Showing 6013 open source projects for "java open source"

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  • Automate contact and company data extraction Icon
    Automate contact and company data extraction

    Build lead generation pipelines that pull emails, phone numbers, and company details from directories, maps, social platforms. Full API access.

    Generate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
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  • All-in-one security tool helps you prevent ransomware and breaches. Icon
    All-in-one security tool helps you prevent ransomware and breaches.

    SIEM + Detection and Response for IT Teams

    Blumira’s detection and response platform enables faster resolution of threats to help you stop ransomware attacks and prevent data breaches. We surface real threats, providing meaningful findings so you know what to prioritize. With our 3-step rapid response, you can automatically block known threats, use our playbooks for easy remediation, or contact our security team for additional guidance. Our responsive security team helps with onboarding, triage and ongoing consultations to continuously help your organization improve your security coverage.
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  • 1
    Elyra

    Elyra

    Elyra extends JupyterLab with an AI centric approach

    Elyra is a set of AI-centric extensions to JupyterLab Notebooks. The Elyra Getting Started Guide includes more details on these features. A version-specific summary of new features is located on the releases page.
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  • 2
    cuML

    cuML

    RAPIDS Machine Learning Library

    cuML is a suite of libraries that implement machine learning algorithms and mathematical primitives functions that share compatible APIs with other RAPIDS projects. cuML enables data scientists, researchers, and software engineers to run traditional tabular ML tasks on GPUs without going into the details of CUDA programming. In most cases, cuML's Python API matches the API from scikit-learn. For large datasets, these GPU-based implementations can complete 10-50x faster than their CPU...
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  • 3
    embedchain

    embedchain

    Framework to easily create LLM powered bots over any dataset

    Embedchain is a framework to easily create LLM-powered bots over any dataset. If you want a javascript version, check out embedchain-js. Embedchain empowers you to create chatbot models similar to ChatGPT, using your own evolving dataset. Start building LLM powered bots under 30 seconds.
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  • 4
    AIaC

    AIaC

    Artificial Intelligence Infrastructure-as-Code Generator

    aiac is a command line tool to generate IaC (Infrastructure as Code) templates, configurations, utilities, queries and more via OpenAI's API. The CLI allows you to ask the model to generate templates for different scenarios (e.g. "get terraform for AWS EC2"). It will make the request, and store the resulting code to a file, or simply print it to standard output. By default, aiac uses the same model used by ChatGPT, but allows using different models.
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  • Desktop and Mobile Device Management Software Icon
    Desktop and Mobile Device Management Software

    It's a modern take on desktop management that can be scaled as per organizational needs.

    Desktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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  • 5
    OpenCLIP

    OpenCLIP

    An open source implementation of CLIP

    The goal of this repository is to enable training models with contrastive image-text supervision and to investigate their properties such as robustness to distribution shift. Our starting point is an implementation of CLIP that matches the accuracy of the original CLIP models when trained on the same dataset. Specifically, a ResNet-50 model trained with our codebase on OpenAI's 15 million image subset of YFCC achieves 32.7% top-1 accuracy on ImageNet. OpenAI's CLIP model reaches 31.3% when...
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  • 6
    DeepPavlov

    DeepPavlov

    A library for deep learning end-to-end dialog systems and chatbots

    ...Guides explain the concepts and components of DeepPavlov. Follow step-by-step instructions to install, configure and extend DeepPavlov framework for your use case. DeepPavlov is an open-source framework for chatbots and virtual assistants development. It has comprehensive and flexible tools that let developers and NLP researchers create production-ready conversational skills and complex multi-skill conversational assistants. Use BERT and other state-of-the-art deep learning models to solve classification, NER, Q&A and other NLP tasks. ...
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  • 7
    gpt-oss-safeguard

    gpt-oss-safeguard

    Safety reasoning models built-upon gpt-oss

    gpt-oss-safeguard is an open-weight reasoning model family released by OpenAI designed specifically for content safety and moderation tasks. Rather than just outputting a numeric “safety score,” it is trained to reason about content with respect to a user-provided policy, allowing flexible, customizable moderation definitions rather than fixed rules — ideal when different platforms have different safety standards. The model comes in at least two variants: a large 120B-parameter version for...
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  • 8
    Best-of Machine Learning with Python

    Best-of Machine Learning with Python

    A ranked list of awesome machine learning Python libraries

    This curated list contains 900 awesome open-source projects with a total of 3.3M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an issue, submit a pull request, or directly edit the projects.yaml.
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  • 9
    Gemma

    Gemma

    Gemma open-weight LLM library, from Google DeepMind

    Gemma, developed by Google DeepMind, is a family of open-weights large language models (LLMs) built upon the research and technology behind Gemini. This repository provides the official implementation of the Gemma PyPI package, a JAX-based library that enables users to load, interact with, and fine-tune Gemma models. The framework supports both text and multi-modal input, allowing natural language conversations that incorporate visual content such as images. It includes APIs for...
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  • Axe Credit Portal - ACP- is axefinance’s future-proof AI-driven solution to digitalize the loan process from KYC to servicing, available as a locally hosted or cloud-based software. Icon
    Axe Credit Portal - ACP- is axefinance’s future-proof AI-driven solution to digitalize the loan process from KYC to servicing, available as a locally hosted or cloud-based software.

    Banks, lending institutions

    Founded in 2004, axefinance is a global market-leading software provider focused on credit risk automation for lenders looking to provide an efficient, competitive, and seamless omnichannel financing journey for all client segments (FI, Retail, Commercial, and Corporate.)
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  • 10
    Granite 3.0 Language Models

    Granite 3.0 Language Models

    New set of lightweight state-of-the-art, open foundation models

    This repository introduces Granite 3.0 language models as lightweight, state-of-the-art open foundation models built to natively support multilinguality, coding, reasoning, and tool usage. A central goal is efficient deployment, including the potential to run on constrained compute resources while remaining useful for a broad span of enterprise tasks. The repo positions the models for both research and commercial use under an Apache-2.0 license, signaling permissive adoption paths....
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  • 11
    CAMEL AI

    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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  • 12
    FlowLens MCP

    FlowLens MCP

    Open-source MCP server that gives your coding agent

    FlowLens MCP Server is an open-source tool designed to give AI-powered coding agents (like Claude Code, Cursor, GitHub Copilot / Codex, and others) full, replayable browser context to dramatically improve debugging, bug reporting, and regression testing for web applications. It works together with a companion browser extension: when a user reproduces a bug or a complicated UI interaction, the extension captures a rich session log, including screen/video recording, network traffic, console logs, DOM events, storage changes, and more, and exports it. ...
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  • 13
    MetaVoice-1B

    MetaVoice-1B

    Foundational model for human-like, expressive TTS

    ...With that scale and dataset volume, MetaVoice aims to push the boundary of what open-source TTS models can achieve: high fidelity, natural prosody, and robustness even for edge cases. As a foundational model, it can serve as the backbone for downstream tasks — such as voice generation, voice cloning, speech generation for virtual agents, or even audio production pipelines.
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  • 14
    D4RL

    D4RL

    Collection of reference environments, offline reinforcement learning

    D4RL (Datasets for Deep Data-Driven Reinforcement Learning) is a benchmark suite focused on offline reinforcement learning — i.e., learning policies from fixed datasets rather than via online interaction with the environment. It contains standardized environments, tasks and datasets (observations, actions, rewards, terminals) aimed at enabling reproducible research in offline RL. Researchers can load a dataset for a given task (e.g., maze navigation, manipulation) and apply their algorithm...
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  • 15
    mcpo

    mcpo

    A simple, secure MCP-to-OpenAPI proxy server

    mcpo is a minimal bridge that exposes any MCP tool as an OpenAPI-compatible HTTP server. Instead of writing glue code, you point mcpo at an MCP server command and it generates REST endpoints and an OpenAPI spec that other systems (or LLM agent frameworks) can call immediately. This design lets you reuse a growing library of MCP servers with platforms that only understand HTTP+OpenAPI, unifying tool access across ecosystems. The project emphasizes “dead-simple” setup and pairs with Open WebUI...
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  • 16
    Context7 MCP

    Context7 MCP

    Up-to-date code documentation for LLMs and AI code editors

    Context7 is a system that aims to inject fresh, version-specific documentation and code snippets into language model prompts, thereby avoiding reliance on outdated training data or hallucinated APIs. It’s designed to integrate with tools that support the Model Context Protocol (MCP), such as Cursor, Windsurf, and other LLM clients. When a user writes a prompt and appends something like “use context7,” the system detects the libraries or frameworks being asked about, fetches the latest...
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  • 17
    AutoMLOps

    AutoMLOps

    Build MLOps Pipelines in Minutes

    AutoMLOps is a service that generates, provisions, and deploys CI/CD integrated MLOps pipelines, bridging the gap between Data Science and DevOps. AutoMLOps provides a repeatable process that dramatically reduces the time required to build MLOps pipelines. The service generates a containerized MLOps codebase, provides infrastructure-as-code to provision and maintain the underlying MLOps infra, and provides deployment functionalities to trigger and run MLOps pipelines. AutoMLOps gives...
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  • 18
    FastChat

    FastChat

    Open platform for training, serving, and evaluating language models

    FastChat is an open platform for training, serving, and evaluating large language model-based chatbots. If you do not have enough memory, you can enable 8-bit compression by adding --load-8bit to the commands above. This can reduce memory usage by around half with slightly degraded model quality. It is compatible with the CPU, GPU, and Metal backend. Vicuna-13B with 8-bit compression can run on a single NVIDIA 3090/4080/T4/V100(16GB) GPU. In addition to that, you can add --cpu-offloading to...
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  • 19
    GLM-4.1V

    GLM-4.1V

    GLM-4.6V/4.5V/4.1V-Thinking, towards versatile multimodal reasoning

    ...It represents a trade-off: somewhat reduced capacity compared to 4.5V or 4.6V, but with benefits in terms of speed, deployability, and lower hardware requirements — making it especially useful for developers experimenting locally, building lightweight agents, or deploying on limited infrastructure. Given its open-source availability under the same project repository, it provides an accessible entry point for testing multimodal reasoning and building proof-of-concept applications.
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  • 20
    Sora.FM

    Sora.FM

    Sora AI Video Generator by Sora.FM

    ...For creators wanting to explore AI-based content generation — for example automated video clips, short-form media, or other generated video content — sorafm offers a starting point. As with many open-source generators in this space, the tradeoff lies in balancing ease-of-use and the limitations of generative output, but the fact that it’s publicly available means users can experiment, iterate, or fork to adapt pipelines: maybe customizing model prompts, video templates, or post-processing.
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  • 21
    Sa2VA

    Sa2VA

    Official Repo For "Sa2VA: Marrying SAM2 with LLaVA

    Sa2VA is a cutting-edge open-source multi-modal large language model (MLLM) developed by ByteDance that unifies dense segmentation, visual understanding, and language-based reasoning across both images and videos. It merges the segmentation power of a state-of-the-art video segmentation model (based on SAM‑2) with the vision-language reasoning capabilities of a strong LLM backbone (derived from models like InternVL2.5 / Qwen-VL series), yielding a system that can answer questions about visual content, perform referring segmentation, and maintain temporal consistency across frames in video. ...
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  • 22
    Step1X-3D

    Step1X-3D

    High-Fidelity and Controllable Generation of Textured 3D Assets

    Step1X-3D is an open-source framework for generating high-fidelity textured 3D assets from scratch — both their geometry and surface textures — using modern generative AI techniques. It combines a hybrid architecture: a geometry generation stage using a VAE-DiT model to output a watertight 3D representation (e.g. TSDF surface), and a texture synthesis stage that conditions on geometry and optionally reference input (or prompts) to produce view-consistent textures using a diffusion-based texture module. ...
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  • 23
    Step-Audio 2

    Step-Audio 2

    Multi-modal large language model designed for audio understanding

    Step-Audio2 is an advanced, end-to-end multimodal large language model designed for high-fidelity audio understanding and natural speech conversation: unlike many pipelines that separate speech recognition, processing, and synthesis, Step-Audio2 processes raw audio, reasons about semantic and paralinguistic content (like emotion, speaker characteristics, non-verbal cues), and can generate contextually appropriate responses — including potentially generating or transforming audio output. It...
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  • 24
    Vidi2

    Vidi2

    Large Multimodal Models for Video Understanding and Editing

    ...Vidi targets applications like intelligent video editing, automated video search, content analysis, and editing assistance, enabling users to efficiently locate relevant segments and objects in hours-long footage. The system is built with open-source release in mind, giving developers access to model code, inference scripts, and evaluation pipelines so they can reproduce research results or integrate Vidi into their own video-processing workflows.
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  • 25
    Gemma in PyTorch

    Gemma in PyTorch

    The official PyTorch implementation of Google's Gemma models

    gemma_pytorch provides the official PyTorch reference for running and fine-tuning Google’s Gemma family of open models. It includes model definitions, configuration files, and loading utilities for multiple parameter scales, enabling quick evaluation and downstream adaptation. The repository demonstrates text generation pipelines, tokenizer setup, quantization paths, and adapters for low-rank or parameter-efficient fine-tuning. Example notebooks walk through instruction tuning and evaluation...
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