#3838th of 70 in Agent frameworks and SDKs

rig

Rust library for building LLM agents, plus a Bevy-based terminal coding agent

Stars
8.9k
License
MIT
Last commit
Oct 2026
Last release
Oct 2026
Language
Rust
Stars, last 29 weeks+2,292
1 Apr 2026: 6,640 stars8 Apr 2026: 6,734 stars15 Apr 2026: 6,819 stars22 Apr 2026: 6,909 stars29 Apr 2026: 7,007 stars6 May 2026: 7,083 stars13 May 2026: 7,182 stars20 May 2026: 7,282 stars27 May 2026: 7,361 stars3 Jun 2026: 7,446 stars10 Jun 2026: 7,512 stars17 Jun 2026: 7,591 stars24 Jun 2026: 7,665 stars1 Jul 2026: 7,738 stars8 Jul 2026: 7,796 stars15 Jul 2026: 7,877 stars22 Jul 2026: 7,958 stars29 Jul 2026: 8,035 stars5 Aug 2026: 8,131 stars12 Aug 2026: 8,205 stars19 Aug 2026: 8,283 stars26 Aug 2026: 8,369 stars2 Sept 2026: 8,460 stars9 Sept 2026: 8,537 stars16 Sept 2026: 8,615 stars23 Sept 2026: 8,686 stars30 Sept 2026: 8,761 stars7 Oct 2026: 8,812 stars14 Oct 2026: 8,876 stars21 Oct 2026: 8,932 stars

6,640 on 1 Apr 20268,932 on 21 Oct 2026

From GitHub's daily star counts.

Checked on GitHub.

Overview

Rig is a Rust library that puts 20+ model providers and 10+ vector stores behind one interface, with agents that support tools, multi-turn streaming and typed hooks. The same repo ships `rig`, a terminal coding agent built as a Bevy app whose tools, commands and sessions are plugins listed in `plugins.toml`. The library is pre-1.0 and releases contain breaking changes.

Who it is for: Rust developers building LLM agents, RAG apps or a terminal coding agent

Strengths

  • 20+ model providers and 10+ vector stores behind one interface
  • Covers completion, embeddings, transcription, audio and image generation
  • Core and agent runtime target browser WASM (wasm32-unknown-unknown)
  • OpenTelemetry GenAI conventions and replay of agent effects via rig-cassette

Weaknesses

  • Pre-1.0; each release contains breaking changes, so migration notes must be read
  • Rust only; the coding agent needs Rust 1.97.1 or newer
  • Coding agent runs on Linux and macOS; Windows is not listed
  • Integrations are separate crates enabled by feature flags, adding setup steps

What it needs

  • GPU optional
  • Needs Rust 1.97.1+, tokio, LLM provider API key
  • Models: OpenAI, AWS Bedrock, Google Vertex AI, Google Gemini gRPC, Candle (local Llama/SmolLM2/Qwen3)

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