Search Results for "ai for windows"
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Showing 1439 open source projects for "ai for windows"
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Stop Storing Third-Party Tokens in Your DatabaseRolling your own OAuth token storage can be a security liability. Token Vault securely stores access and refresh tokens from federated providers and handles exchange and renewal automatically. Connected accounts, refresh exchange, and privileged worker flows included.
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Add Two Lines of Code. Get Full APM.Works out of the box for Rails, Django, Express, Phoenix, and more. Monitoring exceptions and performance in no time.
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Windows-MCP
MCP server enabling AI agents to control and automate Windows OS
Windows-MCP is a lightweight open source project designed to connect AI agents with the Windows operating system through a Model Context Protocol server. It acts as a bridge that allows large language models to directly interact with desktop environments, enabling automated control over applications, files, and system interfaces. Windows-MCP provides capabilities such as file navigation, application management, UI interaction, and QA testing workflows, making it suitable for building autonomous desktop agents. ... -
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Trellis AI
All-in-one AI framework & toolkit for Claude Code & Cursor
Trellis is an advanced workflow and agent orchestration framework designed for building, managing, and scaling intelligent applications that coordinate numerous autonomous components. At its core, Trellis lets developers define units of work — called tasks or agents — and compose them into rich workflows that can operate with concurrency, conditional logic, and dynamic branching, all without sacrificing readability or control. It emphasizes modular design, encouraging users to encapsulate... -
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Flowly AI
Flowly is 100x faster than OpenClaw
Flowly is an open-source personal AI assistant that runs locally on your machine and connects to multiple communication platforms like Telegram, WhatsApp, Discord, and Slack. It acts as a centralized AI system that can perform tasks such as web browsing, file management, command execution, scheduling, and more—all while keeping your data private. Designed for flexibility, Flowly supports multiple AI providers and models through LiteLLM, allowing users to customize how their assistant... -
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AI Runner
Offline inference engine for art, real-time voice conversations
AI Runner is an offline inference engine designed to run a collection of AI workloads on your own machine, including image generation for art, real-time voice conversations, LLM-powered chatbots and automated workflows. It is implemented as a desktop-oriented Python application and emphasizes privacy and self-hosting, allowing users to work with text-to-speech, speech-to-text, text-to-image and multimodal models without sending data to external services. At the core of its LLM stack is a... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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AudioMuse-AI
AudioMuse-AI is an Open Source Dockerized environment
AudioMuse-AI is an open-source system designed to automatically generate playlists and analyze music libraries using artificial intelligence and audio signal processing techniques. The platform runs locally in a Dockerized environment and performs detailed sonic analysis on audio files to understand characteristics such as tempo, mood, and acoustic similarity. By analyzing the underlying audio content rather than relying on external metadata services, the system can organize large personal... -
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Shell-AI
LangChain powered shell command generator and runner CLI
...This approach improves productivity for developers and system administrators who frequently use terminal environments but may not recall every command variation. The application is designed to work across major operating systems including Linux, macOS, and Windows, making it broadly accessible to different development environments. -
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Arcade AI
Arcade Tool Development Kit (TDK), Worker, Evals, and CLI
Arcade AI Platform is a developer-oriented toolkit for building, deploying, and managing tools tailored to AI agents, structured as modular Python packages for flexibility and extensibility. Core platform functionality and schemas. This repository contains the core Arcade libraries, organized as separate packages for maximum flexibility and modularity. Evaluation framework for testing tool performance. Test your MCP server's tools, resources, prompts, elicitation, and OAuth 2. MCPJam is... -
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AutoAgent AI
Autonomous harness engineering
AutoAgent is an experimental AI framework focused on autonomous agent engineering, where a meta-agent iteratively improves another agent’s architecture without direct human intervention. Instead of manually tuning prompts or workflows, developers define high-level goals in a configuration file, and the system continuously modifies its own tools, orchestration, and logic based on benchmark performance. It operates through a loop of testing, analyzing failures, and refining the agent’s... -
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Paperless-AI
AI-powered document analysis and tagging for Paperless-ngx
Paperless-AI is an AI-powered extension designed to enhance document management within Paperless-ngx by automating analysis, classification, and organization tasks. It continuously monitors incoming documents and processes them using various AI backends, enabling automatic assignment of titles, tags, document types, and correspondents. It integrates with multiple OpenAI-compatible services as well as local models, giving users flexibility in how document intelligence is handled. A key... -
Gemini 3 and 200+ AI Models on One PlatformBuild, govern, and optimize agents and models with Gemini Enterprise Agent Platform.
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Ludwig AI
Low-code framework for building custom LLMs, neural networks
Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed),... -
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AI-Media2Doc
AI tool converting video/audio into structured documents instantly
AI-Media2Doc is a web-based application that uses large language models to convert video and audio content into structured, readable documents in a single workflow. It is designed to transform multimedia inputs into formats such as knowledge notes, summaries, mind maps, and social-style articles, making content easier to review and reuse. AI-Media2Doc emphasizes privacy by processing media locally in the browser using WebAssembly-based ffmpeg, ensuring that original video files are not... -
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ai-cookbook
Examples and tutorials to help developers build AI systems
ai-cookbook is an open-source repository that provides practical tutorials, code examples, and reusable snippets designed to help developers build real-world artificial intelligence applications quickly. The project focuses on delivering hands-on engineering guidance rather than theoretical explanations, allowing developers to copy, adapt, and integrate working code directly into their own systems. The repository contains examples that demonstrate how to build AI workflows using modern tools... -
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Datapizza AI
Build reliable Gen AI solutions without overhead
Datapizza AI is a lightweight framework for building modular, multi-agent AI systems that collaborate to solve complex tasks through orchestration and tool usage. The project focuses on simplicity and transparency, enabling developers to construct agent-based workflows without the heavy abstractions and dependencies often found in larger AI frameworks. It provides a flexible architecture where individual agents can be assigned specialized roles, such as web search, reasoning, or... -
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Cybersecurity AI
Cybersecurity AI (CAI), the framework for AI Security
CAI (Cybersecurity AI) is a lightweight open-source framework intended to help security practitioners build and deploy AI-assisted automation for defensive and offensive security workflows. The project frames itself as a practical foundation for “AI security,” focusing on turning security tasks into agentic workflows that can be composed, executed, and iterated on by practitioners. Rather than being a single-purpose tool, CAI is positioned as a framework that supports building multiple... -
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lightning AI
The most intuitive, flexible, way for researchers to build models
Build in days not months with the most intuitive, flexible framework for building models and Lightning Apps (ie: ML workflow templates) which "glue" together your favorite ML lifecycle tools. Build models and build/publish end-to-end ML workflows that "glue" your favorite tools together. Models are “easy”, the “glue” work is hard. Lightning Apps are community-built templates that stitch together your favorite ML lifecycle tools into cohesive ML workflows that can run on your laptop or any... -
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Lepton AI
A Pythonic framework to simplify AI service building
A Pythonic framework to simplify AI service building. Cutting-edge AI inference and training, unmatched cloud-native experience, and top-tier GPU infrastructure. Ensure 99.9% uptime with comprehensive health checks and automatic repairs. -
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CAMEL AI
Finding the Scaling Law of Agents. A multi-agent framework
The rapid advancement of conversational and chat-based language models has led to remarkable progress in complex task-solving. However, their success heavily relies on human input to guide the conversation, which can be challenging and time-consuming. This paper explores the potential of building scalable techniques to facilitate autonomous cooperation among communicative agents and provide insight into their "cognitive" processes. To address the challenges of achieving autonomous... -
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Colossal-AI
Making large AI models cheaper, faster and more accessible
The Transformer architecture has improved the performance of deep learning models in domains such as Computer Vision and Natural Language Processing. Together with better performance come larger model sizes. This imposes challenges to the memory wall of the current accelerator hardware such as GPU. It is never ideal to train large models such as Vision Transformer, BERT, and GPT on a single GPU or a single machine. There is an urgent demand to train models in a distributed environment.... -
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Generative AI
Sample code and notebooks for Generative AI on Google Cloud
Generative AI is a comprehensive collection of code samples, notebooks, and demo applications designed to help developers build generative-AI workflows on the Vertex AI platform. It spans multiple modalities—text, image, audio, search (RAG/grounding) and more—showing how to integrate foundation models like the Gemini family into cloud projects. The README emphasises getting started with prompts, datasets, environments and sample apps, making it ideal for both experimentation and... -
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Klavis AI
MCP integration platforms for AI agents to use tools at any scale
Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher... -
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TorchMetrics AI
Machine learning metrics for distributed, scalable PyTorch application
TorchMetrics is a collection of 100+ PyTorch metrics implementations and an easy-to-use API to create custom metrics. -
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AI-Trader
100% Fully-Automated Agent-Native Trading
AI-Trader is an open-source AI-powered quantitative trading framework designed to combine financial analysis, machine learning, and autonomous trading workflows into a unified research platform. The project integrates large language models, financial indicators, market analysis pipelines, and automated decision-making systems to support strategy generation and market prediction tasks. It is built to help researchers and developers experiment with AI-assisted trading strategies using... -
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AI-DLC
AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI
AI-DLC is an open-source workflow framework from AWS Labs designed to structure software development around AI-assisted engineering processes. The project promotes an “AI-Driven Life Cycle” methodology where coding assistants, IDE agents, and automation systems participate directly in planning, implementation, testing, and operational workflows. Rather than focusing on a single model or IDE, the framework provides reusable rules, templates, and orchestration patterns compatible with tools... -
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Pruna AI
Pruna is a model optimization framework built for developers
Pruna is an open-source, self-hostable AI inference engine designed to help teams deploy and manage large language models (LLMs) efficiently across private or hybrid infrastructures. Built with performance and developer ergonomics in mind, Pruna simplifies inference workflows by enabling multi-model orchestration, autoscaling, GPU resource allocation, and compatibility with popular open-source models. It is ideal for companies or teams looking to reduce reliance on external APIs while... -
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AI Researcher
An autonomous AI researcher
AI Researcher is an experimental open-source project that demonstrates how multiple AI agents can collaborate to conduct complex research tasks from start to finish with minimal human intervention. It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they...
