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Showing 261 open source projects for "deploy"
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Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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TG WS Proxy
Local MTProto proxy server for partial bypassing of Telegram loading
TG WS Proxy is a lightweight proxy server designed to enable Telegram connectivity over WebSocket, particularly in environments where direct access to Telegram servers is restricted. It allows Telegram clients to communicate through alternative transport layers, bypassing network limitations or censorship mechanisms. The project focuses on simplicity and efficiency, providing a minimal setup that can be deployed quickly on various platforms. It supports secure communication and can be... -
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OpenLLM
Operating LLMs in production
An open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease. With OpenLLM, you can run inference with any open-source large-language models, deploy to the cloud or on-premises, and build powerful AI apps. Built-in supports a wide range of open-source LLMs and model runtime, including Llama 2， StableLM, Falcon, Dolly, Flan-T5, ChatGLM, StarCoder, and more. Serve LLMs over RESTful API or gRPC with one command, query via WebUI, CLI, our Python/Javascript client, or any HTTP client. -
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Seldon Core
An MLOps framework to package, deploy, monitor and manage models
...Framework agnostic, supports top ML libraries, toolkits and languages. Advanced deployments with experiments, ensembles and transformers. Our open-source framework makes it easier and faster to deploy your machine learning models and experiments at scale on Kubernetes. The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes. -
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AWS SAM CLI
CLI tool to build, test, debug, and deploy Serverless applications
...To get started with building SAM-based applications, use the SAM CLI. SAM CLI provides a Lambda-like execution environment that lets you locally build, test, debug, and deploy AWS serverless applications. -
Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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Online Boutique
Sample cloud-first application with 10 microservices
...Google uses this application to demonstrate the use of technologies like Kubernetes, GKE, Istio, Stackdriver, and gRPC. This application works on any Kubernetes cluster, like Google Kubernetes Engine (GKE). It’s easy to deploy with little to no configuration. -
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BotCity Framework Core Python
BotCity Framework - Python
Recognize and interact with UI elements using state-of-art computer vision module. Operate any UI interface independent of the technology or platform (desktop, web, terminal). BotCity is a platform to develop, deploy, manage and maintain automation. Automation can be developed in Python or Java using open-source libraries that are market standard. Develop, deploy, manage and scale your Automation Ops using All in One platform that provides task queue, runtime environment management, reports, alerts, logs and much more. -
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Streamlit
The fastest way to build data apps in Python
...Adding a widget is the same as declaring a variable. No need to write a backend, define routes, handle HTTP requests, connect a frontend, write HTML, CSS, JavaScript, etc. Effortlessly share, manage and deploy your apps, directly from Streamlit. Streamlit lets you turn data scripts into sharable web apps in minutes, not weeks. It’s all Python, open-source, and free! And once you’ve created an app you can use our cloud platform to deploy, manage, and share your app! Streamlit can also be installed in a virtual environment on Windows, Mac, and Linux. -
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NautilusTrader
A high-performance algorithmic trading platform
NautilusTrader is an open-source, high-performance, production-grade algorithmic trading platform, provides quantitative traders with the ability to backtest portfolios of automated trading strategies on historical data with an event-driven engine, and also deploy those same strategies live, with no code changes. The platform is 'AI-first', designed to develop and deploy algorithmic trading strategies within a highly performant and robust Python native environment. This helps to address the parity challenge of keeping the Python research/backtest environment, consistent with the production live trading environment. ... -
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LlamaDeploy
Deploy your agentic worfklows to production
...Developers can define workflows that involve multiple steps such as data retrieval, reasoning, tool invocation, and response generation, then deploy them using the framework’s infrastructure tools. The design emphasizes scalability, modularity, and fault-tolerant execution so that agent systems can run reliably in production environments. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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SageMaker Python SDK
Training and deploying machine learning models on Amazon SageMaker
SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. 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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ReClip
Download videos from almost any website
...The application emphasizes simplicity and minimalism, featuring a clean interface built with plain HTML, CSS, and JavaScript without requiring complex build steps or frameworks. Its backend is implemented in a compact Python Flask application, making it easy to deploy and customize. Users can paste multiple URLs at once, select output formats such as MP4 or MP3, and choose quality settings before downloading. The system also includes features like automatic URL deduplication and batch processing to improve usability. -
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Trellis
WordPress LEMP stack with PHP 8.1, Composer, WP-CLI
...Your development virtual machine and your production are as similar as possible. This gives the confidence to know that if your WordPress site works in development, it will also work in production and you can deploy with confidence. trellis-cli provides a command-line interface (CLI) to manage Trellis projects via the `trellis` command with features. -
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Exegol
Fully featured and community-driven hacking environment
Exegol is a community-driven hacking environment, powerful and yet simple enough to be used by anyone in day-to-day engagements. Exegol is the best solution to deploy powerful hacking environments securely, easily, and professionally. No more unstable, not-so-security-focused systems lacking major offensive tools. Kali Linux (and similar alternatives) are great toolboxes for learners, students, and junior pentesters. However professionals have different needs, and their context requires a whole new design. -
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omegaml
MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle
omega|ml is the innovative Python-native MLOps platform that provides a scalable development and runtime environment for your Data Products. Works from laptop to cloud. -
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Q-CTRL Open Controls
Q-CTRL Open Controls
Q-CTRL Open Controls is an open-source Python package that makes it easy to create and deploy established error-robust quantum control protocols from the open literature. The aim of the package is to be the most comprehensive library of published and tested quantum control techniques developed by the community, with easy-to-use export functions allowing users to deploy these controls on. -
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Flagsmith
Open source feature flagging and remote config service
Release features with confidence; manage feature flags across web, mobile, and server-side applications. Use our hosted API, deploy to your own private cloud, or run on-premises. Flagsmith provides an all-in-one platform for developing, implementing, and managing your feature flags. Whether you are moving off an in-house solution or using toggles for the first time, you will be amazed by the power and efficiency gained by using Flagsmith. Flagsmith makes it easy to create and manage feature toggles across web, mobile, and server-side applications. ... -
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OpenVINO Notebooks
Jupyter notebook tutorials for OpenVINO
openvino_notebooks is a collection of interactive Jupyter notebooks designed to demonstrate how to build, optimize, and deploy artificial intelligence applications using the OpenVINO toolkit. The repository provides practical tutorials that guide developers through various AI workflows including computer vision, natural language processing, and generative AI tasks. Each notebook demonstrates how to run pre-trained models, optimize inference performance, and deploy models across hardware such as CPUs, GPUs, and specialized accelerators. ... -
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Xorbits Inference
Replace OpenAI GPT with another LLM in your app
...Xorbits Inference(Xinference) is a powerful and versatile library designed to serve language, speech recognition, and multimodal models. With Xorbits Inference, you can effortlessly deploy and serve your or state-of-the-art built-in models using just a single command. Whether you are a researcher, developer, or data scientist, Xorbits Inference empowers you to unleash the full potential of cutting-edge AI models. -
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RF-DETR
RF-DETR is a real-time object detection and segmentation
...The model is designed to detect objects and segment them within images or video streams using a unified detection pipeline. RF-DETR emphasizes strong performance across both accuracy and latency benchmarks, allowing developers to deploy high-quality detection models in applications that require immediate processing such as robotics, autonomous systems, and industrial inspection. The repository includes Python packages, training scripts, and model configurations that enable researchers and engineers to train and deploy detection models on custom datasets. -
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AWS Serverless Application Model
An open-source framework for building serverless applications
...SAM CLI provides a Lambda-like execution environment that lets you locally build, test, and debug applications defined by SAM templates or through the AWS Cloud Development Kit (CDK). You can also use the SAM CLI to deploy your applications to AWS. SAM and SAM CLI are open-sourced under the Apache 2.0 license. You can contribute new features and enhancements to SAM on GitHub or SAM CLI on GitHub. -
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Pathway AI Pipelines
Ready-to-run cloud templates for RAG
...The templates include built-in indexing, vector search, hybrid search, and caching capabilities that remove the need to assemble separate infrastructure components. Developers can run the applications locally or deploy them to cloud platforms using Docker with minimal setup. Overall, llm-app functions as a practical accelerator for teams building real-time, production-ready AI knowledge systems. -
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Metarget
Framework for automatic construction of vulnerable infrastructures
...There are already some excellent security projects like Vulhub, and VulApps in the open-source community, which pack vulnerable scenes into container images so that researchers could utilize them and deploy scenes quickly. Hence, we develop Metarget and hope to solve the deployment issue above to some extent. Furthermore, we also expect that Metarget could help to construct multilayer vulnerable cloud native scenes automatically. -
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DeerFlow
Deep Research framework, combining language models with tools
...It supports asynchronous task coordination, modular tool integration, and orchestrates the data flow between agents — making it suitable for large-scale or multi-stage research pipelines. Users can deploy it locally or on server infrastructure, integrate custom tools, and benefit from its flexible configuration. -
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FlexLLMGen
Running large language models on a single GPU
...The architecture distributes computation and memory usage across the GPU, CPU, and disk in order to maximize the number of tokens processed during inference. This design allows organizations to deploy powerful language models for high-volume tasks without the infrastructure costs typically associated with large-scale AI systems. The project is particularly useful for workloads that prioritize throughput over latency, including benchmarking experiments and large corpus analysis. -
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Made With ML
Learn how to develop, deploy and iterate on production-grade ML
...It provides structured lessons and practical code examples that demonstrate how to design machine learning workflows, manage datasets, train models, evaluate performance, and deploy inference services. The repository organizes these concepts into modular Python scripts that follow software engineering best practices such as testing, configuration management, logging, and version control. Through a combination of tutorials, notebooks, and production-ready scripts, the project demonstrates how machine learning applications should be developed as maintainable systems rather than isolated experiments.
