EvoScientist-Multi/tests/test_expert_async_subagent.py

"""Tests for the skill-name-injecting AsyncSubAgentMiddleware subclass."""

from __future__ import annotations

import asyncio
from types import SimpleNamespace
from unittest.mock import AsyncMock, MagicMock, patch

import pytest

from EvoScientist.middleware.expert_async_subagent import (
    EvoAsyncSubAgentMiddleware,
    _build_run_input,
)


class _TestPayloadValidationRemoved:
    """Placeholder — the ``_payload_validation_error`` helper was deleted
    when ``payload`` was dropped from the tool schema (PR #391 review, X-4).
    The seven tests that lived here (``TestPayloadValidation``) no longer
    apply: subagent_type is validated by ``_validate_agent_type``,
    ``skill_name`` is injected by construction, and no other user-supplied
    fields reach ``client.runs.create(input=...)``. See
    ``TestBuildRunInput`` below and ``TestStartToolInvocation`` for the
    replacement coverage.
    """


# =============================================================================
# _build_run_input — the shared input-dict factory
# =============================================================================


class TestBuildRunInput:
    """``skill_name`` is injected for expert specs, absent for standard specs.
    The description always lands in ``messages`` verbatim — no LLM-authored
    key can overwrite it (was the pre-fix bug when ``payload`` was in scope).
    """

    def test_expert_spec_injects_skill_name(self):
        spec = {"name": "e", "graph_id": "g", "is_expert": True}
        result = _build_run_input(spec, "literature-review", "write a survey")
        assert result == {
            "messages": [{"role": "user", "content": "write a survey"}],
            "skill_name": "literature-review",
        }

    def test_standard_spec_matches_upstream_shape(self):
        """Standard specs (writing-agent, scheduler, ...) reach ``runs.create``
        with the upstream single-key shape — no ``skill_name`` injected."""
        spec = {"name": "writing-agent", "graph_id": "writing_agent"}
        result = _build_run_input(spec, "writing-agent", "hi")
        assert result == {"messages": [{"role": "user", "content": "hi"}]}

    def test_is_expert_false_treated_as_standard(self):
        """Explicit ``is_expert=False`` matches the default (absent) behaviour."""
        spec = {"name": "std", "graph_id": "writing_agent", "is_expert": False}
        result = _build_run_input(spec, "std", "hi")
        assert result == {"messages": [{"role": "user", "content": "hi"}]}

    def test_description_lands_verbatim(self):
        """Regression guard against the pre-fix bug where an LLM-authored
        ``payload`` could overwrite ``messages`` — description now travels
        through a channel the LLM cannot corrupt."""
        spec = {"name": "e", "graph_id": "g", "is_expert": True}
        result = _build_run_input(
            spec, "e", "write to ./artifacts/e/foo.md a summary of X"
        )
        assert result["messages"][0]["content"] == (
            "write to ./artifacts/e/foo.md a summary of X"
        )


# =============================================================================
# EvoAsyncSubAgentMiddleware — end-to-end tool invocation
# =============================================================================


def _standard_spec():
    return {
        "name": "writing-agent",
        "description": "std writer",
        "graph_id": "writing_agent",
    }


def _expert_spec():
    return {
        "name": "literature-review",
        "description": "expert lit review",
        "graph_id": "expert_container",
        "is_expert": True,
    }


class TestMiddlewareConstruction:
    def test_middleware_has_five_tools(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        names = [t.name for t in mw.tools]
        assert set(names) == {
            "start_async_task",
            "check_async_task",
            "update_async_task",
            "cancel_async_task",
            "list_async_tasks",
        }

    def test_start_tool_schema_matches_upstream(self):
        """The tool signature returned to upstream's exact shape when
        ``payload`` was dropped — schema is now ``deepagents``'s
        ``StartAsyncTaskSchema``."""
        from deepagents.middleware.async_subagents import StartAsyncTaskSchema

        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")
        assert start.args_schema is StartAsyncTaskSchema

    def test_construction_rejects_empty_subagents(self):
        with pytest.raises(ValueError, match="At least one async subagent"):
            EvoAsyncSubAgentMiddleware(async_subagents=[])

    def test_construction_rejects_duplicate_names(self):
        with pytest.raises(ValueError, match="Duplicate"):
            EvoAsyncSubAgentMiddleware(
                async_subagents=[_standard_spec(), _standard_spec()]
            )


def _fake_sync_client():
    client = MagicMock()
    client.threads.create.return_value = {"thread_id": "task-abc"}
    client.runs.create.return_value = {"run_id": "run-xyz"}
    return client


def _fake_async_client():
    client = MagicMock()
    client.threads.create = AsyncMock(return_value={"thread_id": "task-abc"})
    client.runs.create = AsyncMock(return_value={"run_id": "run-xyz"})
    return client


class TestStartToolInvocation:
    """Direct invocation of the start tool's sync function.

    Mocks ``_ClientCache.get_sync`` so we can assert on the ``input`` dict
    handed to ``runs.create`` without any real network round-trip.
    """

    def test_start_injects_skill_name_for_expert_spec(self):
        """The middleware sets ``input_dict['skill_name'] = subagent_type``
        by construction — the shared container graph resolves the right
        persona without a payload dict crossing the LLM channel."""
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_expert_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_sync_client()
        with patch(
            "EvoScientist.middleware.expert_async_subagent._ClientCache.get_sync",
            return_value=client,
        ):
            result = start.func(
                description="write to ./artifacts/literature-review/attn.md a survey on X",
                subagent_type="literature-review",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )

        client.runs.create.assert_called_once()
        kwargs = client.runs.create.call_args.kwargs
        assert kwargs["assistant_id"] == "expert_container"
        assert kwargs["input"]["messages"] == [
            {
                "role": "user",
                "content": (
                    "write to ./artifacts/literature-review/attn.md a survey on X"
                ),
            }
        ]
        assert kwargs["input"]["skill_name"] == "literature-review"
        assert "payload" not in kwargs["input"]
        assert "output_path" not in kwargs["input"]
        # Return value stamps the task into async_tasks state.
        assert "async_tasks" in result.update
        assert "task-abc" in result.update["async_tasks"]

    def test_start_injects_cfg_model_into_configurable(self):
        """cfg.model / cfg.provider land in ``config.configurable`` on every
        ``runs.create`` so the deployed graph re-resolves its chat model per
        run instead of using whatever was baked at container-build time.
        Without this the ``/model`` CLI switch silently doesn't propagate to
        expert launches.
        """
        from EvoScientist.config.settings import EvoScientistConfig

        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_expert_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_sync_client()
        fake_cfg = EvoScientistConfig(model="test-model-abc", provider="test-provider")
        with (
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_sync",
                return_value=client,
            ),
            patch("EvoScientist.EvoScientist._ensure_config", return_value=fake_cfg),
        ):
            start.func(
                description="w",
                subagent_type="literature-review",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )

        kwargs = client.runs.create.call_args.kwargs
        assert "config" in kwargs
        configurable = kwargs["config"]["configurable"]
        assert configurable["model"] == "test-model-abc"
        assert configurable["model_provider"] == "test-provider"

    def test_start_standard_spec_matches_upstream_input_shape(self):
        """Standard subagents (writing-agent, scheduler, ...) reach
        ``runs.create`` with the upstream single-key ``messages`` shape."""
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_sync_client()
        with patch(
            "EvoScientist.middleware.expert_async_subagent._ClientCache.get_sync",
            return_value=client,
        ):
            start.func(
                description="hi",
                subagent_type="writing-agent",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )
        kwargs = client.runs.create.call_args.kwargs
        assert kwargs["input"] == {"messages": [{"role": "user", "content": "hi"}]}

    def test_start_unknown_subagent_returns_error(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        # Patch the resolve-on-miss walk so the negative-miss path stays
        # hermetic — an unpatched call would read the real skills tree.
        with patch(
            "EvoScientist.subagents.expert_container_async"
            ".build_expert_async_subagent_specs",
            return_value=[],
        ):
            result = start.func(
                description="hi",
                subagent_type="does-not-exist",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )
        assert isinstance(result, str)
        assert "Unknown async subagent type" in result


class TestAstartToolInvocation:
    """Mirror ``TestStartToolInvocation`` against ``astart_async_task`` — the
    coroutine langgraph_api actually runs in production. Pre-fix zero
    coverage: X-iZhang flagged that a fix applied only to the sync body
    would leave tests green and production broken."""

    @pytest.mark.asyncio
    async def test_astart_injects_skill_name_for_expert_spec(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_expert_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_async_client()
        with patch(
            "EvoScientist.middleware.expert_async_subagent._ClientCache.get_async",
            return_value=client,
        ):
            result = await start.coroutine(
                description="write to ./artifacts/literature-review/attn.md a survey on X",
                subagent_type="literature-review",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )

        client.runs.create.assert_awaited_once()
        kwargs = client.runs.create.await_args.kwargs
        assert kwargs["assistant_id"] == "expert_container"
        assert kwargs["input"]["skill_name"] == "literature-review"
        assert kwargs["input"]["messages"][0]["content"].startswith(
            "write to ./artifacts/literature-review/attn.md"
        )
        assert "payload" not in kwargs["input"]
        assert "async_tasks" in result.update
        assert "task-abc" in result.update["async_tasks"]

    @pytest.mark.asyncio
    async def test_astart_injects_cfg_model_into_configurable(self):
        from EvoScientist.config.settings import EvoScientistConfig

        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_expert_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_async_client()
        fake_cfg = EvoScientistConfig(model="test-model-abc", provider="test-provider")
        with (
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_async",
                return_value=client,
            ),
            patch("EvoScientist.EvoScientist._ensure_config", return_value=fake_cfg),
        ):
            await start.coroutine(
                description="w",
                subagent_type="literature-review",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )

        kwargs = client.runs.create.await_args.kwargs
        assert "config" in kwargs
        configurable = kwargs["config"]["configurable"]
        assert configurable["model"] == "test-model-abc"
        assert configurable["model_provider"] == "test-provider"

    @pytest.mark.asyncio
    async def test_astart_standard_spec_matches_upstream_input_shape(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_async_client()
        with patch(
            "EvoScientist.middleware.expert_async_subagent._ClientCache.get_async",
            return_value=client,
        ):
            await start.coroutine(
                description="hi",
                subagent_type="writing-agent",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )
        kwargs = client.runs.create.await_args.kwargs
        assert kwargs["input"] == {"messages": [{"role": "user", "content": "hi"}]}

    @pytest.mark.asyncio
    async def test_astart_unknown_subagent_returns_error(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        # Patch the resolve-on-miss walk — see the sync twin.
        with patch(
            "EvoScientist.subagents.expert_container_async"
            ".build_expert_async_subagent_specs",
            return_value=[],
        ):
            result = await start.coroutine(
                description="hi",
                subagent_type="does-not-exist",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )
        assert isinstance(result, str)
        assert "Unknown async subagent type" in result


def _newly_installed_expert_spec():
    """An expert spec as ``build_expert_async_subagent_specs`` would return
    it for a skill installed after the agent was built."""
    return {
        "name": "brand-new-expert",
        "description": "freshly installed expert",
        "graph_id": "expert-container-async",
        "is_expert": True,
    }


class TestResolveOnMiss:
    """Resolve-on-miss: an unknown ``subagent_type`` that names a real,
    newly installed expert becomes dispatchable on the first launch —
    no agent rebuild, no restart. A name that is still unknown after one
    resolution walk gets upstream's error with the refreshed type list."""

    def test_unknown_expert_resolves_and_dispatches(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_sync_client()
        with (
            patch(
                "EvoScientist.subagents.expert_container_async"
                ".build_expert_async_subagent_specs",
                return_value=[_newly_installed_expert_spec()],
            ),
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_sync",
                return_value=client,
            ),
        ):
            result = start.func(
                description="hi",
                subagent_type="brand-new-expert",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )

        # Dispatch succeeded rather than returning the unknown-type error.
        assert "async_tasks" in result.update
        kwargs = client.runs.create.call_args.kwargs
        assert kwargs["input"]["skill_name"] == "brand-new-expert"

    def test_resolution_updates_the_watcher_dict(self):
        """The watcher holds a SEPARATE agent dict from ``agent_map``; the
        resolution must land in both or the completion notification for the
        newly resolved expert silently never fires (the watcher's
        ``get_async`` KeyError is swallowed by its ``try/except``)."""
        watcher_agents: dict = {}
        mw = EvoAsyncSubAgentMiddleware(
            async_subagents=[_standard_spec()], watcher_agents=watcher_agents
        )
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_sync_client()
        with (
            patch(
                "EvoScientist.subagents.expert_container_async"
                ".build_expert_async_subagent_specs",
                return_value=[_newly_installed_expert_spec()],
            ),
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_sync",
                return_value=client,
            ),
        ):
            start.func(
                description="hi",
                subagent_type="brand-new-expert",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )

        assert "brand-new-expert" in watcher_agents

    def test_resolution_never_overwrites_existing_entries(self):
        """``setdefault`` semantics: a spec already in ``agent_map`` keeps its
        identity — an overwrite could smuggle in a spec the running agent
        was not validated against (the constructor already raised on
        duplicate names at build time)."""
        incumbent = {
            "name": "literature-review",
            "description": "original description",
            "graph_id": "incumbent-graph",
            "is_expert": True,
        }
        challenger = {
            "name": "literature-review",
            "description": "different description",
            "graph_id": "challenger-graph",
            "is_expert": True,
        }
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[incumbent])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        # The miss-walk returns BOTH a new expert and a same-name challenger
        # for the incumbent; the dispatch goes to the new name so the walk
        # runs, then to the incumbent to observe which spec survived.
        client = _fake_sync_client()
        with (
            patch(
                "EvoScientist.subagents.expert_container_async"
                ".build_expert_async_subagent_specs",
                return_value=[challenger, _newly_installed_expert_spec()],
            ),
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_sync",
                return_value=client,
            ),
        ):
            start.func(
                description="hi",
                subagent_type="brand-new-expert",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )
            start.func(
                description="hi",
                subagent_type="literature-review",
                runtime=SimpleNamespace(tool_call_id="tc2"),
            )

        # The incumbent's graph_id served both the survivor check and the
        # dispatch: had the challenger overwritten it, this would be
        # "challenger-graph".
        assistant_ids = [
            call.kwargs["assistant_id"] for call in client.runs.create.call_args_list
        ]
        assert "incumbent-graph" in assistant_ids
        assert "challenger-graph" not in assistant_ids

    def test_negative_miss_returns_error_with_refreshed_list(self):
        """A hallucinated name is still an error after the one resolution
        walk — and the message's allowed-type list now includes names the
        walk just added (the second ``_validate_agent_type`` call reads the
        mutated map)."""
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        with patch(
            "EvoScientist.subagents.expert_container_async"
            ".build_expert_async_subagent_specs",
            return_value=[_newly_installed_expert_spec()],
        ):
            result = start.func(
                description="hi",
                subagent_type="still-does-not-exist",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )
        assert isinstance(result, str)
        assert "Unknown async subagent type" in result
        assert "brand-new-expert" in result

    def test_resolution_uses_the_construction_cfg(self):
        """The miss-walk must spec against the cfg the agent was constructed
        with, not a fresh ``get_effective_config()`` read. Re-deriving config
        at dispatch time would let a mid-session ``langgraph_dev_port`` change
        spec a newly resolved expert onto a port the running dev subprocess
        is not on — dispatch accepts the name, only ``runs.create`` fails."""
        construction_cfg = SimpleNamespace(enable_async_subagents=True)
        mw = EvoAsyncSubAgentMiddleware(
            async_subagents=[_standard_spec()], cfg=construction_cfg
        )
        start = next(t for t in mw.tools if t.name == "start_async_task")

        captured: dict = {}

        def capture_cfg(cfg=None, **kwargs):
            captured["cfg"] = cfg
            return [_newly_installed_expert_spec()]

        with patch(
            "EvoScientist.subagents.expert_container_async"
            ".build_expert_async_subagent_specs",
            side_effect=capture_cfg,
        ):
            start.func(
                description="hi",
                subagent_type="brand-new-expert",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )

        assert captured["cfg"] is construction_cfg


class TestAstartResolveOnMiss:
    """Async twins of ``TestResolveOnMiss`` — the coroutine langgraph_api
    actually runs in production."""

    @pytest.mark.asyncio
    async def test_astart_unknown_expert_resolves_and_dispatches(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_async_client()
        to_thread_calls = []

        async def _fake_to_thread(fn, *args):
            to_thread_calls.append(fn.__name__)
            return fn(*args)

        with (
            patch(
                "EvoScientist.subagents.expert_container_async"
                ".build_expert_async_subagent_specs",
                return_value=[_newly_installed_expert_spec()],
            ),
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_async",
                return_value=client,
            ),
            patch("asyncio.to_thread", new=_fake_to_thread),
        ):
            result = await start.coroutine(
                description="hi",
                subagent_type="brand-new-expert",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )

        assert "async_tasks" in result.update
        kwargs = client.runs.create.await_args.kwargs
        assert kwargs["input"]["skill_name"] == "brand-new-expert"
        # The resolution ran off the event loop — langgraph-dev's blockbuster
        # guard turns a skills-tree walk on the loop into a BlockingError.
        assert to_thread_calls == ["_resolve_merge_validate"]

    @pytest.mark.asyncio
    async def test_astart_resolution_updates_the_watcher_dict(self):
        watcher_agents: dict = {}
        mw = EvoAsyncSubAgentMiddleware(
            async_subagents=[_standard_spec()], watcher_agents=watcher_agents
        )
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_async_client()
        with (
            patch(
                "EvoScientist.subagents.expert_container_async"
                ".build_expert_async_subagent_specs",
                return_value=[_newly_installed_expert_spec()],
            ),
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_async",
                return_value=client,
            ),
        ):
            await start.coroutine(
                description="hi",
                subagent_type="brand-new-expert",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )

        assert "brand-new-expert" in watcher_agents

    @pytest.mark.asyncio
    async def test_astart_negative_miss_returns_error(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        with patch(
            "EvoScientist.subagents.expert_container_async"
            ".build_expert_async_subagent_specs",
            return_value=[],
        ):
            result = await start.coroutine(
                description="hi",
                subagent_type="still-does-not-exist",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )
        assert isinstance(result, str)
        assert "Unknown async subagent type" in result

    @pytest.mark.asyncio
    async def test_astart_negative_miss_returns_refreshed_error(self):
        """The async miss path must honor the threaded call's return value:
        the error comes from the worker's merge-and-validate under the
        lock, so its allowed-type list already includes the names the walk
        just merged. A caller that dropped the ``to_thread`` result and
        re-derived the error from a stale message would lose the new
        names."""
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        with patch(
            "EvoScientist.subagents.expert_container_async"
            ".build_expert_async_subagent_specs",
            return_value=[_newly_installed_expert_spec()],
        ):
            result = await start.coroutine(
                description="hi",
                subagent_type="still-does-not-exist",
                runtime=SimpleNamespace(tool_call_id="tc1"),
            )
        assert isinstance(result, str)
        assert "Unknown async subagent type" in result
        assert "brand-new-expert" in result

    @pytest.mark.asyncio
    async def test_astart_known_name_dispatch_skips_the_lock(self):
        """A known-name dispatch on the event loop must never touch
        ``_resolve_lock``: the miss check is a keyed lookup, and all lock
        work lives on the ``to_thread`` worker. Holding the lock from this
        coroutine pins the property — the dispatch completes while the
        lock is unavailable. The pre-reshape shape ran its validation
        under the lock on the loop and hung here until the timeout."""
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_async_client()
        acquired = mw._resolve_lock.acquire()
        assert acquired
        try:
            with patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_async",
                return_value=client,
            ):
                result = await asyncio.wait_for(
                    start.coroutine(
                        description="hi",
                        subagent_type="writing-agent",
                        runtime=SimpleNamespace(tool_call_id="tc1"),
                    ),
                    timeout=2.0,
                )
        finally:
            mw._resolve_lock.release()
        assert "async_tasks" in result.update


class TestResolveOnMissLocking:
    """The resolver's merge and the start tool's map iteration serialize on
    one lock. Deterministic, blocking-based — no timing lottery: each test
    blocks a participant on an event we control and asserts the other side
    genuinely waits for the lock."""

    def test_resolver_merge_waits_for_the_lock(self):
        """With the lock held by an unrelated holder, the resolver's merge
        must not insert into ``agent_map`` until the lock is released.
        Without the lock parameter (or without locking in the resolver),
        the ``setdefault`` lands immediately and the mid-hold assertion
        fails. The return value is the refreshed validation: ``None`` once
        the merged name resolves."""
        import threading
        import time

        from EvoScientist.middleware.expert_async_subagent import (
            _resolve_merge_validate,
        )

        agent_map: dict = {"writing-agent": _standard_spec()}
        watcher_agents: dict = {}
        lock = threading.Lock()
        done = threading.Event()

        def resolver():
            with patch(
                "EvoScientist.subagents.expert_container_async"
                ".build_expert_async_subagent_specs",
                return_value=[_newly_installed_expert_spec()],
            ):
                result = _resolve_merge_validate(
                    agent_map, watcher_agents, None, "brand-new-expert", lock
                )
            assert result is None
            done.set()

        with lock:
            thread = threading.Thread(target=resolver)
            thread.start()
            time.sleep(0.05)
            # The merge is locked out while we hold the lock.
            assert "brand-new-expert" not in agent_map

        thread.join(timeout=5)
        assert done.is_set()
        assert "brand-new-expert" in agent_map
        assert "brand-new-expert" in watcher_agents

    def test_validate_blocks_while_resolver_holds_the_lock(self):
        """End to end through the middleware's own lock, on the SYNC tool
        path (a blocked coroutine would freeze the event loop, making the
        blocking unobservable from the same loop; the sync variant shares
        the identical locked-validation closure). A resolver whose merge
        blocks on an event we control holds the lock; a concurrent
        ``start_async_task`` at a KNOWN name (validation only, no
        resolution) must not complete while the lock is held — its
        ``_validate_agent_type`` joins over ``agent_map`` under the same
        lock. Without the lock, the known-name dispatch completes during
        the resolver's block and the ``thread.is_alive()`` assertion
        fails."""
        import threading
        import time

        from EvoScientist.middleware import expert_async_subagent as mod

        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        resolver_entered = threading.Event()
        resolver_release = threading.Event()
        orig_merge = mod._merge_expert_specs

        def blocking_merge(agent_map, watcher_agents, specs):
            resolver_entered.set()
            assert resolver_release.wait(timeout=10)
            orig_merge(agent_map, watcher_agents, specs)

        def miss_dispatch():
            with patch(
                "EvoScientist.subagents.expert_container_async"
                ".build_expert_async_subagent_specs",
                return_value=[_newly_installed_expert_spec()],
            ):
                return start.func(
                    description="one",
                    subagent_type="brand-new-expert",
                    runtime=SimpleNamespace(tool_call_id="tc1"),
                )

        def known_name_dispatch(done_event):
            client = _fake_sync_client()
            with patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_sync",
                return_value=client,
            ):
                start.func(
                    description="two",
                    subagent_type="writing-agent",
                    runtime=SimpleNamespace(tool_call_id="tc2"),
                )
            done_event.set()

        with patch.object(mod, "_merge_expert_specs", blocking_merge):
            # Thread A: a miss -> resolver enters the merge, acquires the
            # lock, and blocks on our event.
            t1 = threading.Thread(target=miss_dispatch)
            t1.start()
            assert resolver_entered.wait(timeout=10)

            # Thread B: a KNOWN name -> validation only. Must block on the
            # lock the resolver holds.
            b_done = threading.Event()
            t2 = threading.Thread(target=known_name_dispatch, args=(b_done,))
            t2.start()
            time.sleep(0.1)
            assert t2.is_alive()
            assert not b_done.is_set()

            resolver_release.set()
            t1.join(timeout=10)
            t2.join(timeout=10)
            assert b_done.is_set()
            assert not t1.is_alive()
            assert not t2.is_alive()


class TestCallerModelInheritance:
    """start / update forward the *caller's* per-run model into ``runs.create``,
    beating the config-default.

    This is the bill-the-config-default bug on the ``langgraph_server`` backend:
    the model-passthrough proxy runs inside the dev-server process, where
    ``_ensure_config()`` reports the server's config-default (e.g. a billed
    ``gemini-3-flash-preview``) rather than the CLI's per-run choice. The
    launching run's real model reaches the tool as
    ``runtime.config.configurable.model``, so it must win — otherwise a
    sub-agent launched (or continued) while the caller is on a free model
    silently bills the config-default.
    """

    def _runtime(self, *, model="free", provider="openrouter", state=None):
        ns = SimpleNamespace(
            tool_call_id="tc1",
            config={"configurable": {"model": model, "model_provider": provider}},
        )
        if state is not None:
            ns.state = state
        return ns

    def _cfg_default(self):
        from EvoScientist.config.settings import EvoScientistConfig

        return EvoScientistConfig(model="gemini-3-flash-preview", provider="openrouter")

    def _tracked_task(self, agent_name="writing-agent"):
        return {
            "task_id": "task-abc",
            "agent_name": agent_name,
            "thread_id": "task-abc",
            "run_id": "old-run",
            "status": "running",
            "created_at": "2026-05-07T00:00:00Z",
            "last_checked_at": "2026-05-07T00:00:00Z",
            "last_updated_at": "2026-05-07T00:00:00Z",
        }

    def test_start_forwards_caller_model_over_cfg(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_expert_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_sync_client()
        with (
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_sync",
                return_value=client,
            ),
            patch(
                "EvoScientist.EvoScientist._ensure_config",
                return_value=self._cfg_default(),
            ),
        ):
            start.func(
                description="w",
                subagent_type="literature-review",
                runtime=self._runtime(),
            )

        configurable = client.runs.create.call_args.kwargs["config"]["configurable"]
        assert configurable["model"] == "free"
        assert configurable["model_provider"] == "openrouter"

    @pytest.mark.asyncio
    async def test_astart_forwards_caller_model_over_cfg(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_expert_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_async_client()
        with (
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_async",
                return_value=client,
            ),
            patch(
                "EvoScientist.EvoScientist._ensure_config",
                return_value=self._cfg_default(),
            ),
        ):
            await start.coroutine(
                description="w",
                subagent_type="literature-review",
                runtime=self._runtime(),
            )

        configurable = client.runs.create.await_args.kwargs["config"]["configurable"]
        assert configurable["model"] == "free"
        assert configurable["model_provider"] == "openrouter"

    def test_update_forwards_caller_model_over_cfg(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        update = next(t for t in mw.tools if t.name == "update_async_task")

        client = _fake_sync_client()
        state = {"async_tasks": {"task-abc": self._tracked_task()}}
        with (
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_sync",
                return_value=client,
            ),
            patch(
                "EvoScientist.EvoScientist._ensure_config",
                return_value=self._cfg_default(),
            ),
        ):
            update.func(
                task_id="task-abc",
                message="keep going",
                runtime=self._runtime(state=state),
            )

        kwargs = client.runs.create.call_args.kwargs
        assert kwargs["config"]["configurable"]["model"] == "free"
        # Upstream update semantics preserved by delegation.
        assert kwargs["multitask_strategy"] == "interrupt"

    @pytest.mark.asyncio
    async def test_aupdate_forwards_caller_model_over_cfg(self):
        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_standard_spec()])
        update = next(t for t in mw.tools if t.name == "update_async_task")

        client = _fake_async_client()
        state = {"async_tasks": {"task-abc": self._tracked_task()}}
        with (
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_async",
                return_value=client,
            ),
            patch(
                "EvoScientist.EvoScientist._ensure_config",
                return_value=self._cfg_default(),
            ),
        ):
            await update.coroutine(
                task_id="task-abc",
                message="keep going",
                runtime=self._runtime(state=state),
            )

        kwargs = client.runs.create.await_args.kwargs
        assert kwargs["config"]["configurable"]["model"] == "free"
        assert kwargs["multitask_strategy"] == "interrupt"

    def test_caller_scope_reset_after_start(self):
        """The contextvar must not leak past the tool call — a later launch
        with no override falls back to the config-default, not the prior
        caller's model."""
        from EvoScientist.llm import patches as patches_mod

        mw = EvoAsyncSubAgentMiddleware(async_subagents=[_expert_spec()])
        start = next(t for t in mw.tools if t.name == "start_async_task")

        client = _fake_sync_client()
        with (
            patch(
                "EvoScientist.middleware.expert_async_subagent._ClientCache.get_sync",
                return_value=client,
            ),
            patch(
                "EvoScientist.EvoScientist._ensure_config",
                return_value=self._cfg_default(),
            ),
        ):
            start.func(
                description="w",
                subagent_type="literature-review",
                runtime=self._runtime(),
            )
        # Reset restores the default (None) — nothing leaks to the next launch.
        assert not patches_mod._caller_configurable.get()