rag-services is an extensible platform that breaks down RAG pipelines into discrete microservices. It offers a document store service, a vector index service, an embedder service, multiple LLM inference services, and an orchestrator service to coordinate workflows. Each component exposes REST APIs, allowing you to mix and match databases and model providers. With Docker and Docker Compose support, you can deploy locally or in Kubernetes clusters. The framework enables scalable, fault-tolerant RAG solutions for chatbots, knowledge bases, and automated document Q&A.

Arenas is designed to streamline the development lifecycle of LLM-powered agents. Developers can define agent personas, integrate external APIs and tools as plugins, and compose multi-step workflows using a flexible DSL. The framework manages conversation memory, error handling, and logging, enabling robust RAG pipelines and multi-agent collaboration. With a command-line interface and REST API, teams can prototype agents locally and deploy them as microservices or containerized applications. Arenas supports popular LLM providers, offers monitoring dashboards, and includes built-in templates for common use cases. This flexible architecture reduces boilerplate code and accelerates time-to-market for AI-driven solutions across domains like customer engagement, research, and data processing.