Search Results for "docker-compose" - Page 11
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Showing 328 open source projects for "docker-compose"
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1
G-Diffuser Bot
Discord bot and Interface for Stable Diffusion
The first release of the all-in-one installer version of G-Diffuser is here. This release no longer requires the installation of WSL or Docker and has a systray icon to keep track of and launch G-Diffuser components. The infinite zoom scripts have been updated with some improvements, notably a new compositer script that is hundreds of times faster than before. The first release of the all-in-one installer is here. It notably features much easier "one-click" installation and updating, as well as a systray icon to keep track of g-diffuser programs and the server while it is running. ... -
2
ECS Deploy
Powerful CLI tool to simplify Amazon ECS deployments, rollbacks, etc.
ecs-deploy simplifies deployments on Amazon ECS by providing a convenience CLI tool for complex actions, which are executed pretty often. Support for complex task definitions (e.g. multiple containers & task role), easily redeploy the current task definition (including docker pull of eventually updated images), deploy new versions/tags or all containers or just a single container in your task definition, scale up or down by adjusting the desired count of running tasks, add or adjust containers environment variables. Run one-off tasks from the CLI, automatically monitor deployments in New Relic. -
3
OmicSelector
Feature selection and deep learning modeling for omic biomarker study
OmicSelector is an environment, Docker-based web application, and R package for biomarker signature selection (feature selection) from high-throughput experiments and others. It was initially developed for miRNA-seq (small RNA, smRNA-seq; hence the name was miRNAselector), RNA-seq and qPCR, but can be applied for every problem where numeric features should be selected to counteract overfitting of the models. -
4
Pity
API test platform
Pity is a powerful and user-friendly open-source API test platform that supports automated test case creation, test scheduling, and result visualization. Designed for developers and QA teams, it provides a web-based interface for writing, organizing, and executing HTTP tests, making it easy to maintain robust API quality in CI/CD pipelines. -
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5
ipfs-css
Single-purpose css class names and font-face config to IPFS up your UI
The single-purpose CSS class names and @font-face config to IPFS up your UI. Once you've installed ipfs-css from npm, the CSS and SCSS files and the web-fonts are available from your node_modules/ipfs-css directory. You can import the theme.json file which can be used with a ThemeProvider component. All the CSS atoms are generated from that, so you can be sure you're using the same values. While ipfs.css contains everything you need, if you prefer variables for fonts, colors, and gradients,... -
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Opta
The next generation of Infrastructure-as-Code
...Opta is a new kind of Infrastructure-as-Code (IaC) framework that lets engineers work with high-level constructs instead of getting lost in low-level cloud configuration. Opta has a vast library of modules (like EKS, RDS, DynamoDB, GKE, Cloud SQL, and even third-party services like Datadog) that engineers can compose together to build their ideal infrastructure stack. It's built on top of Terraform, and designed so engineers aren’t locked in – anyone can write custom Terraform or even take the Opta-generated Terraform and work independently. -
7
SageMaker MXNet Inference Toolkit
Toolkit for allowing inference and serving with MXNet in SageMaker
...This library provides default pre-processing, predict and postprocessing for certain MXNet model types and utilizes the SageMaker Inference Toolkit for starting up the model server, which is responsible for handling inference requests. AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference, transforms etc. ... -
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DeepStack
The World's Leading Cross Platform AI Engine for Edge Devices
DeepStack is an AI API engine that serves pre-built models and custom models on multiple edge devices locally or on your private cloud. DeepStack runs completely offline and independent of the cloud. You can also install and run DeepStack on any cloud VM with docker installed to serve as your private, state-of-the-art and real-time AI server. -
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Photonix Photo Manager
A modern, web-based photo management server
...This project is currently in development and not feature complete for a version 1.0 yet. If you don't mind putting up with broken parts or want to help out, run the Docker image and give it a go. I'd love for other contributors to get involved. You can move some photos into the folder data/photos and they should get detected and imported immediately. Once you have finished trying out the system you can edit the volume in the docker-compose.yml file where it says ./data/photos to mount wherever you usually keep photos. ... -
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10
Aquila X
Easy build your personal search engine with Aquila Network
Easy build your personal search engine with Aquila Network. Aquila X is the gateway to Aquila Network and it's applications. AquilaX is a smart bookmarking tool. You can keep your bookmarks and search through it's contents. Choose to keep all your data in a local server or in the cloud. This is an open source software and thus is auditable. -
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Easily host files on IPFS
Docker image to host IPFS HTTP gateway with support for pin listing
A docker container containing an HTTP gateway and IPFS node to easily host files on IPFS. You run the docker container with a shared volume for the ipfs storage. If you add files to the volume, they are added to ipfs, pinned and deleted. The software is packaged as a docker container. Pick any of the following options to start the docker container. -
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manage-fastapi
CLI tool for FastAPI. Generating new FastAPI projects & boilerplates
manage-fastapi Project generator and manager for FastAPI. -
13
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. -
14
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. -
15
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. -
16
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. -
17
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. -
18
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. -
19
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. ... -
20
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. -
21
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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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... -
23
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. -
24
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. -
25
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.
