MorGana Form is a full-stack form builder project developed using Next.js, React, TypeScript, Ant Design, PostgreSQL, and other technologies. It allows users to quickly create and collect data through survey forms. The project structure includes components, hooks, utilities, pages, constants, Redux store, themes, types, server-side code, and component packages. Environment variables are required for database settings, NextAuth login configuration, and file upload services. Additionally, the project integrates an AI model for form generation using the Ali Qianwen model API.

AIO Sandbox is an all-in-one agent sandbox environment that combines Browser, Shell, File, MCP operations, and VSCode Server in a single Docker container. It provides a unified, secure execution environment for AI agents and developers, with features like unified file system, multiple interfaces, secure execution, zero configuration, and agent-ready MCP-compatible APIs. The tool allows users to run shell commands, perform file operations, automate browser tasks, and integrate with various development tools and services.

Hub is an open-source, high-performance LLM gateway written in Rust. It serves as a smart proxy for LLM applications, centralizing control and tracing of all LLM calls and traces. Built for efficiency, it provides a single API to connect to any LLM provider. The tool is designed to be fast, efficient, and completely open-source under the Apache 2.0 license.

mcp-prompts is a Python library that provides a collection of prompts for generating creative writing ideas. It includes a variety of prompts such as story starters, character development, plot twists, and more. The library is designed to inspire writers and help them overcome writer's block by offering unique and engaging prompts to spark creativity. With mcp-prompts, users can access a wide range of writing prompts to kickstart their imagination and enhance their storytelling skills.

The MCP TypeScript Server Template is a production-grade framework for building powerful and scalable Model Context Protocol servers with TypeScript. It features built-in observability, declarative tooling, robust error handling, and a modular, DI-driven architecture. The template is designed to be AI-agent-friendly, providing detailed rules and guidance for developers to adhere to best practices. It enforces architectural principles like 'Logic Throws, Handler Catches' pattern, full-stack observability, declarative components, and dependency injection for decoupling. The project structure includes directories for configuration, container setup, server resources, services, storage, utilities, tests, and more. Configuration is done via environment variables, and key scripts are available for development, testing, and publishing to the MCP Registry.

DeepTutor is an AI-powered personalized learning assistant that offers a suite of modules for massive document knowledge Q&A, interactive learning visualization, knowledge reinforcement with practice exercise generation, deep research, and idea generation. The tool supports multi-agent collaboration, dynamic topic queues, and structured outputs for various tasks. It provides a unified system entry for activity tracking, knowledge base management, and system status monitoring. DeepTutor is designed to streamline learning and research processes by leveraging AI technologies and interactive features.

LobeHub Editor is a modern, extensible rich text editor built on Meta's Lexical framework with dual-architecture design, featuring both a powerful kernel and React integration. Optimized for AI applications and chat interfaces, it offers a dual architecture with kernel-based API and React components, rich plugin ecosystem, chat interface ready, slash commands, multiple export formats, customizable UI, file & media support, TypeScript native, and modern build system. The editor provides features like dual architecture, React-first design, rich plugin ecosystem, chat interface readiness, slash commands, multiple export formats, customizable UI, file & media support, TypeScript native, and modern build system.

VT.ai is a multimodal AI platform that offers dynamic conversation routing with SemanticRouter, multi-modal interactions (text/image/audio), an assistant framework with code interpretation, real-time response streaming, cross-provider model switching, and local model support with Ollama integration. It supports various AI providers such as OpenAI, Anthropic, Google Gemini, Groq, Cohere, and OpenRouter, providing a wide range of core capabilities for AI orchestration.

IG-LLM is a framework for solving inverse-graphics problems by instruction-tuning a Large Language Model (LLM) to decode visual embeddings into graphics code. The framework demonstrates natural generalization across distribution shifts without special inductive biases. It provides training and evaluation data for various scenarios like CLEVR, 2D, SO(3), 6-DoF, and ShapeNet. The environment setup can be done using conda/micromamba or Dockerfile. Training can be initiated for each scenario with specific commands, and inference can be performed using the provided script.

Lihil is a performant, productive, and professional web framework designed to make Python the mainstream programming language for web development. It is 100% test covered and strictly typed, offering fast performance, ergonomic API, and built-in solutions for common problems. Lihil is suitable for enterprise web development, delivering robust and scalable solutions with best practices in microservice architecture and related patterns. It features dependency injection, OpenAPI docs generation, error response generation, data validation, message system, testability, and strong support for AI features. Lihil is ASGI compatible and uses starlette as its ASGI toolkit, ensuring compatibility with starlette classes and middlewares. The framework follows semantic versioning and has a roadmap for future enhancements and features.

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.

fluid.sh is a tool designed to manage and debug VMs using AI agents in isolated environments before applying changes to production. It provides a workflow where AI agents work autonomously in sandbox VMs, and human approval is required before any changes are made to production. The tool offers features like autonomous execution, full VM isolation, human-in-the-loop approval workflow, Ansible export, and a Python SDK for building autonomous agents.

Distill is a reliability layer for LLM context that provides deterministic deduplication to remove redundancy before reaching the model. It aims to reduce redundant data, lower costs, provide faster responses, and offer more efficient and deterministic results. The tool works by deduplicating, compressing, summarizing, and caching context to ensure reliable outputs. It offers various installation methods, including binary download, Go install, Docker usage, and building from source. Distill can be used for tasks like deduplicating chunks, connecting to vector databases, integrating with AI assistants, analyzing files for duplicates, syncing vectors to Pinecone, querying from the command line, and managing configuration files. The tool supports self-hosting via Docker, Docker Compose, building from source, Fly.io deployment, Render deployment, and Railway integration. Distill also provides monitoring capabilities with Prometheus-compatible metrics, Grafana dashboard, and OpenTelemetry tracing.

One source of truth for AI CLI skills. Sync everywhere with one command — from personal to organization-wide. Stop managing skills tool-by-tool. `skillshare` gives you one shared skill source and pushes it everywhere your AI agents work. Safe by default with non-destructive merge mode. True bidirectional flow with `collect`. Cross-machine ready with Git-native `push`/`pull`. Team + project friendly with global skills for personal workflows and repo-scoped collaboration. Visual control panel with `skillshare ui` for browsing, install, target management, and sync status in one place.

Agentboard is a Web GUI for tmux optimized for agent TUI's like claude and codex. It provides a shared workspace across devices with features such as paste support, touch scrolling, virtual arrow keys, log tracking, and session pinning. Users can interact with tmux sessions from any device through a live terminal stream. The tool allows session discovery, status inference, and terminal I/O streaming for efficient agent management.

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.

MorGana Form is a full-stack form builder project developed using Next.js, React, TypeScript, Ant Design, PostgreSQL, and other technologies. It allows users to quickly create and collect data through survey forms. The project structure includes components, hooks, utilities, pages, constants, Redux store, themes, types, server-side code, and component packages. Environment variables are required for database settings, NextAuth login configuration, and file upload services. Additionally, the project integrates an AI model for form generation using the Ali Qianwen model API.

PC Agent introduces a novel framework to empower autonomous digital agents through human cognition transfer. It consists of PC Tracker for data collection, Cognition Completion for transforming raw data, and a multi-agent system for decision-making and visual grounding. Users can set up the tool in Python environment, customize data collection with PC Tracker, process data into cognitive trajectories, and run the multi-agent system. The tool aims to enable AI to work autonomously while users sleep, providing a cognitive journey into the digital world.

RoboMatrix is a skill-centric hierarchical framework for scalable robot task planning and execution in an open-world environment. It provides a structured approach to robot task execution using a combination of hardware components, environment configuration, installation procedures, and data collection methods. The framework is developed using the ROS2 framework on Ubuntu and supports robots from DJI's RoboMaster series. Users can follow the provided installation guidance to set up RoboMatrix and utilize it for various tasks such as data collection, task execution, and dataset construction. The framework also includes a supervised fine-tuning dataset and aims to optimize communication and release additional components in the future.

The LLM Engineer's Handbook is an official repository containing a comprehensive guide on creating an end-to-end LLM-based system using best practices. It covers data collection & generation, LLM training pipeline, a simple RAG system, production-ready AWS deployment, comprehensive monitoring, and testing and evaluation framework. The repository includes detailed instructions on setting up local and cloud dependencies, project structure, installation steps, infrastructure setup, pipelines for data processing, training, and inference, as well as QA, tests, and running the project end-to-end.

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.

formsflow.ai is a Free, Open-Source, Low Code Development Platform for rapidly building powerful business applications. It combines leading Open-Source applications including form.io forms, Camunda’s workflow engine, Keycloak’s security, and Redash’s data analytics into a seamless, integrated platform. Check out the installation documentation for installation instructions and features documentation to explore features and capabilities in detail.

Aire is a modern Laravel form builder with a focus on expressive and beautiful code. It allows easy configuration of form components using fluent method calls or Blade components. Aire supports customization through config files and custom views, data binding with Eloquent models or arrays, method spoofing, CSRF token injection, server-side and client-side validation, and translations. It is designed to run on Laravel 5.8.28 and higher, with support for PHP 7.1 and higher. Aire is actively maintained and under consideration for additional features like read-only plain text, cross-browser support for custom checkboxes and radio buttons, support for Choices.js or similar libraries, improved file input handling, and better support for content prepending or appending to inputs.

ConvoForm.com transforms traditional forms into interactive conversational experiences, powered by AI for an enhanced user journey. It offers AI-Powered Form Generation, Real-time Form Editing and Preview, and Customizable Submission Pages. The tech stack includes Next.js for frontend, tRPC for backend, GPT-3.5-Turbo for AI integration, and Socket.io for real-time updates. Local setup requires Node.js, pnpm, Git, PostgreSQL database, Clerk for Authentication, OpenAI key, Redis Database, and Sentry for monitoring. The project is open for contributions and is licensed under the MIT License.

DB2Rest is a modern low-code REST DATA API platform that simplifies the development of intelligent applications. It seamlessly integrates existing and new databases with language models (LMs/LLMs) and vector stores, enabling the rapid delivery of context-aware, reasoning applications without vendor lock-in.

TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Infinity is an AI-native database designed for LLM applications, providing incredibly fast full-text and vector search capabilities. It supports a wide range of data types, including vectors, full-text, and structured data, and offers a fused search feature that combines multiple embeddings and full text. Infinity is easy to use, with an intuitive Python API and a single-binary architecture that simplifies deployment. It achieves high performance, with 0.1 milliseconds query latency on million-scale vector datasets and up to 15K QPS.

PostgresML is a powerful Postgres extension that seamlessly combines data storage and machine learning inference within your database. It enables running machine learning and AI operations directly within PostgreSQL, leveraging GPU acceleration for faster computations, integrating state-of-the-art large language models, providing built-in functions for text processing, enabling efficient similarity search, offering diverse ML algorithms, ensuring high performance, scalability, and security, supporting a wide range of NLP tasks, and seamlessly integrating with existing PostgreSQL tools and client libraries.

LanceDB is an open-source database for vector-search built with persistent storage, which greatly simplifies retrieval, filtering, and management of embeddings. The key features of LanceDB include: Production-scale vector search with no servers to manage. Store, query, and filter vectors, metadata, and multi-modal data (text, images, videos, point clouds, and more). Support for vector similarity search, full-text search, and SQL. Native Python and Javascript/Typescript support. Zero-copy, automatic versioning, manage versions of your data without needing extra infrastructure. GPU support in building vector index(*). Ecosystem integrations with LangChain 🦜️🔗, LlamaIndex 🦙, Apache-Arrow, Pandas, Polars, DuckDB, and more on the way. LanceDB's core is written in Rust 🦀 and is built using Lance, an open-source columnar format designed for performant ML workloads.

Nucleoid is a declarative (logic) runtime environment that manages both data and logic under the same runtime. It uses a declarative programming paradigm, which allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help to distribute the load across multiple instances, which can further improve the performance of the system.

DB-GPT is an open source AI native data app development framework with AWEL(Agentic Workflow Expression Language) and agents. It aims to build infrastructure in the field of large models, through the development of multiple technical capabilities such as multi-model management (SMMF), Text2SQL effect optimization, RAG framework and optimization, Multi-Agents framework collaboration, AWEL (agent workflow orchestration), etc. Which makes large model applications with data simpler and more convenient.

SuperDuperDB is a Python framework for integrating AI models, APIs, and vector search engines directly with your existing databases, including hosting of your own models, streaming inference and scalable model training/fine-tuning. Build, deploy and manage any AI application without the need for complex pipelines, infrastructure as well as specialized vector databases, and moving our data there, by integrating AI at your data's source: - Generative AI, LLMs, RAG, vector search - Standard machine learning use-cases (classification, segmentation, regression, forecasting recommendation etc.) - Custom AI use-cases involving specialized models - Even the most complex applications/workflows in which different models work together SuperDuperDB is **not** a database. Think `db = superduper(db)`: SuperDuperDB transforms your databases into an intelligent platform that allows you to leverage the full AI and Python ecosystem. A single development and deployment environment for all your AI applications in one place, fully scalable and easy to manage.