* fix: use getattr for non-OpenAI provider response compatibility
Fixes#6234Fixes#6235
Use getattr with None fallback for system_fingerprint and output
attributes to prevent AttributeError when non-OpenAI providers
return response objects without these fields.
* fix: use typed variable for response output to satisfy pyright
Fixes#6235
Use getattr with None fallback for the output attribute, and assign
to a typed list variable before the match statement to help pyright
narrow the response item types correctly.
* fix: rename response_outputs to avoid name collision with case-block variable
Fixes#6235
Rename outputs to response_outputs on line 1974 to avoid mypy error
about conflicting variable names in the match statement's case blocks.
Also use list[Any] for explicit generic type annotation.
* fix: use cast(list[Any]) for response output to satisfy pyright
Fixes#6235
The getattr() call returns Unknown type which pyright cannot narrow
in the match statement. Use an explicit cast to list[Any].
* fix: use hasattr guard instead of getattr for response.output
Fixes#6235
Using hasattr(response, 'output') and then accessing response.output
directly gives pyright enough type information to verify the match
statement exhaustiveness. This avoids the cast(list[Any]) approach
which pyright still flagged as partially unknown.
* fix: use ternary operator for response_outputs assignment
Replace if-else block with ternary expression to satisfy ruff SIM108 lint rule.
This fixes the Package Checks (3.11) CI failure.
* fix: use ternary with cast for ruff SIM108 and pyright type safety
Replace if-else block with ternary expression using cast(list[Any], ...)
to satisfy:
- ruff SIM108 (use ternary instead of if-else)
- ruff E501 (line length < 120)
- pyright type narrowing (cast preserves type info lost in ternary)
All local checks pass: ruff check, ruff format, pyright, 298 tests.
* fix: replace hasattr+cast with try/except to preserve pyright types
---------
Co-authored-by: Tao Chen <taochen@microsoft.com>
* Python: fix ConnectTimeout on multi-turn FoundryAgent conversations (#6241)
Expose a `timeout` parameter on `RawFoundryAgentChatClient`,
`_FoundryAgentChatClient`, `RawFoundryAgent`, `FoundryAgent`, and
`RawOpenAIChatClient` so callers can override the HTTP timeout used by
the underlying AsyncOpenAI client.
Root cause: `RawFoundryAgentChatClient.__init__` called
`project_client.get_openai_client()` without configuring any timeout,
inheriting the OpenAI SDK default of `httpx.Timeout(connect=5.0)`.
When connections are recycled between turns under load, the 5 s connect
timeout fires and surfaces as `openai.APITimeoutError`.
Fix:
- `load_openai_service_settings` (`_shared.py`): accept `timeout` and
include it in `client_args` for all three `AsyncOpenAI`/
`AsyncAzureOpenAI` construction paths.
- `RawOpenAIChatClient.__init__` (`_chat_client.py`): accept `timeout`
and forward to `load_openai_service_settings`.
- `RawFoundryAgentChatClient.__init__` (`_agent.py`): accept `timeout`
and set `openai_client.timeout = timeout` on the client returned by
`get_openai_client()` before passing it to the base class.
- `_FoundryAgentChatClient`, `RawFoundryAgent`, `FoundryAgent`: accept
and propagate `timeout` through the construction chain.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add timeout parameter to FoundryAgent and RawOpenAIChatClient
Expose a timeout parameter on RawFoundryAgentChatClient,
_FoundryAgentChatClient, RawFoundryAgent, FoundryAgent, and
RawOpenAIChatClient. When provided, the value is applied to the
underlying AsyncOpenAI client so that connect timeouts under load
or after connection recycling can be tuned by callers.
Previously, get_openai_client() was called without any timeout
override, so the SDK default of httpx.Timeout(connect=5.0) was
inherited and could fire on multi-turn conversations where the
underlying connection is recycled between turns.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Add `timeout` parameter to `FoundryAgent` to fix `ConnectTimeout` on multi-turn conversations
Fixes#6241
* fix(foundry): use with_options to avoid mutating shared OpenAI client timeout (#6241)
Replace direct assignment with
in
RawFoundryAgentChatClient.__init__.
The Azure AI Projects SDK caches and returns a shared AsyncOpenAI client
per AIProjectClient. Mutating its .timeout attribute leaked the override
to all other code paths sharing that client (other agents, user code).
with_options() returns a new client instance with the override applied,
leaving the original shared client untouched.
Update tests to assert with_options is called with the correct timeout
and that the original shared client's timeout attribute is not mutated.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* test(foundry): assert with_options return value flows to instance.client (#6241)
The four timeout propagation tests verified that with_options was called
but did not confirm that the returned (timeout-configured) client was
actually stored on the instance. A silent discard of the return value
would have left the tests green while the timeout had no effect.
Each test now captures the constructed instance and asserts:
assert <instance>.client is openai_client_mock.with_options.return_value
Affected tests:
- test_raw_foundry_agent_chat_client_init_applies_timeout_to_openai_client
- test_raw_foundry_agent_chat_client_init_applies_timeout_with_preview_enabled
- test_foundry_agent_chat_client_init_propagates_timeout
- test_foundry_agent_init_propagates_timeout_to_openai_client
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
`OpenAIChatClient._inner_get_response()` reads `.headers` on the raw streaming
response returned by `client.responses.with_raw_response.create(stream=True)`
(and its three sibling call sites - retrieve-streaming, non-streaming create
and background retrieve) to surface the `x-ms-served-model` Azure header,
introduced in #5910.
When `azure-ai-projects>=2.1.0` experimental GenAI tracing is enabled
(`AZURE_EXPERIMENTAL_ENABLE_GENAI_TRACING=true`), the instrumentor wraps the
raw streaming response in an inline `AsyncStreamWrapper` that exposes
`.response` but not `.headers`. Reading `raw_create_response.headers` then
raises `AttributeError: 'AsyncStreamWrapper' object has no attribute 'headers'`,
which `FoundryChatClient` rethrows as a `ChatClientException` and breaks every
streaming call (workflows and free chat).
Fix: read the header dict via `getattr(raw_response, "headers", None)` at all
four call sites. `_extract_served_model()` already short-circuits on `None`,
so the served-model surfacing degrades gracefully (model stays the deployment
alias) instead of crashing when the response is wrapped by an instrumentor
that does not proxy `.headers`.
Regression test added:
`test_streaming_response_without_headers_attribute_does_not_crash`
simulates a stream wrapper that raises `AttributeError` on `.headers` and
asserts the stream still completes with the deployment alias as `update.model`.
Fixes#6028
Co-authored-by: Emilien Mottet <emilien.mottet@michelin.com>
* Record actual served model as response model for Azure OpenAI
* Formatting
* Fix tests
* Fix pipeline error
* Comments
* Address review: surface served model via ChatResponse.model
Apply blocking review feedback from PR #5910:
- Use ChatResponse.model / ChatResponseUpdate.model as the source of truth
for the Azure x-ms-served-model header value, instead of stashing it in
additional_properties and overriding it again in observability.
Observability already reads response.model; the chat client now overwrites
it post-parse when the served-model header is present. Empirically the
Azure Responses API returns the deployment alias in body.model and the
actual snapshot (e.g. gpt-5-nano-2025-08-07) in this header.
- Move the AZURE_OPENAI_SERVED_MODEL_HEADER constant out of observability.py
and into RawOpenAIChatClient (as the SERVED_MODEL_HEADER ClassVar). The
header is Azure-OpenAI-Responses-API-specific so observability does not
need to know about it.
- Revert the streaming text_format path to client.responses.stream(...) and
drop the _pydantic_model_to_text_format_param helper. That helper imported
from openai.lib._parsing._responses (a private SDK path) and the swap to
responses.create(stream=True) dropped client-side output_parsed for
structured-output streaming. The streaming-with-text_format path is the
only one that does not surface the served-model header - documented inline.
- Wrap the raw streaming responses in async with so the underlying socket
closes deterministically (continuation_token retrieve + create paths).
- Fix the empty-string / whitespace-only header at the source by stripping
in _extract_served_model and returning None when nothing remains.
- Revert unrelated formatting-only churn in _skills.py and test_mcp.py.
- Update unit tests to assert against chat_response.model / update.model
and add an aggregated streaming assertion plus a pin that the
streaming-with-text_format path does not get the header.
Verified end-to-end against Azure OpenAI Responses API: deployment alias
gpt-5-nano now reports gpt-5-nano-2025-08-07 as ChatResponse.model in both
the non-streaming and streaming paths.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: preserve streaming structured output finalization
Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639
Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
* refactor: name streaming response finalizer
Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639
Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
* fix: capture streaming response format after prepare
Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639
Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
* refactor: clarify streaming response format capture
Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639
Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
* test: use public API for streaming structured output
Agent-Logs-Url: https://github.com/microsoft/agent-framework/sessions/f62076ef-558d-49e8-8fe2-f38d527c9639
Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
* Inline the served-model header override at its two call sites
The `_apply_served_model_header` helper was a 1-line wrapper around
`_extract_served_model`. Inlining the `if served_model is not None: ...`
matches the pattern already used in the streaming paths and folds the
explanatory docstring onto `_extract_served_model` (which is now the
single place that knows about the header).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: eavanvalkenburg <13749212+eavanvalkenburg@users.noreply.github.com>
Fixes microsoft/agent-framework#3295. When the OpenAI Responses chat
client sends a request that carries previous_response_id / conversation_id
/ conversation, the server already has the prior turn's response items
and rejects duplicates with "Duplicate item found with id fc_xxx". The
chat client was re-sending them inline whenever the input messages still
carried the items in additional_properties (workflow replay, history
providers, etc.), which broke any tool-using agent with persistent
history.
Decisions:
- Single chokepoint: _prepare_message_for_openai. When the resulting
request uses service-side storage, drop function_call, reasoning,
approval-request/response, and local-shell-call items from the wire
input. Keep function_result with its call_id; the server pairs it to
the prior function_call via that key.
- function_result is preserved unconditionally except for the local-shell
variant, which carries its own server-issued item id.
- No public API change. Wire format change is subtractive and only on
requests that would otherwise 400.
- Re-pointed the strict-xfail in test_full_conversation.py from #4047 to
#3295. Kept xfail because the test asserts executor-level session-id
clearing, which is the defense-in-depth half tracked by 3295-03; this
slice closes the wire-level half.
Files:
- python/packages/openai/agent_framework_openai/_chat_client.py: strip
rule applied alongside the existing reasoning-item branch.
- python/packages/openai/tests/openai/test_openai_chat_client.py: four
new tests pin the contract (function_call, approval, local-shell-call
stripped under storage; everything kept without storage). Updated
pre-existing tests that exercised the storage-on path to either pass
request_uses_service_side_storage=False explicitly or assert the new
strip behavior.
- python/packages/foundry/tests/foundry/test_foundry_chat_client.py:
same explicit storage-off opt-in for the inherited test.
- python/packages/core/tests/workflow/test_full_conversation.py:
re-pointed xfail reason to #3295 and the executor-level follow-up.
Notes for next iteration:
- 3295-01 (HITL wire-format validation against live OpenAI/Foundry) was
not run; it requires the user's API credentials. The PRD design is
locked but the empirical confirmation is still pending. If script 3
fails on either provider, this slice may need to be revisited.
- 3295-03 (clear service_session_id in AgentExecutor on full-history
replay) remains open. After it lands the xfail in
test_full_conversation.py can be removed.
- pytest was not run in this iteration because uv-based pytest commands
required interactive approval. Validation rests on careful reading;
next iteration should run the openai + core test suites.
Fixes#5394.
When `background=True` is combined with local function tools,
`FunctionInvocationLayer` calls `_inner_get_response(options=mutable_options)`
repeatedly with the same dict reference across loop iterations. Once the
first poll retrieves a completed background response, `continuation_token`
stays in `mutable_options`, so every subsequent iteration takes the
`continuation_token is not None` branch and `GET`s the same completed
response instead of `POST`ing the tool results. The loop exits after
`max_iterations` with empty text and the model never sees any tool output.
After the retrieve, if the returned `ChatResponse.continuation_token` is
`None` (the background response is no longer in progress), pop
`continuation_token` and `background` from the shared options dict in
place. The next loop iteration then falls through to the normal
`responses.create`/`parse` path and posts tool results.
The diagnosis and a verified runtime monkeypatch are in the issue; this
is the same fix moved in-tree.
Co-authored-by: Yufeng He <40085740+universeplayer@users.noreply.github.com>
* Python: Support GPT-5 verbosity option and restore Foundry agent_reference
Adds verbosity as a typed Literal["low","medium","high"] field on
OpenAIChatOptions (Responses API) and OpenAIChatCompletionOptions (Chat
Completions API), set in the same way as the existing reasoning options.
For the Responses API, top-level verbosity is translated to the nested
text.verbosity shape the OpenAI service expects. The same field flows
through to FoundryChatClient via the existing FoundryChatOptions alias.
Also fixes#5582: PR #5447 removed the agent_reference injection from
RawFoundryAgentChatClient._prepare_options, so first-turn calls against
a Foundry Prompt Agent went out without model and without agent_reference
and were rejected by the Responses API with "Missing required parameter:
'model'". Restores the injection on the non-preview path
(allow_preview=False) and adds a guard test that asserts the preview
path does not inject agent_reference, since the preview SDK injects it
via project_client.get_openai_client(agent_name=...).
Closes#5516Closes#5582
* Python: Address Copilot review on PR #5619
- Foundry verbosity sample docstring: replace the misleading "set deployment
name on model=" instruction with the actual env-var pattern the sample relies
on (FOUNDRY_PROJECT_ENDPOINT and FOUNDRY_MODEL).
- _build_agent_reference docstring: clarify the helper is used for both
Prompt Agents and HostedAgents on the non-preview path.
- Add a Responses API test that locks in the documented precedence rule:
when both top-level verbosity and text["verbosity"] are supplied, the
top-level value wins.
* Python: Drop redundant Foundry verbosity sample and list OpenAI sample in README
- Remove samples/02-agents/providers/foundry/foundry_chat_client_verbosity.py
per review feedback. The verbosity functionality is identical across the
OpenAI and Foundry clients (FoundryChatOptions is an alias of
OpenAIChatOptions), so a single sample on the OpenAI side is sufficient.
- Add the new client_verbosity.py entry to the OpenAI samples README.
* Python: Fix hosted MCP replay producing orphan function_call_output
Resolves part of #5546. After a turn ran a hosted MCP / Foundry-toolbox-MCP
tool, the next turn's replayed input array carried a function_call_output
with an mcp_* call_id and no matching function_call, and the Responses API
returned a 400.
Two layers covered here:
* Chat-client serialize layer (packages/openai): adds mcp_server_tool_call
and mcp_server_tool_result cases to _prepare_message_for_openai and
_prepare_content_for_openai. Pairs are coalesced via a post-pass into a
single mcp_call input item carrying both arguments and output. Orphan
results are dropped (debug-logged) rather than serialized as orphan
function_call_output, which is what the Responses API rejected.
* Host read layer (packages/foundry_hosting): _item_to_message and
_output_item_to_message now route custom_tool_call_output whose
call_id.startswith("mcp_") to Content.from_mcp_server_tool_result.
Non-mcp_ call_ids continue to produce Content.from_function_result.
Symmetric with the host write-side choice for hosted-MCP results.
Two further fixes (agentserver SDK additions, host write-side single-item
emission) remain tracked on the issue and depend on an SDK release.
* Python: Fix pyright unknown-type in _stringify_mcp_output
cast(Sequence[Any], output) after the isinstance check so pyright stops
flagging the loop variable as unknown. Also normalizes a couple of
em-dashes in docstrings I introduced in the prior commit.
* Python: Harden _stringify_mcp_output for dict-shaped MCP outputs
Address Copilot review on PR #5581. Today the helper falls back to
str() for any non-string, non-text-attribute entry, which produces
Python repr (single-quoted dicts) for the canonical MCP raw-JSON
text-content shape `{"type": "text", "text": "..."}` and any other
dict-shaped output.
Three small changes:
* List-entry path: prefer plain string entries, then `.text` attribute
(Content objects), then `entry["text"]` for Mapping entries in the
canonical MCP shape, then JSON-encode anything else.
* Final fallback: `json.dumps(output, default=str)` so Mappings and
scalars produce valid JSON rather than Python repr.
* Two new unit tests covering the dict-with-text shape and the
non-text-dict JSON fallback.
* Python: Suppress mypy redundant-cast on _stringify_mcp_output narrowing
The cast is needed by pyright (reportUnknownVariableType) but mypy
considers it redundant after the preceding isinstance narrowing.
Pyright's behavior is correct for the strict-mode reporting we run,
so keep the cast and silence mypy on the line.
* 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: Fix file_search citations breaking assistant history roundtrip
The Responses API rejects 'input_file' inside an assistant message, but the
SDK was emitting it whenever an assistant Message contained a hosted_file
content (which is what file_search citations become). Three coordinated fixes:
1. _prepare_content_for_openai now skips hosted_file for the assistant role
instead of mapping to input_file (which the API rejects there).
2. The streaming response.output_text.annotation.added handler attaches
file_citation, container_file_citation, and file_path as annotations on
text content, matching the non-streaming path. Previously streaming
produced standalone HostedFileContent items that always tripped (1).
3. output_text serialization preserves Annotation objects on roundtrip via a
new _annotations_to_output_text helper instead of hardcoding 'annotations'
to []. file_search citations now survive multi-agent forwarding.
Closes#5556.
* Address PR review
- _annotations_to_output_text: fan out one entry per annotated_region for
url_citation/container_file_citation (Annotation.annotated_regions is a
Sequence; the API form carries one start/end per entry).
- Validate region span bounds are ints before emitting; skip otherwise.
- Add test for the file_path branch (annotation with file_id only).
- Add test verifying streamed citation events coalesce onto surrounding
text via _finalize_response so span indices reference the merged text,
not the empty-text streaming carrier.
* Fix streaming response losing created_at from response.completed event (#5347)
The streaming path in _parse_chunk_from_openai did not extract created_at
from the response.completed event, unlike the non-streaming path in
_parse_responses_response. This caused durabletask persistence warnings
when created_at was None.
Extract created_at in the response.completed case and pass it to the
returned ChatResponseUpdate.
Also fix pre-existing pyright errors for optional orjson import in sample
files.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix orjson import suppression to use pyright instead of mypy (#5347)
Replace `# type: ignore[import-not-found]` with
`# pyright: ignore[reportMissingImports]` on optional orjson imports
in conversation sample files, matching the repo's Pyright strict
configuration.
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 OpenAIEmbeddingClient with /openai/v1 endpoint (#5068)
When base_url ends with /openai/v1/ and a credential is provided,
load_openai_service_settings was creating an AsyncAzureOpenAI client.
The Azure SDK rewrites deployment-based endpoints (including /embeddings)
by inserting /deployments/{model}/ into the URL, producing 404s on the
OpenAI-compatible /openai/v1 endpoint.
Use AsyncOpenAI instead of AsyncAzureOpenAI when the resolved base_url
targets /openai/v1, converting the Azure token provider to an async
api_key callable. The responses_mode path is unaffected because the
Responses API (/responses) is not in the SDK's rewrite list.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Fix OpenAIEmbeddingClient to use AsyncOpenAI for /openai/v1 endpoints
Fixes#5068
* Address review feedback: improve test coverage and remove unrelated changes
- Revert unrelated formatting change in test_a2a_agent.py
- Fix test_init_with_openai_v1_base_url_and_api_key_uses_openai_client to
exercise the Azure settings path (via AZURE_OPENAI_BASE_URL env var)
instead of the plain OpenAI path, covering the elif api_key branch
- Add _ensure_async_token_provider unit tests for both sync and async
token providers
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #5068: Python: [Bug]: `OpenAIEmbeddingClient` does not work with `/openai/v1` endpoint
---------
Co-authored-by: MAF Dashboard Bot <maf-dashboard-bot@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
* Fix url_citation annotations dropped in streaming (#5029)
Add url_citation branch to the streaming annotation handler in
_parse_chunk_from_openai, mirroring the existing non-streaming path.
The handler creates an Annotation with type='citation', title, url,
and annotated_regions (TextSpanRegion), wrapped in Content.from_text.
Update test_streaming_annotation_added_with_unknown_type to use a
truly unknown type, and add new tests for url_citation (with and
without url).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #5029: Python: [Bug]: url_citation annotations silently dropped in Foundry streaming (SharePoint grounding citations lost)
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
* Fix reasoning text done events duplicating streamed delta content (#5157)
The OpenAI Responses API sends both reasoning_text.delta (incremental
chunks) and reasoning_text.done (full accumulated text) events. The
chat client was emitting Content for both, causing ag-ui to append the
full done text onto already-accumulated delta text, producing
duplicated reasoning output.
Stop emitting Content for reasoning_text.done and
reasoning_summary_text.done events, matching how output_text.done is
already handled (not emitted). The deltas contain all the content;
the done event is redundant.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix(openai): emit reasoning done content as fallback when no deltas observed (#5157)
Address PR review feedback:
- Track item_ids that received reasoning deltas via seen_reasoning_delta_item_ids set
- Emit content from done events only when no deltas were received for the
item_id, preventing silent content loss on stream resumption
- Add comment documenting code_interpreter done event asymmetry
- Replace redundant ag-ui test with deduplication-focused test
- Add integration test for delta+done sequence in OpenAI chat client tests
- Add fallback path tests for done events without preceding deltas
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #5157: Python: [Bug]: "type": "response.reasoning_text.delta" and "response.reasoning_text.done" both get exposed as "text_reasoning"
* Fix AG-UI reasoning streaming to use proper Start/End pattern (#5157)
_emit_text_reasoning now follows the same streaming pattern as _emit_text:
- Emits ReasoningStartEvent/ReasoningMessageStartEvent only on the first
delta for a given message_id
- Emits only ReasoningMessageContentEvent for subsequent deltas
- Defers ReasoningMessageEndEvent/ReasoningEndEvent until
_close_reasoning_block is called (on content type switch or end-of-run)
This produces the correct protocol pattern:
ReasoningStartEvent
ReasoningMessageStartEvent
ReasoningMessageContentEvent(delta1)
ReasoningMessageContentEvent(delta2)
ReasoningMessageEndEvent
ReasoningEndEvent
Instead of wrapping every delta in a full Start→End sequence.
Backward compatibility is preserved: calling _emit_text_reasoning without
a flow argument still produces the full sequence per call.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix import ordering lint error in AG-UI test file (#5157)
Move inline import of TextMessageContentEvent to the top-level import
block and ensure alphabetical ordering to satisfy ruff I001 rule.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix mypy error: rename loop variable to avoid type conflict with WorkflowEvent
The 'event' variable was already typed as WorkflowEvent[Any] from the
async for loop at line 590. Reusing it in the _close_reasoning_block
loop (which returns list[BaseEvent]) caused an incompatible assignment
error. Renamed to 'reasoning_evt' to avoid the conflict.
Fixes#5162
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #5157: review comment fixes
* narrow test result reporting to explicit pytest JUnit XML
* Fix test args
* Fix pytest-results-action in merge workflow and remove committed test artifacts
Apply the same JUnit XML fix from python-tests.yml to python-merge-tests.yml:
add --junitxml=pytest.xml to all test commands and narrow the results action
path from ./python/**.xml to ./python/pytest.xml. Also remove accidentally
committed pytest.xml and python-coverage.xml and add them to .gitignore.
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Raise clear handler registration error for unresolved TypeVar (#4943)
Detect unresolved TypeVar in message parameter annotations during handler
registration in both _validate_handler_signature (Executor) and
_validate_function_signature (FunctionExecutor). Raises a ValueError with
an actionable message recommending @handler(input=..., output=...) or
@executor(input=..., output=...) instead of letting TypeVar leak through
to a confusing TypeCompatibilityError during workflow edge validation.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4943: reorder checks and harden function executor
- Move TypeVar check before validate_workflow_context_annotation in
_executor.py so users see the more actionable error first
- Wrap get_type_hints in try/except in _function_executor.py matching
the defensive pattern in _executor.py
- Repurpose duplicate test to cover bounded TypeVar rejection
- Add test_function_executor_allows_concrete_types for test symmetry
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Narrow get_type_hints except clause and add missing tests (#4943)
- Narrow `except Exception` to `except (NameError, AttributeError, RecursionError)`
in both _executor.py and _function_executor.py so unexpected failures in
get_type_hints are not silently swallowed.
- Add test_handler_unresolvable_annotation_raises to test_function_executor_future.py
exercising the except branch of get_type_hints in the function executor path.
- Add test_function_executor_rejects_bounded_typevar_in_message_annotation to
test_function_executor.py for parity with the Executor bounded TypeVar test.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add error ordering test for TypeVar vs WorkflowContext priority (#4943)
Add test_handler_typevar_error_takes_priority_over_context_error to verify
that when a handler has both a TypeVar message and an unannotated ctx, the
TypeVar error is raised first (the more actionable issue).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Fix image content serialization sending null file_id to Foundry API
Omit file_id from input_image dict when not present instead of including
it as null, which Azure AI Foundry's stricter schema validation rejects.
* Python: Fix Foundry API rejecting rich content in function_call_output
Azure AI Foundry does not support list-format output in function_call_output
items. Add SUPPORTS_RICH_FUNCTION_OUTPUT flag (default True) to
RawOpenAIChatClient, set to False in RawFoundryChatClient so Foundry
falls back to string output for tool results with images/files.
Also omit file_id from input_image dicts when not set, since Foundry
rejects explicit nulls.
* Python: Surface rich tool content as user message when Foundry lacks support
When SUPPORTS_RICH_FUNCTION_OUTPUT is False, image/file items from tool
results are injected as a follow-up user message so the model can still
process the visual content via Foundry's supported user message format.
* Xfail Foundry image integration test for the meantime
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* 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
* Python: Fix broken samples for GitHub Copilot, declarative, and Responses API
- Add missing on_permission_request handler to github_copilot_basic and
github_copilot_with_session samples (required by copilot SDK)
- Increase timeout for remote MCP query in github_copilot_with_mcp sample
- Soften session isolation claim in github_copilot_with_session sample
- Fix inline_yaml sample: pass project_endpoint via client_kwargs instead
of relying on YAML connection block (AzureAIClient expects
project_endpoint, not endpoint)
- Handle raw JSON schemas in Responses client _convert_response_format
so declarative outputSchema works with the Responses API
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Improve raw JSON schema detection heuristic and add tests
- Broaden raw schema detection to handle anyOf, oneOf, allOf, $ref, $defs
keywords and JSON Schema primitive types, not just 'properties'
- Apply same raw schema handling to azure-ai _shared.py for consistency
- Add unit tests for both openai and azure-ai response_format conversion
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Support MCP sampling tools capability (#4625)
Forward systemPrompt, tools, and toolChoice from MCP sampling requests
to the chat client's get_response() call. Also advertise the
sampling.tools capability to MCP servers when a client is configured.
- Pass SamplingCapability with tools support to ClientSession
- Convert systemPrompt to instructions in options
- Convert MCP Tool objects to FunctionTool instances for options
- Map MCP ToolChoice.mode to tool_choice in options
- Add tests for all new behaviors and update existing sampling tests
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix#4625: Support MCP sampling tool with proper typing and structured content
- Fix mypy error by typing sampling callback options as ChatOptions[None]
instead of dict[str, Any], and importing ChatOptions from _types
- Handle structuredContent from CallToolResult in _parse_tool_result_from_mcp,
serializing it as JSON text Content when present
- Add tests for structuredContent parsing (with and without regular content)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix lint: add author to TODO comment
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4625: remove default=str, add edge-case tests
- Remove default=str from json.dumps for structuredContent to fail fast
on non-JSON-serializable values instead of silently converting
- Add test for non-JSON-serializable structuredContent (TypeError)
- Add tests for empty systemPrompt ('') and empty tools list ([]) edge
cases in sampling callback
- Expand TODO comment noting list[Content] return type constraint for
future result_type support
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Sanitize sampling callback error to avoid leaking internals (#4625)
Log exception details at DEBUG level instead of including them in the
ErrorData message returned to the MCP server, which may be untrusted.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4625: move params to options, restore error info
- Remove stale TODO comment about response_format (ChatOptions already has it)
- Restore {ex} in sampling callback error message for useful debugging info
- Set structuredContent as additional_property on Content for structured access
- Move temperature, max_tokens, stop into options dict (not top-level kwargs)
- Only set temperature when provided (not all models support it)
- Add tests for generation params in options and temperature omission
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix MCP sampling callback and structured content error handling (#4625)
- Guard max_tokens like temperature: only set when not None, so options
can properly evaluate to None when all params are absent
- Wrap json.dumps of structuredContent in try/except to fall back to
str() for non-serializable values instead of propagating TypeError
- Extract test_connect_sampling_capabilities_with_client into its own
test function so pytest can discover it independently
- Add test for max_tokens=None omission from options
- Update structured content non-serializable test to expect fallback
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4625: review comment fixes
* Fix MCP and Azure validation regressions
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Eduard van Valkenburg
·
2026-03-26 07:33:19 +00:00
* Fix streaming path to deliver mcp_server_tool_result content (#4814)
Remove premature mcp_server_tool_result emission from the
response.output_item.added/mcp_call handler — at that point the MCP
server has not yet responded and output is always None.
Add a handler for response.mcp_call.completed that emits
mcp_server_tool_result with the actual tool output, matching the
non-streaming path behavior.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix streaming path to deliver mcp_server_tool_result content (#4814)
Stop eagerly emitting mcp_server_tool_result on response.output_item.added
(when output is always None). Instead, handle response.output_item.done for
mcp_call items, which carries the full McpCall with populated output.
This matches the non-streaming path which guards with 'if item.output is not
None' before emitting the result.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix test docstring to match actual implementation event name
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review: call_id fallback and raw_representation consistency (#4814)
- Add call_id fallback in response.output_item.done mcp_call handler to
match the output_item.added handler pattern
- Use done_item instead of event for raw_representation to keep
consistent with other output_item branches and non-streaming path
- Add test for call_id fallback when id attribute is missing
- Add raw_representation assertions to existing done handler tests
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review: call_id fallback for non-streaming path and test coverage (#4814)
- Apply defensive call_id fallback (getattr with id/call_id/empty) to
non-streaming mcp_call path for consistency with streaming path
- Add raw_representation assertion to call_id fallback test
- Add test for empty-string fallback when neither id nor call_id exist
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>
Eduard van Valkenburg ·
Willow Lopez ·
Evan Mattson ·
Yufeng He ·
Emilien Mottet ·
S3rj ·
Tao Chen ·
Giles Odigwe ·
chetantoshniwal ·