Rig is a framework for building large language model applications, featuring a multi-provider client and a workflow builder for retrieval-augmented generation systems. It serves as an orchestrator for creating autonomous agents that can maintain conversation state and execute complex tasks through custom prompting and plugins.
The project provides standardized interfaces for both completion and embedding model providers, allowing for unified request and response patterns across different engines. It also includes a vector database integration layer that defines a common interface for indexing and retrieving high-dimensional embeddings across various storage backends.
Its broader capabilities cover generative AI workflows for multimedia content production and tools for unstructured data extraction, including sentiment analysis and text classification. The framework supports modular composition, enabling the integration of third-party plugins and custom provider implementations.
