Build a Multi-Tenant RAG with Fine-Grain Authorization using Motia and SpiceDB

The text provides a detailed tutorial on building a retrieval-augmented generation (RAG) pipeline with multi-tenant authorization using Motia's event-driven framework, OpenAI embeddings, Pinecone vector search, and SpiceDB for fine-grained permissions. Inspired by the game Stardew Valley, the author constructs a system where users can log and query farm harvest data using natural language processing, ensuring that access to data is controlled through SpiceDB's relationship-based access control (ReBAC). The tutorial walks through setting up the environment, including creating a Motia project, configuring Pinecone and SpiceDB, and implementing various steps such as storing harvest data, processing embeddings, and querying the data with AI responses. It emphasizes the importance of chunking text for better retrieval accuracy, using event-driven architecture for efficient processing, and maintaining audit logs. The system is designed to support multi-tenant access, where users see only data they have permission to access, and it offers flexibility in choosing AI providers, demonstrating an integration of various modern technologies to create a scalable and secure data querying system.

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