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Description

BaseRT offers a robust inference runtime for LLMs specifically optimized for Apple Silicon, allowing developers to seamlessly access models from Hugging Face, engage in local conversations, or utilize an API compatible with OpenAI through a single command-line interface. Enhanced by meticulously crafted Metal kernels, BaseRT aims to provide exceptional prefill and decoding efficiency on M-series Macs, with benchmark results indicating it performs up to 6.4 times faster in prefill tasks compared to llama.cpp, 3.9 times faster than MLX, and achieves a decoding speed that is 1.33 times quicker. The basert CLI is equipped to manage tasks such as model downloading, conversion, interactive chat, serving capabilities, completion generation, benchmarking, inspection, and bundle signing. Its server functionalities are extensive, encompassing chat interactions, text completions, embeddings, transcription services, tool calls, continuous batching, paged key-value caching, and prefix caching, with support for models that can handle text, vision, and audio data. BaseRT employs a proprietary .base model format that incorporates Q2–Q8 affine quantization, optional AWQ calibration, and signed bundles, and it is capable of converting GGUF, Hugging Face, and MLX checkpoints. Furthermore, this innovative runtime is tailored to maximize the capabilities of Apple Silicon, making it an essential tool for developers in the AI space.

Description

Promptfoo proactively identifies and mitigates significant risks associated with large language models before they reach production. The founders boast a wealth of experience in deploying and scaling AI solutions for over 100 million users, utilizing automated red-teaming and rigorous testing to address security, legal, and compliance challenges effectively. By adopting an open-source, developer-centric methodology, Promptfoo has become the leading tool in its field, attracting a community of more than 20,000 users. It offers custom probes tailored to your specific application, focusing on identifying critical failures instead of merely targeting generic vulnerabilities like jailbreaks and prompt injections. With a user-friendly command-line interface, live reloading, and efficient caching, users can operate swiftly without the need for SDKs, cloud services, or login requirements. This tool is employed by teams reaching millions of users and is backed by a vibrant open-source community. Users can create dependable prompts, models, and retrieval-augmented generation (RAG) systems with benchmarks that align with their unique use cases. Additionally, it enhances the security of applications through automated red teaming and pentesting, while also expediting evaluations via its caching, concurrency, and live reloading features. Consequently, Promptfoo stands out as a comprehensive solution for developers aiming for both efficiency and security in their AI applications.