Ocademy is an AI learning community dedicated to Python, Data Science, Machine Learning, Deep Learning, and MLOps. They promote equal opportunities for everyone to access AI through open-source educational resources. The repository contains curated AI courses, tutorials, books, tools, and resources for learning and creating Generative AI. It also offers an interactive book to help adults transition into AI. Contributors are welcome to join and contribute to the community by following guidelines. The project follows a code of conduct to ensure inclusivity and welcomes contributions from those passionate about Data Science and AI.

TruLens provides a set of tools for developing and monitoring neural nets, including large language models. This includes both tools for evaluation of LLMs and LLM-based applications with _TruLens-Eval_ and deep learning explainability with _TruLens-Explain_. _TruLens-Eval_ and _TruLens-Explain_ are housed in separate packages and can be used independently.

OpenDevin is a platform for autonomous software engineers powered by AI and LLMs. It allows human developers to collaborate with agents to write code, fix bugs, and ship features. The tool operates in a secured docker sandbox and provides access to different LLM providers for advanced configuration options. Users can contribute to the project through code contributions, research and evaluation of LLMs in software engineering, and providing feedback and testing. OpenDevin is community-driven and welcomes contributions from developers, researchers, and enthusiasts looking to advance software engineering with AI.

Friend is an open-source AI wearable device that records everything you say, gives you proactive feedback and advice. It has real-time AI audio processing capabilities, low-powered Bluetooth, open-source software, and a wearable design. The device is designed to be affordable and easy to use, with a total cost of less than $20. To get started, you can clone the repo, choose the version of the app you want to install, and follow the instructions for installing the firmware and assembling the device. Friend is still a prototype project and is provided "as is", without warranty of any kind. Use of the device should comply with all local laws and regulations concerning privacy and data protection.

Kuwa GenAI OS is an open, free, secure, and privacy-focused Generative-AI Operating System. It provides a multi-lingual turnkey solution for GenAI development and deployment on Linux and Windows. Users can enjoy features such as concurrent multi-chat, quoting, full prompt-list import/export/share, and flexible orchestration of prompts, RAGs, bots, models, and hardware/GPUs. The system supports various environments from virtual hosts to cloud, and it is open source, allowing developers to contribute and customize according to their needs.

Workshops is a repository containing workshop subjects and materials for developers. It covers a wide range of topics including AI, AR/VR, hardware, security, software, and peer-to-peer technologies. The repository is designed to provide developers with resources and materials to enhance their skills and knowledge in various technology domains.

Tracecat is an open-source automation platform for security teams. It's designed to be simple but powerful, with a focus on AI features and a practitioner-obsessed UI/UX. Tracecat can be used to automate a variety of tasks, including phishing email investigation, evidence collection, and remediation plan generation.

TEN Framework, short for Transformative Extensions Network, is the world's first real-time multimodal AI agent framework. It offers native support for high-performance, real-time multimodal interactions, supports multiple languages and platforms, enables edge-cloud integration, provides flexibility beyond model limitations, and allows for real-time agent state management. The framework facilitates the development of complex AI applications that transcend the limitations of large models by offering a drag-and-drop programming approach. It is suitable for scenarios like simultaneous interpretation, speech-to-text conversion, multilingual chat rooms, audio interaction, and audio-visual interaction.

ScrapeGraphAI is a web scraping Python library that utilizes LangChain, LLM, and direct graph logic to create scraping pipelines. Users can specify the information they want to extract, and the library will handle the extraction process. This repository contains an official demo/trial for the ScrapeGraphAI library, showcasing its capabilities in web scraping tasks. The tool is designed to simplify the process of extracting data from websites by providing a user-friendly interface and powerful scraping functionalities.

DevChat is an open-source workflow engine that enables developers to create intelligent, automated workflows for engaging with users through a chat panel within their IDEs. It combines script writing flexibility, latest AI models, and an intuitive chat GUI to enhance user experience and productivity. DevChat simplifies the integration of AI in software development, unlocking new possibilities for developers.

Khoj is an open-source, personal AI assistant that extends your capabilities by creating always-available AI agents. You can share your notes and documents to extend your digital brain, and your AI agents have access to the internet, allowing you to incorporate real-time information. Khoj is accessible on Desktop, Emacs, Obsidian, Web, and Whatsapp, and you can share PDF, markdown, org-mode, notion files, and GitHub repositories. You'll get fast, accurate semantic search on top of your docs, and your agents can create deeply personal images and understand your speech. Khoj is self-hostable and always will be.

ScrapeGraphAI is a web scraping Python library that utilizes LangChain, LLM, and direct graph logic to create scraping pipelines. Users can specify the information they want to extract, and the library will handle the extraction process. The tool is designed to simplify web scraping tasks by providing a streamlined and efficient approach to data extraction.

The openfoodfacts-ai repository is dedicated to tracking and storing experimental AI endeavors, models training, and wishlists related to nutrition table detection, category prediction, logos and labels detection, spellcheck, and other AI projects for Open Food Facts. It serves as a hub for integrating AI models into production and collaborating on AI-related issues. The repository also hosts trained models and datasets for public use and experimentation.

Agent Evaluation is a generative AI-powered framework for testing virtual agents. It implements an LLM agent (evaluator) to orchestrate conversations with your own agent (target) and evaluate responses. It supports popular AWS services, allows concurrent multi-turn conversations, defines hooks for additional tasks, and can be used in CI/CD pipelines for faster delivery and stable production environments.

Superagent is an open-source AI assistant framework and API that allows developers to add powerful AI assistants to their applications. These assistants use large language models (LLMs), retrieval augmented generation (RAG), and generative AI to help users with a variety of tasks, including question answering, chatbot development, content generation, data aggregation, and workflow automation. Superagent is backed by Y Combinator and is part of YC W24.

SWE-agent is a tool that turns language models (e.g. GPT-4) into software engineering agents capable of fixing bugs and issues in real GitHub repositories. It achieves state-of-the-art performance on the full test set by resolving 12.29% of issues. The tool is built and maintained by researchers from Princeton University. SWE-agent provides a command line tool and a graphical web interface for developers to interact with. It introduces an Agent-Computer Interface (ACI) to facilitate browsing, viewing, editing, and executing code files within repositories. The tool includes features such as a linter for syntax checking, a specialized file viewer, and a full-directory string searching command to enhance the agent's capabilities. SWE-agent aims to improve prompt engineering and ACI design to enhance the performance of language models in software engineering tasks.

Ocademy is an AI learning community dedicated to Python, Data Science, Machine Learning, Deep Learning, and MLOps. They promote equal opportunities for everyone to access AI through open-source educational resources. The repository contains curated AI courses, tutorials, books, tools, and resources for learning and creating Generative AI. It also offers an interactive book to help adults transition into AI. Contributors are welcome to join and contribute to the community by following guidelines. The project follows a code of conduct to ensure inclusivity and welcomes contributions from those passionate about Data Science and AI.

Reasonable Planning AI is a robust design and data-driven AI solution for game developers. It provides an AI Editor that allows creating AI without Blueprints or C++. The AI can think for itself, plan actions, adapt to the game environment, and act dynamically. It consists of Core components like RpaiGoalBase, RpaiActionBase, RpaiPlannerBase, RpaiReasonerBase, and RpaiBrainComponent, as well as Composer components for easier integration by Game Designers. The tool is extensible, cross-compatible with Behavior Trees, and offers debugging features like visual logging and heuristics testing. It follows a simple path of execution and supports versioning for stability and compatibility with Unreal Engine versions.

Mistreevous is a library written in TypeScript for Node and browsers, used to declaratively define, build, and execute behaviour trees for creating complex AI. It allows defining trees with JSON or a minimal DSL, providing in-browser editor and visualizer. The tool offers methods for tree state, stepping, resetting, and getting node details, along with various composite, decorator, leaf nodes, callbacks, guards, and global functions/subtrees. Version history includes updates for node types, callbacks, global functions, and TypeScript conversion.

AI Engineering Academy aims to provide a structured learning path for individuals looking to learn Applied AI effectively. The platform offers multiple roadmaps covering topics like Retrieval Augmented Generation, Fine-tuning, and Deployment. Each roadmap equips learners with the knowledge and skills needed to excel in applied GenAI. Additionally, the platform will feature Hands-on End-to-End AI projects in the future.

Ocademy is an AI learning community dedicated to Python, Data Science, Machine Learning, Deep Learning, and MLOps. They promote equal opportunities for everyone to access AI through open-source educational resources. The repository contains curated AI courses, tutorials, books, tools, and resources for learning and creating Generative AI. It also offers an interactive book to help adults transition into AI. Contributors are welcome to join and contribute to the community by following guidelines. The project follows a code of conduct to ensure inclusivity and welcomes contributions from those passionate about Data Science and AI.

The go2coding.github.io repository is a collection of resources for AI enthusiasts, providing information on AI products, open-source projects, AI learning websites, and AI learning frameworks. It aims to help users stay updated on industry trends, learn from community projects, access learning resources, and understand and choose AI frameworks. The repository also includes instructions for local and external deployment of the project as a static website, with details on domain registration, hosting services, uploading static web pages, configuring domain resolution, and a visual guide to the AI tool navigation website. Additionally, it offers a platform for AI knowledge exchange through a QQ group and promotes AI tools through a WeChat public account.

The 'step_into_llm' repository is dedicated to the 昇思MindSpore technology open class, which focuses on exploring cutting-edge technologies, combining theory with practical applications, expert interpretations, open sharing, and empowering competitions. The repository contains course materials, including slides and code, for the ongoing second phase of the course. It covers various topics related to large language models (LLMs) such as Transformer, BERT, GPT, GPT2, and more. The course aims to guide developers interested in LLMs from theory to practical implementation, with a special emphasis on the development and application of large models.

AI-lectures is a repository containing educational materials on various topics related to Artificial Intelligence, including Machine Learning, Robotics, and Optimization. It provides full scripts, slides, and exercises with solutions for different lectures. Users can compile the materials into PDFs for easy access and reference. The repository aims to offer comprehensive resources for individuals interested in learning about AI and its applications in intelligent systems.

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.