* Bump Python package versions to 1.5.0 for a release
* Promote orchestrations to 1.0.0rc1
* ci(python-setup): merge dynamic exclude into existing workspace exclude
The python-setup action injected exclude = [...] verbatim into
[tool.uv.workspace], producing a duplicate 'exclude' key when the
section already had a static exclude. Scope the rewrite to the
[tool.uv.workspace] section and append the package to the existing
array when present; idempotent if the package is already excluded.
* Address Copilot review feedback: raise inter-package floors to 1.5.0
- foundry, foundry-local: agent-framework-openai >=1.4.0 -> >=1.5.0
- azure-contentunderstanding: agent-framework-foundry >=1.4.0 -> >=1.5.0
- azurefunctions: pin agent-framework-durabletask to >=1.0.0b260519,<2
Keeps lockstep cohort consistent and avoids mixed 1.4.x / 1.5.0 installs.
* Re-include azurefunctions and durabletask in the uv workspace
The pinned durabletask>=1.4.0 floor is enough to make resolution succeed;
the workspace exclude was over-correction and broke CI samples and pyright
type-checking (re-exports in agent_framework/azure/__init__.pyi plus
samples/04-hosting/{azure_functions,durabletask}/ could not resolve their
imports). Dropping them from agent-framework-core[all] still stands so the
metapackage does not pull them.
* Restore azurefunctions and durabletask in agent-framework-core[all]
The durabletask floor pin keeps users on the safe 1.4.0, so they are once
again included in the metapackage. Update CHANGELOG to reflect the pin
rather than an [all] removal.
* Raise uvicorn ceiling in ag-ui and devui to allow 0.42+
The root override-dependencies pins uvicorn[standard]>=0.34.0 (no upper)
and the workspace lock resolves to 0.47.0. The package ceiling <0.42.0
meant the workspace was no longer testing the declared supported range.
Bump to <1 so the lock fits within the declared bounds.
Also picked up by validate-dependency-bounds: refresh stale orchestrations
RC pin in devui dev deps.
* feat(anthropic): add base_url parameter to AnthropicClient and RawAnthropicClient
Add base_url support to AnthropicSettings TypedDict, RawAnthropicClient,
and AnthropicClient so users can point the client at Foundry or other
Anthropic-compatible endpoints without having to construct AsyncAnthropic
manually.
- Add base_url field to AnthropicSettings (resolved from ANTHROPIC_BASE_URL env var)
- Add base_url parameter to RawAnthropicClient.__init__ and pass it to AsyncAnthropic
- Add base_url parameter to AnthropicClient.__init__ and forward to super
- Add unit tests for base_url on both client classes
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Add `base_url` parameter to `AnthropicClient` and `RawAnthropicClient`
Fixes#5683
* test: add ANTHROPIC_BASE_URL env fallback tests for issue #5683
Add unit tests verifying that both AnthropicClient and RawAnthropicClient
pick up base_url from the ANTHROPIC_BASE_URL environment variable via
load_settings when base_url is not passed explicitly as a constructor arg.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* test(anthropic): explicit base_url kwarg beats ANTHROPIC_BASE_URL env var (#5683)
Add regression tests asserting that when both ANTHROPIC_BASE_URL is set
in the environment *and* an explicit base_url kwarg is passed to
AnthropicClient / RawAnthropicClient, the explicit kwarg wins.
This closes the priority-ordering contract (explicit arg > env var) that
the existing tests left implicit.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Support OpenAI allowed_tools in ToolMode (#5309)
Add allowed_tools field to ToolMode TypedDict, enabling users to restrict
which tools the model may call via the OpenAI allowed_tools tool_choice
type. This preserves prompt caching by keeping all tools in the tools list
while limiting which ones the model can invoke.
- Add allowed_tools: list[str] to ToolMode TypedDict
- Add validation in validate_tool_mode() (only valid when mode == "auto")
- Convert to OpenAI API format in _prepare_options()
- Add tests for validation and API payload generation
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Support OpenAI `allowed_tools` tool choice in Python SDK
Fixes#5309
* Fix#5309: Validate allowed_tools shape and add Chat Completions client support
- validate_tool_mode now checks allowed_tools is a non-string sequence of
strings and normalizes to list[str], raising ContentError for invalid types
- Add missing allowed_tools branch in _chat_completion_client._prepare_options
so allowed_tools is emitted as the OpenAI allowed_tools wire format instead
of being silently dropped
- Add tests for invalid allowed_tools types (string, int, mixed), empty list,
tuple normalization, and Chat Completions client payload generation
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: support allowed_tools with mode 'required' in addition to 'auto'
OpenAI's allowed_tools tool_choice type supports both mode 'auto' and
'required'. Update validation, client conversion, and tests to allow
both modes instead of restricting to 'auto' only.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: use Gemini VALIDATED mode for allowed_tools, warn in unsupported providers
- Use FunctionCallingConfigMode.VALIDATED instead of ANY when allowed_tools
is set with auto mode in Gemini, preserving optional tool-call semantics.
- Handle allowed_tools in required mode with required_function_name precedence.
- Fix allowed_names guard to use identity check (is not None) so empty lists
are preserved.
- Bump google-genai minimum to >=1.32.0 (VALIDATED added in that version).
- Add warnings in Anthropic and Bedrock when allowed_tools is set but not
supported.
- Add Gemini unit tests for allowed_tools with auto, required, empty list,
and required_function_name precedence scenarios.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: Chat Completions API does not support allowed_tools, add integration tests
- Chat Completions API (_chat_completion_client.py) now warns and falls
back to plain mode when allowed_tools is set, since the /chat/completions
endpoint does not support the allowed_tools type.
- Add allowed_tools integration test param to both OpenAIChatClient
(Responses API) and OpenAIChatCompletionClient parametrized option tests.
- Update Chat Completions unit tests to reflect the warn-and-fallback
behavior.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: remove unused walrus operator variable in chat completion client
Remove assigned-but-never-used variable 'allowed' flagged by ruff F841.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: bump package versions for 1.2.2 release
PATCH bump (1.2.1 -> 1.2.2) for the released cohort. Five PRs land in this
window:
- agent-framework-openai: fix file_search citations breaking the assistant-
message history roundtrip (#5557) — drives the released-tier PATCH
- agent-framework-orchestrations: [BREAKING] standardize orchestration
terminal outputs as AgentResponse (#5301)
- agent-framework-core, agent-framework-declarative: preserve Workflow.run()
shared state across calls, accept list[Message] in declarative start
executor, and coerce Enum values when serializing PowerFx symbols (#5531)
- agent-framework-foundry-hosting: add hosted Durable Workflow support
(#5531)
- agent-framework-azure-contentunderstanding: new alpha package — Azure AI
Content Understanding context provider (#4829)
- dependencies: workspace package dependency refresh (#5555)
Per lockstep convention, all 21 beta packages stamp 1.0.0b260429 and all 4
alpha packages (now including the new contentunderstanding) stamp
1.0.0a260429. Date stamp reflects 2026-04-29 Pacific. Every non-core package
floor on agent-framework-core is raised to >=1.2.2; the new
contentunderstanding package's stale >=1.0.0 floor is brought into line.
Two follow-on fixes bundled to keep validate-dependency-bounds-test green
at lowest-direct resolution:
- Bump agent-framework-azure-contentunderstanding's azure-ai-content
understanding lower bound from >=1.0.0 to >=1.0.1 (1.0.0 ships without
proper typing — pyright reports 65 unknown-type errors)
- Add pyright ignore comments to core/foundry/__init__.pyi for the new
alpha package's type-stub imports, since alpha packages are not in
core's [all] extra and therefore aren't installed at lowest-direct
* Python: add #5552 to 1.2.2 CHANGELOG
Add the streaming-span observability fix to the Fixed section. PR is on
upstream/main but not yet pulled into origin/main; the code itself will
land via the PR merge.
* Python: address PR #5561 review feedback on dependency bounds
Two packaging fixes flagged in review:
1. agent-framework-azure-contentunderstanding: add agent-framework-foundry
as a runtime dependency. The package's README directs users to
`pip install agent-framework-azure-contentunderstanding --pre` and the
basic example imports `FoundryChatClient` from `agent_framework.foundry`,
so the documented install path was failing with ImportError. Pulling
agent-framework-foundry into deps makes the advertised entry path
self-contained.
2. agent-framework-foundry: bump agent-framework-openai lower bound from
>=1.1.0 to >=1.2.2,<2. Foundry imports private modules from
agent_framework_openai (`_chat_client.py:22`, `_agent.py:34`), so
resolvers were free to pair foundry==1.2.2 with older OpenAI versions
that lack this release's coordinated Responses/history fix. Lockstep the
floor with the released cohort to prevent mismatched installs.
Both changes pass `validate-dependency-bounds-test` lower + upper at
their respective packages.
* Python: bump package versions for 1.2.1 release
PATCH bump (1.2.0 -> 1.2.1) for the released cohort. The release window
covers two PRs, no new public APIs:
- agent-framework-core: prevent inner_exception from being lost in
AgentFrameworkException (#5167)
- samples: add requirements.txt and .env.example to the a2a/ hosting
sample for pip-based setup (#5510)
Per lockstep convention, all 21 beta packages stamp 1.0.0b260428 and all
3 alpha packages stamp 1.0.0a260428, regardless of per-package code
churn. Every non-core package floor on agent-framework-core is raised to
>=1.2.1 to keep cohort signaling consistent. Date stamp reflects the
local (Asia) cut date 2026-04-28.
* Python: silence pyright unknown-type warnings in hosted-env detection
`azure.ai.agentserver.core` is probed at runtime via `importlib.util.find_spec`
and is not a declared dependency. The existing `# pyright: ignore[reportMissingImports]`
suppresses the missing-import warning, but at `lowest-direct` resolution pyright
still reports the imported symbol (`AgentConfig`) and its members (`from_env`,
`is_hosted`) as unknown, breaking `validate-dependency-bounds-test` for
`packages/core`.
Extend the existing ignore to cover `reportUnknownVariableType` on the import
and `reportUnknownMemberType` on the call site so the bounds check returns to
green. Behavior is unchanged.
Latent since #5455 (shipped in 1.2.0).
* Python: raise agent-framework-gemini lower bound to google-genai>=1.65.0
The Gemini chat client references several `google.genai.types` symbols
(`FileSearch`, `ThinkingLevel`, `SearchTypes`, `McpServer`,
`StreamableHttpTransport`, plus call-site keyword args `mcp_servers` and
`search_types`) that are not present at the lower bound of `google-genai>=1.0.0`.
At `lowest-direct` resolution this caused `validate-dependency-bounds-test` to
fail for `packages/gemini` with eleven `reportAttributeAccessIssue` /
`reportUnknownVariableType` errors.
Walking the upstream `google.genai.types` API:
- `GoogleMaps`, `AuthConfig`: present from 1.40.0
- `FileSearch`: introduced in 1.49.0
- `ThinkingLevel`: introduced in 1.55.0
- `SearchTypes`, `McpServer`, `StreamableHttpTransport`: introduced in 1.65.0
Bump the lower bound to 1.65.0 — the minimum version that exposes every symbol
the package actually uses. Keep the `<2.0.0` upper cap unchanged. With this
bump `validate-dependency-bounds-test` passes for both lower and upper
resolution scenarios across all 27 workspace packages.
Latent since #4847 (Gemini package introduction in 1.1.0); aggravated by
subsequent feature additions that pulled in newer `types.*` symbols.
* Python: add dependabot bumps to 1.2.1 CHANGELOG
Catalog the 15 dependabot dependency updates that merged on `upstream/main`
between python-1.2.0 and the 1.2.1 cut window under a new Changed section:
- Workspace dev/runtime deps: `rich`, `prek`, `python-multipart`, `pyasn1`,
`pytest` (ag-ui, devui, lab), `uv` (lab)
- Frontend deps: `vite` (devui, chatkit), `postcss` (devui, chatkit, handoff),
`picomatch` (devui, handoff)
CHANGELOG-only — no source or pyproject.toml changes. PRs themselves merged
upstream independently of this release branch and will be brought in via the
PR merge.
* Bump Python package versions for 1.2.0 release
Released tier bumps 1.1.1 -> 1.2.0 (core, openai, foundry, root) to
reflect additive public APIs landed since 1.1.0: functional workflow API
(#4238) and FunctionTool SKIP_PARSING sentinel (#5424). All beta packages
stamped 1.0.0b260424, alpha packages 1.0.0a260424. All 26 non-core
agent-framework-core floors raised to >=1.2.0,<2. CHANGELOG consolidates
the never-tagged 1.1.1 entries with the post-merge additions into [1.2.0].
* Update CHANGELOG footer links for 1.2.0
Advance [Unreleased] comparison base from python-1.1.0 to python-1.2.0
and add a [1.2.0] reference link comparing python-1.1.0...python-1.2.0
so the heading links resolve correctly.
* Fix CHANGELOG: restore [1.1.1] section and add proper [1.2.0]
Previous commit incorrectly renamed the [1.1.1] header to [1.2.0], which
wiped the historical 1.1.1 entries and wrongly attributed them to 1.2.0.
This restores [1.1.1] to its origin/main content and adds a new [1.2.0]
section above containing only the commits in python-1.1.1..HEAD:
- #4238 functional workflow API
- #5142 GitHub Copilot OpenTelemetry
- #2403 A2A bridge support
- #5070 oauth_consent_request events in Foundry clients
- #5447 FoundryAgent hosted agent sessions
- #5459 hosting server dependency upgrade + types
- #5389 AG-UI reasoning/multimodal parsing fix
- #5440 stop [TOOLBOXES] warning spam
- #5455 user agent prefix fix
Also corrects the [1.2.0] compare base to python-1.1.1 (not 1.1.0) and
adds the missing [1.1.1] reference link.
* Bump Python version for a release.
* Revert lockstep bumps on unchanged connectors
Per PR review: only connectors that changed (or whose published metadata
changed) should get new versions. Keeps released tier at 1.1.1, a2a/ag-ui
at 1.0.0b260422, foundry-hosting at 1.0.0a260422; reverts the 19 unchanged
betas and 2 unchanged alphas to 1.0.0b260421/1.0.0a260421. Reverts all 26
non-core agent-framework-core floors to >=1.1.0,<2 since no connector
actually depends on a 1.1.1 API or bug fix.
* Restore lockstep prerelease bumps and raise core floors to >=1.1.1
Reverses the lean-revert: all beta packages stamped 1.0.0b260423 and alpha
packages stamped 1.0.0a260423 (Asia date, matching release cut time). All
26 non-core packages raise agent-framework-core lower bound from >=1.1.0,<2
to >=1.1.1,<2 to signal the validated cohort for this release. CHANGELOG
date updated to 2026-04-23.
The local MCP server can't be used for hosted tools tests because
Anthropic's backend needs to reach the MCP URL from their infrastructure
(not localhost on the CI runner). Revert to learn.microsoft.com/api/mcp
but catch BadRequestError, InternalServerError, APIConnectionError, and
APITimeoutError and pytest.skip so upstream outages don't block the
merge queue.
* Python: use local MCP server for hosted tools test and broaden image assertion
The hosted tools integration test was hitting rate limits on the external
learn.microsoft.com MCP server, causing persistent failures that retries
couldn't recover from. Switch to the local MCP server already spun up in
CI via LOCAL_MCP_URL, skipping when the env var isn't set.
Also broaden the image description assertion to accept common synonyms
(cottage, mansion, villa, etc.) instead of just "house", since the model
legitimately uses varied vocabulary for the same image.
* Address review feedback: validate LOCAL_MCP_URL scheme and use word boundaries
- Skip hosted tools test when LOCAL_MCP_URL lacks http/https scheme,
matching the pattern used in test_mcp.py.
- Use regex word boundaries for image assertion to avoid false matches
like "villain" matching "villa".
* Bump Python version to 1.1.0 for a release
* Fix changelog
* 1.0.1 instead of 1.1.0
* Update CHANGELOG.md
* update version and changelog
* Bump lower bounds
* 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>
* [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>
* 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>
* 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>
* feat(python): allow @tool functions to return rich content (images, audio)
Add support for tool functions to return Content objects that the model can perceive natively. Closes#4272
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Anthropic logging + mypy fix
* Address PR review: fix MCP ordering, fold helper into from_function_result, fix Chat client
- Preserve original content order in MCP tool results instead of text-first
- Move _build_function_result logic into Content.from_function_result()
- Chat Completions: inject user message for rich items (API only supports string tool content)
- Update tests for ordering and new from_function_result behavior
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Use native Responses API multi-part output, warn+omit for Chat client
- Responses client: put rich items directly in function_call_output's
output field as list (native API support) instead of user message injection
- Chat client: warn and omit rich items (API doesn't support multi-part
tool results), matching Ollama/Bedrock pattern
- Unify test image: use sample_image.jpg across all integration tests
- Add Azure OpenAI Responses integration test
- Assert model describes house image to verify perception
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix lint: remove print statement, wrap long line
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback: bug fixes, single-pass MCP, unit tests
- Add isinstance guard in from_function_result for non-Content lists
- Fix Anthropic empty tool_content fallback to string result
- Fix Content(type='text', text=None) edge case in parse_result
- Rewrite MCP _parse_tool_result_from_mcp as single-pass (no index counters)
- Add Anthropic unit tests: data image, uri image, unsupported media, all-unsupported
- Add OpenAI Chat unit test: rich items warning and omission
- Add OpenAI Responses unit tests: function_result with/without items
- Add test_types tests: only-rich-items list, non-Content list fallback
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix pyright errors: add type ignore comments for Any list iteration
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix mypy/pyright: ensure ToolExecutionException receives str
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix lint: remove duplicate test_prepare_options_excludes_conversation_id
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* refactor: unify all tool results into Content items
* addressed copilot comments
* pyright fix
* small fix
* comments
* fix: address Copilot review - warnings, blob safety, dedup
- Add warning logs when rich content is dropped in Claude agent and
MCP server handlers (matching Chat/Bedrock/Ollama pattern)
- Defensive blob URI construction: wrap plain base64 in data: prefix
- Simplify Chat client _prepare_content_for_openai to use content.result
- Simplify Responses client text-only path, remove redundant nesting
- Add test for plain base64 blob without data: prefix
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix token double-counting in compaction and address review comments
- Exclude items from _serialize_content() to prevent double-counting
tokens when items mirrors result in function_result content
- Add rich content warning in GitHub Copilot agent tool handler
- Replace raw Content debug log with concise item count/type summary
- Update stale test comments about FunctionTool.invoke return type
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* 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
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Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Added shell tool
* Fixed CI error
* Add ShellTool support for OpenAI and Anthropic providers
- Add shell_tool_call, shell_tool_result, and shell_command_output content types
- Add ShellTool class and shell_tool decorator to core
- Add get_hosted_shell_tool() to OpenAI Responses client
- Handle shell_call and shell_call_output parsing in OpenAI (sync and streaming)
- Map ShellTool to Anthropic bash tool API format
- Parse bash_code_execution_tool_result as shell_tool_result in Anthropic
- Add unit tests for all new functionality
- Add sample scripts for hosted and local shell execution
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Addressed comments
* Reverted ruff change
* Fixed tests
* Addressed comments
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Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* 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>
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Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* 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
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Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* 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>
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Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* 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
* 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
* 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
Yufeng HeandGitHub
Evan MattsonandGitHub
Tao ChenandGitHub
Eduard van ValkenburgandGitHub
Dmytro StrukandGitHub
