L1B3RT45 is a tool designed for jailbreaking all flagship AI models. It is part of the FREEAI project and is named LIBERTAS. Users can join the BASI Discord community for support. The tool was created with love by Pliny the Prompter.

The Atomic Agents framework is a modular and extensible tool designed for creating powerful applications. It leverages Pydantic for data validation and serialization. The framework follows the principles of Atomic Design, providing small and single-purpose components that can be combined. It integrates with Instructor for AI agent architecture and supports various APIs like Cohere, Anthropic, and Gemini. The tool includes documentation, examples, and testing features to ensure smooth development and usage.

This repository contains the documentation for the Strands Agents SDK, a simple yet powerful framework for building and running AI agents. The documentation is built using MkDocs and provides guides, examples, and API references. The official documentation is available online at: https://strandsagents.com.

The ai-collection repository is a collection of various artificial intelligence projects and tools aimed at helping developers and researchers in the field of AI. It includes implementations of popular AI algorithms, datasets for training machine learning models, and resources for learning AI concepts. The repository serves as a valuable resource for anyone interested in exploring the applications of artificial intelligence in different domains.

This repository contains examples showcasing various uses of Spring AI Alibaba, from basic to advanced, and best practices for AI projects. It welcomes contributions related to Spring AI Alibaba usage examples, API usage, Spring AI usage examples, and best practices for AI projects. The project structure is designed to modularize functions for easy access and use.

PythonAiRoad is a repository containing classic original articles source code from the 'Algorithm Gourmet House'. It is a platform for sharing algorithms and code related to artificial intelligence. Users are encouraged to contact the author for further discussions or collaborations. The repository serves as a valuable resource for those interested in AI algorithms and implementations.

BrainX is a tool designed for AI enthusiasts to explore and experiment with various machine learning algorithms and models. It provides a user-friendly interface for building, training, and evaluating AI models. The tool aims to simplify the process of developing AI applications and enable users to quickly prototype and test their ideas.

Azure AI Docs is a repository that provides detailed documentation and resources for developers looking to leverage Microsoft's AI services on the Azure platform. The repository covers a wide range of topics including machine learning, natural language processing, computer vision, and more. Developers can find tutorials, code samples, best practices, and guidelines to help them integrate AI capabilities into their applications seamlessly.

The repository 'ethical' contains the live website for The Institute for Ethical AI & Machine Learning. It provides information about the institute, the Ethical ML Network, and the 8 Machine Learning Principles. The repository is open for contributions by the community through pull requests or issue submissions.

This repository is a comprehensive collection of practical examples, tutorials, and recipes for building powerful LLM-powered applications. From simple chatbots to advanced AI agents, these projects serve as a guide for developers working with various AI frameworks and tools. Powered by Nebius AI Studio - your one-stop platform for building and deploying AI applications.

Spring AI Examples is a repository containing various examples of integrating artificial intelligence capabilities into Spring applications. The examples cover a wide range of AI technologies such as machine learning, natural language processing, computer vision, and more. These examples serve as a practical guide for developers looking to incorporate AI functionalities into their Spring projects.

This repository is part of the Certified Cloud Native Applied Generative AI Engineer program, focusing on Applied Generative AI Fundamentals. It covers prompt engineering, developing custom GPTs, and Multi AI Agent Systems. The course helps in building a strong understanding of generative AI, applying Large Language Models (LLMs) and diffusion models practically. It introduces principles of prompt engineering to work efficiently with AI, creating custom AI models and GPTs using OpenAI, Azure, and Google technologies. It also utilizes open source libraries like LangChain, CrewAI, and LangGraph to automate tasks and business processes.

Disciplined AI Software Development is a comprehensive repository that provides guidelines and best practices for developing AI software in a disciplined manner. It covers topics such as project organization, code structure, documentation, testing, and deployment strategies to ensure the reliability, scalability, and maintainability of AI applications. The repository aims to help developers and teams navigate the complexities of AI development by offering practical advice and examples to follow.

Aishare is a collaborative platform for sharing AI models and datasets. It allows users to upload, download, and explore various AI models and datasets. Users can also rate and comment on the shared resources, providing valuable feedback to the community. Aishare aims to foster collaboration and knowledge sharing in the field of artificial intelligence.

AI Manus is a general-purpose AI Agent system that supports running various tools and operations in a sandbox environment. It offers deployment with minimal dependencies, supports multiple tools like Terminal, Browser, File, Web Search, and messaging tools, allocates separate sandboxes for tasks, manages session history, supports stopping and interrupting conversations, file upload and download, and is multilingual. The system also provides user login and authentication. The project primarily relies on Docker for development and deployment, with model capability requirements and recommended Deepseek and GPT models.

The Ramalama project simplifies working with AI by utilizing OCI containers. It automatically detects GPU support, pulls necessary software in a container, and runs AI models. Users can list, pull, run, and serve models easily. The tool aims to support various GPUs and platforms in the future, making AI setup hassle-free.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.

Sorrentum is an open-source project that aims to combine open-source development, startups, and brilliant students to build machine learning, AI, and Web3 / DeFi protocols geared towards finance and economics. The project provides opportunities for internships, research assistantships, and development grants, as well as the chance to work on cutting-edge problems, learn about startups, write academic papers, and get internships and full-time positions at companies working on Sorrentum applications.

TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Zep is an open-source platform for building and deploying large language model (LLM) applications. It provides a suite of tools and services that make it easy to integrate LLMs into your applications, including chat history memory, embedding, vector search, and data enrichment. Zep is designed to be scalable, reliable, and easy to use, making it a great choice for developers who want to build LLM-powered applications quickly and easily.

This repository codifies the Airflow cluster that is deployed at workflow.telemetry.mozilla.org (behind SSO) and commonly referred to as "WTMO" or simply "Airflow". Some links relevant to users and developers of WTMO: * The `dags` directory in this repository contains some custom DAG definitions * Many of the DAGs registered with WTMO don't live in this repository, but are instead generated from ETL task definitions in bigquery-etl * The Data SRE team maintains a WTMO Developer Guide (behind SSO)

Mojo is a new programming language that bridges the gap between research and production by combining Python syntax and ecosystem with systems programming and metaprogramming features. Mojo is still young, but it is designed to become a superset of Python over time.

PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps you to explore, clean, and analyze your data using generative AI.

Databend is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.