kweaver

KWeaver is an open-source cognitive intelligence development framework that provides data scientists, application developers, and domain experts with the ability for rapid development, comprehensive openness, and high-performance knowledge network generation and cognitive intelligence large model framework. It offers features such as automated and visual knowledge graph construction, visualization and analysis of knowledge graph data, knowledge graph integration, knowledge graph resource management, large model prompt engineering and debugging, and visual configuration for large model access.

LYRAIOS (LLM-based Your Reliable AI Operating System) is an advanced AI assistant platform built with FastAPI and Streamlit, designed to serve as an operating system for AI applications. It offers core features such as AI process management, memory system, and I/O system. The platform includes built-in tools like Calculator, Web Search, Financial Analysis, File Management, and Research Tools. It also provides specialized assistant teams for Python and research tasks. LYRAIOS is built on a technical architecture comprising FastAPI backend, Streamlit frontend, Vector Database, PostgreSQL storage, and Docker support. It offers features like knowledge management, process control, and security & access control. The roadmap includes enhancements in core platform, AI process management, memory system, tools & integrations, security & access control, open protocol architecture, multi-agent collaboration, and cross-platform support.

ATLAS (Adaptive Task & Logic Automation System) is a high-performance Model Context Protocol server designed for LLMs to manage complex task hierarchies. Built with TypeScript, it features ACID-compliant storage, efficient task tracking, and intelligent template management. ATLAS provides LLM Agents task management through a clean, flexible tool interface. The server implements the Model Context Protocol (MCP) for standardized communication between LLMs and external systems, offering hierarchical task organization, task state management, smart templates, enterprise features, and performance optimization.

ComfyUI-fal-API is a repository containing custom nodes for using Flux models with fal API in ComfyUI. It provides nodes for image generation, video generation, language models, and vision language models. Users can easily install and configure the repository to access various nodes for different tasks such as generating images, creating videos, processing text, and understanding images. The repository also includes troubleshooting steps and is licensed under the Apache License 2.0.

TrustEval-toolkit is a dynamic and comprehensive framework for evaluating the trustworthiness of Generative Foundation Models (GenFMs) across dimensions such as safety, fairness, robustness, privacy, and more. It offers features like dynamic dataset generation, multi-model compatibility, customizable metrics, metadata-driven pipelines, comprehensive evaluation dimensions, optimized inference, and detailed reports.

BrowserAI is a tool that allows users to run large language models (LLMs) directly in the browser, providing a simple, fast, and open-source solution. It prioritizes privacy by processing data locally, is cost-effective with no server costs, works offline after initial download, and offers WebGPU acceleration for high performance. It is developer-friendly with a simple API, supports multiple engines, and comes with pre-configured models for easy use. Ideal for web developers, companies needing privacy-conscious AI solutions, researchers experimenting with browser-based AI, and hobbyists exploring AI without infrastructure overhead.

Agentica is a specialized Agentic AI library focused on LLM Function Calling. Users can provide Swagger/OpenAPI documents or TypeScript class types to Agentica for seamless functionality. The library simplifies AI development by handling various tasks effortlessly.

DeepSeekAI is a browser extension plugin that allows users to interact with AI by selecting text on web pages and invoking the DeepSeek large model to provide AI responses. The extension enhances browsing experience by enabling users to get summaries or answers for selected text directly on the webpage. It features context text selection, API key integration, draggable and resizable window, AI streaming replies, Markdown rendering, one-click copy, re-answer option, code copy functionality, language switching, and multi-turn dialogue support. Users can install the extension from Chrome Web Store or Edge Add-ons, or manually clone the repository, install dependencies, and build the extension. Configuration involves entering the DeepSeek API key in the extension popup window to start using the AI-driven responses.

AgentNeo is an advanced, open-source Agentic AI Application Observability, Monitoring, and Evaluation Framework designed to provide deep insights into AI agents, Large Language Model (LLM) calls, and tool interactions. It offers robust logging, visualization, and evaluation capabilities to help debug and optimize AI applications with ease. With features like tracing LLM calls, monitoring agents and tools, tracking interactions, detailed metrics collection, flexible data storage, simple instrumentation, interactive dashboard, project management, execution graph visualization, and evaluation tools, AgentNeo empowers users to build efficient, cost-effective, and high-quality AI-driven solutions.

BrowserAI is a production-ready tool that allows users to run AI models directly in the browser, offering simplicity, speed, privacy, and open-source capabilities. It provides WebGPU acceleration for fast inference, zero server costs, offline capability, and developer-friendly features. Perfect for web developers, companies seeking privacy-conscious AI solutions, researchers experimenting with browser-based AI, and hobbyists exploring AI without infrastructure overhead. The tool supports various AI tasks like text generation, speech recognition, and text-to-speech, with pre-configured popular models ready to use. It offers a simple SDK with multiple engine support and seamless switching between MLC and Transformers engines.

RookieAI_yolov8 is an open-source project designed for developers and users interested in utilizing YOLOv8 models for object detection tasks. The project provides instructions for setting up the required libraries and Pytorch, as well as guidance on using custom or official YOLOv8 models. Users can easily train their own models and integrate them with the software. The tool offers features for packaging the code, managing model files, and organizing the necessary resources for running the software. It also includes updates and optimizations for better performance and functionality, with a focus on FPS game aimbot functionalities. The project aims to provide a comprehensive solution for object detection tasks using YOLOv8 models.

The 'unilm' repository is a collection of tools, models, and architectures for Foundation Models and General AI, focusing on tasks such as NLP, MT, Speech, Document AI, and Multimodal AI. It includes various pre-trained models, such as UniLM, InfoXLM, DeltaLM, MiniLM, AdaLM, BEiT, LayoutLM, WavLM, VALL-E, and more, designed for tasks like language understanding, generation, translation, vision, speech, and multimodal processing. The repository also features toolkits like s2s-ft for sequence-to-sequence fine-tuning and Aggressive Decoding for efficient sequence-to-sequence decoding. Additionally, it offers applications like TrOCR for OCR, LayoutReader for reading order detection, and XLM-T for multilingual NMT.

A SpringBoot web application that generates PPT files using a llm. The tool preprocesses single-page templates and dynamically combines them to generate PPTX files with text replacement functionality. It utilizes technologies such as SpringBoot, MyBatis, MySQL, Redis, WebFlux, Apache POI, Aspose Slides, OSS, and Vue2. Users can deploy the tool by configuring various parameters in the application.yml file and setting up necessary resources like MySQL, OSS, and API keys. The tool also supports integration with open-source image libraries like Unsplash for adding images to the presentations.

Hacx GPT is a cutting-edge AI tool developed by BlackTechX, inspired by WormGPT, designed to push the boundaries of natural language processing. It is an advanced broken AI model that facilitates seamless and powerful interactions, allowing users to ask questions and perform various tasks. The tool has been rigorously tested on platforms like Kali Linux, Termux, and Ubuntu, offering powerful AI conversations and the ability to do anything the user wants. Users can easily install and run Hacx GPT on their preferred platform to explore its vast capabilities.

TabMark is a browser extension that transforms bookmarks into a new tab page, allowing you to easily access and organize your saved bookmarks. It features intelligent AI search for quick answers and supports Chrome and Edge browsers. With TabMark, you can set bookmarks as new tab pages, access rich bookmark context menus, use sidebar bookmarks, utilize floating ball functionality, perform AI intelligent searches, compare search results, customize new tab pages, and access browser shortcuts. The extension enhances browsing efficiency and organization.

Shards is a high-performance, multi-platform, type-safe programming language designed for visual development. It is a dataflow visual programming language that enables building full-fledged apps and games without traditional coding. Shards features automatic type checking, optimized shard implementations for high performance, and an intuitive visual workflow for beginners. The language allows seamless round-trip engineering between code and visual models, empowering users to create multi-platform apps easily. Shards also powers an upcoming AI-powered game creation system, enabling real-time collaboration and game development in a low to no-code environment.

KWeaver is an open-source cognitive intelligence development framework that provides data scientists, application developers, and domain experts with the ability for rapid development, comprehensive openness, and high-performance knowledge network generation and cognitive intelligence large model framework. It offers features such as automated and visual knowledge graph construction, visualization and analysis of knowledge graph data, knowledge graph integration, knowledge graph resource management, large model prompt engineering and debugging, and visual configuration for large model access.

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.

GraphRAG Local Ollama is a repository that offers an adaptation of Microsoft's GraphRAG, customized to support local models downloaded using Ollama. It enables users to leverage local models with Ollama for large language models (LLMs) and embeddings, eliminating the need for costly OpenAPI models. The repository provides a simple setup process and allows users to perform question answering over private text corpora by building a graph-based text index and generating community summaries for closely-related entities. GraphRAG Local Ollama aims to improve the comprehensiveness and diversity of generated answers for global sensemaking questions over datasets.

TrustGraph is a tool that deploys private GraphRAG pipelines to build a RDF style knowledge graph from data, enabling accurate and secure `RAG` requests compatible with cloud LLMs and open-source SLMs. It showcases the reliability and efficiencies of GraphRAG algorithms, capturing contextual language flags missed in conventional RAG approaches. The tool offers features like PDF decoding, text chunking, inference of various LMs, RDF-aligned Knowledge Graph extraction, and more. TrustGraph is designed to be modular, supporting multiple Language Models and environments, with a plug'n'play architecture for easy customization.

Weave is a toolkit for developing Generative AI applications, built by Weights & Biases. With Weave, you can log and debug language model inputs, outputs, and traces; build rigorous, apples-to-apples evaluations for language model use cases; and organize all the information generated across the LLM workflow, from experimentation to evaluations to production. Weave aims to bring rigor, best-practices, and composability to the inherently experimental process of developing Generative AI software, without introducing cognitive overhead.

LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

The VisionCraft API is a free API for using over 100 different AI models. From images to sound.

Kaito is an operator that automates the AI/ML inference model deployment in a Kubernetes cluster. It manages large model files using container images, avoids tuning deployment parameters to fit GPU hardware by providing preset configurations, auto-provisions GPU nodes based on model requirements, and hosts large model images in the public Microsoft Container Registry (MCR) if the license allows. Using Kaito, the workflow of onboarding large AI inference models in Kubernetes is largely simplified.

PyRIT is an open access automation framework designed to empower security professionals and ML engineers to red team foundation models and their applications. It automates AI Red Teaming tasks to allow operators to focus on more complicated and time-consuming tasks and can also identify security harms such as misuse (e.g., malware generation, jailbreaking), and privacy harms (e.g., identity theft). The goal is to allow researchers to have a baseline of how well their model and entire inference pipeline is doing against different harm categories and to be able to compare that baseline to future iterations of their model. This allows them to have empirical data on how well their model is doing today, and detect any degradation of performance based on future improvements.

Tabby is a self-hosted AI coding assistant, offering an open-source and on-premises alternative to GitHub Copilot. It boasts several key features: * Self-contained, with no need for a DBMS or cloud service. * OpenAPI interface, easy to integrate with existing infrastructure (e.g Cloud IDE). * Supports consumer-grade GPUs.

SPEAR (Simulator for Photorealistic Embodied AI Research) is a powerful tool for training embodied agents. It features 300 unique virtual indoor environments with 2,566 unique rooms and 17,234 unique objects that can be manipulated individually. Each environment is designed by a professional artist and features detailed geometry, photorealistic materials, and a unique floor plan and object layout. SPEAR is implemented as Unreal Engine assets and provides an OpenAI Gym interface for interacting with the environments via Python.

Magick is a groundbreaking visual AIDE (Artificial Intelligence Development Environment) for no-code data pipelines and multimodal agents. Magick can connect to other services and comes with nodes and templates well-suited for intelligent agents, chatbots, complex reasoning systems and realistic characters.