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The shape ledger showed the same test scaffolding defined over and over: _bind_user x12 (byte-identical), _dispose_engine x10 in three wordings, _no_supersession x3, _make_mock_session x7 in three subsets, a get-or-create User helper x2 (+3 inlined), and fifteen hand-rolled MagicMock note factories each re-explaining the same "an auto-MagicMock attribute is truthy" hazard (note 2109). Now: conftest.py carries _bind_user / _dispose_engine / _no_supersession as opt-in fixtures (pytestmark = usefixtures(...) per module, so unit tests pay nothing), and tests/helpers.py carries make_mock_session(), ensure_user() and fake_note(**attrs) — the hazard documented once, real values on every attribute the product reads. Call sites were rewritten by AST so titles with dashes and commas survived; the three SimpleNamespace _note stand-ins that only feed a single function stay local. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
90 lines
2.9 KiB
Python
90 lines
2.9 KiB
Python
"""search tool — proves the tool pattern (context + service call + dict shape).
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Service call is mocked; no DB needed."""
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from unittest.mock import AsyncMock, patch
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import pytest
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from scribe.mcp._context import _user_id_ctx
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from scribe.mcp.tools.search import search
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from tests.helpers import fake_note
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@pytest.fixture(autouse=True)
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def _reset_user_ctx():
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"""Each test starts with no MCP context. Tests set it explicitly."""
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token = _user_id_ctx.set(None)
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yield
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_user_id_ctx.reset(token)
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@pytest.mark.asyncio
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async def test_fable_search_raises_without_context():
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with pytest.raises(RuntimeError, match="no MCP user context"):
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await search(q="anything")
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@pytest.mark.asyncio
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async def test_fable_search_returns_repackaged_results():
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_user_id_ctx.set(7)
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fake = fake_note(id=1, title="kafka rebalance", is_task=False, body="HPA details", tags=["ops"])
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with patch(
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"scribe.mcp.tools.search.semantic_search_notes",
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AsyncMock(return_value=[(0.93, fake)]),
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):
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out = await search(q="kafka")
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assert out["total"] == 1
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assert len(out["results"]) == 1
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r = out["results"][0]
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assert r["id"] == 1
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assert r["title"] == "kafka rebalance"
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assert r["body"] == "HPA details"
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assert r["is_task"] is False
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assert r["tags"] == ["ops"]
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assert r["similarity"] == pytest.approx(0.93)
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@pytest.mark.asyncio
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async def test_fable_search_body_is_truncated_to_240_chars():
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_user_id_ctx.set(7)
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long_body = "x" * 500
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fake = fake_note(id=1, title="t", body=long_body)
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with patch(
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"scribe.mcp.tools.search.semantic_search_notes",
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AsyncMock(return_value=[(0.5, fake)]),
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):
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out = await search(q="x")
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assert len(out["results"][0]["body"]) == 240
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@pytest.mark.asyncio
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async def test_fable_search_content_type_filters_at_service_layer():
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"""content_type maps to the is_task kwarg passed to the service."""
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_user_id_ctx.set(7)
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mock_search = AsyncMock(return_value=[])
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with patch("scribe.mcp.tools.search.semantic_search_notes", mock_search):
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await search(q="x", content_type="task")
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assert mock_search.call_args.kwargs["is_task"] is True
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mock_search.reset_mock()
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await search(q="x", content_type="note")
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assert mock_search.call_args.kwargs["is_task"] is False
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mock_search.reset_mock()
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await search(q="x", content_type="all")
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assert mock_search.call_args.kwargs["is_task"] is None
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@pytest.mark.asyncio
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async def test_fable_search_limit_is_clamped():
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_user_id_ctx.set(7)
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mock_search = AsyncMock(return_value=[])
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with patch("scribe.mcp.tools.search.semantic_search_notes", mock_search):
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await search(q="x", limit=999)
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assert mock_search.call_args.kwargs["limit"] == 50
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mock_search.reset_mock()
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await search(q="x", limit=0)
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assert mock_search.call_args.kwargs["limit"] == 1
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