ruby_llm is an LLM integration framework and AI agent orchestrator designed to connect applications to multiple large language model providers through a unified interface. It serves as a toolkit for building autonomous assistants with custom personas, managing structured output via JSON schemas, and implementing vector embedding engines for semantic search.
The project distinguishes itself as an observability suite and multimodal toolkit. It provides specialized capabilities for tracking token usage, calculating model costs, and tracing workflows via OpenTelemetry, while supporting the processing of images, audio, video, and documents through a consistent API.
The framework covers a broad surface of AI infrastructure, including retrieval-augmented generation workflows, multi-step task orchestration, and the ability to expose local Ruby methods as tools for AI models to execute. It also provides utilities for content moderation, multimodal data extraction, and concurrent request management.
The system includes tools to bootstrap AI infrastructure using database migrations and configuration files.
