Search Results for "open source" - Page 67
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Showing 16662 open source projects for "open source"
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Loggifly
Get Alerts from your Docker Container Logs
LoggiFly is a lightweight, open-source monitoring tool designed to watch Docker container logs in real time and trigger alerts, notifications, or automated actions based on predefined keywords or regular expression patterns. Instead of manually scanning logs for issues or relying solely on centralized monitoring stacks, LoggiFly proactively inspects streams of container output and notifies users through services like Ntfy, Slack, Discord, Telegram, or webhooks when significant events occur. ... -
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video2robot
End-to-end pipeline converting generative videos
video2robot is an end-to-end open-source pipeline that converts generative video or prompt-driven motion content into executable humanoid robot motion sequences, enabling researchers and developers to go from high-level action descriptions or videos to robot-ready motion data. The pipeline supports both prompt-to-video generation using models like Veo/Sora and video upload processing, followed by human pose extraction through a 3D pose model and retargeting of that motion to robot joints using a general motion retargeting system. ... -
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OpenTinker
OpenTinker is an RL-as-a-Service infrastructure for foundation models
OpenTinker is an open-source Reinforcement Learning-as-a-Service (RLaaS) infrastructure intended to democratize reinforcement learning for large language model (LLM) agents. Traditional RL setups can be monolithic and difficult to configure, but OpenTinker separates concerns across agent definition, environment interaction, and execution, which lets developers focus on defining the logic of agents and environments separately from how training and inference are run. -
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DFlash
Block Diffusion for Ultra-Fast Speculative Decoding
DFlash is an open-source framework for ultra-fast speculative decoding using a lightweight block diffusion model to draft text in parallel with a target large language model, dramatically improving inference speed without sacrificing generation quality. It acts as a “drafter” that proposes likely continuations which the main model then verifies, enabling significant throughput gains compared to traditional autoregressive decoding methods that generate token by token. -
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MiniMind-V
"Big Model" trains a visual multimodal VLM with 26M parameters
MiniMind-V is an experimental open-source project that aims to train a very small multimodal vision–language model (VLM) from scratch with extremely low compute and cost, making research and experimentation accessible to more people. The repository showcases training workflows and code designed to produce a 26-million parameter model—including both image and text capabilities—using minimal resources in very little time, reflecting a trend toward democratizing AI research. ... -
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DreamO
A Unified Framework for Image Customization
DreamO is a unified, open-source framework from ByteDance for advanced image customization and generation that consolidates multiple “image manipulation” tasks into a single system, rather than requiring separate specialized models. Built on a diffusion-transformer (DiT) backbone, it supports a diverse set of tasks — including identity preservation, virtual “try-on” (e.g. clothing, accessories), style transfer, IP adaptation (objects/characters), and layout/condition-aware customizations — all handled within the same unified architecture. ... -
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InfiniteYou
Flexible Photo Recrafting While Preserving Your Identity
InfiniteYou is an open-source image-generation and “identity-preserving image editing / generation” framework from ByteDance, designed to generate high-fidelity images that preserve a subject’s identity while allowing flexible editing or re-creation according to textual prompts. Using an architecture built around diffusion transformers (DiTs), InfiniteYou introduces a component called InfuseNet that injects identity features derived from reference images into the generation process — via residual connections — so that the output matches the person’s identity closely, without sacrificing visual quality or text-image alignment. ... -
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Matrix
Multi-Agent daTa geneRation Infra and eXperimentation framework
...That design makes Matrix particularly well-suited for large-batch inference, model benchmarking, data curation, augmentation, or generation — whether for language, code, dialogue, or multimodal tasks. It supports both open-source LLMs and proprietary models (via integration with model backends), and works with containerized or sandboxed environments for safe tool execution or external code runs. -
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Evennia
Python MUD/MUX/MUSH/MU* development system
Evennia is a mature, open-source framework written in Python — specifically designed to build text-based, online multiplayer games such as MUDs, MUCKs, MUSHes, MUXes, and other “MU-style” virtual worlds. Rather than prescribing a rigid game structure, Evennia gives you a bare-bones but powerful foundation: default systems handle networking, database/storage, server management, user accounts, characters, rooms, items, chat channels, and basic commands — but you define the gameplay rules, content, and game logic yourself in pure Python modules. ... -
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MetricFlow
MetricFlow allows you to define, build, and maintain metrics in code
MetricFlow is an open-source semantic layer engine designed to help organizations define, manage, and query business metrics in a consistent, governed way. It works alongside a data stack—typically built with dbt—and allows you to express metrics as YAML‐based definitions tied to semantic models and dimension tables, rather than embedding logic ad-hoc across many dashboards or scripts. -
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Meridian
Meridian is an MMM framework
Meridian is a comprehensive, open source marketing mix modeling (MMM) framework developed by Google to help advertisers analyze and optimize the impact of their marketing investments. Built on Bayesian causal inference principles, Meridian enables organizations to evaluate how different marketing channels influence key performance indicators (KPIs) such as revenue or conversions while accounting for external factors like seasonality or economic trends. -
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AReal
Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible
AReaL is an open source, fully asynchronous reinforcement learning training system. AReal is designed for large reasoning and agentic models. It works with models that perform reasoning over multiple steps, agents interacting with environments. It is developed by the AReaL Team at Ant Group (inclusionAI) and builds upon the ReaLHF project. Release of training details, datasets, and models for reproducibility. -
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NVIDIA Isaac Sim
NVIDIA Isaac Sim is an open-source application on NVIDIA Omniverse
NVIDIA Isaac Sim is a high-fidelity robotics simulation platform built on NVIDIA Omniverse to develop, test, and validate AI-driven robots in physically accurate virtual environments. It supports a wide array of robotics formats (URDF, MJCF, CAD), includes GPU-accelerated physics, and features immersive RTX rendering and multisensory simulation. Realistic physics via GPU-accelerated engines and RTX ray tracing. Multi-sensor simulation (RGB-D cameras, Lidar, Radar, IMU, contact sensors).... -
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latexcv
A collection of cv and resume templates written in LaTeX
A collection of user-friendly LaTeX CV and résumé templates (packaged within the R Markdown vitae ecosystem), offering simple themes and templates for creating professional CVs without heavy TeX coding. Supports multiple display themes such as classic, modern, sidebar layouts. -
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NErlNet
Nerlnet is a framework for research and development
NErlNet is a research-grade framework for distributed machine learning over IoT and edge devices. Built with Erlang (Cowboy HTTP), OpenNN, and Python (Flask), it enables simulation of clusters on a single machine or real deployment across heterogeneous devices. -
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pip-tools
A set of tools to keep your pinned Python dependencies fresh
pip-tools enhances Python dependency management by providing pip-compile and pip-sync commands. It transforms human-friendly requirements.in into fully pinned requirements.txt, ensuring reproducible environments. It also resolves transitive dependencies and synchronizes your environment with pinned versions. Widely used in both development and CI workflows, it boosts reliability and eliminates drift in deployed setups. -
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Helium
Lighter web automation with Python
Helium is a Python library built on top of Selenium to make browser automation more intuitive and human-friendly. It replaces verbose boilerplate code with natural language-like API calls such as click("Login") or write("hello", into="Name"). Helium manages browser setup, waits, and teardown, enabling quick development of scripts for testing, scraping, or task automation without requiring deep Selenium knowledge. -
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DrissionPage
Python based web automation tool. Powerful and elegant
DrissionPage is a Python-based automation framework that blends the capabilities of Selenium for browser automation with Requests-HTML for fast, headless web data extraction. It enables seamless switching between browser-controlled and headless HTTP sessions within the same interface. Ideal for web scraping, testing, and automation, DrissionPage is lightweight and highly efficient, offering more flexibility than standard Selenium or Requests usage alone. -
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Dask
Parallel computing with task scheduling
Dask is a Python library for parallel and distributed computing, designed to scale analytics workloads from single machines to large clusters. It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines. -
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Pony ORM
Pony Object Relational Mapper
Pony ORM is a Python ORM that enables developers to write database queries using generator expressions and Pythonic syntax, making code more readable and intuitive. It automatically translates Python expressions into SQL and supports multiple databases including SQLite, MySQL, PostgreSQL, and Oracle. With an emphasis on simplicity and maintainability, Pony ORM is suitable for both small projects and complex applications. -
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MCP Server Qdrant
An official Qdrant Model Context Protocol (MCP) server implementation
The Qdrant MCP Server is an official Model Context Protocol server that integrates with the Qdrant vector search engine. It acts as a semantic memory layer, allowing for the storage and retrieval of vector-based data, enhancing the capabilities of AI applications requiring semantic search functionalities. -
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ADX MCP Server
A Model Context Protocol (MCP) server that enables AI assistants
The Azure Data Explorer MCP Server is a Model Context Protocol (MCP) server that enables AI assistants to query and analyze Azure Data Explorer databases through standardized interfaces. It allows the execution of Kusto Query Language (KQL) queries and exploration of data within Azure Data Explorer clusters. -
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Dataherald
Interact with your SQL database, Natural Language to SQL using LLMs
Dataherald is a platform that allows users to query structured databases using natural language, automatically converting plain English into SQL. It is designed to enable real-time, self-service analytics without needing technical knowledge of databases, making business data easily accessible to non-technical users. Dataherald focuses on speed, accuracy, and scalability for enterprise settings. -
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LazyLLM
Easiest and laziest way for building multi-agent LLMs applications
LazyLLM is an optimized, lightweight LLM server designed for easy and fast deployment of large language models. It is fully compatible with the OpenAI API specification, enabling developers to integrate their own models into applications that normally rely on OpenAI’s endpoints. LazyLLM emphasizes low resource usage and fast inference while supporting multiple models. -
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Liger Kernel
Efficient Triton Kernels for LLM Training
Liger Kernel is a unified kernel developed by LinkedIn to streamline data science and machine learning workflows across different languages and tools. It provides a consistent interface for running code in various languages (such as Python, R, SQL) within a single Jupyter-like environment, enhancing productivity and collaboration for data scientists working in mixed-language projects.
