Lingo is an interactive platform for language learning that provides a modern UI/UX experience. It offers features like courses, quests, and a shop for users to engage with. The tech stack includes React JS, Next JS, Typescript, Tailwind CSS, Vercel, and Postgresql. Users can contribute to the project by submitting changes via pull requests. The platform utilizes resources from CodeWithAntonio, Kenney Assets, Freesound, Elevenlabs AI, and Flagpack. Key dependencies include @clerk/nextjs, @neondatabase/serverless, @radix-ui/react-avatar, and more. Users can follow the project creator on GitHub and Twitter, as well as subscribe to their YouTube channel for updates. To learn more about Next.js, users can refer to the Next.js documentation and interactive tutorial.

Genius is a modern Next.js 14 SaaS AI platform that provides a comprehensive folder structure for app development. It offers features like authentication, dashboard management, landing pages, API integration, and more. The platform is built using React JS, Next JS, TypeScript, Tailwind CSS, and integrates with services like Netlify, Prisma, MySQL, and Stripe. Genius enables users to create AI-powered applications with functionalities such as conversation generation, image processing, code generation, and more. It also includes features like Clerk authentication, OpenAI integration, Replicate API usage, Aiven database connectivity, and Stripe API/webhook setup. The platform is fully configurable and provides a seamless development experience for building AI-driven applications.

Easy Dataset is a specialized application designed to streamline the creation of fine-tuning datasets for Large Language Models (LLMs). It offers an intuitive interface for uploading domain-specific files, intelligently splitting content, generating questions, and producing high-quality training data for model fine-tuning. With Easy Dataset, users can transform domain knowledge into structured datasets compatible with all OpenAI-format compatible LLM APIs, making the fine-tuning process accessible and efficient.

Llama Assistant is an AI-powered assistant that helps with daily tasks, such as voice recognition, natural language processing, summarizing text, rephrasing sentences, answering questions, and more. It runs offline on your local machine, ensuring privacy by not sending data to external servers. The project is a work in progress with regular feature additions.

IMAGINE - AI is a groundbreaking image generator tool that leverages the power of OpenAI's DALL-E 2 API library to create extraordinary visuals. Developed using Node.js and Express, this tool offers a transformative way to unleash artistic creativity and imagination by generating unique and captivating images through simple prompts or keywords.

PankoGPT is an AI companion platform that allows users to easily create and deploy custom AI companions on messaging platforms like WhatsApp, Discord, and Telegram. Users can customize companion behavior, configure settings, and equip companions with various tools without the need for coding. The platform aims to provide contextual understanding and user-friendly interface for creating companions that respond based on context and offer configurable tools for enhanced capabilities. Planned features include expanded functionality, pre-built skills, and optimization for better performance.

FreeGPT4-WEB-API is a Python server that allows you to have a self-hosted GPT-4 Unlimited and Free WEB API, via the latest Bing's AI. It uses Flask and GPT4Free libraries. GPT4Free provides an interface to the Bing's GPT-4. The server can be configured by editing the `FreeGPT4_Server.py` file. You can change the server's port, host, and other settings. The only cookie needed for the Bing model is `_U`.

Llama Assistant is a local AI assistant that respects your privacy. It is an AI-powered assistant that can recognize your voice, process natural language, and perform various actions based on your commands. It can help with tasks like summarizing text, rephrasing sentences, answering questions, writing emails, and more. The assistant runs offline on your local machine, ensuring privacy by not sending data to external servers. It supports voice recognition, natural language processing, and customizable UI with adjustable transparency. The project is a work in progress with new features being added regularly.

Auto-subs is a tool designed to automatically transcribe editing timelines using OpenAI Whisper and Stable-TS for extreme accuracy. It generates subtitles in a custom style, is completely free, and runs locally within Davinci Resolve. It works on Mac, Linux, and Windows, supporting both Free and Studio versions of Resolve. Users can jump to positions on the timeline using the Subtitle Navigator and translate from any language to English. The tool provides a user-friendly interface for creating and customizing subtitles for video content.

Tongyi DeepResearch is an agentic large language model with 30.5 billion total parameters, designed for long-horizon, deep information-seeking tasks. It demonstrates state-of-the-art performance across various search benchmarks. The model features a fully automated synthetic data generation pipeline, large-scale continual pre-training on agentic data, end-to-end reinforcement learning, and compatibility with two inference paradigms. Users can download the model directly from HuggingFace or ModelScope. The repository also provides benchmark evaluation scripts and information on the Deep Research Agent Family.

PySpur is a graph-based editor designed for LLM (Large Language Models) workflows. It offers modular building blocks, node-level debugging, and performance evaluation. The tool is easy to hack, supports JSON configs for workflow graphs, and is lightweight with minimal dependencies. Users can quickly set up PySpur by cloning the repository, creating a .env file, starting docker services, and accessing the portal. PySpur can also work with local models served using Ollama, with steps provided for configuration. The roadmap includes features like canvas, async/batch execution, support for Ollama, new nodes, pipeline optimization, templates, code compilation, multimodal support, and more.

ZenGuard AI enables AI developers to integrate production-level, low-code LLM (Large Language Model) guardrails into their generative AI applications effortlessly. With ZenGuard AI, ensure your application operates within trusted boundaries, is protected from prompt injections, and maintains user privacy without compromising on performance.

LLM Interface is an npm module that streamlines interactions with various Large Language Model (LLM) providers in Node.js applications. It offers a unified interface for switching between providers and models, supporting 36 providers and hundreds of models. Features include chat completion, streaming, error handling, extensibility, response caching, retries, JSON output, and repair. The package relies on npm packages like axios, @google/generative-ai, dotenv, jsonrepair, and loglevel. Installation is done via npm, and usage involves sending prompts to LLM providers. Tests can be run using npm test. Contributions are welcome under the MIT License.

AutoRAG is an AutoML tool designed to automatically find the optimal RAG pipeline for your data. It simplifies the process of evaluating various RAG modules to identify the best pipeline for your specific use-case. The tool supports easy evaluation of different module combinations, making it efficient to find the most suitable RAG pipeline for your needs. AutoRAG also offers a cloud beta version to assist users in running and optimizing the tool, along with building RAG evaluation datasets for a starting price of $9.99 per optimization.

Superlinked is a compute framework for information retrieval and feature engineering systems, focusing on converting complex data into vector embeddings for RAG, Search, RecSys, and Analytics stack integration. It enables custom model performance in machine learning with pre-trained model convenience. The tool allows users to build multimodal vectors, define weights at query time, and avoid postprocessing & rerank requirements. Users can explore the computational model through simple scripts and python notebooks, with a future release planned for production usage with built-in data infra and vector database integrations.

Cognee is an open-source framework designed for creating self-improving deterministic outputs for Large Language Models (LLMs) using graphs, LLMs, and vector retrieval. It provides a platform for AI engineers to enhance their models and generate more accurate results. Users can leverage Cognee to add new information, utilize LLMs for knowledge creation, and query the system for relevant knowledge. The tool supports various LLM providers and offers flexibility in adding different data types, such as text files or directories. Cognee aims to streamline the process of working with LLMs and improving AI models for better performance and efficiency.

Lingo is an interactive platform for language learning that provides a modern UI/UX experience. It offers features like courses, quests, and a shop for users to engage with. The tech stack includes React JS, Next JS, Typescript, Tailwind CSS, Vercel, and Postgresql. Users can contribute to the project by submitting changes via pull requests. The platform utilizes resources from CodeWithAntonio, Kenney Assets, Freesound, Elevenlabs AI, and Flagpack. Key dependencies include @clerk/nextjs, @neondatabase/serverless, @radix-ui/react-avatar, and more. Users can follow the project creator on GitHub and Twitter, as well as subscribe to their YouTube channel for updates. To learn more about Next.js, users can refer to the Next.js documentation and interactive tutorial.

MinePal is a Minecraft companion app with a React frontend, a local backend, and an AI agent. The frontend is built with React and Vite, the local backend APIs are in server.js, and the Minecraft agent logic is in src/agent/. Users can set up the frontend by installing dependencies and building it, refer to the backend repository for backend setup, and navigate to src/agent/ to access actions that the bot can take.

The Ollama Conversation integration adds a conversation agent powered by Ollama in Home Assistant. This agent can be used in automations to query information provided by Home Assistant about your house, including areas, devices, and their states. Users can install the integration via HACS and configure settings such as API timeout, model selection, context size, maximum tokens, and other parameters to fine-tune the responses generated by the AI language model. Contributions to the project are welcome, and discussions can be held on the Home Assistant Community platform.

rclip is a command-line photo search tool powered by the OpenAI's CLIP neural network. It allows users to search for images using text queries, similar image search, and combining multiple queries. The tool extracts features from photos to enable searching and indexing, with options for previewing results in supported terminals or custom viewers. Users can install rclip on Linux, macOS, and Windows using different installation methods. The repository follows the Conventional Commits standard and welcomes contributions from the community.

Honcho is a platform for creating personalized AI agents and LLM powered applications for end users. The repository is a monorepo containing the server/API for managing database interactions and storing application state, along with a Python SDK. It utilizes FastAPI for user context management and Poetry for dependency management. The API can be run using Docker or manually by setting environment variables. The client SDK can be installed using pip or Poetry. The project is open source and welcomes contributions, following a fork and PR workflow. Honcho is licensed under the AGPL-3.0 License.

OpenSumi is a framework designed to help users quickly build AI Native IDE products. It provides a set of tools and templates for creating Cloud IDEs, Desktop IDEs based on Electron, CodeBlitz web IDE Framework, Lite Web IDE on the Browser, and Mini-App liked IDE. The framework also offers documentation for users to refer to and a detailed guide on contributing to the project. OpenSumi encourages contributions from the community and provides a platform for users to report bugs, contribute code, or improve documentation. The project is licensed under the MIT license and contains third-party code under other open source licenses.

The Ultralytics YOLO iOS App GitHub repository offers an advanced object detection tool leveraging YOLOv8 models for iOS devices. Users can transform their devices into intelligent detection tools to explore the world in a new and exciting way. The app provides real-time detection capabilities with multiple AI models to choose from, ranging from 'nano' to 'x-large'. Contributors are welcome to participate in this open-source project, and licensing options include AGPL-3.0 for open-source use and an Enterprise License for commercial integration. Users can easily set up the app by following the provided steps, including cloning the repository, adding YOLOv8 models, and running the app on their iOS devices.

PyAirbyte brings the power of Airbyte to every Python developer by providing a set of utilities to use Airbyte connectors in Python. It enables users to easily manage secrets, work with various connectors like GitHub, Shopify, and Postgres, and contribute to the project. PyAirbyte is not a replacement for Airbyte but complements it, supporting data orchestration frameworks like Airflow and Snowpark. Users can develop ETL pipelines and import connectors from local directories. The tool simplifies data integration tasks for Python developers.

AMchat is a large language model that integrates advanced math concepts, exercises, and solutions. The model is based on the InternLM2-Math-7B model and is specifically designed to answer advanced math problems. It provides a comprehensive dataset that combines Math and advanced math exercises and solutions. Users can download the model from ModelScope or OpenXLab, deploy it locally or using Docker, and even retrain it using XTuner for fine-tuning. The tool also supports LMDeploy for quantization, OpenCompass for evaluation, and various other features for model deployment and evaluation. The project contributors have provided detailed documentation and guides for users to utilize the tool effectively.

Lingo is an interactive platform for language learning that provides a modern UI/UX experience. It offers features like courses, quests, and a shop for users to engage with. The tech stack includes React JS, Next JS, Typescript, Tailwind CSS, Vercel, and Postgresql. Users can contribute to the project by submitting changes via pull requests. The platform utilizes resources from CodeWithAntonio, Kenney Assets, Freesound, Elevenlabs AI, and Flagpack. Key dependencies include @clerk/nextjs, @neondatabase/serverless, @radix-ui/react-avatar, and more. Users can follow the project creator on GitHub and Twitter, as well as subscribe to their YouTube channel for updates. To learn more about Next.js, users can refer to the Next.js documentation and interactive tutorial.

Verbiverse is a tool that uses a large language model to assist in reading PDFs and watching videos, aimed at improving language proficiency. It provides a more convenient and efficient way to use large models through predefined prompts, designed for those looking to enhance their language skills. The tool analyzes unfamiliar words and sentences in foreign language PDFs or video subtitles, providing better contextual understanding compared to traditional dictionary translations or ambiguous meanings. It offers features such as automatic loading of subtitles, word analysis by clicking or double-clicking, and a word database for collecting words. Users can run the tool on Windows x86_64 or ubuntu_22.04 x86_64 platforms by downloading the precompiled packages or by cloning the source code and setting up a virtual environment with Python. It is recommended to use a local model or smaller PDF files for testing due to potential token consumption issues with large files.

AnnA is a Python script designed to create filtered decks in optimal review order for Anki flashcards. It uses Machine Learning / AI to ensure semantically linked cards are reviewed far apart. The script helps users manage their daily reviews by creating special filtered decks that prioritize reviewing cards that are most different from the rest. It also allows users to reduce the number of daily reviews while increasing retention and automatically identifies semantic neighbors for each note.

EngAce is a cutting-edge, generative AI-powered application revolutionizing Vietnamese English learning. It offers personalized learning experiences combining AI with comprehensive features. The repository contains source code, documentation, and resources for the app.

TheoremExplainAgent is an AI system that generates long-form Manim videos to visually explain theorems, proving its deep understanding while uncovering reasoning flaws that text alone often hides. The codebase for the paper 'TheoremExplainAgent: Towards Multimodal Explanations for LLM Theorem Understanding' is available in this repository. It provides a tool for creating multimodal explanations for theorem understanding using AI technology.

Vocabulary Book by DeepSeek is a manual for CET-4, postgraduate entrance examination, and TOEFL vocabulary, providing word meanings, roots, example sentences, mnemonic aids, and mnemonic images. The project uses Cline + DeepSeek-R1-16b for over 80% of the code to automatically encode the vocabulary manual. The generated manual includes vocabulary from A to Z for CET-4, CET-6, postgraduate entrance examination, and TOEFL, along with features to generate Anki cards and PDFs. The tool also allows for the creation of mnemonic images for each word and articles.

The 'awesome-ai-llm4education' repository is a curated list of papers related to artificial intelligence (AI) and large language models (LLM) for education. It collects papers from top conferences, journals, and specialized domain-specific conferences, categorizing them based on specific tasks for better organization. The repository covers a wide range of topics including tutoring, personalized learning, assessment, material preparation, specific scenarios like computer science, language, math, and medicine, aided teaching, as well as datasets and benchmarks for educational research.