aiohttp-remotes is a library containing a set of useful tools for aiohttp.web server. It includes functionalities such as restricting incoming connections to allowed hosts only, protecting web applications with basic auth authorization, ensuring web applications are protected by CloudFlare, processing HTTP headers for secure and relaxed modes, handling HTTPS only, and redirecting plain HTTP to HTTPS automatically. The library provides tools for managing various aspects of web server security and configuration.

debug-gym is a text-based interactive debugging framework designed for debugging Python programs. It provides an environment where agents can interact with code repositories, use various tools like pdb and grep to investigate and fix bugs, and propose code patches. The framework supports different LLM backends such as OpenAI, Azure OpenAI, and Anthropic. Users can customize tools, manage environment states, and run agents to debug code effectively. debug-gym is modular, extensible, and suitable for interactive debugging tasks in a text-based environment.

Verifiers is a library of modular components for creating RL environments and training LLM agents. It includes an async GRPO implementation built around the `transformers` Trainer, is supported by `prime-rl` for large-scale FSDP training, and can easily be integrated into any RL framework which exposes an OpenAI-compatible inference client. The library provides tools for creating and evaluating RL environments, training LLM agents, and leveraging OpenAI-compatible models for various tasks. Verifiers aims to be a reliable toolkit for building on top of, minimizing fork proliferation in the RL infrastructure ecosystem.

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.

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.

A highly robust autonomous agent framework based on the ReAct paradigm, designed for adaptive decision making and multi-agent collaboration. It dynamically generates next actions during agent execution, enhancing robustness. Features a timely abandonment strategy and memory transfer mechanism for multi-agent collaboration. The framework allows developers to balance conservative and exploratory tendencies in agent execution strategies, improving adaptability and task execution efficiency in complex environments. Supports external tool integration, modular design, and MCP protocol compatibility for flexible action space expansion. Multi-agent collaboration mechanism enables agents to focus on specific task components, improving execution efficiency and quality.

AvaTaR is a novel and automatic framework that optimizes an LLM agent to effectively use provided tools and improve performance on a given task/domain. It designs a comparator module to provide insightful prompts to the LLM agent via reasoning between positive and negative examples from training data.

Hal9 is a tool that allows users to create and deploy generative applications such as chatbots and APIs quickly. It is open, intuitive, scalable, and powerful, enabling users to use various models and libraries without the need to learn complex app frameworks. With a focus on AI tasks like RAG, fine-tuning, alignment, and training, Hal9 simplifies the development process by skipping engineering tasks like frontend development, backend integration, deployment, and operations.

The BlinkID Android SDK is a comprehensive solution for implementing secure document scanning and extraction. It offers powerful capabilities for extracting data from a wide range of identification documents. The SDK provides features for integrating document scanning into Android apps, including camera requirements, SDK resource pre-bundling, customizing the UX, changing default strings and localization, troubleshooting integration difficulties, and using the SDK through various methods. It also offers options for completely custom UX with low-level API integration. The SDK size is optimized for different processor architectures, and API documentation is available for reference. For any questions or support, users can contact the Microblink team at help.microblink.com.

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.

Garak is a vulnerability scanner designed for LLMs (Large Language Models) that checks for various weaknesses such as hallucination, data leakage, prompt injection, misinformation, toxicity generation, and jailbreaks. It combines static, dynamic, and adaptive probes to explore vulnerabilities in LLMs. Garak is a free tool developed for red-teaming and assessment purposes, focusing on making LLMs or dialog systems fail. It supports various LLM models and can be used to assess their security and robustness.

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.

This repository, safety-tooling, is designed to be shared across various AI Safety projects. It provides an LLM API with a common interface for OpenAI, Anthropic, and Google models. The aim is to facilitate collaboration among AI Safety researchers, especially those with limited software engineering backgrounds, by offering a platform for contributing to a larger codebase. The repo can be used as a git submodule for easy collaboration and updates. It also supports pip installation for convenience. The repository includes features for installation, secrets management, linting, formatting, Redis configuration, testing, dependency management, inference, finetuning, API usage tracking, and various utilities for data processing and experimentation.

Hurley AI is a next-gen framework for developing intelligent agents through Retrieval-Augmented Generation. It enables easy creation of custom AI assistants and agents, supports various agent types, and includes pre-built tools for domains like finance and legal. Hurley AI integrates with LLM inference services and provides observability with Arize Phoenix. Users can create Hurley RAG tools with a single line of code and customize agents with specific instructions. The tool also offers various helper functions to connect with Hurley RAG and search tools, along with pre-built tools for tasks like summarizing text, rephrasing text, understanding memecoins, and querying databases.

LayerSkip is an implementation enabling early exit inference and self-speculative decoding. It provides a code base for running models trained using the LayerSkip recipe, offering speedup through self-speculative decoding. The tool integrates with Hugging Face transformers and provides checkpoints for various LLMs. Users can generate tokens, benchmark on datasets, evaluate tasks, and sweep over hyperparameters to optimize inference speed. The tool also includes correctness verification scripts and Docker setup instructions. Additionally, other implementations like gpt-fast and Native HuggingFace are available. Training implementation is a work-in-progress, and contributions are welcome under the CC BY-NC license.

LLM-ollama is a plugin that provides access to models running on an Ollama server. It allows users to query the Ollama server for a list of models, register them with LLM, and use them for prompting, chatting, and embedding. The plugin supports image attachments, embeddings, JSON schemas, async models, model aliases, and model options. Users can interact with Ollama models through the plugin in a seamless and efficient manner.

aiohttp-remotes is a library containing a set of useful tools for aiohttp.web server. It includes functionalities such as restricting incoming connections to allowed hosts only, protecting web applications with basic auth authorization, ensuring web applications are protected by CloudFlare, processing HTTP headers for secure and relaxed modes, handling HTTPS only, and redirecting plain HTTP to HTTPS automatically. The library provides tools for managing various aspects of web server security and configuration.

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.