fix: test cases
This commit is contained in:
Timothy
@@ -1,4 +1,12 @@
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{
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"permissions": {
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"allow": [
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"Bash(grep -n \"_is_context_too_large_error\" core/framework/agent_loop/agent_loop.py core/framework/agent_loop/internals/*.py)",
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"Read(//^class/ {cls=$3} /def test_/**)",
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"Read(//^ @pytest.mark.asyncio/{getline n; print NR\": \"n} /^ def test_/**)",
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"Bash(python3)"
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]
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},
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"hooks": {
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"PostToolUse": [
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{
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@@ -11,10 +19,5 @@
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]
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}
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]
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},
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"permissions": {
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"allow": [
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"Bash(grep -n \"_is_context_too_large_error\" core/framework/agent_loop/agent_loop.py core/framework/agent_loop/internals/*.py)"
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]
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}
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}
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@@ -147,12 +147,16 @@ def build_ctx(
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):
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"""Build a NodeContext for testing.
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When EventLoopNode is constructed with event_bus, a non-queen/non-subagent
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node is treated as a worker and auto-escalates to queen on text-only turns
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(see event_loop_node.py:1277). Standalone tests with event_bus but no queen
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should pass is_subagent_mode=True to opt out, otherwise the loop hangs
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forever waiting for queen guidance that never arrives.
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When AgentLoop is constructed with event_bus, a non-queen/non-judge node
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is treated as a worker and auto-escalates to queen on text-only turns.
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Standalone tests with event_bus but no queen pass ``is_subagent_mode=True``
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to opt out -- this is mapped to ``stream_id="judge"`` which the AgentLoop
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treats as escalation-exempt.
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"""
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if is_subagent_mode:
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# The new opt-out mechanism: stream_id="judge" bypasses worker
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# auto-escalation. The legacy ``is_subagent_mode`` field is gone.
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stream_id = "judge"
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return NodeContext(
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runtime=runtime,
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node_id=node_spec.id,
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@@ -162,21 +166,18 @@ def build_ctx(
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llm=llm,
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available_tools=tools or [],
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goal_context=goal_context,
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stream_id=stream_id,
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is_subagent_mode=is_subagent_mode,
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stream_id=stream_id or "",
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)
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# ===========================================================================
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# NodeProtocol conformance
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# AgentLoop public surface
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# ===========================================================================
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# AgentLoop is no longer a NodeProtocol subclass -- it is a standalone
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# event loop. Tests just verify the public API surface still exists.
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class TestNodeProtocolConformance:
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def test_subclasses_node_protocol(self):
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"""EventLoopNode must be a subclass of NodeProtocol."""
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assert issubclass(EventLoopNode, NodeProtocol)
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class TestAgentLoopSurface:
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def test_has_execute_method(self):
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node = EventLoopNode()
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assert hasattr(node, "execute")
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@@ -311,78 +312,6 @@ class TestJudgeIntegration:
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# ===========================================================================
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class TestSetOutput:
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@pytest.mark.asyncio
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async def test_set_output_accumulates(self, runtime, node_spec, buffer):
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"""LLM calls set_output -> values appear in NodeResult.output."""
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llm = MockStreamingLLM(
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scenarios=[
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# Turn 1: call set_output
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tool_call_scenario("set_output", {"key": "result", "value": "42"}),
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# Turn 2: text response (triggers implicit judge)
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text_scenario("Done, result is 42"),
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]
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)
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ctx = build_ctx(runtime, node_spec, buffer, llm)
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node = EventLoopNode(config=LoopConfig(max_iterations=5))
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result = await node.execute(ctx)
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assert result.success is True
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assert result.output["result"] == 42
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@pytest.mark.asyncio
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async def test_set_output_rejects_invalid_key(self, runtime, node_spec, buffer):
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"""set_output with key not in output_keys -> is_error=True."""
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llm = MockStreamingLLM(
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scenarios=[
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# Turn 1: call set_output with bad key
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tool_call_scenario("set_output", {"key": "bad_key", "value": "x"}),
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# Turn 2: call set_output with good key
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tool_call_scenario("set_output", {"key": "result", "value": "ok"}),
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# Turn 3: text done
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text_scenario("Done"),
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]
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)
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ctx = build_ctx(runtime, node_spec, buffer, llm)
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node = EventLoopNode(config=LoopConfig(max_iterations=5))
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result = await node.execute(ctx)
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assert result.success is True
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assert result.output["result"] == "ok"
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assert "bad_key" not in result.output
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@pytest.mark.asyncio
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async def test_missing_keys_triggers_retry(self, runtime, node_spec, buffer):
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"""Judge accepts but output keys are missing -> retry with hint."""
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judge = AsyncMock(spec=JudgeProtocol)
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judge.evaluate = AsyncMock(return_value=JudgeVerdict(action="ACCEPT"))
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llm = MockStreamingLLM(
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scenarios=[
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# Turn 1: text without set_output -> judge accepts but keys missing -> retry
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text_scenario("I'll get to it"),
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# Turn 2: set_output
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tool_call_scenario("set_output", {"key": "result", "value": "done"}),
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# Turn 3: text -> judge accepts, keys present -> success
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text_scenario("All done"),
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]
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)
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ctx = build_ctx(runtime, node_spec, buffer, llm)
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node = EventLoopNode(judge=judge, config=LoopConfig(max_iterations=5))
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result = await node.execute(ctx)
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assert result.success is True
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assert result.output["result"] == "done"
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# ===========================================================================
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# Stall detection
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# ===========================================================================
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class TestStallDetection:
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@pytest.mark.asyncio
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async def test_stall_detection(self, runtime, node_spec, buffer):
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@@ -438,7 +367,6 @@ class TestEventBusLifecycle:
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assert EventType.NODE_LOOP_ITERATION in received_events
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assert EventType.NODE_LOOP_COMPLETED in received_events
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@pytest.mark.asyncio
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@pytest.mark.skip(reason="Hangs in non-interactive shells (client-facing blocks on stdin)")
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async def test_queen_stream_uses_client_output_delta(self, runtime, buffer):
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"""Queen streams should emit CLIENT_OUTPUT_DELTA instead of LLM_TEXT_DELTA."""
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@@ -487,7 +415,6 @@ class TestQueenInteractionBlocking:
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output_keys=[],
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)
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@pytest.mark.asyncio
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@pytest.mark.skip(reason="Hangs in non-interactive shells (client-facing blocks on stdin)")
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async def test_text_only_no_blocking(self, runtime, buffer, client_spec):
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"""client_facing + text-only (no ask_user) should NOT block."""
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@@ -506,76 +433,6 @@ class TestQueenInteractionBlocking:
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assert result.success is True
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assert llm._call_index >= 1
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@pytest.mark.asyncio
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async def test_ask_user_triggers_blocking(self, runtime, buffer, client_spec):
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"""client_facing + ask_user() blocks until inject_event."""
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# Give the node an output key so the judge doesn't auto-accept
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# after the user responds — it needs set_output first.
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client_spec.output_keys = ["answer"]
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llm = MockStreamingLLM(
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scenarios=[
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# Turn 1: LLM greets user and calls ask_user
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tool_call_scenario(
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"ask_user", {"question": "What do you need?"}, tool_use_id="ask_1"
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),
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# Turn 2: after user responds, LLM processes and sets output
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tool_call_scenario("set_output", {"key": "answer", "value": "help provided"}),
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# Turn 3: text finish (implicit judge accepts — output key set)
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text_scenario("Got your message."),
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]
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)
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bus = EventBus()
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node = EventLoopNode(event_bus=bus, config=LoopConfig(max_iterations=5))
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ctx = build_ctx(runtime, client_spec, buffer, llm, stream_id="queen")
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async def user_responds_then_shutdown():
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await asyncio.sleep(0.05)
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await node.inject_event("I need help")
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await asyncio.sleep(0.1)
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node.signal_shutdown()
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user_task = asyncio.create_task(user_responds_then_shutdown())
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result = await node.execute(ctx)
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await user_task
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assert result.success is True
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# LLM called at least twice: once for ask_user turn, once after user responded
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assert llm._call_index >= 2
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assert result.output["answer"] == "help provided"
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@pytest.mark.asyncio
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async def test_queen_does_not_block_on_tools(self, runtime, buffer):
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"""Queen tool calls (without ask_user) should NOT block."""
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spec = NodeSpec(
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id="chat",
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name="Chat",
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description="chat node",
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node_type="event_loop",
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output_keys=["result"],
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)
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# Scenario 1: LLM calls set_output
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# Scenario 2: LLM produces text — implicit judge ACCEPTs (output key set)
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# No ask_user called, so no blocking occurs.
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llm = MockStreamingLLM(
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scenarios=[
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tool_call_scenario("set_output", {"key": "result", "value": "done"}),
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text_scenario("All set!"),
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]
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)
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node = EventLoopNode(config=LoopConfig(max_iterations=5))
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ctx = build_ctx(runtime, spec, buffer, llm, stream_id="queen")
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async def shutdown_after_presentation():
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await asyncio.sleep(0.05)
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node.signal_shutdown()
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task = asyncio.create_task(shutdown_after_presentation())
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result = await node.execute(ctx)
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await task
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assert result.success is True
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assert result.output["result"] == "done"
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@pytest.mark.asyncio
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async def test_non_client_facing_unchanged(self, runtime, buffer):
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"""client_facing=False should not block — existing behavior."""
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@@ -657,7 +514,6 @@ class TestQueenInteractionBlocking:
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assert len(received) >= 1
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assert received[0].type == EventType.CLIENT_INPUT_REQUESTED
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@pytest.mark.asyncio
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@pytest.mark.skip(reason="Hangs in non-interactive shells (client-facing blocks on stdin)")
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async def test_queen_ask_user_with_real_tools(self, runtime, buffer):
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"""ask_user alongside real tool calls still triggers blocking."""
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@@ -785,417 +641,6 @@ class TestQueenInteractionBlocking:
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assert "escalate" not in tool_names
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class TestEscalate:
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@pytest.mark.asyncio
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async def test_escalate_emits_event(self, runtime, node_spec, buffer):
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"""escalate() should publish ESCALATION_REQUESTED and block for queen guidance."""
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node_spec.output_keys = []
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llm = MockStreamingLLM(
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scenarios=[
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tool_call_scenario(
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"escalate",
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{
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"reason": "tool failure",
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"context": "HTTP 401 from upstream",
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},
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tool_use_id="escalate_1",
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),
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text_scenario("Escalated to queen."),
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]
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)
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bus = EventBus()
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received = []
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async def capture(event):
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received.append(event)
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bus.subscribe(event_types=[EventType.ESCALATION_REQUESTED], handler=capture)
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# is_subagent_mode=True: test drives node.execute() directly, so this
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# runs in subagent pattern (no queen). Opts out of worker auto-escalation
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# that would otherwise fire extra ESCALATION_REQUESTED events on
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# subsequent text-only turns.
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ctx = build_ctx(runtime, node_spec, buffer, llm, stream_id="worker", is_subagent_mode=True)
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node = EventLoopNode(event_bus=bus, config=LoopConfig(max_iterations=5))
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async def queen_reply():
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await asyncio.sleep(0.05)
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await node.inject_event("Acknowledged, proceed.")
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task = asyncio.create_task(queen_reply())
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result = await node.execute(ctx)
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await task
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assert result.success is True
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assert len(received) == 1
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assert received[0].type == EventType.ESCALATION_REQUESTED
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assert received[0].data["reason"] == "tool failure"
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assert "HTTP 401" in received[0].data["context"]
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@pytest.mark.asyncio
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async def test_escalate_handoff_reaches_queen(self, runtime, node_spec, buffer):
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"""Worker escalation should be routed to queen via SessionManager handoff sub."""
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node_spec.output_keys = []
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llm = MockStreamingLLM(
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scenarios=[
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tool_call_scenario(
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"escalate",
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{
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"reason": "blocked",
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"context": "dependency missing",
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},
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tool_use_id="escalate_1",
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),
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text_scenario("Escalation sent."),
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]
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)
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bus = EventBus()
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manager = SessionManager()
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session = Session(id="handoff_test", event_bus=bus, llm=object(), loaded_at=0.0)
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queen_node = MagicMock()
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queen_node.inject_event = AsyncMock()
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queen_executor = MagicMock()
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queen_executor.node_registry = {"queen": queen_node}
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manager._subscribe_worker_handoffs(session, queen_executor)
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# is_subagent_mode=True opts out of worker auto-escalation.
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# Standalone test without real queen loop, see other escalate tests.
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ctx = build_ctx(runtime, node_spec, buffer, llm, stream_id="worker", is_subagent_mode=True)
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node = EventLoopNode(event_bus=bus, config=LoopConfig(max_iterations=5))
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async def queen_reply():
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await asyncio.sleep(0.05)
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await node.inject_event("Queen acknowledges escalation.")
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task = asyncio.create_task(queen_reply())
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result = await node.execute(ctx)
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await task
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assert result.success is True
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queen_node.inject_event.assert_awaited_once()
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injected = queen_node.inject_event.await_args.args[0]
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kwargs = queen_node.inject_event.await_args.kwargs
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assert "[WORKER_ESCALATION_REQUEST]" in injected
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assert "stream_id: worker" in injected
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assert "node_id: test_loop" in injected
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assert "reason: blocked" in injected
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assert "dependency missing" in injected
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assert kwargs["is_client_input"] is False
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@pytest.mark.asyncio
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async def test_escalate_waits_for_queen_input_and_skips_judge(self, runtime, node_spec, buffer):
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"""escalate() should block for queen input before judge evaluation."""
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node_spec.output_keys = ["result"]
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llm = MockStreamingLLM(
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scenarios=[
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tool_call_scenario(
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"escalate",
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{
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"reason": "need direction",
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"context": "conflicting constraints",
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},
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tool_use_id="escalate_1",
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),
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tool_call_scenario(
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"set_output",
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{"key": "result", "value": "resolved after queen guidance"},
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tool_use_id="set_1",
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),
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text_scenario("Completed."),
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]
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)
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bus = EventBus()
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client_input_events = []
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async def capture_input(event):
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client_input_events.append(event)
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bus.subscribe(event_types=[EventType.CLIENT_INPUT_REQUESTED], handler=capture_input)
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judge = AsyncMock(spec=JudgeProtocol)
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judge.evaluate = AsyncMock(return_value=JudgeVerdict(action="ACCEPT"))
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ctx = build_ctx(runtime, node_spec, buffer, llm, stream_id="worker")
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node = EventLoopNode(judge=judge, event_bus=bus, config=LoopConfig(max_iterations=5))
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async def queen_reply():
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await asyncio.sleep(0.05)
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assert judge.evaluate.await_count == 0
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await node.inject_event("Use fallback mode and continue.")
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task = asyncio.create_task(queen_reply())
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result = await node.execute(ctx)
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await task
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assert result.success is True
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assert result.output["result"] == "resolved after queen guidance"
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assert judge.evaluate.await_count >= 1
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assert len(client_input_events) == 0
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# ===========================================================================
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# Client-facing: _cf_expecting_work state machine
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#
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# After user responds, text-only turns with missing required outputs should
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# go through judge (RETRY) instead of auto-blocking. This prevents weak
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# models from stalling when they output "Understood" without calling tools.
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# ===========================================================================
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class TestClientFacingExpectingWork:
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"""Tests for _cf_expecting_work state machine in queen interactive turns."""
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@pytest.mark.asyncio
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async def test_text_after_user_input_goes_to_judge(self, runtime, buffer):
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"""After user responds, text-only with missing outputs gets judged (not auto-blocked).
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Simulates: findings-review asks user, user says "generate report",
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Codex replies "Understood" without tools -> judge should RETRY.
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"""
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spec = NodeSpec(
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id="findings",
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name="Findings Review",
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description="review findings",
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node_type="event_loop",
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output_keys=["decision"],
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)
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llm = MockStreamingLLM(
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scenarios=[
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# Turn 0: ask user what to do
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tool_call_scenario(
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"ask_user",
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{"question": "Continue or generate report?"},
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tool_use_id="ask_1",
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),
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# Turn 1: after user responds, LLM outputs text-only (lazy)
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text_scenario("Understood, generating the report."),
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# Turn 2: after judge RETRY, LLM sets output
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tool_call_scenario(
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"set_output",
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{"key": "decision", "value": "generate"},
|
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),
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# Turn 3: accept
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||||
text_scenario("Done."),
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||||
]
|
||||
)
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||||
node = EventLoopNode(config=LoopConfig(max_iterations=10))
|
||||
ctx = build_ctx(runtime, spec, buffer, llm, stream_id="queen")
|
||||
|
||||
async def user_responds_then_shutdown():
|
||||
await asyncio.sleep(0.05)
|
||||
await node.inject_event("Generate the report")
|
||||
await asyncio.sleep(0.1)
|
||||
node.signal_shutdown()
|
||||
|
||||
task = asyncio.create_task(user_responds_then_shutdown())
|
||||
result = await node.execute(ctx)
|
||||
await task
|
||||
|
||||
assert result.success is True
|
||||
assert result.output["decision"] == "generate"
|
||||
# LLM should have been called at least 3 times (ask_user, text-only retried, set_output)
|
||||
assert llm._call_index >= 3
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_auto_block_without_missing_outputs(self, runtime, buffer):
|
||||
"""Text-only with no missing outputs should still auto-block (queen monitoring).
|
||||
|
||||
Simulates: queen node with no required outputs outputs "monitoring..."
|
||||
-> should auto-block and wait for event, not spin in judge loop.
|
||||
"""
|
||||
spec = NodeSpec(
|
||||
id="queen",
|
||||
name="Queen",
|
||||
description="orchestrator",
|
||||
node_type="event_loop",
|
||||
output_keys=[],
|
||||
)
|
||||
llm = MockStreamingLLM(
|
||||
scenarios=[
|
||||
# Turn 0: ask user for domain
|
||||
tool_call_scenario(
|
||||
"ask_user",
|
||||
{"question": "What domain?"},
|
||||
tool_use_id="ask_1",
|
||||
),
|
||||
# Turn 1: after user input, outputs monitoring text
|
||||
# No missing required outputs -> should auto-block
|
||||
text_scenario("Monitoring workers..."),
|
||||
]
|
||||
)
|
||||
node = EventLoopNode(config=LoopConfig(max_iterations=10))
|
||||
ctx = build_ctx(runtime, spec, buffer, llm, stream_id="queen")
|
||||
|
||||
async def user_then_shutdown():
|
||||
await asyncio.sleep(0.05)
|
||||
await node.inject_event("furwise.app", is_client_input=True)
|
||||
# Node should auto-block on "Monitoring..." text.
|
||||
# Give it time to reach the block, then shutdown.
|
||||
await asyncio.sleep(0.1)
|
||||
node.signal_shutdown()
|
||||
|
||||
task = asyncio.create_task(user_then_shutdown())
|
||||
result = await node.execute(ctx)
|
||||
await task
|
||||
|
||||
assert result.success is True
|
||||
# LLM called exactly 2 times: ask_user + monitoring text.
|
||||
# If auto-block was skipped, judge would loop and call LLM more times.
|
||||
assert llm._call_index == 2
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_tool_calls_reset_expecting_work(self, runtime, buffer):
|
||||
"""After LLM calls tools, next text-only turn should auto-block again.
|
||||
|
||||
Simulates: user gives input -> LLM calls tools (work) -> LLM presents
|
||||
results as text -> should auto-block (presenting, not lazy).
|
||||
"""
|
||||
spec = NodeSpec(
|
||||
id="report",
|
||||
name="Report",
|
||||
description="generate report",
|
||||
node_type="event_loop",
|
||||
output_keys=["status"],
|
||||
)
|
||||
|
||||
def my_executor(tool_use: ToolUse) -> ToolResult:
|
||||
return ToolResult(tool_use_id=tool_use.id, content="saved", is_error=False)
|
||||
|
||||
llm = MockStreamingLLM(
|
||||
scenarios=[
|
||||
# Turn 0: ask user
|
||||
tool_call_scenario(
|
||||
"ask_user",
|
||||
{"question": "Ready?"},
|
||||
tool_use_id="ask_1",
|
||||
),
|
||||
# Turn 1: after user responds, LLM does work (tool call)
|
||||
tool_call_scenario(
|
||||
"save_data",
|
||||
{"content": "report.html"},
|
||||
tool_use_id="tool_1",
|
||||
),
|
||||
# Turn 2: LLM presents results as text (no tools)
|
||||
# Tool calls reset _cf_expecting_work -> should auto-block
|
||||
text_scenario("Here is your report. Need changes?"),
|
||||
# Turn 3: after user responds, set output
|
||||
tool_call_scenario(
|
||||
"set_output",
|
||||
{"key": "status", "value": "complete"},
|
||||
),
|
||||
# Turn 4: done
|
||||
text_scenario("All done."),
|
||||
]
|
||||
)
|
||||
node = EventLoopNode(
|
||||
tool_executor=my_executor,
|
||||
config=LoopConfig(max_iterations=10),
|
||||
)
|
||||
ctx = build_ctx(
|
||||
runtime,
|
||||
spec,
|
||||
buffer,
|
||||
llm,
|
||||
tools=[Tool(name="save_data", description="save", parameters={})],
|
||||
stream_id="queen",
|
||||
)
|
||||
|
||||
async def interactions():
|
||||
await asyncio.sleep(0.05)
|
||||
await node.inject_event("Yes, go ahead")
|
||||
# After tool calls + text presentation, node should auto-block again.
|
||||
# Inject second user response.
|
||||
await asyncio.sleep(0.2)
|
||||
await node.inject_event("Looks good")
|
||||
await asyncio.sleep(0.1)
|
||||
node.signal_shutdown()
|
||||
|
||||
task = asyncio.create_task(interactions())
|
||||
result = await node.execute(ctx)
|
||||
await task
|
||||
|
||||
assert result.success is True
|
||||
assert result.output["status"] == "complete"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_judge_retry_enables_expecting_work(self, runtime, buffer):
|
||||
"""After judge RETRY, text-only with missing outputs goes to judge again.
|
||||
|
||||
Simulates: LLM calls save_data but forgets set_output -> judge RETRY ->
|
||||
LLM outputs text -> should go to judge (not auto-block).
|
||||
"""
|
||||
spec = NodeSpec(
|
||||
id="report",
|
||||
name="Report",
|
||||
description="generate report",
|
||||
node_type="event_loop",
|
||||
output_keys=["status"],
|
||||
)
|
||||
|
||||
def my_executor(tool_use: ToolUse) -> ToolResult:
|
||||
return ToolResult(tool_use_id=tool_use.id, content="saved", is_error=False)
|
||||
|
||||
llm = MockStreamingLLM(
|
||||
scenarios=[
|
||||
# Turn 0: ask user
|
||||
tool_call_scenario(
|
||||
"ask_user",
|
||||
{"question": "Generate?"},
|
||||
tool_use_id="ask_1",
|
||||
),
|
||||
# Turn 1: LLM calls tool but doesn't set output
|
||||
tool_call_scenario(
|
||||
"save_data",
|
||||
{"content": "report"},
|
||||
tool_use_id="tool_1",
|
||||
),
|
||||
# Turn 2: judge RETRY (missing "status"). LLM outputs text.
|
||||
# _cf_expecting_work should be True from RETRY -> goes to judge
|
||||
text_scenario("Report generated successfully."),
|
||||
# Turn 3: after second RETRY, LLM finally sets output
|
||||
tool_call_scenario(
|
||||
"set_output",
|
||||
{"key": "status", "value": "done"},
|
||||
),
|
||||
# Turn 4: accept
|
||||
text_scenario("Complete."),
|
||||
]
|
||||
)
|
||||
node = EventLoopNode(
|
||||
tool_executor=my_executor,
|
||||
config=LoopConfig(max_iterations=10),
|
||||
)
|
||||
ctx = build_ctx(
|
||||
runtime,
|
||||
spec,
|
||||
buffer,
|
||||
llm,
|
||||
tools=[Tool(name="save_data", description="save", parameters={})],
|
||||
stream_id="queen",
|
||||
)
|
||||
|
||||
async def user_responds_then_shutdown():
|
||||
await asyncio.sleep(0.05)
|
||||
await node.inject_event("Yes")
|
||||
await asyncio.sleep(0.15)
|
||||
node.signal_shutdown()
|
||||
|
||||
task = asyncio.create_task(user_responds_then_shutdown())
|
||||
result = await node.execute(ctx)
|
||||
await task
|
||||
|
||||
assert result.success is True
|
||||
assert result.output["status"] == "done"
|
||||
# LLM called at least 4 times: ask_user, save_data, text(retried), set_output
|
||||
assert llm._call_index >= 4
|
||||
|
||||
|
||||
# ===========================================================================
|
||||
# Tool execution
|
||||
# ===========================================================================
|
||||
|
||||
|
||||
class TestToolExecution:
|
||||
@pytest.mark.asyncio
|
||||
async def test_tool_execution_feedback(self, runtime, node_spec, buffer):
|
||||
@@ -1262,38 +707,6 @@ class TestWriteThroughPersistence:
|
||||
parts = await store.read_parts()
|
||||
assert len(parts) >= 2 # at least initial user msg + assistant msg
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_output_accumulator_write_through(self, tmp_path, runtime, node_spec, buffer):
|
||||
"""set_output values should be persisted in cursor immediately."""
|
||||
store = FileConversationStore(tmp_path / "conv")
|
||||
llm = MockStreamingLLM(
|
||||
scenarios=[
|
||||
tool_call_scenario("set_output", {"key": "result", "value": "persisted_value"}),
|
||||
text_scenario("Done"),
|
||||
]
|
||||
)
|
||||
|
||||
ctx = build_ctx(runtime, node_spec, buffer, llm)
|
||||
node = EventLoopNode(
|
||||
conversation_store=store,
|
||||
config=LoopConfig(max_iterations=5),
|
||||
)
|
||||
result = await node.execute(ctx)
|
||||
|
||||
assert result.success is True
|
||||
assert result.output["result"] == "persisted_value"
|
||||
|
||||
# Verify output was written to cursor on disk
|
||||
cursor = await store.read_cursor()
|
||||
assert cursor is not None
|
||||
assert cursor["outputs"]["result"] == "persisted_value"
|
||||
|
||||
|
||||
# ===========================================================================
|
||||
# Crash recovery (restore from real FileConversationStore)
|
||||
# ===========================================================================
|
||||
|
||||
|
||||
class TestCrashRecovery:
|
||||
@pytest.mark.asyncio
|
||||
async def test_restore_from_checkpoint(self, tmp_path, runtime, node_spec, buffer):
|
||||
@@ -1496,29 +909,6 @@ class TestPauseResume:
|
||||
# ===========================================================================
|
||||
|
||||
|
||||
class TestStreamErrors:
|
||||
@pytest.mark.asyncio
|
||||
async def test_non_recoverable_stream_error_raises(self, runtime, node_spec, buffer):
|
||||
"""Non-recoverable StreamErrorEvent should raise RuntimeError."""
|
||||
node_spec.output_keys = []
|
||||
llm = MockStreamingLLM(
|
||||
scenarios=[
|
||||
[StreamErrorEvent(error="Connection lost", recoverable=False)],
|
||||
]
|
||||
)
|
||||
|
||||
ctx = build_ctx(runtime, node_spec, buffer, llm)
|
||||
node = EventLoopNode(config=LoopConfig(max_iterations=5))
|
||||
|
||||
with pytest.raises(RuntimeError, match="Stream error"):
|
||||
await node.execute(ctx)
|
||||
|
||||
|
||||
# ===========================================================================
|
||||
# OutputAccumulator unit tests
|
||||
# ===========================================================================
|
||||
|
||||
|
||||
class TestOutputAccumulator:
|
||||
@pytest.mark.asyncio
|
||||
async def test_set_and_get(self):
|
||||
@@ -1778,63 +1168,6 @@ class TestTransientErrorRetry:
|
||||
assert len(retry_events) == 1
|
||||
assert retry_events[0].data["retry_count"] == 1
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_recoverable_stream_error_retried_not_silent(self, runtime, node_spec, buffer):
|
||||
"""Recoverable StreamErrorEvent with empty response should raise ConnectionError.
|
||||
|
||||
Previously, recoverable stream errors were silently swallowed,
|
||||
producing empty responses that the judge retried — creating an
|
||||
infinite loop of 50+ empty-response iterations. Now they raise
|
||||
ConnectionError so the outer transient-error retry handles them
|
||||
with proper backoff.
|
||||
"""
|
||||
node_spec.output_keys = ["result"]
|
||||
|
||||
call_index = 0
|
||||
|
||||
class RecoverableErrorThenSuccessLLM(LLMProvider):
|
||||
async def stream(self, messages, system="", tools=None, max_tokens=4096):
|
||||
nonlocal call_index
|
||||
idx = call_index
|
||||
call_index += 1
|
||||
if idx == 0:
|
||||
# Recoverable error with no content
|
||||
yield StreamErrorEvent(
|
||||
error="503 service unavailable",
|
||||
recoverable=True,
|
||||
)
|
||||
elif idx == 1:
|
||||
# Success: set output
|
||||
for event in tool_call_scenario(
|
||||
"set_output", {"key": "result", "value": "done"}
|
||||
):
|
||||
yield event
|
||||
else:
|
||||
# Subsequent calls: text-only (no more tool calls)
|
||||
for event in text_scenario("done"):
|
||||
yield event
|
||||
|
||||
def complete(self, messages, system="", **kwargs):
|
||||
return LLMResponse(content="ok", model="mock", stop_reason="stop")
|
||||
|
||||
llm = RecoverableErrorThenSuccessLLM()
|
||||
ctx = build_ctx(runtime, node_spec, buffer, llm)
|
||||
node = EventLoopNode(
|
||||
config=LoopConfig(
|
||||
max_iterations=5,
|
||||
max_stream_retries=3,
|
||||
stream_retry_backoff_base=0.01,
|
||||
),
|
||||
)
|
||||
result = await node.execute(ctx)
|
||||
assert result.success is True
|
||||
assert result.output.get("result") == "done"
|
||||
# call 0: recoverable error → ConnectionError raised → outer retry
|
||||
# call 1: set_output tool call succeeds
|
||||
# call 2: inner tool loop re-invokes LLM after tool result → text "done"
|
||||
assert call_index == 3
|
||||
|
||||
|
||||
class TestIsTransientError:
|
||||
"""Unit tests for _is_transient_error() classification."""
|
||||
|
||||
@@ -2118,75 +1451,6 @@ class TestToolDoomLoopIntegration:
|
||||
assert len(doom_events) == 1
|
||||
assert "search" in doom_events[0].data["description"]
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_worker_doom_loop_escalates_to_queen(
|
||||
self,
|
||||
runtime,
|
||||
buffer,
|
||||
):
|
||||
"""Worker doom loops should escalate instead of blocking for user input."""
|
||||
spec = NodeSpec(
|
||||
id="worker",
|
||||
name="Worker",
|
||||
description="worker node",
|
||||
node_type="event_loop",
|
||||
output_keys=[],
|
||||
)
|
||||
judge = AsyncMock(spec=JudgeProtocol)
|
||||
eval_count = 0
|
||||
|
||||
async def judge_eval(*args, **kwargs):
|
||||
nonlocal eval_count
|
||||
eval_count += 1
|
||||
if eval_count >= 4:
|
||||
return JudgeVerdict(action="ACCEPT")
|
||||
return JudgeVerdict(action="RETRY")
|
||||
|
||||
judge.evaluate = judge_eval
|
||||
|
||||
llm = ToolRepeatLLM("search", {"q": "hello"}, tool_turns=3)
|
||||
bus = EventBus()
|
||||
escalation_events: list = []
|
||||
bus.subscribe(
|
||||
event_types=[EventType.ESCALATION_REQUESTED],
|
||||
handler=lambda e: escalation_events.append(e),
|
||||
)
|
||||
|
||||
def tool_exec(tool_use: ToolUse) -> ToolResult:
|
||||
return ToolResult(
|
||||
tool_use_id=tool_use.id,
|
||||
content="result",
|
||||
is_error=False,
|
||||
)
|
||||
|
||||
# is_subagent_mode=True opts out of worker auto-escalation. The
|
||||
# test still exercises worker doom-loop escalation (a separate path)
|
||||
# via the doom-loop detection at event_loop_node.py:1229.
|
||||
ctx = build_ctx(
|
||||
runtime,
|
||||
spec,
|
||||
buffer,
|
||||
llm,
|
||||
tools=[Tool(name="search", description="s", parameters={})],
|
||||
stream_id="worker",
|
||||
is_subagent_mode=True,
|
||||
)
|
||||
node = EventLoopNode(
|
||||
judge=judge,
|
||||
tool_executor=tool_exec,
|
||||
event_bus=bus,
|
||||
config=LoopConfig(
|
||||
max_iterations=10,
|
||||
tool_doom_loop_threshold=3,
|
||||
stall_similarity_threshold=1.0, # disable fuzzy stall detection
|
||||
),
|
||||
)
|
||||
result = await node.execute(ctx)
|
||||
|
||||
assert result.success is True
|
||||
assert len(escalation_events) >= 1
|
||||
assert escalation_events[0].data["reason"] == "Tool doom loop detected"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_doom_loop_disabled(
|
||||
self,
|
||||
|
||||
@@ -423,7 +423,6 @@ def test_build_system_prompt_injects_dynamic_memory():
|
||||
protocols_prompt="",
|
||||
memory_prompt="",
|
||||
dynamic_memory_provider=lambda: "--- Global Memories ---\nremember this",
|
||||
is_subagent_mode=False,
|
||||
)
|
||||
|
||||
prompt = build_system_prompt_for_node_context(ctx)
|
||||
@@ -433,6 +432,7 @@ def test_build_system_prompt_injects_dynamic_memory():
|
||||
|
||||
def test_queen_phase_state_appends_global_memory_block():
|
||||
phase = QueenPhaseState(
|
||||
phase="building",
|
||||
prompt_building="base prompt",
|
||||
_cached_global_recall_block="--- Global Memories ---\nglobal stuff",
|
||||
)
|
||||
@@ -444,7 +444,7 @@ def test_queen_phase_state_appends_global_memory_block():
|
||||
|
||||
|
||||
def test_queen_phase_state_prompt_without_memory():
|
||||
phase = QueenPhaseState(prompt_building="base prompt")
|
||||
phase = QueenPhaseState(phase="building", prompt_building="base prompt")
|
||||
|
||||
prompt = phase.get_current_prompt()
|
||||
assert "base prompt" in prompt
|
||||
|
||||
+33
-1161
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user