This repository contains a project that integrates Angular frontend, Node.js backend, Java services, and AI capabilities. The project aims to demonstrate a full-stack application with modern technologies and AI features. It showcases how to build a scalable and efficient system using Angular for the frontend, Node.js for the backend, Java for services, and AI for advanced functionalities.

TUUI is a desktop MCP client designed for accelerating AI adoption through the Model Context Protocol (MCP) and enabling cross-vendor LLM API orchestration. It is an LLM chat desktop application based on MCP, created using AI-generated components with strict syntax checks and naming conventions. The tool integrates AI tools via MCP, orchestrates LLM APIs, supports automated application testing, TypeScript, multilingual, layout management, global state management, and offers quick support through the GitHub community and official documentation.

Nexa SDK is a comprehensive toolkit supporting ONNX and GGML models for text generation, image generation, vision-language models (VLM), and text-to-speech (TTS) capabilities. It offers an OpenAI-compatible API server with JSON schema mode and streaming support, along with a user-friendly Streamlit UI. Users can run Nexa SDK on any device with Python environment, with GPU acceleration supported. The toolkit provides model support, conversion engine, inference engine for various tasks, and differentiating features from other tools.

MLC LLM is a high-performance universal deployment solution that allows native deployment of any large language models with native APIs with compiler acceleration. It supports a wide range of model architectures and variants, including Llama, GPT-NeoX, GPT-J, RWKV, MiniGPT, GPTBigCode, ChatGLM, StableLM, Mistral, and Phi. MLC LLM provides multiple sets of APIs across platforms and environments, including Python API, OpenAI-compatible Rest-API, C++ API, JavaScript API and Web LLM, Swift API for iOS App, and Java API and Android App.

Nekro Agent is an AI chat plugin and proxy execution bot that is highly scalable, offers high freedom, and has minimal deployment requirements. It features context-aware chat for group/private chats, custom character settings, sandboxed execution environment, interactive image resource handling, customizable extension development interface, easy deployment with docker-compose, integration with Stable Diffusion for AI drawing capabilities, support for various file types interaction, hot configuration updates and command control, native multimodal understanding, visual application management control panel, CoT (Chain of Thought) support, self-triggered timers and holiday greetings, event notification understanding, and more. It allows for third-party extensions and AI-generated extensions, and includes features like automatic context trigger based on LLM, and a variety of basic commands for bot administrators.

The LLM Platform, also known as Inference Hub, is an open-source tool designed to simplify the development and deployment of large language model applications at scale. It provides a unified framework for integrating and managing multiple LLM vendors, models, and related services through a flexible approach. The platform supports various LLM providers, document processing, RAG, advanced AI workflows, infrastructure operations, and flexible configuration using YAML files. Its modular and extensible architecture allows developers to plug in different providers and services as needed. Key components include completers, embedders, renderers, synthesizers, transcribers, document processors, segmenters, retrievers, summarizers, translators, AI workflows, tools, and infrastructure components. Use cases range from enterprise AI applications to scalable LLM deployment and custom AI pipelines. Integrations with LLM providers like OpenAI, Azure OpenAI, Anthropic, Google Gemini, AWS Bedrock, Groq, Mistral AI, xAI, Hugging Face, and more are supported.

ZCF (Zero-Config Claude-Code Flow) is a tool that provides zero-configuration, one-click setup for Claude Code with bilingual support, intelligent agent system, and personalized AI assistant. It offers an interactive menu for easy operations and direct commands for quick execution. The tool supports bilingual operation with automatic language switching and customizable AI output styles. ZCF also includes features like BMad Workflow for enterprise-grade workflow system, Spec Workflow for structured feature development, CCR (Claude Code Router) support for proxy routing, and CCometixLine for real-time usage tracking. It provides smart installation, complete configuration management, and core features like professional agents, command system, and smart configuration. ZCF is cross-platform compatible, supports Windows and Termux environments, and includes security features like dangerous operation confirmation mechanism.

AI Manus is a general-purpose AI Agent system that supports running various tools and operations in a sandbox environment. It offers deployment with minimal dependencies, supports multiple tools like Terminal, Browser, File, Web Search, and messaging tools, allocates separate sandboxes for tasks, manages session history, supports stopping and interrupting conversations, file upload and download, and is multilingual. The system also provides user login and authentication. The project primarily relies on Docker for development and deployment, with model capability requirements and recommended Deepseek and GPT models.

The Spring AI project provides a Spring-friendly API and abstractions for developing AI applications. It offers a portable client API for interacting with generative AI models, enabling developers to easily swap out implementations and access various models like OpenAI, Azure OpenAI, and HuggingFace. Spring AI also supports prompt engineering, providing classes and interfaces for creating and parsing prompts, as well as incorporating proprietary data into generative AI without retraining the model. This is achieved through Retrieval Augmented Generation (RAG), which involves extracting, transforming, and loading data into a vector database for use by AI models. Spring AI's VectorStore abstraction allows for seamless transitions between different vector database implementations.

Spec Workflow MCP is a Model Context Protocol (MCP) server that offers structured spec-driven development workflow tools for AI-assisted software development. It includes a real-time web dashboard and a VSCode extension for monitoring and managing project progress directly in the development environment. The tool supports sequential spec creation, real-time monitoring of specs and tasks, document management, archive system, task progress tracking, approval workflow, bug reporting, template system, and works on Windows, macOS, and Linux.

Nestia is a set of helper libraries for NestJS, providing super-fast/easy decorators, advanced WebSocket routes, Swagger generator, SDK library generator for clients, mockup simulator for client applications, automatic E2E test functions generator, test program utilizing e2e test functions, benchmark program using e2e test functions, super A.I. chatbot by Swagger document, Swagger-UI with online TypeScript editor, and a CLI tool. It enhances performance significantly and offers a collection of typed fetch functions with DTO structures like tRPC, along with a mockup simulator that is fully automated.

New API is a next-generation large model gateway and AI asset management system that provides a wide range of features, including a new UI interface, multi-language support, online recharge function, key query for usage quota, compatibility with the original One API database, model charging by usage count, channel weighted randomization, data dashboard, token grouping and model restrictions, support for various authorization login methods, support for Rerank models, OpenAI Realtime API, Claude Messages format, reasoning effort setting, content reasoning, user-specific model rate limiting, request format conversion, cache billing support, and various model support such as gpts, Midjourney-Proxy, Suno API, custom channels, Rerank models, Claude Messages format, Dify, and more.

LlamaFarm is a comprehensive AI framework that empowers users to build powerful AI applications locally, with full control over costs and deployment options. It provides modular components for RAG systems, vector databases, model management, prompt engineering, and fine-tuning. Users can create differentiated AI products without needing extensive ML expertise, using simple CLI commands and YAML configs. The framework supports local-first development, production-ready components, strategy-based configuration, and deployment anywhere from laptops to the cloud.

JADX-MCP-SERVER is a standalone Python server that interacts with JADX-AI-MCP Plugin to analyze Android APKs using LLMs like Claude. It enables live communication with decompiled Android app context, uncovering vulnerabilities, parsing manifests, and facilitating reverse engineering effortlessly. The tool combines JADX-AI-MCP and JADX MCP SERVER to provide real-time reverse engineering support with LLMs, offering features like quick analysis, vulnerability detection, AI code modification, static analysis, and reverse engineering helpers. It supports various MCP tools for fetching class information, text, methods, fields, smali code, AndroidManifest.xml content, strings.xml file, resource files, and more. Tested on Claude Desktop, it aims to support other LLMs in the future, enhancing Android reverse engineering and APK modification tools connectivity for easier reverse engineering purely from vibes.

KTransformers is a flexible Python-centric framework designed to enhance the user's experience with advanced kernel optimizations and placement/parallelism strategies for Transformers. It provides a Transformers-compatible interface, RESTful APIs compliant with OpenAI and Ollama, and a simplified ChatGPT-like web UI. The framework aims to serve as a platform for experimenting with innovative LLM inference optimizations, focusing on local deployments constrained by limited resources and supporting heterogeneous computing opportunities like GPU/CPU offloading of quantized models.

The Atomic Agents framework is a modular and extensible tool designed for creating powerful applications. It leverages Pydantic for data validation and serialization. The framework follows the principles of Atomic Design, providing small and single-purpose components that can be combined. It integrates with Instructor for AI agent architecture and supports various APIs like Cohere, Anthropic, and Gemini. The tool includes documentation, examples, and testing features to ensure smooth development and usage.

The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.

Sorrentum is an open-source project that aims to combine open-source development, startups, and brilliant students to build machine learning, AI, and Web3 / DeFi protocols geared towards finance and economics. The project provides opportunities for internships, research assistantships, and development grants, as well as the chance to work on cutting-edge problems, learn about startups, write academic papers, and get internships and full-time positions at companies working on Sorrentum applications.

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.

Zep is an open-source platform for building and deploying large language model (LLM) applications. It provides a suite of tools and services that make it easy to integrate LLMs into your applications, including chat history memory, embedding, vector search, and data enrichment. Zep is designed to be scalable, reliable, and easy to use, making it a great choice for developers who want to build LLM-powered applications quickly and easily.

This repository codifies the Airflow cluster that is deployed at workflow.telemetry.mozilla.org (behind SSO) and commonly referred to as "WTMO" or simply "Airflow". Some links relevant to users and developers of WTMO: * The `dags` directory in this repository contains some custom DAG definitions * Many of the DAGs registered with WTMO don't live in this repository, but are instead generated from ETL task definitions in bigquery-etl * The Data SRE team maintains a WTMO Developer Guide (behind SSO)

Mojo is a new programming language that bridges the gap between research and production by combining Python syntax and ecosystem with systems programming and metaprogramming features. Mojo is still young, but it is designed to become a superset of Python over time.

PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps you to explore, clean, and analyze your data using generative AI.

Databend is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.

Sweep is an AI junior developer that turns bugs and feature requests into code changes. It automatically handles developer experience improvements like adding type hints and improving test coverage.

The Teams AI Library is a software development kit (SDK) that helps developers create bots that can interact with Teams and Microsoft 365 applications. It is built on top of the Bot Framework SDK and simplifies the process of developing bots that interact with Teams' artificial intelligence capabilities. The SDK is available for JavaScript/TypeScript, .NET, and Python.

This guide is dedicated to Large Language Models (LLMs) that you can run on your home computer. It assumes your PC is a lower-end, non-gaming setup.

Supercharge WordPress Content Workflows and Engagement with Artificial Intelligence. Tap into leading cloud-based services like OpenAI, Microsoft Azure AI, Google Gemini and IBM Watson to augment your WordPress-powered websites. Publish content faster while improving SEO performance and increasing audience engagement. ClassifAI integrates Artificial Intelligence and Machine Learning technologies to lighten your workload and eliminate tedious tasks, giving you more time to create original content that matters.

Chatbot UI is an open-source AI chat app that allows users to create and deploy their own AI chatbots. It is easy to use and can be customized to fit any need. Chatbot UI is perfect for businesses, developers, and anyone who wants to create a chatbot.

BricksLLM is a cloud native AI gateway written in Go. Currently, it provides native support for OpenAI, Anthropic, Azure OpenAI and vLLM. BricksLLM aims to provide enterprise level infrastructure that can power any LLM production use cases. Here are some use cases for BricksLLM: * Set LLM usage limits for users on different pricing tiers * Track LLM usage on a per user and per organization basis * Block or redact requests containing PIIs * Improve LLM reliability with failovers, retries and caching * Distribute API keys with rate limits and cost limits for internal development/production use cases * Distribute API keys with rate limits and cost limits for students

uAgents is a Python library developed by Fetch.ai that allows for the creation of autonomous AI agents. These agents can perform various tasks on a schedule or take action on various events. uAgents are easy to create and manage, and they are connected to a fast-growing network of other uAgents. They are also secure, with cryptographically secured messages and wallets.

Griptape is a modular Python framework for building AI-powered applications that securely connect to your enterprise data and APIs. It offers developers the ability to maintain control and flexibility at every step. Griptape's core components include Structures (Agents, Pipelines, and Workflows), Tasks, Tools, Memory (Conversation Memory, Task Memory, and Meta Memory), Drivers (Prompt and Embedding Drivers, Vector Store Drivers, Image Generation Drivers, Image Query Drivers, SQL Drivers, Web Scraper Drivers, and Conversation Memory Drivers), Engines (Query Engines, Extraction Engines, Summary Engines, Image Generation Engines, and Image Query Engines), and additional components (Rulesets, Loaders, Artifacts, Chunkers, and Tokenizers). Griptape enables developers to create AI-powered applications with ease and efficiency.