Instill Core is an open-source orchestrator comprising a collection of source-available projects designed to streamline every aspect of building versatile AI features with unstructured data. It includes Instill VDP (Versatile Data Pipeline) for unstructured data, AI, and pipeline orchestration, Instill Model for scalable MLOps and LLMOps for open-source or custom AI models, and Instill Artifact for unified unstructured data management. Instill Core can be used for tasks such as building, testing, and sharing pipelines, importing, serving, fine-tuning, and monitoring ML models, and transforming documents, images, audio, and video into a unified AI-ready format.

Simple Transformers is a library based on the Transformers library by HuggingFace, allowing users to quickly train and evaluate Transformer models with only 3 lines of code. It supports various tasks such as Information Retrieval, Language Models, Encoder Model Training, Sequence Classification, Token Classification, Question Answering, Language Generation, T5 Model, Seq2Seq Tasks, Multi-Modal Classification, and Conversational AI.

Codemod platform is a tool that helps developers create, distribute, and run codemods in codebases of any size. The AI-powered, community-led codemods enable automation of framework upgrades, large refactoring, and boilerplate programming with speed and developer experience. It aims to make dream migrations a reality for developers by providing a platform for seamless codemod operations.

Agenta is an open-source LLM developer platform for prompt engineering, evaluation, human feedback, and deployment of complex LLM applications. It provides tools for prompt engineering and management, evaluation, human annotation, and deployment, all without imposing any restrictions on your choice of framework, library, or model. Agenta allows developers and product teams to collaborate in building production-grade LLM-powered applications in less time.

AnyLabeling is a tool for effortless data labeling with AI support from YOLO and Segment Anything. It combines features from LabelImg and Labelme with an improved UI and auto-labeling capabilities. Users can annotate images with polygons, rectangles, circles, lines, and points, as well as perform auto-labeling using YOLOv5 and Segment Anything. The tool also supports text detection, recognition, and Key Information Extraction (KIE) labeling, with multiple language options available such as English, Vietnamese, and Chinese.

AI-on-the-edge-device is a project that enables users to digitize analog water, gas, power, and other meters using an ESP32 board with a supported camera. It integrates Tensorflow Lite for AI processing, offers a small and affordable device with integrated camera and illumination, provides a web interface for administration and control, supports Homeassistant, Influx DB, MQTT, and REST API. The device captures meter images, extracts Regions of Interest (ROIs), runs them through AI for digitization, and allows users to send data to MQTT, InfluxDb, or access it via REST API. The project also includes 3D-printable housing options and tools for logfile management.

Rivet is a desktop application for creating complex AI agents and prompt chaining, and embedding it in your application. Rivet currently has LLM support for OpenAI GPT-3.5 and GPT-4, Anthropic Claude Instant and Claude 2, [Anthropic Claude 3 Haiku, Sonnet, and Opus](https://www.anthropic.com/news/claude-3-family), and AssemblyAI LeMUR framework for voice data. Rivet has embedding/vector database support for OpenAI Embeddings and Pinecone. Rivet also supports these additional integrations: Audio Transcription from AssemblyAI. Rivet core is a TypeScript library for running graphs created in Rivet. It is used by the Rivet application, but can also be used in your own applications, so that Rivet can call into your own application's code, and your application can call into Rivet graphs.

Clash Royale Build-A-Bot is a project that allows users to build their own bot to play Clash Royale. It provides an advanced state generator that accurately returns detailed information using cutting-edge technologies. The project includes tutorials for setting up the environment, building a basic bot, and understanding state generation. It also offers updates such as replacing YOLOv5 with YOLOv8 unit model and enhancing performance features like placement and elixir management. The future roadmap includes plans to label more images of diverse cards, add a tracking layer for unit predictions, publish tutorials on Q-learning and imitation learning, release the YOLOv5 training notebook, implement chest opening and card upgrading features, and create a leaderboard for the best bots developed with this repository.

Bitcart is a platform designed for merchants, users, and developers, providing easy setup and usage. It includes various linked repositories for core daemons, admin panel, ready store, Docker packaging, Python library for coins connection, BitCCL scripting language, documentation, and official site. The platform aims to simplify the process for merchants and developers to interact and transact with cryptocurrencies, offering a comprehensive ecosystem for managing transactions and payments.

Latent Box is a curated collection of resources for AI, creativity, and art. It aims to bridge the information gap with high-quality content, promote diversity and interdisciplinary collaboration, and maintain updates through community co-creation. The website features a wide range of resources, including articles, tutorials, tools, and datasets, covering various topics such as machine learning, computer vision, natural language processing, generative art, and creative coding.

The llms.txt hub is a centralized repository for llms.txt implementations and resources, facilitating interactions between LLM-powered tools and services with documentation and codebases. It standardizes documentation access, enhances AI model interpretation, improves AI response accuracy, and sets boundaries for AI content interaction across various projects and platforms.

AIResume is an open-source resume creation platform that helps users easily create professional resumes, integrating AI technology to assist users in polishing their resumes. The project allows for template development using Vue 3, Vite, TypeScript, and Ant Design Vue. Users can edit resumes, export them as PDFs, switch between multiple resume templates, and collaborate on template development. AI features include resume refinement, deep optimization based on individual projects or experiences, and simulated interviews for user practice. Additional functionalities include theme color switching, high customization options, dark/light mode switching, real-time preview, drag-and-drop resume scaling, data export/import, data clearing, sample data prefilling, template market showcasing, and more.

WeChatMsg is a tool designed to help users manage and analyze their WeChat data. It aims to provide users with the ability to preserve their precious memories and create a personalized AI companion. The tool allows users to extract and export various types of data from WeChat, such as text, images, contacts, and more. Additionally, it offers features like analyzing chat data and generating visual annual reports. WeChatMsg is built on the idea of empowering users to take control of their data and foster emotional connections through technology.

Jan is an open-source ChatGPT alternative that runs 100% offline on your computer. It supports universal architectures, including Nvidia GPUs, Apple M-series, Apple Intel, Linux Debian, and Windows x64. Jan is currently in development, so expect breaking changes and bugs. It is lightweight and embeddable, and can be used on its own within your own projects.

General Framework is a cross-platform library designed to help create apps with a unified codebase using Flutter. It offers features such as cross-platform support, standardized style code, a CLI for easier usage, API integration for bot development, customizable extensions for faster development, and user-friendly information. The library is intended to streamline the app, server, bot, and userbot creation process by providing a comprehensive set of tools and functionalities.

An Open-Source Engineering Guide for Prompt-in-context-learning from EgoAlpha Lab. 📝 Papers | ⚡️ Playground | 🛠 Prompt Engineering | 🌍 ChatGPT Prompt | ⛳ LLMs Usage Guide > **⭐️ Shining ⭐️:** This is fresh, daily-updated resources for in-context learning and prompt engineering. As Artificial General Intelligence (AGI) is approaching, let’s take action and become a super learner so as to position ourselves at the forefront of this exciting era and strive for personal and professional greatness. The resources include: _🎉Papers🎉_: The latest papers about _In-Context Learning_ , _Prompt Engineering_ , _Agent_ , and _Foundation Models_. _🎉Playground🎉_: Large language models（LLMs）that enable prompt experimentation. _🎉Prompt Engineering🎉_: Prompt techniques for leveraging large language models. _🎉ChatGPT Prompt🎉_: Prompt examples that can be applied in our work and daily lives. _🎉LLMs Usage Guide🎉_: The method for quickly getting started with large language models by using LangChain. In the future, there will likely be two types of people on Earth (perhaps even on Mars, but that's a question for Musk): - Those who enhance their abilities through the use of AIGC; - Those whose jobs are replaced by AI automation. 💎EgoAlpha: Hello! human👤, are you ready?

Instill Core is an open-source orchestrator comprising a collection of source-available projects designed to streamline every aspect of building versatile AI features with unstructured data. It includes Instill VDP (Versatile Data Pipeline) for unstructured data, AI, and pipeline orchestration, Instill Model for scalable MLOps and LLMOps for open-source or custom AI models, and Instill Artifact for unified unstructured data management. Instill Core can be used for tasks such as building, testing, and sharing pipelines, importing, serving, fine-tuning, and monitoring ML models, and transforming documents, images, audio, and video into a unified AI-ready format.

fastRAG is a research framework designed to build and explore efficient retrieval-augmented generative models. It incorporates state-of-the-art Large Language Models (LLMs) and Information Retrieval to empower researchers and developers with a comprehensive tool-set for advancing retrieval augmented generation. The framework is optimized for Intel hardware, customizable, and includes key features such as optimized RAG pipelines, efficient components, and RAG-efficient components like ColBERT and Fusion-in-Decoder (FiD). fastRAG supports various unique components and backends for running LLMs, making it a versatile tool for research and development in the field of retrieval-augmented generation.

AI on OpenShift is a site providing installation recipes, patterns, and demos for AI/ML tools and applications used in Data Science and Data Engineering projects running on OpenShift. It serves as a comprehensive resource for developers looking to deploy AI solutions on the OpenShift platform.

Sematic is an open-source ML development platform that allows ML Engineers and Data Scientists to write complex end-to-end pipelines with Python. It can be executed locally, on a cloud VM, or on a Kubernetes cluster. Sematic enables chaining data processing jobs with model training into reproducible pipelines that can be monitored and visualized in a web dashboard. It offers features like easy onboarding, local-to-cloud parity, end-to-end traceability, access to heterogeneous compute resources, and reproducibility.

SuperKnowa is a fast framework to build Enterprise RAG (Retriever Augmented Generation) Pipelines at Scale, powered by watsonx. It accelerates Enterprise Generative AI applications to get prod-ready solutions quickly on private data. The framework provides pluggable components for tackling various Generative AI use cases using Large Language Models (LLMs), allowing users to assemble building blocks to address challenges in AI-driven text generation. SuperKnowa is battle-tested from 1M to 200M private knowledge base & scaled to billions of retriever tokens.

ZetaForge is an open-source AI platform designed for rapid development of advanced AI and AGI pipelines. It allows users to assemble reusable, customizable, and containerized Blocks into highly visual AI Pipelines, enabling rapid experimentation and collaboration. With ZetaForge, users can work with AI technologies in any programming language, easily modify and update AI pipelines, dive into the code whenever needed, utilize community-driven blocks and pipelines, and share their own creations. The platform aims to accelerate the development and deployment of advanced AI solutions through its user-friendly interface and community support.

AdalFlow is a library designed to help developers build and optimize Large Language Model (LLM) task pipelines. It follows a design pattern similar to PyTorch, offering a light, modular, and robust codebase. Named in honor of Ada Lovelace, AdalFlow aims to inspire more women to enter the AI field. The library is tailored for various GenAI applications like chatbots, translation, summarization, code generation, and autonomous agents, as well as classical NLP tasks such as text classification and named entity recognition. AdalFlow emphasizes modularity, robustness, and readability to support users in customizing and iterating code for their specific use cases.

Data Prep Kit is a community project aimed at democratizing and speeding up unstructured data preparation for LLM app developers. It provides high-level APIs and modules for transforming data (code, language, speech, visual) to optimize LLM performance across different use cases. The toolkit supports Python, Ray, Spark, and Kubeflow Pipelines runtimes, offering scalability from laptop to datacenter-scale processing. Developers can contribute new custom modules and leverage the data processing library for building data pipelines. Automation features include workflow automation with Kubeflow Pipelines for transform execution.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.