# rig **Repository Path**: yangbajing/rig ## Basic Information - **Project Name**: rig - **Description**: No description available - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-05-21 - **Last Updated**: 2025-05-29 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README

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[📑 Docs](https://docs.rig.rs)   •   [🌐 Website](https://rig.rs)   •   [🤝 Contribute](https://github.com/0xPlaygrounds/rig/issues/new)   •   [✍🏽 Blogs](https://docs.rig.rs/guides)
✨ If you would like to help spread the word about Rig, please consider starring the repo! > [!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. ## 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](https://docs.rig.rs) & [crate](https://docs.rs/rig-core/latest/rig/) (API Reference) documentations. Help us improve Rig by contributing to our [Feedback form](https://bit.ly/Rig-Feeback-Form). ## Table of contents - [What is Rig?](#what-is-rig) - [Table of contents](#table-of-contents) - [High-level features](#high-level-features) - [Get Started](#get-started) - [Simple example:](#simple-example) - [Integrations](#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, SQlite, in-memory) - Integrate LLMs in your app with minimal boilerplate ## Get Started ```bash cargo add rig-core ``` ### Simple example: ```rust 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.agent("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`). You can find more examples each crate's `examples` (ie. [`rig-core/examples`](./rig-core/examples)) directory. More detailed use cases walkthroughs are regularly published on our [Dev.to Blog](https://dev.to/0thtachi) and added to Rig's official documentation [(docs.rig.rs)](http://docs.rig.rs). ## Supported Integrations | Model Providers | Vector Stores | |:--------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| |
ChatGPT logo Claude Anthropic logo
Gemini logo
xAI logo perplexity logo|
Mongo DB logo Neo4j logo

Lance DB logo
| Vector stores are available as separate companion-crates: - MongoDB vector store: [`rig-mongodb`](https://github.com/0xPlaygrounds/rig/tree/main/rig-mongodb) - LanceDB vector store: [`rig-lancedb`](https://github.com/0xPlaygrounds/rig/tree/main/rig-lancedb) - Neo4j vector store: [`rig-neo4j`](https://github.com/0xPlaygrounds/rig/tree/main/rig-neo4j) - Qdrant vector store: [`rig-qdrant`](https://github.com/0xPlaygrounds/rig/tree/main/rig-qdrant) - SQLite vector store: [`rig-sqlite`](https://github.com/0xPlaygrounds/rig/tree/main/rig-sqlite) - SurrealDB vector store: [`rig-surrealdb`](https://github.com/0xPlaygrounds/rig/tree/main/rig-surrealdb) The following providers are available as separate companion-crates: - Fastembed: [`rig-fastembed`](https://github.com/0xPlaygrounds/rig/tree/main/rig-fastembed)



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