riscv_ai_infer 🚀

A Rust-based, lightweight AI inference engine optimized for RISC-V boards. This project aims to enable efficient AI model inference on RISC-V systems, especially useful for resource-constrained environments like IoT devices and edge computing.

📜 Table of Contents

• Introduction
• Features
• Installation
• Usage
• Configuration
• Example Output
• Contributing
• License

📝 Introduction

riscv_ai_infer is a tool designed to perform AI model inference on RISC-V hardware. Leveraging Rust’s performance and safety guarantees, this engine is optimized for low-power, resource-constrained devices, making it ideal for edge computing and IoT applications.

✨ Features

• Efficient AI inference using Rust and nalgebra.
• Optimized for RISC-V architecture.
• Caching system to reduce redundant API calls.
• Terminal-based user interface for quick insights.
• Flexible configuration options.

⚙️ Installation

First, ensure you have the Rust toolchain installed. Then, clone this repository and build the project:

git clone https://github.com/bensatlantik/riscv_ai_infer.git
cd riscv_ai_infer
cargo build --release

Usage

You can run the program directly using:

cargo run

Command-Line Arguments (Optional)

To specify a crate for which you want to fetch statistics:

cargo run -- <crate_name>

Configuration

The tool supports a configuration file named config.toml. This is optional and will be skipped if not present.

# Example config.toml
api_key = ""

Example Output

No configuration file found. Skipping...
Cache data: Object {"example_key": String("example_value")}
Crate: serde
Total Downloads: 0
No recent downloads data available.

License

This project is licensed under the MIT License

Author

bensatlantik