6e95517659
* 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>
134 lines
5.4 KiB
Python
134 lines
5.4 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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"""Unit tests for DurableAIAgentClient.
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Focuses on critical client workflows: agent retrieval, protocol compliance, and integration.
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Run with: pytest tests/test_client.py -v
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"""
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from unittest.mock import Mock
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import pytest
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from agent_framework import SupportsAgentRun
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from agent_framework_durabletask import DurableAgentSession, DurableAIAgentClient
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from agent_framework_durabletask._constants import DEFAULT_MAX_POLL_RETRIES, DEFAULT_POLL_INTERVAL_SECONDS
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from agent_framework_durabletask._shim import DurableAIAgent
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@pytest.fixture
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def mock_grpc_client() -> Mock:
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"""Create a mock TaskHubGrpcClient for testing."""
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return Mock()
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@pytest.fixture
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def agent_client(mock_grpc_client: Mock) -> DurableAIAgentClient:
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"""Create a DurableAIAgentClient with mock gRPC client."""
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return DurableAIAgentClient(mock_grpc_client)
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@pytest.fixture
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def agent_client_with_custom_polling(mock_grpc_client: Mock) -> DurableAIAgentClient:
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"""Create a DurableAIAgentClient with custom polling parameters."""
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return DurableAIAgentClient(
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mock_grpc_client,
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max_poll_retries=15,
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poll_interval_seconds=0.5,
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)
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class TestDurableAIAgentClientGetAgent:
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"""Test core workflow: retrieving agents from the client."""
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def test_get_agent_returns_durable_agent_shim(self, agent_client: DurableAIAgentClient) -> None:
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"""Verify get_agent returns a DurableAIAgent instance."""
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agent = agent_client.get_agent("assistant")
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assert isinstance(agent, DurableAIAgent)
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assert isinstance(agent, SupportsAgentRun) # pyrefly: ignore[unsafe-overlap]
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def test_get_agent_shim_has_correct_name(self, agent_client: DurableAIAgentClient) -> None:
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"""Verify retrieved agent has the correct name."""
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agent = agent_client.get_agent("my_agent")
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assert agent.name == "my_agent"
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def test_get_agent_multiple_times_returns_new_instances(self, agent_client: DurableAIAgentClient) -> None:
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"""Verify multiple get_agent calls return independent instances."""
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agent1 = agent_client.get_agent("assistant")
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agent2 = agent_client.get_agent("assistant")
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assert agent1 is not agent2 # Different object instances
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def test_get_agent_different_agents(self, agent_client: DurableAIAgentClient) -> None:
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"""Verify client can retrieve multiple different agents."""
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agent1 = agent_client.get_agent("agent1")
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agent2 = agent_client.get_agent("agent2")
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assert agent1.name == "agent1"
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assert agent2.name == "agent2"
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class TestDurableAIAgentClientIntegration:
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"""Test integration scenarios between client and agent shim."""
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def test_client_agent_has_working_run_method(self, agent_client: DurableAIAgentClient) -> None:
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"""Verify agent from client has callable run method (even if not yet implemented)."""
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agent = agent_client.get_agent("assistant")
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assert hasattr(agent, "run")
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assert callable(agent.run)
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def test_client_agent_can_create_sessions(self, agent_client: DurableAIAgentClient) -> None:
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"""Verify agent from client can create DurableAgentSession instances."""
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agent = agent_client.get_agent("assistant")
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session = agent.create_session()
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assert isinstance(session, DurableAgentSession)
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class TestDurableAIAgentClientPollingConfiguration:
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"""Test polling configuration parameters for DurableAIAgentClient."""
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def test_client_uses_default_polling_parameters(self, agent_client: DurableAIAgentClient) -> None:
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"""Verify client initializes with default polling parameters."""
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assert agent_client.max_poll_retries == DEFAULT_MAX_POLL_RETRIES
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assert agent_client.poll_interval_seconds == DEFAULT_POLL_INTERVAL_SECONDS
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def test_client_accepts_custom_polling_parameters(
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self, agent_client_with_custom_polling: DurableAIAgentClient
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) -> None:
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"""Verify client accepts and stores custom polling parameters."""
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assert agent_client_with_custom_polling.max_poll_retries == 15
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assert agent_client_with_custom_polling.poll_interval_seconds == 0.5
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def test_client_validates_max_poll_retries(self, mock_grpc_client: Mock) -> None:
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"""Verify client validates and normalizes max_poll_retries."""
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# Test with zero - should enforce minimum of 1
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client = DurableAIAgentClient(mock_grpc_client, max_poll_retries=0)
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assert client.max_poll_retries == 1
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# Test with negative - should enforce minimum of 1
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client = DurableAIAgentClient(mock_grpc_client, max_poll_retries=-5)
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assert client.max_poll_retries == 1
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def test_client_validates_poll_interval_seconds(self, mock_grpc_client: Mock) -> None:
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"""Verify client validates and normalizes poll_interval_seconds."""
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# Test with zero - should use default
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client = DurableAIAgentClient(mock_grpc_client, poll_interval_seconds=0)
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assert client.poll_interval_seconds == DEFAULT_POLL_INTERVAL_SECONDS
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# Test with negative - should use default
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client = DurableAIAgentClient(mock_grpc_client, poll_interval_seconds=-0.5)
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assert client.poll_interval_seconds == DEFAULT_POLL_INTERVAL_SECONDS
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# Test with valid float
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client = DurableAIAgentClient(mock_grpc_client, poll_interval_seconds=2.5)
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assert client.poll_interval_seconds == 2.5
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if __name__ == "__main__":
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pytest.main([__file__, "-v", "--tb=short"])
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