New AI tools - Open Source

Just-Chat is a containerized application that allows users to easily set up and chat with their AI agent. Users can customize their AI assistant using a YAML file, add new capabilities with Python tools, and interact with the agent through a chat web interface. The tool supports various modern models like DeepSeek Reasoner, ChatGPT, LLAMA3.3, etc. Users can also use semantic search capabilities with MeiliSearch to find and reference relevant information based on meaning. Just-Chat requires Docker or Podman for operation and provides detailed installation instructions for both Linux and Windows users.

RubyLLM is a delightful Ruby tool for working with AI, providing a beautiful API for various AI providers like OpenAI, Anthropic, Gemini, and DeepSeek. It simplifies AI usage by offering a consistent format, minimal dependencies, and a joyful coding experience. Users can chat, analyze images, audio, and documents, generate images, create vector embeddings, and integrate AI with Ruby code effortlessly. The tool also supports Rails integration, streaming responses, and tool creation, making AI tasks seamless and enjoyable.

LLaVA-MORE is a new family of Multimodal Language Models (MLLMs) that integrates recent language models with diverse visual backbones. The repository provides a unified training protocol for fair comparisons across all architectures and releases training code and scripts for distributed training. It aims to enhance Multimodal LLM performance and offers various models for different tasks. Users can explore different visual backbones like SigLIP and methods for managing image resolutions (S2) to improve the connection between images and language. The repository is a starting point for expanding the study of Multimodal LLMs and enhancing new features in the field.

Jimeng AI Free service provides powerful image generation capabilities with zero configuration deployment and support for multiple tokens. It is fully compatible with the OpenAI interface. The repository also includes other free APIs like Moonshot AI, StepChat, Qwen, GLM AI, Metaso AI, Doubao by ByteDance, Spark by Xunfei, Hailuo AI, DeepSeek, and Emohaa AI. Users can access the service by obtaining a sessionid from Jimeng and using it as a Bearer Token in the Authorization header for API requests. The service supports chat completions and image generations, with different models and parameters available for customization. Various deployment options are provided, including Docker, Docker-compose, Render, Vercel, and native deployment. Users are advised to use the recommended client applications for faster and simpler access to the free API services.

MarkPDFDown is a powerful tool that leverages multimodal large language models to transcribe PDF files into Markdown format. It simplifies the process of converting PDF documents into clean, editable Markdown text by accurately extracting text, preserving formatting, and handling complex document structures including tables, formulas, and diagrams.

This repository contains papers, methods, benchmarks, and evaluations for code generation under multimodal scenarios. It covers UI code generation, scientific code generation, slide code generation, visually rich programming, logo generation, program repair, UML code generation, and general benchmarks.

Perplexity-mcp is a Model Context Protocol (MCP) server that provides web search functionality using Perplexity AI's API. It works with the Anthropic Claude desktop client. The server allows users to search the web with specific queries and filter results by recency. It implements the perplexity_search_web tool, which takes a query as a required argument and can filter results by day, week, month, or year. Users need to set up environment variables, including the PERPLEXITY_API_KEY, to use the server. The tool can be installed via Smithery and requires UV for installation. It offers various models for different contexts and can be added as an MCP server in Cursor or Claude Desktop configurations.

Airo is a tool designed to simplify the process of deploying containers to self-hosted servers. It allows users to focus on building their products without the complexity of Kubernetes or CI/CD pipelines. With Airo, users can easily build and push Docker images, deploy instantly with a single command, update configurations securely using SSH, and set up HTTPS and reverse proxy automatically using Caddy.

FlowDown is a blazing fast and smooth client app for using AI/LLM. It is lightweight and efficient with markdown support, universal compatibility, blazing fast text rendering, automated chat titles, and privacy by design. There are two editions available: FlowDown and FlowDown Community, with various features like chat with AI, fast markdown, privacy by design, bring your own LLM, offline LLM w/ MLX, visual LLM, web search, attachments, and language localization. FlowDown Community is now open-source, empowering developers to build interactive and responsive AI client apps.

Authed is an identity and authentication system designed for AI agents, providing unique identities, secure agent-to-agent authentication, and dynamic access policies. It eliminates the need for static credentials and human intervention in authentication workflows. The protocol is developer-first, open-source, and scalable, enabling AI agents to interact securely across different ecosystems and organizations.

The ComfyUI Web Viewer by vrch.ai is a real-time AI-generated interactive art framework that integrates realtime streaming into ComfyUI workflows. It supports keyboard control nodes, OSC control nodes, sound input nodes, and more, accessible from any device with a web browser. It enables real-time interaction with AI-generated content, ideal for interactive visual projects and enhancing ComfyUI workflows with efficient content management and display.

AI Context is a CLI tool that generates AI-friendly markdown files from GitHub repos, local code, YouTube videos, or webpages. It supports processing local directories, GitHub repositories, YouTube transcripts, and webpages, converting them to markdown format. The tool simplifies interactions with LLMs like ChatGPT and Claude by providing a text-first context creation approach. It offers features for installation, usage, and acknowledgments, with options to process single paths, URLs, or lists of paths concurrently.

RAID is the largest and most comprehensive dataset for evaluating AI-generated text detectors. It contains over 10 million documents spanning 11 LLMs, 11 genres, 4 decoding strategies, and 12 adversarial attacks. RAID is designed to be the go-to location for trustworthy third-party evaluation of popular detectors. The dataset covers diverse models, domains, sampling strategies, and attacks, making it a valuable resource for training detectors, evaluating generalization, protecting against adversaries, and comparing to state-of-the-art models from academia and industry.

Neuron AI is a PHP framework that provides an Agent class for creating fully functional agents to perform tasks like analyzing text for SEO optimization. The framework manages advanced mechanisms such as memory, tools, and function calls. Users can extend the Agent class to create custom agents and interact with them to get responses based on the underlying LLM. Neuron AI aims to simplify the development of AI-powered applications by offering a structured framework with documentation and guidelines for contributions under the MIT license.

LangManus is a community-driven AI automation framework that combines language models with specialized tools for tasks like web search, crawling, and Python code execution. It implements a hierarchical multi-agent system with agents like Coordinator, Planner, Supervisor, Researcher, Coder, Browser, and Reporter. The framework supports LLM integration, search and retrieval tools, Python integration, workflow management, and visualization. LangManus aims to give back to the open-source community and welcomes contributions in various forms.

A web-based calculator to estimate hardware requirements for running Large Language Models (LLMs) in inference mode. This tool helps determine VRAM and system RAM needed for different LLM configurations. It calculates VRAM requirements based on model size, quantization method, context length, and KV cache settings. It provides estimates for required VRAM, minimum system RAM, on-disk model size, and number of GPUs needed. The project uses React, TypeScript, and Vite. Docker support is available with instructions provided. The tool provides approximations for calculations, includes overhead for KV cache, and assumes certain percentages for unified memory and discrete GPU calculations.

PasteMax is a modern file viewer application designed for developers to easily navigate, search, and copy code from repositories. It provides features such as file tree navigation, token counting, search capabilities, selection management, sorting options, dark mode, binary file detection, and smart file exclusion. Built with Electron, React, and TypeScript, PasteMax is ideal for pasting code into ChatGPT or other language models. Users can download the application or build it from source, and customize file exclusions. Troubleshooting steps are provided for common issues, and contributions to the project are welcome under the MIT License.

RAGEN is a reinforcement learning framework designed to train reasoning-capable large language model (LLM) agents in interactive, stochastic environments. It addresses challenges such as multi-turn interactions and stochastic environments through a Markov Decision Process (MDP) formulation, Reason-Interaction Chain Optimization (RICO) algorithm, and progressive reward normalization strategies. The framework consists of MDP formulation, RICO algorithm with rollout and update stages, and reward normalization strategies to stabilize training. RAGEN aims to optimize reasoning and action strategies for LLM agents operating in complex environments.

Ultimate Data Science Toolkit is a comprehensive repository covering Python basics to Generative AI. It includes modules on Python programming, data analysis, statistics, machine learning, MLOps, case studies, and deep learning. The repository provides detailed tutorials on various topics such as Python data structures, control statements, functions, modules, object-oriented programming, exception handling, file handling, web API, databases, list comprehension, lambda functions, Pandas, Numpy, data visualization, statistical analysis, supervised and unsupervised machine learning algorithms, model serialization, ML pipeline orchestration, case studies, and deep learning concepts like neural networks and autoencoders.

This project is an LLM-based Advanced Prompt Generator designed to automate the process of prompt engineering by enhancing given input prompts using large language models (LLMs). The tool can generate advanced prompts with minimal user input, leveraging LLM agents for optimized prompt generation. It supports gpt-4o or gpt-4o-mini, offers FastAPI & Docker deployment for efficiency, provides a Gradio interface for easy testing, and is hosted on Hugging Face Spaces for quick demos. Users can expand model support to offer more variety and flexibility.

TuyaOpen is an open source AI+IoT development framework supporting cross-chip platforms and operating systems. It provides core functionalities for AI+IoT development, including pairing, activation, control, and upgrading. The SDK offers robust security and compliance capabilities, meeting data compliance requirements globally. TuyaOpen enables the development of AI+IoT products that can leverage the Tuya APP ecosystem and cloud services. It continues to expand with more cloud platform integration features and capabilities like voice, video, and facial recognition.

AI-Toolbox is a C++ library aimed at representing and solving common AI problems, with a focus on MDPs, POMDPs, and related algorithms. It provides an easy-to-use interface that is extensible to many problems while maintaining readable code. The toolbox includes tutorials for beginners in reinforcement learning and offers Python bindings for seamless integration. It features utilities for combinatorics, polytopes, linear programming, sampling, distributions, statistics, belief updating, data structures, logging, seeding, and more. Additionally, it supports bandit/normal games, single agent MDP/stochastic games, single agent POMDP, and factored/joint multi-agent scenarios.

The ai-enhanced-audio-book repository contains AI-enhanced audio plugins developed using C++, JUCE, libtorch, RTNeural, and other libraries. It showcases neural networks learning to emulate guitar amplifiers through waveforms. Users can visit the official website for more information and obtain a copy of the book from the publisher Taylor and Francis/ Routledge/ Focal.

MemoAI is an AI-powered tool that provides podcast, video-to-text, and subtitling capabilities for immediate use. It supports audio and video transcription, model selection for paragraph effects, local subtitles translation, text translation using Google, Microsoft, Volcano Translation, DeepL, and AI Translation, speech synthesis in multiple languages, and exporting text and subtitles in common formats. MemoAI is designed to simplify the process of transcribing, translating, and creating subtitles for various media content.

ShitCodify is an AI-powered tool that transforms normal, readable, and maintainable code into hard-to-understand, hard-to-maintain 'shit code'. It uses large language models like GPT-4 to analyze code and apply various 'anti-patterns' and bad practices to reduce code readability and maintainability while keeping the code functional.

AI Chunking is a powerful Python library for semantic document chunking and enrichment using AI. It provides intelligent document chunking capabilities with various strategies to split text while preserving semantic meaning, particularly useful for processing markdown documentation. The library offers multiple chunking strategies such as Recursive Text Splitting, Section-based Semantic Chunking, and Base Chunking. Users can configure chunk sizes, overlap, and support various text formats. The tool is easy to extend with custom chunking strategies, making it versatile for different document processing needs.

AI Hub is a comprehensive solution that leverages artificial intelligence and cloud computing to provide functionalities such as document search and retrieval, call center analytics, image analysis, brand reputation analysis, form analysis, document comparison, and content safety moderation. It integrates various Azure services like Cognitive Search, ChatGPT, Azure Vision Services, and Azure Document Intelligence to offer scalable, extensible, and secure AI-powered capabilities for different use cases and scenarios.

agentUniverse is a multi-agent framework based on large language models, providing flexible capabilities for building individual agents. It focuses on collaborative pattern components to solve problems in various fields and integrates domain experience. The framework supports LLM model integration and offers various pattern components like PEER and DOE. Users can easily configure models and set up agents for tasks. agentUniverse aims to assist developers and enterprises in constructing domain-expert-level intelligent agents for seamless collaboration.

The GFM-RAG is a graph foundation model-powered pipeline that combines graph neural networks to reason over knowledge graphs and retrieve relevant documents for question answering. It features a knowledge graph index, efficiency in multi-hop reasoning, generalizability to unseen datasets, transferability for fine-tuning, compatibility with agent-based frameworks, and interpretability of reasoning paths. The tool can be used for conducting retrieval and question answering tasks using pre-trained models or fine-tuning on custom datasets.

Qiaoqiaoyun is a new generation zero-code product that combines an AI application development platform, AI knowledge base, and zero-code platform, helping enterprises quickly build personalized business applications in an AI way. Users can build personalized applications that meet business needs without any code. Qiaoqiaoyun has comprehensive application building capabilities, form engine, workflow engine, and dashboard engine, meeting enterprise's normal requirements. It is also an AI application development platform based on LLM large language model and RAG open-source knowledge base question-answering system.

LLM-Navigation is a repository dedicated to documenting learning records related to large models, including basic knowledge, prompt engineering, building effective agents, model expansion capabilities, security measures against prompt injection, and applications in various fields such as AI agent control, browser automation, financial analysis, 3D modeling, and tool navigation using MCP servers. The repository aims to organize and collect information for personal learning and self-improvement through AI exploration.

StarWhisper is a multi-modal model repository developed under the support of the National Astronomical Observatory-Zhijiang Laboratory. It includes language models, temporal models, and multi-modal models ranging from 7B to 72B. The repository provides pre-trained models and technical reports for tasks such as pulsar identification, light curve classification, and telescope control. It aims to integrate astronomical knowledge using large models and explore the possibilities of solving specific astronomical problems through multi-modal approaches.

This repository contains inference speed tests on Local Large Language Models on various devices. It provides results for different models tested on Macbook Pro and Mac Studio. Users can contribute their own results by running models with the provided prompt and adding the tokens-per-second output. Note that the results are not verified.

LM Studio Client SDK lmstudio-ts is LM Studio's official JavaScript/TypeScript client SDK. It allows you to use LLMs to respond in chats or predict text completions, define functions as tools, and turn LLMs into autonomous agents that run completely locally, load, configure, and unload models from memory, supports both browser and any Node-compatible environments, generate embeddings for text, and more! Why use `lmstudio-js` over `openai` sdk? Open AI's SDK is designed to use with Open AI's proprietary models. As such, it is missing many features that are essential for using LLMs in a local environment, such as managing loading and unloading models from memory, configuring load parameters (context length, gpu offload settings, etc.), speculative decoding, getting information (such as context length, model size, etc.) about a model, and more. In addition, while `openai` sdk is automatically generated, `lmstudio-js` is designed from ground-up to be clean and easy to use for TypeScript/JavaScript developers.

ComfyUI-IF_AI_LLM is a lighter version of ComfyUI-IF_AI_tools, providing custom nodes to run local and API LLMs and LMMs. It supports various models like Ollama, LlamaCPP, LMstudio, Koboldcpp, TextGen, Transformers, and APIs such as Anthropic, Groq, OpenAI, Google Gemini, Mistral, xAI. Users can create their own profiles (SystemPrompts) with custom presets. The tool offers features like xAI Grok Vision, Mistral, Google Gemini, Anthropic Haiku, OpenAI preview, auto prompts generation, image generation with IF_PROMPTImaGEN via Dalle3, and more. Installation involves searching for IF_LLM in the manager or manually installing ComfyUI-IF_AI_ImaGenPromptMaker by cloning the repository and installing requirements.

AgenticSeek is a voice-enabled AI assistant powered by DeepSeek R1 agents, offering a fully local alternative to cloud-based AI services. It allows users to interact with their filesystem, code in multiple languages, and perform various tasks autonomously. The tool is equipped with memory to remember user preferences and past conversations, and it can divide tasks among multiple agents for efficient execution. AgenticSeek prioritizes privacy by running entirely on the user's hardware without sending data to the cloud.

Aiven Client is the official command-line client for Aiven, a next-generation managed cloud services platform. It focuses on ease of adoption, high fault resilience, customer's peace of mind, and advanced features at competitive price points. The client allows users to interact with Aiven services through a command-line interface, providing functionalities such as authentication, project management, service exploration, service launching, service integrations, custom files management, team management, OAuth2 client configuration, autocomplete support, and auth helpers for connecting to services. Users can perform various tasks related to managing cloud services efficiently using the Aiven Client.

AI-PhD-S25 is a mono-repo for the DOTE 6635 course on AI for Business Research at CUHK Business School. The course aims to provide a fundamental understanding of ML/AI concepts and methods relevant to business research, explore applications of ML/AI in business research, and discover cutting-edge AI/ML technologies. The course resources include Google CoLab for code distribution, Jupyter Notebooks, Google Sheets for group tasks, Overleaf template for lecture notes, replication projects, and access to HPC Server compute resource. The course covers topics like AI/ML in business research, deep learning basics, attention mechanisms, transformer models, LLM pretraining, posttraining, causal inference fundamentals, and more.

Awesome-LLMOps is a curated list of the best LLMOps tools, providing a comprehensive collection of frameworks and tools for building, deploying, and managing large language models (LLMs) and AI agents. The repository includes a wide range of tools for tasks such as building multimodal AI agents, fine-tuning models, orchestrating applications, evaluating models, and serving models for inference. It covers various aspects of the machine learning operations (MLOps) lifecycle, from training to deployment and observability. The tools listed in this repository cater to the needs of developers, data scientists, and machine learning engineers working with large language models and AI applications.

A curated list of companies in the robotics and artificially intelligent agents industry, including large companies, stable start-ups, non-profits, and government research labs. The list covers companies working on autonomous vehicles, robotics, artificial intelligence, machine learning, computer vision, and more. It aims to showcase industry innovators and important players in the field of robotics and AI.

JabRef is an open-source, cross-platform citation and reference management tool that helps users collect, organize, cite, and share research sources. It offers features like searching across online scientific catalogues, importing references in various formats, extracting metadata from PDFs, customizable citation key generator, support for Word and LibreOffice/OpenOffice, and more. Users can organize their research items hierarchically, find and merge duplicates, attach related documents, and keep track of what they read. JabRef also supports sharing via various export options and syncs library contents in a team via a SQL database. It is actively developed, free of charge, and offers native BibTeX and Biblatex support.

Cua is a tool for creating and running high-performance macOS and Linux VMs on Apple Silicon, with built-in support for AI agents. It provides libraries like Lume for running VMs with near-native performance, Computer for interacting with sandboxes, and Agent for running agentic workflows. Users can refer to the documentation for onboarding and explore demos showcasing the tool's capabilities. Additionally, accessory libraries like Core, PyLume, Computer Server, and SOM offer additional functionality. Contributions to Cua are welcome, and the tool is open-sourced under the MIT License.

AIScript is a unique programming language and web framework written in Rust, designed to help developers effortlessly build AI applications. It combines the strengths of Python, JavaScript, and Rust to create an intuitive, powerful, and easy-to-use tool. The language features first-class functions, built-in AI primitives, dynamic typing with static type checking, data validation, error handling inspired by Rust, a rich standard library, and automatic garbage collection. The web framework offers an elegant route DSL, automatic parameter validation, OpenAPI schema generation, database modules, authentication capabilities, and more. AIScript excels in AI-powered APIs, prototyping, microservices, data validation, and building internal tools.

Scholar Copilot is an intelligent academic writing assistant that enhances the research writing process through AI-powered text completion and citation suggestions. It aims to streamline academic writing while maintaining high scholarly standards. The tool provides features such as smart text generation with next-3-sentence suggestions, full section auto-completion, and context-aware writing. It also offers intelligent citation management with real-time citation suggestions, one-click citation insertion, and citation Bibtex generation. Scholar Copilot employs a unified model architecture that integrates retrieval and generation through a dynamic switching mechanism, ensuring coherent text generation with appropriate citation points.

Single File Agents (SFA) is a collection of powerful single-file agents built on top of uv, a modern Python package installer and resolver. These agents aim to perform specific tasks efficiently, demonstrating precise prompt engineering and GenAI patterns. The repository contains agents built across major GenAI providers like Gemini, OpenAI, and Anthropic. Each agent is self-contained, minimal, and built on modern Python for fast and reliable dependency management. Users can run these scripts from their server or directly from a gist. The agents are patternful, emphasizing the importance of setting up effective prompts, tools, and processes for reusability.

The 'duckdb-airport-extension' is a tool that enables the use of Arrow Flight with DuckDB. It provides functions to list available Arrow Flights at a specific endpoint and to retrieve the contents of an Arrow Flight. The extension also supports creating secrets for authentication purposes. It includes features for serializing filters and optimizing projections to enhance data transmission efficiency. The tool is built on top of gRPC and the Arrow IPC format, offering high-performance data services for data processing and retrieval.

tambo ai is a React library that simplifies the process of building AI assistants and agents in React by handling thread management, state persistence, streaming responses, AI orchestration, and providing a compatible React UI library. It eliminates React boilerplate for AI features, allowing developers to focus on creating exceptional user experiences with clean React hooks that seamlessly integrate with their codebase.

FaceAiSharp is a .NET library designed for face-related computer vision tasks. It offers functionalities such as face detection, face recognition, facial landmarks detection, and eye state detection. The library utilizes pretrained ONNX models for accurate and efficient results, enabling users to integrate these capabilities into their .NET applications easily. With a focus on simplicity and performance, FaceAiSharp provides a local processing solution without relying on cloud services, supporting image-based face processing using ImageSharp. It is cross-platform compatible, supporting Windows, Linux, Android, and more.

Stable-Pi-Core is a next-generation decentralized ecosystem integrating blockchain, quantum AI, IoT, edge computing, and AR/VR for secure, scalable, and personalized solutions in payments, governance, and real-world applications. It features a Dual-Value System, cross-chain interoperability, AI-powered security, and a self-healing network. The platform empowers seamless payments, decentralized governance via DAO, and real-world applications across industries, bridging digital and physical worlds with innovative features like robotic process automation, machine learning personalization, and a dynamic cross-chain bridge framework.

This repository contains code for three papers related to evaluating large language models on planning and reasoning about change. It includes benchmarking tools and analysis for assessing the planning abilities of large language models. The latest addition evaluates and enhances the planning and scheduling capabilities of a specific language reasoning model. The repository provides a static test set leaderboard showcasing model performance on various tasks with natural language and planning domain prompts.

Grounded-VideoLLM is a Video Large Language Model specialized in fine-grained temporal grounding. It excels in tasks such as temporal sentence grounding, dense video captioning, and grounded VideoQA. The model incorporates an additional temporal stream, discrete temporal tokens with specific time knowledge, and a multi-stage training scheme. It shows potential as a versatile video assistant for general video understanding. The repository provides pretrained weights, inference scripts, and datasets for training. Users can run inference queries to get temporal information from videos and train the model from scratch.

LLM-Planner is a tool for few-shot grounded planning for embodied agents using large language models. It includes a high-level prompt generator and kNN dataset, allowing users to generate high-level plans for tasks by bringing their low-level controller and an LLM. The tool has been used in various research projects and provides implementation examples from different conferences. Users can cite the tool using the provided information and the tool is available under the MIT License. For questions or issues, users can contact Luke Song.

AgentSquare is an official implementation for the paper 'AgentSquare: Automatic LLM Agent Search in Modular Design Space'. It provides code, prompts, and results for automatic LLM agent search. The tool allows users to set up OpenAI API key, install dependencies, and run various tasks such as ALFworld, Webshop, M3Tooleval, and Sciworld. Users can also contribute new modules to the modular design challenge by standardizing LLM agents with recommended I/O interfaces. The tool aims to offer a platform for fully exploiting successful agent designs and consolidating efforts of the LLM agent research community.

GPT Author is a command-line tool designed to help users write long form, multi-chapter stories by providing a story prompt and generating a synopsis and subsequent chapters using ChatGPT. Users can review and make changes to the generated content before finalizing the story output in Markdown and HTML formats. The tool aims to unleash storytelling genius by combining human input with AI-generated content, offering a seamless writing experience for creating engaging narratives.

LLMOCR is a tool that utilizes a local Large Language Model (LLM) to extract text from images. It offers a user-friendly GUI and supports GPU acceleration for faster inference. The tool is cross-platform, compatible with Windows, macOS ARM, and Linux. Users can prompt the LLM to process images in a customized way. The processing is done locally on the user's machine, ensuring data privacy and security. LLMOCR requires Python 3.8 or higher and KoboldCPP for installation and operation.

CAD-Recode is a 3D CAD reverse engineering method implemented in Python using the CadQuery library. It transforms point clouds into 3D CAD models by leveraging a pre-trained model and additional linear layers. The repository includes an inference demo for users to generate CAD models from point clouds. CAD-Recode has achieved state-of-the-art performance in CAD reconstruction benchmarks such as DeepCAD, Fusion360, and CC3D. Researchers and engineers can utilize this tool to reverse engineer CAD code from point clouds efficiently.

Abliteration is a tool that allows users to create abliterated models using transformers quickly and easily. It is not a tool for uncensorship, but rather for making models that will not explicitly refuse users. Users can clone the repository, install dependencies, and make abliterations using the provided commands. The tool supports adjusting parameters for stubborn models and offers various options for customization. Abliteration can be used for creating modified models for specific tasks or topics.

LLM4EC is an interdisciplinary research repository focusing on the intersection of Large Language Models (LLM) and Evolutionary Computation (EC). It provides a comprehensive collection of papers and resources exploring various applications, enhancements, and synergies between LLM and EC. The repository covers topics such as LLM-assisted optimization, EA-based LLM architecture search, and applications in code generation, software engineering, neural architecture search, and other generative tasks. The goal is to facilitate research and development in leveraging LLM and EC for innovative solutions in diverse domains.

1Backend is a flexible and scalable platform designed for running AI models on private servers and handling high-concurrency workloads. It provides a ChatGPT-like interface for users and a network-accessible API for machines, serving as a general-purpose backend framework. The platform offers on-premise ChatGPT alternatives, a microservices-first web framework, out-of-the-box services like file uploads and user management, infrastructure simplification acting as a container orchestrator, reverse proxy, multi-database support with its own ORM, and AI integration with platforms like LlamaCpp and StableDiffusion.

PlayWord is a tool designed to supercharge web test automation experience with AI. It provides core features such as enabling browser operations and validations using natural language inputs, as well as monitoring interface to record and dry-run test steps. PlayWord supports multiple AI services including Anthropic, Google, and OpenAI, allowing users to select the appropriate provider based on their requirements. The tool also offers features like assertion handling, frame handling, custom variables, test recordings, and an Observer module to track user interactions on web pages. With PlayWord, users can interact with web pages using natural language commands, reducing the need to worry about element locators and providing AI-powered adaptation to UI changes.

The ArXiv MCP Server acts as a bridge between AI assistants and arXiv's research repository, enabling AI models to search for and access papers programmatically through the Message Control Protocol (MCP). It offers features like paper search, access, listing, local storage, and research prompts. Users can install it via Smithery or manually for Claude Desktop. The server provides tools for paper search, download, listing, and reading, along with specialized prompts for paper analysis. Configuration can be done through environment variables, and testing is supported with a test suite. The tool is released under the MIT License and is developed by the Pearl Labs Team.

Polis is an AI powered sentiment gathering platform that offers a more organic approach than surveys and requires less effort than focus groups. It provides a comprehensive wiki, main deployment at https://pol.is, discussions, issue tracking, and project board for users. Polis can be set up using Docker infrastructure and offers various commands for building and running containers. Users can test their instance, update the system, and deploy Polis for production. The tool also provides developer conveniences for code reloading, type checking, and database connections. Additionally, Polis supports end-to-end browser testing using Cypress and offers troubleshooting tips for common Docker and npm issues.

AI Server is a self-hosted private gateway that orchestrates AI requests through a single integration, allowing control over AI providers like LLM, Diffusion, and image transformation. It dynamically delegates requests across various providers, including LLM APIs, Media APIs, and Comfy UI with FFmpeg Agents. The tool also offers built-in UIs for tasks like chat, text-to-image, image-to-text, image upscaling, speech-to-text, and text-to-speech. Additionally, it provides admin UIs for managing AI and media providers, API key access, and monitoring background jobs and AI requests.

Well-Architected Infrastructure as Code (IaC) Analyzer is a project demonstrating how generative AI can evaluate infrastructure code for alignment with best practices. It features a modern web application allowing users to upload IaC documents, complete IaC projects, or architecture diagrams for assessment. The tool provides insights into infrastructure code alignment with AWS best practices, offers suggestions for improving cloud architecture designs, and can generate IaC templates from architecture diagrams. Users can analyze CloudFormation, Terraform, or AWS CDK templates, architecture diagrams in PNG or JPEG format, and complete IaC projects with supporting documents. Real-time analysis against Well-Architected best practices, integration with AWS Well-Architected Tool, and export of analysis results and recommendations are included.

ONE is a modern web and AI agent development toolkit that empowers developers to build AI-powered applications with high performance, beautiful UI, AI integration, responsive design, type safety, and great developer experience. It is perfect for building modern web applications, from simple landing pages to complex AI-powered platforms.

Describer is a tool that analyzes codebases using AI to generate architectural overviews, documentation, explanations, bug reports, and more. It scans all files in a directory and uses Google's Gemini AI to provide insights such as markdown architectural overviews, codebase summaries, code pattern analysis, codebase structure documentation, bug identification, and test idea generation. The tool respects .gitignore rules by default but allows users to include/exclude specific files or patterns for analysis.

AI-UBB is a project related to Artificial Intelligence discipline in the second year of the Faculty of Mathematics and Computer Science at Babes-Bolyai University in Cluj-Napoca. The project involves a team of students working on various aspects of AI under the guidance of their professors.

Next-generation AI translation tool that provides high-quality, precise translations for various common file formats with a single click. It is based on cutting-edge large language models, offering exceptional translation quality with minimal operation, supporting multiple document formats and languages. Features include multi-format compatibility, global language translation, one-click rapid translation, flexible translation engines, and LAN sharing for efficient collaborative work.

MarkFlowy is a lightweight and feature-rich Markdown editor with built-in AI capabilities. It supports one-click export of conversations, translation of articles, and obtaining article abstracts. Users can leverage large AI models like DeepSeek and Chatgpt as intelligent assistants. The editor provides high availability with multiple editing modes and custom themes. Available for Linux, macOS, and Windows, MarkFlowy aims to offer an efficient, beautiful, and data-safe Markdown editing experience for users.

This project aims to integrate mainstream open-source large models to achieve the coordination and cooperation between different types of large models, providing comprehensive and flexible AI content generation services.

LLM Chain is a PHP library for building LLM-based features and applications. It provides abstractions for Language Models and Embeddings Models from platforms like OpenAI, Azure, Google, Replicate, and others. The core feature is to interact with language models via messages, supporting different message types and content. LLM Chain also supports tool calling, document embedding, vector stores, similarity search, structured output, response streaming, image processing, audio processing, embeddings, parallel platform calls, and input/output processing. Contributions are welcome, and the repository contains fixture licenses for testing multi-modal features.

Xianyu AutoAgent is an AI customer service robot system specifically designed for the Xianyu platform, providing 24/7 automated customer service, supporting multi-expert collaborative decision-making, intelligent bargaining, and context-aware conversations. The system includes intelligent conversation engine with features like context awareness and expert routing, business function matrix with modules like core engine, bargaining system, technical support, and operation monitoring. It requires Python 3.8+ and NodeJS 18+ for installation and operation. Users can customize prompts for different experts and contribute to the project through issues or pull requests.

InfiniStore is an open-source high-performance KV store designed to support LLM Inference clusters. It provides high-performance and low-latency KV cache transfer and reuse among inference nodes. In addition to inference clusters, it can be used as a standalone KV store for integration with LLM training or inference services. InfiniStore is currently integrated with vLLM via LMCache and is in progress for integration with SGLang and other inference engines.

llm-resources is a repository providing resources to get started with Large Language Models (LLMs). It includes videos on Neural Networks and LLMs, free courses, prompt engineering guides, explored frameworks, AI assistants, and tips on making RAG work properly. The repository also contains important links and updates related to LLMs, AWS, RAG, agents, model context protocol, and more. It aims to help individuals with a basic understanding of NLP and programming knowledge to explore and utilize LLMs effectively.

ExLlamaV2 is an inference library designed for running local LLMs on modern consumer GPUs. The library supports paged attention via Flash Attention 2.5.7+, offers a new dynamic generator with features like dynamic batching, smart prompt caching, and K/V cache deduplication. It also provides an API for local or remote inference using TabbyAPI, with extended features like HF model downloading and support for HF Jinja2 chat templates. ExLlamaV2 aims to optimize performance and speed across different GPU models, with potential future optimizations and variations in speeds. The tool can be integrated with TabbyAPI for OpenAI-style web API compatibility and supports a standalone web UI called ExUI for single-user interaction with chat and notebook modes. ExLlamaV2 also offers support for text-generation-webui and lollms-webui through specific loaders and bindings.

OneKE is a flexible dockerized system for schema-guided knowledge extraction, capable of extracting information from the web and raw PDF books across multiple domains like science and news. It employs a collaborative multi-agent approach and includes a user-customizable knowledge base to enable tailored extraction. OneKE offers various IE tasks support, data sources support, LLMs support, extraction method support, and knowledge base configuration. Users can start with examples using YAML, Python, or Web UI, and perform tasks like Named Entity Recognition, Relation Extraction, Event Extraction, Triple Extraction, and Open Domain IE. The tool supports different source formats like Plain Text, HTML, PDF, Word, TXT, and JSON files. Users can choose from various extraction models like OpenAI, DeepSeek, LLaMA, Qwen, ChatGLM, MiniCPM, and OneKE for information extraction tasks. Extraction methods include Schema Agent, Extraction Agent, and Reflection Agent. The tool also provides support for schema repository and case repository management, along with solutions for network issues. Contributors to the project include Ningyu Zhang, Haofen Wang, Yujie Luo, Xiangyuan Ru, Kangwei Liu, Lin Yuan, Mengshu Sun, Lei Liang, Zhiqiang Zhang, Jun Zhou, Lanning Wei, Da Zheng, and Huajun Chen.

Data Prep Kit accelerates unstructured data preparation for LLM app developers. It allows developers to cleanse, transform, and enrich unstructured data for pre-training, fine-tuning, instruct-tuning LLMs, or building RAG applications. The kit provides modules for Python, Ray, and Spark runtimes, supporting Natural Language and Code data modalities. It offers a framework for custom transforms and uses Kubeflow Pipelines for workflow automation. Users can install the kit via PyPi and access a variety of transforms for data processing pipelines.

TopicGPT is a repository containing scripts and prompts for the paper 'TopicGPT: Topic Modeling by Prompting Large Language Models' (NAACL'24). The 'topicgpt_python' package offers functions to generate high-level and specific topics, refine topics, assign topics to input text, and correct generated topics. It supports various APIs like OpenAI, VertexAI, Azure, Gemini, and vLLM for inference. Users can prepare data in JSONL format, run the pipeline using provided scripts, and evaluate topic alignment with ground-truth labels.

OpenManus-RL is an open-source initiative focused on enhancing reasoning and decision-making capabilities of large language models (LLMs) through advanced reinforcement learning (RL)-based agent tuning. The project explores novel algorithmic structures, diverse reasoning paradigms, sophisticated reward strategies, and extensive benchmark environments. It aims to push the boundaries of agent reasoning and tool integration by integrating insights from leading RL tuning frameworks and continuously updating progress in a dynamic, live-streaming fashion.

LLMII is a tool that uses a local AI model to label metadata and index images without relying on cloud services or remote APIs. It runs a visual language model on your computer to generate captions and keywords for images, enhancing their metadata for indexing, searching, and organization. The tool can be run multiple times on the same image files, allowing for adding new data, regenerating data, and discovering files with issues. It supports various image formats, offers a user-friendly GUI, and can utilize GPU acceleration for faster processing. LLMII requires Python 3.8 or higher and operates directly on image file metadata fields like MWG:Keyword and XMP:Identifier.

StockTrading AI is a small model stock automatic trading system that integrates with securities platforms, implements automated stock trading, utilizes QuartZ for scheduled tasks to update data daily, employs DL4J framework for LSTM model guidance on stock buying with T+1 short-term trading strategy, utilizes K8S+GithubAction for DevOps, and supports distributed offline training. Future optimizations include obtaining more historical stock data for incremental model training and tuning model hyperparameters to improve price trend prediction accuracy. The system provides various page displays for profit data statistics, trade order queries, stock price viewing, model prediction performance, scheduled task scheduling, and real-time log tracking.

NeoPass is a free Chrome extension designed for students taking tests on exam portals like Iamneo and Wildlife Ecology NPTEL. It provides features such as NPTEL integration, NeoExamShield bypass, AI chatbot with stealth mode, AI search answers/code, MCQ solving, tab switching bypass, pasting when restricted, and remote logout. Users can install the extension by following simple steps and use shortcuts for quick access to features. The tool is intended for educational purposes only and promotes academic integrity.

Learn-AI-Assisted-Python-Programming is a book that introduces readers to the world of AI-assisted programming, focusing on using tools like GitHub Copilot and ChatGPT to create and optimize Python programs. The book guides users, even those with no prior coding experience, on how to leverage AI assistants to quickly turn their ideas into reality without getting bogged down in low-level programming details. Readers will learn to generate code using natural language prompts, fine-tune code manually or with AI assistance, test programs with AI, and automate tedious tasks. The book aims to accelerate the learning journey of Copilot programming and provide a user-friendly and thoughtful approach for beginners.

Nosia is a platform that allows users to run an AI model on their own data. It is designed to be easy to install and use. Users can follow the provided guides for quickstart, API usage, upgrading, starting, stopping, and troubleshooting. The platform supports custom installations with options for remote Ollama instances, custom completion models, and custom embeddings models. Advanced installation instructions are also available for macOS with a Debian or Ubuntu VM setup. Users can access the platform at 'https://nosia.localhost' and troubleshoot any issues by checking logs and job statuses.

Aioshelly is an asynchronous library designed to control Shelly devices. It is currently under development and requires Python version 3.11 or higher, along with dependencies like bluetooth-data-tools, aiohttp, and orjson. The library provides examples for interacting with Gen1 devices using CoAP protocol and Gen2/Gen3 devices using RPC and WebSocket protocols. Users can easily connect to Shelly devices, retrieve status information, and perform various actions through the provided APIs. The repository also includes example scripts for quick testing and usage guidelines for contributors to maintain consistency with the Shelly API.

MCPSharp is a .NET library that helps build Model Context Protocol (MCP) servers and clients for AI assistants and models. It allows creating MCP-compliant tools, connecting to existing MCP servers, exposing .NET methods as MCP endpoints, and handling MCP protocol details seamlessly. With features like attribute-based API, JSON-RPC support, parameter validation, and type conversion, MCPSharp simplifies the development of AI capabilities in applications through standardized interfaces.

media-stack is a self-hosted media ecosystem that combines media management, streaming, AI-powered recommendations, and VPN. It includes tools like Radarr for movie management, Sonarr for TV show management, Prowlarr for torrent indexing, qBittorrent for downloading media, Jellyseerr for media requests, Jellyfin for media streaming, and Recommendarr for AI-powered recommendations. The stack can be deployed with or without a VPN and offers detailed configuration steps for each tool.

RKLLama is a server and client tool designed for running and interacting with LLM models optimized for Rockchip RK3588(S) and RK3576 platforms. It allows models to run on the NPU, with features such as running models on NPU, partial Ollama API compatibility, pulling models from Huggingface, API REST with documentation, dynamic loading/unloading of models, inference requests with streaming modes, simplified model naming, CPU model auto-detection, and optional debug mode. The tool supports Python 3.8 to 3.12 and has been tested on Orange Pi 5 Pro and Orange Pi 5 Plus with specific OS versions.

NeuroSync Player is a real-time AI endpoint server that combines text-to-speech and NeuroSync generations. It includes code for various AI endpoints such as speech-to-text, text-to-speech, embedding, and vision. The tool allows users to connect their llm to Twitch and YouTube, enabling the llm-powered metahuman to respond to viewers in real-time. Additionally, it offers features like push-to-talk, face animation integration, and support for blendshapes generated from audio inputs for Unreal Engine 5. Users can train and fine-tune their own models using NeuroSync Trainer Lite, with simplified loss functions and mixed precision for faster training. The tool also supports data augmentation to help with fine detail reproduction.

WhiskeyAI is a Next.js project that serves as a starting point for developing web applications. It includes a development server for live previewing changes and utilizes next/font for optimizing and loading the Geist font family. The project encourages contributions and feedback from users, providing resources for learning Next.js and deploying applications on the Vercel platform.

PilottAI is a Python framework for building autonomous multi-agent systems with advanced orchestration capabilities. It provides enterprise-ready features for building scalable AI applications. The framework includes hierarchical agent systems, production-ready features like asynchronous processing and fault tolerance, advanced memory management with semantic storage, and integrations with multiple LLM providers and custom tools. PilottAI offers specialized agents for various tasks such as customer service, document processing, email handling, knowledge acquisition, marketing, research analysis, sales, social media, and web search. The framework also provides documentation, example use cases, and advanced features like memory management, load balancing, and fault tolerance.

Shandu is an advanced AI research system that automates comprehensive research processes using language models, web scraping, and iterative exploration to generate well-structured reports with citations. It features intelligent state-based workflow, deep exploration, multi-source information synthesis, enhanced web scraping, smart source evaluation, content analysis pipeline, comprehensive report generation, parallel processing, adaptive search strategy, and full citation management.

ChemicalQDevice innovates new LLM/LLM agent pharmaceutical industry applications regarding cancer drug cost containment, clinical decision support, cancer signaling pathways, bioprocess engineering, biosynthesis, characterization, or drug synthesis. OpenAI, Anthropic, Gemini, or xAI direct chat proprietary software are utilized to generate LLM reports and propose detailed solutions. AI governance is employed with relevant software implementations, model bias amplification mitigation, and generation traceability analyses.

MLX LM is a Python package designed for generating text and fine-tuning large language models on Apple silicon using MLX. It offers integration with the Hugging Face Hub for easy access to thousands of LLMs, support for quantizing and uploading models to the Hub, low-rank and full model fine-tuning capabilities, and distributed inference and fine-tuning with `mx.distributed`. Users can interact with the package through command line options or the Python API, enabling tasks such as text generation, chatting with language models, model conversion, streaming generation, and sampling. MLX LM supports various Hugging Face models and provides tools for efficient scaling to long prompts and generations, including a rotating key-value cache and prompt caching. It requires macOS 15.0 or higher for optimal performance.

Manifold is a powerful platform for workflow automation using AI models. It supports text generation, image generation, and retrieval-augmented generation, integrating seamlessly with popular AI endpoints. Additionally, Manifold provides robust semantic search capabilities using PGVector combined with the SEFII engine. It is under active development and not production-ready.

The oba live tool is a small tool for Douyin small shops and Kuaishou Baiying live broadcasts. It features multiple account management, intelligent message assistant, automatic product explanation, AI automatic reply, and AI intelligent assistant. The tool requires Windows 10 or above, Chrome or Edge browser, and a valid account for Douyin small shops or Kuaishou Baiying. Users can download the tool from the Releases page, connect to the control panel, set API keys for AI functions, and configure auto-reply prompts. The tool is licensed under the MIT license.

WenXin-Starter is a spring-boot-starter for Baidu's 'WenXin Workshop' large model, facilitating quick integration of Baidu's AI capabilities. It provides complete integration with WenXin Workshop's official API documentation, supports WenShengTu, built-in conversation memory, and supports conversation streaming. It also supports QPS control for individual models and queuing mechanism, with upcoming plugin support.

This repository provides Terraform configurations to automatically set up Google Cloud resources and deploy Dify in a highly available configuration. It includes features such as serverless hosting, auto-scaling, and data persistence. Users need a Google Cloud account, Terraform, and gcloud CLI installed to use this tool. The configuration involves setting environment-specific values and creating a GCS bucket for managing Terraform state. The tool allows users to initialize Terraform, create Artifact Registry repository, build and push container images, plan and apply Terraform changes, and cleanup resources when needed.

Open Autonomy is a framework for creating agent services that run as a multi-agent-system and offer enhanced functionalities on-chain. It enables executing complex operations like machine-learning algorithms in a decentralized, trust-minimized, transparent, and robust manner.

anki_packager is an intelligent tool for generating high-quality Anki flashcards for English vocabulary. It integrates multiple curated dictionaries, provides automated learning experiences, supports various features like Google TTS pronunciation and AI models for word summarization and story generation, offers convenient data import from other sources, ensures a good command-line interface, and can be run using Docker. Each flashcard includes detailed learning resources such as definitions, tenses, AI-generated roots for mnemonic aids, phrases, example sentences, word differentiations, and English explanations with AI-generated stories.