Rig - Build Modular and Scalable LLM Applications in Rust

Rig Build Modular and Scalable LLM Applications in Rust

What is Rig?

Rig is a framework designed for building modular and scalable Large Language Model (LLM) applications using the Rust programming language. It provides developers with a unified API to access different LLM providers, simplifying integration and reducing the risk of vendor lock-in.

Rig takes full advantage of Rust's performance features, including zero-cost abstractions and memory safety, enabling high-performance LLM operations. The framework also includes pre-built, modular components for implementing complex AI systems, such as Retrieval-Augmented Generation (RAG) and multi-agent setups. Rig ensures robust and reliable LLM interactions through the application of Rust's strong type system, which provides compile-time correctness.

Features

Unified LLM Interface: Consistent API across different LLM providers, simplifying integration and reducing vendor lock-in.
Rust-Powered Performance: Leverage Rust's zero-cost abstractions and memory safety for high-performance LLM operations.
Advanced AI Workflow Abstractions: Implement complex AI systems like RAG and multi-agent setups with pre-built, modular components.
Type-Safe LLM Interactions: Utilize Rust's strong type system to ensure compile-time correctness in LLM interactions.
Seamless Vector Store Integration: Built-in support for vector stores, enabling efficient similarity search and retrieval for AI applications.
Flexible Embedding Support: Easy-to-use APIs for working with embeddings, crucial for semantic search and content-based recommendations.

Use Cases

Building LLM applications requiring high performance and scalability.
Implementing complex AI systems such as RAG and multi-agent setups.
Developing applications that require efficient similarity search and retrieval.
Creating applications needing semantic search and content-based recommendations.