Showing 4289 open source projects for "java open source"

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  • Retool your internal operations Icon
    Retool your internal operations

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  • 1
    Advanced RAG Techniques

    Advanced RAG Techniques

    Advanced techniques for RAG systems

    Advanced RAG Techniques is a comprehensive collection of tutorials and implementations focused on advanced Retrieval-Augmented Generation (RAG) systems. It is designed to help practitioners move beyond basic RAG setups and explore techniques that improve retrieval quality, context construction, and answer robustness. The repository organizes techniques into categories such as foundational RAG, query enhancement, context enrichment, and advanced retrieval, making it easier to navigate...
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  • 2
    HunyuanWorld-Mirror

    HunyuanWorld-Mirror

    Fast and Universal 3D reconstruction model for versatile tasks

    HunyuanWorld-Mirror focuses on fast, universal 3D reconstruction that can ingest varied inputs and produce multiple kinds of 3D outputs. The model accepts combinations of images, camera intrinsics and poses, or even depth cues, then reconstructs consistent 3D geometry suitable for downstream rendering or editing. The pipeline emphasizes both speed and flexibility so creators can go from casual captures to assets without elaborate capture rigs. Outputs can include point clouds, estimated...
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  • 3
    LLMs-from-scratch

    LLMs-from-scratch

    Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

    LLMs-from-scratch is an educational codebase that walks through implementing modern large-language-model components step by step. It emphasizes building blocks—tokenization, embeddings, attention, feed-forward layers, normalization, and training loops—so learners understand not just how to use a model but how it works internally. The repository favors clear Python and NumPy or PyTorch implementations that can be run and modified without heavyweight frameworks obscuring the logic. Chapters...
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  • 4
    LitterBox

    LitterBox

    A secure sandbox environment for malware developers and red teamers

    LitterBox is a controlled malware-analysis and payload-testing sandbox aimed at red teams who need to validate evasions and behaviors before deployment. It provides an isolated environment to exercise payloads against modern detection stacks, verify signatures and heuristics, and observe runtime characteristics without leaking binaries to third-party vendors. The README frames typical use cases: testing evasion, validating detections, analyzing behavior, and keeping sensitive tooling...
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  • Atera all-in-one platform IT management software with AI agents Icon
    Atera all-in-one platform IT management software with AI agents

    Ideal for internal IT departments or managed service providers (MSPs)

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  • 5
    ArXiv MCP Server

    ArXiv MCP Server

    A Model Context Protocol server for searching and analyzing arXiv

    arxiv-mcp-server bridges AI assistants and the arXiv repository through a clean MCP interface, enabling search, metadata retrieval, and content access without bespoke scraping. With simple tools like “search” and “fetch,” an agent can find papers, pull abstracts, and download PDFs for downstream summarization or analysis. The project includes packaging and CI to publish to PyPI, plus tests and linting for reliability. Issue threads show feature requests such as extracting embedded LaTeX and...
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  • 6
    MCP Shrimp Task Manager

    MCP Shrimp Task Manager

    Shrimp Task Manager is a task tool built for AI Agents

    Shrimp Task Manager is an MCP server that converts natural-language requests into structured development tasks with dependencies, status, and style/format rules—built for agents that reason step-by-step. It emphasizes chain-of-thought and reflection loops, allowing an assistant to plan, refine, and re-prioritize work like a human project assistant. The server exposes typed tools so clients can create tasks, link prerequisites, record progress, and enforce writing or coding standards for...
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  • 7
    Claude Code Subagents Command Collection

    Claude Code Subagents Command Collection

    Claude Code Subagents & Commands Collection + CLI Tool

    This repository aggregates a large set of specialized subagents and slash commands designed for Claude Code, giving developers domain-focused “teammates” they can summon on demand. Each subagent is defined by a concise role, tools, and behaviors, and ships as Markdown you can drop into your .claude/agents/ directory. The collection targets common developer workflows such as scaffolding, refactoring, test writing, documentation, security checks, and project management. It includes a CLI...
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  • 8
    XcodeBuildMCP

    XcodeBuildMCP

    A Model Context Protocol (MCP) server

    XcodeBuildMCP is a Model Context Protocol server that exposes Xcode operations as typed tools and resources so AI assistants can build, test, and debug iOS apps programmatically. It’s organized with a modern plugin architecture and workflow-scoped tool directories, covering common developer actions across projects, schemes, targets, simulators, real devices, and Swift packages. The server aims to be “agent-ready,” surfacing capabilities (build, clean, test, archive, install, run, log...
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  • 9
    ENScan Go

    ENScan Go

    ENScan_GO is an enterprise information reconnaissance tool

    ENScan_GO is an enterprise information reconnaissance tool focused on Chinese corporate data sources. It aggregates official and third-party APIs to pull records like ICP filings, affiliated/holding companies, apps, mini-programs, and WeChat official accounts, then exports merged results for analysis. The tool targets analysts who need one-click collection and normalized output to reduce manual lookups across registries and platforms. Recent releases added a reworked task model with...
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  • Simplify Purchasing For Your Business Icon
    Simplify Purchasing For Your Business

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  • 10
    Firecrawl MCP Server

    Firecrawl MCP Server

    Adds powerful web scraping and search to Cursor and Claude

    firecrawl-mcp-server is the official MCP integration for Firecrawl that brings high-recall web scraping, crawling, and search into IDEs and agent runtimes. It exposes tools for single-page scrape, multi-URL batch jobs, site discovery, and search enrichment, returning cleaned, structured content suitable for downstream LLM reasoning. The server is designed to run with Firecrawl’s hosted API or self-hosted deployments, making it flexible for enterprise data-governance requirements. Built-in...
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  • 11
    4M

    4M

    4M: Massively Multimodal Masked Modeling

    4M is a training framework for “any-to-any” vision foundation models that uses tokenization and masking to scale across many modalities and tasks. The same model family can classify, segment, detect, caption, and even generate images, with a single interface for both discriminative and generative use. The repository releases code and models for multiple variants (e.g., 4M-7 and 4M-21), emphasizing transfer to unseen tasks and modalities. Training/inference configs and issues discuss things...
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  • 12
    LLaMA 3

    LLaMA 3

    The official Meta Llama 3 GitHub site

    This repository is the former home for Llama 3 model artifacts and getting-started code, covering pre-trained and instruction-tuned variants across multiple parameter sizes. It introduced the public packaging of weights, licenses, and quickstart examples that helped developers fine-tune or run the models locally and on common serving stacks. As the Llama stack evolved, Meta consolidated repositories and marked this one deprecated, pointing users to newer, centralized hubs for models,...
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  • 13
    fairseq2

    fairseq2

    FAIR Sequence Modeling Toolkit 2

    fairseq2 is a modern, modular sequence modeling framework developed by Meta AI Research as a complete redesign of the original fairseq library. Built from the ground up for scalability, composability, and research flexibility, fairseq2 supports a broad range of language, speech, and multimodal content generation tasks, including instruction fine-tuning, reinforcement learning from human feedback (RLHF), and large-scale multilingual modeling. Unlike the original fairseq—which evolved into a...
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  • 14
    Portkey AI Gateway

    Portkey AI Gateway

    A blazing fast AI Gateway with integrated guardrails

    Portkey AI Gateway aims to offer a blazing fast, secure, and flexible gateway for interacting with a wide variety of models and enforcing guardrails. It presents a single, friendly API through which you can route to 200+ LLMs, while applying configurable input/output guardrails to enforce policies or restrict certain content. It supports automatic retries, fallbacks, load balancing across providers or keys, and request timeouts to avoid latency spikes. The gateway is multimodal: it can...
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  • 15
    Flow Matching

    Flow Matching

    A PyTorch library for implementing flow matching algorithms

    flow_matching is a PyTorch library implementing flow matching algorithms in both continuous and discrete settings, enabling generative modeling via matching vector fields rather than diffusion. The underlying idea is to parameterize a flow (a time-dependent vector field) that transports samples from a simple base distribution to a target distribution, and train via matching of flows without requiring score estimation or noisy corruption—this can lead to more efficient or stable generative...
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  • 16
    DeiT (Data-efficient Image Transformers)
    DeiT (Data-efficient Image Transformers) shows that Vision Transformers can be trained competitively on ImageNet-1k without external data by using strong training recipes and knowledge distillation. Its key idea is a specialized distillation strategy—including a learnable “distillation token”—that lets a transformer learn effectively from a CNN or transformer teacher on modest-scale datasets. The project provides compact ViT variants (Tiny/Small/Base) that achieve excellent...
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  • 17
    PyTorch3D

    PyTorch3D

    PyTorch3D is FAIR's library of reusable components for deep learning

    PyTorch3D is a comprehensive library for 3D deep learning that brings differentiable rendering, geometric operations, and 3D data structures into the PyTorch ecosystem. It’s designed to make it easy to build and train neural networks that work directly with 3D data such as meshes, point clouds, and implicit surfaces. The library provides fast GPU-accelerated implementations of rendering pipelines, transformations, rasterization, and lighting—making it possible to compute gradients through...
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  • 18
    VGGT

    VGGT

    [CVPR 2025 Best Paper Award] VGGT

    VGGT is a transformer-based framework aimed at unifying classic visual geometry tasks—such as depth estimation, camera pose recovery, point tracking, and correspondence—under a single model. Rather than training separate networks per task, it shares an encoder and leverages geometric heads/decoders to infer structure and motion from images or short clips. The design emphasizes consistent geometric reasoning: outputs from one head (e.g., correspondences or tracks) reinforce others (e.g., pose...
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  • 19
    Seamless Communication

    Seamless Communication

    Foundational Models for State-of-the-Art Speech and Text Translation

    Seamless Communication is a research project focused on building more integrated, low-latency multimodal communication between humans and AI agents. The motivation is to move beyond “text in, text out” and enable direct, live, multi-turn exchange involving language, gesture, gaze, vision, and modality switching without user friction. The system architecture includes a real-time multimodal signal pipeline for audio, video, and sensor data, a dialog manager that can decide when to act (speak,...
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  • 20
    MCPB

    MCPB

    One-click local MCP server installation in desktop apps

    MCPB (MCP Bundles) defines a packaging format and toolchain for one-click installation of local Model Context Protocol (MCP) servers in desktop apps like Claude for macOS and Windows. An .mcpb file is a zip archive containing your server and a manifest.json that declares capabilities, entry points, permissions, and configuration inputs, much like how .crx packages Chrome extensions or .vsix packages VS Code extensions. The goal is to make local tool servers easy for end users to install,...
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  • 21
    Profile Data

    Profile Data

    Analyze computation-communication overlap in V3/R1

    profile-data is a repository that publishes profiling traces and metrics from DeepSeek’s training and inference infrastructure (especially during DeepSeek-V3 / R1 experiments). The profiling data targets insights into computation-communication overlap, pipeline scheduling (e.g. DualPipe), and how MoE / EP / parallelism strategies interact in real systems. The repository contains JSON trace files like train.json, prefill.json, decode.json, and associated assets. Users can load them into tools...
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  • 22
    Tiktoken

    Tiktoken

    tiktoken is a fast BPE tokeniser for use with OpenAI's models

    tiktoken is a high-performance, tokenizer library (based on byte-pair encoding, BPE) designed for use with OpenAI’s models. It handles encoding and decoding text to token IDs efficiently, with minimal overhead. Because tokenization is a fundamental step in preparing text for models, tiktoken is optimized for speed, memory, and correctness in model contexts (e.g. matching OpenAI’s internal tokenization). The repo supports multiple encodings (e.g. “cl100k_base”) and lets users switch encoding...
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  • 23
    Qwen2-Audio

    Qwen2-Audio

    Repo of Qwen2-Audio chat & pretrained large audio language model

    Qwen2-Audio is a large audio-language model by Alibaba Cloud, part of the Qwen series. It is trained to accept various audio signal inputs (including speech, sounds, etc.) and perform both voice chat and audio analysis, producing textual responses. It supports two major modes: Voice Chat (interactive voice only input) and Audio Analysis (audio + text instructions), with both base and instruction-tuned models. It is evaluated on many benchmarks (speech recognition, translation, sound...
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  • 24
    mlr3

    mlr3

    mlr3: Machine Learning in R - next generation

    mlr3 is a modern, object-oriented R framework for machine learning. It provides core abstractions (tasks, learners, resamplings, measures, pipelines) implemented using R6 classes, enabling extensible, composable machine learning workflows. It focuses on clean design, scalability (large datasets), and integration into the wider R ecosystem via extension packages. Users can do classification, regression, survival analysis, clustering, hyperparameter tuning, benchmarking etc., often via...
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  • 25
    Nerve

    Nerve

    The Simple Agent Development Kit

    Nerve is a developer-friendly Agent Development Kit (ADK) that utilizes YAML and a CLI to define, run, orchestrate, and evaluate LLM-driven agents. It supports declarative setups, tool integration, workflow pipelines, and both MCP client and server roles. Nerve is a simple yet powerful Agent Development Kit (ADK) to build, run, evaluate, and orchestrate LLM-based agents using just YAML and a CLI. It’s designed for technical users who want programmable, auditable, and reproducible automation...
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