49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
import pytest
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import respx
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from httpx import Response
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from app.agents import classify_intent as ci
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def test_clear_approve_no_llm(monkeypatch):
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# Patch _llm_classify so we can assert it wasn't called
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called = {"n": 0}
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def fake(text):
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called["n"] += 1
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return ("unclear", None)
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monkeypatch.setattr(ci, "_llm_classify", fake)
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assert ci.classify("승인") == ("approve", None)
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assert ci.classify("OK") == ("approve", None)
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assert ci.classify("진행") == ("approve", None)
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assert ci.classify("agree") == ("approve", None)
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assert called["n"] == 0
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def test_clear_reject_only_no_llm(monkeypatch):
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monkeypatch.setattr(ci, "_llm_classify", lambda t: ("unclear", None))
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assert ci.classify("반려") == ("reject", None)
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assert ci.classify("거절") == ("reject", None)
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def test_reject_with_text_split(monkeypatch):
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monkeypatch.setattr(ci, "_llm_classify", lambda t: ("unclear", None))
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intent, fb = ci.classify("반려, 제목 짧게")
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assert intent == "reject"
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assert "제목 짧게" in fb
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@respx.mock
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def test_ambiguous_calls_llm(monkeypatch):
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monkeypatch.setenv("ANTHROPIC_API_KEY", "k")
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respx.post("https://api.anthropic.com/v1/messages").mock(
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return_value=Response(200, json={"content": [{"type": "text",
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"text": '{"intent":"reject","feedback":"좀 더 화려하게"}'}]})
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)
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intent, fb = ci.classify("음... 좀 더 화려한 분위기가 좋겠어")
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assert intent == "reject"
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assert "화려하게" in fb
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def test_empty_text_returns_unclear():
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assert ci.classify("") == ("unclear", None)
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assert ci.classify(None) == ("unclear", None)
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