Crate rig

Rig is a Rust library for building LLM-powered applications that focuses on ergonomics and modularity.

Table of contents

• High-level features
• Simple Example
• Integrations

High-level features

• Full support for LLM completion and embedding workflows
• Simple but powerful common abstractions over LLM providers (e.g. OpenAI, Cohere) and vector stores (e.g. MongoDB, in-memory)
• Integrate LLMs in your app with minimal boilerplate

Simple example:

use rig::{completion::Prompt, providers::openai};

#[tokio::main]
async fn main() {
    // Create OpenAI client and model.
    // This requires the `OPENAI_API_KEY` environment variable to be set.
    let openai_client = openai::Client::from_env();

    let gpt4 = openai_client.model("gpt-4").build();

    // Prompt the model and print its response
    let response = gpt4
        .prompt("Who are you?")
        .await
        .expect("Failed to prompt GPT-4");

    println!("GPT-4: {response}");
}

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).

Integrations

Rig currently has the following integration sub-libraries:

• MongoDB vector store: rig-mongodb

Modules

• agent
  This module contains the implementation of the Agent struct and its builder.
• cli_chatbot
• completion
  This module contains the implementation of the completion functionality for the LLM (Large Language Model) chat interface. It provides traits, structs, and enums for generating completion requests, handling completion responses, and defining completion models.
• embeddings
  This module provides functionality for working with embeddings and embedding models. Embeddings are numerical representations of documents or other objects, typically used in natural language processing (NLP) tasks such as text classification, information retrieval, and document similarity.
• extractor
• json_utils
• model
  This module contains the implementation of the Agent struct and its builder.
• providers
• rag
• tool
• vector_store