Per-model settings were mirrored to the server as two fields only,
llama_extra_args and max_seq_length. Everything else lived in browser
localStorage, so a model loaded by an API request came up with app
defaults for context length, KV cache dtype, speculative decoding,
tensor parallel and GPU placement.
Store the full config server side and map it onto the same LoadRequest
the picker builds, so a remote load and a picker load of the same model
produce the same command line. Entries are keyed per quant, falling back
to the bare repo id so existing entries keep resolving.
Also moves the API monitor out of the settings tab: a full page at
/api-monitor, plus a floating panel that opens itself when traffic
arrives, and a settings page per model reachable from the Hub.
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