Summary
A developer is seeking architectural and MLOps advice to deploy a unified Knowledge Graph/RAG service, incorporating embedding, reranking, and zero-shot classification, on a laptop with limited resources (8GB VRAM, 16GB system RAM). The service, running in a FastAPI Docker container, is encountering severe memory limit issues and latency, especially after migrating from Windows WSL to native Linux, highlighting the challenges of local AI deployment under stress.
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