feat(agent-office): 텔레그램 자연어 의도 분류

agent-office/tests/test_classify_intent.py

@@ -0,0 +1,48 @@
+import pytest
+import respx
+from httpx import Response
+from app.agents import classify_intent as ci
+
+
+def test_clear_approve_no_llm(monkeypatch):
+    # Patch _llm_classify so we can assert it wasn't called
+    called = {"n": 0}
+    def fake(text):
+        called["n"] += 1
+        return ("unclear", None)
+    monkeypatch.setattr(ci, "_llm_classify", fake)
+    assert ci.classify("승인") == ("approve", None)
+    assert ci.classify("OK") == ("approve", None)
+    assert ci.classify("진행") == ("approve", None)
+    assert ci.classify("agree") == ("approve", None)
+    assert called["n"] == 0
+
+
+def test_clear_reject_only_no_llm(monkeypatch):
+    monkeypatch.setattr(ci, "_llm_classify", lambda t: ("unclear", None))
+    assert ci.classify("반려") == ("reject", None)
+    assert ci.classify("거절") == ("reject", None)
+
+
+def test_reject_with_text_split(monkeypatch):
+    monkeypatch.setattr(ci, "_llm_classify", lambda t: ("unclear", None))
+    intent, fb = ci.classify("반려, 제목 짧게")
+    assert intent == "reject"
+    assert "제목 짧게" in fb
+
+
+@respx.mock
+def test_ambiguous_calls_llm(monkeypatch):
+    monkeypatch.setenv("ANTHROPIC_API_KEY", "k")
+    respx.post("https://api.anthropic.com/v1/messages").mock(
+        return_value=Response(200, json={"content": [{"type": "text",
+            "text": '{"intent":"reject","feedback":"좀 더 화려하게"}'}]})
+    )
+    intent, fb = ci.classify("음... 좀 더 화려한 분위기가 좋겠어")
+    assert intent == "reject"
+    assert "화려하게" in fb
+
+
+def test_empty_text_returns_unclear():
+    assert ci.classify("") == ("unclear", None)
+    assert ci.classify(None) == ("unclear", None)