An efficient implementation of a rate limiter for asyncio using the Leaky bucket algorithm, providing precise control over the rate a code section can be entered. It allows for limiting the number of concurrent entries within a specified time window, ensuring that a section of code is executed a maximum number of times in that period.

TurnkeyML is a tools framework that integrates models, toolchains, and hardware backends to simplify the evaluation and actuation of deep learning models. It supports use cases like exporting ONNX files, performance validation, functional coverage measurement, stress testing, and model insights analysis. The framework consists of analysis, build, runtime, reporting tools, and a models corpus, seamlessly integrated to provide comprehensive functionality with simple commands. Extensible through plugins, it offers support for various export and optimization tools and AI runtimes. The project is actively seeking collaborators and is licensed under Apache 2.0.

Garak is a free tool that checks if a Large Language Model (LLM) can be made to fail in a way that is undesirable. It probes for hallucination, data leakage, prompt injection, misinformation, toxicity generation, jailbreaks, and many other weaknesses. Garak's a free tool. We love developing it and are always interested in adding functionality to support applications.

FastTrackML is an experiment tracking server focused on speed and scalability, fully compatible with MLFlow. It provides a user-friendly interface to track and visualize your machine learning experiments, making it easy to compare different models and identify the best performing ones. FastTrackML is open source and can be easily installed and run with pip or Docker. It is also compatible with the MLFlow Python package, making it easy to integrate with your existing MLFlow workflows.

The `vectara-agentic` Python library is designed for developing powerful AI assistants using Vectara and Agentic-RAG. It supports various agent types, includes pre-built tools for domains like finance and legal, and enables easy creation of custom AI assistants and agents. The library provides tools for summarizing text, rephrasing text, legal tasks like summarizing legal text and critiquing as a judge, financial tasks like analyzing balance sheets and income statements, and database tools for inspecting and querying databases. It also supports observability via LlamaIndex and Arize Phoenix integration.

This prototype synthesizes verified code with an LLM using Monte Carlo Tree Search (MCTS). It explores the space of possible generation of a verified program and checks at every step that it's on the right track by calling the verifier. This prototype uses Dafny, Coq, Lean, Scala, or Rust. By using this technique, weaker models that might not even know the generated language all that well can compete with stronger models.

HuggingFaceGuidedTourForMac is a guided tour on how to install optimized pytorch and optionally Apple's new MLX, JAX, and TensorFlow on Apple Silicon Macs. The repository provides steps to install homebrew, pytorch with MPS support, MLX, JAX, TensorFlow, and Jupyter lab. It also includes instructions on running large language models using HuggingFace transformers. The repository aims to help users set up their Macs for deep learning experiments with optimized performance.

Züs is a high-performance cloud on a fast blockchain offering privacy and configurable uptime. It uses erasure code to distribute data between data and parity servers, allowing flexibility for IT managers to design for security and uptime. Users can easily share encrypted data with business partners through a proxy key sharing protocol. The ecosystem includes apps like Blimp for cloud migration, Vult for personal cloud storage, and Chalk for NFT artists. Other apps include Bolt for secure wallet and staking, Atlus for blockchain explorer, and Chimney for network participation. The QoS protocol challenges providers based on response time, while the privacy protocol enables secure data sharing. Züs supports hybrid and multi-cloud architectures, allowing users to improve regulatory compliance and security requirements.

PolyMind is a multimodal, function calling powered LLM webui designed for various tasks such as internet searching, image generation, port scanning, Wolfram Alpha integration, Python interpretation, and semantic search. It offers a plugin system for adding extra functions and supports different models and endpoints. The tool allows users to interact via function calling and provides features like image input, image generation, and text file search. The application's configuration is stored in a `config.json` file with options for backend selection, compatibility mode, IP address settings, API key, and enabled features.

The `unstructured` library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more. The use cases of `unstructured` revolve around streamlining and optimizing the data processing workflow for LLMs. `unstructured` modular functions and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and efficient in transforming unstructured data into structured outputs.

Magic_Words is a repository containing code for the paper 'What's the Magic Word? A Control Theory of LLM Prompting'. It implements greedy back generation and greedy coordinate gradient (GCG) to find optimal control prompts (magic words). Users can set up a virtual environment, install the package and dependencies, and run example scripts for pointwise control and optimizing prompts for datasets. The repository provides scripts for finding optimal control prompts for question-answer pairs and dataset optimization using the GCG algorithm.

code2prompt is a command-line tool that converts your codebase into a single LLM prompt with a source tree, prompt templating, and token counting. It automates generating LLM prompts from codebases of any size, customizing prompt generation with Handlebars templates, respecting .gitignore, filtering and excluding files using glob patterns, displaying token count, including Git diff output, copying prompt to clipboard, saving prompt to an output file, excluding files and folders, adding line numbers to source code blocks, and more. It helps streamline the process of creating LLM prompts for code analysis, generation, and other tasks.

Generative Models by Stability AI is a repository that provides various generative models for research purposes. It includes models like Stable Video 4D (SV4D) for video synthesis, Stable Video 3D (SV3D) for multi-view synthesis, SDXL-Turbo for text-to-image generation, and more. The repository focuses on modularity and implements a config-driven approach for building and combining submodules. It supports training with PyTorch Lightning and offers inference demos for different models. Users can access pre-trained models like SDXL-base-1.0 and SDXL-refiner-1.0 under a CreativeML Open RAIL++-M license. The codebase also includes tools for invisible watermark detection in generated images.

DevQualityEval is an evaluation benchmark and framework designed to compare and improve the quality of code generation of Language Model Models (LLMs). It provides developers with a standardized benchmark to enhance real-world usage in software development and offers users metrics and comparisons to assess the usefulness of LLMs for their tasks. The tool evaluates LLMs' performance in solving software development tasks and measures the quality of their results through a point-based system. Users can run specific tasks, such as test generation, across different programming languages to evaluate LLMs' language understanding and code generation capabilities.

Windows Agent Arena (WAA) is a scalable Windows AI agent platform designed for testing and benchmarking multi-modal, desktop AI agents. It provides researchers and developers with a reproducible and realistic Windows OS environment for AI research, enabling testing of agentic AI workflows across various tasks. WAA supports deploying agents at scale using Azure ML cloud infrastructure, allowing parallel running of multiple agents and delivering quick benchmark results for hundreds of tasks in minutes.

ScandEval is a framework for evaluating pretrained language models on mono- or multilingual language tasks. It provides a unified interface for benchmarking models on a variety of tasks, including sentiment analysis, question answering, and machine translation. ScandEval is designed to be easy to use and extensible, making it a valuable tool for researchers and practitioners alike.

MiniAiLive provides system integrators with fast, flexible and extremely precise facial recognition with 3D passive face liveness detection (face anti-spoofing) that can be deployed across a number of scenarios, including security, access control, public safety, fintech, smart retail and home protection.

An efficient implementation of a rate limiter for asyncio using the Leaky bucket algorithm, providing precise control over the rate a code section can be entered. It allows for limiting the number of concurrent entries within a specified time window, ensuring that a section of code is executed a maximum number of times in that period.

aiomcache is a Python library that provides an asyncio (PEP 3156) interface to work with memcached. It allows users to interact with memcached servers asynchronously, making it suitable for high-performance applications that require non-blocking I/O operations. The library offers similar functionality to other memcache clients and includes features like setting and getting values, multi-get operations, and deleting keys. Version 0.8 introduces the `FlagClient` class, which enables users to register callbacks for setting or processing flags, providing additional flexibility and customization options for working with memcached servers.

An efficient implementation of a rate limiter for asyncio using the Leaky bucket algorithm, providing precise control over the rate a code section can be entered. It allows for limiting the number of concurrent entries within a specified time window, ensuring that a section of code is executed a maximum number of times in that period.

Bee is an easy and high efficiency ORM framework that simplifies database operations by providing a simple interface and eliminating the need to write separate DAO code. It supports various features such as automatic filtering of properties, partial field queries, native statement pagination, JSON format results, sharding, multiple database support, and more. Bee also offers powerful functionalities like dynamic query conditions, transactions, complex queries, MongoDB ORM, cache management, and additional tools for generating distributed primary keys, reading Excel files, and more. The newest versions introduce enhancements like placeholder precompilation, default date sharding, ElasticSearch ORM support, and improved query capabilities.

claude-api is a web conversation library for ClaudeAI implemented in GoLang. It provides functionalities to interact with ClaudeAI for web-based conversations. Users can easily integrate this library into their Go projects to enable chatbot capabilities and handle conversations with ClaudeAI. The library includes features for sending messages, receiving responses, and managing chat sessions, making it a valuable tool for developers looking to incorporate AI-powered chatbots into their applications.

Aide is a code-first API documentation and utility library for Rust, along with other related utility crates for web-servers. It provides tools for creating API documentation and handling JSON request validation. The repository contains multiple crates that offer drop-in replacements for existing libraries, ensuring compatibility with Aide. Contributions are welcome, and the code is dual licensed under MIT and Apache-2.0. If Aide does not meet your requirements, you can explore similar libraries like paperclip, utoipa, and okapi.

Amadeus Java SDK provides a rich set of APIs for the travel industry, allowing developers to access various functionalities such as flight search, booking, airport information, and more. The SDK simplifies interaction with the Amadeus API by providing self-contained code examples and detailed documentation. Developers can easily make API calls, handle responses, and utilize features like pagination and logging. The SDK supports various endpoints for tasks like flight search, booking management, airport information retrieval, and travel analytics. It also offers functionalities for hotel search, booking, and sentiment analysis. Overall, the Amadeus Java SDK is a comprehensive tool for integrating Amadeus APIs into Java applications.

Rig is a Rust library designed for building scalable, modular, and user-friendly applications powered by large language models (LLMs). It provides full support for LLM completion and embedding workflows, offers simple yet powerful abstractions for LLM providers like OpenAI and Cohere, as well as vector stores such as MongoDB and in-memory storage. With Rig, users can easily integrate LLMs into their applications with minimal boilerplate code.

Celery AsyncIO Pool is a free software tool licensed under GNU Affero General Public License v3+. It provides an AsyncIO worker pool for Celery, enabling users to leverage the power of AsyncIO in their Celery applications. The tool allows for easy installation using Poetry, pip, or directly from GitHub. Users can configure Celery to use the AsyncIO pool provided by celery-aio-pool, or they can wait for the upcoming support for out-of-tree worker pools in Celery 5.3. The tool is actively maintained and welcomes contributions from the community.