⚡ Bolt: Optimize ML model loading with lru_cache

[benpiper]

What: Added functools.lru_cache(maxsize=1) to processor.py (Whisper model) and background_remover.py (RVM model).
Why: Loading large ML models from disk on every invocation creates massive latency overhead and potential OOM errors.
Impact: Reduces model initialization time from multiple seconds to ~0ms on subsequent calls, saving significant CPU and disk I/O.
Measurement: Verify by processing a video twice; the second run should bypass model loading logs and execute much faster.

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PR created automatically by Jules for task 11094566850443358646 started by @benpiper

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