Showing 8931 open source projects for "frameworks"

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  • 1
    SIA

    SIA

    AI framework to autonomously improve the performance of any AI system

    SIA is a self-improving AI framework designed to improve the performance of models or agents on benchmark tasks. It uses an iterative loop where a meta-agent creates or updates a task-specific target agent, while a feedback agent studies results and proposes improvements. The framework can refine both the harness around the task and the agent implementation itself. It is aimed at research and experimentation across tasks such as machine learning benchmarks, legal classification, code...
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  • 2
    zfoo

    zfoo

    Extremely fast enterprise server framework, can be used in RPC

    zfoo is an extremely fast enterprise server framework designed for RPC systems, game servers, web servers, and distributed application backends. It combines asynchronous execution, actor-style design, lock-free architecture, and native GraalVM support to deliver high scalability. The framework supports single-server, microservice, cluster, and gateway deployment modes, making it adaptable to different production architectures. Its protocol system supports many languages, including Java,...
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  • 3
    Hexabot

    Hexabot

    Hexabot is an open-source AI chatbot / agent builder

    Hexabot is an open-source chatbot and conversational AI platform designed to provide a modular and extensible environment for building intelligent assistants. It combines a visual interface with backend flexibility, allowing developers and non-technical users to design conversational flows, integrate APIs, and manage interactions in a structured way. The platform supports both rule-based and AI-driven interactions, enabling hybrid chatbot systems that can handle deterministic workflows...
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  • 4
    Stakpak

    Stakpak

    Ship your code, on autopilot. An open source agent

    Stakpak is an open-source autonomous DevOps agent designed to run continuously on a machine, managing infrastructure, deployments, and operational tasks with minimal human intervention. It acts as a persistent system-level assistant that monitors applications, executes DevOps workflows, and only alerts humans when necessary, effectively automating routine operational responsibilities. The agent is built with strong safety considerations, including guardrails that prevent destructive actions...
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  • 5
    templUI

    templUI

    A growing collection of beautifully designed UI components for Go

    ...It provides a growing collection of beautifully designed, production-ready components styled with Tailwind CSS, allowing developers to construct modern web interfaces without relying on heavy frontend frameworks. One of its defining principles is code ownership, meaning developers can either import components directly or copy them into their projects using a CLI, ensuring full control over customization and long-term maintenance. The library avoids JavaScript frameworks entirely, instead relying on lightweight, vanilla implementations that prioritize speed and simplicity. templUI also emphasizes security and compliance, with features such as CSP-friendly rendering and no inline scripts, making it suitable for enterprise environments.
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  • 6
    Chicory

    Chicory

    Native JVM WebAssembly runtime

    ...Its design eliminates the need for external system libraries, making deployment straightforward and consistent across platforms. The project also supports integration into frameworks and build systems, enabling developers to embed Wasm-based functionality into larger applications.
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  • 7
    Companion notebooks for Deep Learning

    Companion notebooks for Deep Learning

    Jupyter notebooks for the code samples of the book

    ...The material is designed to be accessible while still covering advanced topics, making it suitable for both beginners and intermediate practitioners. It leverages modern libraries and frameworks to demonstrate real-world applications of deep learning techniques. The notebooks also emphasize best practices in model training, evaluation, and deployment. Overall, this project serves as a comprehensive educational resource for learning deep learning through practical experimentation.
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  • 8
    XXL-SSO

    XXL-SSO

    A distributed single-sign-on framework

    XXL-SSO is a distributed single sign-on (SSO) system designed to provide centralized authentication and authorization across multiple applications and services. It enables users to log in once and gain access to various systems without needing to reauthenticate, improving both user experience and security. The project is built with scalability in mind, supporting distributed environments where multiple services need to share identity information. It likely includes token-based authentication...
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  • 9
    FormCreate

    FormCreate

    The easy-to-use Vue low-code visual AI form designer

    ...The tool is designed to significantly reduce development time by allowing users to visually assemble forms while automatically generating the underlying configuration and logic. It supports multiple UI frameworks such as Element Plus and Vant, making it adaptable for both desktop and mobile applications. The platform has been widely applied in enterprise systems such as ERP, OA, and e-commerce platforms, demonstrating its scalability and reliability in production environments. Additionally, it includes support for custom components and extensibility, allowing developers to tailor form behavior to complex business requirements.
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  • 10
    Cosmos-RL

    Cosmos-RL

    Cosmos-RL is a flexible and scalable Reinforcement Learning framework

    Cosmos-RL is a scalable reinforcement learning framework designed specifically for physical AI systems such as robotics, autonomous agents, and multimodal models. It provides a distributed training architecture that separates policy learning and environment rollout processes, enabling efficient and asynchronous reinforcement learning at scale. The framework supports multiple parallelism strategies, including tensor, pipeline, and data parallelism, allowing it to leverage large GPU clusters...
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  • 11
    JAX Toolbox

    JAX Toolbox

    Public CI, Docker images for popular JAX libraries

    ...It provides prebuilt Docker images, continuous integration pipelines, and optimized example implementations that help developers quickly set up and run JAX workloads without complex configuration. The project supports popular JAX-based frameworks and models, including architectures used for large-scale pretraining such as GPT and LLaMA variants. By offering curated environments and tested configurations, it reduces compatibility issues and accelerates development workflows for both research and production. The repository also includes performance-optimized examples that demonstrate best practices for leveraging NVIDIA hardware effectively. ...
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  • 12
    Functions Framework for Node.js

    Functions Framework for Node.js

    FaaS (Function as a service) framework for writing portable Node.js

    Functions Framework for Node.js is a lightweight runtime library that allows developers to write and run portable serverless functions locally or in cloud environments using standard Node.js. It provides a consistent execution model that mimics Google Cloud Functions, enabling developers to build, test, and debug functions on their local machine before deploying them to production. The framework supports multiple function signature types, including HTTP-based functions and event-driven...
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  • 13
    Terraform Examples and Modules for GC

    Terraform Examples and Modules for GC

    End-to-end modular samples and landing zones toolkit for Terraform

    ...It provides a collection of end-to-end blueprints and composable modules that allow teams to implement standardized cloud architectures such as landing zones, networking configurations, and security frameworks. The project is designed to accelerate cloud adoption by offering opinionated yet flexible patterns aligned with Google Cloud best practices, helping organizations bootstrap their environments quickly while maintaining governance and scalability. It supports complex multi-project and multi-environment setups, making it suitable for large enterprises that require consistent infrastructure provisioning across teams.
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  • 14
    Zendriver

    Zendriver

    A blazing fast, async-first, undetectable webscraping

    Zendriver is a modern Python web automation and scraping framework that leverages the Chrome DevTools Protocol to provide fast, asynchronous control over real browser instances. Unlike traditional tools that rely on Selenium or WebDriver, Zendriver communicates directly with the browser through CDP, enabling higher performance and more precise control over browser behavior. The framework is designed to be difficult to detect by anti-bot systems, making it suitable for advanced scraping and...
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  • 15
    Mink

    Mink

    PHP web browser emulator abstraction

    ...This abstraction enables developers to write tests once and run them across different environments without changing the test code. Mink is commonly used in behavior-driven development workflows, particularly with frameworks like Behat, where it helps simulate real user behavior such as clicking links, filling forms, and navigating pages. The library supports session management, allowing multiple browser sessions to run simultaneously and interact with different pages or environments.
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  • 16
    Swarms

    Swarms

    Enterprise multi-agent orchestration framework for scalable AI apps

    ...It emphasizes production readiness, offering modular architecture, high availability, and observability features suitable for large-scale deployments. It supports integration with multiple model providers and existing ecosystems, allowing developers to combine different AI tools and frameworks within a unified system. Swarms also includes mechanisms for agent lifecycle management, memory handling, and dynamic composition, making it adaptable to evolving workloads. Additionally, it focuses on developer productivity through APIs, CLI tools, and templates that simplify building and deploying agent-based applications.
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  • 17
    ARK

    ARK

    Unstyled, accessible UI components for your design System

    ...The project focuses on separating component behavior from visual styling so developers can implement their own design language without being constrained by predefined styles. Built on top of Zag.js state machines, Ark delivers predictable and robust component logic that works consistently across multiple JavaScript frameworks. It supports React, Solid, Vue, and Svelte, enabling developers to share component behavior across ecosystems while maintaining framework-specific implementations. Because the components are headless, developers bring their own CSS frameworks, styling solutions, or design tokens, which makes the library highly adaptable for custom UI systems.
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  • 18
    Vendure Core

    Vendure Core

    Open source headless commerce framework built with TypeScript

    ...Built with Node.js and TypeScript, the platform provides a modular architecture that allows developers to create complex commerce systems tailored to specific business requirements. Vendure separates the backend commerce engine from the front-end storefront, allowing developers to build custom user interfaces using modern frameworks such as React, Angular, or Vue. The framework includes core e-commerce functionality such as product management, order processing, payment handling, and inventory tracking. It also provides a powerful plugin system that allows developers to extend or modify functionality without altering the core platform. Because Vendure exposes its services through a flexible API layer, it can be integrated with multiple storefronts, mobile apps, or third-party services.
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  • 19
    AI-Tutorials/Implementations Notebooks

    AI-Tutorials/Implementations Notebooks

    Codes/Notebooks for AI Projects

    ...Many of the tutorials focus on building AI agents, multi-agent systems, and workflows that integrate language models with external tools or APIs. The codebase acts as a hands-on learning resource, allowing users to experiment with new frameworks, architectures, and machine learning workflows through guided examples.
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  • 20
    The Machine & Deep Learning Compendium

    The Machine & Deep Learning Compendium

    List of references in my private & single document

    The Machine & Deep Learning Compendium is an open-source knowledge repository that compiles summaries, references, and learning materials related to machine learning and deep learning. The project functions as a comprehensive compendium that organizes hundreds of topics covering algorithms, frameworks, research areas, and practical machine learning workflows. Originally created as a personal knowledge base, the repository evolved into a public educational resource designed to help learners explore the rapidly expanding machine learning ecosystem. The compendium includes explanations of concepts across multiple domains such as natural language processing, computer vision, time-series analysis, anomaly detection, and graph learning. ...
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  • 21
    Cog

    Cog

    Package and deploy machine learning models using Docker containers

    ...Developers can define the runtime environment, dependencies, and Python versions required for their models, allowing Cog to build a consistent container environment that follows best practices. Cog also resolves compatibility issues between frameworks and GPU libraries by automatically selecting compatible combinations of CUDA, cuDNN, and machine learning frameworks such as PyTorch or TensorFlow. Cog automatically generates a RESTful HTTP API for running predictions, enabling models to be accessed programmatically through a built-in prediction server.
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  • 22
    Kodezi Chronos

    Kodezi Chronos

    Kodezi Chronos is a debugging-first language model

    ...Another component, Persistent Debug Memory, allows the system to learn patterns from past debugging sessions and apply that knowledge to future problems. The repository mainly contains research documentation, evaluation benchmarks, and experimental frameworks rather than the full proprietary model implementation.
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  • 23
    Autonomous Agents

    Autonomous Agents

    Autonomous Agents (LLMs) research papers. Updated Daily

    ...The project explores how multiple agents can cooperate and interact with complex environments through machine learning, imitation learning, and multimodal sensing. It includes frameworks that integrate visual perception, tactile sensing, and spatial reasoning to guide the actions of robotic agents during manipulation or collaborative tasks. One of the central concepts explored in the repository is the integration of different sensory modalities using advanced machine learning techniques such as Feature-wise Linear Modulation and graph-based attention mechanisms. ...
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  • 24
    DATAGEN

    DATAGEN

    AI-driven multi-agent research assistant automating hypothesis

    ...Instead of requiring users to manually orchestrate each stage of a research process, the platform allows these agents to coordinate automatically and handle the workflow end-to-end. The project integrates several modern AI frameworks including LangChain, LangGraph, and large language models to manage reasoning and data processing tasks. Through this architecture, the system can combine structured data analysis with natural language reasoning to generate insights and research outputs. The platform is designed for researchers, analysts, and developers who want to accelerate data exploration and automate parts of the research lifecycle.
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  • 25
    All Agentic Architectures

    All Agentic Architectures

    Implementation of 17+ agentic architectures

    ...The project acts as a practical learning resource that bridges the gap between theoretical research on autonomous agents and real software implementations. It contains more than a dozen agent architectures implemented using frameworks such as LangChain and LangGraph. Each architecture is explained through runnable notebooks that illustrate how the agent works internally and how it interacts with tools, data sources, or other agents. The repository organizes the architectures into a structured learning path that progresses from simple reasoning agents to complex multi-agent systems. ...
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