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[!WARNING] Here be dragons! As we plan to ship a torrent of features in the following months, future updates will contain breaking changes. With Rig evolving, we’ll annotate changes and highlight migration paths as we encounter them.

Table of contents

• Table of contents
• What is Rig?
• Features
• Who’s using Rig?
• Get Started
  • Simple example
• Integrations

What is Rig?

Rig is a Rust library for building scalable, modular, and ergonomic LLM-powered applications.

More information about this crate can be found in the official and crate API reference documentation.

Features

• Agentic workflows that can handle multi-turn streaming and prompting
• Full GenAI Semantic Convention compatibility
• 20+ model providers, all under one singular unified interface
• 10+ vector store integrations, all under one singular unified interface
• Full support for LLM completion and embedding workflows
• Support for transcription, audio generation and image generation model capabilities
• Integrate LLMs in your app with minimal boilerplate
• Full WASM compatibility (core library only)

Who is using Rig?

Below is a non-exhaustive list of companies and people who are using Rig:

• St Jude - Using Rig for a chatbot utility as part of proteinpaint, a genomics visualisation tool.
• Coral Protocol - Using Rig extensively, both internally as well as part of the Coral Rust SDK.
• VT Code - VT Code is a Rust-based terminal coding agent with semantic code intelligence via Tree-sitter and ast-grep. VT Code uses rig for simplifying LLM calls and implementing the model picker.
• Con - Con is a GPU-accelerated terminal emulator with a built-in AI agent harness. It uses Rig as the provider abstraction layer for its integrated coding agents.
• Dria - a decentralised AI network. Currently using Rig as part of their compute node.
• Nethermind - Using Rig as part of their Neural Interconnected Nodes Engine framework.
• Neon - Using Rig for their app.build V2 reboot in Rust.
• Listen - A framework aiming to become the go-to framework for AI portfolio management agents. Powers the Listen app.
• Cairnify - helps users find documents, links, and information instantly through an intelligent search bar. Rig provides the agentic foundation behind Cairnify’s AI search experience, enabling tool-calling, reasoning, and retrieval workflows.
• Ryzome - Ryzome is a visual AI workspace that lets you build interconnected canvases of thoughts, research, and AI agents to orchestrate complex knowledge work.
• deepwiki-rs - Turn code into clarity. Generate accurate technical docs and AI-ready context in minutes—perfectly structured for human teams and intelligent agents.
• Cortex Memory - The production-ready memory system for intelligent agents. A complete solution for memory management, from extraction and vector search to automated optimization, with a REST API, MCP, CLI, and insights dashboard out-of-the-box.
• Ironclaw - A secure personal AI assistant
• ilert - Incident management & alerting platform. Uses Rig as the multi-provider abstraction in its agentic LLM proxy powering ilert AI.

For a full list, check out our ECOSYSTEM.md file.

Are you also using Rig? Open an issue to have your name added!

Get Started

Use the root rig facade when you want feature-gated access to companion crates, or use rig-core directly when you only need the core provider abstractions.

cargo add rig
# or: cargo add rig-core

Simple example

use rig::client::{CompletionClient, ProviderClient};
use rig::completion::Prompt;
use rig::providers::openai;

#[tokio::main]
async fn main() -> Result<(), anyhow::Error> {
    // Create OpenAI client
    let client = openai::Client::from_env()?;

    // Create agent with a single context prompt
    let comedian_agent = client
        .agent(openai::GPT_5_2)
        .preamble("You are a comedian here to entertain the user using humour and jokes.")
        .build();

    // Prompt the agent and print the response
    let response = comedian_agent.prompt("Entertain me!").await?;

    println!("{response}");

    Ok(())
}

Note using #[tokio::main] requires you enable tokio’s macros and rt-multi-thread features or just full to enable all features (cargo add tokio --features macros,rt-multi-thread).

You can find more examples in each crate’s examples directory (for example, examples). Provider-specific integration coverage lives under tests/providers, with cassette-backed tests that replay offline by default and live-only tests kept separate when real provider APIs are still required. See tests/README.md for test target, replay, record, and cassette safety commands. More detailed use case walkthroughs are regularly published on our Dev.to Blog and added to Rig’s official documentation at docs.rig.rs.

Supported Integrations

The root rig facade exposes companion crates behind one feature per integration:

rig = { version = "0.36.0", features = ["lancedb", "fastembed"] }

Integration	Crate	Feature	Module path
AWS Bedrock	rig-bedrock	bedrock	rig::bedrock
AWS S3Vectors	rig-s3vectors	s3vectors	rig::s3vectors
Cloudflare Vectorize	rig-vectorize	vectorize	rig::vectorize
FastEmbed	rig-fastembed	fastembed	rig::fastembed
Google Gemini gRPC	rig-gemini-grpc	gemini-grpc	rig::gemini_grpc
Google Vertex AI	rig-vertexai	vertexai	rig::vertexai
HelixDB	rig-helixdb	helixdb	rig::helixdb
LanceDB	rig-lancedb	lancedb	rig::lancedb
Memory policies	rig-memory	memory	rig::memory
Milvus	rig-milvus	milvus	rig::milvus
MongoDB	rig-mongodb	mongodb	rig::mongodb
Neo4j	rig-neo4j	neo4j	rig::neo4j
PostgreSQL	rig-postgres	postgres	rig::postgres
Qdrant	rig-qdrant	qdrant	rig::qdrant
ScyllaDB	rig-scylladb	scylladb	rig::scylladb
SQLite	rig-sqlite	sqlite	rig::sqlite
SurrealDB	rig-surrealdb	surrealdb	rig::surrealdb

rig::memory is available without the memory feature; it contains the core conversation memory traits and in-memory backend re-exported from rig-core. Enabling features = ["memory"] adds reusable history-shaping policy types from the rig-memory companion crate to the same module.

We also have some other associated crates that have additional functionality you may find helpful when using Rig:

• rig-onchain-kit - the Rig Onchain Kit. Intended to make interactions between Solana/EVM and Rig much easier to implement.