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438 lines
15 KiB
Python
Executable File
438 lines
15 KiB
Python
Executable File
"""Worker AI 任务单元测试.
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测试覆盖：
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- AI推荐（豆包调用成功/失败/降级）
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- 推荐响应解析（多种格式）
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- 封面生成降级
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"""
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from __future__ import annotations
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import json
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import sys
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import unittest
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from unittest.mock import MagicMock, patch
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sys.path.insert(0, "apps/worker")
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sys.path.insert(0, "packages")
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from worker_app.tasks.ai_tasks import ( # noqa: E402
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_fallback_recommend_clips,
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_parse_recommend_response,
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run_ai_recommend,
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run_generate_cover,
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)
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class TestFallbackRecommend(unittest.TestCase):
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"""降级推荐方案测试."""
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def test_fallback_returns_expected_structure(self):
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"""降级推荐返回正确结构."""
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result = _fallback_recommend_clips(
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plan_id="plan-1",
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template_id="tpl-1",
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asset_ids=["a1", "a2", "a3"],
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editing_mode="one_take",
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target_duration=30.0,
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)
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self.assertIn("clips", result)
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self.assertIn("config", result)
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self.assertIn("total_duration", result)
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self.assertIn("confidence", result)
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def test_fallback_clips_structure(self):
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"""每个片段都有必要字段."""
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result = _fallback_recommend_clips(
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plan_id="plan-1",
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template_id="tpl-1",
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asset_ids=["a1", "a2"],
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editing_mode="one_take",
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target_duration=20.0,
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)
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clips = result["clips"]
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self.assertTrue(len(clips) >= 3) # intro + showcase + outro
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for clip in clips:
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self.assertIn("clip_type", clip)
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self.assertIn("order", clip)
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self.assertIn("text_content", clip)
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self.assertIn("duration", clip)
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self.assertIn("transition_effect", clip)
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self.assertIn("asset_id", clip)
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self.assertIn("start_time", clip)
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self.assertIn("config", clip)
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def test_fallback_first_is_intro_last_is_outro(self):
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"""第一个是开场，最后一个是结尾."""
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result = _fallback_recommend_clips(
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plan_id="plan-1",
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template_id="tpl-1",
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asset_ids=["a1", "a2", "a3"],
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editing_mode="one_take",
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target_duration=30.0,
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)
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clips = result["clips"]
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self.assertEqual(clips[0]["clip_type"], "intro")
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self.assertEqual(clips[-1]["clip_type"], "outro")
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def test_fallback_order_sequential(self):
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"""order 连续递增."""
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result = _fallback_recommend_clips(
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plan_id="plan-1",
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template_id="tpl-1",
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asset_ids=["a1", "a2"],
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editing_mode="one_take",
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target_duration=30.0,
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)
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for i, clip in enumerate(result["clips"]):
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self.assertEqual(clip["order"], i)
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def test_fallback_empty_assets(self):
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"""空素材列表也能生成."""
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result = _fallback_recommend_clips(
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plan_id="plan-1",
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template_id="tpl-1",
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asset_ids=[],
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editing_mode="one_take",
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target_duration=10.0,
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)
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self.assertTrue(len(result["clips"]) >= 2)
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def test_fallback_confidence_in_range(self):
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"""置信度在0-1之间."""
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result = _fallback_recommend_clips(
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plan_id="plan-1",
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template_id="tpl-1",
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asset_ids=["a1"],
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editing_mode="one_take",
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target_duration=10.0,
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)
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self.assertGreaterEqual(result["confidence"], 0.0)
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self.assertLessEqual(result["confidence"], 1.0)
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class TestRecommendResponseParsing(unittest.TestCase):
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"""推荐响应解析测试."""
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def _asset_ids(self):
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return ["a1", "a2", "a3"]
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def test_parse_valid_response(self):
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"""解析正常响应."""
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data = {
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"clips": [
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{
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"clip_type": "intro",
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"order": 0,
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"text_content": "开场",
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"duration": 3.0,
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"transition_effect": "fade",
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"asset_id": "a1",
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"start_time": 0.0,
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"config": {},
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},
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{
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"clip_type": "showcase",
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"order": 1,
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"text_content": "展示",
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"duration": 5.0,
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"transition_effect": "cut",
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"asset_id": "a2",
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"start_time": 1.0,
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"config": {},
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},
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{
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"clip_type": "outro",
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"order": 2,
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"text_content": "结尾",
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"duration": 2.0,
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"transition_effect": "fade",
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"asset_id": "",
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"start_time": 0.0,
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"config": {},
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},
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],
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"title": "精彩视频",
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"confidence": 0.85,
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}
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result = _parse_recommend_response(json.dumps(data), self._asset_ids(), 30.0)
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self.assertIsNotNone(result)
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self.assertEqual(len(result["clips"]), 3)
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self.assertEqual(result["clips"][0]["clip_type"], "intro")
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self.assertEqual(result["confidence"], 0.85)
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self.assertIn("精彩视频", result["config"].get("title", {}).get("text", ""))
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def test_parse_markdown_code_block(self):
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"""解析markdown代码块."""
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data = {
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"clips": [
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{
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"clip_type": "showcase",
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"order": 0,
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"text_content": "t",
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"duration": 3,
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"transition_effect": "cut",
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"asset_id": "a1",
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"start_time": 0,
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"config": {},
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}
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],
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"confidence": 0.7,
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}
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content = "```json\n" + json.dumps(data) + "\n```"
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result = _parse_recommend_response(content, self._asset_ids(), 30.0)
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self.assertIsNotNone(result)
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self.assertEqual(len(result["clips"]), 1)
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def test_parse_empty_content(self):
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"""空内容返回None."""
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result = _parse_recommend_response("", self._asset_ids(), 30.0)
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self.assertIsNone(result)
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def test_parse_invalid_json(self):
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"""无效JSON返回None."""
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result = _parse_recommend_response("不是json", self._asset_ids(), 30.0)
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self.assertIsNone(result)
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def test_parse_no_clips(self):
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"""无clips字段返回None."""
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result = _parse_recommend_response(json.dumps({"title": "abc"}), self._asset_ids(), 30.0)
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self.assertIsNone(result)
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def test_parse_filters_invalid_asset_ids(self):
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"""过滤不在输入列表中的asset_id."""
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data = {
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"clips": [
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{
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"clip_type": "showcase",
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"order": 0,
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"text_content": "t",
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"duration": 3,
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"transition_effect": "cut",
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"asset_id": "fake-id",
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"start_time": 0,
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"config": {},
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}
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],
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"confidence": 0.7,
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}
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result = _parse_recommend_response(json.dumps(data), self._asset_ids(), 30.0)
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self.assertIsNotNone(result)
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# 非法asset_id被清空
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self.assertEqual(result["clips"][0]["asset_id"], "")
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def test_parse_clamps_duration(self):
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"""时长被限制在合理范围."""
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data = {
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"clips": [
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{
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"clip_type": "showcase",
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"order": 0,
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"text_content": "t",
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"duration": 100,
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"transition_effect": "cut",
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"asset_id": "a1",
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"start_time": 0,
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"config": {},
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}
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]
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}
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result = _parse_recommend_response(json.dumps(data), self._asset_ids(), 30.0)
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self.assertIsNotNone(result)
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self.assertLessEqual(result["clips"][0]["duration"], 30.0)
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def test_parse_reorders_clips(self):
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"""clips按order排序并重新编号."""
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data = {
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"clips": [
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{
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"clip_type": "showcase",
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"order": 5,
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"text_content": "b",
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"duration": 3,
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"transition_effect": "cut",
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"asset_id": "a2",
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"start_time": 0,
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"config": {},
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},
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{
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"clip_type": "intro",
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"order": 0,
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"text_content": "a",
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"duration": 3,
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"transition_effect": "fade",
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"asset_id": "a1",
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"start_time": 0,
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"config": {},
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},
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]
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}
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result = _parse_recommend_response(json.dumps(data), self._asset_ids(), 30.0)
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self.assertIsNotNone(result)
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# 第一个应该是order=0的intro
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self.assertEqual(result["clips"][0]["clip_type"], "intro")
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# order被重新编号为连续
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self.assertEqual(result["clips"][0]["order"], 0)
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self.assertEqual(result["clips"][1]["order"], 1)
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def test_parse_confidence_clamped(self):
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"""confidence被限制在0-1."""
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data = {
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"clips": [
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{
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"clip_type": "showcase",
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"order": 0,
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"text_content": "t",
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"duration": 3,
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"transition_effect": "cut",
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"asset_id": "a1",
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"start_time": 0,
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"config": {},
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}
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],
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"confidence": 2.5,
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}
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result = _parse_recommend_response(json.dumps(data), self._asset_ids(), 30.0)
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self.assertIsNotNone(result)
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self.assertLessEqual(result["confidence"], 1.0)
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class TestRunAIRecommend(unittest.TestCase):
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"""run_ai_recommend 集成测试."""
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def test_fallback_when_client_unavailable(self):
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"""客户端不可用时走降级."""
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mock_client = MagicMock()
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mock_client.is_available = False
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mock_client.chat_completion = MagicMock(return_value=None)
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with patch("packages.shared.ai_service.get_doubao_client", return_value=mock_client):
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result = run_ai_recommend(
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plan_id="plan-1",
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template_id="tpl-1",
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asset_ids=["a1", "a2"],
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editing_mode="one_take",
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target_duration=20.0,
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)
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self.assertIn("clips", result)
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self.assertIn("total_duration", result)
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mock_client.chat_completion.assert_not_called()
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def test_doubao_success(self):
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"""豆包调用成功路径."""
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mock_client = MagicMock()
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mock_client.is_available = True
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mock_response = {
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"clips": [
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{
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"clip_type": "intro",
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"order": 0,
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"text_content": "开场",
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"duration": 3.0,
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"transition_effect": "fade",
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"asset_id": "a1",
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"start_time": 0.0,
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"config": {},
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},
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{
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"clip_type": "outro",
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"order": 1,
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"text_content": "结尾",
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"duration": 2.0,
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"transition_effect": "fade",
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"asset_id": "a2",
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"start_time": 0.0,
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"config": {},
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},
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],
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"title": "AI生成标题",
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"confidence": 0.9,
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}
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mock_client.chat_completion = MagicMock(return_value=json.dumps(mock_response))
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with patch("packages.shared.ai_service.get_doubao_client", return_value=mock_client):
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result = run_ai_recommend(
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plan_id="plan-1",
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template_id="tpl-1",
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asset_ids=["a1", "a2"],
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editing_mode="one_take",
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target_duration=30.0,
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)
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self.assertEqual(result["confidence"], 0.9)
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self.assertEqual(len(result["clips"]), 2)
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mock_client.chat_completion.assert_called_once()
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def test_doubao_failure_fallback(self):
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"""豆包调用失败降级."""
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mock_client = MagicMock()
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mock_client.is_available = True
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mock_client.chat_completion = MagicMock(return_value=None)
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with patch("packages.shared.ai_service.get_doubao_client", return_value=mock_client):
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result = run_ai_recommend(
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plan_id="plan-1",
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template_id="tpl-1",
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asset_ids=["a1"],
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editing_mode="one_take",
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target_duration=10.0,
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)
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# 降级后有结果
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self.assertTrue(len(result["clips"]) >= 2)
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mock_client.chat_completion.assert_called_once()
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def test_doubao_unparseable_fallback(self):
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"""豆包返回无法解析时降级."""
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mock_client = MagicMock()
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mock_client.is_available = True
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mock_client.chat_completion = MagicMock(return_value="一堆废话不是json")
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with patch("packages.shared.ai_service.get_doubao_client", return_value=mock_client):
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result = run_ai_recommend(
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plan_id="plan-1",
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template_id="tpl-1",
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asset_ids=["a1"],
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editing_mode="one_take",
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target_duration=10.0,
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)
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# 降级后有结果
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self.assertTrue(len(result["clips"]) >= 2)
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class TestGenerateCover(unittest.TestCase):
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"""封面生成测试（降级路径）."""
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def test_ai_frame_type(self):
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"""AI封面模式返回预期结构."""
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result = run_generate_cover(
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plan_id="plan-1",
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asset_ids=["a1"],
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cover_type="ai_frame",
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)
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self.assertIn("type", result)
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self.assertEqual(result["type"], "ai_frame")
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self.assertIn("image_url", result)
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def test_manual_type(self):
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"""手动选帧模式."""
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result = run_generate_cover(
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plan_id="plan-1",
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asset_ids=["a1"],
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cover_type="manual",
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frame_time=5.0,
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)
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self.assertEqual(result["type"], "manual")
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self.assertEqual(result["frame_time"], 5.0)
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def test_upload_type(self):
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"""上传封面模式."""
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result = run_generate_cover(
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plan_id="plan-1",
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asset_ids=["a1"],
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cover_type="upload",
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)
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self.assertEqual(result["type"], "upload")
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if __name__ == "__main__":
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unittest.main()
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