0xPlaygrounds/rig

Health v2 · maintenance only

Adoption not part of the score

8415 stars · 938 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Rig is a Rust library for building modular, scalable LLM-powered applications and agents, offering a unified API across 20+ model providers plus tools, RAG, memory, and structured output. It compiles to a single binary or WASM and integrates with vector stores via companion crates like rig-mongodb and rig-qdrant.

Use cases

• build ai agents in rust
• call llm providers through one unified api
• build a rag pipeline with vector store retrieval
• give an llm type-safe tool calling
• extract structured output from llm responses
• run local models via ollama
• stream multi-turn chat completions
• deploy an llm app as a single rust binary

When to choose

• your codebase is already Rust and you want AI features without switching stacks
• you need provider-agnostic LLM access with easy backend swapping
• you want compile-time type safety for tool arguments and structured outputs
• you need native performance for orchestration, retrieval, and concurrency
• you want to deploy to edge or browser via WASM

When to avoid

• you need fine-tuning or model training capabilities
• you want automatic retries and rate-limit handling out of the box
• your team works primarily in Python and prefers LangChain-style ecosystems
• you need a fully stable API - the project warns of frequent breaking changes

Facets

library · maturity active

agent-framework llm-inference rag http-client sdk large-language-models machine-learning developer-tools rust cross-platform wasm cli llm-orchestration multi-provider type-safe-tools vector-store-integrations structured-output opentelemetry-genai ai-agents retrieval-augmented-generation

Member repositories

For agents

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