Search Results for "docker-compose" - Page 11
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Showing 316 open source projects for "docker-compose"
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manage-fastapi
CLI tool for FastAPI. Generating new FastAPI projects & boilerplates
manage-fastapi Project generator and manager for FastAPI. -
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Spleeter
Deezer source separation library including pretrained models
...We designed Spleeter so you can use it straight from command line as well as directly in your own development pipeline as a Python library. It can be installed with Conda, with pip or be used with Docker. -
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Aquila DB
An easy to use Neural Search Engine
Aquila DB is a Neural search engine. In other words, it is a database to index Latent Vectors generated by ML models along with JSON Metadata to perform k-NN retrieval. It is dead simple to set up, language-agnostic, and drop in addition to your Machine Learning Applications. Aquila DB, as of current features is a ready solution for Machine Learning engineers and Data scientists to build Neural Information Retrieval applications out of the box with minimal dependencies. -
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SageMaker TensorFlow Serving Container
A TensorFlow Serving solution for use in SageMaker
...You can also run your container locally in Docker to test different models and input inference requests by hand. -
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galacteek
Multi-platform browser for the distributed web
...After opening/mounting the DMG image, hold Control and click on the galacteek icon, and select Open and accept. You probably need to allow the system to install applications from anywhere in the security settings. Docker images are available. They run the full GUI inside a virtual Xorg server (using Xvfb). A VNC server runs on TCP port 5900 of the container, just use a regular VNC client to access the interface. The password to access the VNC service is printed to the console when starting the container. -
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Pytago
A source-to-source transpiler for Python to Go translation
pytago is a source-to-source transpiler that converts some Python into human-readable Go. It enables developers to translate Python codebases into Go, facilitating migration or interoperability between the two languages. -
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ML workspace
All-in-one web-based IDE specialized for machine learning
...This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard) perfectly configured, optimized, and integrated. Usable as remote kernel (Jupyter) or remote machine (VS Code) via SSH. Easy to deploy on Mac, Linux, and Windows via Docker. Jupyter, JupyterLab, and Visual Studio Code web-based IDEs.By default, the workspace container has no resource constraints and can use as much of a given resource as the host’s kernel scheduler allows. -
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Opyrator
Turns your machine learning code into microservices with web API
Instantly turn your Python functions into production-ready microservices. Deploy and access your services via HTTP API or interactive UI. Seamlessly export your services into portable, shareable, and executable files or Docker images. Opyrator builds on open standards - OpenAPI, JSON Schema, and Python type hints - and is powered by FastAPI, Streamlit, and Pydantic. It cuts out all the pain for productizing and sharing your Python code - or anything you can wrap into a single Python function. An Opyrator-compatible function is required to have an input parameter and return value based on Pydantic models. ... -
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Zebrunner Community Edition
Test Automation Management Tool
...It allows you to run various kinds of tests and gain successive levels of confidence in the code quality. Zebrunner CE is integrated by default with Carina open-source TestNG framework and uses Jenkins as a CI Tool. It is built on top of popular docker solutions and includes Postgres database, Zebrunner Reporting, Jenkins Master/Slaves Nodes, Selenium Hub, Mobile Device Farm (MCloud), SonarQube, etc. All components are deployed under NGINX WebServer which can be configured in a fully secured environment. The Zebrunner CE repository: https://github.com/zebrunner/zebrunner -
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Inventory Hunter
Get notified as soon as your next CPU, GPU, or console is in stock
...It was originally created to help the maintainer get notified when an RTX 3070 became available. The project is designed to run continuously on a Raspberry Pi, always-on PC, Mac, or Docker-capable environment. It uses configuration files for supported retailer and product checks, then sends alerts through services such as Discord, Slack, Telegram, or email. The tool is focused on notifications rather than being presented as an automated purchasing system. It is most appropriate for personal inventory monitoring where users want quick alerts without manually refreshing store pages. -
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Nautilus Core
Automation tools for deploying blockchain networks
Naultilus Core is a tool to automate running Tezos Nodes. It allows customization of the most important node features, and easily running multiple nodes, along with different integrations to simplfy node interactions. With each Node in Archive mode, you can also start an instance of Conseil and Arronax. Nautilus Core is only supported in macOS and Linux. Running Tezos Nodes (particularly Archive Nodes) can take massive amounts of storage when fully synced (~300 GB). 16GB of memory is... -
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FastAPI + React
Cookiecutter Template for FastAPI
FastAPI-React is a cookiecutter template that combines FastAPI and React to create full-stack applications. It integrates PostgreSQL, SQLAlchemy, and Docker to provide a comprehensive development environment. -
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py-kms
KMS Server Emulator written in Python
...The software supports multiple versions of the KMS protocol, enabling compatibility with a wide range of Windows and Office releases. It can be deployed in various environments, including standalone systems, Docker containers, and service managers like systemd, making it flexible for testing and development scenarios. The emulator includes features such as logging, configurable network parameters, and persistent storage using SQLite. While it is often used for testing activation workflows, it also serves as a practical example of protocol emulation and reverse engineering in software systems. -
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BudgetML
Deploy a ML inference service on a budget in 10 lines of code
...We built BudgetML because it's hard to find a simple way to get a model in production fast and cheaply. Deploying from scratch involves learning too many different concepts like SSL certificate generation, Docker, REST, Uvicorn/Gunicorn, backend servers etc., that are simply not within the scope of a typical data scientist. BudgetML is our answer to this challenge. It is supposed to be fast, easy, and developer-friendly. It is by no means meant to be used in a full-fledged production-ready setup. It is simply a means to get a server up and running as fast as possible with the lowest costs possible. -
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dumb-init
A minimal init system for Linux containers
...This helps to avoid special kernel behavior applied to PID 1, while also handling regular responsibilities of the init system (like reaping orphaned zombie processes). dumb-init is a simple process supervisor and init system designed to run as PID 1 inside minimal container environments (such as Docker). It is deployed as a small, statically-linked binary written in C. -
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PlaystoreDownloader
A command line tool to download Android applications
...After an initial (one-time) configuration, applications can be downloaded by specifying their package name. There are two ways of getting a working copy of PlaystoreDownloader on your own computer: either by using Docker or by using directly the source code in a Python 3 environment. In both cases, the first thing to do is to get a local copy of this repository, so open up a terminal in the directory where you want to save the project and clone the repository. Apart from valid Google Play Store credentials, the only requirement of this project is a working Python 3 (at least 3.7) installation and pipenv (for dependency management). -
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Atgen A2 Automation
Atgen A2 is a radically simple Workload Automation & Scheduling tool.
Atgen A2 is a radically simple IT automation solution that automates application builds, continuous testing, data parsing & processing, report generation, batch processing, job scheduling, and many other IT needs. Avoid running repetitive batch jobs and managing access to deploy and update your applications — automate in a language that approaches plain English, using SSH or WinRM, with no agents to install on remote systems. https://www.atgensoft.com/ You can install a released version... -
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BigchainDB Server
Meet BigchainDB. The blockchain database
BigchainDB is the blockchain database. This repository is for the BigchainDB Server. Running and testing the latest version of the BigchainDB Server is easy. Make sure you have a recent version of Docker Compose installed. -
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Libra
Ergonomic machine learning for everyone
An ergonomic machine learning library for non-technical users. Save time. Blaze through ML. -
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SageMaker MXNet Training Toolkit
Toolkit for running MXNet training scripts on SageMaker
...You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training. If you have your own algorithms built into SageMaker compatible Docker containers, you can train and host models using these as well. -
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Nebula-Python-SDK
A python SDK for managing Nebula container orchestrator
...First, get NebulaPythonSDK onto your machine, now use it in your code. Nebula container orchestrator aims to help devs and ops treat IoT devices just like distributed Dockerized apps. It aim is to act as Docker orchestrator for IoT devices as well as for distributed services such as CDN or edge computing that can span thousands (possibly even millions) of devices worldwide and it does it all while being open-source and completely free. Nebula imposes no limits on the scale of the cluster, each component in it is designed to scale out to allow millions of workers to be managed by it. ... -
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Makani
Makani was developed a commercial-scale airborne wind turbine
Makani was an ambitious Google X project that sought to harness wind energy using airborne wind turbines — autonomous kites capable of generating power while flying in crosswind patterns. This open-source repository contains the complete software stack that powered Makani’s research and flight systems, including the flight simulator, autopilot controller, avionics firmware, visualization tools, and ground control software. The software enables simulation, control, and analysis of the Makani... -
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repo2docker GitHub Action
A GitHub action to build data science environment images
Trigger repo2docker to build a Jupyter enabled Docker image from your GitHub repository and push this image to a Docker registry of your choice. This will automatically attempt to build an environment from configuration files found in your repository. Images generated by this action are automatically tagged with both latest and <SHA> corresponding to the relevant commit SHA on GitHub. -
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SageMaker Containers
Create SageMaker-compatible Docker containers
...You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to any Docker container, making it compatible with SageMaker for training models. If you use a prebuilt SageMaker Docker image for training, this library may already be included. ... -
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MMdnn
Tools to help users inter-operate among deep learning frameworks
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks,...
