Files
Eduard van Valkenburg 6e95517659 Python: Split type checkers by target (pyright source, 5 checkers on tests/samples) (#6443)
* Python: Split type checkers by target (pyright source, 5 checkers on tests/samples)

Rework the typing setup along the lines of the 'too many type checkers'
approach:

- Pyright (strict) is now the sole source-code type checker; mypy is
  removed from source and its [tool.mypy] block becomes a relaxed profile
  used only for tests/samples.
- Tests are checked by all five checkers (pyright relaxed, mypy, pyrefly,
  ty, zuban); samples by pyright, pyrefly, and ty. All run in a relaxed/
  basic profile so authors aren't forced into over-annotation.
- Add pyrightconfig.tests.json and bump sample pyright configs to basic.
- Unify test/sample typing onto the same parallel fan-out used by source
  pyright via run_command_items in task_runner.py.
- Make version-conditional imports symmetric: keep or drop the
  '# type: ignore' on both branches so results match across interpreter
  versions (local vs CI).
- Update SKILL.md, DEV_SETUP.md, and CODING_STANDARD.md for the five
  gating checkers and pyright on source+tests+samples.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python: Fix merge regressions from main (typing + runtime)

Merging main into the type-checker split branch surfaced regressions that
the new five-checker test suite and unit tests caught:

Runtime fixes:
- anthropic: restore the dropped `cache_read_input_token_count` mapping in
  _parse_usage_from_anthropic (lost during merge conflict resolution).
- gemini: _get_function_calling_mode test helper returned str(enum)
  ('FunctionCallingConfigMode.AUTO') instead of the enum value ('AUTO').
- openai: _response_id_from_token test helper was an infinite self-recursion;
  return token['response_id'].
- orchestrations: reset output_events per approval iteration so the terminal
  output assertion counts only the final run.
- core: drop a stale duplicate harness test whose message ('non-negative')
  contradicted the source ('positive').
- purview: import PolicyLocation/PolicyScope/ProtectionScopeActivities/
  ExecutionMode used by the processor tests.

Type-checker fixes (tests, relaxed profile):
- core: pyright/mypy/pyrefly/ty/zuban green-ups across the harness, MCP,
  observability and types tests.
- anthropic/openai: route provider-namespaced UsageDetails keys through a
  dict cast (extra_items TypedDict unsupported by mypy/ty).
- purview: typed model constructors and cache-mock casts.
- ag-ui: annotate WorkflowContext[Any, Any] so yield_output accepts test
  payloads, guard Optional forwarded_props, and ty-ignore intentional bad args.

Source pyright (sole source checker) flagged unnecessary ignores newly
introduced by merged code in core _tools.py and declarative _declarative_base.py.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python: Isolate per-package mypy cache in test-typing fan-out

The parallel test-typing fan-out runs many mypy processes concurrently,
all defaulting to a single shared ./.mypy_cache. Concurrent writes corrupt
the cache and mypy aborts with INTERNAL ERROR (intermittently, depending on
worker timing) -- which is why CI's Test Typing job failed on a shifting set
of packages while a single-package run was fine.

Give each mypy invocation an isolated cache dir keyed by its target paths so
incremental caching still works per package without races. Other checkers
(zuban/pyrefly/ty/pyright) maintain their own caches and are unaffected.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python: Make lab pyright-only on source (drop source mypy)

Lab was the last package still running mypy on its source code, requiring
mypy-only `# type: ignore` comments that pyright (the sole source checker
everywhere else) flags as unnecessary. Align lab with the rest of the
monorepo:

- Remove the lab source mypy poe tasks (mypy-gaia/lightning/tau2) and the
  now-dead strict [tool.mypy] config block.
- Drop the 'Run lab mypy' CI step; lab source is type-checked by pyright only.

Lab tests remain covered by the workspace test-typing fan-out (mypy, pyrefly,
ty, zuban, pyright over tests using the relaxed root config).

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python: Fix test-typing regressions from latest main merge

A fresh merge from main brought in new test code never run under the
five-checker test-typing suite. Green up across the affected packages:

- core: narrow Optional span.attributes with 'and' guards in span filters
  and assert+cast the json.loads(...attributes[...]) reads (test_observability);
  match the existing as_agent ignore on the protocol-typed fixture (test_clients).
- openai: align new streaming tests with the established chat_options dict
  pattern (ChatOptions TypedDict isn't assignable to dict), route Optional
  .annotations[0] access through a small _first_annotation helper (mirrors the
  file's assert-not-None convention), and annotate a mapped ResponseStream.
- foundry_hosting: annotate error: dict[str, Any] = body.get(...) or {}
  (zuban needs the annotation).
- foundry: narrow ignores for the live AIProjectClient credential arg (pyrefly)
  and connections.get_default (zuban) SDK type gaps.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* updated pyright version

* pyright fix

* Python: Fix source typing for pyright 1.1.410

Pyright 1.1.410 tightened several checks. Apply the same source fixes as
upstream PR #6275:

- anthropic: import AsyncAnthropicBedrock from anthropic.lib.bedrock and
  AsyncAnthropicVertex from anthropic.lib.vertex (no longer re-exported from
  the anthropic top-level package -> reportPrivateImportUsage).
- core _types.py: cast the transform-hook result to UpdateT (reportAssignmentType).
- core _workflows/_events.py: annotate the @contextmanager helper as
  Generator[None] instead of Iterator[None] (reportDeprecated).
- redis: build the combined filter expression with an explicit loop instead of
  reduce(and_, ...), which pyright could no longer fully type (drops the now
  unused functools.reduce / operator.and_ imports).

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Python: Accept plain-text body in Azure Functions workflow/run endpoint

The workflow_orchestrator already accepts plain strings as well as JSON
objects via context.get_input(), but the start_workflow_orchestration HTTP
handler only accepted JSON and returned 400 for any non-JSON body. This made
the functions integration tests that POST text/plain to /api/workflow/run
(e.g. test_09_workflow_shared_state) fail consistently with 400 != 202.

Fall back to the raw request body (decoded as UTF-8) when the body is not
JSON, rejecting only a truly empty body. The JSON path is unchanged.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-18 15:06:20 +00:00

172 lines
6.0 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
from __future__ import annotations
from typing import Any
import pytest
from agent_framework import Content, Message
from agent_framework_bedrock import BedrockChatClient
class _StubBedrockRuntime:
def __init__(self) -> None:
self.calls: list[dict[str, Any]] = []
def converse(self, **kwargs: Any) -> dict[str, Any]:
self.calls.append(kwargs)
return {
"modelId": kwargs["modelId"],
"responseId": "resp-123",
"usage": {"inputTokens": 10, "outputTokens": 5, "totalTokens": 15},
"output": {
"completionReason": "end_turn",
"message": {
"id": "msg-1",
"role": "assistant",
"content": [{"text": "Bedrock says hi"}],
},
},
}
def _make_client() -> BedrockChatClient:
"""Create a BedrockChatClient with a stub runtime for unit tests."""
return BedrockChatClient(
model="amazon.titan-text",
region="us-west-2",
client=_StubBedrockRuntime(), # pyrefly: ignore[bad-argument-type] # ty: ignore[invalid-argument-type] # pyright: ignore[reportArgumentType]
)
async def test_get_response_invokes_bedrock_runtime() -> None:
stub = _StubBedrockRuntime()
client = BedrockChatClient(
model="amazon.titan-text",
region="us-west-2",
client=stub, # pyrefly: ignore[bad-argument-type] # ty: ignore[invalid-argument-type] # pyright: ignore[reportArgumentType]
)
messages = [
Message(role="system", contents=[Content.from_text(text="You are concise.")]),
Message(role="user", contents=[Content.from_text(text="hello")]),
]
response = await client.get_response(messages=messages, options={"max_tokens": 32})
assert stub.calls, "Expected the runtime client to be called"
payload = stub.calls[0]
assert payload["modelId"] == "amazon.titan-text"
assert payload["messages"][0]["content"][0]["text"] == "hello"
assert response.messages[0].contents[0].text == "Bedrock says hi"
assert response.usage_details and response.usage_details["input_token_count"] == 10
def test_build_request_requires_non_system_messages() -> None:
client = BedrockChatClient(
model="amazon.titan-text",
region="us-west-2",
client=_StubBedrockRuntime(), # pyrefly: ignore[bad-argument-type] # ty: ignore[invalid-argument-type] # pyright: ignore[reportArgumentType]
)
messages = [Message(role="system", contents=[Content.from_text(text="Only system text")])]
with pytest.raises(ValueError):
client._prepare_options(messages, {})
def test_prepare_options_tool_choice_none_omits_tool_config() -> None:
"""When tool_choice='none', toolConfig must be omitted entirely.
Bedrock's Converse API only accepts 'auto', 'any', or 'tool' as valid
toolChoice keys. Sending {"none": {}} causes a ParamValidationError.
The fix omits toolConfig so the model won't attempt tool calls.
Fixes #4529.
"""
client = _make_client()
messages = [Message(role="user", contents=[Content.from_text(text="hello")])]
# Even when tools are provided, tool_choice="none" should strip toolConfig
options: dict[str, Any] = {
"tool_choice": "none",
"tools": [
{"toolSpec": {"name": "get_weather", "description": "Get weather", "inputSchema": {"json": {}}}},
],
}
request = client._prepare_options(messages, options)
assert "toolConfig" not in request, (
f"toolConfig should be omitted when tool_choice='none', got: {request.get('toolConfig')}"
)
def test_prepare_options_tool_choice_auto_includes_tool_config() -> None:
"""When tool_choice='auto', toolConfig.toolChoice should be {'auto': {}}."""
client = _make_client()
messages = [Message(role="user", contents=[Content.from_text(text="hello")])]
options: dict[str, Any] = {
"tool_choice": "auto",
"tools": [
{"toolSpec": {"name": "get_weather", "description": "Get weather", "inputSchema": {"json": {}}}},
],
}
request = client._prepare_options(messages, options)
assert "toolConfig" in request
assert request["toolConfig"]["toolChoice"] == {"auto": {}}
def test_prepare_options_tool_choice_required_includes_any() -> None:
"""When tool_choice='required' (no specific function), toolChoice should be {'any': {}}."""
client = _make_client()
messages = [Message(role="user", contents=[Content.from_text(text="hello")])]
options: dict[str, Any] = {
"tool_choice": "required",
"tools": [
{"toolSpec": {"name": "get_weather", "description": "Get weather", "inputSchema": {"json": {}}}},
],
}
request = client._prepare_options(messages, options)
assert "toolConfig" in request
assert request["toolConfig"]["toolChoice"] == {"any": {}}
def test_prepare_options_tool_choice_auto_without_tools_omits_tool_config() -> None:
"""When tool_choice='auto' but no tools are provided, toolConfig must be omitted.
Without tools, setting toolChoice would cause a ParamValidationError from Bedrock.
"""
client = _make_client()
messages = [Message(role="user", contents=[Content.from_text(text="hello")])]
options: dict[str, Any] = {
"tool_choice": "auto",
}
request = client._prepare_options(messages, options)
assert "toolConfig" not in request, (
f"toolConfig should be omitted when no tools are provided, got: {request.get('toolConfig')}"
)
def test_prepare_options_tool_choice_required_without_tools_raises() -> None:
"""When tool_choice='required' but no tools are provided, a ValueError must be raised."""
client = _make_client()
messages = [Message(role="user", contents=[Content.from_text(text="hello")])]
options: dict[str, Any] = {
"tool_choice": "required",
}
with pytest.raises(ValueError, match="tool_choice='required' requires at least one tool"):
client._prepare_options(messages, options)