* Fix magentic manager warning
* Use typing_extensions.Sentinel for _MISSING sentinel value
Replace the bare object() sentinel with typing_extensions.Sentinel per
PEP 661 (now final). Sentinel provides a proper name and repr
('<_MISSING>') and is the idiomatic approach going forward.
Refs #4306
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: correct Sentinel type annotation for max_stall_count param (#6261)
Use int | Sentinel for max_stall_count parameter type annotation instead
of int with cast(Any, _MISSING) to properly express that the parameter
can hold either an int or the _MISSING sentinel value. This fixes the
pyright reportUnnecessaryComparison errors caused by the types int and
Sentinel having no overlap.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Rename _MISSING sentinel to UNSET in orchestrations
The sentinel is user-visible as a default in public init signatures, so
use UNSET (no leading underscore) instead of the private _MISSING name.
Drop the now-unnecessary reportPrivateUsage ignores on the UNSET imports.
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>
* feat(bedrock): add structured output support via Converse API (Fixes#5966)
* fix(bedrock): improve unsupported model exception handling and schema parsing
* refactor(bedrock): use generic traversal for strict schema enforcement
* address Copilot review comments on structured output
* refine bedrock structured output: guard additionalProperties, TypeError check, docs + test
* fix(bedrock): widen response_format to Mapping and add missing test coverage
* 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.
* Remove Foundry toolbox helpers; standardize on MCP for toolbox consumption
- Remove RawFoundryChatClient.get_toolbox() and its fetch_toolbox import
- Remove fetch_toolbox, select_toolbox_tools, get_toolbox_tool_name,
get_toolbox_tool_type, FoundryHostedToolType, ToolboxToolSelectionInput
from agent_framework_foundry._tools
- Remove ExperimentalFeature.TOOLBOXES from _feature_stage.py (no consumers)
- Drop toolbox re-exports from agent_framework_foundry/__init__.py and
agent_framework.foundry namespace
- Update _sanitize_foundry_response_tool docstring to remove toolbox framing;
sanitization logic itself is unchanged
- Update _agent.py docstring: 'toolbox-fetched MCP' → 'hosted MCP'
- Delete tests/test_toolbox.py (all tests covered removed helpers)
- Update test_foundry_chat_client.py: rename/redoc tests that mentioned
toolbox but test sanitization that remains
- Delete foundry_chat_client_with_toolbox.py (bespoke toolbox API sample)
- Delete foundry_toolbox_context_provider.py (relied on select_toolbox_tools)
- Rename foundry_chat_client_with_toolbox_mcp.py →
foundry_chat_client_with_toolbox.py (canonical MCP pattern)
- Rewrite 04_foundry_toolbox/main.py to use MCPStreamableHTTPTool
- Update provider/README, context_providers/README, 04_foundry_toolbox/README
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(samples): update 06_files sample to consume toolbox via MCP (#5670)
Replace removed get_toolbox/select_toolbox_tools APIs with
MCPStreamableHTTPTool, using allowed_tools=["code_interpreter"] to
select only the code interpreter from the toolbox endpoint.
Update .env.example and README to use FOUNDRY_TOOLBOX_ENDPOINT
instead of TOOLBOX_NAME.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(foundry): remove non-existent toolbox helper APIs from README (#5670)
Remove the 'fetch, optionally filter, and pass tools directly' pattern
from the FoundryChatClient toolbox documentation, as select_toolbox_tools
and get_toolbox were removed. Only the MCP endpoint pattern is documented.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(foundry): remove residual toolbox docstring references and reproduction report
Remove REPRODUCTION_REPORT.md (workflow artifact that should not be committed),
and update two remaining docstring references that still said 'toolbox reads'
/'toolbox definition' after the toolbox helpers were removed.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Remove bespoke Foundry toolbox helpers; standardize on MCP for toolbox consumption
Fixes#5670
* fix(#5670): resolve toolbox endpoint from TOOLBOX_NAME fallback; add namespace regression tests
- Add _resolve_toolbox_endpoint() helper in 04_foundry_toolbox/main.py and
06_files/main.py that prefers FOUNDRY_TOOLBOX_ENDPOINT but falls back to
deriving the MCP URL from FOUNDRY_PROJECT_ENDPOINT + TOOLBOX_NAME — fixing
the startup KeyError when agents are deployed via azd provision (which injects
TOOLBOX_NAME, not FOUNDRY_TOOLBOX_ENDPOINT).
- Update 04_foundry_toolbox/.env.example to use FOUNDRY_TOOLBOX_ENDPOINT
(consistent with 06_files).
- Add TOOLBOX_NAME env var to 06_files/agent.yaml so deployed agents have it
available for the fallback derivation.
- Update both READMEs to document the two ways to supply the toolbox endpoint.
- Add test_foundry_namespace_no_longer_exposes_toolbox_helpers() with negative
assertions for FoundryHostedToolType, get_toolbox_tool_name,
get_toolbox_tool_type, and select_toolbox_tools — guarding against accidental
re-introduction of removed symbols.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(samples): fail fast on empty FOUNDRY_TOOLBOX_ENDPOINT; add unit tests
Addresses review feedback for #5670:
- In _resolve_toolbox_endpoint() (04_foundry_toolbox/main.py and
06_files/main.py) change the walrus-operator check from a truthy
test to an explicit 'is not None' guard. An explicitly set empty
string now raises ValueError immediately with a clear message
instead of silently falling through to the fallback URL
construction.
- Add tests/samples/hosting/test_toolbox_endpoint.py covering both
sample modules:
(a) FOUNDRY_TOOLBOX_ENDPOINT set → returned as-is
(b) FOUNDRY_TOOLBOX_ENDPOINT set to empty string → ValueError
(c) fallback constructs URL from FOUNDRY_PROJECT_ENDPOINT + TOOLBOX_NAME,
stripping trailing slashes
(d) neither variable group set → KeyError
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback: remove extraneous test and docstring content
- Remove test_foundry_namespace_no_longer_exposes_toolbox_helpers (no longer warranted)
- Remove docstring from _agent.py _prepare_tools_for_openai (extraneous)
- Trim _chat_client.py _prepare_tools_for_openai docstring to one-liner (toolbox references no longer relevant)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: remove remaining extraneous docstring from RawFoundryChatClient._prepare_tools_for_openai
Address review comment on PR #5671: reviewer noted the description
isn't warranted now that toolbox helpers have been removed. Matches
the pattern in RawFoundryAgentChatClient which has no docstring.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(bedrock): don't send toolChoice when no tools are configured
BedrockChatClient was sending toolConfig.toolChoice even when no tools
were configured (tools=None). AWS Bedrock requires toolConfig.tools to
be present whenever toolChoice is specified, causing a 400 validation
error.
Only set toolChoice when tool_config has a 'tools' key present.
Fixes#5165
Signed-off-by: bahtya <bahtyar153@qq.com>
* test: add tests for toolChoice without tools
- test_prepare_options_tool_choice_auto_without_tools_omits_tool_config
- test_prepare_options_tool_choice_required_without_tools_omits_tool_config
Verifies that toolConfig is omitted when tool_choice is set but no
tools are provided, preventing ParamValidationError from Bedrock.
* fix: address maintainer feedback — remove stray test file, raise ValueError for required without tools
1. Remove test_addition.py — stray duplicate of tests already in
python/packages/bedrock/tests/test_bedrock_client.py, missing all
necessary imports and would fail with NameError.
2. Change tool_choice='required' handling to raise ValueError when no
tools are configured instead of silently falling through. Using
'required' without tools is a logical contradiction — the model
must invoke a tool but none exist — so surfacing this as a
ValueError helps callers catch the misconfiguration early.
3. Update the corresponding test to expect ValueError instead of
silently omitted toolConfig.
---------
Signed-off-by: bahtya <bahtyar153@qq.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.
* 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>
Eduard van Valkenburg
·
2026-04-01 19:00:18 +00:00
* [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>
Eduard van Valkenburg
·
2026-03-20 00:43:37 +00:00
* 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>
Eduard van Valkenburg
·
2026-03-18 18:39:11 +00:00
* 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>
Eduard van Valkenburg
·
2026-03-13 08:58:32 +00:00
* 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>
Bedrock's Converse API only accepts "auto", "any", or "tool" as valid
toolChoice keys. The previous code mapped tool_choice="none" to
{"none": {}}, which causes a botocore.exceptions.ParamValidationError.
When tool_choice="none" (set by FunctionInvocationLayer after exhausting
max iterations), the fix now omits toolConfig entirely so the model
won't attempt tool calls.
Added tests for tool_choice="none", "auto", and "required" modes.
Fixes#4529
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@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
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Eduard van Valkenburg
·
2026-03-05 15:32:24 +00:00
* 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>
Eduard van Valkenburg
·
2026-02-25 17:45:08 +00:00
* 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
Eduard van Valkenburg
·
2026-02-12 13:49:42 +00:00
* 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
Eduard van Valkenburg
·
2026-02-12 08:51:20 +00:00
* 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
Eduard van Valkenburg
·
2026-02-09 17:51:01 +00:00
* 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>
Eduard van Valkenburg
·
2026-02-05 20:09:58 +00:00
* 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
Eduard van Valkenburg
·
2026-02-04 10:13:23 +00:00
Giles Odigwe ·
Evan Mattson ·
Thota Sai Karthik ·
bahtyar ·
Tao Chen ·
Eduard van Valkenburg ·
L. Elaine Dazzio ·
Dmytro Struk ·