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>
376 lines
14 KiB
Python
376 lines
14 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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from collections.abc import AsyncIterable, Awaitable
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from typing import Any, Literal, cast, overload
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import pytest
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from agent_framework import (
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AgentExecutorRequest,
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AgentExecutorResponse,
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AgentResponse,
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AgentResponseUpdate,
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AgentRunInputs,
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AgentSession,
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BaseAgent,
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Content,
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Executor,
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Message,
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ResponseStream,
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WorkflowContext,
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WorkflowRunState,
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handler,
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)
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from agent_framework._workflows._checkpoint import InMemoryCheckpointStorage
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from agent_framework.orchestrations import ConcurrentBuilder
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class _FakeAgentExec(Executor):
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"""Test executor that mimics an agent by emitting an AgentExecutorResponse.
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It takes the incoming AgentExecutorRequest, produces a single assistant message
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with the configured reply text, and sends an AgentExecutorResponse that includes
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full_conversation (the original user prompt followed by the assistant message).
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"""
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def __init__(self, id: str, reply_text: str) -> None:
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super().__init__(id)
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self._reply_text = reply_text
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@handler
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async def run(self, request: AgentExecutorRequest, ctx: WorkflowContext[AgentExecutorResponse]) -> None:
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response = AgentResponse(messages=Message(role="assistant", contents=[self._reply_text]))
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full_conversation = list(request.messages) + list(response.messages)
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await ctx.send_message(AgentExecutorResponse(self.id, response, full_conversation=full_conversation))
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def test_concurrent_builder_rejects_empty_participants() -> None:
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with pytest.raises(ValueError):
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ConcurrentBuilder(participants=[])
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def test_concurrent_builder_rejects_duplicate_executors() -> None:
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a = _FakeAgentExec("dup", "A")
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b = _FakeAgentExec("dup", "B") # same executor id
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with pytest.raises(ValueError):
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ConcurrentBuilder(participants=[a, b])
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async def test_concurrent_default_aggregator_emits_assistants_only() -> None:
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"""Default aggregator yields a single AgentResponse with one assistant message per participant.
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The user prompt is intentionally not included — that belongs in the input, not the answer.
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"""
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e1 = _FakeAgentExec("agentA", "Alpha")
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e2 = _FakeAgentExec("agentB", "Beta")
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e3 = _FakeAgentExec("agentC", "Gamma")
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wf = ConcurrentBuilder(participants=[e1, e2, e3]).build()
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output_events = [ev for ev in await wf.run("prompt: hello world") if ev.type == "output"]
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assert len(output_events) == 1
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response = output_events[0].data
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assert isinstance(response, AgentResponse)
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# Exactly one assistant message per participant; no user prompt.
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assert len(response.messages) == 3
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assert all(m.role == "assistant" for m in response.messages)
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assert {m.text for m in response.messages} == {"Alpha", "Beta", "Gamma"}
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async def test_concurrent_custom_aggregator_callback_is_used() -> None:
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# Two synthetic agent executors for brevity
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e1 = _FakeAgentExec("agentA", "One")
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e2 = _FakeAgentExec("agentB", "Two")
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async def summarize(results: list[AgentExecutorResponse]) -> str:
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texts: list[str] = []
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for r in results:
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msgs: list[Message] = r.agent_response.messages
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texts.append(msgs[-1].text if msgs else "")
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return " | ".join(sorted(texts))
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wf = ConcurrentBuilder(participants=[e1, e2]).with_aggregator(summarize).build()
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completed = False
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output: str | None = None
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async for ev in wf.run("prompt: custom", stream=True):
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if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
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completed = True
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elif ev.type == "output":
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output = cast(str, ev.data)
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if completed and output is not None:
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break
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assert completed
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assert output is not None
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# Custom aggregator returns a string payload
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assert isinstance(output, str)
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assert output == "One | Two"
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async def test_concurrent_custom_aggregator_sync_callback_is_used() -> None:
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e1 = _FakeAgentExec("agentA", "One")
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e2 = _FakeAgentExec("agentB", "Two")
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# Sync callback with ctx parameter (should run via asyncio.to_thread)
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def summarize_sync(results: list[AgentExecutorResponse], _ctx: WorkflowContext[Any]) -> str: # type: ignore[unused-argument]
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texts: list[str] = []
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for r in results:
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msgs: list[Message] = r.agent_response.messages
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texts.append(msgs[-1].text if msgs else "")
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return " | ".join(sorted(texts))
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wf = ConcurrentBuilder(participants=[e1, e2]).with_aggregator(summarize_sync).build()
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completed = False
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output: str | None = None
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async for ev in wf.run("prompt: custom sync", stream=True):
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if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
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completed = True
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elif ev.type == "output":
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output = cast(str, ev.data)
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if completed and output is not None:
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break
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assert completed
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assert output is not None
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assert isinstance(output, str)
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assert output == "One | Two"
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def test_concurrent_custom_aggregator_uses_callback_name_for_id() -> None:
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e1 = _FakeAgentExec("agentA", "One")
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e2 = _FakeAgentExec("agentB", "Two")
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def summarize(results: list[AgentExecutorResponse]) -> str: # type: ignore[override]
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return str(len(results))
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wf = ConcurrentBuilder(participants=[e1, e2]).with_aggregator(summarize).build()
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assert "summarize" in wf.executors
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aggregator = wf.executors["summarize"]
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assert aggregator.id == "summarize"
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async def test_concurrent_with_aggregator_executor_instance() -> None:
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"""Test with_aggregator using an Executor instance (not factory)."""
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class CustomAggregator(Executor):
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@handler
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async def aggregate(self, results: list[AgentExecutorResponse], ctx: WorkflowContext[Any, str]) -> None:
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texts: list[str] = []
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for r in results:
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msgs: list[Message] = r.agent_response.messages
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texts.append(msgs[-1].text if msgs else "")
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await ctx.yield_output(" & ".join(sorted(texts)))
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e1 = _FakeAgentExec("agentA", "One")
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e2 = _FakeAgentExec("agentB", "Two")
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aggregator_instance = CustomAggregator(id="instance_aggregator")
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wf = ConcurrentBuilder(participants=[e1, e2]).with_aggregator(aggregator_instance).build()
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completed = False
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output: str | None = None
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async for ev in wf.run("prompt: instance test", stream=True):
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if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
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completed = True
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elif ev.type == "output":
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output = cast(str, ev.data)
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if completed and output is not None:
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break
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assert completed
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assert output is not None
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assert isinstance(output, str)
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assert output == "One & Two"
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def test_concurrent_builder_rejects_multiple_calls_to_with_aggregator() -> None:
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"""Test that multiple calls to .with_aggregator() raises an error."""
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def summarize(results: list[AgentExecutorResponse]) -> str: # type: ignore[override]
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return str(len(results))
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with pytest.raises(ValueError, match=r"with_aggregator\(\) has already been called"):
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(
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ConcurrentBuilder(participants=[_FakeAgentExec("a", "A")])
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.with_aggregator(summarize)
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.with_aggregator(summarize)
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)
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async def test_concurrent_checkpoint_resume_round_trip() -> None:
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storage = InMemoryCheckpointStorage()
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participants = (
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_FakeAgentExec("agentA", "Alpha"),
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_FakeAgentExec("agentB", "Beta"),
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_FakeAgentExec("agentC", "Gamma"),
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)
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wf = ConcurrentBuilder(participants=list(participants), checkpoint_storage=storage).build()
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baseline_output: AgentResponse | None = None
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async for ev in wf.run("checkpoint concurrent", stream=True):
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if ev.type == "output":
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baseline_output = ev.data # type: ignore[assignment]
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if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
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break
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assert baseline_output is not None
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checkpoints = await storage.list_checkpoints(workflow_name=wf.name)
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assert checkpoints
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checkpoints.sort(key=lambda cp: cp.timestamp)
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resume_checkpoint = checkpoints[1]
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resumed_participants = (
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_FakeAgentExec("agentA", "Alpha"),
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_FakeAgentExec("agentB", "Beta"),
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_FakeAgentExec("agentC", "Gamma"),
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)
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wf_resume = ConcurrentBuilder(participants=list(resumed_participants), checkpoint_storage=storage).build()
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resumed_output: AgentResponse | None = None
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async for ev in wf_resume.run(checkpoint_id=resume_checkpoint.checkpoint_id, stream=True):
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if ev.type == "output":
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resumed_output = ev.data # type: ignore[assignment]
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if ev.type == "status" and ev.state in (
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WorkflowRunState.IDLE,
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WorkflowRunState.IDLE_WITH_PENDING_REQUESTS,
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):
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break
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assert resumed_output is not None
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assert [m.role for m in resumed_output.messages] == [m.role for m in baseline_output.messages]
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assert [m.text for m in resumed_output.messages] == [m.text for m in baseline_output.messages]
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async def test_concurrent_checkpoint_runtime_only() -> None:
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"""Test checkpointing configured ONLY at runtime, not at build time."""
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storage = InMemoryCheckpointStorage()
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agents = [_FakeAgentExec(id="agent1", reply_text="A1"), _FakeAgentExec(id="agent2", reply_text="A2")]
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wf = ConcurrentBuilder(participants=agents).build()
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baseline_output: AgentResponse | None = None
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async for ev in wf.run("runtime checkpoint test", checkpoint_storage=storage, stream=True):
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if ev.type == "output":
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baseline_output = ev.data # type: ignore[assignment]
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if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
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break
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assert baseline_output is not None
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checkpoints = await storage.list_checkpoints(workflow_name=wf.name)
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assert len(checkpoints) >= 2, (
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"Expected at least 2 checkpoints. The first one is after the start executor, "
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"and the second one is after the first round of agent executions."
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)
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checkpoints.sort(key=lambda cp: cp.timestamp)
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resume_checkpoint = checkpoints[1]
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resumed_agents = [_FakeAgentExec(id="agent1", reply_text="A1"), _FakeAgentExec(id="agent2", reply_text="A2")]
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wf_resume = ConcurrentBuilder(participants=resumed_agents).build()
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resumed_output: AgentResponse | None = None
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async for ev in wf_resume.run(
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checkpoint_id=resume_checkpoint.checkpoint_id, checkpoint_storage=storage, stream=True
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):
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if ev.type == "output":
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resumed_output = ev.data # type: ignore[assignment]
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if ev.type == "status" and ev.state in (
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WorkflowRunState.IDLE,
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WorkflowRunState.IDLE_WITH_PENDING_REQUESTS,
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):
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break
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assert resumed_output is not None
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assert [m.role for m in resumed_output.messages] == [m.role for m in baseline_output.messages]
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async def test_concurrent_checkpoint_runtime_overrides_buildtime() -> None:
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"""Test that runtime checkpoint storage overrides build-time configuration."""
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import tempfile
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with tempfile.TemporaryDirectory() as temp_dir1, tempfile.TemporaryDirectory() as temp_dir2:
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from agent_framework._workflows._checkpoint import FileCheckpointStorage
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buildtime_storage = FileCheckpointStorage(temp_dir1)
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runtime_storage = FileCheckpointStorage(temp_dir2)
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agents = [_FakeAgentExec(id="agent1", reply_text="A1"), _FakeAgentExec(id="agent2", reply_text="A2")]
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wf = ConcurrentBuilder(participants=agents, checkpoint_storage=buildtime_storage).build()
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baseline_output: list[Message] | None = None
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async for ev in wf.run("override test", checkpoint_storage=runtime_storage, stream=True):
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if ev.type == "output":
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baseline_output = ev.data # type: ignore[assignment]
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if ev.type == "status" and ev.state == WorkflowRunState.IDLE:
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break
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assert baseline_output is not None
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buildtime_checkpoints = await buildtime_storage.list_checkpoints(workflow_name=wf.name)
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runtime_checkpoints = await runtime_storage.list_checkpoints(workflow_name=wf.name)
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assert len(runtime_checkpoints) > 0, "Runtime storage should have checkpoints"
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assert len(buildtime_checkpoints) == 0, "Build-time storage should have no checkpoints when overridden"
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async def test_concurrent_builder_reusable_after_build_with_participants() -> None:
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"""Test that the builder can be reused to build multiple identical workflows with participants()."""
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e1 = _FakeAgentExec("agentA", "One")
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e2 = _FakeAgentExec("agentB", "Two")
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builder = ConcurrentBuilder(participants=[e1, e2])
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builder.build()
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assert builder._participants[0] is e1 # type: ignore
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assert builder._participants[1] is e2 # type: ignore
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class _EchoAgent(BaseAgent):
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"""Simple agent that appends a single assistant message with its name."""
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@overload
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def run(
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self,
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messages: AgentRunInputs | None = ...,
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*,
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stream: Literal[False] = ...,
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session: AgentSession | None = ...,
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**kwargs: Any,
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) -> Awaitable[AgentResponse[Any]]: ...
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@overload
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def run(
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self,
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messages: AgentRunInputs | None = ...,
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*,
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stream: Literal[True],
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session: AgentSession | None = ...,
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**kwargs: Any,
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) -> ResponseStream[AgentResponseUpdate, AgentResponse[Any]]: ...
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def run(
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self,
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messages: AgentRunInputs | None = None,
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*,
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stream: bool = False,
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session: AgentSession | None = None,
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**kwargs: Any,
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) -> Awaitable[AgentResponse[Any]] | ResponseStream[AgentResponseUpdate, AgentResponse[Any]]:
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if stream:
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async def _stream() -> AsyncIterable[AgentResponseUpdate]:
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yield AgentResponseUpdate(contents=[Content.from_text(text=f"{self.name} reply")])
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return ResponseStream(_stream(), finalizer=AgentResponse.from_updates)
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async def _run() -> AgentResponse:
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return AgentResponse(messages=[Message("assistant", [f"{self.name} reply"])])
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return _run()
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