a month ago
Another failure. Let me check the latest build logs.
Searched build logs
Hide result
21:48:53
21:48:53Downloading pyyaml-6.0.3-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl (806 kB)
21:48:53━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 806.6/806.6 kB 181.9 MB/s eta 0:00:00
21:48:53
21:48:53Downloading requests-2.33.1-py3-none-any.whl (64 kB)
21:48:53━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 64.9/64.9 kB 217.6 MB/s eta 0:00:00
21:48:53
21:48:53Downloading scikit_learn-1.8.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl (9.1 MB)
21:48:53━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 9.1/9.1 MB 191.9 MB/s eta 0:00:00
21:48:53
...and 190 more logs
The real issue: The problem isn't the Dockerfile anymore—it's the image export/import stage. Look at the timeline:
- Pip install finishes at 16:20:46 (fast ✓)
- Build layers complete at 16:20:56
- "importing to docker" starts at 16:25:07 and hangs until 16:27:45 (2.5+ minutes)
The final image is too large. The pip install is pulling CUDA packages (nvidia-cuda-runtime, nvidia-cudnn-cu13, etc.) that shouldn't be there.
The fix: Your requirements.txt has CUDA dependencies. You need to remove them or use CPU-only versions.
1 Replies
a month ago
This question appears to be about your application code rather than the Railway platform, which is outside the scope of what we can help with.
Status changed to Awaiting User Response Railway • about 1 month ago
a month ago
This thread has been marked as solved automatically due to a lack of recent activity. Please re-open this thread or create a new one if you require further assistance. Thank you!
Status changed to Solved Railway • about 1 month ago