Lobe Icons is a collection of popular AI / LLM Model Brand SVG logos and icons. It features lightweight and scalable icons designed with highly optimized scalable vector graphics (SVG) for optimal performance. The collection is tree-shakable, allowing users to import only the icons they need to reduce the overall bundle size of their projects. Lobe Icons has an active community of designers and developers who can contribute and seek support on platforms like GitHub and Discord. The repository supports a wide range of brands across different models, providers, and applications, with more brands continuously being added through contributions. Users can easily install Lobe UI with the provided commands and integrate it with NextJS for server-side rendering. Local development can be done using Github Codespaces or by cloning the repository. Contributions are welcome, and users can contribute code by checking out the GitHub Issues. The project is MIT licensed and maintained by LobeHub.

Lobe CLI Toolbox is an AI CLI Toolbox designed to enhance git commit and i18n workflow efficiency. It includes tools like Lobe Commit for generating Gitmoji-based commit messages and Lobe i18n for automating the i18n translation process. The toolbox also features Lobe label for automatically copying issues labels from a template repo. It supports features such as automatic splitting of large files, incremental updates, and customization options for the OpenAI model, API proxy, and temperature.

Awesome Text2SQL is a curated repository containing tutorials and resources for Large Language Models, Text2SQL, Text2DSL, Text2API, Text2Vis, and more. It provides guidelines on converting natural language questions into structured SQL queries, with a focus on NL2SQL. The repository includes information on various models, datasets, evaluation metrics, fine-tuning methods, libraries, and practice projects related to Text2SQL. It serves as a comprehensive resource for individuals interested in working with Text2SQL and related technologies.

ProChat is a components library focused on quickly building large language model chat interfaces. It empowers developers to create rich, dynamic, and intuitive chat interfaces with features like automatic chat caching, streamlined conversations, message editing tools, auto-rendered Markdown, and programmatic controls. The tool also includes design evolution plans such as customized dialogue rendering, enhanced request parameters, personalized error handling, expanded documentation, and atomic component design.

BMW MD is a simple WhatsApp user BOT created by Ibrahim Tech. It allows users to scan pairing codes or QR codes to connect to WhatsApp and deploy the bot on Heroku. The bot can be used to perform various tasks such as sending messages, receiving messages, and managing contacts. It is released under the MIT License and contributions are welcome.

A collection of papers and resources about Large Language Models (LLM) for Graph Learning (Graph). Integrating LLMs with graph learning techniques to enhance performance in graph learning tasks. Categorizes approaches based on four primary paradigms and nine secondary-level categories. Valuable for research or practice in self-supervised learning for recommendation systems.

EvalAI is an open-source platform for evaluating and comparing machine learning (ML) and artificial intelligence (AI) algorithms at scale. It provides a central leaderboard and submission interface, making it easier for researchers to reproduce results mentioned in papers and perform reliable & accurate quantitative analysis. EvalAI also offers features such as custom evaluation protocols and phases, remote evaluation, evaluation inside environments, CLI support, portability, and faster evaluation.

The KAN-GPT repository is a PyTorch implementation of Generative Pre-trained Transformers (GPTs) using Kolmogorov-Arnold Networks (KANs) for language modeling. It provides a model for generating text based on prompts, with a focus on improving performance compared to traditional MLP-GPT models. The repository includes scripts for training the model, downloading datasets, and evaluating model performance. Development tasks include integrating with other libraries, testing, and documentation.

DuckDuckGPT brings the magic of ChatGPT to DDG (powered by GPT-4!). DuckDuckGPT is a browser extension that allows you to use ChatGPT within DuckDuckGo. This means you can ask ChatGPT questions, get help with tasks, and generate creative content, all without leaving DuckDuckGo. DuckDuckGPT is easy to use. Once you have installed the extension, simply type your question into the DuckDuckGo search bar and hit enter. ChatGPT will then generate a response that will appear below the search results. DuckDuckGPT is a powerful tool that can help you with a wide variety of tasks. Here are just a few examples of what you can use it for: * Get help with research * Write essays and other creative content * Translate languages * Get coding help * Answer trivia questions * And much more! DuckDuckGPT is still in development, but it is already a very powerful tool. As GPT-4 continues to improve, DuckDuckGPT will only get better. So if you are looking for a way to make your DuckDuckGo searches more productive, be sure to give DuckDuckGPT a try.

RealScaler is a Windows app powered by RealESRGAN AI to enhance, upscale, and de-noise photos and videos. It provides an easy-to-use GUI for upscaling images and videos using multiple AI models. The tool supports automatic image tiling and merging to avoid GPU VRAM limitations, resizing images/videos before upscaling, interpolation between original and upscaled content, and compatibility with various image and video formats. RealScaler is written in Python and requires Windows 11/10, at least 8GB RAM, and a Directx12 compatible GPU with 4GB VRAM. Future versions aim to enhance performance, support more GPUs, offer a new GUI with Windows 11 style, include audio for upscaled videos, and provide features like metadata extraction and application from original to upscaled files.

Aim is an open-source, self-hosted ML experiment tracking tool designed to handle 10,000s of training runs. Aim provides a performant and beautiful UI for exploring and comparing training runs. Additionally, its SDK enables programmatic access to tracked metadata — perfect for automations and Jupyter Notebook analysis. **Aim's mission is to democratize AI dev tools 🎯**

LLMFarm is an iOS and MacOS app designed to work with large language models (LLM). It allows users to load different LLMs with specific parameters, test the performance of various LLMs on iOS and macOS, and identify the most suitable model for their projects. The tool is based on ggml and llama.cpp by Georgi Gerganov and incorporates sources from rwkv.cpp by saharNooby, Mia by byroneverson, and LlamaChat by alexrozanski. LLMFarm features support for MacOS (13+) and iOS (16+), various inferences and sampling methods, Metal compatibility (not supported on Intel Mac), model setting templates, LoRA adapters support, LoRA finetune support, LoRA export as model support, and more. It also offers a range of inferences including LLaMA, GPTNeoX, Replit, GPT2, Starcoder, RWKV, Falcon, MPT, Bloom, and others. Additionally, it supports multimodal models like LLaVA, Obsidian, and MobileVLM. Users can customize inference options through JSON files and access supported models for download.

BraveGPT is a userscript that brings the power of ChatGPT to Brave Search. It allows users to engage with a conversational AI assistant directly within their search results, providing instant and personalized responses to their queries. BraveGPT is powered by GPT-4, the latest and most advanced language model from OpenAI, ensuring accurate and comprehensive answers. With BraveGPT, users can ask questions, get summaries, generate creative content, and more, all without leaving the Brave Search interface. The tool is easy to install and use, making it accessible to users of all levels. BraveGPT is a valuable addition to the Brave Search experience, enhancing its capabilities and providing users with a more efficient and informative search experience.

LLMFarm_core.swift is a Swift library designed to work with large language models (LLM). It enables users to load different LLMs with specific parameters. The library supports MacOS (13+) and iOS (16+), offering various inferences and sampling methods. It includes features such as Metal support (not compatible with Intel Mac), model setting templates, LoRA adapters support, and LoRA train support. The library is based on ggml and llama.cpp by Georgi Gerganov, with additional sources from rwkv.cpp by saharNooby and Mia by byroneverson.

This repository is a curated list of open-source libraries for production large language models. It includes tools for data preprocessing, training/finetuning, evaluation/benchmarking, serving/inference, application/RAG, testing/monitoring, and guardrails/security. The repository also provides a new category called LLM Cookbook/Examples for showcasing examples and guides on using various LLM APIs.

The NaLLM project repository explores the synergies between Neo4j and Large Language Models (LLMs) through three primary use cases: Natural Language Interface to a Knowledge Graph, Creating a Knowledge Graph from Unstructured Data, and Generating a Report using static and LLM data. The repository contains backend and frontend code organized for easy navigation. It includes blog posts, a demo database, instructions for running demos, and guidelines for contributing. The project aims to showcase the potential of Neo4j and LLMs in various applications.

Lobe Icons is a collection of popular AI / LLM Model Brand SVG logos and icons. It features lightweight and scalable icons designed with highly optimized scalable vector graphics (SVG) for optimal performance. The collection is tree-shakable, allowing users to import only the icons they need to reduce the overall bundle size of their projects. Lobe Icons has an active community of designers and developers who can contribute and seek support on platforms like GitHub and Discord. The repository supports a wide range of brands across different models, providers, and applications, with more brands continuously being added through contributions. Users can easily install Lobe UI with the provided commands and integrate it with NextJS for server-side rendering. Local development can be done using Github Codespaces or by cloning the repository. Contributions are welcome, and users can contribute code by checking out the GitHub Issues. The project is MIT licensed and maintained by LobeHub.

IBM Generative AI Python SDK is a tool designed for the Tech Preview program for IBM Foundation Models Studio. It brings IBM Generative AI (GenAI) into Python programs, offering various operations and types. Users can start a trial version or request a demo via the provided link. The SDK was recently rewritten and released under V2 in 2024, with a migration guide available. Contributors are welcome to participate in the open-source project by contributing documentation, tests, bug fixes, and new functionality.

Ollama4j is a Java library that serves as a wrapper or binding for the Ollama server. It facilitates communication with the Ollama server and provides models for deployment. The tool requires Java 11 or higher and can be installed locally or via Docker. Users can integrate Ollama4j into Maven projects by adding the specified dependency. The tool offers API specifications and supports various development tasks such as building, running unit tests, and integration tests. Releases are automated through GitHub Actions CI workflow. Areas of improvement include adhering to Java naming conventions, updating deprecated code, implementing logging, using lombok, and enhancing request body creation. Contributions to the project are encouraged, whether reporting bugs, suggesting enhancements, or contributing code.

OpenKore is a custom client and intelligent automated assistant for Ragnarok Online. It is a free, open source, and cross-platform program (Linux, Windows, and MacOS are supported). To run OpenKore, you need to download and extract it or clone the repository using Git. Configure OpenKore according to the documentation and run openkore.pl to start. The tool provides a FAQ section for troubleshooting, guidelines for reporting issues, and information about botting status on official servers. OpenKore is developed by a global team, and contributions are welcome through pull requests. Various community resources are available for support and communication. Users are advised to comply with the GNU General Public License when using and distributing the software.

Quivr-Mobile is a React Native mobile application that allows users to upload files and engage in chat conversations using the Quivr backend API. It supports features like file upload and chatting with a language model about uploaded data. The project uses technologies like React Native, React Native Paper, and React Native Navigation. Users can follow the installation steps to set up the client and contribute to the project by opening issues or submitting pull requests following the existing coding style.

Welcome to `OPEN ODYSSEY 1.0` - an Open-source extravaganza for Python and AI/ML Projects. Collaborating with MLH (Major League Hacking), this repository welcomes contributions in the form of fixing outstanding issues, submitting bug reports or new feature requests, adding new projects, implementing new models, and encouraging creativity. Follow the instructions to contribute by forking the repository, cloning it to your PC, creating a new folder for your project, and making a pull request. The repository also features a special Leaderboard for top contributors and offers certificates for all participants and mentors. Follow `OPEN ODYSSEY 1.0` on social media for swift approval of your quest.

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.