@ruvector/ruvllm

What problem does it solve?

This Skill streamlines the complex process of orchestrating calls to multiple Large Language Models (LLMs), enabling self-learning capabilities and efficient memory management.

Core Features & Use Cases

• Multi-Provider LLM Orchestration: Seamlessly manage and route requests across various LLM providers (Anthropic, OpenAI, Google, local).
• Self-Learning & Adaptation: Implements SONA adaptive learning for continuous improvement of LLM responses.
• Efficient Memory Management: Utilizes HNSW for fast and scalable vector memory indexing, ideal for RAG applications.
• Intelligent Routing: Employs FastGRNN for dynamic model selection based on task complexity, cost, and latency.

Quick Start

Use the ruvector-ruvllm skill to generate a response to the prompt "Explain the concept of quantum entanglement".