75 lines
2.4 KiB
Python
75 lines
2.4 KiB
Python
"""The orchestrator pulls operator-tuned weights from realism_config.
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§3c contract: the planner reads in-memory module globals, but the
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operator's tuning lives in the DB (admin PUT /api/v1/realism/config).
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The orchestrator worker bridges the two by calling
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``_refresh_realism_config(repo)`` at startup and every Nth tick.
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"""
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from __future__ import annotations
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import json
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from unittest.mock import AsyncMock
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import pytest
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from decnet.orchestrator.worker import _refresh_realism_config
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from decnet.realism import planner
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@pytest.fixture(autouse=True)
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def _reset_planner():
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yield
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planner.reset_to_defaults()
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@pytest.mark.asyncio
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async def test_refresh_no_row_keeps_defaults():
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repo = AsyncMock()
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repo.get_realism_config = AsyncMock(return_value=None)
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await _refresh_realism_config(repo)
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assert planner.current_payload()["canary_probability"] == pytest.approx(0.03)
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@pytest.mark.asyncio
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async def test_refresh_applies_stored_payload():
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repo = AsyncMock()
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repo.get_realism_config = AsyncMock(return_value={
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"key": "weights",
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"value": json.dumps({"canary_probability": 0.12}),
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})
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await _refresh_realism_config(repo)
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assert planner.current_payload()["canary_probability"] == pytest.approx(0.12)
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@pytest.mark.asyncio
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async def test_refresh_swallows_db_error():
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"""A wedged DB must not bring down the orchestrator's tick loop."""
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repo = AsyncMock()
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repo.get_realism_config = AsyncMock(side_effect=RuntimeError("boom"))
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await _refresh_realism_config(repo) # does not raise
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# planner unchanged
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assert planner.current_payload()["canary_probability"] == pytest.approx(0.03)
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@pytest.mark.asyncio
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async def test_refresh_swallows_malformed_json():
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repo = AsyncMock()
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repo.get_realism_config = AsyncMock(return_value={
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"key": "weights",
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"value": "not-json",
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})
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await _refresh_realism_config(repo)
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assert planner.current_payload()["canary_probability"] == pytest.approx(0.03)
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@pytest.mark.asyncio
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async def test_refresh_swallows_invalid_payload():
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repo = AsyncMock()
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repo.get_realism_config = AsyncMock(return_value={
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"key": "weights",
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"value": json.dumps({"canary_probability": 9.0}),
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})
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await _refresh_realism_config(repo)
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# Planner config not corrupted by a bad refresh.
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assert planner.current_payload()["canary_probability"] == pytest.approx(0.03)
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