import base64
import json
import tempfile
import unittest
from pathlib import Path

from video_ai_analysis_poc.vlm_client import infer_clip


class VlmClientTests(unittest.TestCase):
    def test_infer_clip_uses_config_prompt_url_and_data_uri_images(self):
        with tempfile.TemporaryDirectory() as tmp:
            output_dir = Path(tmp)
            frame_path = output_dir / "frames" / "video-abc" / "000001.jpg"
            frame_path.parent.mkdir(parents=True)
            frame_path.write_bytes(b"jpg-bytes")
            calls = []

            def http_post(url, payload, timeout_seconds):
                calls.append((url, payload, timeout_seconds))
                return {
                    "status": 200,
                    "body": {
                        "choices": [
                            {
                                "message": {
                                    "content": json.dumps(
                                        {"screen_time": "10:00:01", "events": []}
                                    )
                                }
                            }
                        ]
                    },
                }

            result = infer_clip(
                {
                    "clip_id": "video-abc_c000001",
                    "frame_times": [
                        {
                            "frame_path": "frames/video-abc/000001.jpg",
                            "offset_seconds": 0.0,
                            "timecode": "00:00:00",
                        }
                    ],
                },
                output_dir,
                {
                    "api_base_url": "http://localhost:8679/",
                    "chat_completions_path": "/v1/chat/completions",
                    "model": "memai-zhengxin-v3-20260413",
                    "timeout_seconds": 17,
                    "max_tokens": 256,
                    "temperature": 0,
                    "image_transport": "data_uri",
                },
                {
                    "system": "system prompt from config",
                    "user": "user prompt from config",
                },
                http_post=http_post,
            )

        self.assertEqual(result["raw_response"], '{"screen_time": "10:00:01", "events": []}')
        self.assertEqual(len(calls), 1)
        url, payload, timeout_seconds = calls[0]
        self.assertEqual(url, "http://localhost:8679/v1/chat/completions")
        self.assertEqual(timeout_seconds, 17)
        self.assertEqual(payload["model"], "memai-zhengxin-v3-20260413")
        self.assertEqual(payload["messages"][0]["role"], "system")
        self.assertEqual(payload["messages"][0]["content"], "system prompt from config")
        user_content = payload["messages"][1]["content"]
        self.assertEqual(user_content[0], {"type": "text", "text": "user prompt from config"})
        self.assertEqual(user_content[1]["type"], "image_url")
        expected_data = base64.b64encode(b"jpg-bytes").decode("ascii")
        self.assertEqual(
            user_content[1]["image_url"]["url"],
            f"data:image/jpeg;base64,{expected_data}",
        )
        self.assertEqual(result["http_status"], 200)
        self.assertIsInstance(result["latency_ms"], int)


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