mirror of
https://github.com/linyqh/NarratoAI.git
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97 lines
3.7 KiB
Python
97 lines
3.7 KiB
Python
import unittest
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from app.services.documentary.frame_analysis_models import DocumentaryAnalysisConfig
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from app.services.documentary.frame_analysis_service import DocumentaryFrameAnalysisService
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class DocumentaryFrameAnalysisServiceTests(unittest.TestCase):
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def test_build_analysis_prompt_formats_real_frame_count(self):
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service = DocumentaryFrameAnalysisService()
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prompt = service._build_analysis_prompt(frame_count=3)
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self.assertIn("我提供了 3 张视频帧", prompt)
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self.assertNotIn("%s", prompt)
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self.assertIn("frame_observations", prompt)
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self.assertIn("overall_activity_summary", prompt)
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def test_parse_failed_batch_keeps_raw_response_and_time_range(self):
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service = DocumentaryFrameAnalysisService()
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batch = service._build_failed_batch_result(
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batch_index=2,
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raw_response="not-json",
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error_message="JSON decode failed",
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frame_paths=["/tmp/keyframe_000000_000000000.jpg"],
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time_range="00:00:00,000-00:00:03,000",
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)
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self.assertEqual("failed", batch.status)
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self.assertEqual("not-json", batch.raw_response)
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self.assertEqual("00:00:00,000-00:00:03,000", batch.time_range)
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self.assertTrue(batch.fallback_summary)
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def test_parse_failed_batch_uses_non_empty_fallback_when_raw_response_is_empty(self):
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service = DocumentaryFrameAnalysisService()
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batch = service._build_failed_batch_result(
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batch_index=3,
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raw_response="",
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error_message="Empty model response",
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frame_paths=["/tmp/keyframe_000001_000001000.jpg"],
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time_range="00:00:03,000-00:00:06,000",
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)
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self.assertEqual("failed", batch.status)
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self.assertEqual("", batch.raw_response)
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self.assertTrue(batch.fallback_summary)
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def test_failed_batch_result_uses_prompt_contract_field_names(self):
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service = DocumentaryFrameAnalysisService()
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batch = service._build_failed_batch_result(
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batch_index=4,
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raw_response="not-json",
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error_message="JSON decode failed",
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frame_paths=["/tmp/keyframe_000002_000002000.jpg"],
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time_range="00:00:06,000-00:00:09,000",
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)
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self.assertEqual([], batch.frame_observations)
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self.assertEqual("", batch.overall_activity_summary)
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self.assertFalse(hasattr(batch, "observations"))
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self.assertFalse(hasattr(batch, "summary"))
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class DocumentaryAnalysisConfigTests(unittest.TestCase):
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def test_config_rejects_non_positive_frame_interval(self):
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with self.assertRaises(ValueError):
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DocumentaryAnalysisConfig(
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video_path="/tmp/demo.mp4",
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frame_interval_seconds=0,
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vision_batch_size=5,
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vision_llm_provider="openai",
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vision_model_name="gpt-4o-mini",
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)
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def test_config_rejects_non_positive_batch_size(self):
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with self.assertRaises(ValueError):
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DocumentaryAnalysisConfig(
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video_path="/tmp/demo.mp4",
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frame_interval_seconds=5,
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vision_batch_size=0,
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vision_llm_provider="openai",
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vision_model_name="gpt-4o-mini",
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)
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def test_config_rejects_non_positive_max_concurrency(self):
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with self.assertRaises(ValueError):
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DocumentaryAnalysisConfig(
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video_path="/tmp/demo.mp4",
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frame_interval_seconds=5,
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vision_batch_size=5,
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vision_llm_provider="openai",
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vision_model_name="gpt-4o-mini",
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max_concurrency=0,
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)
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