feat: replace GLM API with local Ollama structured output, remove ~400 lines of JSON repair code

tests/test_ai_planner_parse_json.py

@@ -1,87 +1,47 @@
 import os
 import unittest
-
+from unittest.mock import patch, MagicMock
 from ai_planner import AIPlanner
 
 
-class TestAIPlannerParseJson(unittest.TestCase):
+class TestAIPlannerFallback(unittest.TestCase):
     def setUp(self):
-        # AIPlanner 생성 시 ZAI_API_KEY가 필요하므로 테스트에서는 더미를 주입한다.
-        os.environ.setdefault("ZAI_API_KEY", "dummy")
         self.planner = AIPlanner()
 
-    def test_parse_json_object(self):
-        raw = (
+    def test_fallback_uses_ore_anchor_from_summary(self):
+        summary = "- 위치: (0, 0)\n- iron-ore: 100타일 (앵커: 50, 30)\n"
+        plan = self.planner._fallback_plan_from_summary(summary)
+        actions = plan["actions"]
+        self.assertTrue(any(a["action"] == "mine_resource" for a in actions))
+
+    def test_fallback_explore_when_no_anchors(self):
+        summary = "- 위치: (0, 0)\n"
+        plan = self.planner._fallback_plan_from_summary(summary)
+        actions = plan["actions"]
+        self.assertTrue(any(a["action"] == "explore" for a in actions))
+
+    def test_decide_returns_actions_from_ollama(self):
+        mock_response = MagicMock()
+        mock_response.message.content = (
             '{"thinking":"t","current_goal":"g",'
             '"actions":[{"action":"explore","params":{"direction":"east","max_steps":1},"reason":"x"}],'
             '"after_this":"a"}'
         )
-        plan = self.planner._parse_json(raw)
-        self.assertEqual(plan["current_goal"], "g")
-        self.assertEqual(len(plan["actions"]), 1)
-        self.assertEqual(plan["actions"][0]["action"], "explore")
+        with patch("ai_planner.ollama.Client") as MockClient:
+            MockClient.return_value.chat.return_value = mock_response
+            actions = self.planner.decide("## 스텝 1\n현재 상태: 초기")
+        self.assertIsInstance(actions, list)
+        self.assertTrue(len(actions) >= 1)
+        self.assertEqual(actions[0]["action"], "explore")
 
-    def test_parse_json_array_top_level(self):
-        raw = '[{"action":"explore","params":{"direction":"east","max_steps":1},"reason":"x"}]'
-        plan = self.planner._parse_json(raw)
-        self.assertEqual(len(plan["actions"]), 1)
-        self.assertEqual(plan["actions"][0]["action"], "explore")
-        self.assertIn("after_this", plan)
+    def test_decide_falls_back_when_ollama_raises(self):
+        summary = "- 위치: (10, 10)\n- iron-ore: 50타일 (앵커: 60, 10)\n"
+        with patch("ai_planner.ollama.Client") as MockClient:
+            MockClient.return_value.chat.side_effect = Exception("connection refused")
+            actions = self.planner.decide(summary)
+        self.assertIsInstance(actions, list)
+        self.assertTrue(len(actions) >= 1)
 
-    def test_parse_json_array_with_code_fence(self):
-        raw = (
-            "```json\n"
-            '[{"action":"explore","params":{"direction":"east","max_steps":1},"reason":"x"}]\n'
-            "```"
-        )
-        plan = self.planner._parse_json(raw)
-        self.assertEqual(len(plan["actions"]), 1)
-        self.assertEqual(plan["actions"][0]["action"], "explore")
-
-    def test_extract_glm_text_prefers_content_then_reasoning(self):
-        # content가 비어있고 reasoning_content에 JSON이 들어있는 케이스
-        fake = {
-            "choices": [
-                {
-                    "finish_reason": "length",
-                    "message": {
-                        "content": "",
-                        "reasoning_content": '{"thinking":"t","current_goal":"g","actions":[],"after_this":"a"}',
-                    },
-                }
-            ]
-        }
-        extracted = self.planner._extract_glm_assistant_text(fake)
-        self.assertIn('"current_goal":"g"', extracted)
-
-    def test_extract_glm_text_uses_reasoning_when_content_has_no_json(self):
-        fake = {
-            "choices": [
-                {
-                    "finish_reason": "length",
-                    "message": {
-                        "content": "1. **Current State Analysis:**\n- Location: (0, 0)\n- Inventory: {...}",
-                        "reasoning_content": '{"thinking":"t","current_goal":"g","actions":[{"action":"explore","params":{"direction":"east","max_steps":1},"reason":"x"}],"after_this":"a"}',
-                    },
-                }
-            ]
-        }
-        extracted = self.planner._extract_glm_assistant_text(fake)
-        self.assertIn('"current_goal":"g"', extracted)
-
-    def test_parse_json_selects_actions_object_when_multiple_json_objects_exist(self):
-        # 분석 텍스트 안에 먼저 나오는 하위 JSON({ "foo": 1 })이 있고,
-        # 뒤에 실제 계획 JSON({ "actions": [...] })이 있는 경우를 검증한다.
-        raw = (
-            "1. Analyze...\n"
-            '{"foo": 1}\n'
-            "2. Continue...\n"
-            '{"thinking":"t","current_goal":"g",'
-            '"actions":[{"action":"explore","params":{"direction":"east","max_steps":1},"reason":"x"}],'
-            '"after_this":"a"}'
-        )
-        plan = self.planner._parse_json(raw)
-        self.assertEqual(plan["current_goal"], "g")
-        self.assertEqual(len(plan["actions"]), 1)
-        self.assertEqual(plan["actions"][0]["action"], "explore")
 
+if __name__ == "__main__":
+    unittest.main()