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https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
synced 2026-06-18 23:39:34 +00:00
dd8d2ccc9e
Railway build was failing with "Image of size 5.7 GB exceeded limit of 4.0 GB" because sentence-transformers pulled torch with full CUDA/NVIDIA GPU packages (~3 GB). Fix: multi-stage Dockerfile that: 1. Installs CPU-only torch first (--index-url pytorch.org/whl/cpu) saving ~3 GB (200 MB CPU vs 3.2 GB CUDA) 2. Multi-stage build: builder + runtime (smaller final image) 3. Non-root user (app:1000) 4. tini init for proper signal handling 5. Built-in HEALTHCHECK with 60s start-period 6. railway.toml with healthcheck path and restart policy Also fixes healthcheck failure: start-period=60s gives the app time to initialize before Railway starts checking /health. Expected image size: ~2 GB (down from 5.7 GB). https://claude.ai/code/session_01W1rJthWDkasijTdXCfxVHs
10 lines
255 B
TOML
10 lines
255 B
TOML
[build]
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dockerfilePath = "Dockerfile"
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[deploy]
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healthcheckPath = "/api/v1/health"
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healthcheckTimeout = 120
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startCommand = "uvicorn app.main:app --host 0.0.0.0 --port ${PORT:-8000} --workers 2"
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restartPolicyType = "ON_FAILURE"
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restartPolicyMaxRetries = 3
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