Showing 8931 open source projects for "frameworks"

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  • 1
    TensorRT LLM

    TensorRT LLM

    TensorRT LLM provides users with an easy-to-use Python API

    ...It includes support for cutting-edge inference methods like speculative decoding and inflight batching, enabling real-time and large-scale AI applications. TensorRT-LLM integrates seamlessly with NVIDIA’s broader inference ecosystem, including Triton Inference Server and distributed deployment frameworks, making it suitable for production environments.
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  • 2
    Gooo

    Gooo

    Toolkit for developing web applications in Vue, Templ, and Go

    ...The project emphasizes simplicity and flexibility, enabling users to integrate its components into scripts or larger systems. While not as feature-heavy as enterprise frameworks, it serves as a foundation for experimentation and rapid prototyping in data extraction or automation tasks. Its design reflects a developer-centric approach, prioritizing extensibility and ease of modification over polished interfaces.
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  • 3
    Google Research: Language

    Google Research: Language

    Shared repository for open-sourced projects from the Google AI Lang

    ...Many of the projects included in the repository correspond to research papers released by Google researchers and provide implementations of new NLP algorithms or experimental frameworks. These implementations often explore advanced techniques such as language modeling, semantic understanding, information retrieval, and multilingual text processing. The repository functions as a collaborative hub where different research initiatives can publish their code, enabling the broader community to reproduce experiments and build upon published work.
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  • 4
    Machine Learning Foundations

    Machine Learning Foundations

    Machine Learning Foundations: Linear Algebra, Calculus, Statistics

    ...Each section introduces theoretical concepts and then illustrates them through practical coding examples to reinforce understanding. The project is designed for students and practitioners who want to strengthen their foundational knowledge before working with more advanced machine learning frameworks.
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  • 5
    rebroswer-patches

    rebroswer-patches

    Patches for Puppeteer and Playwright to reduce automation detection

    rebrowser-patches is an open source collection of patches designed to improve the stealth capabilities of browser automation frameworks. It focuses primarily on enhancing Puppeteer and Playwright by modifying parts of their source code that may reveal automation activity to websites. Many modern websites rely on bot detection mechanisms that identify automation through behavioral or technical signals, and these patches aim to reduce those detection vectors. By applying targeted fixes, the project helps developers minimize automation leaks that are difficult or impossible to address through configuration options alone. ...
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  • 6
    Jina-Serve

    Jina-Serve

    Build multimodal AI applications with cloud-native stack

    Jina Serve is an open-source framework designed for building, deploying, and scaling AI services and machine learning pipelines in production environments. The framework allows developers to create microservices that expose machine learning models through APIs that communicate using protocols such as HTTP, gRPC, and WebSockets. It is built with a cloud-native architecture that supports deployment on local machines, containerized environments, or large orchestration platforms such as...
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  • 7
    Better Agents

    Better Agents

    Standards for building agents, better

    Better Agents is a command-line tool and framework designed to standardize the development of AI agents and improve the workflow for building production-ready agent systems. The project provides a structured set of best practices and templates that help developers organize their agent projects in a way that promotes maintainability, scalability, and reliability. Rather than being a full execution framework itself, Better-Agents focuses on enhancing coding assistants and agent development...
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  • 8
    MiroThinker

    MiroThinker

    MiroThinker is an open source deep research agent

    MiroThinker is an open-source deep research AI agent designed to perform complex reasoning, information gathering, and predictive analysis tasks. The system focuses on enabling long-horizon research workflows by allowing the agent to interact repeatedly with external tools, search systems, and data sources while refining its reasoning through iterative steps. Rather than simply generating responses from a single prompt, the agent performs structured multi-step reasoning processes that...
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  • 9
    OneFileLLM

    OneFileLLM

    Specify a github or local repo, github pull request

    OneFileLLM is an open-source project designed to simplify the distribution and execution of large language model applications by packaging them into a single portable file. The concept behind the project is to eliminate the complexity normally associated with deploying AI systems, which often require multiple dependencies, frameworks, and configuration steps. Instead, the entire runtime environment, model interface, and application logic are bundled together into a single executable artifact. This design allows developers to share AI tools in a format that can be easily distributed and executed across different machines without complicated installation procedures. ...
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  • 10
    Aix-DB

    Aix-DB

    Based on the LangChain/LangGraph framework

    ...The system is designed as a ChatBI solution that allows users to query datasets using natural language and receive structured insights, charts, and visualizations automatically. Built on frameworks such as LangChain and LangGraph, Aix-DB integrates retrieval-augmented generation and Text-to-SQL capabilities to convert user questions into executable database queries. The platform supports multiple types of data sources and provides an end-to-end pipeline that includes intent recognition, SQL generation, database execution, and visual presentation of results. ...
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  • 11
    LLMs-Zero-to-Hero

    LLMs-Zero-to-Hero

    From nobody to big model (LLM) hero

    ...The repository presents a structured learning pathway that begins with fundamental concepts in machine learning and progresses toward advanced topics such as model pre-training, fine-tuning, and deployment. Rather than relying entirely on existing frameworks, the project encourages readers to implement important components themselves in order to gain a deeper understanding of how modern language models work internally. It includes explanations of dense transformer architectures, mixture-of-experts models, training pipelines, and techniques used in contemporary LLM development.
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  • 12
    MoBA

    MoBA

    MoBA: Mixture of Block Attention for Long-Context LLMs

    MoBA, short for Mixture of Block Attention, is an open-source research implementation of a novel attention mechanism designed to improve the efficiency of large language models processing extremely long contexts. The architecture adapts ideas from Mixture-of-Experts networks and applies them directly to the attention mechanism of transformer models. Instead of forcing each token to attend to every other token in the sequence, MoBA divides the context into blocks and dynamically routes...
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  • 13
    Kernel Memory

    Kernel Memory

    Research project. A Memory solution for users, teams, and applications

    Kernel Memory is an open-source reference architecture developed by Microsoft to help developers build memory systems for AI applications powered by large language models. The project focuses on enabling applications to store, index, and retrieve information so that AI systems can incorporate external knowledge when generating responses. It supports scenarios such as document ingestion, semantic search, and retrieval-augmented generation, allowing language models to answer questions using...
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  • 14
    KG-LLM-Papers

    KG-LLM-Papers

    Papers integrating knowledge graphs (KGs) and large language models

    KG-LLM-Papers is a curated academic resource that collects and organizes research papers exploring the intersection between knowledge graphs and large language models. The repository functions as a continuously updated index of scholarly work that investigates how structured knowledge representations can enhance the reasoning, factual accuracy, and interpretability of language models. It includes surveys, benchmark studies, and cutting-edge research that examine topics such as knowledge...
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  • 15
    LLM-Finetuning

    LLM-Finetuning

    LLM Finetuning with peft

    LLM-Finetuning is an open educational repository that provides practical notebooks and tutorials for fine-tuning large language models using modern machine learning frameworks. The project focuses on parameter-efficient fine-tuning methods such as LoRA and QLoRA, which allow large models to be adapted to new tasks without requiring full retraining. Instead of requiring specialized hardware or complex training pipelines, many examples are designed to run in cloud notebook environments such as Google Colab. ...
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  • 16
    Happy-LLM

    Happy-LLM

    Large Language Model Principles and Practice Tutorial from Scratch

    Happy-LLM is an open-source educational project created by the Datawhale AI community that provides a structured and comprehensive tutorial for understanding and building large language models from scratch. The project guides learners through the entire conceptual and practical pipeline of modern LLM development, starting with foundational natural language processing concepts and gradually progressing to advanced architectures and training techniques. It explains the Transformer...
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  • 17
    MyPerf4J

    MyPerf4J

    High performance Java APM. Powered by ASM

    MyPerf4J is an open source Java performance monitoring and profiling tool designed to help developers and operations teams analyze application behavior with minimal overhead. It focuses on providing lightweight yet high-precision metrics collection for method execution times, throughput, and latency, making it particularly useful in high-performance production environments. The project emphasizes low performance impact by using efficient time recording and aggregation techniques, allowing...
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  • 18
    do - Dependency Injection

    do - Dependency Injection

    A dependency injection toolkit based on Go 1.18+ Generics

    ...It also includes lifecycle management features like health checks and graceful shutdown handling, making it suitable for production services and microservices. Overall, samber/do delivers a modern, generics-powered alternative to traditional reflection-based DI frameworks in Go.
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  • 19
    Oat UI

    Oat UI

    Ultra-lightweight, zero dependency, semantic HTML, CSS, JS UI library

    Oat is an ultra-lightweight front-end UI library designed to automatically style semantic HTML using minimal CSS and JavaScript with zero external dependencies. The project focuses on simplicity and performance, allowing developers to create clean, modern interfaces without relying on heavy frameworks or complex build systems. Oat works by applying sensible default styling directly to standard HTML elements, meaning developers can achieve polished layouts with little to no custom classes. Its small footprint makes it especially attractive for static sites, documentation, prototypes, and low-overhead web applications. The library can be installed via npm, CDN, or direct download, making it flexible across different development workflows. ...
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  • 20
    raygui

    raygui

    A simple and easy-to-use immediate-mode gui library

    ...Because the library is distributed as a single header file containing both declarations and implementations, including it in a project is simple and doesn’t require complex build configurations. raygui supports a wide range of controls and customization options for colors, fonts, and layout metrics, and also includes a built-in set of 1-bit icons that can be embedded into controls. It’s intended for tools development, rapid GUIs for editors or debug interfaces, and simple applications that need basic UI without heavy frameworks.
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  • 21
    Cube Studio

    Cube Studio

    Cube Studio open source cloud native one-stop machine learning

    Cube Studio is an open-source, cloud-native end-to-end machine learning and AI platform designed to support the full lifecycle of AI development — from data preparation and interactive notebook coding to distributed training, model tuning, and deployment in production-ready environments. It provides a unified interface where teams can manage data sources, track datasets, and build pipelines using drag-and-drop workflow orchestration, making it accessible for both engineers and data...
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  • 22
    Agentic Data Scientist

    Agentic Data Scientist

    An end-to-end Data Scientist

    ...The framework supports interoperability with existing data tools and libraries, letting the agents leverage libraries like pandas, scikit-learn, and visualization frameworks to perform real computations rather than mock demonstrations.
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  • 23
    Open Wearables

    Open Wearables

    Self-hosted platform to unify wearable health data

    ...This approach allows users to break free from manufacturer lock-in while enabling richer, customizable dashboards, real-time visualizations, and personalized health analytics that match real-world needs rather than a one-size-fits-all model. It provides building blocks for federated data storage, modular device drivers, and plugin frameworks so contributions from different communities can extend capabilities without rewriting core logic.
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  • 24
    TailwindSQL

    TailwindSQL

    TailwindSQL lets you write SQL queries using Tailwind-style class name

    TailwindSQL is an experimental library that lets developers write SQL queries using Tailwind-style class names, essentially turning database queries into declarative class attributes that can be used directly in frameworks like React Server Components. Inspired by the simplicity and utility of Tailwind CSS, TailwindSQL allows developers to describe database queries using a familiar syntax such as db-table-column-where-field-value, collapsing traditional SQL into readable, utility-driven structures that map directly to data fetches. When used in React Server Components, these class-style queries are parsed and executed at render time with zero client-side JavaScript, letting you fetch and render data without writing SQL strings explicitly. ...
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  • 25
    nanocode

    nanocode

    Minimal Claude Code alternative. Single Python file, zero dependencies

    ...The project exemplifies how lightweight architectures can still support practical agent workflows without complex infrastructure, making it suitable for developers exploring agent frameworks or building custom coding assistants.
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