Introduction

⚠️ Warning: The documentation is still in development. Some sections and examples might change as the library evolves.

LatchLM is a provider-agnostic client library for AI models. Its goal is to provide a uniform, modular, interface for interacting with different providers. By abstracting away provider-specific details, LatchLM allows you to integrate with multiple AI APIs seamlessly.

At the core of LatchLM is the AiProvider trait, which defines an asynchronous interface to send requests to an LLM. This trait simplifies the development of non-blocking applications that interact with AI models.

Key components include:

• AiProvider Trait: Abstracts the underlying API call, enabling provider-agnostic interactions.
• AiModel Trait: Represents specific AI model variants. Implementing this trait allows you to convert model variants into string identifiers (via AsRef<str>), ensuring reliable model referencing.
• ModelId: encapsulates metadata about an Ai model, such as unique identifier and a human-readable name.
• AiRequest: Represents the request to be sent to an AI model.
• AiResponse: Wraps the response from a model, allowing you to handle responses in a uniform way.

LatchLM is built with extensibility in mind, meaning that adding support for a new provider often requires only implementing the core traits. This design allows you to focus on building AI-driven applications without being locked into a single vendor.

Getting Started

To use LatchLM you can just import it in your Cargo.toml file:

[dependencies]
latchlm = "0.1.0"