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Commits
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3daed114ee |
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> |
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632f67b92e |
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> |
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cfb033e5d4 |
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> |
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7e0767a0a0 |
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> |
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dcc218dbac |
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> |
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Tao ChenandGitHub
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9cafd7e58b |
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 |
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bf4ad48cf2 |
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> |
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01fc518b29 |
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> |
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f970a699d8 |
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> |
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 Yufeng HeandGitHub
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f29bae8fbc |
Python: run sync tools off the event loop (#5773)
* fix: run sync tools off event loop * chore: silence harness tool marker type check |
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c6951c21f6 |
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
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49a6e433a3 |
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> |
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Peter IbekweandGitHub
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6086a74302 |
Python: Promote agent-framework-declarative package to RC (#6256)
* Promote agent-framework-declarative package to RC * Update missed package status file. |
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 Dineshsuriya DandGitHub
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a5f355e04a |
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.
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e0d0ad16a0 |
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> |
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f36096ce1a |
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> |
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8091d052d8 |
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> |
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 westeyandGitHub
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52a8045bb6 |
Python: Add background agent support to harness agent (#6155)
* Add background agent support to harness agent * Address PR comments |
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Yufeng HeandGitHub
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78d175a1e2 |
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 |
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e8ff541ebf |
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> |
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b000a2cf51 |
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> |
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Tao ChenandGitHub
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0578f4c910 | Backfill chat span request model if it's unknown and response model is avaliable (#6160) | ||
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f7c5b8d108 |
Python: [Breaking] Refactor Skill API to async resource and script lookup (#6135)
Port of .NET commit
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Evan MattsonandGitHub
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a84ad42f6d |
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. |
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af787569b3 |
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> |
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efdabd56dc |
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> |
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ef86fb51d5 |
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> |
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d5c07f2623 |
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> |
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westeyandGitHub
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ae989b92e7 |
Python: Add a BackgroundAgentsProvider for python (#6069)
* Add a BackgroundAgentsProvider for python * Address PR comments and fix linting warnings * Address PR comment |
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westeyandGitHub
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bd4fc64b4d |
Python: Align ModeProvider tool names and instructions (#6071)
* Align ModeProvider tool names and instructions * Address PR comments |
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578416a379 |
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> |
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|
950673ba47 |
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> |
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c8b8198af1 |
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> |
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47f5c3397f |
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> |
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72a6157c6a |
[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> |
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 BaidarandGitHub
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0ba552b84c |
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 |
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Evan MattsonandGitHub
|
4b0522d62d |
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.
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 Tao ChenGitHubCopilotEduard van Valkenburgcopilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>eavanvalkenburg |
1b6f7d80fd |
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> |
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Evan MattsonandGitHub
|
3bbc81554b |
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 from
|
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19b2367366 |
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> |
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47fa59f8e9 |
Python: bump package versions for 1.4.0 release (#5872)
* fixes * fixes * Python: bump package versions for 1.4.0 release Cuts the python-1.4.0 release. MINOR bump on the released cohort (agent-framework, agent-framework-core, agent-framework-openai, agent-framework-foundry: 1.3.0 -> 1.4.0), driven by breaking changes in experimental skills API and new features. All 21 beta packages stamp 1.0.0b260514, all 3 alpha packages stamp 1.0.0a260514, and ag-ui remains at 1.0.0rc1 (freshly promoted). Date stamp reflects 2026-05-14 Pacific. - Released cohort: 1.3.0 -> 1.4.0 - Beta packages (21): 1.0.0b260507 -> 1.0.0b260514 - Alpha packages (3): 1.0.0a260507 -> 1.0.0a260514 - ag-ui: stays at 1.0.0rc1 (dep bound updated only) - Inter-package dependency lower bounds updated (>=1.3.0 -> >=1.4.0) - Fix chatkit StructuredInputItem exhaustiveness for openai-chatkit 1.6.4 - Update CHANGELOG compare links - uv.lock refreshed Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Yufeng HeandGitHub
|
410268b624 |
Python: forward MCP tool call metadata (#5815)
* Python: forward MCP tool call metadata * fix: preserve MCP tool meta after prompt reload |
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7432105ebe |
Python: Support list[str] arguments for file-based skill scripts (#5850)
Port of .NET PR #5475. Broadens the args type from dict[str, Any] | None to dict[str, Any] | list[str] | None across the skill script API surface, enabling CLI-style argv forwarding to subprocess scripts. Changes: - SkillScript.run(), InlineSkillScript.run(), FileSkillScript.run(): widen args type; InlineSkillScript rejects list with TypeError - FileSkillScript.parameters_schema: returns array-of-strings schema - FileSkill.content: appends <scripts> block with parameters_schema - SkillScriptRunner protocol: widen args type - SkillsProvider._run_skill_script: widen args type - run_skill_script tool schema: accept object, array, or null - subprocess_script_runner sample: accept list[str], reject dict - class_based_skill sample: fix missing SkillFrontmatter wrapper - Standardize 'folder' to 'directory' in docstrings (#5712) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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d40670748d |
[BREAKING] Python: Align file skill folder discovery with agentskills.io spec (#5807)
* Align Python FileSkillsSource with agentskills.io spec Update FileSkillsSource to scan spec-defined subdirectories instead of recursive rglob for resource and script discovery: - Resources: scan 'references/' and 'assets/' (was: entire skill tree) - Scripts: scan 'scripts/' (was: entire skill tree) - Add resource_directories and script_directories parameters for customization, with '.' root indicator for skill root files - Add directory validation: reject '..' traversal, absolute paths, empty names; normalize separators and deduplicate directories - Non-recursive scanning within each configured directory (top-level only) - Containment check validates files against target directory, not just skill root, for stronger path-traversal defense - Case-insensitive directory deduplication via os.path.normcase() - Cross-platform absolute path rejection in directory validation - Sort discovery results for stable ordering - Update SkillsProvider.from_paths() to pass new parameters through - Update all tests for new subdirectory-scoped discovery behavior Resolves #5711. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: tighten path validation and add containment guard - Narrow Windows absolute path check to proper drive-root pattern (re.match r'^[A-Za-z]:[/\\]') to avoid rejecting valid POSIX names - Add _is_path_within_directory guard before _has_symlink_in_path in both discovery methods to prevent ValueError on escaped paths Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Log warning on OSError during directory listing in skill discovery Address review comment: _discover_resource_files and _discover_script_files previously swallowed OSError silently when iterdir() failed. Now log a warning so permission errors and transient FS failures are visible instead of making resource/script directories silently disappear. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Evan MattsonandGitHub
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09a3d0d307 |
Python: Strip server-issued response item IDs under storage (#3295) (#5690)
Fixes microsoft/agent-framework#3295. When the OpenAI Responses chat client sends a request that carries previous_response_id / conversation_id / conversation, the server already has the prior turn's response items and rejects duplicates with "Duplicate item found with id fc_xxx". The chat client was re-sending them inline whenever the input messages still carried the items in additional_properties (workflow replay, history providers, etc.), which broke any tool-using agent with persistent history. Decisions: - Single chokepoint: _prepare_message_for_openai. When the resulting request uses service-side storage, drop function_call, reasoning, approval-request/response, and local-shell-call items from the wire input. Keep function_result with its call_id; the server pairs it to the prior function_call via that key. - function_result is preserved unconditionally except for the local-shell variant, which carries its own server-issued item id. - No public API change. Wire format change is subtractive and only on requests that would otherwise 400. - Re-pointed the strict-xfail in test_full_conversation.py from #4047 to #3295. Kept xfail because the test asserts executor-level session-id clearing, which is the defense-in-depth half tracked by 3295-03; this slice closes the wire-level half. Files: - python/packages/openai/agent_framework_openai/_chat_client.py: strip rule applied alongside the existing reasoning-item branch. - python/packages/openai/tests/openai/test_openai_chat_client.py: four new tests pin the contract (function_call, approval, local-shell-call stripped under storage; everything kept without storage). Updated pre-existing tests that exercised the storage-on path to either pass request_uses_service_side_storage=False explicitly or assert the new strip behavior. - python/packages/foundry/tests/foundry/test_foundry_chat_client.py: same explicit storage-off opt-in for the inherited test. - python/packages/core/tests/workflow/test_full_conversation.py: re-pointed xfail reason to #3295 and the executor-level follow-up. Notes for next iteration: - 3295-01 (HITL wire-format validation against live OpenAI/Foundry) was not run; it requires the user's API credentials. The PRD design is locked but the empirical confirmation is still pending. If script 3 fails on either provider, this slice may need to be revisited. - 3295-03 (clear service_session_id in AgentExecutor on full-history replay) remains open. After it lands the xfail in test_full_conversation.py can be removed. - pytest was not run in this iteration because uv-based pytest commands required interactive approval. Validation rests on careful reading; next iteration should run the openai + core test suites. |
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ab09246dc4 |
[Python] [Breaking] Extract skill spec metadata into SkillFrontmatter (#5775)
* Fix Skill docstring consistency and spelling - Add ClassSkill to Skill class docstring concrete implementations list - Normalize 'defence' to 'defense' for American English consistency - Remove extra blank line in InlineSkill docstring example Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix E501 line-too-long lint error in test_skills.py Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix stale test section header to reflect SkillFrontmatter API Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix metadata children overriding top-level frontmatter fields Scope YAML_KV_RE to column-0 keys only so indented children under metadata: are not mistakenly parsed as top-level fields. Add regression test and spec fields to sample SKILL.md files. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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7d23582e2b |
Python: fix: prevent MCP message_handler deadlock on notification reload (#4866)
* fix(python): prevent MCP message_handler deadlock on notification reload When an MCP server sends a notifications/tools/list_changed or notifications/prompts/list_changed notification, the message_handler previously awaited load_tools()/load_prompts() directly. Since the handler runs on the MCP SDK's single-threaded receive loop, this caused a deadlock: load_tools() sends a list_tools request and waits for its response, but the receive loop cannot deliver that response while blocked in the handler. This manifested as a timeout in call_tool(), which then surfaced as "Error: Function failed." to the model instead of the real tool output. The MATLAB MCP server reliably triggers this because it sends a tools/list_changed notification during tool execution. Fix: schedule reloads as background asyncio.Tasks via a new _schedule_reload() helper, freeing the receive loop immediately. Fixes #4828 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback: fix exc_info, coalesce reloads, shutdown cleanup, tests - Fix exc_info=exc -> exc_info=True in _schedule_reload and message_handler - Tighten _schedule_reload param type from Any to Coroutine[Any, Any, None] - Coalesce reloads: cancel-and-replace per reload kind to prevent unbounded growth - Cancel pending reload tasks in _close_on_owner before tearing down session - Re-raise CancelledError in _safe_reload to respect task cancellation - Replace flaky asyncio.sleep(0) with asyncio.wait_for/gather in tests - Add caplog assertions to verify reload failure is actually logged - Assert _pending_reload_tasks cleanup on error path Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: address review comments on MCP reload handling - Fix exc_info=True -> exc_info=message in message_handler error logging, since the handler is not called from an except block - Await cancelled reload tasks in _close_on_owner before tearing down the session to avoid 'Task was destroyed but pending' warnings - Add cancel-and-replace test verifying duplicate notifications cancel the first reload task and only keep one in flight Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: remove Task.cancelling() call for Python 3.10 compat Task.cancelling() was added in Python 3.11. Replace with awaiting the task and checking cancelled() instead. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add debug log when cancelling superseded reload task Log at DEBUG level when a new notification cancels an in-flight reload task, improving observability of the cancel-and-replace behavior. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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0340b7596b |
Python: bump package versions for 1.3.0 release (#5706)
* Python: bump package versions for 1.3.0 release MINOR bump on the released cohort (agent-framework, agent-framework-core, agent-framework-openai, agent-framework-foundry: 1.2.2 -> 1.3.0). All 22 beta packages stamp 1.0.0b260507 and all 3 alpha packages stamp 1.0.0a260507 per the lockstep convention. Date stamp reflects 2026-05-07 Pacific. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review: bump foundry_local openai floor, fix devui orchestrations pin, clarify breaking scope - foundry_local: bump agent-framework-openai lower bound from >=1.1.0 to >=1.3.0 - devui: update stale agent-framework-orchestrations dev pin from 1.0.0b260402 to 1.0.0b260507 - CHANGELOG: clarify [BREAKING] applies to experimental skills API only Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Revert devui orchestrations pin to 1.0.0b260402 to avoid breaking DevUI Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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1d94518f37 |
Python: Add ClassSkill for class-based skill definitions (#5678)
* Python: Add ClassSkill for class-based skill definitions Add ClassSkill abstract base class with decorator-based resource and script discovery, porting .NET's AgentClassSkill (PRs #5027 and #5183) to Python. - Add ClassSkill(Skill, ABC) with instructions abstract property, cached content/resources/scripts properties - Add @ClassSkill.resource and @ClassSkill.script static method decorators for auto-discovery of methods and properties - Extract _build_skill_content() and _create_resource_element() shared helpers from InlineSkill for reuse - Add _discover_marked_members() for scanning class hierarchies - Add _make_method_name() for Python-to-skill name conversion - Add class_based_skill sample (UnitConverterSkill) - Update mixed_skills sample with TemperatureConverterSkill - Add 58 new tests covering ClassSkill, decorator discovery, property resources, inheritance, kwargs forwarding, and duplicate detection - Export ClassSkill from agent_framework public API Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: replace try/except/continue with assignment to satisfy bandit B112 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * address PR review feedback - Walk cls.__mro__ in _discover_marked_members for inherited property resources - Use inspect.getattr_static for MRO-aware is_property check - Return defensive copies from resources/scripts properties - Raise TypeError on wrong decorator stacking order (@resource above @property) - Log warning instead of silently swallowing descriptor errors during discovery - Validate explicit name= at decoration time via _validate_member_name - Add tests for all of the above Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix temperature converter skill: make resource necessary for script Refactor TemperatureConverterSkill so the agent must read the formulas resource (factor/offset) before calling the script, aligning with the volume-converter pattern. - Resource: numeric factor/offset table instead of symbolic formulas - Script: generic linear transform (value * factor + offset) - Instructions: updated to reflect new workflow Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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2a9b68d1bd |
Python: Fix MCPStreamableHTTPTool leaking asyncio.CancelledError when MCP server is unreachable (#5687)
* fix: wrap asyncio.CancelledError in ToolException in _connect_on_owner (#5667) asyncio.CancelledError is a BaseException (not Exception) in Python 3.8+. When an MCP server is unreachable, the MCP library's internal anyio task group raises CancelledError, which escaped all three 'except Exception' handlers in _connect_on_owner(). This propagated through _run_lifecycle_owner -> _run_on_lifecycle_owner -> connect -> __aenter__, bypassing user except Exception blocks entirely. Fix: change the three except-Exception clauses in _connect_on_owner to 'except (Exception, asyncio.CancelledError)' so spurious CancelledErrors from the MCP transport layer are caught and wrapped in ToolException, consistent with the method's documented contract. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(mcp): propagate genuine task CancelledError in connect() (#5667) On Python >= 3.11, check task.cancelling() > 0 before wrapping CancelledError as ToolException in the three except blocks inside _connect_on_owner(). When the current task is being cancelled by its caller, the CancelledError now propagates after cleanup, consistent with the existing pattern at _mcp.py:560-564 and _runner.py:115-120. On Python < 3.11 task.cancelling() is unavailable, so MCP-internal CancelledErrors still cannot be reliably distinguished from caller-driven cancellation; they continue to be wrapped as ToolException with a comment documenting the trade-off. Tests: - Add cleanup assertion to transport-creation CancelledError test - Add MCPStdioTool variants exercising the 'command' message branches for both transport-creation and initialize CancelledError paths - Add Python 3.11+-gated tests verifying genuine task cancellation propagates (and still cleans up) for transport and initialize stages Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(mcp): log CancelledError with exc_info before wrapping in ToolException (#5667) CancelledError inherits from BaseException (not Exception) on Python >= 3.8, so the 'inner_exception=ex if isinstance(ex, Exception) else None' guard always yields None for CancelledError. This means ToolException.__init__ calls logger.log(level, message, exc_info=None), dropping the traceback. Add an explicit logger.debug(error_msg, exc_info=ex) before each raise ToolException(...) in the three CancelledError handlers so the full traceback is preserved in debug logs when MCP-internal cancellation is wrapped rather than propagated. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #5667: Python: [Bug]: Error Handling Issue regarding Python MCPStreamableHTTPTool Class * refactor(_mcp): extract cancellation helper, fix session error msg and exc_info - Extract _should_propagate_cancelled_error() helper to eliminate duplicated genuine-cancellation detection logic across the three connect() except blocks - Fix session-creation ToolException message to include exception details (e.g. 'Failed to create MCP session: <ex>') matching the transport and initialize failure paths - Change exc_info=ex to exc_info=True in all three logger.debug() calls for idiomatic logging - Add tests for _should_propagate_cancelled_error helper - Add regression test asserting session error message includes exception text - Add test verifying logger.debug is called with exc_info=True Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor: factor out _close_and_check_cancelled helper in _connect_on_owner Addresses review comment on PR #5687: 1. Add _close_and_check_cancelled() helper method that combines _safe_close_exit_stack() + _should_propagate_cancelled_error() into a single await-able call. This eliminates the duplicated close-then-check pattern that appeared identically in all three connect phases (transport, session, initialize), reducing future drift risk. 2. Comments 2 and 3 (missing {ex} in session error message and non-idiomatic exc_info=ex) were already addressed in the current code: all error messages include {ex} and all logger.debug calls use exc_info=True. 3. Add test_connect_genuine_cancellation_during_session_creation_propagates to cover the previously untested genuine-cancellation path in the session-creation phase (transport and initialize phases already had tests). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #5667: review comment fixes --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |