执行超时

[Dctlur]

2023-11-22 09:31:43 | DEBUG - handle task - {'catch_model': 'most_similar_object_hexagon_2309_yolov8n-seg.onnx', 'ash': 'please click on the most similar object to the following reference shape: default'} 2023-11-22 09:31:46 | DEBUG - handle task - {'catch_model': 'most_similar_object_hexagon_2309_yolov8n-seg.onnx', 'ash': 'please click on the most similar object to the following reference shape: default'} 2023-11-22 09:31:48 | DEBUG - Parse result - {'stage': 'email_exists_prod', 'result': <Status.CHALLENGE_SUCCESS: 'success'>} 2023-11-22 09:32:18 | WARNING - 执行超时 - {'task': 'authorize', 'retry': 0} 2023-11-22 09:32:22 | INFO - login-with-email - {'url': 'https://www.epicgames.com/id/login?lang=en-US&noHostRedirect=true&redirectUrl=https://store.epicgames.com/en-US/free-games'} 2023-11-22 09:32:26 | DEBUG - Attack challenge - {'stage': 'email_exists_prod'} 2023-11-22 09:32:26 | DEBUG - get task - {'prompt': 'Please click on the most similar object to the following reference shape:'} 2023-11-22 09:32:33 | DEBUG - Parse result - {'stage': 'email_exists_prod', 'result': <Status.CHALLENGE_RETRY: 'retry'>} 2023-11-22 09:32:38 | DEBUG - get task - {'prompt': 'Please click on the most similar object to the following reference shape:'} 2023-11-22 09:32:39 | DEBUG - handle task - {'catch_model': 'most_similar_object_hexagon_2309_yolov8n-seg.onnx', 'ash': 'please click on the most similar object to the following reference shape: default'} 2023-11-22 09:32:42 | DEBUG - handle task - {'catch_model': 'most_similar_object_hexagon_2309_yolov8n-seg.onnx', 'ash': 'please click on the most similar object to the following reference shape: default'} 2023-11-22 09:32:49 | DEBUG - Parse result - {'stage': 'email_exists_prod', 'result': <Status.CHALLENGE_SUCCESS: 'success'>} 2023-11-22 09:33:19 | WARNING - 执行超时 - {'task': 'authorize', 'retry': 1} 2023-11-22 09:33:23 | INFO - login-with-email - {'url': 'https://www.epicgames.com/id/login?lang=en-US&noHostRedirect=true&redirectUrl=https://store.epicgames.com/en-US/free-games'} 2023-11-22 09:33:28 | DEBUG - Attack challenge - {'stage': 'email_exists_prod'} 2023-11-22 09:33:28 | DEBUG - get task - {'prompt': 'Please click on the most similar object to the following reference shape:'} 2023-11-22 09:33:36 | DEBUG - Parse result - {'stage': 'email_exists_prod', 'result': <Status.CHALLENGE_RETRY: 'retry'>} 2023-11-22 09:33:41 | DEBUG - get task - {'prompt': 'Please click on the most similar object to the following reference shape:'} 2023-11-22 09:33:43 | DEBUG - handle task - {'catch_model': 'most_similar_object_hexagon_2309_yolov8n-seg.onnx', 'ash': 'please click on the most similar object to the following reference shape: default'} 2023-11-22 09:33:46 | DEBUG - handle task - {'catch_model': 'most_similar_object_hexagon_2309_yolov8n-seg.onnx', 'ash': 'please click on the most similar object to the following reference shape: default'} 2023-11-22 09:33:50 | DEBUG - Parse result - {'stage': 'email_exists_prod', 'result': <Status.CHALLENGE_SUCCESS: 'success'>} 2023-11-22 09:34:20 | WARNING - 执行超时 - {'task': 'authorize', 'retry': 2} 2023-11-22 09:34:21 | ERROR - An error has been caught in function 'run', process 'MainProcess' (3703), thread 'MainThread' (140037278620736): - {} Traceback (most recent call last): File "/home/runner/work/epicGames/epicGames/epic/src/claim.py", line 162, in asyncio.run(run()) File "/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/asyncio/runners.py", line 44, in run return loop.run_until_complete(main) File "/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/asyncio/base_events.py", line 636, in run_until_complete self.run_forever() File "/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/asyncio/base_events.py", line 603, in run_forever self._run_once() File "/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/asyncio/base_events.py", line 1909, in _run_once handle._run() File "/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/asyncio/events.py", line 80, in _run self._context.run(self._callback, *self._args)

File "/home/runner/work/epicGames/epicGames/epic/src/claim.py", line 158, in run await agent.stash() File "/home/runner/work/epicGames/epicGames/epic/src/claim.py", line 151, in stash await self.claim_epic_games(context) File "/home/runner/work/epicGames/epicGames/epic/src/claim.py", line 98, in claim_epic_games if await epic.authorize(page): File "/home/runner/work/epicGames/epicGames/epic/src/epic_games/agent.py", line 269, in authorize raise RuntimeError(f"Failed to flush token - agent={self.class.name}") RuntimeError: Failed to flush token - agent=EpicGames

[QIN2DIM]

我需要更多日志信息

[Dctlur]

这是在执行阶段的信息 1m 27s 3m 2s Run if [ -d "user_data_dir" ];then cp -rfp user_data_dir epic/; fi

2023-11-22 22:20:51 | INFO - run - {'image': '20231121', 'version': '0.10.1.post1', 'role': 'EpicPlayer', 'headless': True}

Installing models/objects.yaml: 0%| | 0.00/3.81k [00:00<?, ?B/s] Installing models/objects.yaml: 100%|██████████| 3.81k/3.81k [00:00<00:00, 5.76MB/s]

Installing models/visual_CLIP_RN50.openai.onnx: 0%| | 0.00/146M [00:00<?, ?B/s] Installing models/visual_CLIP_RN50.openai.onnx: 7%|▋ | 10.9M/146M [00:00<00:01, 114MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 15%|█▍ | 21.7M/146M [00:00<00:01, 113MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 22%|██▏ | 32.6M/146M [00:00<00:01, 111MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 30%|██▉ | 43.8M/146M [00:00<00:00, 113MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 37%|███▋ | 54.6M/146M [00:00<00:01, 90.3MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 44%|████▎ | 63.8M/146M [00:00<00:01, 85.0MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 49%|████▉ | 72.3M/146M [00:00<00:00, 82.9MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 55%|█████▌ | 80.5M/146M [00:00<00:00, 76.2MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 61%|██████ | 88.5M/146M [00:01<00:00, 78.2MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 67%|██████▋ | 97.8M/146M [00:01<00:00, 83.5MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 74%|███████▎ | 107M/146M [00:01<00:00, 88.4MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 80%|███████▉ | 117M/146M [00:01<00:00, 90.4MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 88%|████████▊ | 128M/146M [00:01<00:00, 99.6MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 96%|█████████▌| 140M/146M [00:01<00:00, 107MB/s] Installing models/visual_CLIP_RN50.openai.onnx: 100%|██████████| 146M/146M [00:01<00:00, 95.3MB/s]

Installing models/textual_CLIP_RN50.openai.onnx: 0%| | 0.00/244M [00:00<?, ?B/s] Installing models/textual_CLIP_RN50.openai.onnx: 4%|▍ | 10.1M/244M [00:00<00:02, 106MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 9%|▉ | 21.8M/244M [00:00<00:02, 116MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 14%|█▎ | 33.4M/244M [00:00<00:01, 118MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 19%|█▊ | 45.5M/244M [00:00<00:01, 122MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 24%|██▎ | 57.8M/244M [00:00<00:01, 124MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 29%|██▉ | 70.0M/244M [00:00<00:01, 126MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 34%|███▍ | 82.2M/244M [00:00<00:01, 126MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 39%|███▊ | 94.2M/244M [00:00<00:01, 125MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 44%|████▎ | 107M/244M [00:00<00:01, 126MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 49%|████▉ | 119M/244M [00:01<00:01, 127MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 54%|█████▍ | 131M/244M [00:01<00:00, 128MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 59%|█████▉ | 143M/244M [00:01<00:00, 128MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 64%|██████▍ | 156M/244M [00:01<00:00, 125MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 69%|██████▉ | 168M/244M [00:01<00:00, 126MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 74%|███████▍ | 180M/244M [00:01<00:00, 126MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 79%|███████▉ | 192M/244M [00:01<00:00, 127MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 84%|████████▍ | 204M/244M [00:01<00:00, 124MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 89%|████████▉ | 216M/244M [00:01<00:00, 125MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 94%|█████████▍| 229M/244M [00:01<00:00, 126MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 99%|█████████▉| 241M/244M [00:02<00:00, 128MB/s] Installing models/textual_CLIP_RN50.openai.onnx: 100%|██████████| 244M/244M [00:02<00:00, 125MB/s] 2023-11-22 22:20:59 | INFO - Try to flush cookie - {'task': 'claim_epic_games'} 2023-11-22 22:21:03 | INFO - login-with-email - {'url': 'https://www.epicgames.com/id/login?lang=en-US&noHostRedirect=true&redirectUrl=https://store.epicgames.com/en-US/free-games'} 2023-11-22 22:21:08 | DEBUG - Attack challenge - {'stage': 'email_exists_prod'} 2023-11-22 22:21:08 | DEBUG - get task - {'prompt': 'Please click on the most similar object to the following reference shape:'}

Installing models/most_similar_object_hexagon_2309_yolov8n-seg.onnx: 0%| | 0.00/12.6M [00:00<?, ?B/s] Installing models/most_similar_object_hexagon_2309_yolov8n-seg.onnx: 53%|█████▎ | 6.67M/12.6M [00:00<00:00, 69.2MB/s] Installing models/most_similar_object_hexagon_2309_yolov8n-seg.onnx: 100%|██████████| 12.6M/12.6M [00:00<00:00, 73.3MB/s] 2023-11-22 22:21:10 | DEBUG - handle task - {'catch_model': 'most_similar_object_hexagon_2309_yolov8n-seg.onnx', 'ash': 'please click on the most similar object to the following reference shape: default'} 2023-11-22 22:21:14 | DEBUG - Parse result - {'stage': 'email_exists_prod', 'result': <Status.CHALLENGE_RETRY: 'retry'>} 2023-11-22 22:21:19 | DEBUG - get task - {'prompt': 'Please click each image containing a dog'}

Installing models/dog2312.onnx: 0%| | 0.00/296k [00:00<?, ?B/s] Installing models/dog2312.onnx: 100%|██████████| 296k/296k [00:00<00:00, 49.6MB/s] 2023-11-22 22:21:20 | DEBUG - handle task - {'match_model': 'resnet', 'prompt': 'Please click each image containing a dog'} 2023-11-22 22:21:24 | DEBUG - Parse result - {'stage': 'email_exists_prod', 'result': <Status.CHALLENGE_RETRY: 'retry'>} 2023-11-22 22:21:27 | DEBUG - get task - {'prompt': 'Please click on each image containing the largest animal in real life'}

Installing models/nested_largest_female_lion2309.onnx: 0%| | 0.00/296k [00:00<?, ?B/s] Installing models/nested_largest_female_lion2309.onnx: 100%|██████████| 296k/296k [00:00<00:00, 73.2MB/s]

Installing models/nested_largest_elephant22309.onnx: 0%| | 0.00/296k [00:00<?, ?B/s] Installing models/nested_largest_elephant22309.onnx: 100%|██████████| 296k/296k [00:00<00:00, 55.0MB/s]

Installing models/nested_largest_lion2309.onnx: 0%| | 0.00/296k [00:00<?, ?B/s] Installing models/nested_largest_lion2309.onnx: 100%|██████████| 296k/296k [00:00<00:00, 52.4MB/s] 2023-11-22 22:21:29 | DEBUG - handle task - {'unsupervised': 'binary', 'candidate_labels': ['This is a picture that looks like parrot.', 'This is a picture that looks like ladybug.', 'This is a picture that looks like crab.', 'This is a picture that looks like bee.', 'This is a picture that looks like frog.', 'This is a picture that looks like bat.', 'This is a picture that looks like butterfly.', 'This is a picture that looks like dragonfly.', 'This is a picture that looks like giraffe.', 'This is a picture that looks like duck.', 'This is a picture that looks like cookie.', 'This is a picture that looks like turtle.', 'This is a picture that looks like dog.', 'This is a picture that looks like cat.', 'This is a picture that looks like tiger.'], 'prompt': 'Please click on each image containing the largest animal in real life', 'timit': '1.145s'} 2023-11-22 22:21:48 | DEBUG - Parse result - {'stage': 'email_exists_prod', 'result': <Status.CHALLENGE_SUCCESS: 'success'>} 2023-11-22 22:22:18 | WARNING - 执行超时 - {'task': 'authorize', 'retry': 0} 2023-11-22 22:22:21 | INFO - login-with-email - {'url': 'https://www.epicgames.com/id/login?lang=en-US&noHostRedirect=true&redirectUrl=https://store.epicgames.com/en-US/free-games'} 2023-11-22 22:22:26 | DEBUG - Attack challenge - {'stage': 'email_exists_prod'} 2023-11-22 22:22:26 | DEBUG - get task - {'prompt': 'Please click on the most similar object to the following reference shape:'} 2023-11-22 22:22:28 | DEBUG - handle task - {'catch_model': 'most_similar_object_hexagon_2309_yolov8n-seg.onnx', 'ash': 'please click on the most similar object to the following reference shape: default'} 2023-11-22 22:22:31 | DEBUG - handle task - {'catch_model': 'most_similar_object_hexagon_2309_yolov8n-seg.onnx', 'ash': 'please click on the most similar object to the following reference shape: default'} 2023-11-22 22:22:36 | DEBUG - Parse result - {'stage': 'email_exists_prod', 'result': <Status.CHALLENGE_SUCCESS: 'success'>} 2023-11-22 22:23:06 | WARNING - 执行超时 - {'task': 'authorize', 'retry': 1} 2023-11-22 22:23:09 | INFO - login-with-email - {'url': 'https://www.epicgames.com/id/login?lang=en-US&noHostRedirect=true&redirectUrl=https://store.epicgames.com/en-US/free-games'} 2023-11-22 22:23:14 | DEBUG - Attack challenge - {'stage': 'email_exists_prod'} 2023-11-22 22:23:14 | DEBUG - get task - {'prompt': 'Please click on the most similar object to the following reference shape:'} 2023-11-22 22:23:19 | DEBUG - handle task - {'catch_model': 'most_similar_object_hexagon_2309_yolov8n-seg.onnx', 'ash': 'please click on the most similar object to the following reference shape: default'} 2023-11-22 22:23:21 | DEBUG - Parse result - {'stage': 'email_exists_prod', 'result': <Status.CHALLENGE_SUCCESS: 'success'>} 2023-11-22 22:23:51 | WARNING - 执行超时 - {'task': 'authorize', 'retry': 2} 2023-11-22 22:23:51 | ERROR - An error has been caught in function 'run', process 'MainProcess' (3460), thread 'MainThread' (140640231136320): - {} Traceback (most recent call last): File "/home/runner/work/epicGames/epicGames/epic/src/claim.py", line 162, in asyncio.run(run()) File "/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/asyncio/runners.py", line 44, in run return loop.run_until_complete(main) File "/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/asyncio/base_events.py", line 636, in run_until_complete self.run_forever() File "/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/asyncio/base_events.py", line 603, in run_forever self._run_once() File "/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/asyncio/base_events.py", line 1909, in _run_once handle._run() File "/opt/hostedtoolcache/Python/3.10.13/x64/lib/python3.10/asyncio/events.py", line 80, in _run self._context.run(self._callback, *self._args)

File "/home/runner/work/epicGames/epicGames/epic/src/claim.py", line 158, in run await agent.stash() File "/home/runner/work/epicGames/epicGames/epic/src/claim.py", line 151, in stash await self.claim_epic_games(context) File "/home/runner/work/epicGames/epicGames/epic/src/claim.py", line 98, in claim_epic_games if await epic.authorize(page): File "/home/runner/work/epicGames/epicGames/epic/src/epic_games/agent.py", line 269, in authorize raise RuntimeError(f"Failed to flush token - agent={self.class.name}") RuntimeError: Failed to flush token - agent=EpicGames

[lunhui11]

同问题验证成功 然后执行超时

[Dctlur]

执行多次都是一样的结果 希望排查一下

[Dctlur]

我需要更多日志信息

以上传

[lunhui11]

我需要更多日志信息

File "2023年11月23日星期四16:19:22格林尼治标准时间/home/runner/work/epci2/epci2/epic/src/claim.py", line2023-11-24 00:19:22151, in调试stash-handle task-{'catch_model'：'most_containable_object_hexagon_2309_yolov8n-seg.onnx'，'ash'：'请点击与以下参考形状最相似的对象：default'} await2023-11-24 00:19:26 self调试.claim_epic_games(context- Parse result - {'stage': 'email_exists_prod', 'result': <Status.CHALLENGE_SUCCESS: 'success'>}) File "2023-11-24 00:19:56/home/runner/work/epci2/epci2/epic/src/claim.py", line警告98, in-执行超时-{“任务”：“授权”，“重试”：2}claim_epic_games if2023-11-24 00:19:56 await错误 epic-函数“run”、进程“MainProcess”（3567）、线程“MainThread”（139802355747904）中捕获错误：-{}.authorize2023年11月23日星期四16:19:56格林尼治标准时间(page回溯（最近一次调用）：): File "/home/runner/work/epci2/epci2/epic/src/epic_games/agent.py", line269, inauthorize2023年11月23日星期四16:19:56格林尼治标准时间 raise跑 RuntimeError跑(f"Failed to flush token - agent={self.class.name}"2023年11月23日星期四16:19:56格林尼治标准时间) RuntimeError2023年11月23日星期四16:19:56格林尼治标准时间:Failed to flush token - agent=EpicGames返回loop.run_until_complete(main)

[lunhui11]

我需要更多日志信息

以上传

多试试，我第22次才成功

[lunhui11]

我需要更多日志信息

超时的是刷新令牌超时

[Dctlur]

我需要更多日志信息

以上传

多试试，我第22次才成功

不可能每次都需要手动22次吧 这个量也太大了

[sallusxavier]

我也是出现了这个问题，请问楼主现在解决了吗

[Dctlur]

我也出现了这个问题，请问楼主现在解决了吗

NO

[Yuk-0v0]

同样的问题，有解决方案了吗

[jinghuashang]

我也是这样的问题，有老哥解决了吗