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Commits
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6b94315161 |
Python: Add timeout parameter to FoundryAgent to fix ConnectTimeout on multi-turn conversations (#6263)
* Python: fix ConnectTimeout on multi-turn FoundryAgent conversations (#6241) Expose a `timeout` parameter on `RawFoundryAgentChatClient`, `_FoundryAgentChatClient`, `RawFoundryAgent`, `FoundryAgent`, and `RawOpenAIChatClient` so callers can override the HTTP timeout used by the underlying AsyncOpenAI client. Root cause: `RawFoundryAgentChatClient.__init__` called `project_client.get_openai_client()` without configuring any timeout, inheriting the OpenAI SDK default of `httpx.Timeout(connect=5.0)`. When connections are recycled between turns under load, the 5 s connect timeout fires and surfaces as `openai.APITimeoutError`. Fix: - `load_openai_service_settings` (`_shared.py`): accept `timeout` and include it in `client_args` for all three `AsyncOpenAI`/ `AsyncAzureOpenAI` construction paths. - `RawOpenAIChatClient.__init__` (`_chat_client.py`): accept `timeout` and forward to `load_openai_service_settings`. - `RawFoundryAgentChatClient.__init__` (`_agent.py`): accept `timeout` and set `openai_client.timeout = timeout` on the client returned by `get_openai_client()` before passing it to the base class. - `_FoundryAgentChatClient`, `RawFoundryAgent`, `FoundryAgent`: accept and propagate `timeout` through the construction chain. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add timeout parameter to FoundryAgent and RawOpenAIChatClient Expose a timeout parameter on RawFoundryAgentChatClient, _FoundryAgentChatClient, RawFoundryAgent, FoundryAgent, and RawOpenAIChatClient. When provided, the value is applied to the underlying AsyncOpenAI client so that connect timeouts under load or after connection recycling can be tuned by callers. Previously, get_openai_client() was called without any timeout override, so the SDK default of httpx.Timeout(connect=5.0) was inherited and could fire on multi-turn conversations where the underlying connection is recycled between turns. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Add `timeout` parameter to `FoundryAgent` to fix `ConnectTimeout` on multi-turn conversations Fixes #6241 * fix(foundry): use with_options to avoid mutating shared OpenAI client timeout (#6241) Replace direct assignment with in RawFoundryAgentChatClient.__init__. The Azure AI Projects SDK caches and returns a shared AsyncOpenAI client per AIProjectClient. Mutating its .timeout attribute leaked the override to all other code paths sharing that client (other agents, user code). with_options() returns a new client instance with the override applied, leaving the original shared client untouched. Update tests to assert with_options is called with the correct timeout and that the original shared client's timeout attribute is not mutated. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * test(foundry): assert with_options return value flows to instance.client (#6241) The four timeout propagation tests verified that with_options was called but did not confirm that the returned (timeout-configured) client was actually stored on the instance. A silent discard of the return value would have left the tests green while the timeout had no effect. Each test now captures the constructed instance and asserts: assert <instance>.client is openai_client_mock.with_options.return_value Affected tests: - test_raw_foundry_agent_chat_client_init_applies_timeout_to_openai_client - test_raw_foundry_agent_chat_client_init_applies_timeout_with_preview_enabled - test_foundry_agent_chat_client_init_propagates_timeout - test_foundry_agent_init_propagates_timeout_to_openai_client 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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fa8cfb7567 |
Python: Fix FoundryAgent stripping model from PromptAgent requests (#5526)
* Fix FoundryAgent stripping model from PromptAgent requests
Move run_options.pop('model', None) inside the _uses_foundry_agent_session()
conditional so that model is only stripped for hosted agent sessions (where
the server manages the model) and preserved for PromptAgent requests that
require it in the Responses API call.
Fixes #5525
* test: add coverage for resp_* continuation preserving model
Adds test_raw_foundry_agent_chat_client_prepare_options_preserves_model_for_resp_continuation
to explicitly verify that HostedAgent v1 / v2-no-session paths (where conversation_id
starts with resp_) preserve model and previous_response_id without triggering the
hosted-session gate.
---------
Co-authored-by: Benke Qu <bequ@microsoft.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
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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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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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 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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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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 Yufeng HeandGitHub
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55dc3ce734 |
Python: fix: pass Foundry agent default headers (#6040)
* fix: pass Foundry agent default headers * test: loosen Foundry default header assertions |
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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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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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Yufeng HeandGitHub
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46ed66cfd5 | Python: include tool definitions for Foundry agent evals (#5974) | ||
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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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Evan MattsonandGitHub
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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
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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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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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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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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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e56e6dad4d |
Python: Remove bespoke Foundry toolbox helpers; standardize on MCP for toolbox consumption (#5671)
* Remove Foundry toolbox helpers; standardize on MCP for toolbox consumption - Remove RawFoundryChatClient.get_toolbox() and its fetch_toolbox import - Remove fetch_toolbox, select_toolbox_tools, get_toolbox_tool_name, get_toolbox_tool_type, FoundryHostedToolType, ToolboxToolSelectionInput from agent_framework_foundry._tools - Remove ExperimentalFeature.TOOLBOXES from _feature_stage.py (no consumers) - Drop toolbox re-exports from agent_framework_foundry/__init__.py and agent_framework.foundry namespace - Update _sanitize_foundry_response_tool docstring to remove toolbox framing; sanitization logic itself is unchanged - Update _agent.py docstring: 'toolbox-fetched MCP' → 'hosted MCP' - Delete tests/test_toolbox.py (all tests covered removed helpers) - Update test_foundry_chat_client.py: rename/redoc tests that mentioned toolbox but test sanitization that remains - Delete foundry_chat_client_with_toolbox.py (bespoke toolbox API sample) - Delete foundry_toolbox_context_provider.py (relied on select_toolbox_tools) - Rename foundry_chat_client_with_toolbox_mcp.py → foundry_chat_client_with_toolbox.py (canonical MCP pattern) - Rewrite 04_foundry_toolbox/main.py to use MCPStreamableHTTPTool - Update provider/README, context_providers/README, 04_foundry_toolbox/README Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(samples): update 06_files sample to consume toolbox via MCP (#5670) Replace removed get_toolbox/select_toolbox_tools APIs with MCPStreamableHTTPTool, using allowed_tools=["code_interpreter"] to select only the code interpreter from the toolbox endpoint. Update .env.example and README to use FOUNDRY_TOOLBOX_ENDPOINT instead of TOOLBOX_NAME. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(foundry): remove non-existent toolbox helper APIs from README (#5670) Remove the 'fetch, optionally filter, and pass tools directly' pattern from the FoundryChatClient toolbox documentation, as select_toolbox_tools and get_toolbox were removed. Only the MCP endpoint pattern is documented. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(foundry): remove residual toolbox docstring references and reproduction report Remove REPRODUCTION_REPORT.md (workflow artifact that should not be committed), and update two remaining docstring references that still said 'toolbox reads' /'toolbox definition' after the toolbox helpers were removed. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Remove bespoke Foundry toolbox helpers; standardize on MCP for toolbox consumption Fixes #5670 * fix(#5670): resolve toolbox endpoint from TOOLBOX_NAME fallback; add namespace regression tests - Add _resolve_toolbox_endpoint() helper in 04_foundry_toolbox/main.py and 06_files/main.py that prefers FOUNDRY_TOOLBOX_ENDPOINT but falls back to deriving the MCP URL from FOUNDRY_PROJECT_ENDPOINT + TOOLBOX_NAME — fixing the startup KeyError when agents are deployed via azd provision (which injects TOOLBOX_NAME, not FOUNDRY_TOOLBOX_ENDPOINT). - Update 04_foundry_toolbox/.env.example to use FOUNDRY_TOOLBOX_ENDPOINT (consistent with 06_files). - Add TOOLBOX_NAME env var to 06_files/agent.yaml so deployed agents have it available for the fallback derivation. - Update both READMEs to document the two ways to supply the toolbox endpoint. - Add test_foundry_namespace_no_longer_exposes_toolbox_helpers() with negative assertions for FoundryHostedToolType, get_toolbox_tool_name, get_toolbox_tool_type, and select_toolbox_tools — guarding against accidental re-introduction of removed symbols. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix(samples): fail fast on empty FOUNDRY_TOOLBOX_ENDPOINT; add unit tests Addresses review feedback for #5670: - In _resolve_toolbox_endpoint() (04_foundry_toolbox/main.py and 06_files/main.py) change the walrus-operator check from a truthy test to an explicit 'is not None' guard. An explicitly set empty string now raises ValueError immediately with a clear message instead of silently falling through to the fallback URL construction. - Add tests/samples/hosting/test_toolbox_endpoint.py covering both sample modules: (a) FOUNDRY_TOOLBOX_ENDPOINT set → returned as-is (b) FOUNDRY_TOOLBOX_ENDPOINT set to empty string → ValueError (c) fallback constructs URL from FOUNDRY_PROJECT_ENDPOINT + TOOLBOX_NAME, stripping trailing slashes (d) neither variable group set → KeyError Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback: remove extraneous test and docstring content - Remove test_foundry_namespace_no_longer_exposes_toolbox_helpers (no longer warranted) - Remove docstring from _agent.py _prepare_tools_for_openai (extraneous) - Trim _chat_client.py _prepare_tools_for_openai docstring to one-liner (toolbox references no longer relevant) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: remove remaining extraneous docstring from RawFoundryChatClient._prepare_tools_for_openai Address review comment on PR #5671: reviewer noted the description isn't warranted now that toolbox helpers have been removed. Matches the pattern in RawFoundryAgentChatClient which has no docstring. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Evan MattsonandGitHub
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f3db60fa65 |
Python: Support GPT-5 verbosity option and restore Foundry agent_reference (#5619)
* Python: Support GPT-5 verbosity option and restore Foundry agent_reference Adds verbosity as a typed Literal["low","medium","high"] field on OpenAIChatOptions (Responses API) and OpenAIChatCompletionOptions (Chat Completions API), set in the same way as the existing reasoning options. For the Responses API, top-level verbosity is translated to the nested text.verbosity shape the OpenAI service expects. The same field flows through to FoundryChatClient via the existing FoundryChatOptions alias. Also fixes #5582: PR #5447 removed the agent_reference injection from RawFoundryAgentChatClient._prepare_options, so first-turn calls against a Foundry Prompt Agent went out without model and without agent_reference and were rejected by the Responses API with "Missing required parameter: 'model'". Restores the injection on the non-preview path (allow_preview=False) and adds a guard test that asserts the preview path does not inject agent_reference, since the preview SDK injects it via project_client.get_openai_client(agent_name=...). Closes #5516 Closes #5582 * Python: Address Copilot review on PR #5619 - Foundry verbosity sample docstring: replace the misleading "set deployment name on model=" instruction with the actual env-var pattern the sample relies on (FOUNDRY_PROJECT_ENDPOINT and FOUNDRY_MODEL). - _build_agent_reference docstring: clarify the helper is used for both Prompt Agents and HostedAgents on the non-preview path. - Add a Responses API test that locks in the documented precedence rule: when both top-level verbosity and text["verbosity"] are supplied, the top-level value wins. * Python: Drop redundant Foundry verbosity sample and list OpenAI sample in README - Remove samples/02-agents/providers/foundry/foundry_chat_client_verbosity.py per review feedback. The verbosity functionality is identical across the OpenAI and Foundry clients (FoundryChatOptions is an alias of OpenAIChatOptions), so a single sample on the OpenAI side is sufficient. - Add the new client_verbosity.py entry to the OpenAI samples README. |
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540193ccef |
Python: Reduce flaky integration tests and improve CI signal quality (#5454)
* Enable Ollama integration tests in CI and rename report to Integration Test Report
- Install Ollama, cache models (qwen2.5:0.5b + nomic-embed-text), and start
server in the Misc integration job for both workflow files
- Set OLLAMA_MODEL and OLLAMA_EMBEDDING_MODEL env vars so the 5 Ollama tests
are no longer skipped
- Rename Flaky Test Report to Integration Test Report throughout (job names,
artifact names, cache keys, file names, script titles/docstrings)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Bump Ollama model to qwen2.5:1.5b for better instruction following
The 0.5b model was too small to reliably follow simple prompts like
'Say Hello World', causing test assertion failures. The 1.5b model
follows instructions more reliably while still being small enough
for fast CI pulls (~1GB).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Re-enable reliable streaming integration tests
Remove the hard skip on test_03_reliable_streaming tests that was
temporarily disabled for instability investigation. CI infrastructure
(Azurite, DTS emulator, Redis, func CLI) is already in place.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Re-enable skipped Functions/DurableTask tests and bump timeout to 480s
- Remove hard skips from 4 tests in test_11_workflow_parallel.py
- Remove hard skip from test_conditional_branching in test_06_dt_multi_agent_orchestration_conditionals.py
- Increase pytest --timeout from 360 to 480 for Functions+DurableTask CI job
- Updated in both python-merge-tests.yml and python-integration-tests.yml
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Re-skip failing Functions/DurableTask tests with specific root causes
- test_11_workflow_parallel (4 tests): xdist worker crashes during execution
- test_conditional_branching: orchestration fails with RuntimeError, not a timeout
- Keep 480s timeout bump for remaining Functions tests
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix auth routing in samples 06/11: api_key -> credential for Azure OpenAI
Both samples passed a bearer token provider via api_key= which caused the
client to route to api.openai.com instead of Azure OpenAI, resulting in
401 Unauthorized. Changed to credential= which correctly triggers Azure
routing and picks up AZURE_OPENAI_ENDPOINT from the environment.
- samples/azure_functions/11_workflow_parallel/function_app.py: 1 fix
- samples/durabletask/06_multi_agent_orchestration_conditionals/worker.py: 2 fixes
- Re-enable 4 parallel workflow tests and 1 conditional branching test
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Re-skip parallel workflow tests: xdist worker distribution issue
The 4 parallel workflow tests crash because xdist worksteal distributes
them across separate workers, each spawning its own func process against
shared emulators. Auth fix (api_key->credential) was valid and stays.
test_conditional_branching now passes with the auth fix.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix E501 line-too-long in azurefunctions parallel test skip reasons
Wrap skip reason strings to stay within 120 char line limit.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add retry logic and port-conflict fix for Ollama CI setup
- Kill any auto-started Ollama before launching serve (fixes port
conflict: 'address already in use')
- Retry ollama pull up to 3 times with 15s backoff (fixes 429 rate
limit failures)
- Applied to both python-merge-tests.yml and python-integration-tests.yml
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix flaky integration tests and re-enable skipped tests
- Foundry agent: add allow_preview=True to custom client test
- Foundry hosting: raise max_output_tokens 50->200, add temperature,
relax assertion in test_temperature_and_max_tokens
- Foundry embedding: update skip reason with root cause (endpoint mismatch)
- OpenAI file search: fix vector store indexing race condition by polling
file_counts before querying; fix get_streaming_response -> get_response(stream=True)
- Azure OpenAI file search: remove skip (transient 500 resolved)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove temperature from foundry hosting test (unsupported by CI model)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Stabilize Ollama tool call integration tests with no-arg function
Use a no-argument greet() function instead of hello_world(arg1) for
integration tests. The 1.5B model in CI is unreliable at generating
correct tool call arguments, causing 'Argument parsing failed' errors.
A no-arg function eliminates this flakiness entirely.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Increase reliable streaming test timeouts from 30s to 60s
The LLM call through Azure OpenAI + Redis streaming pipeline can exceed
30s in CI due to cold starts or throttling. Raise to 60s to reduce
flaky timeouts while still bounded by pytest's 120s per-test limit.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Re-enable workflow parallel tests with xdist_group marker
The tests were skipped because xdist distributes module tests across
workers, each spawning their own func process (port conflicts). Adding
xdist_group forces all tests in this module onto a single worker so
the module-scoped function_app_for_test fixture works correctly.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Revert "Re-enable workflow parallel tests with xdist_group marker"
This reverts commit
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Evan MattsonandGitHub
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f5419b9f38 |
Python: bump package versions for 1.2.2 release (#5561)
* Python: bump package versions for 1.2.2 release PATCH bump (1.2.1 -> 1.2.2) for the released cohort. Five PRs land in this window: - agent-framework-openai: fix file_search citations breaking the assistant- message history roundtrip (#5557) — drives the released-tier PATCH - agent-framework-orchestrations: [BREAKING] standardize orchestration terminal outputs as AgentResponse (#5301) - agent-framework-core, agent-framework-declarative: preserve Workflow.run() shared state across calls, accept list[Message] in declarative start executor, and coerce Enum values when serializing PowerFx symbols (#5531) - agent-framework-foundry-hosting: add hosted Durable Workflow support (#5531) - agent-framework-azure-contentunderstanding: new alpha package — Azure AI Content Understanding context provider (#4829) - dependencies: workspace package dependency refresh (#5555) Per lockstep convention, all 21 beta packages stamp 1.0.0b260429 and all 4 alpha packages (now including the new contentunderstanding) stamp 1.0.0a260429. Date stamp reflects 2026-04-29 Pacific. Every non-core package floor on agent-framework-core is raised to >=1.2.2; the new contentunderstanding package's stale >=1.0.0 floor is brought into line. Two follow-on fixes bundled to keep validate-dependency-bounds-test green at lowest-direct resolution: - Bump agent-framework-azure-contentunderstanding's azure-ai-content understanding lower bound from >=1.0.0 to >=1.0.1 (1.0.0 ships without proper typing — pyright reports 65 unknown-type errors) - Add pyright ignore comments to core/foundry/__init__.pyi for the new alpha package's type-stub imports, since alpha packages are not in core's [all] extra and therefore aren't installed at lowest-direct * Python: add #5552 to 1.2.2 CHANGELOG Add the streaming-span observability fix to the Fixed section. PR is on upstream/main but not yet pulled into origin/main; the code itself will land via the PR merge. * Python: address PR #5561 review feedback on dependency bounds Two packaging fixes flagged in review: 1. agent-framework-azure-contentunderstanding: add agent-framework-foundry as a runtime dependency. The package's README directs users to `pip install agent-framework-azure-contentunderstanding --pre` and the basic example imports `FoundryChatClient` from `agent_framework.foundry`, so the documented install path was failing with ImportError. Pulling agent-framework-foundry into deps makes the advertised entry path self-contained. 2. agent-framework-foundry: bump agent-framework-openai lower bound from >=1.1.0 to >=1.2.2,<2. Foundry imports private modules from agent_framework_openai (`_chat_client.py:22`, `_agent.py:34`), so resolvers were free to pair foundry==1.2.2 with older OpenAI versions that lack this release's coordinated Responses/history fix. Lockstep the floor with the released cohort to prevent mismatched installs. Both changes pass `validate-dependency-bounds-test` lower + upper at their respective packages. |
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866a325b48 |
Python: [BREAKING] Standardize orchestration terminal outputs as AgentResponse (#5301)
* Fix orchestration outputs so as_agent() returns the final answer only. Align other orchestration outputs * Fix orchestration output issues from review comments 1. Sample cleanup: Remove commented-out FoundryChatClient block and update prerequisites to reference OPENAI_CHAT_MODEL_ID instead of FOUNDRY_* vars. 2. Sequential approval output: Change _EndWithConversation.end_with_agent_executor_response from a no-op sink to yield response.agent_response. When the last participant is AgentApprovalExecutor (via with_request_info), _EndWithConversation is the output executor so the yield produces the terminal answer. When the last participant is a regular AgentExecutor, _EndWithConversation is not in output_executors so the yield is silently filtered out. 3. Forward data events through WorkflowExecutor: _process_workflow_result now also forwards 'data' events from sub-workflows so that emit_intermediate_data=True on AgentExecutor works correctly when wrapped in AgentApprovalExecutor. 4. Concurrent docstring: Update _AggregateAgentConversations docstring to say 'deterministic participant order' instead of 'completion order'. 5. Add test_concurrent_intermediate_outputs_emits_data_events verifying that ConcurrentBuilder(intermediate_outputs=True) emits per-participant data events alongside the single aggregated output event. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add tests for sequential workflow with_request_info and intermediate_outputs (#5301) Address PR review comments 2, 3, and 5: - Add test_sequential_request_info_last_participant_emits_output: Verifies that when the last participant is wrapped via with_request_info() (AgentApprovalExecutor), the workflow still emits a terminal output after approval, exercising the _EndWithConversation.end_with_agent_executor_response fallback path. - Add test_sequential_request_info_with_intermediate_outputs_emits_data_events: Verifies that emit_intermediate_data=True works correctly through AgentApprovalExecutor wrapping—WorkflowExecutor._process_result already forwards data events from sub-workflows, so intermediate agent responses surface as data events in the parent workflow. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright type errors from AgentResponse output refactor (#5301) Update cast() calls in _group_chat.py and _magentic.py to use WorkflowContext[Never, AgentResponse] instead of the old WorkflowContext[Never, list[Message]], matching the updated method signatures in _base_group_chat_orchestrator.py. Fix _sequential.py _EndWithConversation.end_with_agent_executor_response to declare WorkflowContext[Any, AgentResponse] so yield_output accepts AgentResponse[None]. Fix _workflow_executor.py data event forwarding to handle nullable executor_id. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright reportUnknownVariableType in _agent.py (#5301) Extract event.data into a typed local variable before the isinstance check to avoid pyright narrowing it to AgentResponse[Unknown]. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright reportMissingImports for orjson in file history samples (#5301) Add pyright: ignore[reportMissingImports] to orjson imports that are already guarded by try/except ImportError, matching the existing pattern used elsewhere in the samples. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #5301: review comment fixes * Address review feedback for #5301: review comment fixes * Revert sequential_workflow_as_agent sample to FoundryChatClient Reverts the mistaken switch from FoundryChatClient to OpenAIChatClient in the sequential workflow as agent sample. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address ultrareview feedback: emit_data_events rename + WorkflowAgent reasoning conversion Layered on top of the prior review-feedback work in this branch. Renames: - AgentExecutor.emit_intermediate_data -> emit_data_events (mechanical rename; orchestration semantics live at the orchestration layer, not the general-purpose executor). Forwarded through MagenticAgentExecutor, AgentApprovalExecutor, and all orchestration call sites. - HandoffAgentExecutor._check_terminate_and_yield -> _should_terminate (pure predicate; no longer yields anything). HandoffBuilder docstring rewritten to describe the new per-agent AgentResponse output contract. WorkflowAgent reasoning-content conversion: - Add _rewrite_text_to_reasoning(contents) and _msg_as_reasoning(msg) helpers; the as_agent() path now reframes text content from data events as text_reasoning Content blocks before merging into the AgentResponse. - Consumers iterate msg.contents and branch on content.type — same path they already use for Claude thinking and OpenAI reasoning. No new field on Message/AgentResponse/WorkflowEvent. - Streaming branch constructs fresh AgentResponseUpdate instances instead of mutating shared payloads (regression test added). - Helper _msg_maybe_reasoning consolidates the conditional rewrite at three call sites in the non-streaming conversion. Tests: - TestWorkflowAgentReasoningHelpers + TestWorkflowAgentDataEventReasoningConversion add 9 new tests covering helpers, non-streaming, streaming, mixed content, already-reasoning passthrough, and mutation-safety regression. - Updated test_sequential_as_agent_with_intermediate_outputs_includes_chain to assert text_reasoning content for intermediate agents. * Fix pyright: widen event.data to Any to avoid partial-unknown narrowing The streaming conversion path narrowed event.data via isinstance against generic AgentResponse, producing AgentResponse[Unknown] and tripping reportUnknownVariableType/reportUnknownMemberType. Binding data: Any before the check keeps runtime behavior identical while restoring a fully known type for downstream access. * Clean up design * Scope to agent output semantics only * yield AgentResponseUpdate streaming, AgentResponse non-streaming * Fix mypy/pyright: widen cast types at GroupChat callsites Eight callsites in _group_chat.py still cast to WorkflowContext[Never, AgentResponse] but the base orchestrator methods now accept the wider WorkflowContext[Never, AgentResponse | AgentResponseUpdate] (mode-aware yields). W_OutT is invariant, so the narrower cast is not assignable. Magentic was widened in the same commit; this catches the GroupChat callsites that were missed. * Python: skip flaky Foundry / Foundry Hosting integration tests (#5553) These two integration tests have been failing in the merge queue across multiple unrelated PRs (5301, 5531). Both are marked `@pytest.mark.flaky` with 3 retries, but all attempts fail back-to-back. Skipping both with a reason pointing to #5553 so they can be fixed properly without continuing to block unrelated merges. - packages/foundry_hosting/tests/test_responses_int.py::TestOptions::test_temperature_and_max_tokens - packages/foundry/tests/foundry/test_foundry_embedding_client.py::TestFoundryEmbeddingIntegration::test_text_embedding_live Also includes a one-line uv.lock specifier-ordering normalization auto-applied by the poe-check pre-commit hook. --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Evan MattsonandGitHub
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3a463b8bf6 |
Python: bump package versions for 1.2.1 release (#5536)
* Python: bump package versions for 1.2.1 release PATCH bump (1.2.0 -> 1.2.1) for the released cohort. The release window covers two PRs, no new public APIs: - agent-framework-core: prevent inner_exception from being lost in AgentFrameworkException (#5167) - samples: add requirements.txt and .env.example to the a2a/ hosting sample for pip-based setup (#5510) Per lockstep convention, all 21 beta packages stamp 1.0.0b260428 and all 3 alpha packages stamp 1.0.0a260428, regardless of per-package code churn. Every non-core package floor on agent-framework-core is raised to >=1.2.1 to keep cohort signaling consistent. Date stamp reflects the local (Asia) cut date 2026-04-28. * Python: silence pyright unknown-type warnings in hosted-env detection `azure.ai.agentserver.core` is probed at runtime via `importlib.util.find_spec` and is not a declared dependency. The existing `# pyright: ignore[reportMissingImports]` suppresses the missing-import warning, but at `lowest-direct` resolution pyright still reports the imported symbol (`AgentConfig`) and its members (`from_env`, `is_hosted`) as unknown, breaking `validate-dependency-bounds-test` for `packages/core`. Extend the existing ignore to cover `reportUnknownVariableType` on the import and `reportUnknownMemberType` on the call site so the bounds check returns to green. Behavior is unchanged. Latent since #5455 (shipped in 1.2.0). * Python: raise agent-framework-gemini lower bound to google-genai>=1.65.0 The Gemini chat client references several `google.genai.types` symbols (`FileSearch`, `ThinkingLevel`, `SearchTypes`, `McpServer`, `StreamableHttpTransport`, plus call-site keyword args `mcp_servers` and `search_types`) that are not present at the lower bound of `google-genai>=1.0.0`. At `lowest-direct` resolution this caused `validate-dependency-bounds-test` to fail for `packages/gemini` with eleven `reportAttributeAccessIssue` / `reportUnknownVariableType` errors. Walking the upstream `google.genai.types` API: - `GoogleMaps`, `AuthConfig`: present from 1.40.0 - `FileSearch`: introduced in 1.49.0 - `ThinkingLevel`: introduced in 1.55.0 - `SearchTypes`, `McpServer`, `StreamableHttpTransport`: introduced in 1.65.0 Bump the lower bound to 1.65.0 — the minimum version that exposes every symbol the package actually uses. Keep the `<2.0.0` upper cap unchanged. With this bump `validate-dependency-bounds-test` passes for both lower and upper resolution scenarios across all 27 workspace packages. Latent since #4847 (Gemini package introduction in 1.1.0); aggravated by subsequent feature additions that pulled in newer `types.*` symbols. * Python: add dependabot bumps to 1.2.1 CHANGELOG Catalog the 15 dependabot dependency updates that merged on `upstream/main` between python-1.2.0 and the 1.2.1 cut window under a new Changed section: - Workspace dev/runtime deps: `rich`, `prek`, `python-multipart`, `pyasn1`, `pytest` (ag-ui, devui, lab), `uv` (lab) - Frontend deps: `vite` (devui, chatkit), `postcss` (devui, chatkit, handoff), `picomatch` (devui, handoff) CHANGELOG-only — no source or pyproject.toml changes. PRs themselves merged upstream independently of this release branch and will be brought in via the PR merge. |
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Evan MattsonandGitHub
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0b69d7fd15 |
Python: Bump Python package versions for 1.2.0 release (#5468)
* Bump Python package versions for 1.2.0 release Released tier bumps 1.1.1 -> 1.2.0 (core, openai, foundry, root) to reflect additive public APIs landed since 1.1.0: functional workflow API (#4238) and FunctionTool SKIP_PARSING sentinel (#5424). All beta packages stamped 1.0.0b260424, alpha packages 1.0.0a260424. All 26 non-core agent-framework-core floors raised to >=1.2.0,<2. CHANGELOG consolidates the never-tagged 1.1.1 entries with the post-merge additions into [1.2.0]. * Update CHANGELOG footer links for 1.2.0 Advance [Unreleased] comparison base from python-1.1.0 to python-1.2.0 and add a [1.2.0] reference link comparing python-1.1.0...python-1.2.0 so the heading links resolve correctly. * Fix CHANGELOG: restore [1.1.1] section and add proper [1.2.0] Previous commit incorrectly renamed the [1.1.1] header to [1.2.0], which wiped the historical 1.1.1 entries and wrongly attributed them to 1.2.0. This restores [1.1.1] to its origin/main content and adds a new [1.2.0] section above containing only the commits in python-1.1.1..HEAD: - #4238 functional workflow API - #5142 GitHub Copilot OpenTelemetry - #2403 A2A bridge support - #5070 oauth_consent_request events in Foundry clients - #5447 FoundryAgent hosted agent sessions - #5459 hosting server dependency upgrade + types - #5389 AG-UI reasoning/multimodal parsing fix - #5440 stop [TOOLBOXES] warning spam - #5455 user agent prefix fix Also corrects the [1.2.0] compare base to python-1.1.1 (not 1.1.0) and adds the missing [1.1.1] reference link. |
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7b70f80036 |
Python: Surface oauth_consent_request events from Responses API in Foundry clients (#5070)
* Fix Foundry clients not surfacing oauth_consent_request events (#5054) Override _parse_chunk_from_openai in both RawFoundryChatClient and RawFoundryAgentChatClient to intercept response.output_item.added events with item.type == 'oauth_consent_request'. The consent link is validated (HTTPS required) and converted to Content.from_oauth_consent_request, which the AG-UI layer already knows how to emit as a CUSTOM event. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback for #5054 OAuth consent parsing - Extract shared helper (try_parse_oauth_consent_event) to avoid duplicated logic between RawFoundryChatClient and RawFoundryAgentChatClient - Use urllib.parse.urlparse() for HTTPS validation instead of case-sensitive startswith check - Sanitize log messages to avoid leaking consent_link tokens; log only item id - Add model=self.model to ChatResponseUpdate to match parent behavior - Add assertions on role, raw_representation, and model in happy-path tests - Add test for empty-string consent_link - Add test verifying non-oauth events delegate to super() Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Handle response.oauth_consent_requested top-level event (#5054) Add support for the top-level response.oauth_consent_requested stream event in addition to the response.output_item.added variant. The service may emit either form; handle both so the consent link is reliably surfaced. Extract _validate_consent_link helper within _oauth_helpers.py to reduce nesting. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #5054: Python: [Bug]: `FoundryAgent` (Responses API) Does Not Surface `oauth_consent_request` as a CUSTOM AG-UI Event * Address review feedback: defensive getattr and dedicated helper tests (#5054) - Use getattr(event, 'type', None) in try_parse_oauth_consent_event for defensive access against malformed events without a type attribute - Add test_oauth_helpers.py with unit tests for _validate_consent_link and try_parse_oauth_consent_event covering edge cases: - HTTPS URL with empty netloc (https:///path) - Warning log messages for rejected consent links - Event objects missing 'type' attribute Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #5054: Python: [Bug]: `FoundryAgent` (Responses API) Does Not Surface `oauth_consent_request` as a CUSTOM AG-UI Event * Fix mypy: match _parse_chunk_from_openai signature with superclass Add seen_reasoning_delta_item_ids parameter to _parse_chunk_from_openai overrides in both RawFoundryChatClient and RawFoundryAgentChatClient to match the updated superclass signature on main. Update super() calls and test assertions accordingly. 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> Co-authored-by: Evan Mattson <evan.mattson@microsoft.com> |
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62e02da698 |
Python: update FoundryAgent for hosted agent sessions (#5447)
* fixes to FoundryAgent to connect to new hosted agents Co-authored-by: Copilot <copilot@github.com> * fix mypy Co-authored-by: Copilot <copilot@github.com> * Python: remove Foundry service session helpers Remove the public hosted-agent service session CRUD helpers from FoundryAgent and drop the related feature-stage inventory entry. Update the hosted-agent sample to create and delete service sessions directly through the preview AIProjectClient APIs, and tighten a few test harnesses surfaced by full workspace validation. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix from merge * fix hosted env detection Co-authored-by: Copilot <copilot@github.com> * reverted sample update * fix tests and code Co-authored-by: Copilot <copilot@github.com> * remove aenter * skipping some tests Co-authored-by: Copilot <copilot@github.com> --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Tao ChenandGitHub
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0989e68d1c |
Python: Fix user agent prefix (#5455)
* Fix hosting user agent missing * Fix other providers * Add more tests * comments * Fix tests |
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Evan MattsonandGitHub
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b084d0461d |
Python: (foundry): stop emitting [TOOLBOXES] warning for every FoundryChatClient call (#5440)
* Python: Foundry: make response tool sanitizer internal, drop TOOLBOXES warning sanitize_foundry_response_tool runs on every tool passed to the Foundry Responses API, so its @experimental(TOOLBOXES) decorator was emitting a [TOOLBOXES] ExperimentalWarning for any FoundryChatClient call, even when no toolbox was involved. The function isn't in __all__ and has no external callers. Rename to _sanitize_foundry_response_tool and drop the decorator; the actual toolbox-facing public helpers remain gated. * Python: Foundry: silence pyright on intentional cross-module private import |
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Evan MattsonandGitHub
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acec9caa2f |
Python: Bump Python package versions for a release. (#5432)
* Bump Python version for a release. * Revert lockstep bumps on unchanged connectors Per PR review: only connectors that changed (or whose published metadata changed) should get new versions. Keeps released tier at 1.1.1, a2a/ag-ui at 1.0.0b260422, foundry-hosting at 1.0.0a260422; reverts the 19 unchanged betas and 2 unchanged alphas to 1.0.0b260421/1.0.0a260421. Reverts all 26 non-core agent-framework-core floors to >=1.1.0,<2 since no connector actually depends on a 1.1.1 API or bug fix. * Restore lockstep prerelease bumps and raise core floors to >=1.1.1 Reverses the lean-revert: all beta packages stamped 1.0.0b260423 and alpha packages stamped 1.0.0a260423 (Asia date, matching release cut time). All 26 non-core packages raise agent-framework-core lower bound from >=1.1.0,<2 to >=1.1.1,<2 to signal the validated cohort for this release. CHANGELOG date updated to 2026-04-23. |
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Evan MattsonandGitHub
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fffd0acb3e |
Python: fix(foundry): reconcile toolbox hosted-tool payloads with Responses API (#5414)
* fix(foundry): reconcile toolbox hosted-tool payloads with Responses API * docs(foundry): update create_sample_toolbox docstring to reflect all tools created |
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aa582d021d |
Python: feat(evals): add ground_truth support for similarity evaluator (#5234)
* feat(evals): add ground_truth support for similarity evaluator - Include expected_output as ground_truth in Foundry JSONL dataset rows - Add ground_truth to item schema and data mapping for similarity evaluator - Add expected_output parameter to evaluate_workflow - Add similarity Pattern 3 to evaluate_agent and evaluate_workflow samples - Add tests for ground_truth in dataset, schema, and evaluate_workflow * Apply suggestions from code review Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * fix: wrap long line to satisfy ruff E501 --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> |
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Evan MattsonandGitHub
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2c8036779c |
Python: Bump versions for a release. Update CHANGELOG (#5385)
* Bump versions for a release. Update CHANGELOG * Bump devui |
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04aaf0c1fe |
Python: Add support for Foundry Toolboxes (#5346)
* Add support for the Foundry Toolbox in MAF Introduces a Foundry Toolbox integration: FoundryChatClient gains a get_toolbox() helper plus select_toolbox_tools(), normalize_tools in the core package flattens tool-collection wrappers (ToolboxVersionObject and generic iterables, while leaving Pydantic BaseModel instances alone), and the new agent_framework.foundry namespace re-exports the toolbox helpers. Ships with unit tests, a sample, and a design doc. azure-ai-projects is pinned to the public >=2.0.0,<3.0 range and the lockfile resolves from public PyPI. The toolbox test module skips when Toolbox* types are unavailable so CI stays green until the public 2.1.0 SDK lands. OMC tooling directories (.omc/, .omx/) are gitignored. * Update to latest azure ai projects package * Improve sample * Rename ADR to 0025 * Update ADR * Apply suggestion from @alliscode Co-authored-by: Ben Thomas <ben.thomas@microsoft.com> * Improve samples * Update test --------- Co-authored-by: Ben Thomas <ben.thomas@microsoft.com> |
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Evan MattsonandGitHub
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4a36f10888 |
Python: Bump Python version to 1.0.1 for a release (#5196)
* Bump Python version to 1.1.0 for a release * Fix changelog * 1.0.1 instead of 1.1.0 * Update CHANGELOG.md * update version and changelog * Bump lower bounds |
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18d1ba3624 |
Python: Strip tools from FoundryAgent request when agent_reference is present (#5101)
_prepare_options() now removes tools, tool_choice, and parallel_tool_calls from run_options after injecting agent_reference. The Foundry API rejects requests containing both fields. FunctionTools are still invoked client-side by the function invocation layer. Fixes #5087 Co-authored-by: Matt Van Horn <455140+mvanhorn@users.noreply.github.com> Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com> Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com> |
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36cafe4e5a |
Python: Raise clear handler registration error for unresolved TypeVar annotations (#4944)
* Raise clear handler registration error for unresolved TypeVar (#4943) Detect unresolved TypeVar in message parameter annotations during handler registration in both _validate_handler_signature (Executor) and _validate_function_signature (FunctionExecutor). Raises a ValueError with an actionable message recommending @handler(input=..., output=...) or @executor(input=..., output=...) instead of letting TypeVar leak through to a confusing TypeCompatibilityError during workflow edge validation. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4943: reorder checks and harden function executor - Move TypeVar check before validate_workflow_context_annotation in _executor.py so users see the more actionable error first - Wrap get_type_hints in try/except in _function_executor.py matching the defensive pattern in _executor.py - Repurpose duplicate test to cover bounded TypeVar rejection - Add test_function_executor_allows_concrete_types for test symmetry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Narrow get_type_hints except clause and add missing tests (#4943) - Narrow `except Exception` to `except (NameError, AttributeError, RecursionError)` in both _executor.py and _function_executor.py so unexpected failures in get_type_hints are not silently swallowed. - Add test_handler_unresolvable_annotation_raises to test_function_executor_future.py exercising the except branch of get_type_hints in the function executor path. - Add test_function_executor_rejects_bounded_typevar_in_message_annotation to test_function_executor.py for parity with the Executor bounded TypeVar test. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add error ordering test for TypeVar vs WorkflowContext priority (#4943) Add test_handler_typevar_error_takes_priority_over_context_error to verify that when a handler has both a TypeVar message and an unannotated ctx, the TypeVar error is raised first (the more actionable issue). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix image content serialization sending null file_id to Foundry API Omit file_id from input_image dict when not present instead of including it as null, which Azure AI Foundry's stricter schema validation rejects. * Python: Fix Foundry API rejecting rich content in function_call_output Azure AI Foundry does not support list-format output in function_call_output items. Add SUPPORTS_RICH_FUNCTION_OUTPUT flag (default True) to RawOpenAIChatClient, set to False in RawFoundryChatClient so Foundry falls back to string output for tool results with images/files. Also omit file_id from input_image dicts when not set, since Foundry rejects explicit nulls. * Python: Surface rich tool content as user message when Foundry lacks support When SUPPORTS_RICH_FUNCTION_OUTPUT is False, image/file items from tool results are injected as a follow-up user message so the model can still process the visual content via Foundry's supported user message format. * Xfail Foundry image integration test for the meantime --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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3446eb8d5d |
Python: [BREAKING] update to v1.0.0 (#5062)
* updates to final deprecated pieces and versions * fix mypy * fix readme links |
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Eduard van ValkenburgandGitHub
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95fd5ec658 |
Python: [BREAKING] Python: move Azure AI embeddings to Foundry (#5056)
* renamed AzureAIINferenceEmbeddings and lazy load azure-cosmos and env var rename * updated coverage * fix readme |
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7607acd009 |
Python: Add experimental decorator to all Evals pieces (#5040)
* Initial plan * feat(python): add experimental decorator to all Evals pieces Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/99d71249-a5d6-4977-a5b5-6ffe0a3be2bc Co-authored-by: TaoChenOSU <12570346+TaoChenOSU@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: TaoChenOSU <12570346+TaoChenOSU@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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519bb0cb2b |
Python: updated declarative samples and handling of non-pydantic response formats (#5022)
* updated declarative samples and handling of non-pydantic response formats * fixed from comments * update docstring |
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6acab3d1d6 |
Python: [BREAKING] Standardize model selection on model (#4999)
* Refactor Anthropic model option and provider clients Rename the Anthropic client model option from model_id to model, add provider-specific Anthropic wrappers for Foundry, Bedrock, and Vertex, and expose them through the Anthropic, Foundry, Amazon, and Google namespaces. Update core option handling, docs, samples, and tests accordingly. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Anthropic skills sample typing Cast the Anthropic beta client to Any in the skills sample so the pre-commit sample pyright check no longer fails on beta skills and files endpoints that are not exposed by the current SDK stubs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * undo sample mypy * Retry CI after transient external failures Retrigger PR validation after an unrelated Copilot review workflow SAML failure and a transient external tau2 git fetch failure in the Windows Python test setup. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback on model option merging Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address Anthropic compatibility review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * moved all to `model` * fixes for azure ai search * Python: standardize remaining sample env var names Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix foundry-local pyright compatibility Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated env vars in cicd --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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b065a4ce51 |
Python: [BREAKING] update context provider APIs, middleware, and per-service-call history persistence (#4992)
* Rename provider base APIs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Allow provider-added chat and function middleware Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Simulate service-stored history per model call Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix typing regressions in CI Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix response ID suppression review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Rename per-service-call history persistence APIs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address context persistence review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize markdown sample docs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Persist service continuation state per call Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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3a49b1d6dd |
Python: [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces (#4990)
* [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces Also clean up follow-on docs, environment guidance, package metadata, and lab test stability. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix deleted semantic-kernel sample links Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * improve foundry language * Fix A2A Foundry sample regression Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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35adfdb318 |
Python: Foundry Evals integration for Python (#4750)
* Foundry Evals integration for Python Merged and refactored eval module per Eduard's PR review: - Merge _eval.py + _local_eval.py into single _evaluation.py - Convert EvalItem from dataclass to regular class - Rename to_dict() to to_eval_data() - Convert _AgentEvalData to TypedDict - Simplify check system: unified async pattern with isawaitable - Parallelize checks and evaluators with asyncio.gather - Add all/any mode to tool_called_check - Fix bool(passed) truthy bug in _coerce_result - Remove deprecated function_evaluator/async_function_evaluator aliases - Remove _MinimalAgent, tighten evaluate_agent signature - Set self.name in __init__ (LocalEvaluator, FoundryEvals) - Limit FoundryEvals to AsyncOpenAI only - Type project_client as AIProjectClient - Remove NotImplementedError continuous eval code - Add evaluation samples in 02-agents/ and 03-workflows/ - Update all imports and tests (167 passing) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: resolve mypy redundant-cast errors while keeping pyright happy Use cast(list[Any], x) with type: ignore[redundant-cast] comments to satisfy both mypy (which considers casting Any redundant) and pyright strict mode (which needs explicit casts to narrow Unknown types). Also fix evaluator decorator check_name type annotation to be explicitly str, resolving mypy str|Any|None mismatch. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: CI failures — pyupgrade, evaluator overloads, sample API, reset attr - Apply pyupgrade: Sequence from collections.abc, remove forward-ref quotes - Add @overload signatures to evaluator() for proper @evaluator usage - Fix evaluate_workflow sample to use WorkflowBuilder(start_executor=) API - Fix _workflow.py executor.reset() to use getattr pattern for pyright - Remove unused EvalResults forward-ref string in default_factory lambda Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: skip gRPC-dependent observability test The test_configure_otel_providers_with_env_file_and_vs_code_port test triggers gRPC OTLP exporter creation, but the grpc dependency is optional and not installed by default. Add skipif decorator matching the pattern used by all other gRPC exporter tests in the same file. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: add nosec B101 for bandit assert check Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * style: align eval samples with repo conventions - Move module docstrings before imports (after copyright header) - Add -> None return type to all main() and helper functions - Fix line-too-long in multiturn sample conversation data - Add Workflow import for typed return in all_patterns_sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback: async fixes, sample bugs, deprecation warnings - Simplify _ensure_async_result to direct await (async-only clients) - Replace get_event_loop() with get_running_loop() - Narrow _fetch_output_items exception handling to specific types - Add warning log when _filter_tool_evaluators falls back to defaults - Add DeprecationWarning to options alias in Agent.__init__ - Add DeprecationWarning to evaluate_response() - Rename raw key to _raw_arguments in convert_message fallback - Fix evaluate_agent_sample.py: replace evals.select() with FoundryEvals() - Fix evaluate_multiturn_sample.py: use Message/Content/FunctionTool types - Fix evaluate_workflow_sample.py: replace evals.select() with FoundryEvals() - Update test mocks to use AsyncMock for awaited API calls Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add test coverage for review feedback items - Add num_repetitions=2 positive test verifying 2×items and 4 agent calls - Add _poll_eval_run tests: timeout, failed, and canceled paths - Add evaluate_traces tests: validation error, response_ids path, trace_ids path - Add evaluate_foundry_target happy-path test with target/query verification Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix ruff ISC004 lint error and apply formatter - Wrap implicit string concatenation in parens in evaluate_multiturn_sample.py - Apply ruff formatter to 6 other files with minor formatting drift Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove core type changes (extracted to fix/workflow-stale-session branch) Reverts changes to _agents.py, _agent_executor.py, and _workflow.py back to upstream/main. These fixes are now in a separate PR. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review round 2: bugs, tests, and architecture Code fixes: - Fix _normalize_queries inverted condition (single query now replicates to match expected_count) - Fix substring match bug: 'end' in 'backend' matched; use exact set lookup for executor ID filtering - Fix used_available_tools sample: tool_definitions→tools param, use FunctionTool attribute access instead of dict .get() - Add None-check in _resolve_openai_client for misconfigured project - Add Returns section to evaluate_workflow docstring - Cache inspect.signature in @evaluator wrapper (avoid per-item reflection) Architecture: - Extract _evaluate_via_responses as module-level helper; evaluate_traces now calls it directly instead of creating a FoundryEvals instance - Move Foundry-specific typed-content conversion out of core to_eval_data; core now returns plain role/content dicts, FoundryEvals applies AgentEvalConverter in _evaluate_via_dataset Tests: - evaluate_response() deprecation warning emission and delegation - num_repetitions > 1 with expected_output and expected_tool_calls - Mock output_items.list in test_evaluate_calls_evals_api - Update to_eval_data assertions for plain-dict format - Unknown param error now raised at @evaluator decoration time Skipped (separate PR): executor reset loop, xfail removal, options alias Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix CI: revert test_full_conversation, fix pyright errors - Revert test_full_conversation.py to upstream/main (the session preservation test was incorrectly changed to assert clearing) - Fix pyright reportUnnecessaryComparison on get_openai_client() None check by adding ignore comment - Fix pyright reportPrivateUsage: add public EvalItem.split_messages() method and use it in FoundryEvals._evaluate_via_dataset instead of accessing private _split_conversation Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review round 3: reliability, test gaps, cleanup - Add try/except guard for non-numeric score in _coerce_result - Add poll_interval minimum bound (0.1s) to prevent tight loops - Add runtime async client check in _resolve_openai_client - Remove _ensure_async_result wrapper (10 call sites → direct await) - Better error message when queries provided without agent - Import-time asserts for evaluator set consistency - Remove 28 redundant @pytest.mark.asyncio decorators - Add doc note about _raw_arguments sensitive data - Tests: tool_called_check mode=any, _normalize_queries branches, _extract_result_counts paths, _extract_per_evaluator, bare check via evaluate_agent, output_items assertion, modulo wrapping, async client check, queries-without-agent error Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix CI: ruff S101 assert, pyright and mypy arg-type errors - Replace module-level assert with if/raise for evaluator set consistency checks (ruff S101 disallows bare assert) - Add type: ignore[arg-type] and pyright: ignore[reportArgumentType] on OpenAI SDK evals API calls that pass dicts where typed params are expected (SDK accepts dicts at runtime) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review round 4: bugs, reliability, test fixes - Fix all_passed ignoring parent result_counts when sub_results present - Fix _extract_tool_calls: parse string arguments via json.loads before falling back to None (real LLM responses use string arguments) - Sanitize _raw_arguments to '[unparseable]' to avoid leaking sensitive tool-call data to external evaluation services - Add NOTE comment on to_eval_data message serialization dropping non-text content (tool calls, results) - Eliminate double conversation split in _evaluate_via_dataset: build JSONL dicts directly from split_messages + AgentEvalConverter - Raise poll_interval floor from 0.1s to 1.0s to prevent rate-limit exhaustion - Fix MagicMock(name=...) bug in test: sets display name not .name attr - Fix mock_output_item.sample: use MagicMock object instead of dict so _fetch_output_items exercises error/usage/input/output extraction Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review round 5: reliability, docs, test coverage Code fixes: - Move import-time RuntimeError checks to unit tests (avoids breaking imports for all users on developer set-drift mistake) - _filter_tool_evaluators now raises ValueError when all evaluators require tools but no items have tools (was silently substituting) - Add poll_interval upper bound (60s) to prevent single-iteration sleep - Log exc_info=True in _fetch_output_items for debugging API changes - Fix evaluate() docstring: remove claim about Responses API optimization - Validate target dict has 'type' key in evaluate_foundry_target - Document to_eval_data() limitation: non-text content is omitted Tests: - TestEvaluatorSetConsistency: verify _AGENT/_TOOL subsets of _BUILTIN - TestEvaluateTracesAgentId: agent_id-only path with lookback_hours - TestFilterToolEvaluatorsRaises: ValueError on all-tool no-items - TestEvaluateFoundryTargetValidation: target without 'type' key - Assert items==[] on failed/canceled poll results - Mock output_items.list in response_ids test for full flow - TestAllPassedSubResults: result_counts=None + sub_results delegation and parent failures override sub_results - TestBuildOverallItemEmpty: empty workflow outputs returns None Skipped r5-07 (_raw_arguments length hint): marginal debugging value, could leak content size information. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix error message: evaluate_responses() → evaluate_traces(response_ids=...) The referenced function doesn't exist; the correct API is evaluate_traces(response_ids=...) from the azure-ai package. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove dead to_eval_data() method, fix docstring claims - Remove to_eval_data() from EvalItem (dead code after r4-05 JSONL refactor) - Migrate 15 tests from to_eval_data() to split_messages() - Update sample to use split_messages() + Message properties - Remove unimplemented Responses API optimization docstring claim - Update split_messages() docstring to not reference removed method Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Reduce default eval timeout from 600s to 180s (3 minutes) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove dead _evaluate_via_responses method from FoundryEvals The method was never called — evaluate() uses _evaluate_via_dataset, and evaluate_traces() calls _evaluate_via_responses_impl directly. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Revert unrelated formatting changes to get-started samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright: remove phantom FoundryMemoryProvider import, apply ruff format - Remove import of non-existent _foundry_memory_provider module (incorrectly kept during rebase conflict resolution) - Apply ruff formatter to test_local_eval.py and get-started samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix eval samples: use FoundryChatClient for Agent() The upstream provider-leading client refactor (#4818) made client= a required parameter on Agent(). Update the three getting-started eval samples to use FoundryChatClient with FOUNDRY_PROJECT_ENDPOINT, matching the standard pattern from 01-get-started samples. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Simplify self-reflection sample using FoundryEvals Replace ~80 lines of manual OpenAI evals API code (create_eval, run_eval, manual polling, raw JSONL params) with FoundryEvals: - evaluate_groundedness() uses FoundryEvals.evaluate() with EvalItem - Remove create_openai_client(), create_eval(), run_eval() functions - Remove openai SDK type imports (DataSourceConfigCustom, etc.) - run_self_reflection_batch creates FoundryEvals instance once, reuses it for all iterations across all prompts Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update eval samples to FoundryChatClient and FOUNDRY_PROJECT_ENDPOINT - Migrate all foundry_evals samples from AzureOpenAIResponsesClient to FoundryChatClient - Update env var from AZURE_AI_PROJECT_ENDPOINT to FOUNDRY_PROJECT_ENDPOINT - Use AzureCliCredential consistently across all samples - Fix README.md: correct function names (evaluate_dataset -> FoundryEvals.evaluate, evaluate_responses -> evaluate_traces) - Update self_reflection .env.example and README.md Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix lint errors in eval samples (E501, ASYNC240, formatting) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove evaluate_all_patterns_sample.py (redundant with focused samples) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix async credential mismatch: use azure.identity.aio for async AIProjectClient AIProjectClient from azure.ai.projects.aio requires an async credential. Switch all foundry_evals samples from azure.identity.AzureCliCredential to azure.identity.aio.AzureCliCredential. Also pass project_client to FoundryChatClient instead of duplicating endpoint+credential. Close credential in self_reflection sample to avoid resource leak. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Revert test_observability.py to upstream/main (not our test) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address moonbox3 review: sphinx docstrings, pagination, isinstance check - Convert all Example:: / Typical usage:: code blocks to .. code-block:: python format matching codebase convention (both _evaluation.py and _foundry_evals.py) - Add async pagination in _fetch_output_items via async for (handles large result sets) - Replace hasattr(__aenter__) with isinstance(client, AsyncOpenAI) in _resolve_openai_client - Move AsyncOpenAI import from TYPE_CHECKING to runtime (needed for isinstance) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix test failures and address remaining moonbox3 review comments - Fix tests: use MagicMock(spec=AsyncOpenAI) for project_client mocks (isinstance check now requires proper type, not duck-typing) - Fix tests: replace mock_page.__iter__ with _AsyncPage helper for async for - Fix evaluate_response: auto-extract queries from response messages when query is not provided (previously always raised ValueError) - Add debug logging when skipping internal _-prefixed executor IDs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address Tao's PR review comments on Foundry Evals - T1: Add comment explaining builtin.* pass-through in _resolve_evaluator - T2: Add comment referencing OpenAI evals API for testing_criteria dict - T3: Document Mustache-style {{item.*}} template placeholders - T4: Document poll loop 60s sleep upper bound rationale - T5: Narrow run type to RunRetrieveResponse, use typed field access instead of vars()/getattr dance in _extract_result_counts and _extract_per_evaluator; use run.error and run.report_url directly - T6: Clarify openai_client docstring re: Azure Foundry endpoint - T8: Remove misleading empty expected_tool_calls from sample - Update tests to match real SDK PerTestingCriteriaResult shape Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove unnecessary Any union from run type annotations RunRetrieveResponse is the correct type — no backward compat needed for a brand new feature. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Accept FoundryChatClient instead of raw AsyncOpenAI FoundryEvals now takes client: FoundryChatClient as its primary parameter instead of openai_client: AsyncOpenAI. The builtin.* evaluators require a Foundry endpoint, so the type should reflect that. - FoundryEvals.__init__: client: FoundryChatClient replaces openai_client - evaluate_traces / evaluate_foundry_target: same change - _resolve_openai_client: extracts .client from FoundryChatClient - project_client fallback retained for standalone functions - All samples updated to construct FoundryChatClient and pass as client= - Tests updated (openai_client= → client=) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove implicit 60s upper bound on poll interval If a developer sets a higher poll_interval, respect it. Only clamp to remaining time and enforce a 1s minimum for rate-limit protection. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove 1s floor on poll interval — let the developer control it Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update python/samples/05-end-to-end/evaluation/foundry_evals/.env.example Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> * Update python/samples/02-agents/evaluation/evaluate_agent.py Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> * Address eavanvalkenburg review (round 2) on Python eval PR - Rename model_deployment -> model across FoundryEvals and all samples - Make model param optional, resolves from client.model - Convert EvalResults from dataclass to regular class - Remove deprecated evaluate_response() function - Refactor splitters: BUILT_IN_SPLITTERS dict + standalone functions - Change per_turn_items from classmethod to staticmethod - Simplify EvalCheck type alias to use Awaitable[CheckResult] - Remove errored property from EvalResults - Remove default value from Evaluator protocol eval_name - Rename assert_passed -> raise_for_status, add EvalNotPassedError - Type agent param as SupportsAgentRun | None - Fix Arguments docstring - Update __init__.py exports - Update all tests and samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Move FoundryEvals to foundry package, split tool eval sample - Move _foundry_evals.py from azure-ai to foundry package - Move test_foundry_evals.py to foundry/tests/ - Update lazy re-exports in agent_framework.foundry namespace - Update .pyi type stubs - All samples now import from agent_framework.foundry - Split tool-call evaluation into evaluate_tool_calls_sample.py - Fix all_passed to check errored count from result_counts - Fix raise_for_status to include errored item details Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Auto-create FoundryChatClient from env vars when no client provided FoundryEvals() now works zero-config when FOUNDRY_PROJECT_ENDPOINT and FOUNDRY_MODEL environment variables are set. Auto-creates a FoundryChatClient under the hood, matching the established env var pattern. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright errors: remove dead _normalize_queries, suppress EvalAPIError check - Remove unused _normalize_queries function and its tests - Add pyright ignore for EvalAPIError None check (defensive guard) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Support multimodal image content in eval pipeline Add image (data/uri) content handling to AgentEvalConverter.convert_message() so that Content.from_data() and Content.from_uri() image payloads are preserved as input_image parts in the Foundry evaluator format. - Handle Content type='data' and type='uri' → emit input_image parts - Add 6 unit tests for image content through convert_message/convert_messages - Add integration test verifying images flow through EvalItem → JSONL path - Add evaluate_multimodal.py sample demonstrating local image eval Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address remaining review comments - Fix project_client docstring to say async-only (not sync/async) - Add builtin evaluator name validation warning in _resolve_evaluator - Replace getattr with typed attribute access in _poll_eval_run, _extract_result_counts, _extract_per_evaluator, _fetch_output_items - Remove cast import from _foundry_evals (no longer needed) - Tighten _coerce_result: honour explicit 'passed' when both 'score' and 'passed' are present; remove performative cast - Fix self_reflection sample: add env file existence check - Fix traces sample: correct Pattern 2 section label - Update all Foundry eval samples to FoundryChatClient + FOUNDRY_MODEL (remove AIProjectClient + AZURE_AI_MODEL_DEPLOYMENT_NAME pattern) - Add eval_name and OpenAI client docs to FoundryEvals docstring - Update test mocks to match typed SDK objects (_MockResultCounts) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix ruff lint errors (E501, SIM108, SIM102) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix pyright errors: type-narrow dict to dict[str, Any], add ignore comments Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Replace ConversationSplitter type alias with Protocol ConversationSplitter is now a runtime-checkable Protocol with a named 'conversation' parameter, making the expected signature self-documenting. ConversationSplit enum members gain a __call__ method so they satisfy the protocol directly -- ConversationSplit.LAST_TURN(conversation) works. This simplifies _split_conversation from an isinstance dispatch to a single split(conversation) call. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Standardize on AZURE_AI_MODEL_DEPLOYMENT_NAME and fix Unicode in samples - Replace FOUNDRY_MODEL with AZURE_AI_MODEL_DEPLOYMENT_NAME in all eval samples to match repo convention - Replace Unicode symbols with ASCII equivalents in all eval sample print statements to avoid cp1252 encoding errors on Windows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update python/samples/03-workflows/evaluation/evaluate_workflow.py Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> * Apply suggestions from code review Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> * Rename ADR 0020 to 0023 (foundry evals integration) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: alliscode <bentho@microsoft.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com> |
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Giles OdigweandGitHub
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0e00e5f8dd |
Python: Update Python Packages for rc6 (#4979)
* python package update * small fix |
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b1b528e4a8 |
Python: [BREAKING] Remove deprecated kwargs compatibility paths (#4858)
* [BREAKING] Remove deprecated kwargs compatibility paths Remove the deprecated kwargs compatibility shims across core agents, clients, tools, middleware, and telemetry. Keep workflow kwargs behavior intact in this branch and follow up separately in #4850. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix PR CI fallout for kwargs removal Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updates * Fix Azure AI CI fallout Remove the stale _get_current_conversation_id override from the Azure AI client after the OpenAI base helper was deleted. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixed new classes * Fix Assistants deprecated import gating Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix integration replay regressions Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Switch multi-agent hosting samples to Azure chat completions Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Simplify Azure multi-agent sample config Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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cc0cfaaac8 |
[BREAKING] Python: fix OpenAI Azure routing and provider samples (#4925)
* Python: fix OpenAI Azure routing and provider samples Prefer OpenAI when OPENAI_API_KEY is present unless Azure is explicitly requested. Clarify constructor docs, keep deprecated Azure wrappers compatible with stricter settings validation, and refresh the provider samples and tests to use the current client patterns. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix bandit * Python: align OpenAI embedding Azure routing Extend the shared OpenAI-vs-Azure routing and credential behavior to the embedding client, add Azure embedding regression coverage, and refresh the embedding samples to use the generic client path. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix embedding client pyright check Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: thin OpenAI embedding wrapper Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: document embedding overload routing Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix callable OpenAI key routing Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix Azure credential routing tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: address OpenAI review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: narrow Azure routing markers Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: refine OpenAI model fallback order Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: narrow Azure deployment docs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: remove embedding routing wording Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: run embedding Azure integration tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * changed variable name * Python: expand OpenAI package README Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * clarified readme * Python: fix Azure OpenAI integration setup Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: correct Azure integration env mapping Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated code to fix int tests * test updates * test fix * fix test setup * updates to tests and setup * remove openai assistants int tests * improvements in int tests * fix env var * fix env vars * fix azure responses test * trigger actions --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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c012aac5f2 |
Python: [BREAKING] Reduce core dependencies and simplify optional integrations (#4904)
* improved dependencies and some fixes * fix for mypy * improve mcp |