Stage 2 of the candle-native pivot. Fleshes out CandleHarness with a
LoadedModel registry keyed by model_id, hf-hub-backed GGUF download,
and Qwen3 quantized weight construction via candle-transformers'
quantized_qwen3 module. unload_model drops the entry; Drop on the
candle ModelWeights frees device memory.
Device selection prefers CUDA (gated behind the new `cuda` feature),
falling back to CPU when CUDA is unavailable so default builds work
on non-GPU hosts. The candle CUDA toolchain isn't pulled in unless
`--features cuda` is passed, keeping CI green on CPU runners.
Config gains a [harness.candle] block with an optional hf_cache path.
HarnessRegistry::from_configs now takes HarnessSettings so per-harness
config flows through.
A gated tests/candle_lifecycle.rs exercises real load → list → unload
→ list-empty when run with `--features cuda-integration` against a
host with HF network access. The default-feature test in tests/api.rs
covers the wrong-harness rejection path without needing the network.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Package name, lib name, and binary all now just "neuron" without
the cortex- prefix.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- MistralRsHarness: Harness trait impl wrapping mistral.rs HTTP API
(list/load/unload models, health check, start/stop via systemd)
- HarnessRegistry: maps harness name -> Box<dyn Harness>, built from
neuron.toml config
- Neuron API endpoints: GET /models, POST /models/load,
POST /models/unload, GET /models/:id/endpoint
- NeuronConfig: figment-based config loading from neuron.toml
- Integration test: full model lifecycle through mock mistral.rs
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
