import unittest

from ai_planner import AIPlanner


class TestAIPlannerLMStudioCompat(unittest.TestCase):
    def test_build_chat_payload_has_legacy_chat_keys(self):
        payload = AIPlanner._build_chat_payload("hello")

        self.assertIn("messages", payload)
        self.assertIn("options", payload)
        self.assertEqual(payload["messages"][1]["content"], "hello")

    def test_build_input_only_payload_has_minimal_keys(self):
        payload = AIPlanner._build_input_only_payload("hello")

        self.assertIn("input", payload)
        self.assertNotIn("messages", payload)
        self.assertEqual(payload["stream"], False)
        self.assertIn("hello", payload["input"])

    def test_payload_candidates_order(self):
        payloads = AIPlanner._build_payload_candidates("hello")
        self.assertEqual(len(payloads), 2)
        self.assertIn("messages", payloads[0])
        self.assertIn("input", payloads[1])
        self.assertNotIn("messages", payloads[1])

    def test_extract_response_content_supports_message_content(self):
        data = {
            "message": {
                "content": (
                    '{"thinking":"t","current_goal":"g","actions":[],"after_this":"a"}'
                )
            }
        }
        content = AIPlanner._extract_response_content(data)
        self.assertIn('"current_goal":"g"', content)

    def test_extract_response_content_supports_output_text(self):
        data = {
            "output_text": (
                '{"thinking":"t","current_goal":"g","actions":[],"after_this":"a"}'
            )
        }
        content = AIPlanner._extract_response_content(data)
        self.assertIn('"after_this":"a"', content)


if __name__ == "__main__":
    unittest.main()