, with root continuing to exactly pin agent-framework-core[all]. Bumps the changed prerelease packages agent-framework-a2a, agent-framework-chatkit, agent-framework-declarative, agent-framework-devui, and agent-framework-foundry-hosting to the 260528 date stamp, raises core floors on the packages included in this release, raises Foundry's OpenAI floor alongside OpenAI, and raises ChatKit's openai-chatkit floor to the minimum version required by the current typed API usage. No beta cohort bump was applied; the absent mistal/mistral package was intentionally not bumped because no such package exists in this branch.
Evan Mattson ·
2026-05-28 19:45:31 +09:00 -
Python: Align c# and python TodoProvider tool names (#6107)
* Align c# and python TodoProvider tool names * Potential fix for pull request finding Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> * Address PR review: remove __slots__ and add typed schemas for tool params - Remove __slots__ from TodoItem, TodoInput, and TodoCompleteInput classes (not needed for low-instance-count objects and hinders dev scenarios) - Add _TodoAddItemSchema and _TodoCompleteItemSchema TypedDicts to provide proper JSON schema for todos_add and todos_complete tool parameters - Use typing_extensions for Python 3.10 compatibility Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
westey ·
2026-05-28 08:40:13 +00:00 -
feat(a2a): add A2AAgentSession with reference_task_ids and input-required support (#5980)
* feat(a2a): link follow-up messages via reference_task_ids Track the task_id from A2A responses (task, status_update, artifact_update, and message payloads) on session.state and include it as reference_task_ids on subsequent outgoing messages. This enables remote agents to correlate follow-up messages as task refinements per the A2A spec. Resolves #5938 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * feat(a2a): add A2AAgentSession for typed protocol state tracking Introduce A2AAgentSession (subclass of AgentSession) with context_id, task_id, and task_state properties. This follows the DurableAgentSession pattern and mirrors the .NET A2AAgentSession design. - Track task_id, context_id, and task_state from all response payload types - Validate context_id consistency (raise on mismatch) - Auto-assign server-generated context_id when not set - Only A2AAgentSession gets reference tracking (no state dict fallback) - Plain AgentSession continues to work without reference tracking - Add serialization support (to_dict/from_dict) - Export via agent_framework.a2a and agent_framework_a2a Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * style: remove unnecessary string annotation (pyupgrade) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: use AgentSession.from_dict for state deserialization Avoids importing private _deserialize_state, matching the DurableAgentSession pattern. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: track context_id from message payloads in A2AAgentSession Previously, context_id was only captured from task, status_update, and artifact_update payloads. Message-only responses (which carry context_id but may lack task_id) were silently lost. This fix: - Captures msg.context_id in the message handler - Persists session state when either last_task_id or last_context_id is present (not only when task_id is truthy) - Only updates task_id/task_state when a task_id was actually returned - Adds a test for message-only context_id tracking Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * addressed comments * Gate status content to INPUT_REQUIRED/terminal states (match .NET) Match .NET's GetUserInputRequests pattern: only emit TaskStatusUpdateEvent message content when state is INPUT_REQUIRED or terminal. Intermediate status text (WORKING, SUBMITTED) is no longer surfaced to callers. When state is INPUT_REQUIRED, set additional_properties['input_required'] = True so callers can distinguish input requests from final responses. Closes #5937 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review: remove message task_id tracking, defensive fallbacks, and input_required flag - Do not track task_id from Message payloads (simple interactions without task tracking) - Remove 'or last_task_id' fallback from status_update and artifact_update handlers (spec guarantees task_id is always set) - Remove additional_properties['input_required'] flag (content gating to INPUT_REQUIRED/terminal states is the signal itself) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Giles Odigwe ·
2026-05-28 08:36:49 +00:00 -
Python: Add a HarnessAgent with available features and sample (#6041)
* Add a HarnessAgent with available features and sample * Fix formatting * Address PR comments and fix mypy error * Add web search support to HarnessAgent * Fix build warning * Apply suggestions from code review Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> * Address PR comments * Address PR comments * Address further PR comments. * Fix markdown broken link --------- Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
2026-05-27 14:54:00 +01:00 -
Python: feat(foundry): add to_prompt_agent / deploy_as_prompt_agent (experimental) (#5959)
* feat(foundry): add experimental to_prompt_agent converter Adds `to_prompt_agent(agent)`, an experimental converter (`ExperimentalFeature.TO_PROMPT_AGENT`) that turns an Agent Framework `Agent` into a Foundry `PromptAgentDefinition` ready to publish via `AIProjectClient.agents.create_version(...)`. Behaviour: * `agent.client` must be a `FoundryChatClient` (or subclass); otherwise `TypeError` is raised. The model deployment name is lifted from the bound client so the same Agent definition used for local runs can be published as a hosted prompt agent without restating the model. * Foundry SDK tool instances (from `FoundryChatClient.get_*_tool()`) are passed through unchanged. AF `FunctionTool`s (and `@tool`-decorated callables) are emitted as Foundry `FunctionTool` declarations. * Local AF MCP tools cannot be expressed in a `PromptAgentDefinition`; the converter raises `ValueError` and points at `FoundryChatClient.get_mcp_tool()` for hosted MCP servers. * The converter walks both `agent.default_options["tools"]` and `agent.mcp_tools` because `normalize_tools()` splits local MCP off into its own list. Re-exported through the `agent_framework.foundry` lazy-loading namespace (updates both `__init__.py` and the `__init__.pyi` type stub). Adds a portable-agent sample showing the same `Agent` driven through both `agent.run(...)` and `to_prompt_agent(agent)`, and a README section covering the new converter. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * chore(samples): remove snippet tags from portable agent sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * chore(samples): inline FoundryChatClient and enable prompt-agent publish Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * chore(samples): drop async credential context manager Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs(foundry): trim README to_prompt_agent example to publish-only flow Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs(foundry): note FoundryAgent runs @tool callables for deployed prompt agents Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(foundry): address review comments on to_prompt_agent converter * Construct `PromptAgentDefinition` `Tool` from a dict via `**tool_item` unpacking rather than the positional Mapping constructor \u2014 cleaner and matches the typical Pydantic / Azure SDK pattern. * Drop the redundant `isinstance(mcp_tool, MCPTool)` guard in `_convert_tools`; the parameter is already typed `Iterable[MCPTool]` so the second `raise` was unreachable. The remaining single `raise` fires for every entry as intended. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(foundry): match Agent.__init__ model resolution in to_prompt_agent * Read the model from `agent.default_options.get("model")` first, falling back to `agent.client.model`. This mirrors the order `Agent.__init__` uses (`_agents.py:740`) when assembling default_options, so the model the agent runs with is the same model the converter publishes \u2014 e.g. when the caller passes `default_options={"model": "..."}` to override the bound client. * Updated the missing-model error message to point at both the client and the default_options paths. * Added tests: * tool-only agent with no `instructions` produces a definition where `instructions` is `None` and is omitted from the dict payload (`Agent.__init__` strips None values from default_options before storing them). * `default_options['model']` wins over the bound client's model. * Fallback to client.model when default_options has no model. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * feat(foundry): add deploy_as_prompt_agent helper + samples Adds `deploy_as_prompt_agent(agent)`, a convenience wrapper around `to_prompt_agent` that reuses the bound FoundryChatClient's project client to call `project_client.agents.create_version(...)`. Defaults `agent_name` / `description` from `agent.name` / `agent.description` so the Agent stays the single source of truth. * Exposed from `agent_framework_foundry` and the lazy-loading `agent_framework.foundry` namespace (including the .pyi stub). * Marked experimental with the existing `ExperimentalFeature.TO_PROMPT_AGENT` tag. * Tests cover the happy path, name/description defaulting, explicit override, no-name error, metadata + description forwarding, extra kwargs passthrough, and the experimental metadata. Samples: * Renamed the existing sample to `creating_prompt_agents.py`, drops 'portable' wording, presents `deploy_as_prompt_agent` first as the recommended path and `to_prompt_agent` + `AIProjectClient` as the two-step alternative, and adds a cleanup step that deletes the published agent so re-runs stay idempotent. * New `using_prompt_agents.py` shows the end-to-end loop: deploy the agent, connect to it with `FoundryAgent` passing the same local `@tool` callable, run a query against the deployed prompt agent, then clean up. README updated to introduce `deploy_as_prompt_agent` as the recommended path and link to both runnable samples. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(foundry): restore missing-model ValueError in to_prompt_agent The check was accidentally dropped while reworking docstrings in the previous commit. Test `test_to_prompt_agent_rejects_missing_model` exercises this path and was failing on CI as a result. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor(foundry): rename deploy_as_prompt_agent -> create_prompt_agent Renames the helper across the foundry package, core lazy-loader stubs, tests, README and samples. The new name better matches the action performed (a prompt-agent definition is created in Foundry) and is consistent with the surrounding ''create_*'' API surface. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor(foundry): drop create_prompt_agent, enrich to_prompt_agent params Remove the create_prompt_agent helper and consolidate on to_prompt_agent. Expose every PromptAgentDefinition parameter that has either an Agent Framework equivalent (sourced from default_options) or no equivalent (accepted as a keyword argument). * default_options-sourced (with kwarg overrides): temperature, top_p, string tool_choice * kwarg-only Foundry knobs: reasoning, text, structured_inputs, rai_config, ToolChoiceParam tool_choice Precedence is always: explicit keyword > default_options entry > unset. Tests cover every path (defaults, default_options, kwargs, kwarg override). Samples and README rewritten around the enriched to_prompt_agent. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor(foundry): single source of truth for prompt-agent options Stop duplicating the generation-parameter surface between FoundryChatOptions and to_prompt_agent. Translate every field with an Agent Framework equivalent (temperature, top_p, tool_choice, reasoning, response_format/text/verbosity) from agent.default_options via a new RawFoundryChatClient helper _prepare_prompt_agent_options. Only Foundry-specific fields with no AF equivalent — structured_inputs and rai_config — remain as keyword arguments on to_prompt_agent. - tool_choice is dropped when there are no tools (mirrors _prepare_options semantics and avoids polluting tool-less prompt agents with Agent.__init__'s 'auto' default). - response_format Pydantic models route through openai.lib._parsing._responses.type_to_text_format_param; dict shapes go through the existing _prepare_response_and_text_format helper. - default_options is not mutated; text dict is defensively copied. Tests, README, and creating_prompt_agents.py sample updated to reflect the new single-source model. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs(foundry): consolidate prompt-agent sample Drop creating_prompt_agents.py (the publish-only variant) and rename using_prompt_agents.py to foundry_prompt_agents.py so the single sample covers the full convert -> publish -> connect -> run loop. Update the README link list accordingly. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs(foundry): run local Agent + deployed agent in same sample Add an agent.run() call against the local Agent before publishing, then run the deployed prompt agent on the same query. Expand the docstring with a compare-and-contrast covering runtime/latency, configurability, and persistence/sharing differences between the two execution paths. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * test(foundry): cover conflicting response_format + text.format in to_prompt_agent Exercises the ValueError path when a Pydantic response_format would overwrite an explicit text.format mapping with a different shape. Lifts _chat_client.py coverage from 89% to 90%. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor(foundry): move _prepare_prompt_agent_options into _to_prompt_agent Lift the translation helper off RawFoundryChatClient and into the _to_prompt_agent module as a module-private function that takes the client as its first argument. The chat client no longer needs to carry a method whose only consumer is the prompt-agent converter, while still serving as the source of the request-path helper (_prepare_response_and_text_format) that the converter reuses for dict-shaped response_format values. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs(python): codify GA terminology + post-run docs review Add two pieces of guidance to python/AGENTS.md: * Terminology - reserve 'GA' for hosted services; use 'released' or 'stable' for Agent Framework code/features to match the feature-lifecycle stages. * Maintaining Documentation - review AGENTS.md and skills at the end of every run and update any guidance the conversation made stale; before adding a new principle, ask the user to confirm it should be captured. Also pulls in a docstring fix in foundry_prompt_agents.py that swaps the stray 'GA' for 'released', applying the new terminology rule. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * address PR review: strict=True default, Tool._deserialize dispatch, sample cleanup safety - FunctionTool published as strict=True so the server-side schema validation matches what the local FoundryAgent(tools=[same_callable]) dispatcher enforces. AF FunctionTool has no 'strict' attribute, so the safer default is used uniformly instead of silently downgrading to a permissive contract. - _validate_mapping_tool now dispatches through ProjectsTool._deserialize so dict-shaped tools rehydrate to the concrete subclass (FunctionTool, WebSearchTool, ...) via the 'type' discriminator instead of returning a generic Tool. Added a test that asserts isinstance(WebSearchTool) and a new test for the function-typed dict path. - foundry_prompt_agents.py sample now wraps credential + project client in async with and the create_version / run flow in try/finally so a failure on connect or run still deletes the published prompt agent rather than leaving an orphaned, billable resource in the user's Foundry project. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(ci): correct linkspector ignorePattern typo (./pulls -> ./pull) GitHub PR URLs use the singular segment /pull/N (compare to /issues/N for issues). The existing './pulls' ignore pattern never matched anything as a result, so legitimately stale PR links (e.g. PRs deleted from forks) surface as linkspector failures on unrelated PRs. This is the same convention the './issues' rule above already follows. Fixes the markdown-link-check failure on a dangling link in dotnet/src/Microsoft.Agents.AI.DurableTask/CHANGELOG.md. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Eduard van Valkenburg ·
2026-05-27 13:31:21 +00:00 -
Python: Add a BackgroundAgentsProvider for python (#6069)
* Add a BackgroundAgentsProvider for python * Address PR comments and fix linting warnings * Address PR comment
2026-05-27 09:12:01 +00:00 -
Python: Align ModeProvider tool names and instructions (#6071)
* Align ModeProvider tool names and instructions * Address PR comments
2026-05-26 14:37:34 +00:00 -
Python: fix(core): point @experimental warnings at user code, not stdlib internals (#5996)
* fix(core): point @experimental warnings at user code, not stdlib internals Previously the wrappers installed by @experimental called warnings.warn with a fixed stacklevel=3. ABCMeta inserts an extra abc.__new__ frame when an experimental ABC is subclassed, so the warning landed inside abc.py (or <frozen abc>:106 on modern CPython) instead of the user's class Sub(...) line. Resolve the user frame by walking inspect.currentframe(), skipping frames whose module name is abc/functools/typing/contextlib (or submodules), then emit via warnings.warn_explicit so the recorded filename/lineno point at user code. Falls back to warnings.warn with stacklevel=2 if no user frame is found. Module-name matching is used because frozen stdlib modules report '<frozen abc>' as their filename. Also install a one-line warnings.formatwarning specifically for FeatureStageWarning so 'file:line: ExperimentalWarning: [ID] Name ...' prints without the secondary source-snippet line. Other categories delegate to the stdlib default formatter unchanged. Added a regression test that subclasses an @experimental ABC inside warnings.catch_warnings and asserts the recorded filename equals the test file. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(core): address review feedback on @experimental warning fix - Make _install_feature_stage_formatter idempotent: tag the installed formatter with a marker attribute and short-circuit re-installation, so re-imports/reloads don't wrap the formatter on top of itself. Also expose the previous formatter via __wrapped__ for restoration. - Avoid leaking frame references in _resolve_user_frame: capture data into plain locals inside try and del frame/candidate in finally, per CPython's guidance on inspect.currentframe usage. - Drop redundant _WARNED_FEATURES.clear() in the new ABC subclass test (the autouse fixture already handles it). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * changed query for foundry web search test --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-05-22 12:07:10 +00:00 -
Python: bump package versions for 1.6.0 release (#6017)
* Python: bump package versions for 1.6.0 release - Released cohort (agent-framework, core, openai, foundry): 1.5.0 -> 1.6.0 - Beta packages (21 packages): 1.0.0b260519 -> 1.0.0b260521 - Alpha packages (azure-contentunderstanding, foundry-hosting, gemini, monty): 1.0.0a260518/19 -> 1.0.0a260521 - ag-ui stays at 1.0.0rc2, orchestrations at 1.0.0rc1 (dependency bounds updated) - Inter-package dependency lower bounds updated (>=1.5.0,<2 -> >=1.6.0,<2) - Update CHANGELOG compare links - uv.lock refreshed Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review: bump RC packages, add shell tool to changelog - ag-ui: 1.0.0rc2 -> 1.0.0rc3 - orchestrations: 1.0.0rc1 -> 1.0.0rc2 - Add shell tool (#5664) to CHANGELOG - uv.lock refreshed Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-05-22 01:59:20 +00:00 -
Python: Prevent duplicate system instructions in Python telemetry (#5981)
* Initial plan * Fix duplicated system instructions in Python telemetry * Clarify telemetry message filtering * test: cover separate and in-history system messages * Clarify observability message logging split * Simplify observability logging serialization * Harden observability regression test * Reuse observability span message serialization * Clarify observability logging loops * Polish observability message serialization * Tighten observability zip checks * Refactor observability message capture loop * Fix telemetry logging for separate system instructions * Refine observability OTEL message typing * Restore prepended-instruction logging path in _capture_messages * Revert logging change in _capture_messages; keep chat-history-only logging --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Copilot ·
2026-05-21 19:59:06 +00:00 -
Python: feat(foundry): add experimental hosted tool factories on FoundryChatClient (#5958)
* feat(foundry): add experimental hosted tool factories on FoundryChatClient Adds eight new `@experimental` static factory methods on `FoundryChatClient` covering Foundry-hosted tools that previously had no helper: - get_azure_ai_search_tool - get_sharepoint_tool - get_fabric_tool - get_memory_search_tool - get_computer_use_tool - get_browser_automation_tool - get_bing_custom_search_tool - get_a2a_tool All factories are marked with the new `ExperimentalFeature.FOUNDRY_TOOLS` tag and resolve the underlying `azure-ai-projects` preview classes lazily through a `_require_sdk_class` helper so older SDK versions still import cleanly and fail with a clear `ImportError` only on use. Tests cover each factory's return type and field wiring, the experimental metadata, and the missing-SDK-class fallback. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * test(foundry): address review comments on tool-factory tests * Skip preview-tool tests gracefully (`_skip_if_sdk_class_missing`) when the installed `azure-ai-projects` does not expose the required preview class, matching the lazy-import guard in production code so the test suite stays green on older SDK installs. * Add `filterwarnings("ignore::FutureWarning")` to each new tool-factory test (and the parametrized metadata test) so they remain stable under strict warning configurations \u2014 the global dedup in `_feature_stage._WARNED_FEATURES` makes `pytest.warns` brittle across ordered runs. * Use `monkeypatch.setattr(..., None, raising=False)` instead of `delattr` in the missing-SDK-class test so it works for modules that implement PEP 562 `__getattr__`. * Split the long `get_bing_custom_search_tool` return into two lines for readability. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(foundry): harden tool-factory kwargs against silent override * Reorder the dict-literal kwargs assembly in get_azure_ai_search_tool, get_memory_search_tool, and get_bing_custom_search_tool so explicit parameters always take precedence over **kwargs (matching the safe pattern already used in get_a2a_tool). This prevents a caller passing `project_connection_id`, `index_name`, `memory_store_name`, `scope`, or `instance_name` through `**kwargs` from silently overriding the explicit security-sensitive arguments. * Update the README experimental note to reflect once-per-feature-id dedup semantics of `_feature_stage._WARNED_FEATURES` rather than claiming a per-factory "first use" warning. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * feat(foundry): split FOUNDRY_TOOLS / FOUNDRY_PREVIEW_TOOLS, add bing-grounding - Add ExperimentalFeature.FOUNDRY_PREVIEW_TOOLS to distinguish wrappers around preview Foundry SDK tool classes (Sharepoint/Fabric/Memory/ComputerUse/ BrowserAutomation/BingCustomSearch/A2A) from FOUNDRY_TOOLS, which is for GA-SDK wrappers that are simply new in agent-framework-foundry (AzureAISearch, BingGrounding). - Add get_bing_grounding_tool factory and a 'Choosing a web grounding tool' comparison block on get_web_search_tool / get_bing_grounding_tool / get_bing_custom_search_tool docstrings. - Drop the _require_sdk_class lazy resolver: every guarded class is available at azure-ai-projects>=2.1.0 (the package floor), so import them eagerly. Concrete return types replace 'Any'. - README: split the experimental factories into two tables, one per feature flag, with a note explaining the distinction. - Tests: split into FOUNDRY_TOOLS / FOUNDRY_PREVIEW_TOOLS factory cases; drop the obsolete missing-SDK-class ImportError test. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-05-21 08:39:08 +00:00 -
[BREAKING] Python: Enable instrumentation by default (#5865)
* Enable instrumentation by default * Update samples * Optimization when span is not recording * Address Copilot comments * Revert uv.lock * Add warning * Formatting * Fix mypy * Add disable_instrumentation() with sticky user-intent semantics Add a public disable_instrumentation() entry point so users can explicitly opt out of Agent Framework telemetry, with a sticky-disable flag that makes the user's intent "leading" — no framework code path (foundry's configure_azure_monitor, configure_otel_providers, enable_instrumentation, enable_sensitive_telemetry, or direct OBSERVABILITY_SETTINGS.enable_* writes) can re-enable instrumentation until the user explicitly clears the disable with enable_instrumentation(force=True) / enable_sensitive_telemetry(force=True). Also addresses the two remaining unresolved review threads on the PR: 1. test_observability_settings_defaults_instrumentation_true pins the new "ENABLE_INSTRUMENTATION defaults to True when env unset" behavior. 2. test_enable_instrumentation_reads_env_sensitive_data restores coverage for the post-import load_dotenv() fallback path. Implementation: - ObservabilitySettings.enable_instrumentation / enable_sensitive_data become properties backed by _enable_*. While _user_disabled is True, the getters return False and the setters drop True writes (defense in depth so third- party writes can't subvert the disable). - Public is_user_disabled read-only property lets integrations (e.g. foundry's configure_azure_monitor) cheaply check the disable state without poking at privates. - enable_instrumentation() and enable_sensitive_telemetry() short-circuit with an info log when disabled; gain a force=True kwarg that clears the disable. - configure_otel_providers() still creates providers / exporters / views so a later force-enable can use them, but logs an info message when called while disabled. - Foundry's FoundryChatClient.configure_azure_monitor and FoundryAgent.configure_azure_monitor early-return when the user has disabled, so Azure Monitor's global providers aren't installed unnecessarily. Tests: 11 new tests covering default-on, env re-read at call time, sticky behavior against each re-enable surface (enable_instrumentation, enable_sensitive_telemetry, configure_otel_providers, direct attribute writes), force=True override, re-arming the disable, and the __all__ export. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: document disable_instrumentation() and force=True paths Add a "Disabling instrumentation" section to the observability sample README that walks through: - The distinction between the ENABLE_INSTRUMENTATION env var (initial, non-sticky) and disable_instrumentation() (process-wide, sticky). - Why the sticky semantics matter: framework integrations like FoundryChatClient.configure_azure_monitor() can call enable_instrumentation() as part of their setup, and the user's opt-out needs to win. - All five surfaces guarded by the sticky disable (property reads, public enable functions, configure_otel_providers, direct attribute writes, is_user_disabled-aware integrations). - The force=True escape hatch on both enable_instrumentation() and enable_sensitive_telemetry(). - How third-party integrations should consult OBSERVABILITY_SETTINGS.is_user_disabled. - The limits of the disable (does not tear down existing providers / in-flight spans / third-party instrumentation, does not persist across processes). Cross-links the new section from the ENABLE_INSTRUMENTATION row in the env vars table. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: soften disable_instrumentation() overclaim about telemetry guarantees Replace 'no telemetry will be emitted no matter what' (which is too strong, since callers can still pass force=True or mutate private attributes) with language framing the disable as a user-intent contract that library and framework code is expected to honor: the framework actively short-circuits the public enable paths, force=True and private-attribute writes are acknowledged as out-of-contract escape hatches that integrations should not use on the user's behalf. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: correct observability Dependencies section - opentelemetry-sdk is no longer a hard dependency; it is lazily imported by create_resource(), create_metric_views(), and configure_otel_providers() with a clear ImportError when missing. Day-to-day instrumentation works with opentelemetry-api alone provided some other component configures the global OpenTelemetry providers (Azure Monitor, an APM agent, application bootstrap, etc.). - opentelemetry-semantic-conventions-ai is no longer used anywhere in the source; remove it from the listed dependencies. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: replace stale observability migration guide with current PR's only relevant migration The old guide documented the move away from setup_observability(otlp_endpoint=...) which was an earlier-release API change unrelated to this PR and stale enough that it's more confusing than helpful at this point. Replace it with a short note on the single migration this PR introduces: callers of enable_instrumentation(enable_sensitive_data=True) should switch to enable_sensitive_telemetry(). Cross-link to the Disabling instrumentation section for the rare 'force on without enabling sensitive data' use case where enable_instrumentation() still applies. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-05-20 11:52:08 +00:00 -
Python: Skip MCP prompt loading when unsupported (#5370)
* Python: Skip MCP prompt loading when unsupported * Fix MCP pagination pyright checks * Simplify MCP support flag checks
Baidar ·
2026-05-20 11:50:26 +00:00 -
Python: Bump Python package versions for a release (#5964)
* Bump Python package versions to 1.5.0 for a release * Promote orchestrations to 1.0.0rc1 * ci(python-setup): merge dynamic exclude into existing workspace exclude The python-setup action injected exclude = [...] verbatim into [tool.uv.workspace], producing a duplicate 'exclude' key when the section already had a static exclude. Scope the rewrite to the [tool.uv.workspace] section and append the package to the existing array when present; idempotent if the package is already excluded. * Address Copilot review feedback: raise inter-package floors to 1.5.0 - foundry, foundry-local: agent-framework-openai >=1.4.0 -> >=1.5.0 - azure-contentunderstanding: agent-framework-foundry >=1.4.0 -> >=1.5.0 - azurefunctions: pin agent-framework-durabletask to >=1.0.0b260519,<2 Keeps lockstep cohort consistent and avoids mixed 1.4.x / 1.5.0 installs. * Re-include azurefunctions and durabletask in the uv workspace The pinned durabletask>=1.4.0 floor is enough to make resolution succeed; the workspace exclude was over-correction and broke CI samples and pyright type-checking (re-exports in agent_framework/azure/__init__.pyi plus samples/04-hosting/{azure_functions,durabletask}/ could not resolve their imports). Dropping them from agent-framework-core[all] still stands so the metapackage does not pull them. * Restore azurefunctions and durabletask in agent-framework-core[all] The durabletask floor pin keeps users on the safe 1.4.0, so they are once again included in the metapackage. Update CHANGELOG to reflect the pin rather than an [all] removal. * Raise uvicorn ceiling in ag-ui and devui to allow 0.42+ The root override-dependencies pins uvicorn[standard]>=0.34.0 (no upper) and the workspace lock resolves to 0.47.0. The package ceiling <0.42.0 meant the workspace was no longer testing the declared supported range. Bump to <1 so the lock fits within the declared bounds. Also picked up by validate-dependency-bounds: refresh stale orchestrations RC pin in devui dev deps.2026-05-20 09:20:53 +09:00 -
Python: Record actual served model from Azure OpenAI (#5910)
* Record actual served model as response model for Azure OpenAI * Formatting * Fix tests * Fix pipeline error * Comments * Address review: surface served model via ChatResponse.model Apply blocking review feedback from PR #5910: - Use ChatResponse.model / ChatResponseUpdate.model as the source of truth for the Azure x-ms-served-model header value, instead of stashing it in additional_properties and overriding it again in observability. Observability already reads response.model; the chat client now overwrites it post-parse when the served-model header is present. Empirically the Azure Responses API returns the deployment alias in body.model and the actual snapshot (e.g. gpt-5-nano-2025-08-07) in this header. - Move the AZURE_OPENAI_SERVED_MODEL_HEADER constant out of observability.py and into RawOpenAIChatClient (as the SERVED_MODEL_HEADER ClassVar). The header is Azure-OpenAI-Responses-API-specific so observability does not need to know about it. - Revert the streaming text_format path to client.responses.stream(...) and drop the _pydantic_model_to_text_format_param helper. That helper imported from openai.lib._parsing._responses (a private SDK path) and the swap to responses.create(stream=True) dropped client-side output_parsed for structured-output streaming. The streaming-with-text_format path is the only one that does not surface the served-model header - documented inline. - Wrap the raw streaming responses in async with so the underlying socket closes deterministically (continuation_token retrieve + create paths). - Fix the empty-string / whitespace-only header at the source by stripping in _extract_served_model and returning None when nothing remains. - Revert unrelated formatting-only churn in _skills.py and test_mcp.py. - Update unit tests to assert against chat_response.model / update.model and add an aggregated streaming assertion plus a pin that the streaming-with-text_format path does not get the header. Verified end-to-end against Azure OpenAI Responses API: deployment alias gpt-5-nano now reports gpt-5-nano-2025-08-07 as ChatResponse.model in both the non-streaming and streaming paths. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: preserve streaming structured output finalization Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639 Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * refactor: name streaming response finalizer Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639 Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * fix: capture streaming response format after prepare Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639 Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * refactor: clarify streaming response format capture Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639 Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * test: use public API for streaming structured output Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639 Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * Inline the served-model header override at its two call sites The `_apply_served_model_header` helper was a 1-line wrapper around `_extract_served_model`. Inlining the `if served_model is not None: ...` matches the pattern already used in the streaming paths and folds the explanatory docstring onto `_extract_served_model` (which is now the single place that knows about the header). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
2026-05-19 06:38:53 +00:00 -
Python: Improve the handling of intermediate outputs for workflows and orchestrations (#5623)
* Improve the handling of intermediate outputs for workflows and orchestrations * Address PR review feedback on intermediate output forwarding - Switch workflow.as_agent() forwarding to an explicit allowlist of {output, intermediate, data, request_info} so orchestration-internal events (group_chat, handoff_sent, magentic_orchestrator) stay inside the workflow instead of leaking into agent responses via str(data) coercion. - Stop raising on intermediate AgentResponseUpdate in non-streaming run(); surface the partial as a Message with text_reasoning content. The defensive raise still applies to terminal output events, where Update payloads would corrupt message ordering. - Extend the DevUI workflow-event mapper so intermediate yields wrapping plain strings, Messages, and list[Message] render as visible output items instead of generic completed-trace events. - Add orchestration coverage for GroupChat, Handoff, and Magentic builders (default vs intermediate_outputs=True; structural where end-to-end is heavy). * Lift output-designation policy into a value type Replace the ``Workflow._output_executors`` list and the ``RunnerContext.should_label_as_intermediate`` Protocol method with a single immutable ``OutputDesignation`` value type owned by ``Workflow``. Thread the designation as a parameter through the existing call chain (Runner -> EdgeRunner -> Executor -> WorkflowContext) so ``yield_output`` consults the threaded snapshot directly rather than calling back into the runner context. Removes the ``InProcRunnerContext._workflow`` back-reference and the ``WorkflowBuilder.build()`` assignment that wired it up. Adds the public predicate ``Workflow.is_terminal_executor(executor_id)`` for external observers; ``OutputDesignation`` itself stays package-internal. Key decisions - ``OutputDesignation.designated`` is ``frozenset[str] | None`` -- ``None`` preserves legacy "every yield is type='output'" behavior, any frozenset (including empty) opts into strict mode. The ``DeprecationWarning`` for legacy mode at build time is unchanged. - ``output_designation`` is an optional parameter on ``Runner``, ``EdgeRunner.send_message``, ``EdgeRunner._execute_on_target``, ``Executor.execute``, ``Executor._create_context_for_handler``, and ``WorkflowContext.__init__``. Each defaults to legacy ``OutputDesignation()`` so direct callers (Azure Functions ``CapturingRunnerContext``, ``test_runner`` recording fixtures) keep working without ceremony. - The workflow-level filter in ``_run_core`` reads ``self._output_designation`` live, preserving today's semantics where mutating the designation after build still affects subsequent runs (used by two existing tests). - ``Workflow.to_dict()`` continues to emit ``"output_executors": list[str] | None`` (sorted from the frozenset). Checkpoint format unchanged. Files changed - _workflow.py: add ``OutputDesignation`` dataclass; replace ``_output_executors`` with ``_output_designation``; add ``is_terminal_executor``; delete ``_should_yield_output_event``. - _runner_context.py: drop ``should_label_as_intermediate`` Protocol method and ``InProcRunnerContext`` impl; drop ``_workflow`` back-reference. - _workflow_builder.py: remove ``context._workflow = workflow`` assignment. - _runner.py, _edge_runner.py, _executor.py, _workflow_context.py: thread ``output_designation`` parameter through the call chain. - tests/workflow/test_output_designation.py (new): three-state coverage of the value type plus the public predicate delegation. - tests/workflow/test_workflow_builder.py, test_validation.py, test_workflow.py, test_runner.py and orchestrations/tests/test_orchestration_intermediate_vs_terminal.py: switch probes from ``_output_executors`` set checks to ``get_output_executors`` / ``is_terminal_executor``; update two post-build mutation tests to set ``_output_designation`` instead. Verification - core/tests/workflow/, orchestrations/tests/, azurefunctions/tests/: 1119 passed, 42 skipped, 2 xfailed. - ``uv run poe lint``: clean. - ``uv run poe typing``: only the pre-existing ``_AGENT_FORWARDED_EVENT_TYPES`` pyright warning from394bcd607remains. Notes for next iteration - The builder's own ``_output_executors`` attribute (``list[Executor | SupportsAgentRun]``) is intentionally untouched; the issue scoped the rename to the workflow attribute. - Adjacent review candidates (twin ``WorkflowAgent`` translators, ``_AGENT_FORWARDED_EVENT_TYPES`` kind classifier, ``_event_origin_context`` ContextVar removal, ``WorkflowEvent`` ADT split, legacy-mode removal) remain out of scope. * Add explicit workflow output designation Key decisions - Extend the internal OutputDesignation value type from terminal-only membership to output/intermediate/hidden classification. Legacy mode remains outputs=None, so workflows built without output_executors or intermediate_executors still label every yield_output as type='output'. - WorkflowBuilder now accepts intermediate_executors. Providing either designation enters explicit mode; output executors emit output, intermediate executors emit intermediate, and unlisted yield_output payloads are hidden from caller-facing events while remaining in executor_completed data. - Empty explicit designation, duplicate entries, overlaps, unknown executors, and designated executors without workflow output annotations fail build validation. Existing orchestration builders pass intermediate-capable participants through intermediate_executors to preserve current intermediate_outputs behavior until participant-oriented designation lands. Files changed - packages/core/agent_framework/_workflows/_workflow.py, _workflow_builder.py, _workflow_context.py, _validation.py, _events.py - packages/core/tests/workflow/test_output_designation.py, test_output_executors_contract.py, test_strict_mode_event_labeling.py, test_validation.py, test_workflow.py, test_workflow_agent_intermediate.py - packages/orchestrations/agent_framework_orchestrations/_sequential.py, _concurrent.py, _group_chat.py, _magentic.py - packages/core/AGENTS.md Verification - uv run pytest packages/core/tests/workflow packages/orchestrations/tests packages/devui/tests/devui/test_mapper.py -q - uv run pytest packages/azurefunctions/tests -q - uv run poe lint - uv run poe typing fails only on pre-existing packages/core/agent_framework/_workflows/_agent.py _AGENT_FORWARDED_EVENT_TYPES private-use pyright error. Notes for next iteration - issues/03-core-workflow-explicit-designation.md was moved to issues/done but issues/ remains untracked and intentionally excluded from this commit. - Slice 4 should tighten workflow.as_agent() mapping for hidden emissions and streaming-only update payloads; Slice 5 should replace orchestration intermediate_outputs with participant-oriented designation. * Tighten workflow-as-agent output mapping Key decisions - Treat AgentResponseUpdate as a streaming-only payload across the workflow.as_agent() adapter, so non-streaming agent runs now reject both terminal output and intermediate workflow events carrying updates. - Keep streaming classification behavior explicit: terminal update payloads remain normal text content, while intermediate update payloads are rewritten to text_reasoning content. - Add explicit-mode coverage proving hidden yield_output emissions do not appear in non-streaming AgentResponse messages or streaming AgentResponseUpdate chunks. Files changed - packages/core/agent_framework/_workflows/_agent.py - packages/core/tests/workflow/test_workflow_agent_intermediate.py Verification - uv run pytest packages/core/tests/workflow/test_workflow_agent_intermediate.py -q - uv run pytest packages/core/tests/workflow/test_workflow_agent.py packages/core/tests/workflow/test_workflow_agent_intermediate.py -q - uv run pytest packages/core/tests/workflow packages/orchestrations/tests packages/devui/tests/devui/test_mapper.py -q - uv run poe lint - uv run poe typing fails only on the pre-existing packages/core/agent_framework/_workflows/_agent.py _AGENT_FORWARDED_EVENT_TYPES private-use pyright error. Blockers or notes for next iteration - issues/04-workflow-as-agent-output-mapping.md was moved to issues/done/ but issues/ remains untracked and intentionally excluded from this commit. - Slice 5 should replace orchestration intermediate_outputs with participant-oriented designation. * Add orchestration participant output designation Key decisions - Replace orchestration intermediate_outputs with participant-oriented output_participants and intermediate_participants across Sequential, Concurrent, GroupChat, Magentic, and Handoff builders. - Keep synthetic final executors terminal by default for Concurrent, GroupChat, and Magentic; keep Sequential's final participant terminal by default; keep Handoff participants terminal by default. - Centralize participant designation validation for empty explicit designation, duplicates, overlaps, and unknown participants, then map validated participants to workflow output/intermediate executors. Files changed - packages/orchestrations/agent_framework_orchestrations/_participant_designation.py - packages/orchestrations/agent_framework_orchestrations/_sequential.py - packages/orchestrations/agent_framework_orchestrations/_concurrent.py - packages/orchestrations/agent_framework_orchestrations/_group_chat.py - packages/orchestrations/agent_framework_orchestrations/_magentic.py - packages/orchestrations/agent_framework_orchestrations/_handoff.py - packages/orchestrations/tests/test_orchestration_intermediate_vs_terminal.py - packages/orchestrations/tests/test_magentic.py Blockers or notes for next iteration - issues/05-orchestration-participant-designation.md was moved to issues/done/ but issues/ remains untracked and intentionally excluded from this commit. - Slice 7 should migrate samples and docs away from intermediate_outputs to the new participant designation API. - uv run poe typing still fails only on the pre-existing packages/core/agent_framework/_workflows/_agent.py _AGENT_FORWARDED_EVENT_TYPES private-use pyright error. * Migrate samples to explicit output designation Key decisions - Replace sample usage of the removed orchestration intermediate_outputs boolean with participant-oriented intermediate_participants designation. - Update raw workflow guidance to show output_executors together with intermediate_executors, and document that unlisted yields are hidden in explicit designation mode. - Keep orchestration final outputs terminal while streaming designated participant responses as intermediate progress, including workflow.as_agent() samples where intermediates map to text_reasoning content. - Refresh workflow and orchestration README guidance plus the changelog reference so public docs no longer point users at intermediate_outputs. Files changed - CHANGELOG.md - packages/orchestrations/README.md - samples/README.md - samples/03-workflows/README.md - samples/03-workflows/control-flow/intermediate_vs_terminal_outputs.py - samples/03-workflows/orchestrations/README.md - samples/03-workflows/orchestrations/group_chat_agent_manager.py - samples/03-workflows/orchestrations/group_chat_philosophical_debate.py - samples/03-workflows/orchestrations/group_chat_simple_selector.py - samples/03-workflows/orchestrations/magentic.py - samples/03-workflows/orchestrations/magentic_human_plan_review.py - samples/03-workflows/orchestrations/sequential_chain_only_agent_responses.py - samples/03-workflows/agents/group_chat_workflow_as_agent.py - samples/03-workflows/agents/magentic_workflow_as_agent.py - samples/03-workflows/agents/sequential_workflow_as_agent.py - samples/semantic-kernel-migration/orchestrations/group_chat.py - samples/semantic-kernel-migration/orchestrations/magentic.py Blockers or notes for next iteration - issues/07-samples-and-docs-explicit-output-designation.md was moved to issues/done/ but issues/ remains untracked and intentionally excluded from this commit. - issues/06-devui-intermediate-event-rendering.md remains present and appears already satisfied by existing DevUI mapper/tests from the prior implementation slice. - PRD-explicit-workflow-output-designation.md remains untracked and intentionally excluded from this commit. * Render DevUI intermediate workflow outputs Key decisions - Preserve workflow output designation metadata on visible DevUI output messages and text deltas so intermediate/data emissions remain distinguishable from terminal output. - Render intermediate workflow message items in the execution timeline using executor metadata, while excluding them from the final workflow result aggregation. - Keep terminal output message rendering unchanged and retain legacy data events on the intermediate compatibility path. Files changed - packages/devui/agent_framework_devui/_mapper.py - packages/devui/frontend/src/components/features/workflow/execution-timeline.tsx - packages/devui/frontend/src/components/features/workflow/workflow-view.tsx - packages/devui/frontend/src/types/openai.ts - packages/devui/tests/devui/test_mapper.py Blockers or notes for next iteration - issues/06-devui-intermediate-event-rendering.md was moved to issues/done/ but issues/ remains untracked and intentionally excluded from this commit. - PRD-explicit-workflow-output-designation.md remains untracked and intentionally excluded from this commit. - uv run poe typing still fails only on the pre-existing packages/core/agent_framework/_workflows/_agent.py _AGENT_FORWARDED_EVENT_TYPES private-use pyright error. * Fix mypy * Clarify orchestration participant output config * Rename participant output kwargs for clarity output_participants -> final_output_from, intermediate_participants -> intermediate_output_from. The old names read like categories of participant; the new names make it clear the kwarg designates which participants' outputs surface as final vs. intermediate events. * Rename core workflow output kwargs with deprecation shim Adds final_output_from / intermediate_output_from as canonical kwargs on Workflow and WorkflowBuilder. Old output_executors / intermediate_executors kwargs continue to work but emit DeprecationWarning via a shared coalesce helper that also rejects supplying both. Wire-format keys in to_dict() stay as output_executors / intermediate_executors so checkpoint compatibility is preserved. Internal call sites in orchestrations and samples updated to the new names so users following sample code learn the canonical vocabulary; legacy callers still work with a one-shot warning. * Suppress pyright reportPrivateUsage on cross-module sentinel import * Update docstrings * Propagate sub-workflow intermediate outputs, fix handoff/sequential intermediate-only designation, and shore up tests, sample, and docstrings around the intermediate output contract. * Add canonical workflow output_from selection Key decisions:\n- Make output_from the canonical workflow-output allow-list and keep output_executors/final_output_from as deprecated compatibility aliases.\n- Treat empty output_from/intermediate_output_from lists as explicit selections and keep validation responsible for empty, duplicate, overlap, and unknown selections.\n- Remove the branch-only public intermediate_executors WorkflowBuilder kwarg while preserving legacy wire keys in to_dict().\n\nFiles changed:\n- packages/core/agent_framework/_workflows/_workflow.py\n- packages/core/agent_framework/_workflows/_workflow_builder.py\n- packages/core/agent_framework/_workflows/_workflow_context.py\n- packages/core/agent_framework/_workflows/_agent.py\n- packages/core/agent_framework/_workflows/_agent_executor.py\n- packages/core/tests/workflow/* output-selection coverage updates\n- packages/core/AGENTS.md\n- issues/done/001-canonical-list-based-output-selection.md\n\nBlockers/notes:\n- Orchestration builders still pass final_output_from internally; follow-up issue 004 should migrate them to output_from.\n- Legacy omitted-selection behavior and explicit all/all_other literals are left for issues 002 and 003. * Add explicit all workflow output selection Key decisions: - Treat output_from='all' as an explicit workflow-output selection sentinel and expand it at build time to executors with declared workflow output types. - Keep omitted output selections in legacy all-output mode with a deprecation warning that names output_from and intermediate_output_from and points to output_from='all'. - Reject intermediate_output_from='all' at construction because the all-output literal is output-only for this issue. Files changed: - packages/core/agent_framework/_workflows/_workflow_builder.py - packages/core/tests/workflow/test_output_executors_contract.py - issues/done/002-explicit-all-output-and-legacy-migration.md Blockers/notes: - all_other intermediate-output selection remains for issue 003. - Workflow-as-agent/orchestration parity remains for issue 004. * Add all-other intermediate output selection Key decisions: - Treat intermediate_output_from='all_other' as an explicit intermediate-output selection sentinel and expand it at build time after the workflow graph is complete. - Expand all_other to output-capable executors not selected by output_from; omitted or empty output_from selects no workflow outputs, while output_from='all' leaves an empty intermediate selection. - Keep output_from='all_other' invalid so all_other remains intermediate-output-only and runtime classification still receives concrete executor-id sets. Files changed: - packages/core/agent_framework/_workflows/_workflow_builder.py - packages/core/tests/workflow/test_output_executors_contract.py - issues/done/003-all-other-intermediate-output-selection.md Blockers/notes: - Workflow-as-agent and orchestration parity remains for issue 004. - Full documentation updates remain for issue 005. * Add orchestration output selection parity Key decisions: - Expose output_from on sequential, concurrent, group chat, handoff, and magentic builders while keeping final_output_from as a deprecated compatibility alias. - Resolve orchestration participant selections through the same explicit rules as workflows: output_from='all', intermediate_output_from='all_other', hidden unselected participant payloads, and overlap/duplicate/unknown/invalid-literal validation. - Continue preserving documented orchestration defaults by always designating each pattern's terminal internal executor where applicable. Files changed: - packages/orchestrations/agent_framework_orchestrations/_participant_output_config.py - packages/orchestrations/agent_framework_orchestrations/_sequential.py - packages/orchestrations/agent_framework_orchestrations/_concurrent.py - packages/orchestrations/agent_framework_orchestrations/_group_chat.py - packages/orchestrations/agent_framework_orchestrations/_handoff.py - packages/orchestrations/agent_framework_orchestrations/_magentic.py - packages/orchestrations/agent_framework_orchestrations/_orchestration_request_info.py - packages/orchestrations/tests/test_orchestration_intermediate_vs_terminal.py - issues/done/004-workflow-as-agent-and-orchestration-parity.md Blockers/notes: - Full documentation and sample migration wording remains for issue 005. - Existing tests that intentionally use final_output_from now emit the new deprecation warning. * Document workflow output selection contract Key decisions: - Use Workflow Output and Intermediate Output as the developer-facing terms for selected caller-facing emissions. - Document output_from and intermediate_output_from as the canonical API, with output_from as an allow-list and unselected payloads hidden unless explicitly selected as intermediate. - Add scenario and invalid-selection tables for workflow and orchestration docs, including legacy omission warnings, output_from='all', intermediate_output_from='all_other', list selections, invalid literals, overlap, duplicates, unknown selections, and empty explicit selections. - Migrate samples away from final_output_from and output_executors except where compatibility aliases are explicitly documented. Files changed: - packages/core/AGENTS.md - packages/orchestrations/README.md - packages/orchestrations/agent_framework_orchestrations/_handoff.py - packages/orchestrations/agent_framework_orchestrations/_sequential.py - samples/03-workflows/README.md - samples/03-workflows/control-flow/intermediate_vs_terminal_outputs.py - samples/03-workflows/human-in-the-loop/agents_with_approval_requests.py - samples/03-workflows/orchestrations/README.md - samples/04-hosting/foundry-hosted-agents/responses/05_workflows/main.py - scripts/sample_validation/create_dynamic_workflow_executor.py - issues/done/005-document-output-selection-contract.md Blockers/notes: - Direct full Ruff on scripts/sample_validation/create_dynamic_workflow_executor.py still reports pre-existing docstring/print/line-length issues outside this docs migration; syntax-focused checks for changed files pass. - No remaining AFK issue files are present under issues/. * Latest updates * Typing fixes * Cleanup2026-05-19 00:15:25 +00:00 -
Python: Parse YAML block scalars in SKILL.md frontmatter (#5863)
The frontmatter parser previously matched only single-line `key: value` pairs, so block scalar indicators (`|` literal, `>` folded, with chomping `-`/`+`) were silently truncated to the indicator character. Multi-line descriptions like `description: >\n ...` lost their content. Add `_parse_yaml_scalar_value()` which detects block scalar indicators, collects indented continuation lines, strips the common leading indentation, joins per scalar style (newlines for `|`, spaces for `>`), and applies chomping per the YAML 1.2 spec. Update `_extract_frontmatter()` to use the helper for unquoted values. Adds 15 unit tests covering literal/folded styles, all chomping variants, indentation handling, content containing colons, non-description fields, tab indentation, blank-line preservation, and a regression test for plain values. Fixes #5713. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
SergeyMenshykh ·
2026-05-15 09:47:00 +00:00 -
Python: bump package versions for 1.4.0 release (#5872)
* fixes * fixes * Python: bump package versions for 1.4.0 release Cuts the python-1.4.0 release. MINOR bump on the released cohort (agent-framework, agent-framework-core, agent-framework-openai, agent-framework-foundry: 1.3.0 -> 1.4.0), driven by breaking changes in experimental skills API and new features. All 21 beta packages stamp 1.0.0b260514, all 3 alpha packages stamp 1.0.0a260514, and ag-ui remains at 1.0.0rc1 (freshly promoted). Date stamp reflects 2026-05-14 Pacific. - Released cohort: 1.3.0 -> 1.4.0 - Beta packages (21): 1.0.0b260507 -> 1.0.0b260514 - Alpha packages (3): 1.0.0a260507 -> 1.0.0a260514 - ag-ui: stays at 1.0.0rc1 (dep bound updated only) - Inter-package dependency lower bounds updated (>=1.3.0 -> >=1.4.0) - Fix chatkit StructuredInputItem exhaustiveness for openai-chatkit 1.6.4 - Update CHANGELOG compare links - uv.lock refreshed Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-05-15 09:31:03 +09:00 -
Python: forward MCP tool call metadata (#5815)
* Python: forward MCP tool call metadata * fix: preserve MCP tool meta after prompt reload
Yufeng He ·
2026-05-14 21:50:39 +00:00 -
Python: Support list[str] arguments for file-based skill scripts (#5850)
Port of .NET PR #5475. Broadens the args type from dict[str, Any] | None to dict[str, Any] | list[str] | None across the skill script API surface, enabling CLI-style argv forwarding to subprocess scripts. Changes: - SkillScript.run(), InlineSkillScript.run(), FileSkillScript.run(): widen args type; InlineSkillScript rejects list with TypeError - FileSkillScript.parameters_schema: returns array-of-strings schema - FileSkill.content: appends <scripts> block with parameters_schema - SkillScriptRunner protocol: widen args type - SkillsProvider._run_skill_script: widen args type - run_skill_script tool schema: accept object, array, or null - subprocess_script_runner sample: accept list[str], reject dict - class_based_skill sample: fix missing SkillFrontmatter wrapper - Standardize 'folder' to 'directory' in docstrings (#5712) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-05-14 17:58:10 +00:00 -
[BREAKING] Python: Align file skill folder discovery with agentskills.io spec (#5807)
* Align Python FileSkillsSource with agentskills.io spec Update FileSkillsSource to scan spec-defined subdirectories instead of recursive rglob for resource and script discovery: - Resources: scan 'references/' and 'assets/' (was: entire skill tree) - Scripts: scan 'scripts/' (was: entire skill tree) - Add resource_directories and script_directories parameters for customization, with '.' root indicator for skill root files - Add directory validation: reject '..' traversal, absolute paths, empty names; normalize separators and deduplicate directories - Non-recursive scanning within each configured directory (top-level only) - Containment check validates files against target directory, not just skill root, for stronger path-traversal defense - Case-insensitive directory deduplication via os.path.normcase() - Cross-platform absolute path rejection in directory validation - Sort discovery results for stable ordering - Update SkillsProvider.from_paths() to pass new parameters through - Update all tests for new subdirectory-scoped discovery behavior Resolves #5711. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: tighten path validation and add containment guard - Narrow Windows absolute path check to proper drive-root pattern (re.match r'^[A-Za-z]:[/\\]') to avoid rejecting valid POSIX names - Add _is_path_within_directory guard before _has_symlink_in_path in both discovery methods to prevent ValueError on escaped paths Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Log warning on OSError during directory listing in skill discovery Address review comment: _discover_resource_files and _discover_script_files previously swallowed OSError silently when iterdir() failed. Now log a warning so permission errors and transient FS failures are visible instead of making resource/script directories silently disappear. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-05-14 10:28:22 +00:00 -
Python: Strip server-issued response item IDs under storage (#3295) (#5690)
Fixes microsoft/agent-framework#3295. When the OpenAI Responses chat client sends a request that carries previous_response_id / conversation_id / conversation, the server already has the prior turn's response items and rejects duplicates with "Duplicate item found with id fc_xxx". The chat client was re-sending them inline whenever the input messages still carried the items in additional_properties (workflow replay, history providers, etc.), which broke any tool-using agent with persistent history. Decisions: - Single chokepoint: _prepare_message_for_openai. When the resulting request uses service-side storage, drop function_call, reasoning, approval-request/response, and local-shell-call items from the wire input. Keep function_result with its call_id; the server pairs it to the prior function_call via that key. - function_result is preserved unconditionally except for the local-shell variant, which carries its own server-issued item id. - No public API change. Wire format change is subtractive and only on requests that would otherwise 400. - Re-pointed the strict-xfail in test_full_conversation.py from #4047 to #3295. Kept xfail because the test asserts executor-level session-id clearing, which is the defense-in-depth half tracked by 3295-03; this slice closes the wire-level half. Files: - python/packages/openai/agent_framework_openai/_chat_client.py: strip rule applied alongside the existing reasoning-item branch. - python/packages/openai/tests/openai/test_openai_chat_client.py: four new tests pin the contract (function_call, approval, local-shell-call stripped under storage; everything kept without storage). Updated pre-existing tests that exercised the storage-on path to either pass request_uses_service_side_storage=False explicitly or assert the new strip behavior. - python/packages/foundry/tests/foundry/test_foundry_chat_client.py: same explicit storage-off opt-in for the inherited test. - python/packages/core/tests/workflow/test_full_conversation.py: re-pointed xfail reason to #3295 and the executor-level follow-up. Notes for next iteration: - 3295-01 (HITL wire-format validation against live OpenAI/Foundry) was not run; it requires the user's API credentials. The PRD design is locked but the empirical confirmation is still pending. If script 3 fails on either provider, this slice may need to be revisited. - 3295-03 (clear service_session_id in AgentExecutor on full-history replay) remains open. After it lands the xfail in test_full_conversation.py can be removed. - pytest was not run in this iteration because uv-based pytest commands required interactive approval. Validation rests on careful reading; next iteration should run the openai + core test suites.
2026-05-13 22:09:04 +00:00 -
[Python] [Breaking] Extract skill spec metadata into SkillFrontmatter (#5775)
* Fix Skill docstring consistency and spelling - Add ClassSkill to Skill class docstring concrete implementations list - Normalize 'defence' to 'defense' for American English consistency - Remove extra blank line in InlineSkill docstring example Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix E501 line-too-long lint error in test_skills.py Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix stale test section header to reflect SkillFrontmatter API Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix metadata children overriding top-level frontmatter fields Scope YAML_KV_RE to column-0 keys only so indented children under metadata: are not mistakenly parsed as top-level fields. Add regression test and spec fields to sample SKILL.md files. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-05-13 20:35:52 +00:00 -
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>
2026-05-13 20:09:59 +00:00 -
Python: bump package versions for 1.3.0 release (#5706)
* Python: bump package versions for 1.3.0 release MINOR bump on the released cohort (agent-framework, agent-framework-core, agent-framework-openai, agent-framework-foundry: 1.2.2 -> 1.3.0). All 22 beta packages stamp 1.0.0b260507 and all 3 alpha packages stamp 1.0.0a260507 per the lockstep convention. Date stamp reflects 2026-05-07 Pacific. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review: bump foundry_local openai floor, fix devui orchestrations pin, clarify breaking scope - foundry_local: bump agent-framework-openai lower bound from >=1.1.0 to >=1.3.0 - devui: update stale agent-framework-orchestrations dev pin from 1.0.0b260402 to 1.0.0b260507 - CHANGELOG: clarify [BREAKING] applies to experimental skills API only Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Revert devui orchestrations pin to 1.0.0b260402 to avoid breaking DevUI Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-05-08 08:57:02 +09:00 -
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>
2026-05-07 19:39:12 +00:00 -
Python: Fix
MCPStreamableHTTPToolleakingasyncio.CancelledErrorwhen 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>
2026-05-07 17:58:30 +00:00 -
Python: Add
base_urlparameter toAnthropicClientandRawAnthropicClient(#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>
2026-05-07 17:57:09 +00:00 -
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>
2026-05-07 02:58:38 +00:00 -
Python: Remove bespoke Foundry toolbox helpers; standardize on MCP for toolbox consumption (#5671)
* Remove Foundry toolbox helpers; standardize on MCP for toolbox consumption - Remove RawFoundryChatClient.get_toolbox() and its fetch_toolbox import - Remove fetch_toolbox, select_toolbox_tools, get_toolbox_tool_name, get_toolbox_tool_type, FoundryHostedToolType, ToolboxToolSelectionInput from agent_framework_foundry._tools - Remove ExperimentalFeature.TOOLBOXES from _feature_stage.py (no consumers) - Drop toolbox re-exports from agent_framework_foundry/__init__.py and agent_framework.foundry namespace - Update _sanitize_foundry_response_tool docstring to remove toolbox framing; sanitization logic itself is unchanged - Update _agent.py docstring: 'toolbox-fetched MCP' → 'hosted MCP' - Delete tests/test_toolbox.py (all tests covered removed helpers) - Update test_foundry_chat_client.py: rename/redoc tests that mentioned toolbox but test sanitization that remains - Delete foundry_chat_client_with_toolbox.py (bespoke toolbox API sample) - Delete foundry_toolbox_context_provider.py (relied on select_toolbox_tools) - Rename foundry_chat_client_with_toolbox_mcp.py → foundry_chat_client_with_toolbox.py (canonical MCP pattern) - Rewrite 04_foundry_toolbox/main.py to use MCPStreamableHTTPTool - Update provider/README, context_providers/README, 04_foundry_toolbox/README Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(samples): update 06_files sample to consume toolbox via MCP (#5670) Replace removed get_toolbox/select_toolbox_tools APIs with MCPStreamableHTTPTool, using allowed_tools=["code_interpreter"] to select only the code interpreter from the toolbox endpoint. Update .env.example and README to use FOUNDRY_TOOLBOX_ENDPOINT instead of TOOLBOX_NAME. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(foundry): remove non-existent toolbox helper APIs from README (#5670) Remove the 'fetch, optionally filter, and pass tools directly' pattern from the FoundryChatClient toolbox documentation, as select_toolbox_tools and get_toolbox were removed. Only the MCP endpoint pattern is documented. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(foundry): remove residual toolbox docstring references and reproduction report Remove REPRODUCTION_REPORT.md (workflow artifact that should not be committed), and update two remaining docstring references that still said 'toolbox reads' /'toolbox definition' after the toolbox helpers were removed. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Remove bespoke Foundry toolbox helpers; standardize on MCP for toolbox consumption Fixes #5670 * fix(#5670): resolve toolbox endpoint from TOOLBOX_NAME fallback; add namespace regression tests - Add _resolve_toolbox_endpoint() helper in 04_foundry_toolbox/main.py and 06_files/main.py that prefers FOUNDRY_TOOLBOX_ENDPOINT but falls back to deriving the MCP URL from FOUNDRY_PROJECT_ENDPOINT + TOOLBOX_NAME — fixing the startup KeyError when agents are deployed via azd provision (which injects TOOLBOX_NAME, not FOUNDRY_TOOLBOX_ENDPOINT). - Update 04_foundry_toolbox/.env.example to use FOUNDRY_TOOLBOX_ENDPOINT (consistent with 06_files). - Add TOOLBOX_NAME env var to 06_files/agent.yaml so deployed agents have it available for the fallback derivation. - Update both READMEs to document the two ways to supply the toolbox endpoint. - Add test_foundry_namespace_no_longer_exposes_toolbox_helpers() with negative assertions for FoundryHostedToolType, get_toolbox_tool_name, get_toolbox_tool_type, and select_toolbox_tools — guarding against accidental re-introduction of removed symbols. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(samples): fail fast on empty FOUNDRY_TOOLBOX_ENDPOINT; add unit tests Addresses review feedback for #5670: - In _resolve_toolbox_endpoint() (04_foundry_toolbox/main.py and 06_files/main.py) change the walrus-operator check from a truthy test to an explicit 'is not None' guard. An explicitly set empty string now raises ValueError immediately with a clear message instead of silently falling through to the fallback URL construction. - Add tests/samples/hosting/test_toolbox_endpoint.py covering both sample modules: (a) FOUNDRY_TOOLBOX_ENDPOINT set → returned as-is (b) FOUNDRY_TOOLBOX_ENDPOINT set to empty string → ValueError (c) fallback constructs URL from FOUNDRY_PROJECT_ENDPOINT + TOOLBOX_NAME, stripping trailing slashes (d) neither variable group set → KeyError Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback: remove extraneous test and docstring content - Remove test_foundry_namespace_no_longer_exposes_toolbox_helpers (no longer warranted) - Remove docstring from _agent.py _prepare_tools_for_openai (extraneous) - Trim _chat_client.py _prepare_tools_for_openai docstring to one-liner (toolbox references no longer relevant) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: remove remaining extraneous docstring from RawFoundryChatClient._prepare_tools_for_openai Address review comment on PR #5671: reviewer noted the description isn't warranted now that toolbox helpers have been removed. Matches the pattern in RawFoundryAgentChatClient which has no docstring. 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>
2026-05-06 23:56:16 +00:00 -
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>
2026-05-06 09:45:06 +00:00 -
Python: Add Python parity for InvokeMcpTool in declarative workflow (#5630)
* Add Python parity for HttpRequestAction in declarative workflow * Ran pyupgrade and pright to fix CI issues * Fix conversation ID dot parsing for http executor * Removed unnecessary export command * Initial implementation of invoke mcp tool in python * Update sample to support require approval to be toggled by environment variable. * Fix cache and PR comments * Update python/samples/03-workflows/declarative/invoke_mcp_tool/main.py Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> --------- Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
Peter Ibekwe ·
2026-05-05 20:16:03 +00:00 -
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>
2026-05-05 18:08:08 +00:00 -
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>
2026-05-05 10:09:19 +00:00 -
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>
2026-05-05 10:06:16 +00:00 -
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>
2026-05-05 08:39:41 +00:00 -
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>
2026-05-04 21:19:50 +00:00 -
Python: Add Python parity for HttpRequestAction in declarative workflow (#5599)
* Add Python parity for HttpRequestAction in declarative workflow * Ran pyupgrade and pright to fix CI issues * Fix conversation ID dot parsing for http executor * Removed unnecessary export command
2026-05-01 23:04:07 +00:00 -
Python: Support OpenAI and Gemini
allowed_toolstool 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>
2026-04-29 17:43:47 +00:00 -
Python: bump package versions for 1.2.2 release (#5561)
* Python: bump package versions for 1.2.2 release PATCH bump (1.2.1 -> 1.2.2) for the released cohort. Five PRs land in this window: - agent-framework-openai: fix file_search citations breaking the assistant- message history roundtrip (#5557) — drives the released-tier PATCH - agent-framework-orchestrations: [BREAKING] standardize orchestration terminal outputs as AgentResponse (#5301) - agent-framework-core, agent-framework-declarative: preserve Workflow.run() shared state across calls, accept list[Message] in declarative start executor, and coerce Enum values when serializing PowerFx symbols (#5531) - agent-framework-foundry-hosting: add hosted Durable Workflow support (#5531) - agent-framework-azure-contentunderstanding: new alpha package — Azure AI Content Understanding context provider (#4829) - dependencies: workspace package dependency refresh (#5555) Per lockstep convention, all 21 beta packages stamp 1.0.0b260429 and all 4 alpha packages (now including the new contentunderstanding) stamp 1.0.0a260429. Date stamp reflects 2026-04-29 Pacific. Every non-core package floor on agent-framework-core is raised to >=1.2.2; the new contentunderstanding package's stale >=1.0.0 floor is brought into line. Two follow-on fixes bundled to keep validate-dependency-bounds-test green at lowest-direct resolution: - Bump agent-framework-azure-contentunderstanding's azure-ai-content understanding lower bound from >=1.0.0 to >=1.0.1 (1.0.0 ships without proper typing — pyright reports 65 unknown-type errors) - Add pyright ignore comments to core/foundry/__init__.pyi for the new alpha package's type-stub imports, since alpha packages are not in core's [all] extra and therefore aren't installed at lowest-direct * Python: add #5552 to 1.2.2 CHANGELOG Add the streaming-span observability fix to the Fixed section. PR is on upstream/main but not yet pulled into origin/main; the code itself will land via the PR merge. * Python: address PR #5561 review feedback on dependency bounds Two packaging fixes flagged in review: 1. agent-framework-azure-contentunderstanding: add agent-framework-foundry as a runtime dependency. The package's README directs users to `pip install agent-framework-azure-contentunderstanding --pre` and the basic example imports `FoundryChatClient` from `agent_framework.foundry`, so the documented install path was failing with ImportError. Pulling agent-framework-foundry into deps makes the advertised entry path self-contained. 2. agent-framework-foundry: bump agent-framework-openai lower bound from >=1.1.0 to >=1.2.2,<2. Foundry imports private modules from agent_framework_openai (`_chat_client.py:22`, `_agent.py:34`), so resolvers were free to pair foundry==1.2.2 with older OpenAI versions that lack this release's coordinated Responses/history fix. Lockstep the floor with the released cohort to prevent mismatched installs. Both changes pass `validate-dependency-bounds-test` lower + upper at their respective packages.
2026-04-29 17:51:48 +09:00 -
Python: Fix spans not correctly nested when using streaming (#5552)
* Fix spans not correctly nested when using streaming * fix pre commit * Address comments
2026-04-29 08:21:28 +00:00 -
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>
2026-04-29 00:51:49 +00:00 -
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>
2026-04-29 00:35:36 +00:00 -
[Python] Add agent-framework-azure-ai-contentunderstanding package (#4829)
* feat: add agent-framework-azure-contentunderstanding package Add Azure Content Understanding integration as a context provider for the Agent Framework. The package automatically analyzes file attachments (documents, images, audio, video) using Azure CU and injects structured results (markdown, fields) into the LLM context. Key features: - Multi-document session state with status tracking (pending/ready/failed) - Configurable timeout with async background fallback for large files - Output filtering via AnalysisSection enum - Auto-registered list_documents() and get_analyzed_document() tools - Supports all CU modalities: documents, images, audio, video - Content limits enforcement (pages, file size, duration) - Binary stripping of supported files from input messages Public API: - ContentUnderstandingContextProvider (main class) - AnalysisSection (output section selector enum) - ContentLimits (configurable limits dataclass) Tests: 46 unit tests, 91% coverage, all linting and type checks pass. * fix: update CU fixtures with real API data, fix test assertions - Replace synthetic fixtures with real CU API responses (sanitized) - Update test assertions to match real data (Contoso vs CONTOSO, TotalAmount vs InvoiceTotal, field values from real analysis) - Add --pre install note in README (preview package) - Document unenforced ContentLimits fields (max_pages, duration) * chore: add connector .gitignore, update uv.lock * refactor: rename to azure-ai-contentunderstanding, fix CI issues Align naming with Azure SDK convention and AF pattern: - Directory: azure-contentunderstanding -> azure-ai-contentunderstanding - PyPI: agent-framework-azure-contentunderstanding -> agent-framework-azure-ai-contentunderstanding - Module: agent_framework_azure_contentunderstanding -> agent_framework_azure_ai_contentunderstanding CI fixes: - Inline conftest helpers to avoid cross-package import collision in xdist - Remove PyPI badge and dead API reference link from README (package not published yet) * feat: add samples (document_qa, invoice_processing, multimodal_chat) - document_qa.py: Single PDF upload, CU context provider, follow-up Q&A - invoice_processing.py: Structured field extraction with prebuilt-invoice - multimodal_chat.py: Multi-file session with status tracking - Add ruff per-file-ignores for samples/ directory - Update README with samples section, env vars, and run instructions * feat: add remaining samples (devui_multimodal_agent, large_doc_file_search) - S3: devui_multimodal_agent/ — DevUI web UI with CU-powered file analysis - S4: large_doc_file_search.py — CU extraction + OpenAI vector store RAG - Update README and samples/README.md with all 5 samples * feat: add file_search integration for large document RAG Add FileSearchConfig — when provided, CU-extracted markdown is automatically uploaded to an OpenAI vector store and a file_search tool is registered on the context. This enables token-efficient RAG retrieval for large documents without users needing to manage vector stores manually. - FileSearchConfig dataclass (openai_client, vector_store_name) - Auto-create vector store, upload markdown, register file_search tool - Auto-cleanup on close() - When file_search is enabled, skip full content injection (use RAG instead) - Update large_doc_file_search sample to use the integration - 4 new tests (50 total, 90% coverage) * fix: add key-based auth support to all samples Follow established AF pattern: check for API key env var first, fall back to AzureCliCredential. Supports AZURE_OPENAI_API_KEY and AZURE_CONTENTUNDERSTANDING_API_KEY environment variables. * FEATURE(python): add analyzer auto-detection, file_search RAG, and lazy init _context_provider.py: - Make analyzer_id optional (default None) with auto-detection by media type prefix: audio->audioSearch, video->videoSearch, else documentSearch - Add _ensure_initialized() for lazy client creation in before_run() - Add FileSearchConfig-based vector store upload - Fix: background-completed docs in file_search mode now upload to vector store instead of injecting full markdown into context messages - Add _pending_uploads queue for deferred vector store uploads devui_file_search_agent/ (new sample): - DevUI agent combining CU extraction + OpenAI file_search RAG azure_responses_agent (existing sample fix): - Add AzureCliCredential support and AZURE_AI_PROJECT_ENDPOINT fallback Tests (19 new), Docs updated (AGENTS.md, README.md) * feat(cu): MIME sniffing, media-aware formatting, unified timeout, vector store expiration - Add three-layer MIME detection (fast path → filetype binary sniff → filename fallback) to handle unreliable upstream MIME types (e.g. mp4 sent as application/octet-stream). Adds filetype>=1.2,<2 dependency. - Media-aware output formatting: video shows duration/resolution + all fields as JSON; audio promotes Summary as prose; document unchanged. - Unified timeout for all media types (removed file_search special-case that waited indefinitely for video/audio). All files use max_wait with background polling fallback. - Vector store created with expires_after=1 day as crash safety net. - Add 8 MIME sniffing tests (TestMimeSniffing class). * fix: merge all CU content segments for video/audio analysis CU's prebuilt-videoSearch and prebuilt-audioSearch analyzers split long media files into multiple `contents[]` segments. Previously, `_extract_sections()` only read `contents[0]`, causing truncated duration, missing transcript, and incomplete fields for any video/audio longer than a single scene. Now iterates all segments and merges: - duration: global min(startTimeMs) → max(endTimeMs) - markdown: concatenated with `---` separators - fields: same-named fields collected into per-segment list - metadata (kind, resolution): taken from first segment Single-segment results (documents, short audio) are unaffected. Update test fixture to realistic 3-segment video structure and expand assertions to verify multi-segment merging. Add documentation for multi-segment processing and speaker diarization limitation. * refactor: improve CU context provider docs and remove ContentLimits - Improve class docstring: clarify endpoint (Azure AI Foundry URL with example), credential (AzureKeyCredential vs Entra ID), and analyzer_id (prebuilt/custom with auto-selection behavior and reference links) - Add SUPPORTED_MEDIA_TYPES comments explaining MIME-based matching behavior and add missing file types per CU service docs - Use namespaced logger to align with other packages - Remove ContentLimits and related code/tests - Rename DEFAULT_MAX_WAIT to DEFAULT_MAX_WAIT_SECONDS for clarity * feat: support user-provided vector store in FileSearchConfig - Add vector_store_id field to FileSearchConfig (None = auto-create) - Track _owns_vector_store to only delete auto-created stores on close() - Remove vector_store_name; use internal _DEFAULT_VECTOR_STORE_NAME - Add inline comments for private state fields - Document output_sections default in docstring - Update AGENTS.md, samples, and tests * fix: remove ContentLimits from README code block * refactor: create CU client in __init__ instead of __aenter__ Follow Azure AI Search provider pattern: create the client eagerly in __init__, make __aenter__ a no-op. This ensures __aexit__/close() is always safe to call and eliminates the _ensure_initialized() workaround. * docs: add file_search param to class docstring * feat: introduce FileSearchBackend abstraction for cross-client support Replace direct OpenAI client usage with FileSearchBackend ABC: - OpenAIFileSearchBackend: for OpenAIChatClient (Responses API) - FoundryFileSearchBackend: for FoundryChatClient (Azure Foundry) - Shared base _OpenAICompatBackend for common vector store CRUD FileSearchConfig now takes a backend instead of openai_client. Factory methods from_openai() and from_foundry() for convenience. BREAKING: FileSearchConfig(openai_client=...) -> FileSearchConfig.from_openai(...) * refactor: FileSearchBackend abstraction + caller-owned vector store * fix: file_search reliability and sample improvements - Poll vector store indexing (create_and_poll) to ensure file_search returns results immediately after upload - Set status to failed when vector store upload fails - Skip get_analyzed_document tool in file_search mode to prevent LLM from bypassing RAG - Simplify sample auth: single credential, direct parameters - Use from_foundry backend for Foundry project endpoints * perf: set max_num_results=10 for file_search to reduce token usage * fix: move import to top of file (E402 lint) * chore: remove unused imports * fix: align azure-ai-contentunderstanding with MAF coding conventions - Add module-level docstrings to __init__.py and _context_provider.py - Use Self return type for __aenter__ (with typing_extensions fallback) - Use explicit typed params for __aexit__ signature - Add sync TokenCredential to AzureCredentialTypes union - Pass AGENT_FRAMEWORK_USER_AGENT to ContentUnderstandingClient - Remove unused ContentLimits from public API and tests - Fix FileSearchConfig tests to match refactored backend API - Fix lifecycle tests to match eager client initialization * refactor: improve CU context provider API surface and fix CI - Refactor _analyze_file to return DocumentEntry instead of mutating dict - Remove TokenCredential from AzureCredentialTypes (fixes mypy/pyright CI) - Remove OpenAIFileSearchBackend/FoundryFileSearchBackend from public API (internal to FileSearchConfig factory methods) - Remove DocumentStatus from public exports (implementation detail) - Update file_search comments to reflect backend-agnostic design - Add DocumentStatus enum, analysis/upload duration tracking - Add combined timeout for CU analysis + vector store upload * fix: improve file_search samples and move tool guidelines to context provider - Delete redundant devui_file_search_agent sample (duplicate of azure_openai variant) - Move tool usage guidelines from sample agent instructions into context provider (extend_instructions in step 6, applied automatically for all file_search users) - Fix file_search purpose: use from_foundry() for Azure OpenAI (purpose="assistants") - Add filename hint in upload instructions for targeted file_search queries - Reduce max_num_results from 10 to 3 in both devui samples - Simplify agent instructions in both samples (remove tool-specific guidance) * feat: improve source_id, integration tests, and content assertions - Rename DEFAULT_SOURCE_ID to "azure_ai_contentunderstanding" (matches azure_ai_search convention) - Improve source_id docstring to describe default value - Clarify _detect_and_strip_files docstring (CU-supported files) - Add invoice.pdf test fixture from Azure CU samples repo - Refactor integration tests to use invoice.pdf directly (assert instead of skip when fixture missing) - Add URI content test (Content.from_uri with external URL) - Add "CONTOSO LTD." content assertion to all integration tests - Use max_wait=None in integration tests (wait until complete) * feat: reject duplicate filenames, add integration tests and sample comments - Reject duplicate document keys in before_run (skip + warn LLM to rename) - Update _derive_doc_key docstring to document uniqueness constraint - Add unit tests for duplicate filename rejection (cross-turn and same-turn) - Add integration test for data URI content (from_uri with base64) - Add integration test for background analysis (max_wait timeout + resolve) - Add filename recommendation comments to all samples' Content.from_data() * chore: improve doc key derivation, comments, and README - Replace hash-based doc key with uuid4 for anonymous uploads (O(1), no payload traversal) - Remove hashlib import (no longer needed) - Add File Naming section to README (filename importance, duplicate rejection) - Improve inline comments (_derive_doc_key, _extract_binary, URL parsing) * test: strengthen _format_result assertions with exact expected strings - Replace loose 'in' checks with exact 'assert formatted == expected' for both multi-segment and single-segment format tests - Add object-type fields (ShippingAddress, Speakers) to test data to cover nested dict/list serialization - Add position-based ordering assertions to verify structural correctness (header -> markdown -> fields across segments) * refactor: move invoice.pdf to shared sample_assets directory - Move invoice.pdf from tests/cu/test_data/ to python/samples/shared/sample_assets/ as single source of truth - Add INVOICE_PDF_PATH constant in test_integration.py pointing to the shared location - Update document_qa.py, invoice_processing.py, large_doc_file_search.py to use invoice.pdf instead of sample.pdf * refactor: reorganize samples into numbered dirs and simplify auth - Move script samples into 01-get-started/ with numbered prefixes (01_document_qa, 02_multimodal_chat, 03_invoice_processing, 04_large_doc_file_search) - Move devui samples into 02-devui/ with 01-multimodal_agent and 02-file_search_agent/{azure_openai_backend,foundry_backend} - Move invoice.pdf to CU package-local samples/shared/sample_assets/ - Replace kwargs dicts with direct constructor calls; support both API key (AZURE_OPENAI_API_KEY) and AzureCliCredential - Update README sample table with new paths * fix: resolve CI lint errors (D205, RUF001, E501) - Fix D205: single-line docstring summary for _detect_and_strip_files - Fix RUF001: replace EN DASH with HYPHEN-MINUS in segment headers - Fix E501: wrap long assertion lines in tests - Also includes samples reorg and auth simplification * refactor: overhaul samples — FoundryChatClient, sessions, remove get_analyzed_document Samples: - Switch all samples from deprecated AzureOpenAIResponsesClient to FoundryChatClient - Add 02_multi_turn_session.py showing AgentSession persistence across turns - Rewrite 03_multimodal_chat.py with real PDF + audio + video (parallel analysis), per-modality follow-ups, cross-document question, elapsed time, user prompts, and input token counts - Renumber: 02->03 multimodal, 03->04 invoice, 04->05 file_search Context provider: - Remove get_analyzed_document tool -- full content is in conversation history via InMemoryHistoryProvider, no retrieval tool needed - Remove follow-up turn instructions about tools - Only list_documents tool remains (for status queries) - Update README to reflect tool removal * feat: add 05_background_analysis sample and fix 04 session/max_wait - Add 05_background_analysis.py demonstrating non-blocking CU analysis with max_wait=1s, status tracking via list_documents(), and automatic background task resolution on subsequent turns - Fix 04_invoice_processing.py: add max_wait=None and AgentSession - Rename 05→06 large_doc_file_search - Update README sample table * docs: update README and fix sample 06 README: - Switch Quick Start from AzureOpenAIResponsesClient to FoundryChatClient - Add AgentSession to Quick Start example - Fix status values: pending -> analyzing/uploading/ready/failed - Fix env var: AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME -> AZURE_OPENAI_DEPLOYMENT_NAME - Update samples section with new paths, link to samples/README.md - Update multi-segment description to reflect per-segment fields Sample 06: - Fix from_openai -> from_foundry for Azure endpoints - Add AgentSession and max_wait=None * docs: rewrite README — concise format, prerequisites, CU link * fix: resolve pyright errors in _format_result segment cast * docs: add numbered section comments and fresh sample output to all samples - Add numbered section comments (# 1. ..., # 2. ...) per SAMPLE_GUIDELINES - Re-run all 6 samples and update expected output with real results - Fix duplicate sample output blocks in 04 and 05 - Update README code example to use public invoice URL * feat: add load_settings support for env var configuration - Make endpoint optional in constructor — auto-loads from AZURE_CONTENTUNDERSTANDING_ENDPOINT env var via load_settings() - Add ContentUnderstandingSettings TypedDict - Add env_file_path/env_file_encoding params for .env file support - Add 4 unit tests: env var loading, explicit override, missing endpoint error, missing credential error - Update README with env var auto-resolution docs - Follows framework convention used by all other packages * docs: polish README — fix duplicate env var, add Next steps, service limits link * chore: trim invoice fixture from 199K to 33 lines Keep only VendorName, InvoiceTotal, DueDate, InvoiceDate, InvoiceId fields and first 500 chars of markdown. Strip spans/source/coordinates. Reduces fixture from 6.6MB to 1.2KB. * feat: per-file analyzer_id override via additional_properties - Read analyzer_id from Content.additional_properties for per-file override - Resolution order: per-file > provider-level > auto-detect by media type - Update class docstring documenting filename and analyzer_id properties - Update sample 04 to demonstrate per-file override (prebuilt-invoice) - Add unit test for per-file analyzer override * Trim PDF test fixture and clarify unique filename requirement - Trim analyze_pdf_result.json from 4427 to 23 lines by removing pages, words, lines, paragraphs, sections, spans, and source fields that are not used by any unit test. - Add docstring note that filename must be unique within a session; duplicate filenames are rejected and the file will not be analyzed. * Update python/packages/azure-ai-contentunderstanding/agent_framework_azure_ai_contentunderstanding/_context_provider.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update python/packages/azure-ai-contentunderstanding/agent_framework_azure_ai_contentunderstanding/_context_provider.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update python/packages/azure-ai-contentunderstanding/samples/02-devui/02-file_search_agent/azure_openai_backend/agent.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update python/packages/azure-ai-contentunderstanding/samples/02-devui/01-multimodal_agent/agent.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update python/packages/azure-ai-contentunderstanding/samples/01-get-started/06_large_doc_file_search.py Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Fix AGENTS.md to match implementation; remove unused variable in test helper AGENTS.md: - Remove _ensure_initialized() reference (client is created in __init__) - Fix multi-segment docs: segments kept as list, not merged into fields - Remove get_analyzed_document() reference (only list_documents registered) - Update sample names to match current directory structure test_context_provider.py: - Simplify _make_data_uri() — remove unused 'encoded' variable * Fix premature file_search instruction for background-completed docs - Change _resolve_pending_tasks() instruction from 'Use file_search' to 'being indexed' since the upload hasn't completed yet at that point. - Add LLM instruction on upload failure in step 1b so the agent can inform the user the document isn't searchable. * fix: wrap long line in devui agent instructions (E501) * Fix Copilot review: unused logger, stray code in README, await cancelled tasks - _file_search.py: Remove unused logger and logging import - 01-multimodal_agent/README.md: Remove accidentally pasted Python script - _context_provider.py close(): Await cancelled tasks before closing client to prevent 'Task destroyed but pending' warnings * Sanitize doc keys and fix duplicate filename re-injection - Add _sanitize_doc_key() to strip control characters, collapse whitespace, and cap length at 255 chars — prevents prompt injection via crafted filenames in extend_instructions() calls. - Track accepted doc_keys in step 3 so step 5 only injects content for files actually analyzed this turn, not pre-existing duplicates. - Soften duplicate upload instruction wording (remove IMPORTANT/caps). * fix: add type annotation to tasks_to_cancel for pyright * Move per-session mutable state to state dict for session isolation Previously _pending_tasks, _pending_uploads, and _uploaded_file_ids were stored on self, shared across all sessions. This caused cross-session leakage: Session A's background task results could be injected into Session B's context. Now these are stored in the per-session state dict. Global copies (_all_pending_tasks, _all_uploaded_file_ids) are kept on self only for best-effort cleanup in close(). Add 2 new TestSessionIsolation tests verifying that background tasks and resolved content stay within their originating session. * Remove unused AnalysisSection enum values Only MARKDOWN and FIELDS are handled by _extract_sections(). Remove FIELD_GROUNDING, TABLES, PARAGRAPHS, SECTIONS to avoid exposing dead options to users. * Recursively flatten object/array field values for cleaner LLM output - Use SDK .value property with recursive extraction for object/array fields - Object: AmountDue -> {Amount: 610, CurrencyCode: USD} (was raw SDK dict) - Array: LineItems -> list of flattened items (was raw SDK list) - Update invoice fixture with object/array fields from prebuilt-invoice - Add 3 unit tests for object, array, and nested object field extraction * Preserve sub-field confidence; compare full expected JSON in tests * Remove incorrect MIME aliases (audio/mp4, video/x-matroska) * feat: add AnalysisInput, content_range, warnings, and category support - Use SDK AnalysisInput model instead of raw body dict for begin_analyze - Forward content_range from additional_properties to CU (page/time ranges) - Extract CU warnings with code/message/target (ODataV4Format) into output - Include content-level category from classifier analyzers - Add 5 new tests: warnings, category, content_range forwarding - Fix pyright with explicit casts; fix en-dash lint (RUF002) * fix: falsy-0 bug in duration calc; improve test coverage - Fix start_time_ms=0 treated as falsy by 'or' short-circuit, use 'is None' checks instead for duration and segment time extraction - Update warnings test to use RAI ContentFiltered codes - Enrich warnings extraction to include code/message/target (ODataV4Format) - Add multi-segment video category test with per-segment assertions * refactor: split _context_provider.py into focused modules - Extract _constants.py: SUPPORTED_MEDIA_TYPES, MIME_ALIASES, analyzer maps - Extract _detection.py: file detection, MIME sniffing, doc key derivation - Extract _extraction.py: result extraction, field flattening, LLM formatting - _context_provider.py delegates via thin wrappers (793 lines, was 1255) - Update test imports to use _constants.py for SUPPORTED_MEDIA_TYPES * docs: update AGENTS.md with DocumentStatus, FileSearchBackend, and _file_search.py * refactor: replace AnalysisSection enum with Literal type for simpler DX - Remove AnalysisSection(str, Enum) class, replace with Literal["markdown", "fields"] type alias - Users can now pass plain strings: output_sections=["markdown"] — no extra import needed - AnalysisSection type alias still exported for type annotation use - Update all samples, tests, and internal code to use string literals - Address PR review feedback (eavanvalkenburg) * refactor: replace asyncio.Task with continuation tokens for serializable state - Replace state["_pending_tasks"] (asyncio.Task — not serializable) with state["_pending_tokens"] (dict of continuation token strings) so the framework can persist session state to disk/storage - Resume pending analyses via Azure SDK continuation_token mechanism - Fix: resumed pollers have stale cached status (done() always False), use asyncio.wait_for(poller.result()) with 10s min timeout instead - Remove _background_poll(), _all_pending_tasks, and task cancellation - Address PR review feedback (eavanvalkenburg): state must be serializable * fix: resolve CI lint (RUF052) and mypy (call-overload) errors * feat: add structured output (Pydantic model) to invoice processing sample - Use response_format=InvoiceResult for schema-constrained LLM output - Use output_sections=["fields"] only (no markdown needed for structured output) - Add LowConfidenceField model with confidence values - Add comments about prebuilt-invoice extensive schema vs simplified model - Address PR review feedback (eavanvalkenburg): use structured response * fix: use FOUNDRY_PROJECT_ENDPOINT and FOUNDRY_MODEL env vars in all samples Replace AZURE_AI_PROJECT_ENDPOINT → FOUNDRY_PROJECT_ENDPOINT and AZURE_OPENAI_DEPLOYMENT_NAME → FOUNDRY_MODEL across all sample .py and README.md files. Address PR review feedback (eavanvalkenburg). * refactor: remove background_analysis sample, use FoundryChatClient in DevUI - Remove 05_background_analysis.py (per reviewer feedback — discuss max_wait design separately from samples) - Renumber 06_large_doc_file_search.py → 05_large_doc_file_search.py - Replace AzureOpenAIResponsesClient with FoundryChatClient in all DevUI samples - Replace client.as_agent() with Agent(client=client, ...) everywhere - Add max_wait comments explaining interactive vs batch usage - Update README.md and AGENTS.md - Address PR review feedback (eavanvalkenburg) * fix: vector_stores API moved from beta namespace in OpenAI SDK * docs: add comments about multi-file support and CU service limits in file_search sample * fix: broken markdown links after sample removal and renumbering * fix: migrate BaseContextProvider to ContextProvider (non-deprecated) * fix: Message(text=) -> Message(contents=[]) for API compatibility * Inline _constants.py into consuming modules Remove _constants.py and move constants to where they are used: - SUPPORTED_MEDIA_TYPES, MIME_ALIASES → _detection.py - MEDIA_TYPE_ANALYZER_MAP, DEFAULT_ANALYZER → _context_provider.py Addresses review feedback to reduce file count. * Mark package as alpha per package management skill - Version: 1.0.0b260401 → 1.0.0a260401 - Classifier: Development Status 4 - Beta → 3 - Alpha - Add to PACKAGE_STATUS.md as alpha Follows the alpha package checklist from python-package-management skill. * Replace extend_instructions with extend_messages for status notifications Status/error/result notifications now use extend_messages (conversation context) instead of extend_instructions (system prompt). This avoids system prompt bloat and keeps behavioral directives separate from event notifications. - 11 extend_instructions calls → extend_messages (role='user') - 1 extend_instructions retained: tool usage guidelines (behavioral) - 6 test assertions updated to check context_messages All 84 unit tests + 5 live integration tests pass. * Fix lint: E402 import order, ISC004 implicit string concatenation - Move constants after all imports to fix E402 - Wrap multi-line strings in parentheses inside contents=[] to fix ISC004 * Fix lint: remove unused json import in invoice sample * Fix CI: apply ruff format + fix E501 line length after reformatting ruff format expands Message() calls to multi-line, pushing string indentation deeper. Break long strings to fit within 120 char limit after formatting. Also removes unused json import in sample. * Address review feedback: keyword-only args, accept pre-built client, remove wrappers - All __init__ args now keyword-only (matches FoundryChatClient pattern) - New 'client' param accepts pre-built ContentUnderstandingClient - core dep bound: >=1.0.0rc5 → >=1.0.0,<2 - Self import moved after local imports - Removed 9 static method wrappers; callsites use module functions directly - Tests updated to import derive_doc_key and format_result directly * fix: remove duplicate ContentUnderstandingClient instantiation The client was being created twice — once inside the if/else block and again unconditionally after it. The second instantiation overwrote the pre-built client path and failed type checking when credential was None. * rename: azure-ai-contentunderstanding → azure-contentunderstanding Package: agent-framework-azure-ai-contentunderstanding → agent-framework-azure-contentunderstanding Module: agent_framework_azure_ai_contentunderstanding → agent_framework_azure_contentunderstanding Directory: packages/azure-ai-contentunderstanding → packages/azure-contentunderstanding Per agreement with PM and MAF team to drop 'AI' from the package name. * feat: add ContentUnderstanding re-export to agent_framework.foundry namespace Enables: from agent_framework.foundry import ContentUnderstandingContextProvider Exports: ContentUnderstandingContextProvider, FileSearchConfig, FileSearchBackend, AnalysisSection, DocumentStatus Updates all samples and README to use the foundry namespace import. * fix: add missing copyright headers to standalone sample scripts * chore: remove .vscode/settings.json and add to .gitignore * refactor: reuse FoundryChatClient.client for vector store ops in file_search sample Address review feedback from TaoChenOSU: - 05_large_doc_file_search.py: use client.client instead of manually constructing AsyncAzureOpenAI; remove openai dependency - azure_openai_backend/agent.py: import reorder only (AIProjectClient kept — required for sync vector store creation in DevUI) * fix: skip closing client when caller passes pre-built client When a ContentUnderstandingClient is passed via client=, the caller owns its lifecycle. Added _owns_client flag so close() only closes the client when we created it internally. --------- Co-authored-by: yungshinlin <yungshin@msn.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>Yung-Shin Lin ·
2026-04-28 20:55:59 +00:00 -
Python: bump package versions for 1.2.1 release (#5536)
* Python: bump package versions for 1.2.1 release PATCH bump (1.2.0 -> 1.2.1) for the released cohort. The release window covers two PRs, no new public APIs: - agent-framework-core: prevent inner_exception from being lost in AgentFrameworkException (#5167) - samples: add requirements.txt and .env.example to the a2a/ hosting sample for pip-based setup (#5510) Per lockstep convention, all 21 beta packages stamp 1.0.0b260428 and all 3 alpha packages stamp 1.0.0a260428, regardless of per-package code churn. Every non-core package floor on agent-framework-core is raised to >=1.2.1 to keep cohort signaling consistent. Date stamp reflects the local (Asia) cut date 2026-04-28. * Python: silence pyright unknown-type warnings in hosted-env detection `azure.ai.agentserver.core` is probed at runtime via `importlib.util.find_spec` and is not a declared dependency. The existing `# pyright: ignore[reportMissingImports]` suppresses the missing-import warning, but at `lowest-direct` resolution pyright still reports the imported symbol (`AgentConfig`) and its members (`from_env`, `is_hosted`) as unknown, breaking `validate-dependency-bounds-test` for `packages/core`. Extend the existing ignore to cover `reportUnknownVariableType` on the import and `reportUnknownMemberType` on the call site so the bounds check returns to green. Behavior is unchanged. Latent since #5455 (shipped in 1.2.0). * Python: raise agent-framework-gemini lower bound to google-genai>=1.65.0 The Gemini chat client references several `google.genai.types` symbols (`FileSearch`, `ThinkingLevel`, `SearchTypes`, `McpServer`, `StreamableHttpTransport`, plus call-site keyword args `mcp_servers` and `search_types`) that are not present at the lower bound of `google-genai>=1.0.0`. At `lowest-direct` resolution this caused `validate-dependency-bounds-test` to fail for `packages/gemini` with eleven `reportAttributeAccessIssue` / `reportUnknownVariableType` errors. Walking the upstream `google.genai.types` API: - `GoogleMaps`, `AuthConfig`: present from 1.40.0 - `FileSearch`: introduced in 1.49.0 - `ThinkingLevel`: introduced in 1.55.0 - `SearchTypes`, `McpServer`, `StreamableHttpTransport`: introduced in 1.65.0 Bump the lower bound to 1.65.0 — the minimum version that exposes every symbol the package actually uses. Keep the `<2.0.0` upper cap unchanged. With this bump `validate-dependency-bounds-test` passes for both lower and upper resolution scenarios across all 27 workspace packages. Latent since #4847 (Gemini package introduction in 1.1.0); aggravated by subsequent feature additions that pulled in newer `types.*` symbols. * Python: add dependabot bumps to 1.2.1 CHANGELOG Catalog the 15 dependabot dependency updates that merged on `upstream/main` between python-1.2.0 and the 1.2.1 cut window under a new Changed section: - Workspace dev/runtime deps: `rich`, `prek`, `python-multipart`, `pyasn1`, `pytest` (ag-ui, devui, lab), `uv` (lab) - Frontend deps: `vite` (devui, chatkit), `postcss` (devui, chatkit, handoff), `picomatch` (devui, handoff) CHANGELOG-only — no source or pyproject.toml changes. PRs themselves merged upstream independently of this release branch and will be brought in via the PR merge.
2026-04-28 18:23:26 +09:00 -
Python: Add
requirements.txtand.env.exampleto thea2a/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>
2026-04-27 22:22:07 +00:00 -
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>
bahtyar ·
2026-04-27 04:53:06 +00:00