Search Results for "radeon-project" - Page 24
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Showing 3486 open source projects for "radeon-project"
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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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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Patroni
A template for PostgreSQL high availability with Etcd, Consul, etc.
...We call Patroni a "template" because it is far from being a one-size-fits-all or plug-and-play replication system. It will have its own caveats. Use wisely. Currently supported PostgreSQL versions 9.3 to 14. Patroni originated as a fork of Governor, the project from Compose. It includes plenty of new features. For an example of a Docker-based deployment with Patroni, see Spilo, currently in use at Zalando. -
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Python Slack SDK
Slack Developer Kit for Python
...It is useful for bots, workflow tools, internal automations, admin dashboards, notifications, onboarding assistants, and Slack-native business applications. Developers can use it to send messages, respond to events, verify requests, manage app authorization, and integrate Slack into Python services. The project is especially helpful for teams that want a maintained, first-party Python interface instead of manually building every Slack API request. -
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OPAL
Policy and data administration, distribution, and real-time updates
...It works with policy engines such as OPA and Cedar so applications can make decisions using current policy and data without constantly rebuilding custom sync logic. The project aggregates policy and data from external sources, watches for changes, and distributes updates to connected policy agents. It is built for cloud-native and microservice environments where authorization rules change frequently and need to propagate quickly. OPAL separates policy decision-making from policy distribution, which helps teams build more maintainable and consistent permission systems. ... -
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Translation Agent
Agentic translation using reflection workflow
...This structure makes the system more steerable than a traditional translation pipeline. Users can adjust prompts to control tone, formality, terminology, idiom handling, and regional language choices. The project includes example scripts and a simple Python interface for translating between source and target languages. It is useful for researchers, developers, and localization teams exploring how LLM-based workflows can produce better, more customizable translations. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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NVIDIA AI Blueprint
Suite of reference architectures for building GPU-accelerated vision
...It combines accelerated vision microservices, vision language models, large language models, embeddings, and NVIDIA NIM microservices to process both stored and streaming video. The project is organized around real-time video intelligence, downstream analytics, and agentic offline processing. It supports workflows such as natural-language video search, visual question answering, long-video summarization, clip retrieval, verified alerts, and incident analysis. It is designed for technical users who need deployable reference architectures for smart spaces, warehouse automation, SOP validation, monitoring, and operational video analytics. ... -
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Frigate Home Assistant Integration
Frigate integration for Home Assistant
...It depends on MQTT, because Frigate communicates many of its events and states through that channel. Users can also enable Home Assistant’s media source support to browse Frigate media from the Home Assistant interface. The project is especially useful for people building local-first camera monitoring systems with object detection, automations, and smart home alerts. -
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OpenSwarm
Claude code for everything except coding
...The included agents can handle research, data analysis, slide decks, documents, images, videos, scheduling, messaging, and other productivity tasks. It is designed for outputs like pitch decks, market research, SEO content, quarterly reports, launch campaigns, visual assets, and multimedia projects. The project can connect to external services through integrations and can be customized into purpose-specific swarms for areas such as SEO, sales, marketing, finance, customer support, or research. Its main appeal is giving technical users a forkable, terminal-based framework for building agent teams that produce polished business and creative deliverables. -
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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 such as Amazon Q Developer, Claude Code, Cursor, GitHub Copilot, and Cline. ... -
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nunif
Misc; latest version of waifu2x; 2D video to stereo 3D video
nunif is a deep learning–based image processing framework focused on image upscaling, restoration, denoising, and enhancement tasks using neural network models. The project provides a collection of AI-powered utilities designed primarily for anime-style artwork, illustrations, and high-quality image restoration workflows. It includes command-line tools and graphical interfaces for applying trained neural models to improve image resolution and visual clarity while minimizing artifacts. nunif supports GPU acceleration and batch processing, making it suitable for creators, archivists, and enthusiasts handling large image collections. ... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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Thoth
Thoth - Personal AI Sovereignty. A local-first AI assistant
Thoth is an AI-driven system designed to support advanced reasoning, knowledge processing, or agentic workflows, likely inspired by the concept of structured intelligence and decision-making. It focuses on organizing and synthesizing information in a way that enables deeper insights and more autonomous behavior. The project may incorporate LLMs, data pipelines, and modular components to handle complex tasks such as reasoning, planning, or knowledge retrieval. Its architecture likely emphasizes extensibility, allowing developers to customize workflows or integrate external tools. Thoth appears to target users interested in building intelligent systems that go beyond simple prompt-response interactions. ... -
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Claude Ads
Comprehensive paid advertising audit & optimization skill
...The architecture uses parallel subagents to speed up audits and includes financial modeling and A/B testing guidance. It runs locally, ensuring privacy and control over sensitive advertising data. The project is aimed at replacing manual audit workflows with fast, automated, and repeatable analysis. -
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Viral-Clips-Crew
Your CrewAI Powered Video Editing Assistant
...The system integrates tools like FFmpeg and AI models to handle segmentation, cropping, and formatting for vertical video platforms. It supports automation workflows that allow creators to produce multiple clips efficiently at scale. The project focuses on content repurposing, helping users adapt long videos into formats suitable for platforms like TikTok and YouTube Shorts. Its modular design allows customization of each processing stage, including selection logic and visual formatting. Overall, it serves as a tool for automating short-form content creation. -
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Cal.diy
Scheduling infrastructure for absolutely everyone
The Cal.diy project is a fully open-source, self-hosted scheduling platform that provides an alternative to proprietary booking tools while giving users complete control over their infrastructure. It is a community-driven fork of Cal.com that removes all enterprise and commercial features, ensuring that the entire codebase remains MIT-licensed and accessible. -
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Nothing Ever Happens
Focused async Python bot for Polymarket
Nothing Ever Happens is an experimental open-source trading bot designed for the Polymarket platform that implements a deliberately simple and unconventional strategy: automatically buying “No” positions across non-sports binary prediction markets. The project is built in Python using asynchronous architecture, allowing it to monitor markets, evaluate opportunities, and execute trades continuously with minimal latency. Its core concept is based on statistical observations that a majority of prediction market outcomes resolve negatively, and it attempts to exploit this base-rate bias through systematic participation rather than predictive modeling. ... -
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colleague-skill
Transform a cold separation into a warm Skill
colleague-skill is a specialized agent skill designed to simulate a collaborative teammate within AI-driven workflows, enabling agents to behave more like human colleagues in problem-solving scenarios. The project focuses on enhancing interaction quality by introducing role-based behavior, contextual awareness, and cooperative task execution. It allows agents to provide suggestions, feedback, and alternative approaches, mimicking real-world collaboration dynamics. The system likely integrates with broader agent frameworks, enabling seamless inclusion in multi-agent environments. ... -
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Clawith
OpenClaw for Teams
...Its architecture suggests support for multi-agent collaboration, enabling distributed problem-solving and task delegation. It may also include monitoring and control features to ensure that agent behavior remains aligned with user goals. The project reflects a broader trend toward building AI systems that act as autonomous operators rather than passive assistants. Overall, Clawith serves as a foundation for building advanced, action-oriented AI workflows. -
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MetaClaw
Just talk to your agent
MetaClaw is an AI or agent-oriented system that appears to focus on advanced control, coordination, or training of autonomous agents, potentially within reinforcement learning or tool-using environments. The project likely emphasizes meta-level reasoning, where agents are not only executing tasks but also adapting their strategies based on feedback and performance signals. It may incorporate mechanisms for learning from interactions, improving decision-making over time, and generalizing across different domains. The architecture suggests scalability, allowing the system to handle multiple agents or complex workflows simultaneously. ... -
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autoresearch-win-rtx
AI agents running research on single-GPU nanochat training
autoresearch-win-rtx is a Windows-based implementation of the autoresearch framework designed to run autonomous AI research loops on consumer NVIDIA RTX GPUs. It adapts the original autoresearch concept to a Windows environment, enabling users to perform iterative machine learning optimization without requiring specialized Linux or data center setups. The system revolves around a small set of core files, including a training script that is continuously modified by an AI agent, along with... -
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LeWorldModel
Official code base for LeWorldModel: Stable End-to-End Joint-Embedding
LeWorldModel is a minimalist tiling window manager designed for the X11 windowing system, focusing on simplicity, performance, and efficient use of screen space. It provides automatic window tiling behavior, organizing application windows into structured layouts without requiring manual resizing or positioning. The project emphasizes a lightweight design, minimizing resource usage while maintaining responsiveness and stability. It is highly configurable through source code or configuration files, allowing users to tailor behavior, keybindings, and layouts to their preferences. le-wm is intended for users who prefer keyboard-driven workflows and a distraction-free desktop environment. ... -
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LinkdAPI Python
Powerful, lightweight B2B Data API for enriching professional profiles
...It supports rapid development by abstracting low-level implementation details, allowing developers to focus on building features rather than managing connectivity. The project is designed with scalability in mind, making it suitable for both small applications and larger systems that require reliable API orchestration. It also emphasizes maintainability and clarity, ensuring that integrations remain consistent and easy to update over time. -
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TNT
A lightweight library for PyTorch training tools and utilities
TNT is a lightweight training framework developed by Meta that simplifies the process of building and managing machine learning training loops using PyTorch. The project focuses on providing a flexible yet structured environment for implementing training pipelines without the complexity of large deep learning frameworks. It introduces modular abstractions that allow developers to organize training logic into reusable components such as trainers, evaluators, and callbacks. This design helps separate concerns such as model training, evaluation, logging, and checkpointing, making machine learning experiments easier to manage. ... -
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RL with PyTorch
Clean, Robust, and Unified PyTorch implementation
RL with PyTorch is a research-oriented repository that provides implementations of deep reinforcement learning algorithms using the PyTorch framework. The project focuses on helping developers and researchers understand reinforcement learning methods by providing clean and reproducible implementations of well-known algorithms. It includes code for popular deep reinforcement learning techniques such as Deep Q-Networks, policy gradient methods, actor-critic architectures, and other modern RL approaches. ... -
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Finance
150+ quantitative finance Python programs
Finance is a repository that compiles structured notes and educational material related to financial analysis, markets, and quantitative finance concepts. The project focuses on explaining key principles used in finance and investment analysis, including topics such as financial statements, valuation models, portfolio theory, and financial markets. The repository is designed as a study reference for students and professionals who want to understand financial systems and the analytical frameworks used in financial decision-making. ... -
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Data Science Articles from CodeCut
Collection of useful data science topics along with articles
...Instead of providing a single software package, the repository aggregates articles, tutorials, and examples covering many topics within the data science ecosystem. The materials address areas such as MLOps, data management, project organization, testing practices, visualization techniques, and productivity tools used by data scientists. Each topic often includes references to code repositories, demonstrations, and video tutorials that show how the tools can be applied in real projects. The repository is intended to help practitioners stay updated with current best practices and technologies in the field of data science. -
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mosaicml composer
Supercharge Your Model Training
composer is a deep learning training framework built on PyTorch and designed to make large-scale model training more efficient, scalable, and customizable. At the center of the project is a highly optimized Trainer abstraction that simplifies the management of training loops, parallelization, metrics, logging, and data loading. The framework is intended for modern workloads that may span anything from a single GPU to very large distributed training environments, which makes it suitable for both experimentation and production-scale development. ...
