LLM Configuration

Configure RuVLLM for local inference and fine-tuning.

When to use

When you need to configure local LLM inference, create MicroLoRA adapters for task-specific fine-tuning, or set up SONA for real-time adaptation.

Steps

1. Check status — call mcp__plugin_ruflo-core_ruflo__ruvllm_status to see current model and adapter state
2. Generate config — call mcp__plugin_ruflo-core_ruflo__ruvllm_generate_config with model parameters
3. Create MicroLoRA — call mcp__plugin_ruflo-core_ruflo__ruvllm_microlora_create for task-specific adapters
4. Adapt MicroLoRA — call mcp__plugin_ruflo-core_ruflo__ruvllm_microlora_adapt with training data
5. Create SONA — call mcp__plugin_ruflo-core_ruflo__ruvllm_sona_create for real-time neural adaptation
6. Adapt SONA — call mcp__plugin_ruflo-core_ruflo__ruvllm_sona_adapt with feedback signals

MicroLoRA vs SONA

| Feature | MicroLoRA | SONA | |---------|-----------|------| | Speed | Minutes to train | <0.05ms adaptation | | Scope | Task-specific fine-tuning | Real-time micro-adjustments | | Persistence | Saved as adapter weights | Session-scoped | | Use case | Specialized domain tasks | Continuous feedback loops |