Files
microsoft--agent-framework/python/packages/chatkit/tests/test_converter.py
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

425 lines
14 KiB
Python

# Copyright (c) Microsoft. All rights reserved.
"""Tests for ChatKit to Agent Framework converter utilities."""
from unittest.mock import Mock
import pytest
from agent_framework import Message
from chatkit.types import InferenceOptions, UserMessageTextContent
from pydantic import AnyUrl
from agent_framework_chatkit import ThreadItemConverter, simple_to_agent_input
class TestThreadItemConverter:
"""Tests for ThreadItemConverter class."""
@pytest.fixture
def converter(self):
"""Create a ThreadItemConverter instance for testing."""
return ThreadItemConverter()
async def test_to_agent_input_none(self, converter):
"""Test converting empty list returns empty list."""
result = await converter.to_agent_input([])
assert result == []
async def test_to_agent_input_with_text(self, converter):
"""Test converting user message with text content."""
from datetime import datetime
from chatkit.types import UserMessageItem
input_item = UserMessageItem(
id="msg_1",
thread_id="thread_1",
created_at=datetime.now(),
type="user_message",
content=[UserMessageTextContent(text="Hello, how can you help me?")],
attachments=[],
inference_options=InferenceOptions(),
)
result = await converter.to_agent_input(input_item)
assert len(result) == 1
assert isinstance(result[0], Message)
assert result[0].role == "user"
assert result[0].text == "Hello, how can you help me?"
async def test_to_agent_input_empty_text(self, converter):
"""Test converting user message with empty or whitespace-only text."""
from datetime import datetime
from chatkit.types import UserMessageItem
input_item = UserMessageItem(
id="msg_1",
thread_id="thread_1",
created_at=datetime.now(),
type="user_message",
content=[UserMessageTextContent(text=" ")],
attachments=[],
inference_options=InferenceOptions(),
)
result = await converter.to_agent_input(input_item)
assert result == []
async def test_to_agent_input_no_content(self, converter):
"""Test converting user message with no content."""
from datetime import datetime
from chatkit.types import UserMessageItem
input_item = UserMessageItem(
id="msg_1",
thread_id="thread_1",
created_at=datetime.now(),
type="user_message",
content=[],
attachments=[],
inference_options=InferenceOptions(),
)
result = await converter.to_agent_input(input_item)
assert result == []
async def test_to_agent_input_multiple_content_parts(self, converter):
"""Test converting user message with multiple text content parts."""
from datetime import datetime
from chatkit.types import UserMessageItem
input_item = UserMessageItem(
id="msg_1",
thread_id="thread_1",
created_at=datetime.now(),
type="user_message",
content=[
UserMessageTextContent(text="Hello "),
UserMessageTextContent(text="world!"),
],
attachments=[],
inference_options=InferenceOptions(),
)
result = await converter.to_agent_input(input_item)
assert len(result) == 1
assert result[0].text == "Hello world!"
def test_hidden_context_to_input(self, converter):
"""Test converting hidden context item to Message."""
hidden_item = Mock()
hidden_item.content = "This is hidden context information"
result = converter.hidden_context_to_input(hidden_item)
assert isinstance(result, Message)
assert result.role == "system"
assert result.text == "<HIDDEN_CONTEXT>This is hidden context information</HIDDEN_CONTEXT>"
def test_tag_to_message_content(self, converter):
"""Test converting tag to message content."""
from chatkit.types import UserMessageTagContent
tag = UserMessageTagContent(
type="input_tag",
id="tag_1",
text="john",
data={"name": "John Doe"},
interactive=False,
)
result = converter.tag_to_message_content(tag)
assert result.type == "text"
# Since data is a dict, getattr won't work, so it will fall back to text
assert result.text == "<TAG>Name:john</TAG>"
def test_tag_to_message_content_no_name(self, converter):
"""Test converting tag with no name to message content."""
from chatkit.types import UserMessageTagContent
tag = UserMessageTagContent(
type="input_tag",
id="tag_2",
text="jane",
data={},
interactive=False,
)
result = converter.tag_to_message_content(tag)
assert result.type == "text"
assert result.text == "<TAG>Name:jane</TAG>"
async def test_attachment_to_message_content_file_without_fetcher(self, converter):
"""Test that FileAttachment without data fetcher returns None."""
from chatkit.types import FileAttachment
attachment = FileAttachment(
id="file_123",
name="document.pdf",
mime_type="application/pdf",
type="file",
)
result = await converter.attachment_to_message_content(attachment)
assert result is None
async def test_attachment_to_message_content_image_with_preview_url(self, converter):
"""Test that ImageAttachment with preview_url creates UriContent."""
from chatkit.types import ImageAttachment
attachment = ImageAttachment(
id="img_123",
name="photo.jpg",
mime_type="image/jpeg",
type="image",
preview_url=AnyUrl("https://example.com/photo.jpg"),
)
result = await converter.attachment_to_message_content(attachment)
assert result.type == "uri"
assert result.uri == "https://example.com/photo.jpg"
assert result.media_type == "image/jpeg"
async def test_attachment_to_message_content_with_data_fetcher(self):
"""Test attachment conversion with data fetcher."""
from chatkit.types import FileAttachment
# Mock data fetcher
async def fetch_data(attachment_id: str) -> bytes:
return b"file content data"
converter = ThreadItemConverter(attachment_data_fetcher=fetch_data)
attachment = FileAttachment(
id="file_123",
name="document.pdf",
mime_type="application/pdf",
type="file",
)
result = await converter.attachment_to_message_content(attachment)
assert result is not None
assert result.type == "data"
assert result.media_type == "application/pdf"
async def test_to_agent_input_with_image_attachment(self):
"""Test converting user message with text and image attachment."""
from datetime import datetime
from chatkit.types import ImageAttachment, UserMessageItem
attachment = ImageAttachment(
id="img_123",
name="photo.jpg",
mime_type="image/jpeg",
type="image",
preview_url=AnyUrl("https://example.com/photo.jpg"),
)
input_item = UserMessageItem(
id="msg_1",
thread_id="thread_1",
created_at=datetime.now(),
type="user_message",
content=[UserMessageTextContent(text="Check out this photo!")],
attachments=[attachment],
inference_options=InferenceOptions(),
)
converter = ThreadItemConverter()
result = await converter.to_agent_input(input_item)
assert len(result) == 1
message = result[0]
assert message.role == "user"
assert len(message.contents) == 2
# First content should be text
assert message.contents[0].type == "text"
assert message.contents[0].text == "Check out this photo!"
# Second content should be UriContent for the image
assert message.contents[1].type == "uri"
assert message.contents[1].uri == "https://example.com/photo.jpg"
assert message.contents[1].media_type == "image/jpeg"
async def test_to_agent_input_with_file_attachment_and_fetcher(self):
"""Test converting user message with file attachment using data fetcher."""
from datetime import datetime
from chatkit.types import FileAttachment, UserMessageItem
attachment = FileAttachment(
id="file_123",
name="report.pdf",
mime_type="application/pdf",
type="file",
)
input_item = UserMessageItem(
id="msg_1",
thread_id="thread_1",
created_at=datetime.now(),
type="user_message",
content=[UserMessageTextContent(text="Here's the document")],
attachments=[attachment],
inference_options=InferenceOptions(),
)
# Create converter with data fetcher
async def fetch_data(attachment_id: str) -> bytes:
return b"PDF content data"
converter = ThreadItemConverter(attachment_data_fetcher=fetch_data)
result = await converter.to_agent_input(input_item)
assert len(result) == 1
message = result[0]
assert len(message.contents) == 2
# First content should be text
assert message.contents[0].type == "text"
# Second content should be DataContent for the file
assert message.contents[1].type == "data"
assert message.contents[1].media_type == "application/pdf"
def test_task_to_input(self, converter):
"""Test converting TaskItem to Message."""
from datetime import datetime
from chatkit.types import CustomTask, TaskItem
task_item = TaskItem(
id="task_1",
thread_id="thread_1",
created_at=datetime.now(),
type="task",
task=CustomTask(type="custom", title="Analysis", content="Analyzed the data"),
)
result = converter.task_to_input(task_item)
assert isinstance(result, Message)
assert result.role == "user"
assert "Analysis: Analyzed the data" in result.text
assert "<Task>" in result.text
def test_task_to_input_no_custom_task(self, converter):
"""Test that non-custom tasks return None."""
from datetime import datetime
from chatkit.types import TaskItem, ThoughtTask
task_item = TaskItem(
id="task_1",
thread_id="thread_1",
created_at=datetime.now(),
type="task",
task=ThoughtTask(type="thought", title="Think", content="Thinking..."),
)
result = converter.task_to_input(task_item)
assert result is None
def test_workflow_to_input(self, converter):
"""Test converting WorkflowItem to ChatMessages."""
from datetime import datetime
from chatkit.types import CustomTask, Workflow, WorkflowItem
workflow_item = WorkflowItem(
id="wf_1",
thread_id="thread_1",
created_at=datetime.now(),
type="workflow",
workflow=Workflow(
type="custom",
tasks=[
CustomTask(type="custom", title="Step 1", content="First step"),
CustomTask(type="custom", title="Step 2", content="Second step"),
],
),
)
result = converter.workflow_to_input(workflow_item)
assert isinstance(result, list)
assert len(result) == 2
assert all(isinstance(msg, Message) for msg in result)
assert "Step 1: First step" in result[0].text
assert "Step 2: Second step" in result[1].text
def test_workflow_to_input_empty(self, converter):
"""Test that workflows with no custom tasks return None."""
from datetime import datetime
from chatkit.types import Workflow, WorkflowItem
workflow_item = WorkflowItem(
id="wf_1",
thread_id="thread_1",
created_at=datetime.now(),
type="workflow",
workflow=Workflow(type="custom", tasks=[]),
)
result = converter.workflow_to_input(workflow_item)
assert result is None
def test_widget_to_input(self, converter):
"""Test converting WidgetItem to Message."""
from datetime import datetime
from chatkit.types import WidgetItem
from chatkit.widgets import Card, Text # ty: ignore[deprecated]
widget_item = WidgetItem(
id="widget_1",
thread_id="thread_1",
created_at=datetime.now(),
type="widget",
widget=Card(key="card1", children=[Text(value="Hello")]), # ty: ignore[deprecated]
)
result = converter.widget_to_input(widget_item)
assert isinstance(result, Message)
assert result.role == "user"
assert "widget_1" in result.text
assert "graphical UI widget" in result.text
class TestSimpleToAgentInput:
"""Tests for simple_to_agent_input helper function."""
async def test_simple_to_agent_input_empty_list(self):
"""Test simple conversion with empty list."""
result = await simple_to_agent_input([])
assert result == []
async def test_simple_to_agent_input_with_text(self):
"""Test simple conversion with text content."""
from datetime import datetime
from chatkit.types import UserMessageItem
input_item = UserMessageItem(
id="msg_1",
thread_id="thread_1",
created_at=datetime.now(),
type="user_message",
content=[UserMessageTextContent(text="Test message")],
attachments=[],
inference_options=InferenceOptions(),
)
result = await simple_to_agent_input(input_item)
assert len(result) == 1
assert isinstance(result[0], Message)
assert result[0].role == "user"
assert result[0].text == "Test message"