mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
main
487 Commits
-
Python: Fix Python OTel usage detail attributes (#6493)
* fix python otel usage detail attributes Map cached/read/reasoning usage detail fields to standard OTel GenAI attributes while preserving provider-specific legacy keys. Add focused coverage for direct response spans, aggregated agent spans, and provider usage parsing. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * address usage detail review feedback Omit missing OpenAI Responses usage detail counts while preserving zero-valued counts. Record zero-valued token usage in OTel histograms and add regression coverage. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Eduard van Valkenburg ·
2026-06-15 07:10:14 +00:00 -
Python: [BREAKING] Align FileAccess tools with .NET — directory discovery and recursive search (#6476)
* Align FileAccess tools with .Net; add directory discovery and recursive search * Fix choices field description: spacing, line length, grammar Addresses PR review: separate concatenated string literals with proper spacing/newlines, wrap lines under the 120-char Ruff limit, and fix "doesn't" -> "don't". Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR comments --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
westey ·
2026-06-15 06:55:21 +00:00 -
Python: Add AgentLoopMiddleware for re-running agents in a loop (#6174)
* Python: Add AgentLoopMiddleware for re-running agents in a loop Add `AgentLoopMiddleware`, an `AgentMiddleware` that re-runs the wrapped agent in a loop. A single configurable class covers three common patterns, each with a convenience classmethod factory: - Ralph loop (`.ralph(...)`): no exit criteria, with feedback tracking (`record_feedback`/`progress`), progress injection (`inject_progress`), optional fresh context per iteration (`fresh_context`), and an early-stop completion signal (`is_complete`). - Predicate (`.with_predicate(...)`): loop while a `should_continue` callable returns True (e.g. paired with `todos_remaining`/`background_tasks_running`). - Judge (`.with_judge(...)`): a second chat client decides whether the original request was answered, using a `JudgeVerdict` structured-output response. The loop also auto-resolves pending function-approval / user-input requests via an `on_approval_request` callable (bounded by `max_approval_rounds`), and the next iteration's input is controlled by `next_message`. Supports both streaming and non-streaming runs. Exports `AgentLoopMiddleware`, `JudgeVerdict`, `todos_remaining`, and `background_tasks_running`. Adds tests, a sample, and docs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Refine AgentLoopMiddleware API and sample - with_judge: add criteria list with {{criteria}} templating into judge instructions plus an agent-side instruction; add fresh_context, additional judge feedback relay; default judge max_iterations. - should_continue is now required and positional; supports (bool, str|None) feedback tuples surfaced to next_message/record_feedback via feedback kwarg. - Judge forwards full multi-modal request and response messages. - Default max_iterations=10 (explicit None = unbounded); removed is_complete and Ralph terminology; ShouldContinueResult is a real TypeAlias. - Sample: stream all loops, print iteration counts via injected user-block boundaries (robust to function calling), <role>: content formatting, per-method expected output, and a looping todo sample. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix CI checks for AgentLoopMiddleware - Resolve pyright errors in _loop.py: drop the always-true final_result None check (the while loop always assigns it) and cast finish_reason to the AgentResponse constructor's expected type. - Apply pyupgrade --py310-plus: import TypeAlias from typing. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Resolve mypy/pyright disagreement on finish_reason pyright infers AgentResponse.finish_reason as including str and rejects the direct assignment, while mypy considers a cast redundant. Drop the cast and suppress only pyright with a targeted reportArgumentType ignore, satisfying both type checkers. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Add todo+judge AgentLoopMiddleware sample Add a second AgentLoopMiddleware sample that composes two criteria in one should_continue predicate: a TodoProvider check (evaluated first) and a report-style judge chat client (evaluated once todos are complete) that grades the assembled report against shared requirements. Register it in the middleware samples README. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Compose todo+judge loops as two middleware Rework the todo+judge sample to compose two AgentLoopMiddleware on the agent itself (middleware=[judge_loop, todo_loop]) instead of a single hand-written predicate. The inner todos_remaining loop drafts the report todo-by-todo and the outer with_judge loop re-runs it until an editor chat client judges the report publication-ready, reusing the built-in helpers. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Reset session for fresh_context loops via snapshot/restore AgentLoopMiddleware.fresh_context previously only reset context.messages, so with an attached session each iteration still reloaded the local transcript or re-threaded the service-side conversation id and the model saw the accumulated history. Snapshot the session once before the loop (via to_dict) and restore it (from_dict + field copy) between iterations, so every pass starts from the pre-loop baseline. The final iteration's pass is persisted (no restore after the terminating iteration), so a subsequent agent.run continues from there. Removed the obsolete warning, updated docstrings and core AGENTS.md, and added tests: a snapshot/restore round-trip, a session-reset streaming x fresh_context x inject_progress x store matrix across multiple runs and loop iterations, and response_format parsing across the loop. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Updated samples and docstrings --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-12 14:35:54 +00:00 -
Python: Add opt-in AG-UI thread snapshot persistence and hydration (#6471)
* feat(ag-ui): add thread snapshot store primitives Key decisions:\n- Introduce an AGUIThreadSnapshot model limited to replayable messages, optional Shared State, and optional interrupt state.\n- Define AGUIThreadSnapshotStore as an async protocol keyed by explicit Snapshot Scope and AG-UI Thread id.\n- Add InMemoryAGUIThreadSnapshotStore as memory-only, latest-only, bounded local/demo/test storage; no file-backed store is introduced.\n- Require snapshot_scope_resolver whenever an endpoint is configured with a snapshot store, including pre-wrapped runners, so thread ids are not authorization boundaries.\n\nFiles changed:\n- packages/ag-ui/agent_framework_ag_ui/_snapshots.py\n- packages/ag-ui/agent_framework_ag_ui/__init__.py\n- packages/ag-ui/agent_framework_ag_ui/_agent.py\n- packages/ag-ui/agent_framework_ag_ui/_workflow.py\n- packages/ag-ui/agent_framework_ag_ui/_endpoint.py\n- packages/core/agent_framework/ag_ui/__init__.py\n- packages/core/agent_framework/ag_ui/__init__.pyi\n- packages/ag-ui/tests/ag_ui/test_snapshots.py\n- packages/ag-ui/tests/ag_ui/test_endpoint.py\n- packages/ag-ui/tests/ag_ui/test_public_exports.py\n- packages/ag-ui/AGENTS.md\n\nVerification:\n- uv run pytest packages/ag-ui/tests/ag_ui/test_snapshots.py packages/ag-ui/tests/ag_ui/test_public_exports.py packages/ag-ui/tests/ag_ui/test_endpoint.py::test_endpoint_requires_snapshot_scope_resolver_when_store_configured packages/ag-ui/tests/ag_ui/test_endpoint.py::test_endpoint_accepts_snapshot_store_with_scope_resolver -q\n- uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py::test_endpoint_requires_snapshot_scope_resolver_when_store_configured packages/ag-ui/tests/ag_ui/test_endpoint.py::test_endpoint_requires_snapshot_scope_resolver_when_wrapped_runner_has_store packages/ag-ui/tests/ag_ui/test_endpoint.py::test_endpoint_accepts_snapshot_store_with_scope_resolver -q\n- uv run poe syntax -P ag-ui -C\n- uv run poe pyright -P ag-ui\n- uv run poe syntax -P core -C\n- uv run poe pyright -P core\n- uv run poe typing -P ag-ui\n- uv run poe typing -P core\n- uv run poe test -P ag-ui\n- uv run poe check -P ag-ui\n- git diff --check\n- git diff --cached --check\n\nBlockers / next iteration:\n- No blockers. Next slice can use the store contract to capture and hydrate agent snapshots.\n- uv repeatedly refreshed azure-ai-projects in uv.lock during local runs; reverted the generated lockfile churn because this change does not alter dependencies.\n- The poe-check commit hook was skipped after manual verification because it reformatted unrelated core MCP files outside this task. * feat(ag-ui): hydrate agent threads from snapshots Key decisions: - Resolve Snapshot Scope per endpoint request and pass it to the AG-UI runner only when snapshot storage is active. - Treat empty messages with no resume payload as an agent Hydrate Request when a scoped snapshot store is configured, replaying stored Shared State and message snapshots without invoking the wrapped agent. - Save the latest replayable agent message snapshot and Shared State at normal completion under Snapshot Scope plus AG-UI Thread id; no durable or file-backed store is introduced. Files changed: - packages/ag-ui/agent_framework_ag_ui/_agent_run.py - packages/ag-ui/agent_framework_ag_ui/_endpoint.py - packages/ag-ui/agent_framework_ag_ui/_snapshots.py - packages/ag-ui/tests/ag_ui/test_endpoint.py Verification: - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_hydrates_stored_thread_snapshot_without_invoking_agent -q - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_hydrates_stored_thread_snapshot_without_invoking_agent packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_hydrates_snapshots_by_scope_and_thread -q - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py::test_endpoint_empty_messages packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_hydrates_stored_thread_snapshot_without_invoking_agent packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_hydrates_snapshots_by_scope_and_thread -q - uv run poe syntax -P ag-ui -C - uv run poe pyright -P ag-ui - uv run poe typing -P ag-ui - uv run poe test -P ag-ui - uv run poe check -P ag-ui - git diff --check - git diff --cached --check Blockers / next iteration: - No blockers. Next slice can reconstruct normal new-user agent turns from stored snapshots. - uv repeatedly refreshed azure-ai-projects in uv.lock during local runs; reverted the generated lockfile churn because this change does not alter dependencies. - The poe-check commit hook was skipped after manual verification because it refreshed unrelated uv.lock dependency resolution. * feat(ag-ui): reconstruct agent turns from snapshots Key decisions: - Load scoped thread snapshots for non-hydrate agent requests only when snapshot storage is active and no resume payload is present. - Rebuild prior AG-UI history from stored snapshot messages, preserving the incoming new user suffix and treating stored snapshot content as authoritative over conflicting prior client history. - Merge stored Shared State with request state overrides before schema defaults and existing state-context injection. Files changed: - packages/ag-ui/agent_framework_ag_ui/_agent_run.py - packages/ag-ui/tests/ag_ui/test_endpoint.py Verification: - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_prepends_stored_snapshot_for_new_user_turn -q - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_deduplicates_full_history_and_merges_fresh_state -q - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py::test_endpoint_empty_messages packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_hydrates_stored_thread_snapshot_without_invoking_agent packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_hydrates_snapshots_by_scope_and_thread packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_prepends_stored_snapshot_for_new_user_turn packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_deduplicates_full_history_and_merges_fresh_state -q - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py -q - uv run poe syntax -P ag-ui -C - uv run poe pyright -P ag-ui - uv run poe test -P ag-ui - uv run poe check -P ag-ui - uv run poe typing -P ag-ui - git diff --check - git diff --cached --check Blockers / next iteration: - No blockers. Next slice can enable workflow AG-UI Thread Snapshot persistence and hydration. - uv repeatedly refreshed azure-ai-projects in uv.lock during local runs; reverted the generated lockfile churn because this change does not alter dependencies. - The poe-check commit hook was skipped after manual verification because it refreshes unrelated uv.lock dependency resolution. * feat(ag-ui): hydrate workflow threads from snapshots Key decisions: - Handle workflow Hydrate Requests before resolving or invoking the wrapped workflow when snapshot storage and Snapshot Scope are active. - Capture only replayable workflow protocol data: workflow-emitted state snapshots, workflow-emitted message snapshots, and synthesized messages from text/tool output. - Keep workflow snapshot capture inactive without configured persistence, and skip saving snapshots when the workflow stream emits RUN_ERROR. Files changed: - packages/ag-ui/agent_framework_ag_ui/_workflow.py - packages/ag-ui/tests/ag_ui/test_endpoint.py Verification: - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py::test_workflow_endpoint_hydrates_emitted_snapshots_without_invoking_workflow packages/ag-ui/tests/ag_ui/test_endpoint.py::test_workflow_endpoint_hydrates_synthesized_text_and_tool_snapshot -q - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py -q - uv run pytest packages/ag-ui/tests/ag_ui/golden/test_scenario_workflow.py -q - uv run poe syntax -P ag-ui -C - uv run poe pyright -P ag-ui - uv run poe test -P ag-ui - uv run poe typing -P ag-ui - uv run poe check -P ag-ui - git diff --check - git diff --cached --check Blockers / next iteration: - No blockers. Next slice can preserve interruption state and protect snapshots on errors across agent and workflow endpoints. - uv repeatedly refreshed azure-ai-projects in uv.lock during local runs; reverted the generated lockfile churn because this change does not alter dependencies. - The poe-check commit hook was skipped after manual verification because it refreshes unrelated uv.lock dependency resolution. * feat(ag-ui): preserve interrupted thread snapshots Key decisions: - Capture workflow RUN_FINISHED interrupt metadata in replayable AG-UI Thread Snapshots so Hydrate Requests can restore pending workflow actions without invoking or resuming the workflow. - Keep failed agent and workflow runs from replacing the last good snapshot; RUN_ERROR streams leave the previous snapshot available for hydration. - Verify interruption hydration through endpoint-level AG-UI streams for both agent and workflow wrappers, including Shared State replay and no wrapped runner invocation. Files changed: - packages/ag-ui/agent_framework_ag_ui/_workflow.py - packages/ag-ui/tests/ag_ui/test_endpoint.py Verification: - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py::test_workflow_endpoint_hydrates_interrupted_thread_without_invoking_workflow -q - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_hydrates_interrupted_thread_without_invoking_agent packages/ag-ui/tests/ag_ui/test_endpoint.py::test_agent_endpoint_run_error_does_not_overwrite_previous_snapshot packages/ag-ui/tests/ag_ui/test_endpoint.py::test_workflow_endpoint_hydrates_interrupted_thread_without_invoking_workflow packages/ag-ui/tests/ag_ui/test_endpoint.py::test_workflow_endpoint_run_error_does_not_overwrite_previous_snapshot -q - uv run pytest packages/ag-ui/tests/ag_ui/test_endpoint.py -q - uv run pytest packages/ag-ui/tests/ag_ui/golden/test_scenario_workflow.py -q - uv run poe syntax -P ag-ui -C - uv run poe pyright -P ag-ui - uv run poe test -P ag-ui - uv run poe typing -P ag-ui - uv run poe check -P ag-ui - git diff --check - git diff --cached --check Blockers / next iteration: - No blockers. Next slice can document AG-UI Thread Snapshot security and usage. - uv repeatedly refreshed azure-ai-projects in uv.lock during local runs; reverted the generated lockfile churn because this change does not alter dependencies. - The poe-check commit hook was skipped after manual verification because it refreshes unrelated uv.lock dependency resolution. * docs(ag-ui): document thread snapshot security Key decisions: - Document AG-UI Thread Snapshot persistence as opt-in and disabled unless a snapshot_store is configured. - Place Snapshot Scope guidance next to endpoint authentication guidance, making clear that AG-UI Thread ids identify threads but do not authorize snapshot access. - Describe built-in storage as in-memory only, process-local, latest-only, and not durable production storage; durable stores remain app-owned implementations of AGUIThreadSnapshotStore. - Call out snapshot confidentiality impact and that no file-backed AG-UI snapshot store is provided. Files changed: - packages/ag-ui/README.md Verification: - uv run python scripts/check_md_code_blocks.py packages/ag-ui/README.md --no-glob - git diff --check - git diff --cached --check - commit hook without SKIP ran changed-package lint/format and AG-UI README markdown-code-lint successfully before stopping because uv.lock was modified - uv run poe markdown-code-lint (failed due existing unrelated packages/mistral/README.md missing agent_framework_mistral import resolution; changed AG-UI README blocks passed) Blockers / next iteration: - No blockers. Local issue/PRD planning artifacts remain uncommitted. - uv refreshed azure-ai-projects in uv.lock during markdown lint and the commit hook; reverted the generated lockfile churn because this documentation change does not alter dependencies. - The poe-check commit hook was skipped after manual verification because it refreshes unrelated uv.lock dependency resolution. * fix(ag-ui): harden thread snapshot persistence edge cases - Persist the completed confirm_changes turn with interrupt=None so hydration no longer replays a stale pending interrupt after the user responds; resume requests prepend stored history so the persisted thread is not truncated. - Defer endpoint default_state application to the runners when snapshot persistence is active, filling only keys missing from both the stored snapshot state and the request state so defaults never reset persisted Shared State. - Always fold the turn's output into the persisted messages snapshot even when the outbound MESSAGES_SNAPSHOT event is suppressed for predictive tools without confirmation. - Load the stored snapshot on workflow follow-up turns, reconstruct full thread history into the run input, and seed the snapshot builder with merged state so saving a new turn no longer replaces prior history. - Move snapshot message reconstruction helpers to _run_common for reuse by the workflow runner; load stored agent snapshots on resume turns for state merge. - Add endpoint regression tests for all four scenarios. * fix(ag-ui): protect snapshot history on resume and harden suffix trust - Prepend stored thread history when persisting snapshots for resume runs on both the agent and workflow paths, so a resumed interrupt no longer overwrites the stored thread with just the resume turn's output. - Filter the incoming message suffix during thread reconstruction: only user turns and tool results answering backend-issued tool calls (stored tool calls or pending interrupts) may extend authoritative history. Client-forged assistant and tool messages are dropped and logged instead of being persisted and replayed. - Close the workflow snapshot builder's tool-call group when a tool result or text message lands, so synthesized transcripts keep tool results adjacent to their tool_calls message and stay valid as provider replay history. - Export DEFAULT_MAX_THREAD_SNAPSHOTS from agent_framework_ag_ui and expose SnapshotScopeResolver through the core ag_ui facade and stub. - Add regression tests for agent and workflow resume history preservation, forged suffix rejection, builder tool-call grouping, and the export surface. * fix(ag-ui): tolerate snapshot save failures and scope workflow cache - Wrap snapshot_store.save() on both the agent and workflow paths so a transient store failure (timeout, connection refused) is logged instead of propagating. Previously a failing save converted an already-streamed successful run into RUN_ERROR, and on the workflow path emitted RUN_ERROR after RUN_FINISHED, violating the single-terminal-event invariant. The previous snapshot stays available for hydration. - Key the workflow_factory instance cache by (snapshot_scope, thread_id). The Snapshot Scope is the authorization boundary, so the same thread id under different scopes no longer shares an in-memory workflow instance. clear_thread_workflow accepts an optional snapshot_scope and clears all scopes for the thread when omitted. - Add tests: save-failure tolerance for agent and workflow endpoints, scope-isolated workflow cache, async snapshot_scope_resolver support, and in-memory store key validation errors. * fix(ci): ignore all dotnet.microsoft.com links in linkspector The existing ignore pattern only matched https://dotnet.microsoft.com/download, but Microsoft sites insert a locale segment between host and path (e.g. /en-us/download/dotnet/10.0), so localized links slip past the pattern and get checked. dotnet.microsoft.com bot-blocks CI link checkers with intermittent 403s across the whole site, which fails markdown-link-check on unrelated pull requests since linkspector scans the entire repository. Ignore the domain wholesale, matching how platform.openai.com is already handled for the same reason. A 403 from bot blocking is indistinguishable from a removed page, so the checker cannot produce a meaningful signal for this domain either way. * ag-ui: simplify raw_messages assignment and drop OrderedDict - Replace list(cast(...)) with a typed annotation for raw_messages (_agent_run.py:866) per review suggestion - Replace OrderedDict with a plain dict in InMemoryAGUIThreadSnapshotStore (_snapshots.py:136); regular dicts are insertion-order-safe since Python 3.7, so OrderedDict is unnecessary. Update _evict_oldest to use next(iter(...)) for FIFO removal instead of popitem(last=False). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #2458: review comment fixes --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Evan Mattson ·
2026-06-12 08:29:38 +00:00 -
Python: Integrate shell tool into harness agent (#6451)
* Integrate shell tool into AgentHarness * Validate shell_executor exposes as_function() with a clear TypeError Addresses PR review feedback: a public factory should fail fast with an actionable error rather than a cryptic AttributeError when an incompatible shell_executor is supplied. Validation happens upfront, regardless of whether the client supports shell tools. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Type shell harness params via TYPE_CHECKING import Addresses PR review feedback: type shell_executor and shell_environment_provider_options instead of Any, using a TYPE_CHECKING import from agent_framework_tools.shell. The import never executes at runtime, so there is no circular dependency, and the lazy runtime import of ShellEnvironmentProvider is retained. Since ShellExecutor is a protocol without as_function(), the validated getattr result is invoked directly. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-11 20:51:59 +00:00 -
Python: Add tool approval middleware (#6414)
* Add Python tool approval middleware Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix tool approval restored state handling Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Gate hidden approvals on explicit approval responses Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Handle string inputs in approval replay scan Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Cover argument-scoped approval rules Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Refine tool approval state and budgets Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix tool approval PR CI failures Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Revert DevUI Aspire README link change Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-11 17:35:44 +00:00 -
Python: [Generated by SRE Agent] Fix MCP allowed_tools empty list handling (#6296)
* Fix MCP allowed_tools empty list handling When allowed_tools is set to an empty list [], the falsy check 'if not self.allowed_tools' incorrectly treats it as unconfigured (same as None), causing all tools to be exposed. Change to an explicit 'is None' check so that an empty list correctly results in no tools being allowed. Co-authored-by: Azure SRE Agent <noreply@microsoft.com> * Clarify allowed_tools docstring: None vs [] semantics Per Eduard's review on PR #6296: explicitly document that None exposes all tools and [] exposes none, across all four MCPTool / MCPStdioTool / MCPStreamableHTTPTool / MCPWebsocketTool docstrings. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * allowed_tools docstring: recommend load_tools=False for full disable Per Eduard's follow-up on PR #6296: `load_tools=False` is the cleaner idiom when you don't want to expose any tools. Reframe `allowed_tools=[]` in the docstring as a runtime guard / inspection-only path and cross-reference `load_tools`. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Azure SRE Agent <noreply@microsoft.com> Co-authored-by: Giles Odigwe <79032838+giles17@users.noreply.github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
chetantoshniwal ·
2026-06-11 06:46:46 +00:00 -
Python: HarnessAgent: Disable compaction when max tokens not provided (#6410)
* HarnessAgent: Disable compaction when max tokens not provided * Fix regression. * Address PR comments * Require max_output_tokens to be positive Reject max_output_tokens=0 (must be positive), mirroring max_context_window_tokens. Addresses PR review feedback. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-10 13:57:23 +00:00 -
Python: Parse MCP CallToolResult.structuredContent field to prevent tool results returning None (#6421)
* Parse structuredContent from MCP CallToolResult (#3313) The _parse_tool_result_from_mcp method only iterated over the content field from CallToolResult, ignoring the structuredContent field entirely. MCP servers that return JSON data via structuredContent (e.g., Power BI MCP) appeared to return None. Add handling for structuredContent: when present, serialize it as JSON text and append it to the result list. This preserves the data for the LLM while maintaining backward compatibility with existing behavior. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Parse MCP CallToolResult.structuredContent field to prevent tool results returning None Fixes #3313 * Address review feedback: add default=str to json.dumps and remove .checkpoints/ - Add default=str to json.dumps for structuredContent serialization so non-JSON-serializable values (e.g. bytes) degrade gracefully instead of raising TypeError - Remove all .checkpoints/ runtime artifacts from the repository - Add **/.checkpoints/ to .gitignore to prevent future accidental commits - Add test for non-serializable structuredContent values Fixes #3313 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #3313: Python: MCP CallToolResult.structuredContent field is not parsed, causing tool results to return None --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Giles Odigwe ·
2026-06-10 12:51:09 +00:00 -
Python: [BREAKING] Add sampling guardrails to MCP tools (#6413)
* Add sampling guardrails to MCP tools Add approval, token, and request-count controls to the MCP sampling callback used when an MCPTool is configured with a chat client. - Add `sampling_approval_callback`, `sampling_max_tokens`, and `sampling_max_requests` parameters to `MCPTool` and its `MCPStdioTool`, `MCPStreamableHTTPTool`, and `MCPWebsocketTool` subclasses, positioned directly after `client`. - Gate each server-initiated `sampling/createMessage` request behind the approval callback, which denies by default when no callback is provided. - Clamp the requested `maxTokens` to `sampling_max_tokens` and enforce a per-session request count via `sampling_max_requests`. - Log incoming sampling requests at WARNING level (counts only). - Export `SamplingApprovalCallback` from the public API. - Add tests, a sample, and documentation updates. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Make sampling denial message context-aware Distinguish the deny-by-default case (no approval callback configured) from an explicit denial by a configured `sampling_approval_callback`, so the returned ErrorData message is accurate for callback-driven denials and exceptions. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-10 10:17:36 +00:00 -
Python: bump package versions for 1.8.1 release (#6420)
* Python: bump package versions for 1.8.1 release * Python: bump agent-framework-foundry-hosting for 1.8.1 release * Python: bump ag-ui and azurefunctions for 1.8.1 release * Remove incorrect agent-framework-foundry changelog entry for #6259 * Add [1.8.1] changelog compare link and update [Unreleased] base --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Copilot ·
2026-06-09 21:27:42 +00:00 -
Python: [Generated by SRE Agent] docs: clarify checkpoint storage security model and deserialization trust boundaries (#6295)
* docs: clarify checkpoint storage security model and deserialization trust boundaries Add Security Model documentation sections to the checkpoint encoding and Azure Functions serialization modules explaining: - Checkpoint storage is a trusted data source requiring access controls - The RestrictedUnpickler allowlist is defense-in-depth, not a security boundary - Developer responsibilities for securing storage backends - Guidance on using allowed_types and strip_pickle_markers Co-authored-by: Azure SRE Agent <noreply@microsoft.com> * Apply suggestions from code review Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Azure SRE Agent <noreply@microsoft.com> Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
2026-06-09 16:53:48 +00:00 -
Python: Filter MCP tool kwargs to declared params via allowlist (#6399)
* Filter MCP tool kwargs to declared params via allowlist Previously MCPTool combined framework runtime kwargs (from FunctionInvocationContext.kwargs) with the LLM-supplied arguments and stripped only a hardcoded denylist of known framework keys before forwarding to the MCP server. Any new framework-injected kwarg leaked to the server unless the denylist was updated. Switch to an allowlist built from each tool's declared parameters (inputSchema.properties). Only declared params are forwarded; everything else is stripped. Add an `additional_tool_argument_names` constructor argument so users can opt extra names back in, globally (Sequence[str]) and/or per remote tool name (Mapping with reserved "*" global key). The existing denylist is kept as a safety net for framework-named params a server declares in its schema; explicitly opted-in extras always win. The reserved _meta handling is unchanged. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address MCP allowlist review comments and fix reload arg loss - Fix pyright reportUnknownArgumentType in _load_tools (cast schema properties). - Register declared param names before the existing-tool skip guard so that tool-list reloads preserve the allowlist for already-loaded tools (previously unchanged tools silently dropped all declared args after a background reload). - Handle bare-string values in an additional_tool_argument_names mapping instead of iterating their characters. - Clarify the framework denylist comment: explicit extras override the denylist. - Make the extras-override-denylist test unambiguous (opt in a denylisted name). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-09 07:37:11 +00:00 -
Python: Fix per-service-call history persistence with server-storing clients (#6310)
* Fix per-service-call history persistence with server-storing clients When an Agent set require_per_service_call_history_persistence=True together with a HistoryProvider, and the chat client stored history server-side by default (e.g. OpenAIChatClient, STORES_BY_DEFAULT=True), the external history provider was silently never persisted. Unify persistence on the per-service-call middleware: when the flag is set and a HistoryProvider exists, the middleware is always installed and owns persistence. service_stores_history now only selects middleware behavior: - service does not store: load providers and drive the function loop with a local sentinel conversation id, or - service stores: skip loading (the service owns history) and persist each service call while the real conversation id flows through. Also rationalize chat-options handling in _prepare_run_context: - _merge_options now skips None overrides and strips remaining None values, so an unset `store` is never forwarded and the service decides its own default. - Resolve `store` and `conversation_id` once from a single combined view (effective_options) instead of probing both default and runtime dicts; the auto-injection and per-service-call resolution now agree on conversation_id. Fixes #5798 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Correct as_agent() docstring: persistence is per service call, not once per run Address PR review: when the client stores history server-side, the per-service-call middleware still persists after each model call; only provider loading is skipped. The previous "persist once per run()" wording contradicted the implementation. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: docs, missing-conversation-id warning, and tests - Clarify that require_per_service_call_history_persistence is a no-op when no HistoryProvider is present (docstrings in _agents.py and _clients.py). - Warn on every service call when the client stores history server-side but returns no conversation_id, so the (uncommon) loss of cross-turn resumability cannot fail silently. - Add tests: storing client + existing conversation_id does not raise and the id propagates; two runs on the same session keep persisting with a stable service_session_id and no provider loading; storing-without-conversation-id warns per call. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-09 05:47:57 +00:00 -
Python: feat(python): Add MCP client OTel spans per GenAI semantic conventions (#6349)
* feat(python): Add MCP client OTel spans per GenAI semantic conventions Implement MCP client spans per the OTel GenAI Semantic Conventions for MCP (https://opentelemetry.io/docs/specs/semconv/gen-ai/mcp/#client). Operations instrumented: - initialize: CLIENT span capturing MCP session setup - tools/list: CLIENT span for tool listing (per-page) - prompts/list: CLIENT span for prompt listing (per-page) - tools/call: CLIENT span (nested under execute_tool when called via FunctionTool) - prompts/get: CLIENT span Span attributes follow the MCP semantic conventions: - Required: mcp.method.name - Conditional: error.type, gen_ai.tool.name, gen_ai.prompt.name - Recommended: gen_ai.operation.name, mcp.protocol.version, mcp.session.id, network.transport, server.address, server.port Transport-specific attributes per subclass: - MCPStdioTool: network.transport=pipe - MCPStreamableHTTPTool: network.transport=tcp, network.protocol.name=http - MCPWebsocketTool: network.transport=tcp, network.protocol.name=websocket All span creation gated behind OBSERVABILITY_SETTINGS.ENABLED. Closes #3624 Closes #4697 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor: simplify MCP spans — remove enrichment logic and protocol version caching - Always create nested CLIENT spans for tools/call instead of enriching the parent execute_tool span - Remove _ACTIVE_TOOL_EXECUTION_SPAN contextvar (no longer needed) - Remove enrich_span_with_mcp_attributes() helper - Remove _otel_error_type preservation in FunctionTool.invoke() - Remove _mcp_protocol_version instance variable; protocol version is only set on the initialize span where it is available Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Refine copilot solution * fix: enable automatic exception recording on MCP spans Remove record_exception=False and set_status_on_exception=False from create_mcp_client_span. Let OTel handle exception recording and status setting automatically. The manual set_mcp_span_error calls for tools/call still correctly set error.type (which OTel's automatic handling doesn't touch), so tool_error is preserved. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Reduce number of lines * Add comment to sample * test: address PR review comments on MCP observability tests - Fix initialize test to call mocked session.initialize() and read protocolVersion from the result instead of hardcoding it - Add tools/call McpError error-path test - Add prompts/get McpError error-path test Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix export error --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Tao Chen ·
2026-06-05 19:23:01 +00:00 -
Python: Refactor workflow as agent pending request handling (#6259)
* WIP: Refactor Workflow as agent pending request handling * WIP: debugging empty message bug * Working: Workflow as agent with function approval * Address Copilot comments * Fix mypy * Address comments and fix pipeline * Request info non function approval now becomes function call * Revert uv.lock * Fix mypy * Bump min version of azure-ai-project * Remove RequestInfoFunctionArgs * fix tests * Fix failing tests * Fix sample
2026-06-05 17:23:19 +00:00 -
Python: MCP long-running task support in Python (#6319)
* MCP long-running task support in Python * Fix pyupgrade and AGENTS.md reconnect description - pyupgrade: drop forward-reference string annotations in _mcp.py (Python 3.10+ resolves them natively now that MCPTaskOptions is defined before use). - AGENTS.md: align reconnect description with current behavior. Phase 1 (initial tools/call) does NOT retry on connection loss; raises 'connection lost; task state unknown' instead, so a server that accepted the request but lost the response cannot start the operation twice. Phase 2 (tasks/get / tasks/result) still reconnects once against the same task_id. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix bandit nosec marker for CI pipeline * Address PR feedbacks * Clarifiied comments and addressed more PR feedbacks. --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Peter Ibekwe ·
2026-06-05 00:04:55 +00:00 -
Python: bump package versions for 1.8.0 release (#6351)
- Released cohort (core, openai, foundry, root): 1.7.0 -> 1.8.0 - agent-framework-github-copilot: promote to RC (1.0.0rc1) - agent-framework-orchestrations: rc2 -> rc3 (bug fix) - Beta/alpha packages with changes: a2a, anthropic, azurefunctions, bedrock, foundry-hosting, mistral bumped to new date stamp (260604) - Inter-package dependency bounds updated for changed packages - CHANGELOG.md and PACKAGE_STATUS.md updated Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-04 23:03:24 +00:00 -
Python: Fix compaction message-id collisions and tool-loop summary persistence (#6299)
* Fix compaction message-id collisions and tool-loop summary persistence Fixes two bugs in the compaction strategies: - #5237: incremental group annotation assigned message ids by position within the re-annotated slice, so moving the re-annotation start back to a previous group start restarted ids at 0 and produced collisions (e.g. a user message reusing an assistant message's id), merging groups and causing tool-result compaction to wrongly exclude messages. group_messages/_ensure_message_ids now take an id_offset and guard against existing-id collisions; annotate_message_groups threads the slice start index through as the offset. - #4991: the function-invocation loop copied the message list each iteration, so summaries inserted by compaction landed in a throwaway copy and were lost across tool-loop iterations (only the persistent excluded flags survived). _prepare_messages_for_model_call now compacts the list in place when messages is a list, so inserted summaries persist. Adds regression tests (incremental id uniqueness, existing-id collision avoidance, idempotency, and tool-loop summary persistence including streaming and conversation-id modes). Also adds a summarization.py sample demonstrating SummarizationStrategy directly with a real client, and reworks advanced.py with tool-call groups and a real summarizer. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Guard incremental message-id assignment against prefix-id collisions Addresses PR review on #5237: _ensure_message_ids only guarded against collisions within the re-annotated slice. A preexisting (e.g. user-supplied) id in the preserved prefix could still be reassigned in the suffix when the id was numerically out of position, merging groups across the re-annotation boundary again. group_messages/_ensure_message_ids now accept reserved_ids, and annotate_message_groups passes the preserved prefix's ids so auto-assigned suffix ids never collide across the full list. Adds a regression test reproducing the out-of-position prefix-id collision. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-04 08:37:59 +00:00 -
Python: run sync tools off the event loop (#5773)
* fix: run sync tools off event loop * chore: silence harness tool marker type check
Yufeng He ·
2026-06-04 04:42:08 +00:00 -
Python: Add MCP-based skills discovery (McpSkillsSource) (#6169)
* Add MCP-based skills discovery (McpSkill, McpSkillsSource, McpSkillResource) Implement Agent Skills discovery over MCP following the SEP-2640 convention: - McpSkillsSource: reads skill://index.json to discover skills served by an MCP server - McpSkill: lazily fetches SKILL.md content via resources/read on demand - McpSkillResource: wraps MCP resource results (text and binary) - Path traversal protection in get_resource for defense in depth - Samples for Foundry Toolbox and standalone MCP skills server - Comprehensive unit tests (514 lines) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review comments: rename to MCP* convention, fix error handling and samples - Rename McpSkill/McpSkillResource/McpSkillsSource to MCPSkill/MCPSkillResource/MCPSkillsSource - Add data-URI prefix stripping for blob resource decoding - Let non-McpError exceptions propagate from get_resource() - Fix contradictory test comment - Use interactive input() in mcp_based_skill sample - Remove misleading sample output block Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Restore debug logging for McpError in get_resource() Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Use AzureCliCredential in Foundry toolbox skills sample for consistency Replace DefaultAzureCredential with AzureCliCredential to match the credential convention used in all other samples. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Use MCPStreamableHTTPTool in MCP skills sample Replace raw mcp library imports (ClientSession, streamable_http_client) with the framework's MCPStreamableHTTPTool to keep MCP server connections consistent regardless of whether skills are enabled. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Branch on McpError.error.code so only not-found errors return empty Previously _try_read_index() and get_resource() swallowed every McpError as 'no skills available', making auth failures, server crashes, and connection drops indistinguishable from a server that simply has no skills. Now only two codes are treated as not-found: - -32002 (MCP-spec Resource not found) - -32601 (METHOD_NOT_FOUND — server lacks resources/read) All other McpError codes and non-McpError exceptions propagate with a warning log, surfacing real failures visibly. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add tests for non-McpError and non-not-found error propagation in MCP skills Cover the re-raise branch in MCPSkill.get_resource for plain ConnectionError/TimeoutError, the generic McpError (code 0) propagation on get_resource, and TimeoutError propagation in _try_read_index. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Revert "Use MCPStreamableHTTPTool in MCP skills sample" This reverts commit
f31ed0ded9. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Introduce MCP_SKILLS experimental feature for MCP skill classes Add a separate MCP_SKILLS feature ID to ExperimentalFeature enum and use it for MCPSkillResource, MCPSkill, and MCPSkillsSource, since their promotion timeline is partly outside of our control. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>semenshi-m ·
2026-06-03 18:09:50 +00:00 -
Python: progressive tool exposure via FunctionInvocationContext (#6233)
* Python: progressive tool exposure via FunctionInvocationContext Add first-class progressive tool exposure to the Python core function-calling loop. Tools can now add or remove real FunctionTool schemas at runtime via the injected FunctionInvocationContext, taking effect on the next iteration of the loop. - FunctionInvocationContext gains a live `tools` list plus experimental `add_tools()` / `remove_tools()` helpers (feature: PROGRESSIVE_TOOLS). - The function-calling loop establishes a run-local, normalized tools list and threads it into the context at both invocation paths so mutations propagate. - Add a sample (dynamic_tool_exposure.py) and a tools samples README, including a note that CodeAct providers (Monty/Hyperlight) use their own provider-level tool management instead. Supersedes #3877. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Validate non-negative input in dynamic_tool_exposure sample tools Address review feedback: factorial and fibonacci now return an error message for negative n instead of producing incorrect results. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Make add_tools atomic and surface swallowed function errors Address review feedback on progressive tool exposure: - add_tools now validates the full batch against a throwaway copy before committing, so a duplicate-name clash partway through a sequence leaves the live tool list unchanged (all-or-nothing). - _auto_invoke_function now logs a warning (with traceback) when a tool raises, so contract errors such as a duplicate-name ValueError from add_tools are debuggable without enabling include_detailed_errors. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Avoid retaining tracebacks when logging swallowed function errors Logging with exc_info=exc fed the exception traceback to the logging machinery, whose frame references created reference cycles collected lazily by the cyclic GC. On Windows that could drop a hyperlight WasmSandbox on a non-owning thread ("unsendable, dropped on another thread"), crashing the xdist worker. Log a pre-formatted message with the exception repr instead, so no traceback object is retained. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * added missing decorator --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-03 09:01:07 +00:00 -
Python: Promote agent-framework-declarative package to RC (#6256)
* Promote agent-framework-declarative package to RC * Update missed package status file.
2026-06-02 19:30:05 +00:00 -
Python: Fix OTLP HTTP base-endpoint losing /v1/{signal} auto-append (#5913)
* Python: Fix OTLP HTTP base-endpoint losing /v1/{signal} auto-append Per the OTel spec, OTEL_EXPORTER_OTLP_ENDPOINT is a *base* URL for HTTP — the SDK auto-appends /v1/traces, /v1/metrics, /v1/logs when it reads the env var directly. Signal-specific endpoint env vars are *full* URLs used verbatim. _get_exporters_from_env read the base endpoint and forwarded it as the constructor ``endpoint=`` argument, which the SDK always treats as a full signal URL. As a result, with OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4318 and HTTP protocol, the exporter sent to http://localhost:4318 instead of http://localhost:4318/v1/traces (and likewise for metrics/logs). Replicate the spec's auto-append here when falling back to the base endpoint under HTTP. gRPC behavior is unchanged. * Python: Fix mypy type errors in OTLP endpoint assignment Pre-declare traces_endpoint, metrics_endpoint, logs_endpoint as str | None before the if/else block. Mypy inferred str from the if-branch f-string assignments and then rejected the str | None expressions in the else-branch as incompatible.Dineshsuriya D ·
2026-06-02 09:59:50 +00:00 -
Python: feat(evals): Foundry Adaptive Evals integration (rubric-generation) (#6101)
* Python: feat(evals): RubricScore type + EvalScoreResult.dimensions Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: feat(foundry-evals): RubricDimension + GeneratedEvaluatorRef + accept in evaluators= Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: feat(evals): parse rubric_scores from output items + assertion helpers Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: feat(evals): BaseAgent.as_eval_source / Workflow.as_eval_source Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: feat(foundry-evals): EvalGenerationSource + generate_rubric helper Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: feat(foundry-evals): YAML config loader + sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix(evals): address PR review feedback Addresses 4 Copilot review comments on PR #6101: 1. assert_dimension_score_at_least: drop the (not evaluator or found_any) guard so require_applicable=True correctly raises when the named evaluator produces no entries for the dimension. Adds TestRubricAssertions covering the regression. 2. GeneratedEvaluatorRef docstring: reword to describe actual behaviour (pinning recommended, not required) so it matches the dataclass default and FoundryEvals warning path. 3. _poll_generation_job: switch from asyncio.get_event_loop() to get_running_loop() and bound the per-iteration sleep by remaining time, matching _poll_eval_run. 4. generate_rubric: type category as Literal['quality','safety'] and validate at the entry point with a ValueError; drop the silent 'invalid -> quality' rewrite in _generation_job_to_ref. Adds a regression test. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: feat(foundry-evals): hosted-agent-aware rubric generation * Auto-detect hosted Foundry agents in agent_as_eval_source: when the agent's chat_client exposes a string agent_name (the convention used by RawFoundryAgentChatClient for PromptAgents/HostedAgents), emit a type='agent' EvalGenerationSource so the service fetches instructions and tools from the agent registry instead of relying on the local wrapper (which holds neither for hosted agents). * Add hosted_agent_version kwarg and a new agent_version field on EvalGenerationSource so PromptAgent runs can pin to a specific hosted version for reproducible rubric generation. * Add force_prompt_source escape hatch to bypass auto-detection and always emit a rendered prompt dossier - useful when the local wrapper carries overrides the service-side agent doesnt see. * Fix _to_sdk_source for dataset sources: SDK ctor takes name=/version=, not dataset_name=/dataset_version=. The mismatch would raise TypeError against the real azure-ai-projects 2.3.0a* SDK; only unmocked integration paths were affected. Tests cover: auto-detection happy path, versionless hosted agent, explicit hosted_agent_version forwarding, force_prompt_source override, non-string chat_client attrs (MagicMock test doubles) not mis-detected, agent_version forwarded through _to_sdk_source, and the corrected dataset SDK kwarg names. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(foundry-evals): accept canonical dimension_scores key per docs The published Foundry rubric-evaluator output (Microsoft Learn 'Rubric evaluators' reference) places per-dimension breakdowns under properties.dimension_scores, not properties.rubric_scores. The parser now tries dimension_scores first and falls back to rubric_scores for preview-build compatibility, and tolerates non-list payloads (e.g. MagicMock auto-attrs) by trying the next candidate when parsing yields zero entries. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * feat(foundry-evals): add manual create_rubric_evaluator Adds FoundryEvals.create_rubric_evaluator as the agent-framework surface over project_client.beta.evaluators.create_version. This is the manual counterpart to generate_rubric: callers supply RubricDimension instances (authored locally, ported from another framework, or hand-tuned) and we POST a RubricBasedEvaluatorDefinition. The service auto-attaches the non-editable residual dimension (general_quality for quality, general_policy_compliance for safety). Per the Microsoft Learn 'Rubric evaluators' reference, the auto-generation path (create_generation_job) is primarily a portal/UI feature; external SDK clients with rich local agent context are better served by manual create_version. This keeps generate_rubric for users who want to round-trip through a Foundry-registered agent. Validation up front: weight must be in [1,10], ids unique, descriptions non-empty, pass_threshold in [0,1]. The returned GeneratedEvaluatorRef is identical in shape to one obtained from generate_rubric, so downstream evaluators= lists work unchanged. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * samples(foundry-evals): manual rubric sample + namespace re-exports Adds evaluate_with_manual_rubric_sample.py demonstrating the end-to-end dev scenario for FoundryEvals.create_rubric_evaluator: hand-author a list of RubricDimension, register via create_rubric_evaluator, then use the pinned GeneratedEvaluatorRef alongside built-in evaluators in an agent regression run. Also re-exports RubricDimension, GeneratedEvaluatorRef, build_sources, and load_evals_config from agent_framework.foundry (both the lazy runtime shim and the type stub) so the rubric samples can import everything from a single namespace; the auto-generate sample was previously broken because the shim was missing build_sources / load_evals_config. Updates the foundry-evals README with a chooser entry for the two rubric paths. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * feat(foundry-evals): remove rubric creation flows; keep consumption only Reframes agent-framework as a pure consumer of Foundry rubric evaluators: scoring against rubrics that already exist (authored in the Foundry portal or via the dedicated SDK / REST surface) instead of creating them from the SDK. Removed creation surface area: - FoundryEvals.generate_rubric (auto-generate path) and create_rubric_evaluator (manual path), plus all _GenerationSdkTypes / _ManualRubricSdkTypes / _to_sdk_dimensions / _coalesce_generation_sources / _to_sdk_source / _poll_generation_job / _generation_job_to_ref / _evaluator_version_to_ref / _get_beta_evaluators / _import_*_sdk_types helpers. - EvalGenerationSource (the input source discriminator), RubricDimension (the input dimension type), agent_as_eval_source / workflow_as_eval_source / _detect_hosted_foundry_agent helpers, and the YAML-config loader (_evals_config.py with RubricGenerationSpec / RubricSourceSpec / parse_evals_config / load_evals_config / build_sources). - BaseAgent.as_eval_source / Workflow.as_eval_source plus the _render_agent_dossier / _render_workflow_dossier helpers in core. These existed only to feed the now-removed generation pipeline. - Samples evaluate_with_generated_rubric_sample.py, evaluate_with_manual_rubric_sample.py, and evaluators.yaml. Replaced with a short README section showing how to reference an existing rubric evaluator via GeneratedEvaluatorRef. Kept (consumption surface): - GeneratedEvaluatorRef, slimmed to (name, version, display_name). Still accepted alongside built-in evaluator strings in FoundryEvals(evaluators=[...]). Versionless refs still warn. - RubricScore on EvalScoreResult.dimensions plus EvalResults.assert_dimension_score_at_least for per-dimension CI gates. - _parse_dimension_entries / _extract_rubric_scores output parsing (both canonical dimension_scores and the legacy rubric_scores key). Tests: 160/160 foundry unit tests and 71/71 core local-eval tests pass; pyright is clean across changed files. The pre-existing tests/core/test_telemetry.py::test_detect_hosted_fallback_import_error failure is unrelated and reproduces on the prior commit. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * samples(foundry-evals): add evaluate_with_rubric_sample Adds a runnable end-to-end sample showing how to consume a pre-existing rubric evaluator created in Foundry: reference it with GeneratedEvaluatorRef(name, version), mix it with built-in evaluators in FoundryEvals, and gate CI with assert_dimension_score_at_least on a specific dimension. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(foundry-evals): satisfy mypy on _fetch_output_items mypy infers OutputItemListResponse.sample as dict[str, object] | None while pyright correctly infers the typed Sample model. Cast to Any so both type checkers accept the attribute access pattern, rename the local to avoid shadowing the inner-loop sample binding, and drop the now-stale pyright suppressions. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs(foundry-evals): drop unpublished rubric-evaluators learn.microsoft.com link The Adaptive Evals authoring docs are not yet published on Microsoft Learn, so the link 404s. Keep the descriptive text without the broken hyperlink; we can re-add it once the docs ship. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * test(foundry-evals): hoist repeated local imports to module top Per code review feedback (eavanvalkenburg): the test file repeated 'from agent_framework_foundry._foundry_evals import ...' inside 22 test bodies and 'from agent_framework_foundry import GeneratedEvaluatorRef' inside 8 more. Move all of them to the existing top-level imports; the symbols are the same across tests and the local imports were redundant. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Ben Thomas <25218250+alliscode@users.noreply.github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Ben Thomas ·
2026-06-01 23:01:56 +00:00 -
Python: Fix core observability unsafe serialization of function-call arguments containing dataclass/framework objects (#6026)
* fix: safely serialize function-call arguments in core observability Apply make_json_safe() to content.arguments in _to_otel_part() before building the otel message dict, so that dataclass/framework payloads (e.g. workflow request_info events) do not cause a TypeError when _capture_messages() calls json.dumps(). Lift make_json_safe() into agent_framework._serialization (no new external deps — dataclasses/datetime only) so the core observability path can use it without a dependency on the ag-ui adapter. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(core): safely serialize workflow request_info payloads in observability (#5733) - Add make_json_safe() helper to recursively convert non-serializable objects - Use make_json_safe() in _to_otel_part() for function_call arguments - Fix CustomPayload test class to use @dataclass (resolves B903 lint error) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(serialization): guard callability and normalize dict keys in make_json_safe (#5733) - Use callable(getattr(obj, method, None)) instead of hasattr() so that non-callable attributes named model_dump/to_dict/dict do not raise TypeError at runtime. - Wrap each call in try/except TypeError to handle callables with mandatory arguments gracefully. - Convert dict keys to str() so that non-string keys (e.g. datetime, int) cannot cause json.dumps to raise TypeError. - Add regression tests for both scenarios. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address observability serialization review feedback --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-01 21:41:52 +00:00 -
Python: refresh dev dependencies and validate runtime bounds (#6238)
Updates third-party dev dependencies across the Python workspace and validates that all runtime dependency bounds still hold at both ends. Dev dependency bumps (root, lab, declarative, durabletask): - uv 0.11.6 -> 0.11.17, ruff 0.15.8 -> 0.15.15, pytest-asyncio 1.3.0 -> 1.4.0, mcp 1.27.0 -> 1.27.2, azure-monitor-opentelemetry 1.8.7 -> 1.8.8, poethepoet 0.42.1 -> 0.46.0, prek 0.3.9 -> 0.4.3, types-python-dateutil and types-PyYaml stub bumps. - Transitive Dependabot items swept via lock: idna 3.11 -> 3.17, pip 26.0.1 -> 26.1.2. Deliberately excluded: - opentelemetry-sdk stays 1.40.0: azure-monitor-opentelemetry (incl. 1.8.8) hard-pins opentelemetry-sdk==1.40. - mypy stays 1.20.0 and pyright stays 1.1.408: the 2.1.0 / 1.1.409 bumps introduce new diagnostics that fail type checking and need dedicated PRs. - rich kept as a range: agentlightning (lab[lightning]) forces rich==13.9.4. Code/formatting changes driven by the ruff upgrade: - devui lifespan now uses try/finally so shutdown cleanup always runs (ruff RUF075). - Removed unused TYPE_CHECKING imports in core and foundry flagged by ruff 0.15.15. - Reapplied ruff 0.15.15 formatting to the files it changed. Validation: validate-dependency-bounds-test "*" passes (31/31 lower + 31/31 upper); typing 62/62; lint 31/31; devui tests pass. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-01 17:53:56 +00:00 -
Python: Add background agent support to harness agent (#6155)
* Add background agent support to harness agent * Address PR comments
2026-06-01 17:20:39 +00:00 -
Python: coalesce code interpreter history chunks (#5801)
* fix: coalesce code interpreter history chunks * fix: narrow content item list types * fix: remove redundant content list casts
2026-06-01 13:26:20 +00:00 -
Python: consolidate MCP reliability fixes (#6145)
* Python: consolidate MCP reliability fixes Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix MCP cleanup and metadata typing Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Satisfy MCP metadata mypy typing Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Pyright metadata mapping type Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-05-29 07:21:14 +00:00 -
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>
2026-05-28 20:09:50 +00:00 -
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>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.
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>
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>
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>
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>
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