Remix Antd Admin is a full-stack management system built on Remix and Antd/TailwindCSS, featuring RBAC permission management and remix-i18n integration. It aims to provide a modern, simple, fast, and scalable full-stack website. The project is currently in development, transitioning from UI to full-stack, with a focus on stable architecture. The frontend utilizes remix data flow with server-side rendering, while the backend API uses redux-toolkit/query, prisma, rxjs, zod, and remix action/loader for server API services. The project includes authorization management with jose jwt for external API services beyond web applications. Key libraries used are Remix, express, Prisma, and pgsql.

The MiniAiLive Face Recognition LivenessDetection Server SDK provides system integrators with fast, flexible, and extremely precise facial recognition that can be deployed across various scenarios, including security, access control, public safety, fintech, smart retail, and home protection. The SDK is fully on-premise, meaning all processing happens on the hosting server, and no data leaves the server. The project structure includes bin, cpp, flask, model, python, test_image, and Dockerfile directories. To set up the project on Linux, download the repo, install system dependencies, and copy libraries into the system folder. For Windows, contact MiniAiLive via email. The C++ example involves replacing the license key in main.cpp, building the project, and running it. The Python example requires installing dependencies and running the project. The Python Flask example involves replacing the license key in app.py, installing dependencies, and running the project. The Docker Flask example includes building the docker image and running it. To request a license, contact MiniAiLive. Contributions to the project are welcome by following specific steps. An online demo is available at https://demo.miniai.live. Related products include MiniAI-Face-Recognition-LivenessDetection-AndroidSDK, MiniAI-Face-Recognition-LivenessDetection-iOS-SDK, MiniAI-Face-LivenessDetection-AndroidSDK, MiniAI-Face-LivenessDetection-iOS-SDK, MiniAI-Face-Matching-AndroidSDK, and MiniAI-Face-Matching-iOS-SDK. MiniAiLive is a leading AI solutions company specializing in computer vision and machine learning technologies.

OpenManus is an open-source project aiming to replicate the capabilities of the Manus AI agent, known for autonomously executing complex tasks like travel planning and stock analysis. The project provides a modular, containerized framework using Docker, Python, and JavaScript, allowing developers to build, deploy, and experiment with a multi-agent AI system. Features include collaborative AI agents, Dockerized environment, task execution support, tool integration, modular design, and community-driven development. Users can interact with OpenManus via CLI, API, or web UI, and the project welcomes contributions to enhance its capabilities.

JetStream is a throughput and memory optimized engine for LLM inference on XLA devices, starting with TPUs (and GPUs in future -- PRs welcome). It is designed to provide high performance and scalability for large language models, enabling efficient inference on cloud-based TPUs. JetStream leverages XLA to optimize the execution of LLM models, resulting in faster and more efficient inference. Additionally, JetStream supports quantization techniques to further enhance performance and reduce memory consumption. By utilizing JetStream, developers can deploy and run LLM models on TPUs with ease, achieving optimal performance and cost-effectiveness.

JetStream is a throughput and memory optimized engine for Large Language Model (LLM) inference on XLA devices, specifically TPUs. It provides reference engine implementations for Jax and Pytorch models, along with documentation for online inference, serving Gemma using TPUs on GKE, benchmarking, observability, profiling, and standalone local setup. Users can easily set up a local server, run tests, and test core modules. JetStream aims to enhance the performance of LLM inference on XLA devices.

MLX-VLM is a package designed for running Vision LLMs on Mac systems using MLX. It provides a convenient way to install and utilize the package for processing large language models related to vision tasks. The tool simplifies the process of running LLMs on Mac computers, offering a seamless experience for users interested in leveraging MLX for vision-related projects.

This repository is a modification based on the pixi-live2d-display project. It provides a platform for TTS (Text-to-Speech) functionality and a large model voice chat page. Users can install node.js, run the provided commands, and access the specified URLs to utilize the features.

LLM-FuzzX is an open-source user-friendly fuzz testing tool for large language models (e.g., GPT, Claude, LLaMA), equipped with advanced task-aware mutation strategies, fine-grained evaluation, and jailbreak detection capabilities. It helps researchers and developers quickly discover potential security vulnerabilities and enhance model robustness. The tool features a user-friendly web interface for visual configuration and real-time monitoring, supports various advanced mutation methods, integrates RoBERTa model for real-time jailbreak detection and evaluation, supports multiple language models like GPT, Claude, LLaMA, provides visualization analysis with seed flowcharts and experiment data statistics, and offers detailed logging support for main, mutation, and jailbreak logs.

Bavarder is an AI-powered chit-chat tool designed for informal conversations about unimportant matters. Users can engage in light-hearted discussions with the AI, simulating casual chit-chat scenarios. The tool provides a platform for users to interact with AI in a fun and entertaining way, offering a unique experience of engaging with artificial intelligence in a conversational manner.

This repository contains an MLIR-based toolchain for AI Engine-enabled devices, such as AMD Ryzen™ AI and Versal™. This repository can be used to generate low-level configurations for the AI Engine portion of these devices. AI Engines are organized as a spatial array of tiles, where each tile contains AI Engine cores and/or memories. The spatial array is connected by stream switches that can be configured to route data between AI Engine tiles scheduled by their programmable Data Movement Accelerators (DMAs). This repository contains MLIR representations, with multiple levels of abstraction, to target AI Engine devices. This enables compilers and developers to program AI Engine cores, as well as describe data movements and array connectivity. A Python API is made available as a convenient interface for generating MLIR design descriptions. Backend code generation is also included, targeting the aie-rt library. This toolchain uses the AI Engine compiler tool which is part of the AMD Vitis™ software installation: these tools require a free license for use from the Product Licensing Site.

Spatz is a complete, fullstack template for Svelte that includes features such as Sveltekit for building fast web apps, Pocketbase for User Auth and Database, OpenAI for chatbots, Vercel AI SDK for AI/ML models, TailwindCSS for UI development, DaisyUI for components, and Zod for schema declaration and validation. The template provides a structured project setup with components, stores, routes, and APIs. It also offers theming and styling options with pre-loaded themes from DaisyUI. Contributions are welcomed through feature requests or pull requests.

A powerful starting kit for building AI-powered video applications. This toolkit simplifies the complexities of working with AI video models in the browser. It offers browser-native video processing, AI model integration, advanced media capabilities, and developer utilities. The tech stack includes fal.ai for AI model infrastructure, Next.js for React framework, Remotion for video processing, IndexedDB for browser-based storage, Vercel for deployment platform, and UploadThing for file upload. The kit provides features like seamless video handling, multi-clip composition, audio track integration, voiceover support, metadata encoding, and ready-to-use UI components.

This Code Interpreter SDK allows you to run AI-generated Python code and each run share the context. That means that subsequent runs can reference to variables, definitions, etc from past code execution runs. The code interpreter runs inside the E2B Sandbox - an open-source secure micro VM made for running untrusted AI-generated code and AI agents. - ✅ Works with any LLM and AI framework - ✅ Supports streaming content like charts and stdout, stderr - ✅ Python & JS SDK - ✅ Runs on serverless and edge functions - ✅ 100% open source (including infrastructure)

The enhance_llm repository contains three main parts: 1. Vector model domain fine-tuning based on llama_index and qwen fine-tuning BGE vector model. 2. Large model domain fine-tuning based on PEFT fine-tuning qwen1.5-7b-chat, with sft and dpo. 3. High-order retrieval enhanced generation (RAG) system based on the above domain work, implementing a two-stage RAG system. It includes query rewriting, recall reordering, retrieval reordering, multi-turn dialogue, and more. The repository also provides hardware and environment configurations along with star history and licensing information.

Flock is a workflow-based low-code platform that enables rapid development of chatbots, RAG applications, and coordination of multi-agent teams. It offers a flexible, low-code solution for orchestrating collaborative agents, supporting various node types for specific tasks, such as input processing, text generation, knowledge retrieval, tool execution, intent recognition, answer generation, and more. Flock integrates LangChain and LangGraph to provide offline operation capabilities and supports future nodes like Conditional Branch, File Upload, and Parameter Extraction for creating complex workflows. Inspired by StreetLamb, Lobe-chat, Dify, and fastgpt projects, Flock introduces new features and directions while leveraging open-source models and multi-tenancy support.

Smile (Statistical Machine Intelligence and Learning Engine) is a comprehensive machine learning, NLP, linear algebra, graph, interpolation, and visualization system in Java and Scala. It covers every aspect of machine learning, including classification, regression, clustering, association rule mining, feature selection, manifold learning, multidimensional scaling, genetic algorithms, missing value imputation, efficient nearest neighbor search, etc. Smile implements major machine learning algorithms and provides interactive shells for Java, Scala, and Kotlin. It supports model serialization, data visualization using SmilePlot and declarative approach, and offers a gallery showcasing various algorithms and visualizations.

Remix Antd Admin is a full-stack management system built on Remix and Antd/TailwindCSS, featuring RBAC permission management and remix-i18n integration. It aims to provide a modern, simple, fast, and scalable full-stack website. The project is currently in development, transitioning from UI to full-stack, with a focus on stable architecture. The frontend utilizes remix data flow with server-side rendering, while the backend API uses redux-toolkit/query, prisma, rxjs, zod, and remix action/loader for server API services. The project includes authorization management with jose jwt for external API services beyond web applications. Key libraries used are Remix, express, Prisma, and pgsql.

Synmetrix (prev. MLCraft) is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube (Cube.js) for flexible data models that consolidate metrics from various sources, enabling downstream distribution via a SQL API for integration into BI tools, reporting, dashboards, and data science. Use cases include data democratization, business intelligence, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

Synmetrix is an open source data engineering platform and semantic layer for centralized metrics management. It provides a complete framework for modeling, integrating, transforming, aggregating, and distributing metrics data at scale. Key features include data modeling and transformations, semantic layer for unified data model, scheduled reports and alerts, versioning, role-based access control, data exploration, caching, and collaboration on metrics modeling. Synmetrix leverages Cube.js to consolidate metrics from various sources and distribute them downstream via a SQL API. Use cases include data democratization, business intelligence and reporting, embedded analytics, and enhancing accuracy in data handling and queries. The tool speeds up data-driven workflows from metrics definition to consumption by combining data engineering best practices with self-service analytics capabilities.

Gin-vue-admin is a full-stack development platform based on Vue and Gin, integrating features like JWT authentication, dynamic routing, dynamic menus, Casbin authorization, form generator, code generator, etc. It provides various example files to help users focus more on business development. The project offers detailed documentation, video tutorials for setup and deployment, and a community for support and contributions. Users need a certain level of knowledge in Golang and Vue to work with this project. It is recommended to follow the Apache2.0 license if using the project for commercial purposes.

Cool-admin-java is an open-source backend permission management system with features like Ai coding, flow arrangement, modularity, and plugin support. It is used to quickly build backend applications. The system offers a modern development experience by providing functionalities such as one-click generation of API interfaces to frontend pages, drag-and-drop flow arrangement, modularized code for easy maintenance, and extensibility through plugin installation for features like payments, SMS, and emails.

Iceburg CRM is a metadata driven CRM with AI abilities that allows users to quickly prototype any CRM. It offers features like metadata creations, import/export in multiple formats, field validation, themes, role permissions, calendar, audit logs, API, workflow, field level relationships, module level relationships, and more. Created with Vue 3 for the frontend, Laravel 10 for the backend, Tailwinds with DaisyUI plugin, and Inertia for routing. Users can install default, admin panel, core, custom, or AI versions. The tool supports AI Assist for module data suggestions and provides API endpoints for CRM modules, search, specific module data, record updates, and deletions. Iceburg CRM also includes themes, custom field types, calendar, datalets, workflow, roles and permissions, import/export functionality, and custom seeding options.

Sdcb Chats is a powerful and flexible frontend for large language models, supporting multiple functions and platforms. Whether you want to manage multiple model interfaces or need a simple deployment process, Sdcb Chats can meet your needs. It supports dynamic management of multiple large language model interfaces, integrates visual models to enhance user interaction experience, provides fine-grained user permission settings for security, real-time tracking and management of user account balances, easy addition, deletion, and configuration of models, transparently forwards user chat requests based on the OpenAI protocol, supports multiple databases including SQLite, SQL Server, and PostgreSQL, compatible with various file services such as local files, AWS S3, Minio, Aliyun OSS, Azure Blob Storage, and supports multiple login methods including Keycloak SSO and phone SMS verification.

Slurm-web is an open source web dashboard designed for Slurm based HPC clusters. It provides a graphical user interface to track jobs, insights, and visualizations for monitoring HPC supercomputers. The tool offers features like interactive charts, job filtering, live status updates, node visualization, RBAC permissions, LDAP authentication, and integration with Prometheus for metrics collection.

Resonance is a framework designed to facilitate interoperability and messaging between services in your infrastructure and beyond. It provides AI capabilities and takes full advantage of asynchronous PHP, built on top of Swoole. With Resonance, you can: * Chat with Open-Source LLMs: Create prompt controllers to directly answer user's prompts. LLM takes care of determining user's intention, so you can focus on taking appropriate action. * Asynchronous Where it Matters: Respond asynchronously to incoming RPC or WebSocket messages (or both combined) with little overhead. You can set up all the asynchronous features using attributes. No elaborate configuration is needed. * Simple Things Remain Simple: Writing HTTP controllers is similar to how it's done in the synchronous code. Controllers have new exciting features that take advantage of the asynchronous environment. * Consistency is Key: You can keep the same approach to writing software no matter the size of your project. There are no growing central configuration files or service dependencies registries. Every relation between code modules is local to those modules. * Promises in PHP: Resonance provides a partial implementation of Promise/A+ spec to handle various asynchronous tasks. * GraphQL Out of the Box: You can build elaborate GraphQL schemas by using just the PHP attributes. Resonance takes care of reusing SQL queries and optimizing the resources' usage. All fields can be resolved asynchronously.

Aiogram bot template is a boilerplate for creating Telegram bots using Aiogram framework. It provides a solid foundation for building robust and scalable bots with a focus on code organization, database integration, and localization.

Pluto is a development tool dedicated to helping developers **build cloud and AI applications more conveniently** , resolving issues such as the challenging deployment of AI applications and open-source models. Developers are able to write applications in familiar programming languages like **Python and TypeScript** , **directly defining and utilizing the cloud resources necessary for the application within their code base** , such as AWS SageMaker, DynamoDB, and more. Pluto automatically deduces the infrastructure resource needs of the app through **static program analysis** and proceeds to create these resources on the specified cloud platform, **simplifying the resources creation and application deployment process**.

The official Node.js client for Pinecone, written in TypeScript. This client library provides a high-level interface for interacting with the Pinecone vector database service. With this client, you can create and manage indexes, upsert and query vector data, and perform other operations related to vector search and retrieval. The client is designed to be easy to use and provides a consistent and idiomatic experience for Node.js developers. It supports all the features and functionality of the Pinecone API, making it a comprehensive solution for building vector-powered applications in Node.js.

Aiohttp pydantic is an aiohttp view to easily parse and validate requests. You define using function annotations what your methods for handling HTTP verbs expect, and Aiohttp pydantic parses the HTTP request for you, validates the data, and injects the parameters you want. It provides features like query string, request body, URL path, and HTTP headers validation, as well as Open API Specification generation.

This repository contains shared codebase for two projects: gcloud-aio and gcloud-rest. gcloud-aio is built for Python 3's asyncio, while gcloud-rest is a threadsafe requests-based implementation. It provides clients for Google Cloud services like Auth, BigQuery, Datastore, KMS, PubSub, Storage, and Task Queue. Users can install the library using pip and refer to the documentation for usage details. Developers can contribute to the project by following the contribution guide.

aioconsole is a Python package that provides asynchronous console and interfaces for asyncio. It offers asynchronous equivalents to input, print, exec, and code.interact, an interactive loop running the asynchronous Python console, customization and running of command line interfaces using argparse, stream support to serve interfaces instead of using standard streams, and the apython script to access asyncio code at runtime without modifying the sources. The package requires Python version 3.8 or higher and can be installed from PyPI or GitHub. It allows users to run Python files or modules with a modified asyncio policy, replacing the default event loop with an interactive loop. aioconsole is useful for scenarios where users need to interact with asyncio code in a console environment.

aiosqlite is a Python library that provides a friendly, async interface to SQLite databases. It replicates the standard sqlite3 module but with async versions of all the standard connection and cursor methods, along with context managers for automatically closing connections and cursors. It allows interaction with SQLite databases on the main AsyncIO event loop without blocking execution of other coroutines while waiting for queries or data fetches. The library also replicates most of the advanced features of sqlite3, such as row factories and total changes tracking.