llm-config

# 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 |