6441 projects for "python-snap7" with 1 filter applied:

  • Forever Free Full-Stack Observability | Grafana Cloud Icon
    Forever Free Full-Stack Observability | Grafana Cloud

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  • 1
    MediaManager

    MediaManager

    A modern selfhosted media management system for your media library

    ...It is designed for ease of deployment with Docker, supports standardized metadata sources such as TMDB and TVDB, and integrates OAuth/OIDC for secure authentication. Users can browse, search, and manage their media with a responsive web frontend while developers benefit from a clean codebase that uses Python and modern web technologies. Its holistic approach toward acquisition, tracking, and library maintenance reduces duplication, improves media discovery workflows, and simplifies long-term management of large media collections.
    Downloads: 0 This Week
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  • 2
    Habit Tracker

    Habit Tracker

    Habit Tracker for the AI Coding Workshop

    Habit Tracker is a personal habit-tracking web application designed to help users build and maintain daily habits through intuitive UI and analytics that visualize progress over time. It runs locally with a FastAPI backend (Python) and a React frontend, storing all data in a lightweight SQLite database so there’s no need for user accounts or cloud storage, which keeps habit data fully private and self-contained. The app provides streak tracking and completion rates for each habit, giving users feedback on consistency and motivation by showing how often habits are completed and where they may be lagging. ...
    Downloads: 0 This Week
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  • 3
    Starlark in Go

    Starlark in Go

    Starlark in Go: the Starlark configuration language, implemented in Go

    ...Unlike Python, Starlark supports parallel execution across multiple threads and maintains deterministic behavior, making it suitable for scalable and reproducible workloads. It offers familiar syntax features such as dictionaries, lists, and first-class functions with lexical scoping.
    Downloads: 0 This Week
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  • 4
    EPLB

    EPLB

    Expert Parallelism Load Balancer

    EPLB is DeepSeek’s open implementation of a load balancing algorithm designed for expert parallelism (EP) settings in MoE architectures. In EP, different “experts” are mapped to different GPUs or nodes, so load imbalance becomes a performance bottleneck if certain experts are invoked much more often. EPLB solves this by duplicating heavily used experts (redundancy) and then placing those duplicates across GPUs to even out computational load. It uses policies like hierarchical load balancing...
    Downloads: 0 This Week
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  • Go From AI Idea to AI App Fast Icon
    Go From AI Idea to AI App Fast

    One platform to build, fine-tune, and deploy ML models. No MLOps team required.

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  • 5
    DualPipe

    DualPipe

    A bidirectional pipeline parallelism algorithm

    DualPipe is a bidirectional pipeline parallelism algorithm open-sourced by DeepSeek, introduced in their DeepSeek-V3 technical framework. The main goal of DualPipe is to maximize overlap between computation and communication phases during distributed training, thus reducing idle GPU time (i.e. “pipeline bubbles”) and improving cluster efficiency. Traditional pipeline parallelism methods (e.g. 1F1B or staggered pipelining) leave gaps because forward and backward phases can’t fully overlap...
    Downloads: 0 This Week
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  • 6
    Phi-3-MLX

    Phi-3-MLX

    Phi-3.5 for Mac: Locally-run Vision and Language Models

    Phi-3-Vision-MLX is an Apple MLX (machine learning on Apple silicon) implementation of Phi-3 Vision, a lightweight multi-modal model designed for vision and language tasks. It focuses on running vision-language AI efficiently on Apple hardware like M1 and M2 chips.
    Downloads: 1 This Week
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  • 7
    Superduper

    Superduper

    Superduper: Integrate AI models and machine learning workflows

    Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. ...
    Downloads: 0 This Week
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  • 8
    RL Games

    RL Games

    RL implementations

    rl_games is a high-performance reinforcement learning framework optimized for GPU-based training, particularly in environments like robotics and continuous control tasks. It supports advanced algorithms and is built with PyTorch.
    Downloads: 0 This Week
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  • 9
    DI-engine

    DI-engine

    OpenDILab Decision AI Engine

    DI-engine is a unified reinforcement learning (RL) platform for reproducible and scalable RL research. It offers modular pipelines for various RL algorithms, with an emphasis on production-level training and evaluation.
    Downloads: 0 This Week
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  • Secure File Transfer for Windows with Cerberus by Redwood Icon
    Secure File Transfer for Windows with Cerberus by Redwood

    Protect and share files over FTP/S, SFTP, HTTPS and SCP with the #1 rated Windows file transfer server.

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  • 10
    Parsera

    Parsera

    Lightweight library for scraping web-sites with LLMs

    Scrape data from any website with only a link and column descriptions. Parsera is a tool designed to scrape web content, specifically handling poorly structured or messy websites.
    Downloads: 0 This Week
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  • 11
    Jupyter Notebook Tools for Sphinx

    Jupyter Notebook Tools for Sphinx

    Sphinx source parser for Jupyter notebooks

    nbsphinx is a Sphinx extension that provides a source parser for *.ipynb files. Custom Sphinx directives are used to show Jupyter Notebook code cells (and of course their results) in both HTML and LaTeX output. Un-evaluated notebooks – i.e. notebooks without stored output cells – will be automatically executed during the Sphinx build process.
    Downloads: 0 This Week
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  • 12
    AI Marketing Skills

    AI Marketing Skills

    Open-source AI marketing skills for Claude Code

    AI Marketing Skills is a comprehensive open-source framework designed to transform AI agents into fully operational marketing and sales systems by equipping them with structured, reusable “skills” that automate real business workflows. Instead of simple prompts, the project provides complete operational modules that include scripts, scoring systems, and decision-making logic, allowing AI tools like Claude Code to execute complex marketing tasks end-to-end. The system is organized into...
    Downloads: 3 This Week
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  • 13
    Spring AI Alibaba Examples

    Spring AI Alibaba Examples

    Spring AI Alibaba examples for building and testing AI apps

    Spring AI Alibaba Examples provides a collection of example projects that demonstrate how to use Spring AI and Spring AI Alibaba across different scenarios, from basic setups to more advanced AI applications. It is designed to help developers understand core concepts, explore practical implementations, and follow best practices when building AI-powered systems using the Spring ecosystem. Each module focuses on a specific use case such as chat, image processing, audio handling, graph...
    Downloads: 3 This Week
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  • 14
    BackAnt CLI

    BackAnt CLI

    Let your AI agent create clean, easy to maintain flask backends

    BackAnt CLI is an AI-native backend scaffolding tool designed to generate production-ready Flask APIs from a JSON specification or a small set of CLI commands. Its main goal is to reduce the repetitive work involved in setting up layered backend projects by generating key application components automatically rather than forcing developers to assemble them by hand. The tool creates a structured backend architecture that includes routes, services, repositories, models, startup files, Docker...
    Downloads: 3 This Week
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  • 15
    MetaVoice-1B

    MetaVoice-1B

    Foundational model for human-like, expressive TTS

    MetaVoice — in the form of its source repository “metavoice-src” — is a large-scale text-to-speech (TTS) model. Specifically, the base model (MetaVoice-1B) uses around 1.2 billion parameters and has been trained on a massive dataset — reportedly around 100,000 hours of speech data. The goal is to provide human-like, expressive, and flexible TTS: able to generate natural-sounding speech that can handle diverse inputs and likely generalize over voice styles, intonation, prosody, and perhaps...
    Downloads: 3 This Week
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  • 16
    DeepSeek Coder

    DeepSeek Coder

    DeepSeek Coder: Let the Code Write Itself

    DeepSeek-Coder is a series of code-specialized language models designed to generate, complete, and infill code (and mixed code + natural language) with high fluency in both English and Chinese. The models are trained from scratch on a massive corpus (~2 trillion tokens), of which about 87% is code and 13% is natural language. This dataset covers project-level code structure (not just line-by-line snippets), using a large context window (e.g. 16K) and a secondary fill-in-the-blank objective...
    Downloads: 3 This Week
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  • 17
    LeWorldModel

    LeWorldModel

    Official code base for LeWorldModel: Stable End-to-End Joint-Embedding

    LeWorldModel is a minimalist tiling window manager designed for the X11 windowing system, focusing on simplicity, performance, and efficient use of screen space. It provides automatic window tiling behavior, organizing application windows into structured layouts without requiring manual resizing or positioning. The project emphasizes a lightweight design, minimizing resource usage while maintaining responsiveness and stability. It is highly configurable through source code or configuration...
    Downloads: 1 This Week
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  • 18
    Watermark-Removal

    Watermark-Removal

    Machine learning image inpainting task that removes watermarks

    Watermark-Removal repository is a machine learning project focused on removing visible watermarks from digital images using deep learning and image inpainting techniques. The system analyzes an image containing a watermark and attempts to reconstruct the underlying visual content so that the watermark is removed while preserving the original appearance of the image. The project uses neural network models inspired by research in contextual attention and gated convolution, which are methods...
    Downloads: 1 This Week
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  • 19
    cracking-the-data-science-interview

    cracking-the-data-science-interview

    A Collection of Cheatsheets, Books, Questions, and Portfolio

    Cracking the Data Science Interview is an open educational repository that collects study materials, resources, and reference links for preparing for data science interviews. The project organizes content across many fundamental areas of data science, including statistics, probability, SQL, machine learning, and deep learning. It includes cheat sheets that summarize important technical concepts commonly discussed during technical interviews. The repository also provides links to recommended...
    Downloads: 1 This Week
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  • 20
    MathModelAgent

    MathModelAgent

    An Agent Designed for Mathematical Modeling

    MathModelAgent is an AI agent system designed specifically for assisting with mathematical modeling tasks and academic problem solving. The platform automates the process of analyzing mathematical problems, constructing models, generating code for simulations or computations, and producing a complete research-style report. The project uses a multi-agent architecture where different specialized agents handle tasks such as problem interpretation, modeling design, programming implementation,...
    Downloads: 1 This Week
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  • 21
    Karpathy

    Karpathy

    An agentic Machine Learning Engineer

    karpathy is an experimental agentic machine learning engineer framework designed to automate many aspects of the ML development workflow. The project sets up a sandboxed environment where an AI agent can access datasets, run experiments, and generate machine learning artifacts through a web interface. Its startup script automatically prepares the environment by creating a sandbox directory, installing key ML libraries, and launching the agent interface. The system is tightly integrated with...
    Downloads: 1 This Week
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  • 22
    claude-code-best-practice

    claude-code-best-practice

    Practice made claude perfect

    claude-code-best-practice is a structured knowledge repository that documents advanced workflows, architectural patterns, and optimization strategies for developers using Claude Code in agentic development environments. Rather than being a traditional software library, the project functions as a living playbook that demonstrates how to compose skills, agents, memory files, and rules into maintainable AI-assisted coding systems. The repository emphasizes modularity and progressive disclosure,...
    Downloads: 1 This Week
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  • 23
    Auto-Deep-Research

    Auto-Deep-Research

    Your Fully-Automated Personal AI Assistant

    Auto-Deep-Research is a system designed to fully automate deep research workflows using language models, retrieval, planning, and multi-stage reasoning to produce structured research artifacts such as surveys, benchmarks, reports, and even prototypes without heavy human intervention. Users provide a research topic or multifaceted goal, and the system autonomously breaks the objective down into subtasks like literature collection, critical summarization, cross-comparison, citation extraction,...
    Downloads: 1 This Week
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  • 24
    GitHub520

    GitHub520

    Community-maintained approach to improving access to GitHub services

    GitHub520 is a community-maintained approach to improving access to GitHub services from regions with network friction by leveraging host mappings. The repository provides a regularly updated list of domain-to-IP entries meant to be appended to a system’s hosts file so certain GitHub endpoints resolve faster or more reliably. It includes scripts or guidance to automate updates, reducing the need for manual lookups when IPs change. The project’s goal is pragmatic: improve developer...
    Downloads: 1 This Week
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  • 25
    The Hypersim Dataset

    The Hypersim Dataset

    Photorealistic Synthetic Dataset for Holistic Indoor Scene

    Hypersim is a large-scale, photorealistic synthetic dataset and tooling suite for indoor scene understanding research. It provides richly annotated renderings—RGB, depth, surface normals, instance and semantic segmentations, and material/lighting metadata—produced from high-fidelity virtual environments. The dataset spans diverse furniture layouts, room types, and camera trajectories, enabling robust training for geometry, segmentation, and SLAM-adjacent tasks. Rendering pipelines and...
    Downloads: 1 This Week
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