earth2studio

Earth2Studio is a Python-based package designed to enable users to quickly get started with AI weather and climate models. It provides access to pre-trained models, diagnostic tools, data sources, IO utilities, perturbation methods, and sample workflows for building custom weather prediction workflows. The package aims to empower users to explore AI-driven meteorology through modular components and seamless integration with other Nvidia packages like Modulus.

Argilla is a collaboration platform for AI engineers and domain experts that require high-quality outputs, full data ownership, and overall efficiency. It helps users improve AI output quality through data quality, take control of their data and models, and improve efficiency by quickly iterating on the right data and models. Argilla is an open-source community-driven project that provides tools for achieving and maintaining high-quality data standards, with a focus on NLP and LLMs. It is used by AI teams from companies like the Red Cross, Loris.ai, and Prolific to improve the quality and efficiency of AI projects.

Nixtla is a production-ready generative pretrained transformer for time series forecasting and anomaly detection. It can accurately predict various domains such as retail, electricity, finance, and IoT with just a few lines of code. TimeGPT introduces a paradigm shift with its standout performance, efficiency, and simplicity, making it accessible even to users with minimal coding experience. The model is based on self-attention and is independently trained on a vast time series dataset to minimize forecasting error. It offers features like zero-shot inference, fine-tuning, API access, adding exogenous variables, multiple series forecasting, custom loss function, cross-validation, prediction intervals, and handling irregular timestamps.

Bisheng is a leading open-source **large model application development platform** that empowers and accelerates the development and deployment of large model applications, helping users enter the next generation of application development with the best possible experience.

Macaw-LLM is a pioneering multi-modal language modeling tool that seamlessly integrates image, audio, video, and text data. It builds upon CLIP, Whisper, and LLaMA models to process and analyze multi-modal information effectively. The tool boasts features like simple and fast alignment, one-stage instruction fine-tuning, and a new multi-modal instruction dataset. It enables users to align multi-modal features efficiently, encode instructions, and generate responses across different data types.

The NVIDIA TensorRT Model Optimizer is a library designed to quantize and compress deep learning models for optimized inference on GPUs. It offers state-of-the-art model optimization techniques including quantization and sparsity to reduce inference costs for generative AI models. Users can easily stack different optimization techniques to produce quantized checkpoints from torch or ONNX models. The quantized checkpoints are ready for deployment in inference frameworks like TensorRT-LLM or TensorRT, with planned integrations for NVIDIA NeMo and Megatron-LM. The tool also supports 8-bit quantization with Stable Diffusion for enterprise users on NVIDIA NIM. Model Optimizer is available for free on NVIDIA PyPI, and this repository serves as a platform for sharing examples, GPU-optimized recipes, and collecting community feedback.

Wren Engine is a semantic engine designed to serve as the backbone of the semantic layer for LLMs. It simplifies the user experience by translating complex data structures into a business-friendly format, enabling end-users to interact with data using familiar terminology. The engine powers the semantic layer with advanced capabilities to define and manage modeling definitions, metadata, schema, data relationships, and logic behind calculations and aggregations through an analytics-as-code design approach. By leveraging Wren Engine, organizations can ensure a developer-friendly semantic layer that reflects nuanced data relationships and dynamics, facilitating more informed decision-making and strategic insights.

hugegraph-ai aims to explore the integration of HugeGraph with artificial intelligence (AI) and provide comprehensive support for developers to leverage HugeGraph's AI capabilities in their projects. It includes modules for large language models, graph machine learning, and a Python client for HugeGraph. The project aims to address challenges like timeliness, hallucination, and cost-related issues by integrating graph systems with AI technologies.

EmbedJs is a NodeJS framework that simplifies RAG application development by efficiently processing unstructured data. It segments data, creates relevant embeddings, and stores them in a vector database for quick retrieval.

FreeGenius AI is an ambitious project offering a comprehensive suite of AI solutions that mirror the capabilities of LetMeDoIt AI. It is designed to engage in intuitive conversations, execute codes, provide up-to-date information, and perform various tasks. The tool is free, customizable, and provides access to real-time data and device information. It aims to support offline and online backends, open-source large language models, and optional API keys. Users can use FreeGenius AI for tasks like generating tweets, analyzing audio, searching financial data, checking weather, and creating maps.

Onyx is an open-source Gen-AI and Enterprise Search tool that serves as an AI Assistant connected to company documents, apps, and people. It provides a chat interface, can be deployed anywhere, and offers features like user authentication, role management, chat persistence, and UI for configuring AI Assistants. Onyx acts as an Enterprise Search tool across various workplace platforms, enabling users to access team-specific knowledge and perform tasks like document search, AI answers for natural language queries, and integration with common workplace tools like Slack, Google Drive, Confluence, etc.

Quadratic is a modern multiplayer spreadsheet application that integrates Python, AI, and SQL functionalities. It aims to streamline team collaboration and data analysis by enabling users to pull data from various sources and utilize popular data science tools. The application supports building dashboards, creating internal tools, mixing data from different sources, exploring data for insights, visualizing Python workflows, and facilitating collaboration between technical and non-technical team members. Quadratic is built with Rust + WASM + WebGL to ensure seamless performance in the browser, and it offers features like WebGL Grid, local file management, Python and Pandas support, Excel formula support, multiplayer capabilities, charts and graphs, and team support. The tool is currently in Beta with ongoing development for additional features like JS support, SQL database support, and AI auto-complete.

LabelLLM is an open-source data annotation platform designed to optimize the data annotation process for LLM development. It offers flexible configuration, multimodal data support, comprehensive task management, and AI-assisted annotation. Users can access a suite of annotation tools, enjoy a user-friendly experience, and enhance efficiency. The platform allows real-time monitoring of annotation progress and quality control, ensuring data integrity and timeliness.

Refly.AI is an open-source AI-native creation engine that empowers users to transform ideas into production-ready content. It features a free-form canvas interface with multi-threaded conversations, knowledge base integration, contextual memory, intelligent search, WYSIWYG AI editor, and more. Users can leverage AI-powered capabilities, context memory, knowledge base integration, quotes, and AI document editing to enhance their content creation process. Refly offers both cloud and self-hosting options, making it suitable for individuals, enterprises, and organizations. The tool is designed to facilitate human-AI collaboration and streamline content creation workflows.

Buildel is an AI automation platform that empowers users to create versatile workflows without writing code. It supports multiple providers and interfaces, offers pre-built use cases, and allows users to bring their own API keys. Ideal for AI-powered document retrieval, conversational interfaces, and data integration. Users can get started at app.buildel.ai or run Buildel locally with Node.js, Elixir/Erlang, Docker, Git, and JQ installed. Join the community on Discord for support and discussions.

InvokeAI is a leading creative engine built to empower professionals and enthusiasts alike. Generate and create stunning visual media using the latest AI-driven technologies. InvokeAI offers an industry leading Web Interface, interactive Command Line Interface, and also serves as the foundation for multiple commercial products.

Awesome Large Weather Models (LWMs) is a curated collection of articles and resources related to large weather models used in AI for Earth and AI for Science. It includes information on various cutting-edge weather forecasting models, benchmark datasets, and research papers. The repository serves as a hub for researchers and enthusiasts to explore the latest advancements in weather modeling and forecasting.

Earth2Studio is a Python-based package designed to enable users to quickly get started with AI weather and climate models. It provides access to pre-trained models, diagnostic tools, data sources, IO utilities, perturbation methods, and sample workflows for building custom weather prediction workflows. The package aims to empower users to explore AI-driven meteorology through modular components and seamless integration with other Nvidia packages like Modulus.

Welcome to the μLearn x Pathway Initiative, an exciting adventure into the world of Artificial Intelligence (AI)! This comprehensive course, developed in collaboration with Pathway, will empower you with the knowledge and skills needed to navigate the fascinating world of AI, with a special focus on Large Language Models (LLMs).

Autonomous agents are designed to achieve specific objectives through self-guided instructions. With the emergence and growth of large language models (LLMs), there is a growing trend in utilizing LLMs as fundamental controllers for these autonomous agents. This repository conducts a comprehensive survey study on the construction, application, and evaluation of LLM-based autonomous agents. It explores essential components of AI agents, application domains in natural sciences, social sciences, and engineering, and evaluation strategies. The survey aims to be a resource for researchers and practitioners in this rapidly evolving field.

Firebase Genkit (beta) is a framework with powerful tooling to help app developers build, test, deploy, and monitor AI-powered features with confidence. Genkit is cloud optimized and code-centric, integrating with many services that have free tiers to get started. It provides unified API for generation, context-aware AI features, evaluation of AI workflow, extensibility with plugins, easy deployment to Firebase or Google Cloud, observability and monitoring with OpenTelemetry, and a developer UI for prototyping and testing AI features locally. Genkit works seamlessly with Firebase or Google Cloud projects through official plugins and templates.

The Vector Cookbook is a collection of recipes and sample application starter kits for building AI applications with LLMs using PostgreSQL and Timescale Vector. Timescale Vector enhances PostgreSQL for AI applications by enabling the storage of vector, relational, and time-series data with faster search, higher recall, and more efficient time-based filtering. The repository includes resources, sample applications like TSV Time Machine, and guides for creating, storing, and querying OpenAI embeddings with PostgreSQL and pgvector. Users can learn about Timescale Vector, explore performance benchmarks, and access Python client libraries and tutorials.

The W3C Cognitive AI Community Group focuses on advancing Cognitive AI through collaboration on defining use cases, open source implementations, and application areas. The group aims to demonstrate the potential of Cognitive AI in various domains such as customer services, healthcare, cybersecurity, online learning, autonomous vehicles, manufacturing, and web search. They work on formal specifications for chunk data and rules, plausible knowledge notation, and neural networks for human-like AI. The group positions Cognitive AI as a combination of symbolic and statistical approaches inspired by human thought processes. They address research challenges including mimicry, emotional intelligence, natural language processing, and common sense reasoning. The long-term goal is to develop cognitive agents that are knowledgeable, creative, collaborative, empathic, and multilingual, capable of continual learning and self-awareness.

The Enterprise Azure OpenAI Hub is a comprehensive repository designed to guide users through the world of Generative AI on the Azure platform. It offers a structured learning experience to accelerate the transition from concept to production in an Enterprise context. The hub empowers users to explore various use cases with Azure services, ensuring security and compliance. It provides real-world examples and playbooks for practical insights into solving complex problems and developing cutting-edge AI solutions. The repository also serves as a library of proven patterns, aligning with industry standards and promoting best practices for secure and compliant AI development.

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.