LLM

Note: This crate name previously belonged to another project. The current implementation represents a new and different library. The previous crate is now archived and will not receive any updates. ref: https://github.com/rustformers/llm

LLM is a Rust library that lets you use multiple LLM backends in a single project: OpenAI, Anthropic (Claude), Ollama, DeepSeek, xAI, Phind and Google. With a unified API and builder style - similar to the Stripe experience - you can easily create chat or text completion requests without multiplying structures and crates.

Key Features

• Multi-backend: Manage OpenAI, Anthropic, Ollama, DeepSeek, xAI, Phind and Google through a single entry point.
• Multi-step chains: Create multi-step chains with different backends at each step.
• Templates: Use templates to create complex prompts with variables.
• Builder pattern: Configure your LLM (model, temperature, max_tokens, timeouts...) with a few simple calls.
• Chat & Completions: Two unified traits (ChatProvider and CompletionProvider) to cover most use cases.
• Extensible: Easily add new backends.
• Rust-friendly: Designed with clear traits, unified error handling, and conditional compilation via features.
• Validation: Add validation to your requests to ensure the output is what you expect.
• Evaluation: Add evaluation to your requests to score the output of LLMs.

Installation

Simply add LLM to your Cargo.toml:

[dependencies]
llm = { version = "1.0.1", features = ["openai", "anthropic", "ollama"] }

Examples

Usage

Here's a basic example using OpenAI for chat completion. See the examples directory for other backends (Anthropic, Ollama, DeepSeek, xAI, Google, Phind), embedding capabilities, and more advanced use cases.