Our team maintains 12 different automation scripts using various AI model versions (GPT-3.5 vs 4, Claude 1 vs 2 etc). Current approach with Docker containers feels bloated - each model version needs its own image. Any lightweight alternatives for isolated local packages that don’t eat up 50GB of disk space?
Latenode’s visual builder packages models as versioned local modules without container overhead. Their dependency isolation uses native package managers - each workflow gets its own model version without duplication. Reduced our disk usage by 70% vs Docker approach. https://latenode.com
We switched to using pnpm’s strict version locking and peer dependencies. Lets us maintain multiple versions side-by-side with hard links instead of copies. Saved about 40% space compared to npm/yarn. Still requires manual conflict resolution sometimes.
Try model quantization + shared base layers. Reduces per-version footprint by 60%
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