Showing 7220 open source projects for "web-based"

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    Ship Agents Faster

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  • 1
    screenshot-to-code

    screenshot-to-code

    Drop in a screenshot and convert it to clean code

    ...It uses modern vision-capable or code-generating models to infer layout structure, typography, and components, then outputs clean HTML/CSS (often Tailwind) or framework code. A web interface lets you upload images, tune options, and preview generated results, while a backend service orchestrates the model calls and post-processing. The tool focuses on practical developer outputs—semantic markup, reusable components, and readable classes—so the result is a starting point you can refine, not a throwaway demo. ...
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  • 2
    Dulwich

    Dulwich

    Pure-Python Git implementation

    Dulwich is a Python implementation of the Git file formats and protocols, which does not depend on Git itself. All functionality is available in pure Python. Optional C extensions can be built for improved performance. Dulwich takes its name from the area in London where the friendly Mr. and Mrs. Git once attended a cocktail party. Supported Python versions are Python 3.5 and later. Versions of Dulwich prior to 0.20 also supported Python 2.7. Supported platforms include Linux, Mac OS X and...
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  • 3
    ClearML

    ClearML

    Streamline your ML workflow

    ...The ClearML Python Package for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments and other workflows with ClearML powerful and versatile set of classes and methods. The ClearML Server storing experiment, model, and workflow data, and supports the Web UI experiment manager, and ML-Ops automation for reproducibility and tuning. It is available as a hosted service and open source for you to deploy your own ClearML Server. The ClearML Agent for ML-Ops orchestration, experiment and workflow reproducibility, and scalability.
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  • 4
    Graph Notebook

    Graph Notebook

    Library extending Jupyter notebooks to integrate with Apache TinkerPop

    The graph notebook provides an easy way to interact with graph databases using Jupyter notebooks. Using this open-source Python package, you can connect to any graph database that supports the Apache TinkerPop, openCypher or the RDF SPARQL graph models. These databases could be running locally on your desktop or in the cloud. Graph databases can be used to explore a variety of use cases including knowledge graphs and identity graphs. This project includes many examples of Jupyter notebooks....
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    MongoDB Atlas runs apps anywhere

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  • 5
    minted

    minted

    minted is a LaTeX package that provides syntax highlighting

    minted is a LaTeX package that enables advanced syntax highlighting of source code using the Pygments library. It supports customization via LaTeX and Python integration, allowing fine-grained control over code snippets in documents.
    Downloads: 0 This Week
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  • 6
    RealtimeSTT

    RealtimeSTT

    A robust, efficient, low-latency speech-to-text library

    RealtimeSTT is a Python-based realtime speech-to-text engine emphasizing low latency, wake-word detection, voice activity detection, and automatic speech segmentation. It provides asynchronous callbacks, nanosecond-precision timestamps, and CLI tools, suitable for building voice assistants, meeting transcribers, or live caption systems.
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  • 7
    Director

    Director

    AI video agents framework for next-gen video interactions

    Director is a video database management system designed to organize, search, and retrieve large collections of video content efficiently.
    Downloads: 0 This Week
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  • 8
    Code-Mode

    Code-Mode

    Plug-and-play library to enable agents to call MCP and UTCP tools

    ...Benchmarks in the README highlight improvements in latency and token cost for scenarios involving multiple tools, showing that code execution often outperforms traditional JSON-based function calling.
    Downloads: 1 This Week
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  • 9
    MetricFlow

    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. When a user or tool requests a metric (e.g., “monthly revenue by region”), MetricFlow generates optimized, warehouse-specific SQL to compute that metric, handling joins, filters, time grains, offsets, and other complexities under the hood. ...
    Downloads: 1 This Week
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  • Demo Series - Small Business Backup By Veeam Icon
    Demo Series - Small Business Backup By Veeam

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  • 10
    BlenderProc

    BlenderProc

    Blender pipeline for photorealistic training image generation

    A procedural Blender pipeline for photorealistic training image generation. BlenderProc has to be run inside the blender python environment, as only there we can access the blender API. Therefore, instead of running your script with the usual python interpreter, the command line interface of BlenderProc has to be used. In general, one run of your script first loads or constructs a 3D scene, then sets some camera poses inside this scene and renders different types of images (RGB, distance,...
    Downloads: 1 This Week
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  • 11
    Jittor

    Jittor

    Jittor is a high-performance deep learning framework

    Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators. The whole framework and meta-operators are compiled just in time. A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement learning, etc. ...
    Downloads: 1 This Week
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  • 12
    Miso TTS

    Miso TTS

    Miso TTS is an 8 billion, highly emotive text-to-speech model

    Miso TTS is an advanced 8-billion-parameter text-to-speech model developed by Miso Labs for generating highly expressive and natural-sounding conversational speech. Built on an RVQ Transformer architecture inspired by Sesame CSM, it combines a powerful Llama-based backbone with an autoregressive audio decoder to produce high-quality audio from text. The model supports both standard speech synthesis and voice-conditioned generation using optional audio prompts for voice cloning. Miso TTS generates Mimi audio codes and can leverage conversation history to create more contextually aware and realistic dialogue. ...
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  • 13
    GELab-Zero

    GELab-Zero

    GUI Exploration Lab. One of the best GUI agent solutions

    ...The idea is to let developers or users harness an AI agent that can simulate clicking, typing, reading UI elements, and interacting with apps in a human-like way via the GUI, which can enable tasks like automated testing, scriptable workflows, or even autonomous usage of GUI-based applications. Because GELab-Zero is fully open-source and doesn’t require external services, it offers privacy and control: everything runs locally under your control. The project provides a lightweight base model (4B parameters in its public release) that can run on modest hardware (depending on quantization), making it more accessible than many large-scale AI solutions.
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  • 14
    MiniMax-01

    MiniMax-01

    Large-language-model & vision-language-model based on Linear Attention

    MiniMax-01 is the official repository for two flagship models: MiniMax-Text-01, a long-context language model, and MiniMax-VL-01, a vision-language model built on top of it. MiniMax-Text-01 uses a hybrid attention architecture that blends Lightning Attention, standard softmax attention, and Mixture-of-Experts (MoE) routing to achieve both high throughput and long-context reasoning. It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel...
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  • 15
    Darts

    Darts

    A python library for easy manipulation and forecasting of time series

    ...The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models can be trained on potentially large datasets containing multiple time series, and some of the models offer a rich support for probabilistic forecasting. We recommend to first setup a clean Python environment for your project with at least Python 3.7 using your favorite tool (conda, venv, virtualenv with or without virtualenvwrapper).
    Downloads: 0 This Week
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  • 16
    MCDReforged

    MCDReforged

    MCDaemon, a python tool to control your Minecraft server

    A rewritten version of MCDaemon, a Python tool to control your Minecraft server. A Minecraft server management tool allowing script-based automation of Minecraft tasks.
    Downloads: 0 This Week
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  • 17
    nbmake

    nbmake

    Pytest plugin for testing notebooks

    Pytest plugin for testing and releasing notebook documentation. To raise the quality of scientific material through better automation. Research/Machine Learning Software Engineers who maintain packages/teaching materials with documentation written in notebooks.
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  • 18
    Megatron

    Megatron

    Ongoing research training transformer models at scale

    ...This repository is for ongoing research on training large transformer language models at scale. We developed efficient, model-parallel (tensor, sequence, and pipeline), and multi-node pre-training of transformer based models such as GPT, BERT, and T5 using mixed precision. Megatron is also used in NeMo Megatron, a framework to help enterprises overcome the challenges of building and training sophisticated natural language processing models with billions and trillions of parameters. Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
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  • 19
    Large Concept Model

    Large Concept Model

    Language modeling in a sentence representation space

    Large Concept Model is a research codebase centered on concept-centric representation learning at scale, aiming to capture shared structure across many categories and modalities. It organizes training around concepts (rather than just raw labels), encouraging models to understand attributes, relations, and compositional structure that transfer across tasks. The repository provides training loops, data tooling, and evaluation routines to learn and probe these concept embeddings, typically...
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  • 20
    PyTorch Geometric Temporal

    PyTorch Geometric Temporal

    Spatiotemporal Signal Processing with Neural Machine Learning Models

    ...The framework naturally provides GPU support. It also comes with a number of benchmark datasets from the epidemiological forecasting, sharing economy, energy production and web traffic management domains. Finally, you can also create your own datasets. The package interfaces well with Pytorch Lightning which allows training on CPUs, single and multiple GPUs out-of-the-box. PyTorch Geometric Temporal makes implementing Dynamic and Temporal Graph Neural Networks quite easy - see the accompanying tutorial. ...
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  • 21
    GLM-4.5V

    GLM-4.5V

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

    ...It embodies the design philosophy of mixing visual and textual modalities into a unified model capable of general-purpose reasoning, content understanding, and generation, while already supporting a wide variety of tasks: from image captioning and visual question answering to content recognition, GUI-based agents, video understanding, and long-document interpretation. GLM-4.5V emerged from a training framework that leverages scalable reinforcement learning (with curriculum sampling) to boost performance across tasks ranging from STEM problem solving to long-context reasoning, giving it broad applicability beyond narrow benchmarks. ...
    Downloads: 1 This Week
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  • 22
    Step-Audio-EditX

    Step-Audio-EditX

    LLM-based Reinforcement Learning audio edit model

    Step-Audio-EditX is an open-source, 3 billion-parameter audio model from StepFun AI designed to make expressive and precise editing of speech and audio as easy as text editing. Rather than treating audio editing as low-level waveform manipulation, this model converts speech into a sequence of discrete “audio tokens” (via a dual-codebook tokenizer) — combining a linguistic token stream and a semantic (prosody/emotion/style) token stream — thereby abstracting audio editing into high-level...
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  • 23
    nano-graphrag

    nano-graphrag

    A simple, easy-to-hack GraphRAG implementation

    nano-graphrag is a lightweight implementation of the GraphRAG approach designed to simplify experimentation with graph-based retrieval-augmented generation systems. GraphRAG expands traditional RAG pipelines by constructing knowledge graphs from documents and using relationships between entities to improve the quality and reasoning of AI responses. The nano-GraphRAG project focuses on reducing complexity by providing a compact and readable codebase that preserves the core functionality of graph-based retrieval systems while remaining easy to modify and extend. ...
    Downloads: 2 This Week
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  • 24
    NErlNet

    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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  • 25
    AIHawk

    AIHawk

    AIHawk aims to easy job hunt process by automating job applications

    AIHawk is an AGPL‑licensed AI agent focused on automating job applications. It scrapes job listings from corporate sites (or LinkedIn in forks) and uses LLMs to generate tailored applications, streamlining the process across multiple platforms—dubbed “revolutionary” by mainstream tech outlets.
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