76 lines
2.3 KiB
Python
76 lines
2.3 KiB
Python
from __future__ import annotations
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from typing import Any
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import pytest
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from src.models.drift import DriftIntent
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from src.services import openclaw as openclaw_module
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from src.services.drift_interpreter import NemotronDriftInterpreter
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class _FakeOpenClaw:
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def __init__(self) -> None:
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self.alert_context: dict[str, Any] | None = None
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async def call(
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self,
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prompt: str,
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alert_context: dict[str, Any] | None = None,
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) -> tuple[str, str, bool]:
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self.alert_context = alert_context
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return (
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'{"intent":"automated_change","explanation":"HPA 自動調整","risk":"LOW","confidence":0.8}',
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"ollama_gcp_a",
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True,
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)
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@pytest.mark.asyncio
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async def test_drift_interpreter_declares_ollama_first_governance_lane(
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monkeypatch: pytest.MonkeyPatch,
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) -> None:
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fake_openclaw = _FakeOpenClaw()
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monkeypatch.setattr(openclaw_module, "get_openclaw", lambda: fake_openclaw)
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result = await NemotronDriftInterpreter()._call_nemotron("請分析漂移")
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assert result.intent == DriftIntent.AUTOMATED_CHANGE
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assert fake_openclaw.alert_context is not None
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assert fake_openclaw.alert_context["enforce_ollama_first"] is True
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assert fake_openclaw.alert_context["task_type"] == "diagnose"
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assert fake_openclaw.alert_context["allow_gcp_heavy_model"] is True
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def test_drift_interpreter_strips_think_blocks_before_json_parse() -> None:
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result = NemotronDriftInterpreter()._parse_response(
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"""
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<think>先判斷 replicas 變化是否為 HPA。</think>
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{
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"intent": "automated_change",
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"explanation": "replicas 變化通常是 HPA 自動調整",
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"risk": "LOW",
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"confidence": 0.72
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}
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"""
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)
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assert result.intent == DriftIntent.AUTOMATED_CHANGE
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assert result.risk == "LOW"
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assert result.confidence == 0.72
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def test_drift_interpreter_extracts_json_from_markdown() -> None:
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result = NemotronDriftInterpreter()._parse_response(
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"""
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以下為判斷：
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```json
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{"intent":"human_error","explanation":"欄位異常變更","risk":"MEDIUM","confidence":0.61}
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```
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"""
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)
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assert result.intent == DriftIntent.HUMAN_ERROR
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assert result.risk == "MEDIUM"
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assert result.confidence == 0.61
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