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peibekwe/declarative-python-bugfix
100
Commits
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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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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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4609535e22 |
Python: feat: add agent-framework-monty (Monty-backed CodeAct provider) (#5915)
* Python: feat: add agent-framework-monty (Monty-backed CodeAct)
New alpha package that wraps pydantic-monty (a Rust-based Python
interpreter) behind the same CodeAct API surface as
agent-framework-hyperlight, so users can swap providers with minimal
code change.
Public API (agent_framework_monty):
- MontyCodeActProvider — ContextProvider that injects a run-scoped
execute_code tool plus dynamic CodeAct instructions.
- MontyExecuteCodeTool — standalone FunctionTool for mixed-tool agents
or manual static wiring.
- FileMount / FileMountInput / MountMode — public types mirroring the
Hyperlight names, with Monty's mode (read-only/read-write/overlay)
and write_bytes_limit on FileMount.
Constructor kwargs (both classes) mirror Hyperlight where possible:
tools, approval_mode, workspace_root, file_mounts; plus a Monty-only
resource_limits forwarding ResourceLimits to Monty.start().
Filesystem flow:
- workspace_root auto-mounts at /input (read-write), matching Hyperlight.
- file_mounts accepts string shorthand, (host, mount) tuple, or
FileMount with mode + write cap.
- Files written under read-write mounts are scanned post-execution and
returned as Content.from_data items (mirrors Hyperlight /output).
- overlay mounts buffer writes in-memory; read-only mounts reject writes.
Internals:
- _monty_bridge.InlineCodeBridge ports the inline (non-durable) bridge
from anthonychu/maf-codeact-monty-python; handles FunctionSnapshot /
FutureSnapshot pause/resume, dispatches direct typed calls + the
call_tool fallback, forwards mount/limits to Monty.start(...).
- generate_type_stubs emits per-tool stubs so Monty's `ty` type-checker
rejects bad calls before any host tool runs.
Alpha-policy compliance (per python-package-management skill):
- Added agent-framework-monty = { workspace = true } to root
pyproject.toml.
- Added row to python/PACKAGE_STATUS.md.
- Added monty entry under Experimental in python/AGENTS.md.
- NOT added to core[all]; NO agent_framework.monty lazy shim (deferred
to beta promotion).
Samples (three sets, import from agent_framework_monty directly):
- samples/02-agents/context_providers/code_act/monty_code_act.py
(provider pattern) + updated local README.
- samples/02-agents/tools/monty_code_interpreter/ (standalone +
manual-wiring + README).
- samples/04-hosting/foundry-hosted-agents/responses/11_monty_codeact/
(full hosted-agent layout with uv-based pyproject.toml + Dockerfile,
Azure Monitor wiring via APPLICATIONINSIGHTS_CONNECTION_STRING +
enable_instrumentation, ENABLE_INSTRUMENTATION and
ENABLE_SENSITIVE_DATA env vars). The alpha wheel is vendored into
./wheels/ (gitignored) via vendor-wheel.sh; new row added to the
parent Responses-API README.
Tests:
- 28 hermetic unit tests (stubbed pydantic_monty).
- 18 integration tests marked @pytest.mark.integration, auto-skipped
when pydantic_monty is unimportable; exercise the real Monty
runtime: print round-trip, last-expression value, direct typed
tool dispatch, call_tool fallback, async tool, asyncio.gather
parallelism, ty type-check rejection, OS blocked by default,
workspace_root read+write capture, read-only / overlay mount
semantics, resource_limits.max_duration_secs abort, approval
gating end-to-end, full Agent run with a scripted chat client.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: fix: monty FileMount test compares against the normalized POSIX path
The shorthand string mount goes through _normalize_mount_path, which
rewrites Windows drive letters like 'C:\\Users\\...' into
'/C:/Users/...' (POSIX-style). The Windows CI runners surfaced this
because tmp_path resolves to a backslashed Windows path; the test was
comparing against the raw str(host_a) instead of the normalized form.
Compare against _normalize_mount_path(str(host_a)) so the assertion is
platform-independent.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: fix: address PR #5915 review feedback
- _execute_code_tool docstring: clarify that the Monty backend supports
scoped filesystem access via workspace_root / file_mounts (blocked by
default).
- _to_monty_mount: import pydantic_monty lazily through load_monty so
missing-dependency errors surface as the same actionable RuntimeError
the rest of the package raises (not a bare ImportError at module load).
Renamed _load_monty -> load_monty for the same reason.
- _python_type_repr: emit None for type(None) instead of Any, and
normalize both typing.Union[...] and PEP-604 X | Y to PEP-604 syntax
so Optional[X] / Union[..., None] / -> None signatures round-trip
correctly through ty validation. Added a regression test.
- _PrintCollector: track a running character count instead of
recomputing sum(len(c) for c in self.chunks) per callback. Eliminates
the O(n^2) cost on print-heavy code.
- Instructions: mention that the value of the final expression is also
returned alongside captured stdout (matches actual behavior).
- 11_monty_codeact Dockerfile: pin ghcr.io/astral-sh/uv to 0.11.6
instead of :latest for reproducible builds.
- 11_monty_codeact README: replace the bare "see parent README" pointer
with sample-specific steps (./vendor-wheel.sh + uv sync + uv run),
since the sample uses pyproject.toml + a vendored wheel rather than
requirements.txt.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: sample: 11_monty_codeact installs agent-framework-monty from PyPI
Drop the vendored-wheel scaffolding now that agent-framework-monty is on
PyPI as an alpha (1.0.0a*) release:
- pyproject.toml: remove [tool.uv.sources] override; keep [tool.uv]
prerelease = "allow" so uv pulls the alpha automatically.
- Dockerfile: drop the COPY wheels/ step.
- README: drop the ./vendor-wheel.sh setup step and the
not-yet-on-PyPI warning.
- Delete vendor-wheel.sh and the gitignored wheels/ directory.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: fix(monty): harden post-execution file capture against symlink escape
Same class of issue as the MSRC-reported Hyperlight finding: the
post-execution capture walked workspace_root with Path.rglob() +
is_file() + read_bytes() - all of which follow symlinks. An attacker
who controls the workspace (cloned repo, extracted archive, shared
workspace) could pre-place `workspace/leak.txt -> /etc/passwd` or
`workspace/outside_dir -> /etc/` and have host files surface as
captured Content items.
Monty's mount layer already rejects symlink reads from inside the
sandbox across all three modes (verified empirically), so the runtime
path was safe. This commit closes the post-execution scan path.
Changes:
- New `_iter_real_files(root)` walker that uses iterdir() +
is_symlink() to skip symlinks at every directory level and yields
only real files. Replaces the previous `host_root.rglob("*")` calls
in both `_snapshot_writable_mounts` and `_capture_written_files`.
- Use `Path.lstat()` instead of `Path.stat()` so size/mtime can never
be taken from a symlink target.
- Three new integration tests reproducing the MSRC attack shape
against the workspace_root flow: symlink-to-file outside workspace,
symlink-to-directory outside workspace, and a guard ensuring
legitimate sandbox writes are still captured when symlinks are
present.
Per user request, hyperlight is untouched in this commit (separate fix).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: fix(monty): skip symlink regression tests when unsupported
Apply the same Windows-CI safety guard as the hyperlight fix in PR #5919:
the three symlink integration tests create symlinks via Path.symlink_to(),
which fails with OSError / NotImplementedError on unprivileged Windows
runners. Add a local _symlinks_supported helper (mirroring the one in
packages/core/tests/core/test_skills.py) and pytest.skip when symlinks
aren't available, so the tests no longer fail for environment reasons.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: fix(monty): address PR #5915 follow-up review feedback
- _invoke_tool: drop the inspect.iscoroutinefunction(...) branch and
always `await self.tool_map[name](**kwargs)`. Every entry in
tool_map is `partial(FunctionTool.invoke, skip_parsing=True)` and
FunctionTool.invoke is `async def`, so the branching was dead code -
and on Python versions affected by cpython#98590,
iscoroutinefunction(partial(bound_async_method, ...)) returns False,
causing the bridge to take the asyncio.to_thread path, return an
unawaited coroutine, and surface it as a JSON-serialization failure
for every tool call. Added a regression test
test_invoke_tool_awaits_partial_wrapped_async_method.
- generate_type_stubs: skip tools whose name is not a valid Python
identifier or is a Python keyword. FunctionTool.name has no upstream
validation, so a name like "weird-name" produced a syntax error in
the stubs and a name like "broken\n pass\nasync def injected"
would inject arbitrary stub source. Non-identifier names stay
reachable via `call_tool("weird-name", ...)` at runtime; they just
don't get type-checked stubs. Added regression test
test_generate_type_stubs_skips_non_identifier_tool_names.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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8636c70ddf |
ci(python-setup): drop -U upgrade flag from uv sync (#5961)
The shared composite action ran `uv sync --all-packages --all-extras
--dev -U` on every job, which upgrades every dependency to the latest
compatible version instead of using the pinned versions in `uv.lock`.
That is currently producing a hard resolver failure on every CI job:
No solution found when resolving dependencies for split
(markers: python_full_version >= '3.11' and sys_platform == 'darwin')
Because there are no versions of durabletask and
agent-framework-durabletask depends on durabletask>=1.3.0,<2,
we can conclude that agent-framework-durabletask's requirements
are unsatisfiable.
Dropping `-U` makes the install use the workspace lockfile, which is
what is reproducible locally and what we publish releases against.
Upgrades should be opt-in (via a scheduled job or a separate workflow)
rather than implicit on every CI run.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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66a09a76af |
Python: fix: hyperlight skips symlinks when staging sandbox input (#5919)
* Python: fix(hyperlight): skip symlinks when staging files into the sandbox The helpers that populate the sandbox input tree (``_copy_path`` and the ``_path_tree_signature`` walker used for cache invalidation) relied on ``Path.is_file()``, ``Path.is_dir()`` and ``shutil.copy2`` - all of which follow symlinks by default. When the source tree contains symlinks, that let entries from outside the configured input source surface inside the sandbox. Harden both code paths to never follow symlinks: - ``_copy_path`` now bails out via ``Path.is_symlink()`` before any ``is_dir()`` / ``is_file()`` check, skips non-regular files, and uses ``shutil.copy2(..., follow_symlinks=False)`` as defense in depth. - New ``_iter_real_entries`` walker replaces the previous ``Path.rglob`` call inside ``_path_tree_signature`` (rglob follows directory symlinks). - ``_path_tree_signature`` switches to ``Path.lstat()`` so size/mtime are never read through a symlink target. Added regression tests covering: - A pre-placed file symlink in ``workspace_root`` (top level). - A pre-placed directory symlink in ``workspace_root``. - A nested file symlink inside a real subdirectory. - ``_path_tree_signature`` ignoring symlinks so the cache key reflects only what is actually staged. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix(hyperlight): address PR #5919 review feedback - _iter_real_entries now yields directories and regular files only, skipping non-regular entries (sockets/FIFOs/devices). Keeps the cache-key signature consistent with what _copy_path actually stages. - The four new symlink regression tests skip when the platform does not support symlink creation (e.g. unprivileged Windows runners), via a local _symlinks_supported helper modelled on the one in packages/core/tests/core/test_skills.py. Prevents OSError / NotImplementedError from failing CI jobs that have nothing to do with the change under test. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: fix(hyperlight): address PR #5919 follow-up review feedback - _copy_path docstring: narrow the scope to "symlink entries present in the source tree at rest" and explicitly call out that the copy is NOT atomic with respect to concurrent mutation of the source tree. Callers who need that stronger guarantee should snapshot their workspace before passing it in. Avoids overpromising on a TOCTOU window that pathlib cannot express; closing it properly would need fd-based traversal (O_NOFOLLOW | O_DIRECTORY + os.scandir(fd)) with a separate Windows story, which is out of scope for this targeted fix. - _path_tree_signature: drop the `if path.is_symlink(): return ()` short-circuit. Resolve a symlink root to its real target before walking instead. The public construction flow already resolves workspace_root / file_mounts[].host_path up front so this never affected user-facing code, but the short-circuit was misleading and would have produced an empty, stable signature for any direct caller that builds a _RunConfig without going through the public constructor. Defense in depth: even if a future call site forgets to resolve the root, the cache key still reflects real contents. - Added regression test test_path_tree_signature_walks_through_symlinked_root: a symlinked workspace root must produce a non-empty signature, AND the signature must change when the real target's contents change so the cache key actually invalidates. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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a95493a909 |
Python: Core: notify agent of external AgentModeProvider mode changes (#5650)
When the operating mode is changed externally (e.g. via a slash-command handler calling set_agent_mode), the agent's chat history still shows the prior set_mode tool call near the end. Updating only the system instructions is insufficient — models tend to anchor on the recent tool call and ignore the new mode. Mirror the .NET AgentModeProvider behavior: when set_agent_mode detects an actual mode change, record the previous mode in provider state. On the next before_run, the provider pops that flag and injects a user-role notification message announcing the switch, so the most recent context unambiguously reflects the current mode. The agent-driven set_mode tool path bypasses this so it does not trigger a redundant notification on its own change. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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ddfbdf5c7a |
Python: information-flow control prompt injection defense (#5331)
* Python: Information-flow control based prompt injection defense (#5024) * fides integration * documentation * documentation * documentation * human-approval on policy violation * numenous hyena 'works' * IFC based implementation * minor edits in documentation * rebasing the branch and running the email example * Add security tests for IFC middleware * Fix Role.TOOL NameError in approval handling * tiered labelling scheme * 3 tier labelling scheme in middleware * Adapt security middleware to list[Content] tool results * Refactor SecureAgentConfig as context provider and address Copilot review comments * Update FIDES docs to reflect context provider pattern and update code for ContextProvider rename * Fix security examples: use OpenAIChatClient instead of non-existent AzureOpenAIChatClient * Address PR review: consolidate security modules, remove ContentLineage, update docs * remove unrelated files * remove comment from _tools.py and rename decision file * Fix CI failures: Bandit B110, broken md links, hosted approval passthrough * apply template to decision doc 0024 * minor fixes to decision doc 0024 --------- Co-authored-by: Aashish <t-akolluri@microsoft.com> * Python: follow up FIDES security flow (#5330) * Python: follow up FIDES security flow Refine the secure approval path, mark the security classes with the FIDES experimental feature label, and clean up the related docs/tests. Also fix workspace-level validation regressions uncovered while running the full Python check suite. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: remove FIDES GitHub MCP sample Drop the GitHub MCP security sample from the FIDES follow-up branch while keeping the remaining security docs and samples intact. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: fix paths and update FIDES implementation (#5352) * Python: updated import naming and comment from review (#5421) * updated import naming and comment from review * Add approval replay None call-id test Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Address PR 5331 comments and track sesssion while calling Agent in email_security_example (#5446) * Address PR review: fix paths and update FIDES implementation * Address PR comments and add session tracking in email example in samples * Fix session creation and resolve merge conflict in docstring example * Resolve merge conflict in docstring example * Python: add test for empty-message pruning in approval result replacement (#5617) Adds test coverage for the second-pass logic in `_replace_approval_contents_with_results` that removes messages whose `contents` list becomes empty after first-pass content removal. Addresses review comment on PR #5331: https://github.com/microsoft/agent-framework/pull/5331#discussion_r3129039445 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: shrutitople <shruti.tople@gmail.com> Co-authored-by: Aashish <t-akolluri@microsoft.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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e7dc3b91f1 |
.NET: Add Microsoft.Agents.AI.Hyperlight package for CodeAct integration (.NET) (#5329)
* Add Microsoft.Agents.AI.Hyperlight package for CodeAct integration Introduces a new Microsoft.Agents.AI.Hyperlight package that enables CodeAct-style sandboxed code execution via Hyperlight (hyperlight-sandbox .NET SDK, PR #46) for .NET agents, following the docs/features/code_act/dotnet-implementation.md design and the Python agent_framework_hyperlight reference. Highlights: - HyperlightCodeActProvider (AIContextProvider): injects an execute_code tool and CodeAct guidance per invocation; single-instance-per-agent via a fixed StateKeys value; supports multiple provider-owned tools (exposed inside the sandbox via call_tool), file mounts, and an outbound domain allow-list; snapshot/restore per run. - HyperlightExecuteCodeFunction: standalone AIFunction for manual/static wiring when the sandbox configuration is fixed. - Approval model via CodeActApprovalMode (AlwaysRequire / NeverRequire) with propagation from ApprovalRequiredAIFunction-wrapped tools. - Unit tests (instruction builder, tool bridge, approval computation, provider CRUD, ProvideAIContextAsync snapshot isolation and approval wrapping). - Env-gated integration test (HYPERLIGHT_PYTHON_GUEST_PATH). - Three samples under samples/02-agents/AgentWithCodeAct (interpreter, tool-enabled, manual wiring). Build is not yet runnable: requires .NET SDK 10.0.200 and the not-yet-published HyperlightSandbox.Api 0.1.0-preview NuGet package. Package is marked IsPackable=false until the dependency is available. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR #5329 review feedback for Hyperlight CodeAct provider - A. Build-breakers: drop unused usings, override test TargetFrameworks off net472, drop redundant Microsoft.Extensions.AI.Abstractions PackageRef. - B. API: keep CRUD but rebuild sandbox when config fingerprint changes; add HyperlightCodeActProviderOptions.CreateForWasm/CreateForJavaScript factory methods (Backend/ModulePath now read-only); rename WorkspaceRoot to HostInputDirectory; convert AllowedDomain & FileMount from record to sealed class; drop ToolBridge.Unwrap (ApprovalRequiredAIFunction is invocable as-is). - C. ToolBridge: collapse SerializeResult switch; add comment explaining AOT-driven choice to keep JsonNode.Parse over typed Deserialize. - D. InstructionBuilder: drop language-specific 'Python code' phrasing; strip host filesystem paths from execute_code description. - E. Style polish: ternary expression-body for ComputeApprovalRequired, .Where(x is not null), .ToList() over .ToArray() in IReadOnlyList returns. - F. Samples: add guest-module / KVM-WHP build instructions to Step01; note future Excel-upload sample in Step02. Also adds SandboxExecutorTests covering the new RunSnapshot.ComputeFingerprint used for sandbox-rebuild detection. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Align Hyperlight package id and JS warm-up with merged upstream SDK The .NET SDK in hyperlight-dev/hyperlight-sandbox PR #46 has merged. The published package id is Hyperlight.HyperlightSandbox.Api (the bare HyperlightSandbox.Api remains the assembly/namespace) and the reference CodeExecutionTool uses 'void 0;' as the JavaScript warm-up no-op. Update the package reference, project comment, README, and SandboxExecutor warm-up accordingly. No functional change beyond that — all other public APIs we depend on (SandboxBuilder.With*, Sandbox.Run/RegisterToolAsync/AllowDomain/Snapshot/ Restore, ExecutionResult, SandboxBackend) match the merged shape. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Bump Hyperlight package to 0.4.0 and fix build/test issues Hyperlight.HyperlightSandbox.Api 0.4.0 is now published on nuget.org. Bump the version reference and address the analyzer/runtime issues that surfaced once restore could complete: - Add HyperlightJsonContext source-generated JsonSerializerContext for the execute_code result + tool error envelopes; route arbitrary AIFunction results through AIJsonUtilities.DefaultOptions to keep IsAotCompatible=true. - Replace explicit ObjectDisposedException throws with ObjectDisposedException.ThrowIf (CA1513). - Use HyperlightSandbox.Api.SandboxBackend in cref docs to disambiguate. - Update tests to match AIContext.Tools being IEnumerable<AITool>, drop ConfigureAwait(false) in xUnit test methods (xUnit1030), use collection expressions for AllowedDomain methods. - Add 'using OpenAI.Chat;' to all three samples so AsAIAgent resolves. - Verified: dotnet build of all four hyperlight projects + samples succeeds on net8/9/10; dotnet test for the unit tests passes 32/32 on net10.0. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix CI check failures: file encoding (UTF-8 BOM + LF) and broken markdown link - Convert all new .cs/.csproj files to UTF-8 with BOM and LF line endings to satisfy the dotnet/.editorconfig charset/end_of_line settings enforced by check-format. - Drop unused System.Collections.Generic using in HyperlightCodeActProviderTests. - Add missing using Microsoft.Extensions.AI in CodeActApprovalMode.cs and shorten ApprovalRequiredAIFunction cref (IDE0001). - Fix broken README link to docs/decisions/0024-codeact-integration.md. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: AIFunction inheritance, packaging, GetService approval check - HyperlightExecuteCodeFunction now inherits AIFunction directly. The AsAIFunction() indirection is gone; instances are accepted anywhere an AIFunction is. Approval requirement is surfaced via GetService<ApprovalRequiredAIFunction>() which lazily exposes a wrapping ApprovalRequiredAIFunction proxy when the effective ApprovalMode/tool stack requires it. - ComputeApprovalRequired now uses GetService<ApprovalRequiredAIFunction>() so approval-required tools nested anywhere in the AITool decorator stack are detected (not just the top-most class). - csproj: drop IsPackable=false (ready to release with the published Hyperlight.HyperlightSandbox.Api 0.4.0 dependency); add PackageReadmeFile and pack README.md at the package root, matching the pattern used by Aspire.Hosting.AgentFramework.DevUI / Microsoft.Agents.AI.DurableTask. - Update Step03 sample and README wording to reflect direct AIFunction usage. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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d7ca9c8f16 |
Python: Core: add experimental session-mode harness context provider (#5611)
* Python: Core: add experimental session-mode harness context provider Introduces the _harness namespace and the first context provider: SessionModeContextProvider, with get_session_mode / set_session_mode helpers and a DEFAULT_MODE_SOURCE_ID constant. Behind @experimental(ExperimentalFeature.HARNESS). Also folds in a small _sessions.py cleanup (try/except ImportError -> contextlib.suppress) touched while developing the harness. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: align session-mode harness with .NET AgentModeProvider Mirror the default mode descriptions and instruction template used by the .NET AgentModeProvider so the cross-language harness UX is consistent. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: address review feedback on session-mode harness - json.dumps tool outputs to stay valid for arbitrary mode names - normalize configured mode keys (lower+strip) so custom-cased configs work - raise TypeError instead of silently replacing non-dict session state - mark get_session_mode/set_session_mode as @experimental(HARNESS) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: rename SessionModeContextProvider to AgentModeProvider Match the .NET AgentModeProvider class name for cross-language consistency. Helpers renamed accordingly: get_session_mode -> get_agent_mode, set_session_mode -> set_agent_mode. The default source_id is now "agent_mode". Construction pattern stays Pythonic (kwargs, not an options object). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: address AgentModeProvider review feedback - default_mode now defaults to None and falls back to the first configured mode, decoupling the kwarg from the built-in 'plan'/'execute' set. - get_agent_mode catches ValueError when a previously persisted mode is no longer in available_modes and resets to the default mode (matching the non-string recovery branch). Added regression coverage for both behaviors. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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57c901a245 |
Python: Fix hyperlight WasmSandbox cross-thread Drop and harden hosted-agent sample (#5603)
* update hyperlight to beta and move samples, add hosted agent sample * Python: Fix hyperlight WasmSandbox cross-thread Drop and harden sample Root cause: when a worker-side closure raised, the exception's __traceback__ retained frame locals that included the partially constructed PyO3 sandbox. Future.result() re-raised that exception on the caller thread, and when the caller's exception was eventually GC'd the frame locals were released off-thread, dec_ref'ing the unsendable sandbox from the wrong thread and tripping the PyO3 panic '_native_wasm::WasmSandbox is unsendable, but is being dropped on another thread'. Fix: * Add _SandboxWorker._run_on_worker which catches every exception on the worker, drops __traceback__ there, deletes the original exception, and re-raises a fresh instance on the caller thread. initialize and execute route through it; dispose keeps its bare-submit semantics. * Add an opt-in diagnostic module _drop_diagnostic (no-op unless HYPERLIGHT_TRACE_DROPS=1) that installs a sys.unraisablehook and dumps owner-thread + per-thread stacks on any future cross-thread unsendable Drop. Useful for triaging similar PyO3 regressions. * Tests: cross-thread invocation, traceback-leak isolation, _SandboxEntry attribute-shape check, and a stale-reference stress test driven through asyncio.to_thread. Sample (samples/04-hosting/foundry-hosted-agents/responses/06_hyperlight_codeact): * Dockerfile installs agent-framework-* from in-tree source with python/ as build context so unreleased fixes can be validated end-to-end. * call_server.py pins the Responses API version. * main.py enables include_detailed_errors=True so future tool failures surface the actual exception text instead of a bare 'Error: Function failed.' string. * README.md documents the in-tree-package build and the Hyperlight hypervisor requirement (/dev/kvm on Linux, MSHV on Windows). Hosted environments without hypervisor passthrough surface 'No Hypervisor was found for Sandbox'; this is a hosting constraint, not a hyperlight bug. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: remove _drop_diagnostic from hyperlight package The diagnostic module was useful while bisecting the cross-thread Drop bug, but it is no longer needed now that _SandboxWorker._run_on_worker prevents the panic at the source. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: address PR review feedback on hyperlight - Use lazy agent_framework.hyperlight import in sample main.py. - Env-driven endpoint (FOUNDRY_AGENT_ENDPOINT) in call_server.py; remove personal URLs. - Align agent.yaml model deployment with manifest (gpt-4.1-mini). - Tighten Dockerfile requirements guard; drop dangling deploy.ps1 reference. - Preserve exception args when sanitizing tracebacks in _run_on_worker. - Add public _SandboxWorker.is_alive(); update test to avoid private attr. - Add namespace coverage tests for agent_framework.hyperlight lazy loader. - Add prominent note: Foundry hosted-agent runtime does not yet support Hyperlight (no hypervisor exposed); container works locally with /dev/kvm. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: bump hyperlight-sandbox dependencies to 0.4.x Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: renumber hyperlight codeact sample to 08 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Coerce worker exception args to strings for cross-thread safety Stringify exc.args on the worker thread before propagating, so any PyO3 unsendable object captured in args (e.g. via a caller-supplied callback or underlying SDK) cannot be Dropped on the calling thread. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * moved sample --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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550209fe6e |
Python: Core: add experimental todo-list harness context provider (#5612)
* Python: Core: add experimental todo-list harness context provider Adds TodoListContextProvider with pluggable TodoStore backends: TodoSessionStore (in-session) and TodoFileStore (JSONL on disk). Public types: TodoItem, TodoInput. Behind @experimental(ExperimentalFeature.HARNESS). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: align todo harness instructions with .NET TodoProvider Reformat DEFAULT_TODO_INSTRUCTIONS to mirror the .NET TodoProvider DefaultInstructions wording and structure, and bring the class docstring closer to the .NET XML <remarks> block. Keeps Python tool names in snake_case. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: address review feedback on todo harness - mark TodoStore as @experimental(HARNESS) for surface consistency - TodoSessionStore.load_state now raises ValueError on malformed items - TodoFileStore now namespaces persisted state by source_id - TodoFileStore now safely encodes session_id/owner and verifies path containment (matches FileHistoryProvider pattern) - per-(session, source_id) asyncio.Lock around read-modify-write to avoid races Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: rename TodoListContextProvider to TodoProvider Match the .NET TodoProvider class name for cross-language consistency. Other public types (TodoStore, TodoSessionStore, TodoFileStore, TodoItem, TodoInput) are unchanged. Construction stays Pythonic (kwargs, not an options object). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: address TodoProvider review feedback - TodoStore.load_state/save_state are now async; TodoFileStore performs disk I/O via asyncio.to_thread so the event loop is no longer blocked while the per-session mutation lock is held. - TodoSessionStore now raises ValueError for malformed top-level state (non-dict / non-list 'items' / non-int 'next_id') to match the TodoFileStore contract instead of silently re-defaulting. - Both stores now clamp next_id to max(item.id) + 1 after load to make ID collisions impossible after recovery or reconfiguration. - TodoFileStore writes atomically by writing a sibling temp file and os.replace-ing it so a crash mid-write cannot truncate the state file. - TodoFileStore.load_state no longer creates parent directories for sessions that never write; mkdir is deferred to save_state. - TodoProvider mutation locks now live in a weakref.WeakKeyDictionary keyed by AgentSession, so locks for GC'd sessions are evicted instead of leaking in long-running services. Tests cover each change including a TodoFileStore-backed end-to-end provider flow, atomic-write recovery, and lock GC eviction. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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4a2da953ca |
Python: Core: add experimental memory harness context provider (#5613)
* Python: Core: add experimental memory harness context provider Adds MemoryContextProvider with topic-indexed long-term memory and chat-driven compaction. Pluggable MemoryStore backends include MemoryFileStore. Public types: MemoryIndexEntry, MemoryTopicRecord. Behind @experimental(ExperimentalFeature.HARNESS). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Core: address review feedback on memory harness - mark MemoryStore as @experimental(HARNESS) for surface consistency - safely encode owner id and verify path containment (matches FileHistoryProvider pattern) - namespace MemoryFileStore on-disk layout by source_id to avoid cross-provider collisions - before_run computes index_entries once and only rewrites MEMORY.md when content changes - asyncio locks around topic/state read-modify-write to avoid concurrent-write races Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR feedback: harden memory store IO + consolidation behavior - Atomic writes via os.replace + temp sibling for topic, state, and index files so crashes/disk-full failures cannot leave a truncated half-written file. - Stop creating directories on read paths: list_topics/read_state/search_transcripts and get_messages return empty when nothing has been written. mkdir is deferred to the actual save path (write_topic/write_state/save_messages). - Escape lines that look like markdown headings on render and unescape them on parse, so a memory or summary containing '## Summary'/'## Memories' cannot tamper with the topic file structure. - Narrow extraction/consolidation chat-client failure handling to ChatClientException, asyncio.TimeoutError, and OSError. Programmer errors (AttributeError, TypeError, ...) now propagate so misconfigured clients fail loudly. - Log a payload-prefix preview for every silent shape branch in _extract_memories and _consolidate_topic so unparsable extractor output is debuggable instead of invisible. - Restructure _run_consolidation: read maintenance state and topic snapshot under the state lock, run the LLM consolidation loop without holding the state lock, and only advance last_consolidated_at/sessions_since_consolidation if at least one topic succeeded. Transient consolidation failures now leave the maintenance window in place so the next after_run retries instead of silently sliding forward. - Add regression tests for: markdown-marker round-trip, atomic-write recovery on os.replace failure, no-mkdir on pure read paths, transient consolidation failure preserves state, and propagation of programmer errors. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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c1cc6ee6df |
Python: Enforce approval_mode in Claude and GitHub Copilot agents (#5562)
* Python: Enforce approval_mode in Claude and GitHub Copilot agents Tools declared with approval_mode="always_require" were bypassed by the ClaudeAgent and GitHubCopilotAgent because their SDK-managed tool-calling loops invoke FunctionTool.invoke() directly via package-supplied handlers, skipping the standard _try_execute_function_calls approval gate. Per discussion on #5494, the fix lives in the agents (not in FunctionTool): any flag added to the tool itself can be spoofed by code with the same level of access, so the security boundary is the agent that owns the tool-calling loop. - Add on_function_approval option to ClaudeAgentOptions and GitHubCopilotOptions. Callback receives a FunctionCallContent describing the pending call and returns bool (sync or async). - Gate FunctionTool.invoke() inside each agent's existing tool-handler closure when approval_mode == "always_require". Default policy is deny; callbacks that raise also deny safely. - Deny path returns a tool-error to the model (Claude: text content; Copilot: ToolResult(result_type="failure", error="approval_denied")) so the LLM can react gracefully instead of silently failing. - Tests for both agents covering: deny by default, sync False, sync True, async True, callback-raises -> deny, no-op for never_require tools. - Samples demonstrating sync, async, and deny-by-default flows for both agents. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: preserve empty arg dicts, reject runtime approval override - _resolve_function_approval no longer collapses {} into None when building the FunctionCallContent passed to the callback (Claude + Copilot). - Claude _apply_runtime_options and Copilot _run_impl/_stream_updates now raise ValueError if on_function_approval is supplied via per-run options, instead of silently ignoring it. Approval policy must be set at agent construction time. - Drop unnecessary # type: ignore[attr-defined] on Content.name/.arguments in samples (Content is a unified class with both attributes defined). - Add regression tests for the new runtime-options validation. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * warning when non callback handler and approval needed --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.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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58ff4ad3a9 |
Python: Hyperlight: thread-confine sandbox, skip parsing on host callbacks, schema/tool cleanup (#5424)
* improved parsing of tool call results and tweaks * Address PR review: skip_parsing flag, broader registry close, comment fix - FunctionTool.invoke now takes a boolean skip_parsing flag instead of the SKIP_PARSING sentinel; the sentinel is still accepted as result_parser at construction time to opt out of parsing for every call. The two paths are equivalent. - _SandboxRegistry.close now invokes any sandbox close/shutdown hook on the entry's own worker thread (PyO3 unsendable), then shuts the worker down, then cleans up the per-entry temporary directories. - Clarified the _SandboxWorker.shutdown comment to describe the actual ThreadPoolExecutor.shutdown(wait=False, cancel_futures=False) semantics. - Hyperlight host callback uses skip_parsing=True (the new flag). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Drop redundant 'is not SKIP_PARSING' guard that mypy 1.x flags After callable(configured_parser) the sentinel is already excluded; the extra identity check tripped mypy's non-overlapping identity warning. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixed sandbox working on copy of tool --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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3e54a689fc |
Python: Add search tool content for OpenAI responses (#5302)
* Add OpenAI search tool content parsing Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix typing * simplified oai image test * same for azure * skip az responses api test --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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69894eded8 |
Python: Flatten hyperlight execute_code output (#5333)
* small fix for hyperlight * improved sandbox dependency |
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b03cb324d5 |
Python: Add Hyperlight CodeAct package and docs (#5185)
* initial work on code_mode * updated samples * updates to codeact * udpated codeact * Draft CodeAct ADR and sample updates Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * initial implementation and adr and feature * Python: Limit Hyperlight wasm backend to Python <3.14 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix CI for Hyperlight CodeAct PR Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Run Hyperlight integration when available Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Address Hyperlight review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Simplify Hyperlight file mount inputs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Accept Path host paths in Hyperlight mounts Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix Hyperlight mount typing for CI Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * temp run integration test * Python: Strengthen Hyperlight real sandbox tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * added additional tests * Python: Simplify Hyperlight CodeAct API Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * set tests as non-integration * Retry Hyperlight allowed-domain registration Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Gate Hyperlight integration tests by runtime support Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Hyperlight skip test on Python 3.14 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Delay Hyperlight runtime probe until test execution Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Relax Hyperlight Windows integration stdout assertion Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Scan Hyperlight output directory for artifacts Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Retry Hyperlight output artifact collection Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Harden Hyperlight integration output assertions Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Retry Hyperlight read-back check in integration test Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Simplify Hyperlight integration write assertion Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Avoid pathlib in Hyperlight integration sandbox Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Use socket network check in Hyperlight sandbox Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Replace blocked Azure AI Search blog link Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Clarify Hyperlight guest stdlib limits Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Use _socket in Hyperlight integration sandbox Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Handle Hyperlight mounted file paths Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Broaden Hyperlight sandbox path fallbacks Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Search Hyperlight guest mounts recursively Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Split Hyperlight mount coverage Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Split Hyperlight live network tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Hyperlight file-write test on Windows Enable the sandbox filesystem by providing a workspace_root so /output is mounted. Remove os.path.exists assertion (unsupported in WASM guest) and fix Content data assertion to use .uri. Skip the network integration test on Windows where the WASM sandbox lacks the encodings.idna codec. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: ADR intro, manual wiring sample, doc clarifications - Add CodeAct introduction section to ADR for unfamiliar readers - Clarify 'less runtime efficient' con with specific overhead description - Add note in Python impl doc clarifying ADR vs impl doc split - Explain why before_run hooks must be per-run (CRUD, concurrency, approval) - Rename code_interpreter variable to codeact in E2E sample - Add manual static wiring sample (codeact_manual_wiring.py) - Add 'when to use which pattern' guidance to samples README Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR #5185 review comments and add .NET CodeAct design doc - Fix async callback: _make_sandbox_callback returns sync wrapper with thread + asyncio.run() bridge (was broken with real Wasm FFI) - Fix stale output: clear output_dir before each sandbox.run() call - Fix blocking event loop: _run_code now async with asyncio.to_thread() - Revert _agents.py options['tools'] injection (unnecessary; provider uses context.extend_tools()) - Revert SessionContext.options docstring back to read-only - Add real-sandbox test fixtures (shared/restored/fresh) - Add 8 new real-sandbox tests for callback round-trip, stale output, event loop non-blocking, basic execution, stdout/stderr, errors, snapshot/restore, and tool registration - Add comprehensive .NET HyperlightCodeActProvider design document Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update hyperlight README with code snippets and remove Public API section Replace bare export list with Quick Start code examples covering the context provider, standalone tool, manual static wiring, and file mounts / network access patterns. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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90a633967c |
Python: Fix Gemini client support for Gemini API and Vertex AI (#5258)
* Add Gemini and Vertex AI client support Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address Gemini PR review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * removed sample run readme part --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com> |
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ff05c22c58 |
Python: add experimental file history provider (#5248)
* add experimental file history provider * Improve file history provider writes Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * typo * cleanup * cleanup * fix in readme * added security messages * Refine file history provider locking Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * added additional sample --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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2b251d904f |
Python: Fix reasoning replay when store=False (#5250)
* fix reasoning content when store=False * Remove accidental worktree entries Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * remove local session sample * removed left over files * Add attribution override regression 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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Eduard van ValkenburgandGitHub
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98e17764a4 |
Python: Fix DevUI streaming memory growth and add cross-platform regression coverage (#5221)
* fix for memory leak in devui * update async sleep * remove old func |
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f94a75daa5 |
Python: Fix response_format crash on background polling with empty text (#5146)
* Guard against empty text in _parse_structured_response_value (#5145) When using response_format with background=True (Responses API), polling an in-progress response produces empty text. _parse_structured_response_value unconditionally passed this to model_validate_json/json.loads, causing ValidationError or JSONDecodeError. Add an early return of None when text is empty, matching the existing guard for response_format=None. This allows .value to safely return None for in-progress background responses. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix `response_format` crash on background polling with empty text Fixes #5145 --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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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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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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Eduard van ValkenburgandGitHub
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2cb78ea12e | fix and unify devui samples (#5025) | ||
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Eduard van ValkenburgandGitHub
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cee0a458fe |
Python: fixed middleware samples (#5026)
* fixed samples * small update to explanation * add snippet fix on root readme |
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Eduard van ValkenburgandGitHub
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4b9856e66f |
Python: updated azure ai inference sample (#5028)
* updated azure ai inference sample * openai multimodel fix * update language |
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Eduard van ValkenburgandGitHub
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2a8c3e2dcf | fixes to azure ai search init, samples (#5021) | ||
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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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55b6e7a9f4 |
Python: Add Python feature lifecycle decorators for released APIs (#4975)
* Add Python feature lifecycle decorators Introduce reusable experimental and release-candidate decorators for released packages, migrate the Skills APIs to the new staged metadata and warning system, and add lifecycle guidance plus samples. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Python CI follow-ups Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Preserve protocol runtime checks Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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9c57680f00 |
Python: Add header_provider to Streamable HTTP MCP servers (#4849)
* Python: Add header_provider to MCPStreamableHTTPTool (#4808) Add a header_provider callback parameter to MCPStreamableHTTPTool that enables injecting dynamic per-request HTTP headers from runtime kwargs (originating from FunctionInvocationContext.kwargs set in agent middleware). The implementation uses contextvars and httpx event hooks to ensure headers are task-local and safe for concurrent tool calls: - header_provider receives the runtime kwargs dict and returns headers - call_tool sets a ContextVar before delegating to MCPTool.call_tool - An httpx request event hook reads from the ContextVar and injects headers Example usage: mcp_tool = MCPStreamableHTTPTool( name="web-api", url="https://api.example.com/mcp", header_provider=lambda kwargs: { "X-Auth-Token": kwargs.get("auth_token", ""), }, ) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4808: Python: [Bug]: Unable to pass AgentContext to MCPStreamableHTTPTool * Add test for header_provider via FunctionTool.invoke with FunctionInvocationContext Addresses PR review comment: exercises the full pipeline from FunctionInvocationContext.kwargs through FunctionTool.invoke to MCPStreamableHTTPTool.call_tool and header_provider, rather than testing call_tool in isolation. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4808: review comment fixes * Fix streamable MCP transport defaults Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Azure AI test client mocks Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix MCP runtime kwarg regressions Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize MCP tool runtime kwargs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Use context kwargs in MCP wrappers Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated mcp samples * fix link --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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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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efb14cedb1 |
Python: Support structuredContent in MCP tool results and fix sampling options type (#4763)
* Support MCP sampling tools capability (#4625) Forward systemPrompt, tools, and toolChoice from MCP sampling requests to the chat client's get_response() call. Also advertise the sampling.tools capability to MCP servers when a client is configured. - Pass SamplingCapability with tools support to ClientSession - Convert systemPrompt to instructions in options - Convert MCP Tool objects to FunctionTool instances for options - Map MCP ToolChoice.mode to tool_choice in options - Add tests for all new behaviors and update existing sampling tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix #4625: Support MCP sampling tool with proper typing and structured content - Fix mypy error by typing sampling callback options as ChatOptions[None] instead of dict[str, Any], and importing ChatOptions from _types - Handle structuredContent from CallToolResult in _parse_tool_result_from_mcp, serializing it as JSON text Content when present - Add tests for structuredContent parsing (with and without regular content) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix lint: add author to TODO comment Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4625: remove default=str, add edge-case tests - Remove default=str from json.dumps for structuredContent to fail fast on non-JSON-serializable values instead of silently converting - Add test for non-JSON-serializable structuredContent (TypeError) - Add tests for empty systemPrompt ('') and empty tools list ([]) edge cases in sampling callback - Expand TODO comment noting list[Content] return type constraint for future result_type support Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Sanitize sampling callback error to avoid leaking internals (#4625) Log exception details at DEBUG level instead of including them in the ErrorData message returned to the MCP server, which may be untrusted. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4625: move params to options, restore error info - Remove stale TODO comment about response_format (ChatOptions already has it) - Restore {ex} in sampling callback error message for useful debugging info - Set structuredContent as additional_property on Content for structured access - Move temperature, max_tokens, stop into options dict (not top-level kwargs) - Only set temperature when provided (not all models support it) - Add tests for generation params in options and temperature omission Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix MCP sampling callback and structured content error handling (#4625) - Guard max_tokens like temperature: only set when not None, so options can properly evaluate to None when all params are absent - Wrap json.dumps of structuredContent in try/except to fall back to str() for non-serializable values instead of propagating TypeError - Extract test_connect_sampling_capabilities_with_client into its own test function so pytest can discover it independently - Add test for max_tokens=None omission from options - Update structured content non-serializable test to expect fallback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address review feedback for #4625: review comment fixes * Fix MCP and Azure validation regressions Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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c012aac5f2 |
Python: [BREAKING] Reduce core dependencies and simplify optional integrations (#4904)
* improved dependencies and some fixes * fix for mypy * improve mcp |
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5e056b672e |
Python: [BREAKING] Python: Provider-leading client design & OpenAI package extraction (#4818)
* Python: Provider-leading client design & OpenAI package extraction Major refactoring of the Python Agent Framework client architecture: - Extract OpenAI clients into new `agent-framework-openai` package - Core package no longer depends on openai, azure-identity, azure-ai-projects - Rename clients for discoverability: OpenAIResponsesClient → OpenAIChatClient, OpenAIChatClient → OpenAIChatCompletionClient - Unify `model_id`/`deployment_name`/`model_deployment_name` → `model` param - New FoundryChatClient for Azure AI Foundry Responses API - New FoundryAgent/FoundryAgentClient for connecting to pre-configured Foundry agents - Remove OpenAIBase/OpenAIConfigMixin from non-deprecated client MRO - Deprecate AzureOpenAI* clients, AzureAIClient, OpenAIAssistantsClient - Reorganize samples: azure_openai+azure_ai+azure_ai_agent → azure/ - ADR-0020: Provider-Leading Client Design Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: missing Agent imports in samples, .model_id → .model in foundry_local sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: CI failures — mypy errors, coverage targets, sample imports - azure-ai mypy: add type ignores for TypedDict total=, model arg, forward ref - Coverage: replace core.azure/openai targets with openai package target - project_provider: add type annotation for opts dict Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: populate openai .pyi stub, fix broken README links, coverage targets Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixes * updated observabilitty * reset azure init.pyi * fix errors * updated adr number * fix foundry local * fixed not renamed docstrings and comments, and added deprecated markers to old classes * fix tests and pyprojects * fix test vars * updated function tests * update durable * updated test setup for functions * Fix Foundry auth in workflow samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize Python integration workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update hosting samples for Foundry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger full CI rerun Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger CI rerun again Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * trigger rerun * trigger rerun * fix for litellm * undo durabletask changes * Move Foundry APIs into foundry namespace Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Foundry pyproject formatting Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Split provider samples by Foundry surface Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Restore hosting sample requirements Also fix the Foundry Local sample link after the provider sample move. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated tests * udpated foundry integration tests * removed dist from azurefunctions tests * Use separate Foundry clients for concurrent agents Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix client setup in azfunc and durable * disabled two tests * updated setup for some function and durable tests * improved azure openai setup with new clients * ignore deprecated * fixes * skip 11 * remove openai assistants int tests --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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81e2336d47 |
Python: avoid duplicate agent response telemetry (#4685)
* Python: avoid duplicate agent response telemetry * Python: conditionally suppress duplicate agent telemetry * Simplify telemetry ownership tracking Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Aggregate token usage from inner chat spans on invoke_agent span The invoke_agent span now carries the aggregated input/output token counts from all inner chat completion spans that occur during an agent run. Previously, when inner ChatTelemetryLayer spans captured usage, the outer AgentTelemetryLayer skipped setting usage entirely to avoid duplication. Now a new INNER_ACCUMULATED_USAGE context variable tracks cumulative usage across all inner completions, and the agent span always reports the total. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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0cd40f8354 |
Python: [BREAKING] Refactor middleware layering and split Anthropic raw client (#4746)
* [BREAKING] Refactor middleware layering and raw clients Reorder chat client layers so function invocation wraps chat middleware, and chat middleware stays outside telemetry while still running for each inner model call. Add middleware pipeline caching, refresh docs and samples, and split Anthropic into raw and public clients to match the standard layering model. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Tighten typing ignores in ancillary modules Add targeted typing ignores in workflow visualization and lab modules so pyright stays clean alongside the middleware refactor work. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix categorize_middleware to unpack tuple/Sequence and use relative MRO assertions - Broaden isinstance check in categorize_middleware from list to Sequence so tuples and other Sequence types are properly unpacked instead of being appended as a single item. - Replace fragile hardcoded MRO index assertions in anthropic test with relative ordering via mro.index(). - Add regression tests for categorize_middleware with tuple, list, and None inputs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix middleware string decomposition, add middleware param to FunctionInvocationLayer, and add tests (#4710) - Guard categorize_middleware Sequence check against str/bytes to prevent character-by-character decomposition of accidentally passed strings - Add explicit middleware parameter to FunctionInvocationLayer.get_response and merge it into client_kwargs before categorization, fixing the inconsistency where only OpenAIChatClient supported this parameter - Add assertions that RawAnthropicClient does not inherit convenience layers - Add chat middleware cache test with non-empty base middleware - Add tests for single unwrapped middleware item and string input Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Apply pre-commit auto-fixes * Apply pre-commit auto-fixes * Address review feedback for #4710: review comment fixes --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Copilot <copilot@github.com> |
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4b21f38650 |
Python: Fix A2AAgent to invoke context providers before and after run (#4757)
* Fix A2AAgent to invoke context providers before and after run A2AAgent.run() bypassed the context provider lifecycle (before_run/after_run) that BaseAgent defines as a contract for all agents. This caused A2AAgent to violate the semantic definition of BaseAgent, resulting in inconsistency with other agent implementations. The fix follows the same pattern used by WorkflowAgent: - Create SessionContext and run before_run on all context providers before processing the A2A stream - Collect response updates and run after_run on all context providers after the stream is fully consumed - Auto-create a session when context providers are configured but no session is explicitly passed Fixes #4754 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Apply pre-commit auto-fixes * Remove reproduction report from repository Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback for #4754 - Validate messages when no continuation_token: raise ValueError if normalized_messages is empty, preventing IndexError on messages[-1] - Import BaseContextProvider/SessionContext from public agent_framework package instead of internal agent_framework._sessions module - Add test for ValueError on run(None) without continuation_token Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Improve test coverage for empty-messages guard in A2AAgent.run (#4754) - Parameterize test to cover both messages=None and messages=[] inputs - Add test verifying run(None, continuation_token=...) does not raise 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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bf8d9672e1 |
Python: Aggregate token usage across tool-call loop iterations in invoke_agent span (#4739)
* Fix invoke_agent span to aggregate token usage across LLM calls (#4062) The FunctionInvocationLayer._get_response() loop was overwriting the response on each iteration, so usage_details only reflected the last chat completion call. Now tracks aggregated_usage across all iterations using add_usage_details() and sets it on the returned response. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Apply pre-commit auto-fixes * Remove reproduction report artifact Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Apply pre-commit auto-fixes * Apply pre-commit auto-fixes --------- Co-authored-by: Copilot <copilot@github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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f48c4512d3 |
Python: Simplify Python Poe tasks and unify package selectors (#4722)
* updated automation tasks and commands, with alias for the time being * Restore aggregate test exclusions Preserve the legacy all-tests scope for test --all by excluding lab and devui from the default aggregate sweep, while still allowing explicit package selection. Also ignore hidden/generated test directories such as .mypy_cache during aggregate discovery. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated versions in pre-commit --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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acaf6b7054 |
Python: Fix ENABLE_SENSITIVE_DATA env var ignored when set after module import (#4743)
* Python: Re-read env vars in configure_otel_providers and enable_instrumentation (#4119) Fix ENABLE_SENSITIVE_DATA and VS_CODE_EXTENSION_PORT env vars being ignored when load_dotenv() runs after module import. The module-level OBSERVABILITY_SETTINGS singleton cached env state at import time, and configure_otel_providers() / enable_instrumentation() never re-read from os.environ when parameters were None. Both functions now construct a fresh ObservabilitySettings() to pick up current env vars when explicit parameters are not provided, matching the existing behavior of the env_file_path branch. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review feedback for #4119: avoid throwaway ObservabilitySettings - Add _read_bool_env/_read_int_env helpers to read env vars without constructing a full ObservabilitySettings (which calls create_resource()) - Replace ObservabilitySettings() in enable_instrumentation() and configure_otel_providers() else-branch with direct env reads - Add enable_console_exporters parameter to configure_otel_providers() for override parity with enable_sensitive_data and vs_code_extension_port - Propagate _resource and _executed_setup in the non-env_file_path branch - Make existing tests hermetic (clear VS_CODE_EXTENSION_PORT and ENABLE_CONSOLE_EXPORTERS env vars) - Add tests: enable_console_exporters env refresh, explicit param overrides for both enable_instrumentation() and configure_otel_providers() Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address remaining review feedback for #4119 - Refresh enable_console_exporters in enable_instrumentation() for consistency with configure_otel_providers(), so env var changes after import are picked up by both public API functions - Make test_configure_otel_providers_reads_env_vs_code_port hermetic by clearing ENABLE_CONSOLE_EXPORTERS from the environment - Add test_enable_instrumentation_reads_env_console_exporters to cover the new refresh behavior Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove unconditional enable_console_exporters overwrite from enable_instrumentation() (#4119) enable_instrumentation() is documented as not configuring exporters, so managing enable_console_exporters there was a leaky abstraction. The unconditional _read_bool_env call silently reset the value to False when ENABLE_CONSOLE_EXPORTERS was absent from env, clobbering any value previously set by configure_otel_providers(enable_console_exporters=True). - Remove the unconditional overwrite line from enable_instrumentation() - Replace test_enable_instrumentation_reads_env_console_exporters with test_enable_instrumentation_does_not_touch_console_exporters - Add regression test: enable_instrumentation() does not clobber a previously configured enable_console_exporters value - Add test: explicit enable_sensitive_data param still leaves enable_console_exporters untouched 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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705ed47a0b |
Python: Fix missing methods on the Content class in durable tasks (#4738)
* Fix Content serialization in DurableAgentStateUnknownContent (#4719) DurableAgentStateUnknownContent.from_unknown_content() stored raw Content objects without converting them to dicts, causing json.dumps to fail in Azure Durable Functions' entity state serialization. This affected content types not explicitly handled (e.g., mcp_server_tool_call/result). The fix converts Content objects to dicts via to_dict() when storing in DurableAgentStateUnknownContent, and restores them via Content.from_dict() in to_ai_content(). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add to_json and from_json methods to Content class (#4719) Add to_json() and from_json() methods to the Content class to match the serialization interface provided by SerializationMixin on other model classes. Also fix pre-existing pyright type errors in durabletask's DurableAgentStateUnknownContent.to_ai_content(). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: add type guard, remove to_json, add fallback, and tests - Remove Content.to_json() per reviewer request (comment 3) - Add type guard in Content.from_json() for non-dict JSON (comments 1, 4) - Wrap json.JSONDecodeError as ValueError for consistent exception contract - Add try/except fallback in to_ai_content() for invalid Content dicts (comment 5) - Add test_content_to_dict_exclude_none and test_content_to_dict_exclude_fields (comment 2) - Add test_unknown_content_to_ai_content_fallback_on_invalid_type_dict (comment 5) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Apply pre-commit auto-fixes * Address review feedback for #4719: review comment fixes * Remove Content.from_json, move logic to consuming code (#4719) Remove the from_json convenience method from Content class per review feedback. This is the same trivial json.loads + from_dict wrapper as to_json which was already removed. Consumers should call json.loads and Content.from_dict directly. Update tests to use Content.from_dict(json.loads(...)) pattern and remove from_json-specific error handling tests (those errors are already covered by json.loads and Content.from_dict). 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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192a283c9a |
Python: Reduce Azure chat client import overhead (#4744)
* Reduce Azure chat client import overhead Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Azure chat client type annotations and add _parse_text_from_openai tests - Move Choice and ChunkChoice imports under TYPE_CHECKING to avoid runtime import cost (from __future__ annotations is already present) - Restore proper typed signature (Choice | ChunkChoice) instead of Any - Add direct unit tests for _parse_text_from_openai covering: - Choice with message content - ChunkChoice with delta content - Refusal branch for both Choice and ChunkChoice - No content/no refusal returning None - None delta (async content filtering) returning None Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> Co-authored-by: Copilot <copilot@github.com> |
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cdb51e6a41 |
Python: fix thread serialization for multi-turn tool calls (#4684)
* Python: strip fc_id from loaded history * Move fc_id replay handling into Responses client Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Remove unnecessary pytest asyncio marker Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add Responses integration test for fc_id replay Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * removed old arg --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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0fdcfd0f4c |
Python: preserve A2A message context_id (#4686)
* Python: forward A2A context_id * Avoid duplicating A2A context ids Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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1b7940c91e |
Python: keep MCP cleanup on the owner task (#4687)
* Python: keep MCP cleanup on owner task * Avoid MCP owner task deadlocks Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix MCP owner-task timeout tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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052ba7be07 |
Python: normalize empty MCP tool output to null (#4683)
* Python: normalize empty MCP tool output to null * Python: hardcode null for empty MCP output |
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50fdcbaf57 |
Python: chore(python): improve dependency range automation (#4343)
* chore(python): improve dependency range automation - tighten dependency bounds and coding standards guidance\n- add dependency range validation workflow, reporting, and issue automation\n- update related tests and dependency pins for compatibility Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated text and pyarrow * new lock * fixed workflow * updated deps * fix tiktoken * chore(python): refine dependency validation workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs(python): add high-level dependency validation comments Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * WIP * added additional comments and excludes * added dev dependency handling and workflow and updates to package ranges * added readme and simplified commands * fix markers * chore(python): address dependency review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Tighten dependency bounds, remove stale overrides, restore Python 3.10 support - Apply dependency bound policy across all packages: stable >=1.0 deps use >=floor,<next_major; pre-1.0/prerelease deps use validated hard-bounded ranges - Remove stale root tool.uv.override-dependencies (uvicorn, websockets, grpcio) - Lower github_copilot requires-python to >=3.10 with github-copilot-sdk gated behind python_version >= 3.11 marker; import raises ImportError on 3.10 - Skip github_copilot pyright/mypy/test tasks on Python <3.11 - Use version-conditional pyrightconfig for samples on Python 3.10 - Add compatibility fix in core responses client for older openai typed dicts - Normalize uv.lock prerelease mode and refresh dev dependencies - Update CODING_STANDARD.md, DEV_SETUP.md, and package management skill docs Closes #902 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * small tweaks * add note in workflow * fix workflows and several versions * fix duplicate --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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a4b9539b62 |
[BREAKING] Python: clean up kwargs across agents, chat clients, tools, and sessions (#4581)
* Python: clean up kwargs across agents, chat clients, tools, and sessions (#3642) Audit and refactor public **kwargs usage across core agents, chat clients, tools, sessions, and provider packages per the migration strategy codified in CODING_STANDARD.md. Key changes: - Add explicit runtime buckets: function_invocation_kwargs and client_kwargs on RawAgent.run() and chat client get_response() layers. - Refactor FunctionTool to prefer explicit ctx: FunctionInvocationContext injection; legacy **kwargs tools still work via _forward_runtime_kwargs. - Refactor Agent.as_tool() to use direct JSON schema, always-streaming wrapper, approval_mode parameter, and UserInputRequiredException propagation (integrates PR #4568 behavior). - Remove implicit session bleeding into FunctionInvocationContext; tools that need a session must receive it via function_invocation_kwargs. - Lower chat-client layers after FunctionInvocationLayer accept only compatibility **kwargs (client_kwargs flattened, function_invocation_kwargs ignored). - Add layered docstring composition from Raw... implementations via _docstrings.py helper. - Clean up provider constructors to use explicit additional_properties. - Deprecation warnings on legacy direct kwargs paths. - Update samples, tests, and typing across all 23 packages. Resolves #3642 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * clarified docstring * feedback fixes * Add unit tests for _docstrings.py build/apply helpers Tests cover: no docstring source, no extra kwargs, appending to existing Keyword Args section, inserting after Args, inserting in plain docstrings, multiline descriptions, ordering, and apply_layered_docstring. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add test for propagate_session TypeError on non-AgentSession values Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add tests for multi-content and empty UserInputRequiredException propagation Cover the branching logic in _try_execute_function_calls for: - Multiple user_input_request items in a single exception (extra_user_input_contents path) - Empty contents list (fallback function_result path) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add tests for DurableAIAgent.get_session forwarding service_session_id Verifies get_session correctly forwards service_session_id and session_id to the executor's get_new_session, replacing the removed kwargs test. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Simplify ag-ui test stub to read session from client_kwargs only Remove dual-mode detection (client_kwargs vs raw kwargs fallback) from the test mock. Session is now read exclusively from client_kwargs, matching the settled public calling convention. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated create and get sessions in durable * fixed docstrings * fix test * updated session handling * updated from main * updated tests --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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b7990908fe | fix duplicate names between supplied tools and mcp servers (#4649) | ||
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3e03a305f6 |
Python: Implement annotation-based context compaction (#4469)
* Implement annotation-based context compaction Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Handle missing compaction attributes in BaseChatClient Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix CI typing and bandit issues Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Optimize incremental compaction annotation pass Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refinement * Python: add ToolResultCompactionStrategy and CompactionProvider Add ToolResultCompactionStrategy that collapses older tool-call groups into short summary messages (e.g. [Tool calls: get_weather]) while keeping the most recent groups verbatim. This mirrors the .NET ToolResultCompactionStrategy from PR #4533. Add CompactionProvider as a context-provider that auto-applies compaction before each agent turn and stores compacted history in session state after each turn. Includes tests and samples for both features. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refinement and alignment with dotnet PR * updated tool result compaction * updated tool result compaction * Python: add ToolResultCompactionStrategy, CompactionProvider, and skip_excluded - ToolResultCompactionStrategy collapses older tool-call groups into [Tool results: func_name: result] summaries with bidirectional tracing (same pattern as SummarizationStrategy). - CompactionProvider as BaseContextProvider with separate before_strategy and after_strategy parameters. before_strategy compacts loaded context; after_strategy compacts stored history via history_source_id. - InMemoryHistoryProvider gains skip_excluded flag to filter out messages marked as excluded by compaction strategies. - Tests, samples, and exports updated. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixed checks * fix mypy * Fix: ensure summary messages from both strategies get full compaction annotations SummarizationStrategy was not calling annotate_message_groups after inserting its summary message, so the summary lacked core group annotations (id, kind, index, has_reasoning, _excluded). Added the missing call. ToolResultCompactionStrategy already had it. Added tests verifying both strategies produce fully annotated summaries. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated propagation * fix mypy --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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23d6d91c8f |
Python: [Breaking] Upgrade to azure-ai-projects 2.0+ (#4536)
* Prepare azure-ai-projects 2.0 GA compatibility Add allow_preview support for internal AIProjectClient creation, keep backward compatibility for renamed SDK model classes, and align Azure AI/core paths and tests for GA validation workflows. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * upgrade to ai-project==2.0.0 * Python: remove azure-ai-projects keyword-guard paths Assume azure-ai-projects 2.0+ in Azure AI client/provider/responses code paths by removing _supports_keyword_argument gating and related fallback branching. Also fix pyright typing in FoundryMemoryProvider memory store calls by using ResponseInputItemParam-typed items. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * check fixes * Python: remove unsupported foundry_features option Drop foundry_features from Azure AI client and provider surfaces because azure-ai-projects 2.0.0 does not expose that create_version parameter. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: add allow_preview to Foundry memory provider Propagate allow_preview when FoundryMemoryProvider constructs an AIProjectClient and update tests accordingly. Also finish wiring allow_preview through AzureAIClient-facing surfaces and related docs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * aligning docstrings * udpated lock --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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55ddd841b7 |
Python: Fix Python pyright package scoping and typing remediation (#4426)
* Fix Python pyright package scoping and typing remediation Implements issue #4407 by removing the root pyright include, adding package-level pyright includes, and resolving pyright/mypy typing issues across Python packages. Also cleans unnecessary casts and applies line-level, rule-specific ignores where external libraries are too dynamic. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Reduce pyright cost in handoff cloning Simplify cloned_options construction in HandoffAgentExecutor to avoid expensive TypedDict narrowing/inference in _handoff.py, which was causing pyright to spend a long time in orchestrations. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix types * Fix lint and type-check regressions Resolve current Python package check failures across lint, pyright, and mypy after recent code changes, including purview/declarative pyright issues and multiple ruff simplification findings. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixed hooks * Stabilize package tests and test tasks Resolve cross-package non-integration test failures, simplify streaming type flow, harden locale/culture handling, and standardize package test poe tasks to exclude integration tests where applicable. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * lots of small fixes * Fix current Python test regressions Address current failing unit tests in azure-ai, bedrock, and azure-cosmos while keeping Bedrock parsing logic inline (no new static helper methods). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * small fixes * small fixes * removed pydantic from json * final updates * fix core * fix tests * fix obser --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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2a20750110 |
ADR: Python context compaction strategy (#3802)
* Add ADR for Python context compaction strategy * Remove async vs sync open question - compact() is async * updated adr * docs: refine context compaction ADR Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated adr * further refinement * renamed and numbered * remove XX version --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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c37f74f898 |
Python: Add Azure Cosmos history provider package (#4271)
* Created cosmos history provider * add marker * Python: address Cosmos PR feedback - address provider/test/sample review feedback and cleanup typing - add cosmos integration test coverage and skip gating - add dedicated cosmos emulator jobs to python merge/integration workflows - switch cosmos workflow execution to package poe integration-tests task Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: handle empty Cosmos session id - replace default partition fallback for empty session_id - log warning and generate GUID when session_id is empty - update unit tests to validate GUID fallback behavior Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix sample * fix cross partition query --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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6138487888 |
Python: Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference (#4207)
* Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference Add embedding client implementations to existing provider packages: - OllamaEmbeddingClient: Text embeddings via Ollama's embed API - BedrockEmbeddingClient: Text embeddings via Amazon Titan on Bedrock - AzureAIInferenceEmbeddingClient: Text and image embeddings via Azure AI Inference, supporting Content | str input with separate model IDs for text (AZURE_AI_INFERENCE_EMBEDDING_MODEL_ID) and image (AZURE_AI_INFERENCE_IMAGE_EMBEDDING_MODEL_ID) endpoints Additional changes: - Rename EmbeddingCoT -> EmbeddingT, EmbeddingOptionsCoT -> EmbeddingOptionsT - Add otel_provider_name passthrough to all embedding clients - Register integration pytest marker in all packages - Add lazy-loading namespace exports for Ollama and Bedrock embeddings - Add image embedding sample using Cohere-embed-v3-english - Add azure-ai-inference dependency to azure-ai package Part of #1188 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix mypy duplicate name and ruff lint issues - Rename second 'vector' variable to 'img_vector' in image embedding loop - Combine nested with statements in tests - Remove unused result assignments in tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updates from feedback * Fix CI failures in embedding usage handling - Fix Azure AI embedding mypy issues by normalizing vectors to list[float], safely accumulating optional usage token fields, and filtering None entries before constructing GeneratedEmbeddings - Avoid Bandit false positive by initializing usage details as an empty dict - Update OpenAI embedding tests to assert canonical usage keys (input_token_count/total_token_count) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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4530504a3d |
Python: Azure AI Search provider improvements - EmbeddingGenerator, async context manager, KB message handling (#4212)
* small updates and improvements in the azure AISearch provider * Fix mypy errors and embedding function test - Use separate variable for embeddings result to avoid mypy type reassignment error - Fix test_vectorized_query_with_embedding_function: use real async function instead of AsyncMock which falsely matches SupportsGetEmbeddings protocol Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixes from feedback --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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acc49196c1 |
Python: updated integration tests and guidance (#4181)
* updated integration tests and guidance * fixed merge test * updated integration tests * fix: remove duplicate --dist loadfile flag from pytest-xdist config Only one --dist mode can be active at a time; the second value silently overrides the first. Keep --dist worksteal (dynamic load balancing) and remove the redundant --dist loadfile from all workflow files and pyproject.toml configs. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: add keep-in-sync notes for merge and integration test workflows Both python-merge-tests.yml and python-integration-tests.yml share the same parallel job structure. Added sync reminders in workflow file comments, the python-testing SKILL.md, and CODING_STANDARD.md. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * refactor: remove RUN_INTEGRATION_TESTS flag Integration test gating now uses two mechanisms: - `@pytest.mark.integration` for test selection via `-m` filtering - `skip_if_*_disabled` for credential/service availability checks The RUN_INTEGRATION_TESTS env var was redundant since the marker handles selection and the skip decorators already check for actual credentials. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: sync missing env vars from merge-tests to integration-tests Add OPENAI_EMBEDDINGS_MODEL_ID and AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME to python-integration-tests.yml to match python-merge-tests.yml. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: remove remaining RUN_INTEGRATION_TESTS from embedding tests and docs Missed test_openai_embedding_client.py and vector-stores README in the earlier cleanup. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * set functions tests to 3.10 --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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6305e3e092 |
Python: feat(python): Add embedding abstractions and OpenAI implementation (Phase 1) (#4153)
* feat(python): Add embedding abstractions and OpenAI implementation (Phase 1) This PR contains two parts: 1. **Overall migration plan** for porting vector stores and embeddings from Semantic Kernel to Agent Framework (docs/features/vector-stores-and-embeddings/README.md) covering all 10 phases from core abstractions through connectors and TextSearch. 2. **Phase 1 implementation** — core embedding abstractions and OpenAI/Azure OpenAI embedding clients: Core types (_types.py): - EmbeddingGenerationOptions TypedDict (total=False) - Embedding[EmbeddingT] generic class with model_id, dimensions, created_at - GeneratedEmbeddings[EmbeddingT, EmbeddingOptionsT] list container with options, usage - EmbeddingInputT (default str) and EmbeddingT (default list[float]) TypeVars Protocol + base class (_clients.py): - SupportsGetEmbeddings protocol — Generic[EmbeddingInputT, EmbeddingT, OptionsContraT] - BaseEmbeddingClient ABC — Generic[EmbeddingInputT, EmbeddingT, OptionsCoT] Telemetry (observability.py): - EmbeddingTelemetryLayer with gen_ai.operation.name = "embeddings" OpenAI implementation (openai/_embedding_client.py): - RawOpenAIEmbeddingClient, OpenAIEmbeddingClient, OpenAIEmbeddingOptions - Uses _ensure_client() factory pattern Azure OpenAI implementation (azure/_embedding_client.py): - AzureOpenAIEmbeddingClient following AzureOpenAIChatClient pattern - Supports API key, Entra ID credentials, env var configuration Tests: - 47 unit tests for types, protocol, base class, OpenAI, and Azure clients - 6 integration tests (gated behind RUN_INTEGRATION_TESTS + credentials) Samples: - samples/02-agents/embeddings/openai_embeddings.py - samples/02-agents/embeddings/azure_openai_embeddings.py Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Add AzureOpenAIEmbeddingClient to azure __init__.pyi stub Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * ci: Add embedding env vars to Python integration tests Map OPENAI_EMBEDDING_MODEL_ID and AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME from GitHub vars to the integration test environment. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Handle base64 encoding_format in OpenAI embedding client When encoding_format='base64' is used, the OpenAI API returns base64-encoded floats instead of a JSON array. Decode these automatically to list[float] so the return type stays consistent regardless of encoding format. Also adds a unit test for base64 decoding and fixes minor docstring/import issues. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Only record INPUT_TOKENS for embedding telemetry Embeddings have no output/completion tokens. Remove OUTPUT_TOKENS recording which was double-counting prompt_tokens via the total_tokens fallback. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Resolve mypy variance error and lint warning Use contravariant/covariant TypeVars for SupportsGetEmbeddings Protocol. Combine nested if into single statement in telemetry layer. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Make EmbeddingCoT invariant for mypy compatibility GeneratedEmbeddings is invariant in its type param, so the Protocol TypeVar cannot be covariant. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Address PR review - empty values guard, service_url for telemetry - Add early return for empty values in get_embeddings to avoid unnecessary API calls - Add service_url() method to RawOpenAIEmbeddingClient for proper telemetry endpoint reporting - Add test for empty values behavior Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix OpenAI chat client compatibility with third-party endpoints and OTel 0.4.14 (#4161) * Fix system message content sent as list instead of string Some OpenAI-compatible endpoints (e.g. NVIDIA NIM) reject system messages when content is a list of content parts. This change flattens system and developer message content to a plain string in the Chat Completions client. Fixes https://github.com/microsoft/agent-framework/issues/1407 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix compatibility with opentelemetry-semantic-conventions-ai 0.4.14 Version 0.4.14 removed several LLM_* attributes from SpanAttributes (LLM_SYSTEM, LLM_REQUEST_MODEL, LLM_RESPONSE_MODEL, LLM_REQUEST_MAX_TOKENS, LLM_REQUEST_TEMPERATURE, LLM_REQUEST_TOP_P, LLM_TOKEN_TYPE). Move these to the OtelAttr enum with their well-known gen_ai.* string values and update all references in observability.py and tests. Fixes https://github.com/microsoft/agent-framework/issues/4160 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Flatten text-only message content to string for all roles Extend the system/developer fix to all message roles. Text-only content lists are now post-processed into plain strings, while multimodal content (text + images/audio) remains as a list. This fixes compatibility with OpenAI-like endpoints that cannot deserialize list content (e.g. Foundry Local's Neutron backend). Partially fixes https://github.com/microsoft/agent-framework/issues/4084 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix streaming text lost when usage data in same chunk Some providers (e.g. Gemini) include both usage data and text content in the same streaming chunk. The early return on chunk.usage caused text and tool call parsing to be skipped entirely. Remove the early return and process usage alongside text/tool calls. Fixes https://github.com/microsoft/agent-framework/issues/3434 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix mypy errors in _chat_client.py Rename shadowed variable 'args' in system/developer branch to 'sys_args' and rename loop variable 'content' to 'msg_content' to avoid type conflict. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * reorder imports * fix: Use OtelAttr.REQUEST_MODEL instead of removed SpanAttributes.LLM_REQUEST_MODEL Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: Add score_threshold to vector store plan Reference SK .NET PR #13501 for score threshold filtering semantics. Include score_threshold in SearchOptions from Phase 3. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * docs: Add reference to roji's SK .NET MEVD work for SQL connectors Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: Clear env vars in construction tests to avoid CI leakage Tests for missing API key / model ID now use monkeypatch.delenv to ensure env vars from the integration test environment don't prevent the expected ValueError from being raised. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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55398e21df |
Python: Add max_function_calls to FunctionInvocationConfiguration (#2329) (#4175)
* Add max_function_calls to FunctionInvocationConfiguration (#2329) Add a new per-request max_function_calls setting to FunctionInvocationConfiguration that limits the total number of individual function invocations across all iterations within a single get_response call. This complements max_iterations (which limits LLM roundtrips) by providing a hard cap on actual tool executions regardless of parallelism. - Add max_function_calls field to FunctionInvocationConfiguration (default: None/unlimited) - Track cumulative function call count in both streaming and non-streaming tool loops - Force tool_choice='none' when the limit is reached - Add validation in normalize_function_invocation_configuration - Improve docstrings for FunctionInvocationConfiguration, FunctionTool, and @tool to clarify semantics of max_iterations vs max_function_calls vs max_invocations - Add tests for parallel calls, single calls, unlimited mode, and config validation Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add sample for controlling total tool executions Showcases all three mechanisms for limiting tool executions: 1. max_iterations — caps LLM roundtrips 2. max_function_calls — caps total individual function invocations per request 3. max_invocations — lifetime cap on a specific tool instance Plus a combined scenario demonstrating defense in depth. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Suppress ruff E305/fmt in hosting sample to preserve XML doc tags The XML snippet tags (# <create_agent> / # </create_agent>) are used for docs extraction and must stay adjacent to the code they wrap. Both ruff check (E305) and ruff format add blank lines after the function definition, pushing the closing tag away. Suppress with ruff: noqa: E305 and fmt: off. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add per-agent tool wrapping scenario to control_total_tool_executions sample Show that wrapping the same callable with @tool multiple times creates independent FunctionTool instances with separate invocation counters, enabling per-agent max_invocations budgets for shared functions. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Clarify max_function_calls is a best-effort limit The limit is checked after each batch of parallel calls completes, so the current batch always runs to completion even if it overshoots the limit. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address PR review: fix docstring reference, clarify best-effort in sample - Fix malformed Sphinx :attr: role in FunctionTool docstring — use plain backtick reference instead - Update sample to say 'best-effort cap' instead of 'hard cap' for max_function_calls, noting it's checked between iterations - Parametrize pattern is correct (fixture override, matching existing tests) Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * clarify max_invocations limits --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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b1c7c7c844 |
Python: Fix OpenAI chat client compatibility with third-party endpoints and OTel 0.4.14 (#4161)
* Fix system message content sent as list instead of string Some OpenAI-compatible endpoints (e.g. NVIDIA NIM) reject system messages when content is a list of content parts. This change flattens system and developer message content to a plain string in the Chat Completions client. Fixes https://github.com/microsoft/agent-framework/issues/1407 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix compatibility with opentelemetry-semantic-conventions-ai 0.4.14 Version 0.4.14 removed several LLM_* attributes from SpanAttributes (LLM_SYSTEM, LLM_REQUEST_MODEL, LLM_RESPONSE_MODEL, LLM_REQUEST_MAX_TOKENS, LLM_REQUEST_TEMPERATURE, LLM_REQUEST_TOP_P, LLM_TOKEN_TYPE). Move these to the OtelAttr enum with their well-known gen_ai.* string values and update all references in observability.py and tests. Fixes https://github.com/microsoft/agent-framework/issues/4160 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Flatten text-only message content to string for all roles Extend the system/developer fix to all message roles. Text-only content lists are now post-processed into plain strings, while multimodal content (text + images/audio) remains as a list. This fixes compatibility with OpenAI-like endpoints that cannot deserialize list content (e.g. Foundry Local's Neutron backend). Partially fixes https://github.com/microsoft/agent-framework/issues/4084 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix streaming text lost when usage data in same chunk Some providers (e.g. Gemini) include both usage data and text content in the same streaming chunk. The early return on chunk.usage caused text and tool call parsing to be skipped entirely. Remove the early return and process usage alongside text/tool calls. Fixes https://github.com/microsoft/agent-framework/issues/3434 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix mypy errors in _chat_client.py Rename shadowed variable 'args' in system/developer branch to 'sys_args' and rename loop variable 'content' to 'msg_content' to avoid type conflict. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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67ce1baecf |
Python: fix reasoning model workflow handoff and history serialization (#4083)
* fix: strip function_call and text_reasoning from cross-agent workflow handoff When a reasoning model (e.g. gpt-5-mini) runs as Agent 1 in a workflow, its response includes text_reasoning items (with server-scoped IDs like rs_XXXX) and function_call items. Forwarding these to Agent 2 in a fresh conversation caused API errors because the reasoning/call IDs are scoped to the original stored response context. Changes: - Strip 'function_call', 'text_reasoning', 'function_approval_request', and 'function_approval_response' from handoff messages in _agent_executor.py - Keep 'function_result' so the actual tool output content is preserved for the next agent's context - Update unit tests to reflect that function_result messages survive handoff (messages grow from 2→3: user, tool(result), assistant(summary)) - Fix incorrect test assertions in test_function_invocation_stop_clears_* that assumed the client layer updates session.service_session_id - Also fixed _extract_function_calls to search all messages with call_id deduplication, and the error-limit stop path to submit function_call_output items before halting (via tool_choice=none cleanup call) Relates to: https://github.com/microsoft/agent-framework/issues/4047 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: reasoning model workflow handoff and history serialization Fixes multiple related issues when using reasoning models (gpt-5-mini, gpt-5.2) in multi-agent workflows that chain agents via from_response or replay full conversation history via AgentExecutorRequest. ## Reasoning items always emitted on output_item.added When a reasoning model produces encrypted or hidden reasoning (no visible text), the Responses API still fires a reasoning output item without any reasoning_text.delta events. Previously no text_reasoning Content was emitted in that case, making it invisible to downstream logic. Both the non-streaming (_parse_response_from_openai) and streaming (output_item.added) paths now always emit at least one text_reasoning Content — with empty text if no content is available — so co-occurrence detection and serialization guards work reliably. ## Reasoning items only serialized when paired with a function_call The Responses API only accepts reasoning items in input when they directly preceded a function_call in the original response. Sending a reasoning item that preceded a text response (no tool call) causes: "reasoning was provided without its required following item" _prepare_message_for_openai now checks has_function_call per message and skips text_reasoning serialization when there is no accompanying function_call. ## summary field is an array, not an object The reasoning item summary field sent to the Responses API must be an array of objects ([{"type": "summary_text", "text": ...}]), not a single object. Fixed _prepare_content_for_openai accordingly. ## service_session_id cleared when explicit history is provided When a workflow coordinator replays a full conversation (including function calls from a previous agent run) back to an executor via AgentExecutorRequest or from_response, the executor's session still held a service_session_id (previous_response_id) from the prior run. The API then received the same function-call items twice — once from previous_response_id (server-stored) and once from the explicit input — causing: "Duplicate item found with id fc_...". AgentExecutor.run (when should_respond=True) and from_response now reset self._session.service_session_id = None before running so that explicit input is the sole source of conversation context. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * small improvements in text reasoning * refactor: add reset_service_session to AgentExecutorRequest for explicit history replay Replace the implicit 'always clear service_session_id when should_respond=True' with an explicit opt-in field on AgentExecutorRequest. The old approach used should_respond=True as a proxy for 'full history replay', but that conflates two distinct intents: - Orchestrations group chat sends should_respond=True with an empty/single-message list (not a full replay) — unnecessarily clearing service_session_id. - HITL / feedback coordinators send the full prior conversation and truly need a fresh service session ID to avoid duplicate-item API errors. Changes: - Add AgentExecutorRequest.reset_service_session: bool = False - AgentExecutor.run only clears service_session_id when this flag is True - AgentExecutor.from_response unchanged (always clears; always full conversation) - Set reset_service_session=True in all full-history-replay call sites: agents_with_HITL.py, azure_chat_agents_tool_calls_with_feedback.py, autogen-migration round-robin coordinator, tau2 runner - Update _FullHistoryReplayCoordinator test helper to pass the flag Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * comment update * fixes from feedback * fix test * reverted changes to agent executor * fix: remove reset_service_session from tau2 runner Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * two other reverts * fix sample --------- Co-authored-by: Giles Odigwe <79032838+giles17@users.noreply.github.com> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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5ee06853a1 |
Python: [BREAKING] Redesign Python exception hierarchy (#4082)
* [BREAKING] Redesign Python exception hierarchy Replace the flat ServiceException family with domain-scoped branches: - AgentException (with InvalidAuth, InvalidRequest, InvalidResponse, ContentFilter) - ChatClientException (same consistent suberrors) - IntegrationException (same + InitializationError) - WorkflowException (Runner, Convergence, Checkpoint, Validation, Action, Declarative) - ContentError (AdditionItemMismatch) - ToolException / ToolExecutionException (unchanged) - MiddlewareException / MiddlewareTermination (unchanged) Key changes: - All Service* exceptions removed (ServiceException, ServiceInitializationError, etc.) - AgentExecutionException split into AgentInvalidRequest/ResponseException - AgentInvocationError removed, split into AgentInvalidRequest/ResponseException - Workflow exceptions moved from _workflows/_exceptions.py into main exceptions.py - _workflows/__init__.py emptied; main __init__.py imports directly from submodules - Purview exceptions re-parented under IntegrationException hierarchy - Init validation errors use built-in ValueError/TypeError instead of custom exceptions - CODING_STANDARD.md updated with hierarchy design and rationale Fixes microsoft/agent-framework#3410 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Clarify ToolException vs ToolExecutionException docstrings ToolException: base class for all tool-related exceptions (preconditions, connection/init failures). ToolExecutionException: runtime call failures (tool call failed, reconnect failed, MCP errors). Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix remaining stale imports from agent_framework._workflows - azurefunctions: _context.py, _app.py, _serialization.py, test_func_utils.py used 'from agent_framework._workflows import X' which broke after emptying _workflows/__init__.py; changed to direct submodule imports - azure-ai-search: test still referenced ServiceInitializationError; updated to ValueError to match production code Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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fd4e6e816c |
Unify Azure credential handling across all Python packages (#4088)
Replace ad_token, ad_token_provider, and get_entra_auth_token with a unified credential parameter across all Azure-related packages. Core changes: - Add AzureCredentialTypes (TokenCredential | AsyncTokenCredential) and AzureTokenProvider (Callable[[], str | Awaitable[str]]) type aliases - Add resolve_credential_to_token_provider() using azure.identity's get_bearer_token_provider for automatic token caching/refresh - Update AzureOpenAIChatClient, AzureOpenAIResponsesClient, and AzureOpenAIAssistantsClient to accept credential: AzureCredentialTypes | AzureTokenProvider - Remove ad_token, ad_token_provider params and get_entra_auth_token helpers Package updates: - azure-ai: Accept AzureCredentialTypes on AzureAIClient, AzureAIAgentClient, AzureAIProjectAgentProvider, AzureAIAgentsProvider - azure-ai-search: Accept AzureCredentialTypes on AzureAISearchContextProvider - purview: Accept AzureCredentialTypes | AzureTokenProvider on PurviewClient, PurviewPolicyMiddleware, PurviewChatPolicyMiddleware Fixes #3449 Fixes #3500 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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f93ceae43a |
Simplify memory sample to use session state (#4085)
- Rename UserNameProvider → UserMemoryProvider - Use session state (state dict) instead of instance variables - Use context.extend_instructions() instead of context.instructions.append() - Use DEFAULT_SOURCE_ID class attribute - Fix imports to use public agent_framework API - Add session state inspection at end of sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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aab80d9ed9 |
Python: Fix Eval samples (#4033)
* fix red team sample * Updated self-reflection * fix for workflow eval sample * fix test |
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534e5f5bf7 |
Python: improve .env handling and observability samples (#4032)
* Python: improve .env precedence and observability samples - Switch load_settings to explicit precedence: overrides -> explicit .env -> environment -> defaults\n- Raise when env_file_path is provided but missing\n- Update settings docs and tests for new behavior\n- Refresh observability samples and README guidance for env loading options\n\nCloses #3864\n\nCo-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixed some imports * Fix load_settings CI regressions Allow explicit env_file_path values that exist but are not regular files (for example /dev/null) by checking path existence before dotenv parsing, and restore a dict accumulator with typed return cast to satisfy mypy. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Avoid implicit dotenv in observability Only load dotenv in observability helpers when env_file_path is explicitly provided, and remove test os.devnull workarounds that are no longer necessary. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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794f84c190 |
Python: Fix Anthropic option conflicts and manager parse retries (#4000)
* Python: Fix Anthropic kwargs and manager parse retries - Strip unsupported Anthropic kwargs from prepared run options while preserving provider-specific mappings. - Keep stream mode explicit at Anthropic SDK call sites and prevent duplicate stream kwarg conflicts. - Add bounded default retries with strict retry prompt for agent-based group chat manager parse failures. - Add regression tests in anthropic and orchestrations packages covering #3371, #3827, and #3078. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Fix Anthropic test lint import Add missing Any import in anthropic test module to fix ruff F821 failures in Package Checks. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Python: Revert group chat changes from PR 4000 Revert orchestrations changes so this PR only contains Anthropic client fixes. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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  Eduard van ValkenburgGitHubeavanvalkenburgCopilotcopilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> |
cc98d5b6f7 |
Python: [BREAKING] Scope provider state by source_id and standardize source IDs (#3995)
* Initial plan * Add FoundryMemoryProvider and tests Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * Add sample and documentation for FoundryMemoryProvider Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * Address code review feedback for FoundryMemoryProvider Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * Address PR review comments: Add DEFAULT_SOURCE_ID, use logging.getLogger, move state to session.state Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com> * Fix Foundry memory ItemParam usage and exports Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Refactor provider hook state and standardize source IDs Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Support endpoint-based Foundry memory init Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix core README workflows link Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated implementation and sample * Split out Foundry memory provider changes Remove FoundryMemoryProvider implementation/tests/sample plus export and docs mentions from this branch so only non-Foundry changes remain. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger CI rerun for PR #3995 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> Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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aab621f5eb |
Python: Fix tool normalization and provider sample consolidation (#3953)
* Fix tool normalization and provider samples - restore callable/single-tool normalization paths and unset tool-choice behavior\n- consolidate and expand chat/provider samples (OpenAI/Azure/Anthropic/Ollama/Bedrock)\n- migrate Bedrock lazy import surface to agent_framework.amazon and move provider samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * small fix in sample * Finalize provider, samples, and core cleanup Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix CopilotTool passthrough in agent Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix link --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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dc9439a75a |
Python: [BREAKING] Fix #3613 chat/agent message typing alignment (#3920)
* Fix #3613 message typing across chat and agents * Address #3613 review feedback and sample input style * refactor: use shared AgentRunMessages aliases (#3613) * refactor: rename agent run input aliases for #3613 * samples: inline image content in run calls * core: export AgentRunInputs from package init * core: use explicit init re-exports without __all__ * updated logging and inits * Fix core mypy export and samples XML note * Remove AgentRunInputsOrNone and dedupe loggers * Remove prepare_messages helper * fix integration tests |
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b68d0f93e3 |
Python: Warn on unsupported AzureAIClient runtime tool/structured_output overrides (#3919)
* Guard AzureAIClient runtime tool and structured output overrides * Simplify AzureAI runtime option pruning logic * small fix * slight update * fix error message in test * fix test var * Move Azure AI runtime override checks Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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fc9c81b0b1 |
Python: [BREAKING] Remove FunctionTool[Any] compatibility shim for schema passthrough (#3600) (#3907)
* Fix #3600: Pass JSON schemas through without Pydantic conversion This change optimizes FunctionTool and MCP flows by passing JSON schemas directly to providers without converting them to Pydantic models first. Key changes: - Store JSON schema as-is when supplied to FunctionTool - Skip Pydantic model_validate for schema-supplied tools in invoke() - Return MCP tool schemas directly without conversion - Add comprehensive tests for schema passthrough behavior Performance benefits: - Eliminates expensive Pydantic model creation for supplied schemas - Preserves exact schema structure (additionalProperties, custom fields, etc.) - Reduces memory overhead and initialization time Maintains backward compatibility: - Function signature inference still uses Pydantic models - Explicit Pydantic models passed as input_model work as before - All existing tests pass * Fix schema passthrough validation and remove helper * Simplify FunctionTool without generic model dependency * Fix FunctionTool typing fallout in 3600 * Remove FunctionTool[Any] compatibility shim * Use serializable kwargs in OTEL tool args |
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Eduard van ValkenburgandGitHub
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e563849be3 | Align Python hosting get-started sample with Azure Functions (#3922) | ||
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Eduard van ValkenburgandGitHub
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4452997e8d |
Python: Replace wildcard imports with explicit imports (#3908)
* Python: Replace wildcard imports with explicit imports - Replace all 'from ... import *' with explicit symbol imports - Add __all__ declarations to namespace packages for re-exports - Update CODING_STANDARD.md to prohibit wildcard imports - Maintain exported API and preserve all functionality fixes #3605 * Refine wildcard guidance example text * Simplify explicit exports without self-aliases |
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Eduard van ValkenburgandGitHub
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a39fd69f76 | Add memory run snippet tag for docs extraction (#3921) | ||
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Eduard van ValkenburgandGitHub
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f3ea872156 | Add default in-memory history provider for workflow agents (#3918) | ||
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Eduard van ValkenburgandGitHub
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e9b3a5bbc7 |
Python: fix: prevent repeating instructions in continued Responses API conversations (#3909)
* fix: prevent repeating instructions in continued Responses API conversations - Instructions are now only prepended to messages on the first turn - When conversation_id/response_id exists (continuation), instructions are skipped - Covers OpenAI and Azure Responses API paths - Adds regression tests for all continuation scenarios Fixes #3498 * Apply lint fixes to continuation tests * Consolidate responses continuation tests |
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Eduard van ValkenburgandGitHub
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1e350ea22f |
Python: [BREAKING] PR2 — Wire context provider pipeline, remove old types, update all consumers (#3850)
* PR2: Wire context provider pipeline and update all internal consumers - Replace AgentThread with AgentSession across all packages - Replace ContextProvider with BaseContextProvider across all packages - Replace context_provider param with context_providers (Sequence) - Replace thread= with session= in run() signatures - Replace get_new_thread() with create_session() - Add get_session(service_session_id) to agent interface - DurableAgentThread -> DurableAgentSession - Remove _notify_thread_of_new_messages from WorkflowAgent - Wire before_run/after_run context provider pipeline in RawAgent - Auto-inject InMemoryHistoryProvider when no providers configured * fix: update all tests for context provider pipeline, fix lazy-loaders, remove old test files * refactor: update all sample files for context provider pipeline (AgentThread→AgentSession, ContextProvider→BaseContextProvider) * fix: update remaining ag-ui references (client docstring, getting_started sample) * fix: make get_session service_session_id keyword-only to avoid confusion with session_id * refactor: rename _RunContext.thread_messages to session_messages * refactor: remove _threads.py, _memory.py, and old provider files; migrate devui to use plain message lists * rename: remove _new_ prefix from test files * refactor: rewrite SlidingWindowChatMessageStore as SlidingWindowHistoryProvider(InMemoryHistoryProvider) * fix: read full history from session state directly instead of reaching into provider internals * fix: update stale .pyi stubs, sample imports, and README references for new provider types * fix: remove stale message_store, _notify_thread_of_new_messages, and session_id.key references in samples * refactor: merge context_providers and sessions sample folders into sessions, remove aggregate_context_provider * refactor: UserInfoMemory stores state in session.state instead of instance attributes * feat: add Pydantic BaseModel support to session state serialization Pydantic models stored in session.state are now automatically serialized via model_dump() and restored via model_validate() during to_dict()/from_dict() round-trips. Models are auto-registered on first serialization; use register_state_type() for cold-start deserialization. Also export register_state_type as a public API. * fix mem0 * Update sample README links and descriptions for session terminology - Replace 'thread' with 'session' in sample descriptions across all READMEs - Update file links for renamed samples (mem0_sessions, redis_sessions, etc.) - Fix Threads section → Sessions section in main samples/README.md - Update tools, middleware, workflows, durabletask, azure_functions READMEs - Update architecture diagrams in concepts/tools/README.md - Update migration guides (autogen, semantic-kernel) * Fix broken Redis README link to renamed sample * Fix Mem0 OSS client search: pass scoping params as direct kwargs AsyncMemory (OSS) expects user_id/agent_id/run_id as direct kwargs, while AsyncMemoryClient (Platform) expects them in a filters dict. Adds tests for both client types. Port of fix from #3844 to new Mem0ContextProvider. * Fix rebase issues: restore missing _conversation_state.py and checkpoint decode logic - Add back _conversation_state.py (encode/decode_chat_messages) lost in rebase - Fix on_checkpoint_restore to decode cache/conversation with decode_chat_messages - Fix on_checkpoint_restore to use decode_checkpoint_value for pending requests - Add tests/workflow/__init__.py for relative import support - Fix test_agent_executor checkpoint selection (checkpoints[1] not superstep) * Add STORES_BY_DEFAULT ClassVar to skip redundant InMemoryHistoryProvider injection Chat clients that store history server-side by default (OpenAI Responses API, Azure AI Agent) now declare STORES_BY_DEFAULT = True. The agent checks this during auto-injection and skips InMemoryHistoryProvider unless the user explicitly sets store=False. * Fix broken markdown links in azure_ai and redis READMEs * Fix getting-started samples to use session API instead of removed thread/ContextProvider API * updates to workflow as agent * fix group chat import * Rename Thread→Session throughout, fix service_session_id propagation, remove stale AGUIThread - Fix: Propagate conversation_id from ChatResponse back to session.service_session_id in both streaming and non-streaming paths in _agents.py - Rename AgentThreadException → AgentSessionException - Remove stale AGUIThread from ag_ui lazy-loader - Rename use_service_thread → use_service_session in ag-ui package - Rename test functions from *_thread_* to *_session_* - Rename sample files from *_thread* to *_session* - Update docstrings and comments: thread → session - Update _mcp.py kwargs filter: add 'session' alongside 'thread' - Fix ContinuationToken docstring example: thread=thread → session=session - Fix _clients.py docstring: 'Agent threads' → 'Agent sessions' * Fix broken markdown links after thread→session file renames * fix azure ai test |
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Eduard van ValkenburgandGitHub
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a2856d3b92 |
Python: restructure: Python samples into progressive 01-05 layout (#3862)
* restructure: Python samples into progressive 01-05 layout - 01-get-started/: 6 numbered steps (hello agent → hosting) - 02-agents/: all agent concept samples (tools, middleware, providers, etc.) - 03-workflows/: ALL existing workflow samples preserved as-is - 04-hosting/: azure-functions, durabletask, a2a - 05-end-to-end/: demos, evaluation, hosted agents - Old files moved to _to_delete/ for review - Added AGENTS.md with structure documentation - autogen-migration/ and semantic-kernel-migration/ preserved at root * fix: switch to AzureOpenAI Foundry, fix CI failures - Switch all 01-get-started samples to AzureOpenAIResponsesClient with Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT + AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential) - Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes - Fix test paths in packages/ that referenced old getting_started/ dirs: durabletask conftest + streaming test, azurefunctions conftest, devui conftest + capture_messages + openai_sdk_integration - Fix workflow_as_agent_human_in_the_loop.py import (sibling import) - Update hosting READMEs and tool comment paths - Replace root README.md with new structure overview - Update AGENTS.md to document Azure OpenAI Foundry as default provider * cleanup: remove _to_delete folder, copy resource files to active dirs All files in _to_delete/ were either: - Exact duplicates of files in the new structure (240 files) - Same file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since active samples reference them. * fix: address PR review comments, centralize resources, remove root duplicates - Fix type annotation in 04_memory.py (string union -> proper types) - Fix old sample paths in observability files - Fix grammar/spelling in observability samples - Move sample_assets/ and resources/ to shared/ folder - Remove 8 duplicate observability files from 02-agents root - Update resource path references in multimodal_input and provider samples * fix: update broken links from old getting_started paths to new structure - Update relative paths in READMEs: getting_started/ → 01-get-started/, 02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/ - Fix absolute GitHub URLs in package READMEs - Fix broken link in ollama package README * fix: convert absolute GitHub URLs to relative paths for link checker Absolute URLs to python/samples/ on main branch 404 until PR merges. Converted to relative paths that linkspector can verify locally. * fix: update link for handoff sample moved to orchestrations/ * fix: update chatkit-integration README path from demos/ to 05-end-to-end/ * fix: update broken links in orchestrations README to match flat directory structure |
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Eduard van ValkenburgandGitHub
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8ed50009c6 |
Python: Centralize tool result parsing in FunctionTool.invoke() (#3854)
* Centralize tool result parsing in FunctionTool.invoke() - Add parse_result static method to FunctionTool that converts raw function return values to strings at invocation time - Add result_parser parameter to FunctionTool and @tool decorator for custom parsing - Remove prepare_function_call_results from all 9 consumer files and from the public API - Update MCPTool to parse MCP types directly to strings via _parse_tool_result_from_mcp and _parse_prompt_result_from_mcp - Change MCPTool parse_tool_results/parse_prompt_results type from Literal[True] | Callable | None to Callable | None - Remove ReturnT type parameter from FunctionTool (now single generic ArgsT since invoke() always returns str) - Update all subclass signatures and docstrings Fixes #1147 * Fix test_mcp_tool_call_tool_with_meta_integration for string results The test was still accessing result[0].additional_properties but invoke() now returns a string, not a list of Content objects. * Fix SIM108 lint: use binary operator for output assignment * Fix bedrock: use FunctionTool.parse_result instead of str() fallback str(result) turns None into literal 'None' and dicts into Python reprs with single quotes, breaking JSON parsing. Use the shared parse_result which handles None as '' and serializes via json.dumps. * updated lock * updates from feedback |
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Eduard van ValkenburgandGitHub
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8457533c69 |
Python: Replace Pydantic Settings with TypedDict + load_settings() (#3843)
* Replace Pydantic Settings with TypedDict + load_settings() - Remove pydantic-settings dependency, add python-dotenv - Delete _pydantic.py (AFBaseSettings, HTTPsUrl) - Add _settings.py with generic load_settings() function, SecretString, type coercion, and Required field validation (SettingNotFoundError) - Convert all 13 settings classes from AFBaseSettings subclasses to TypedDict definitions with load_settings() calls - Update all consumers from attribute access to dict access - Add 20 unit tests for load_settings() covering basic loading, dotenv, SecretString, type coercion, and required field validation - Update all existing tests for new settings patterns * Fix mypy type errors from settings conversion - Fix str | None attribute access in responses_client (walrus operator) - Fix SecretString | None narrowing in bedrock (type: ignore after guard) - Convert _context_provider.py attribute access to dict access (missed file) - Fix endpoint type narrowing in search_provider and context_provider - Fix purview: str | None .rstrip(), int | None defaults, urlparse bytes * Address PR review: required_fields param, type validation, fixes - Move required field validation from TypedDict annotations (Required) to a required_fields parameter on load_settings(), enabling runtime decisions about which fields are required - Remove Required imports and restore from __future__ import annotations in ollama and foundry_local - Add _check_override_type() for deterministic ServiceInitializationError on invalid override types (e.g. dict passed for str field) - Fix all multi-exception test catches back to single exception type - Fix Ollama host=None: use .get() so None is passed through to SDK default - Fix Purview processor: use explicit is-None checks instead of or operator - Remove unused BaseModel import from openai/_shared.py - Add 4 new tests (24 total): required_fields param, type validation * Fix type validation: allow int for float fields _check_override_type now permits int values for float-typed fields, matching Python's standard numeric promotion behavior. * fix: wrap urlparse arg with str() to fix mypy bytes endswith error |
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0521f5bed8 |
Python: [BREAKING] Simplify API: ChatAgent -> Agent, ChatMessage -> Message (#3747)
* [BREAKING] Rename ChatAgent -> Agent, ChatMessage -> Message, ChatClientProtocol -> SupportsChatGetResponse Simplify the public API by removing redundant 'Chat' prefix from core types: - ChatAgent -> Agent - RawChatAgent -> RawAgent - ChatMessage -> Message - ChatClientProtocol -> SupportsChatGetResponse Also renamed internal WorkflowMessage (was Message in _runner_context) to avoid collision. No backward compatibility aliases - this is a clean breaking change. * [BREAKING] Rename Agent chat_client parameter to client * Fix rebase issues: WorkflowMessage references and broken markdown links * Fix formatting and lint issues from code quality checks * Fix import ordering in workflow sample files * fixed rebase * Fix test failures: use WorkflowMessage and A2AMessage after ChatMessage→Message rename - Replace Message(data=..., source_id=...) with WorkflowMessage(...) in workflow tests - Fix isinstance check in A2A agent to use A2AMessage instead of Message - Fix import in test_workflow_observability.py (Message→WorkflowMessage) * Fix lint, fmt, and sample errors after ChatMessage→Message rename - Auto-fix 70+ ruff lint issues across samples (ChatMessage→Message refs) - Fix HostedVectorStoreContent→Content.from_hosted_vector_store in file search sample - Fix _normalize_messages→normalize_messages in custom agent sample - Fix context.terminate→raise MiddlewareTermination in middleware samples - Fix with_update_hook→with_transform_hook in override middleware sample - Add TOptions_co import back to custom_chat_client sample - Add noqa for FastAPI File() default in chatkit sample - Fix B023 loop variable capture in weather agent sample * fix: update Agent constructor calls from chat_client to client in declaration-only tool tests * fix: add register_cleanup to devui lazy-loading proxy and type stub * fixed tests and updated new pieces * fix agui typevar * fix merge errors * fix merge conflicts * fiux merge * Remove unused links --------- Co-authored-by: Evan Mattson <evan.mattson@microsoft.com> |
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Eduard van ValkenburgandGitHub
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ac0e6b0ee1 |
Python: PR1 — New session and context provider types (side-by-side) (#3763)
* PR1: Add core context provider types and tests New types in _sessions.py (no changes to existing code): - SessionContext: per-invocation state with extend_messages/get_messages/ extend_instructions/extend_tools and read-only response property - _ContextProviderBase: base class with before_run/after_run hooks - _HistoryProviderBase: storage base with load/store flags, abstract get_messages/save_messages, default before_run/after_run - AgentSession: lightweight session with state dict, to_dict/from_dict - InMemoryHistoryProvider: built-in provider storing in session.state 35 unit tests covering all classes and configuration flags. * feat: keyword-only params, stateless InMemoryHistoryProvider, deep serialization - Make before_run/after_run parameters keyword-only - InMemoryHistoryProvider stores ChatMessage objects directly (no per-cycle serialization) - Deep serialization via to_dict/from_dict only at session boundary - State type registry for automatic deserialization of registered types - Updated tests for new serialization approach * feat: add new-pattern provider implementations for external packages - _RedisContextProvider(BaseContextProvider) - Redis search/vector context - _RedisHistoryProvider(BaseHistoryProvider) - Redis-backed message storage - _Mem0ContextProvider(BaseContextProvider) - Mem0 semantic memory - _AzureAISearchContextProvider(BaseContextProvider) - Azure AI Search (semantic + agentic) All use temporary _ prefix names for side-by-side coexistence with existing providers. Will be renamed in PR2 when old ContextProvider/ChatMessageStore are removed. * test: add tests for new-pattern provider implementations - 32 tests for _RedisContextProvider and _RedisHistoryProvider - 29 tests for _Mem0ContextProvider - 17 tests for _AzureAISearchContextProvider * fix: address PR review comments and CI failures - Move module docstring before imports in _sessions.py (review comment) - Import TYPE_CHECKING unconditionally in Redis _context_provider.py (NameError on Python <3.12) - Fix Mem0 test_init_auto_creates_client_when_none to patch at class level * feat: add source attribution to extend_messages Set attribution marker in additional_properties for each message added via extend_messages(), matching the tool attribution pattern. Uses setdefault to preserve any existing attribution. * refactor: make attribution value a dict with source_id key * add attribution and use sets for filters * Add source_type to message attribution and copy messages in extend_messages - SessionContext.extend_messages now accepts source as str or object with source_id attribute; when an object is passed, its class name is recorded as source_type in the attribution dict - Messages are shallow-copied before attribution is added so callers' original objects are never mutated - Filter framework-internal keys (attribution) from A2A wire metadata to prevent leaking internal state over the wire * fix: correct mypy type: ignore comment from union-attr to attr-defined * set attribution to _attribution * adjusted naming of bools |
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Eduard van ValkenburgandGitHub
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35097d8c75 |
Python: Add long-running agents and background responses support (#3808)
* Python: Add long-running agents and background responses support - Add ContinuationToken TypedDict to core types - Add continuation_token field to ChatResponse, ChatResponseUpdate, AgentResponse, and AgentResponseUpdate - Add background and continuation_token options to OpenAIResponsesOptions - Implement polling via responses.retrieve() and streaming resumption in RawOpenAIResponsesClient - Propagate continuation tokens through agent run() and map_chat_to_agent_update - Fix streaming telemetry 'Failed to detach context' error in both ChatTelemetryLayer and AgentTelemetryLayer by avoiding trace.use_span() context attachment for async-managed spans - Add 14 unit tests for continuation token types and background flows - Add background_responses sample showing polling and stream resumption Fixes #2478 * Python: Add A2A long-running task support via ContinuationToken - Make ContinuationToken provider-agnostic (total=False, optional task_id/context_id fields) - Add background param to A2AAgent.run() controlling token emission - Add poll_task() for single-request task state retrieval - Add resubscribe support via continuation_token param on run() - Extract _updates_from_task() and _map_a2a_stream() for cleaner code - Streamline run()/streaming by removing intermediate _stream_updates wrapper - Update A2A sample to show background=False (default) with link to background_responses sample - Remove stale BareAgent from __all__ - Add 12 new A2A continuation token tests * fix logic for overriding continuation token when done * refactored ContinuationToken setup |
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Eduard van ValkenburgandGitHub
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8ad66637d8 |
Python: Fix prek runner duplication and add skills (#3791)
* Python: fix prek runner running fmt/lint in all packages on core change When a core package file changed, run_tasks_in_changed_packages.py ran fmt, lint, and pyright in ALL 22 packages (66 tasks). Only type-checking tasks (pyright, mypy) need to propagate to all packages since type changes in core affect downstream packages. File-local tasks (fmt, lint) only need to run in packages with actual file changes. This reduces a core-only change from 66 tasks to 24 tasks (2 local + 22 pyright). Also adds no-commit-to-branch builtin hook to protect the main branch from direct commits. * Python: add agent skills extracted from AGENTS.md and coding standards Add 5 skills to python/.github/skills/ following the Agent Skills format: - python-development: coding standards, type annotations, docstrings, logging - python-testing: test structure, fixtures, running tests, async mode - python-code-quality: linting, formatting, type checking, prek hooks, CI - python-package-management: monorepo structure, lazy loading, versioning - python-samples: sample structure, PEP 723, documentation guidelines * Python: deduplicate AGENTS.md and instructions with agent skills * updated skills * fixes from review * Python: increase timeout for web search integration test |
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Eduard van ValkenburgandGitHub
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9f14a0f33f |
Python: ADR: Unifying Context Management with ContextMiddleware (Python) (#3609)
* Add ADR for Python ContextMiddleware unification * Add session serialization/deserialization design to ADR * Add Related Issues section mapping to ADR * Update session management: create_session, get_session_by_id, agent.serialize_session * ADR: Add hooks alternative, context compaction discussion, and PR feedback - Add Option 3: ContextHooks with before_run/after_run pattern - Add detailed pros/cons for both wrapper and hooks approaches - Add Open Discussion section on context compaction strategies - Clarify response_messages is read-only (use AgentMiddleware for modifications) - Add SimpleRAG examples showing input-only filtering - Clarify default storage only added when NO middleware configured - Add RAGWithBuffer examples for self-managed history - Rename hook methods to before_run/after_run * ADR: Restructure and add .NET comparison - Add class hierarchy clarification for both options - Merge detailed design sections (side-by-side comparison) - Move detailed design before decision outcome - Move compaction discussion after decision - Add .NET implementation comparison (feature equivalence) - Update .NET method names to match actual implementation - Rename hook methods to before_run/after_run - Fix storage context table for injected context * tweaks * fix smart load * ADR: Add naming discussion note for ContextHooks - Note that class and method names are open for discussion - Add alternative method naming options table - Include invoking/invoked as option matching current Python and .NET * Update context middleware design: remove smart mode, add attribution filtering - Remove smart mode for load_messages (now explicit bool, default True) - Add attribution marker in additional_properties for message filtering - Update validation to warn on multiple or zero storage loaders - Add note about ChatReducer naming from .NET - Note that attribution should not be propagated to storage * Add Decision 2: Instance Ownership (instances in session vs agent) - Option A: Instances in Session (current proposal) - Option B: Instances in Agent, State in Session - B1: Simple dict state with optional return - B2: SessionState object with mutable wrapper - Updated examples to use Hooks pattern (before_run/after_run) - Added open discussion on hook factories in Option B model * Update ADR: Choose ContextPlugin with before_run/after_run and Option B1 Decision outcomes: - Option 3 (Hooks pattern) with ContextPlugin class name - Methods: before_run/after_run - Option B1: Instances in Agent, State in Session (simple dict) - Whole state dict passed to plugins (mutable, no return needed) - Added trust note: plugins reason over messages, so they're trusted by default Status changed from proposed to accepted. * Add agent and session params to before_run/after_run methods Signature now: before_run(agent, session, context, state) * Remove ContextPluginRunner, store plugins directly on agent Simpler design: agent stores Sequence[ContextPlugin] and calls before_run/after_run directly in the run method. * Update workplan to 2 PRs for simpler review * updated doc * Refine ADR: serialization, ownership, decorators, session methods, exports - Add to_dict()/from_dict() on AgentSession with 'type' discriminator - Present serialization as Option A (direct) vs Option B (through agent) - Rewrite ownership section as 2x2 matrix (orthogonal decision) - Move Instance Ownership Options before Decision Outcome - Fix get_session to use service_session_id, split from create_session - Add decorator-based provider convenience API (@before_run/@after_run) - Add _ prefix naming strategy for all PR1 types (core + external) - Constructor compatibility table for existing providers - Add load_messages=False skip logic to all agent run loops - Clarify abstract vs non-abstract in execution pattern samples - Update auto-provision: trigger on conversation_id or store=True - Document root package exports (ContextProvider, HistoryProvider, etc.) - Rename section heading to 'Key Design Considerations' * Rename ADR to 0016-python-context-middleware.md * Fix broken link: #3-unified-storage-middleware → #3-unified-storage |
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Eduard van ValkenburgandGitHub
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977c3adfb2 |
Python: replace pre-commit with prek, add PEP 723 script deps, clean up dev dependencies (#3748)
* python: replace pre-commit with prek, add PEP 723 script deps, clean up dev dependencies - Replace pre-commit with prek (Rust-native, faster pre-commit alternative) - Move supported hooks to repo: builtin for zero-clone speed - Add new builtin hooks: trailing-whitespace, check-merge-conflict, detect-private-key, check-added-large-files - Update all hook versions to latest (pre-commit-hooks v6, pyupgrade v3.21.2, bandit 1.9.3, uv-pre-commit 0.10.0) - Add PEP 723 inline script metadata to 34 samples with external deps - Remove autogen-agentchat/autogen-ext from dev deps (now declared per-sample) - Remove unused dev deps: pytest-env, tomli-w - Add agent-framework-core>=1.0.0b260130 lower bound to all 21 packages - Update CI workflow to use j178/prek-action - Update docs: DEV_SETUP.md, AGENTS.md, CODING_STANDARD.md, SAMPLE_GUIDELINES.md * updated lock * python: fix prek config paths for local execution and CI workflow Remove global 'files: ^python/' filter and strip python/ prefix from all path patterns in .pre-commit-config.yaml so prek finds files when run from the python/ directory. Update CI workflow to use --cd python instead of --config path. Include trailing whitespace fixes and dev dependency cleanup. * python: move helper scripts to scripts/ folder and exclude from checks * python: exclude AGENTS.md from prek markdown code lint * python: exclude AGENTS.md and azure_ai_search sample from markdown lint * fix m365 sample * python: ignore CPY rule for samples with PEP 723 headers * fix in dev_setup * python: replace aiofiles with regular open in samples * python: suppress reportUnusedImport in markdown code block checker * python: use samples pyright config for markdown code block checker Write a temp pyrightconfig.json matching pyrightconfig.samples.json rules (typeCheckingMode=off, only reportMissingImports and reportAttributeAccessIssue). Filter output to only fail on these rules since syntax-level errors (top-level await, undefined vars) are expected in README documentation snippets. * python: use markdown-code-lint with fixed globs instead of prek file list The prek-markdown-code-lint task received all changed files including non-README markdown and files with pre-existing broken imports. Replace with the standard markdown-code-lint task which uses the correct glob patterns (README.md, packages/**/README.md, samples/**/*.md). * python: exclude READMEs with pre-existing broken imports from markdown lint * python: fix broken README code snippets instead of excluding them - ag-ui: replace TextContent (removed) with content.type == 'text' - durabletask: fix import path to durabletask.worker.TaskHubGrpcWorker - orchestrations: use constructor params instead of .participants() method - observability: mark deprecated code blocks as plain text, filter reportMissingImports to agent_framework modules only - remove README excludes from markdown-code-lint task * add revision to gaia download * feat(python): parallelize checks across packages Run (package × task) cross-product in parallel using ThreadPoolExecutor and subprocesses. Key changes: - Add scripts/task_runner.py with shared parallel execution engine - Update run_tasks_in_packages_if_exists.py to accept multiple tasks - Update run_tasks_in_changed_packages.py with --files flag and parallel support - Add check-packages poe task (fmt+lint+pyright+mypy in parallel) - Add prek-markdown-code-lint and prek-samples-check with change detection - Split CI code quality workflow into parallel prek and mypy jobs - Update DEV_SETUP.md to document new parallel behavior Core package changes still trigger checks on all packages. * feat(ci): split code quality into 4 parallel jobs Split the single prek job into parallel jobs: - pre-commit-hooks: lightweight hooks (SKIP=poe-check) - package-checks: fmt/lint/pyright/mypy via check-packages - samples-markdown: samples-lint, samples-syntax, markdown-code-lint - mypy: change-detected mypy checks All 4 jobs run concurrently (×2 Python versions = 8 runners). * feat(ci): use only Python 3.10 for code quality checks * refactor(python): add future annotations and remove quoted types Add `from __future__ import annotations` to 93 package files that used quoted string annotations, then run pyupgrade --py310-plus to remove the now-unnecessary quotes. Fixes https://github.com/microsoft/agent-framework/issues/3578 |
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Eduard van ValkenburgandGitHub
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390f93344c |
Python: Add samples syntax checking with pyright (#3710)
* Add samples syntax checking with pyright - Add pyrightconfig.samples.json with relaxed type checking but import validation - Add samples-syntax poe task to check samples for syntax and import errors - Add samples-syntax to check and pre-commit-check tasks - Fix 78 sample errors: - Update workflow builder imports to use agent_framework_orchestrations - Change content type isinstance checks to content.type comparisons - Use Content factory methods instead of removed content type classes - Fix TypedDict access patterns for Annotation - Fix various API mismatches (normalize_messages, ChatMessage.text, role) * fixed a bunch of samples and tweaks to pre-commit * updated lock * updated lock * fixes * added lint to samples |
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3dc59c83b5 |
Python: [BREAKING] Moved to a single get_response and run API (#3379)
* WIP * big update to new ResponseStream model * fixed tests and typing * fixed tests and typing * fixed tools typevar import * fix * mypy fix * mypy fixes and some cleanup * fix missing quoted names * and client * fix imports agui * fix anthropic override * fix agui * fix ag ui * fix import * fix anthropic types * fix mypy * refactoring * updated typing * fix 3.11 * fixes * redid layering of chat clients and agents * redid layering of chat clients and agents * Fix lint, type, and test issues after rebase - Add @overload decorators to AgentProtocol.run() for type compatibility - Add missing docstring params (middleware, function_invocation_configuration) - Fix TODO format (TD002) by adding author tags - Fix broken observability tests from upstream: - Replace non-existent use_instrumentation with direct instantiation - Replace non-existent use_agent_instrumentation with AgentTelemetryLayer mixin - Fix get_streaming_response to use get_response(stream=True) - Add AgentInitializationError import - Update streaming exception tests to match actual behavior * Fix AgentExecutionException import error in test_agents.py - Replace non-existent AgentExecutionException with AgentRunException * Fix test import and asyncio deprecation issues - Add 'tests' to pythonpath in ag-ui pyproject.toml for utils_test_ag_ui import - Replace deprecated asyncio.get_event_loop().run_until_complete with asyncio.run * Fix azure-ai test failures - Update _prepare_options patching to use correct class path - Fix test_to_azure_ai_agent_tools_web_search_missing_connection to clear env vars * Convert ag-ui utils_test_ag_ui.py to conftest.py - Move test utilities to conftest.py for proper pytest discovery - Update all test imports to use conftest instead of utils_test_ag_ui - Remove old utils_test_ag_ui.py file - Revert pythonpath change in pyproject.toml * fix: use relative imports for ag-ui test utilities * fix agui * Rename Bare*Client to Raw*Client and BaseChatClient - Renamed BareChatClient to BaseChatClient (abstract base class) - Renamed BareOpenAIChatClient to RawOpenAIChatClient - Renamed BareOpenAIResponsesClient to RawOpenAIResponsesClient - Renamed BareAzureAIClient to RawAzureAIClient - Added warning docstrings to Raw* classes about layer ordering - Updated README in samples/getting_started/agents/custom with layer docs - Added test for span ordering with function calling * Fix layer ordering: FunctionInvocationLayer before ChatTelemetryLayer This ensures each inner LLM call gets its own telemetry span, resulting in the correct span sequence: chat -> execute_tool -> chat Updated all production clients and test mocks to use correct ordering: - ChatMiddlewareLayer (first) - FunctionInvocationLayer (second) - ChatTelemetryLayer (third) - BaseChatClient/Raw...Client (fourth) * Remove run_stream usage * Fix conversation_id propagation * Python: Add BaseAgent implementation for Claude Agent SDK (#3509) * Added ClaudeAgent implementation * Updated streaming logic * Small updates * Small update * Fixes * Small fix * Naming improvements * Updated imports * Addressed comments * Updated package versions * Update Claude agent connector layering * fix test and plugin * Store function middleware in invocation layer * Fix telemetry streaming and ag-ui tests * Remove legacy ag-ui tests folder * updates * Remove terminate flag from FunctionInvocationContext, use MiddlewareTermination instead - Remove terminate attribute from FunctionInvocationContext - Add result attribute to MiddlewareTermination to carry function results - FunctionMiddlewarePipeline.execute() now lets MiddlewareTermination propagate - _auto_invoke_function captures context.result in exception before re-raising - _try_execute_function_calls catches MiddlewareTermination and sets should_terminate - Fix handoff middleware to append to chat_client.function_middleware directly - Update tests to use raise MiddlewareTermination instead of context.terminate - Add middleware flow documentation in samples/concepts/tools/README.md - Fix ag-ui to use FunctionMiddlewarePipeline instead of removed create_function_middleware_pipeline * fix: remove references to removed terminate flag in purview tests, add type ignore * fix: move _test_utils.py from package to test folder * fix: call get_final_response() to trigger context provider notification in streaming test * fix: correct broken links in tools README * docs: clarify default middleware behavior in summary table * fix: ensure inner stream result hooks are called when using map()/from_awaitable() * Fix mypy type errors * Address PR review comments on observability.py - Remove TODO comment about unconsumed streams, add explanatory note instead - Remove redundant _close_span cleanup hook (already called in _finalize_stream) - Clarify behavior: cleanup hooks run after stream iteration, if stream is not consumed the span remains open until garbage collected * Remove gen_ai.client.operation.duration from span attributes Duration is a metrics-only attribute per OpenTelemetry semantic conventions. It should be recorded to the histogram but not set as a span attribute. * Remove duration from _get_response_attributes, pass directly to _capture_response Duration is a metrics-only attribute. It's now passed directly to _capture_response instead of being included in the attributes dict that gets set on the span. * Remove redundant _close_span cleanup hook in AgentTelemetryLayer _finalize_stream already calls _close_span() in its finally block, so adding it as a separate cleanup hook is redundant. * Use weakref.finalize to close span when stream is garbage collected If a user creates a streaming response but never consumes it, the cleanup hooks won't run. Now we register a weak reference finalizer that will close the span when the stream object is garbage collected, ensuring spans don't leak in this scenario. * Fix _get_finalizers_from_stream to use _result_hooks attribute Renamed function to _get_result_hooks_from_stream and fixed it to look for the _result_hooks attribute which is the correct name in ResponseStream class. * Add missing asyncio import in test_request_info_mixin.py * Fix leftover merge conflict marker in image_generation sample * Update integration tests * Fix integration tests: increase max_iterations from 1 to 2 Tests with tool_choice options require at least 2 iterations: 1. First iteration to get function call and execute the tool 2. Second iteration to get the final text response With max_iterations=1, streaming tests would return early with only the function call/result but no final text content. * Fix duplicate function call error in conversation-based APIs When using conversation_id (for Responses/Assistants APIs), the server already has the function call message from the previous response. We should only send the new function result message, not all messages including the function call which would cause a duplicate ID error. Fix: When conversation_id is set, only send the last message (the tool result) instead of all response.messages. * Add regression test for conversation_id propagation between tool iterations Port test from PR #3664 with updates for new streaming API pattern. Tests that conversation_id is properly updated in options dict during function invocation loop iterations. * Fix tool_choice=required to return after tool execution When tool_choice is 'required', the user's intent is to force exactly one tool call. After the tool executes, return immediately with the function call and result - don't continue to call the model again. This fixes integration tests that were failing with empty text responses because with tool_choice=required, the model would keep returning function calls instead of text. Also adds regression tests for: - conversation_id propagation between tool iterations (from PR #3664) - tool_choice=required returns after tool execution * Document tool_choice behavior in tools README - Add table explaining tool_choice values (auto, none, required) - Explain why tool_choice=required returns immediately after tool execution - Add code example showing the difference between required and auto - Update flow diagram to show the early return path for tool_choice=required * Fix tool_choice=None behavior - don't default to 'auto' Remove the hardcoded default of 'auto' for tool_choice in ChatAgent init. When tool_choice is not specified (None), it will now not be sent to the API, allowing the API's default behavior to be used. Users who want tool_choice='auto' can still explicitly set it either in default_options or at runtime. Fixes #3585 * Fix tool_choice=none should not remove tools In OpenAI Assistants client, tools were not being sent when tool_choice='none'. This was incorrect - tool_choice='none' means the model won't call tools, but tools should still be available in the request (they may be used later in the conversation). Fixes #3585 * Add test for tool_choice=none preserving tools Adds a regression test to ensure that when tool_choice='none' is set but tools are provided, the tools are still sent to the API. This verifies the fix for #3585. * Fix tool_choice=none should not remove tools in all clients Apply the same fix to OpenAI Responses client and Azure AI client: - OpenAI Responses: Remove else block that popped tool_choice/parallel_tool_calls - Azure AI: Remove tool_choice != 'none' check when adding tools When tool_choice='none', the model won't call tools, but tools should still be sent to the API so they're available for future turns. Also update README to clarify tool_choice=required supports multiple tools. Fixes #3585 * Keep tool_choice even when tools is None Move tool_choice processing outside of the 'if tools' block in OpenAI Responses client so tool_choice is sent to the API even when no tools are provided. * Update test to match new parallel_tool_calls behavior Changed test_prepare_options_removes_parallel_tool_calls_when_no_tools to test_prepare_options_preserves_parallel_tool_calls_when_no_tools to reflect that parallel_tool_calls is now preserved even when no tools are present, consistent with the tool_choice behavior. * Fix ChatMessage API and Role enum usage after rebase - Update ChatMessage instantiation to use keyword args (role=, text=, contents=) - Fix Role enum comparisons to use .value for string comparison - Add created_at to AgentResponse in error handling - Fix AgentResponse.from_updates -> from_agent_run_response_updates - Fix DurableAgentStateMessage.from_chat_message to convert Role enum to string - Add Role import where needed * Fix additional ChatMessage API and method name changes - Fix ChatMessage usage in workflow files (use text= instead of contents= for strings) - Fix AgentResponse.from_updates -> from_agent_run_response_updates in workflow files - Fix test files for ChatMessage and Role enum usage * Fix remaining ChatMessage API usage in test files * Fix more ChatMessage and Role API changes in source and test files - Fix ChatMessage in _magentic.py replan method - Fix Role enum comparison in test assertions - Fix remaining test files with old ChatMessage syntax * Fix ChatMessage and Role API changes across packages - Add Role import where missing - Fix ChatMessage signature: positional args to keyword args (role=, text=, contents=) - Fix Role enum comparisons: .role.value instead of .role string - Fix FinishReason enum usage in ag-ui event converters - Rename AgentResponse.from_updates to from_agent_run_response_updates in ag-ui Fixes API compatibility after Types API Review improvements merge * Fix ChatMessage and Role API changes in github_copilot tests * Fix ChatMessage and Role API changes in redis and github_copilot packages - Fix redis provider: Role enum comparison using .value - Fix redis tests: ChatMessage signature and Role comparisons - Fix github_copilot tests: ChatMessage signature and Role comparisons - Update docstring examples in redis chat message store * Fix ChatMessage and Role API changes in devui package - Fix executor: ChatMessage signature change - Fix conversations: Role enum to string conversion in two places - Fix tests: ChatMessage signatures and Role comparisons * Fix ChatMessage and Role API changes in a2a and lab packages - Fix a2a tests: Role comparisons and ChatMessage signatures - Fix lab tau2 source: Role enum comparison in flip_messages, log_messages, sliding_window - Fix lab tau2 tests: ChatMessage signatures and Role comparisons * Remove duplicate test files from ag-ui/tests (tests are in ag_ui_tests) * Fix ChatMessage and Role API changes across packages After rebasing on upstream/main which merged PR #3647 (Types API Review improvements), fix all packages to use the new API: - ChatMessage: Use keyword args (role=, text=, contents=) instead of positional args - Role: Compare using .value attribute since it's now an enum Packages fixed: - ag-ui: Fixed Role value extraction bugs in _message_adapters.py - anthropic: Fixed ChatMessage and Role comparisons in tests - azure-ai: Fixed Role comparison in _client.py - azure-ai-search: Fixed ChatMessage and Role in source/tests - bedrock: Fixed ChatMessage signatures in tests - chatkit: Fixed ChatMessage and Role in source/tests - copilotstudio: Fixed ChatMessage and Role in tests - declarative: Fixed ChatMessage in _executors_agents.py - mem0: Fixed ChatMessage and Role in source/tests - purview: Fixed ChatMessage in source/tests * Fix mypy errors for ChatMessage and Role API changes - durabletask: Use str() fallback in role value extraction - core: Fix ChatMessage in _orchestrator_helpers.py to use keyword args - core: Add type ignore for _conversation_state.py contents deserialization - ag-ui: Fix type ignore comments (call-overload instead of arg-type) - azure-ai-search: Fix get_role_value type hint to accept Any - lab: Move get_role_value to module level with Any type hint * Improve CI test timeout configuration - Increase job timeout from 10 to 15 minutes - Reduce per-test timeout to 60s (was 900s/300s) - Add --timeout_method thread for better timeout handling - Add --timeout-verbose to see which tests are slow - Reduce retries from 3 to 2 and delay from 10s to 5s This ensures individual test timeouts are shorter than the job timeout, providing better visibility when tests hang. With 60s timeout and 2 retries, worst case per test is ~180s. * Fix ChatMessage API usage in docstrings and source - Fix ChatMessage positional args in docstrings: _serialization.py, _threads.py, _middleware.py - Fix ChatMessage in tau2 runner.py - Fix role comparison in _orchestrator_helpers.py to use .value - Fix role comparison in _group_chat.py docstring example - Fix role assertions in test_durable_entities.py to use .value * Revert tool_choice/parallel_tool_calls changes - must be removed when no tools OpenAI API requires tool_choice and parallel_tool_calls to only be present when tools are specified. Restored the logic that removes these options when there are no tools. - Restored check in _chat_client.py to remove tool_choice and parallel_tool_calls when no tools present - Restored same logic in _responses_client.py - Reverted test to expect the correct behavior * fixed issue in tests * fix: resolve merge conflict markers in ag-ui tests * fix: restructure ag-ui tests and fix Role/FinishReason to use string types * fix: streaming function invocation and middleware termination - Refactor streaming function invocation to use get_final_response() on inner streams - Fix MiddlewareTermination to accept result parameter for passing results - Fix _AutoHandoffMiddleware to use MiddlewareTermination instead of context.terminate - Fix AgentMiddlewareLayer.run() to properly forward function/chat middleware - Remove duplicate middleware registration in AgentMiddlewareLayer.__init__ - Fix exception handling in _auto_invoke_function to properly capture termination - Fix mypy errors in core package - Update tests to use stream=True parameter for unified run API * fix all tests command * Refactor integration tests to use pytest fixtures - Merge testutils.py into conftest.py for azurefunctions integration tests - Merge dt_testutils.py into conftest.py for durabletask integration tests - Convert all integration tests to use fixtures instead of direct imports (fixes ModuleNotFoundError with --import-mode=importlib) - Add sample_helper fixture for azurefunctions tests - Add agent_client_factory and orchestration_helper fixtures for durabletask - Integration tests now skip with descriptive messages when services unavailable - Restructure devui tests into tests/devui/ with proper conftest.py - Add test organization guidelines to CODING_STANDARD.md - Remove __init__.py from test directories per pytest best practices * Fix pytest_collection_modifyitems to only skip integration tests The hook was skipping all tests in the test session, not just integration tests. Now it only skips items in the integration_tests directory. * Fix mem0 tests failing on Python 3.13 Use patch.object on the imported module instead of @patch with string path to ensure the mock takes effect regardless of import timing. * fix mem0 * another attempt for mem0 * fix for mem0 * fix mem0 * Increase worker initialization wait time in durabletask tests Increase from 2 to 8 seconds to allow time for: - Python startup and module imports - Azure OpenAI client creation - Agent registration with DTS worker - Worker connection to DTS This helps prevent test failures in CI where the first tests may run before the worker is fully ready to process requests. * Fix streaming test to use ResponseStream with finalizer The _consume_stream method now expects a ResponseStream that can provide a final AgentResponse via get_final_response(). Update the test to use ResponseStream with AgentResponse.from_updates as the finalizer. * Fix MockToolCallingAgent to use new ResponseStream API and update samples * small updates to run_stream to run * fix sub workflow * temp fix for az func test --------- Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com> |
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Eduard van ValkenburgandGitHub
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eaad042241 |
.NET: Python: Add AGENTS.md files and update coding standards (#3644)
* Add AGENTS.md files and update coding standards for Python - Add root python/AGENTS.md with project structure and package links - Add AGENTS.md for each package describing purpose and main classes - Update .github/copilot-instructions.md with improved structure - Update python/CODING_STANDARD.md with API review guidance: - Future annotations convention (#3578) - TypeVar naming convention (#3594) - Mapping vs MutableMapping (#3577) - Avoid shadowing built-ins (#3583) - Explicit exports (#3605) - Exception documentation guidelines (#3410) - Simplify python/.github/instructions/python.instructions.md to reference AGENTS.md - Remove AGENTS.md from .gitignore * Fix purview import path in AGENTS.md * Address PR review comments and restructure instructions - Slim down .github/copilot-instructions.md to reference language-specific docs - Add ADR section explaining templates and purpose - Create dotnet/AGENTS.md with .NET-specific build commands, conventions, and sample guidance - Update Python build/test instructions for core vs isolated changes - Fix Microsoft.Extensions.AI package references - Update kwargs guidance per issue #3642 - Fix Python sample helper placement (top, not bottom) - Document new 'typing' poe task in DEV_SETUP.md * Add 'typing' poe task to run both pyright and mypy * Add kwargs guidelines from issue #3642 to CODING_STANDARD.md * Clarify that connector packages pull in core as dependency |
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Eduard van ValkenburgandGitHub
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838a7fd61d |
Python: [BREAKING] Types API Review improvements (#3647)
* Replace Role and FinishReason classes with NewType + Literal
- Remove EnumLike metaclass from _types.py
- Replace Role class with NewType('Role', str) + RoleLiteral
- Replace FinishReason class with NewType('FinishReason', str) + FinishReasonLiteral
- Update all usages across codebase to use string literals
- Remove .value access patterns (direct string comparison now works)
- Add backward compatibility for legacy dict serialization format
- Update tests to reflect new string-based types
Addresses #3591, #3615
* Simplify ChatResponse and AgentResponse type hints (#3592)
- Remove overloads from ChatResponse.__init__
- Remove text parameter from ChatResponse.__init__
- Remove | dict[str, Any] from finish_reason and usage_details params
- Remove **kwargs from AgentResponse.__init__
- Both now accept ChatMessage | Sequence[ChatMessage] | None for messages
- Update docstrings and examples to reflect changes
- Fix tests that were using removed kwargs
- Fix Role type hint usage in ag-ui utils
* Remove text parameter from ChatResponseUpdate and AgentResponseUpdate (#3597)
- Remove text parameter from ChatResponseUpdate.__init__
- Remove text parameter from AgentResponseUpdate.__init__
- Remove **kwargs from both update classes
- Simplify contents parameter type to Sequence[Content] | None
- Update all usages to use contents=[Content.from_text(...)] pattern
- Fix imports in test files
- Update docstrings and examples
* Rename from_chat_response_updates to from_updates (#3593)
- ChatResponse.from_chat_response_updates → ChatResponse.from_updates
- ChatResponse.from_chat_response_generator → ChatResponse.from_update_generator
- AgentResponse.from_agent_run_response_updates → AgentResponse.from_updates
* Remove try_parse_value method from ChatResponse and AgentResponse (#3595)
- Remove try_parse_value method from ChatResponse
- Remove try_parse_value method from AgentResponse
- Remove try_parse_value calls from from_updates and from_update_generator methods
- Update samples to use try/except with response.value instead
- Update tests to use response.value pattern
- Users should now use response.value with try/except for safe parsing
* Add agent_id to AgentResponse and clarify author_name documentation (#3596)
- Add agent_id parameter to AgentResponse class
- Document that author_name is on ChatMessage objects, not responses
- Update ChatResponse docstring with author_name note
- Update AgentResponse docstring with author_name note
* Simplify ChatMessage.__init__ signature (#3618)
- Make contents a positional argument accepting Sequence[Content | str]
- Auto-convert strings in contents to TextContent
- Remove overloads, keep text kwarg for backward compatibility with serialization
- Update _parse_content_list to handle string items
- Update all usages across codebase to use new format: ChatMessage("role", ["text"])
* Allow Content as input on run and get_response
- Update prepare_messages and normalize_messages to accept Content
- Update type signatures in _agents.py and _clients.py
- Add tests for Content input handling
* Fix ChatMessage usage across packages and samples
Update all remaining ChatMessage(role=..., text=...) to use new
ChatMessage('role', ['text']) signature.
* Fix Role string usage and response format parsing
- Fix redis provider: remove .value access on string literals
- Fix durabletask ensure_response_format: set _response_format before accessing .value
* Fix ollama .value and ai_model_id issues, handle None in content list
- Fix ollama _chat_client: remove .value on string literals
- Fix ollama _chat_client: rename ai_model_id to model_id
- Fix _parse_content_list: skip None values gracefully
* Fix A2AAgent type signature to include Content
* Fix Role/FinishReason NewType dict annotations and improve test coverage to 95%
* Fix mypy errors for Role/FinishReason NewType usage
* Fix Role.TOOL and Role.ASSISTANT usage in _orchestrator_helpers.py
* Fix Role NewType usage in durabletask _models.py
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Eduard van ValkenburgandGitHub
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1226828ec2 |
Python: added generic types to ChatOptions and ChatResponse/AgentResponse for Response Format (#3305)
* added generic types to ChatOptions and ChatResponse/AgentResponse for response format * fix typevar import * fix for older python versions * fix missing import * fixed imports * fixed mypy * mypy fix |
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Eduard van ValkenburgandGitHub
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a7d924a7d2 |
Python: [BREAKING] changed AIFunction to FunctionTool and @ai_function to @tool (#3413)
* changed AIFunction to FunctionTool and @ai_function to @tool * test and mypy fixes * mypy fix * switch function tool to always_require * fix noop * fix github copilot imports * test fixes * fix ollama test * fixes for tests * fix tests * reverted change to always_require and extended timeout * fix test |
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Eduard van ValkenburgandGitHub
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83e6229c11 |
Python: [Breaking] Simplified Content types to a single class with classmethod constructors. (#3252)
* ported Content to a new model * fixed linting * fixes * fixed data format handling * fix for 3.10 mypy * fix * fix int test |