EnergeticAI is a Node.js library designed to simplify the integration of open-source AI models. It leverages TensorFlow.js optimized for serverless functions, ensuring fast cold starts and efficient performance. With pre-trained models for common AI tasks like embeddings and classifiers, it accelerates the deployment process, making AI integration seamless for developers. By focusing on serverless optimization, it ensures up to 67x faster execution, ideal for modern microservices architecture.

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.