Search Results for "apache framework" - Page 2
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Showing 74 open source projects for "apache framework"
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Opsdroid
An open source chat-ops bot framework
Designed to take messages from chat services and execute Python functions (skills) based on their contents. Connector modules transfer messages between opsdroid and a particular chat service. Database modules allow opsdroid to persist information in a database of your choice. Parsers/Matchers modules gather the meaning of what was said and match a skill. Skills are what make opsdroid tick. They define how opsdroid should respond and what actions to take. -
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Unsloth-MLX
Bringing the Unsloth experience to Mac users via Apple's MLX framework
Unsloth-MLX offers developers the power of Unsloth’s efficient large language model fine-tuning experience on Apple Silicon Macs by wrapping Apple’s native MLX framework with an API fully compatible with Unsloth workflows. This project removes traditional barriers that prevent Mac users from prototyping and experimenting with LLM training locally by allowing the same code used in cloud GPU environments to run on M-series hardware, improving workflow continuity and reducing iteration costs.... -
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django-prometheus
Export Django monitoring metrics for Prometheus.io
Export Django monitoring metrics for Prometheus.io. This library provides Prometheus metrics for Django-related operations. Prometheus uses Histogram based grouping for monitoring latencies. You can define custom buckets for latency, adding more buckets decreases performance but increases accuracy. SQLite, MySQL, and PostgreSQL databases can be monitored. Just replace the ENGINE property of your database, replacing django.db.backends with django_prometheus.db.backends. You may want to... -
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Trame
Weave various components and technologies into a Web App
Developed by Kitware, trame is a Python-based framework that allows developers to create web applications with desktop-like functionality. It enables the integration of various components and technologies, such as VTK and ParaView, into web applications written entirely in Python. With best-in-class platforms at its core, trame provides complete control of 3D visualizations and data processing. -
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BentoML
Unified Model Serving Framework
BentoML simplifies ML model deployment and serves your models at a production scale. Support multiple ML frameworks natively: Tensorflow, PyTorch, XGBoost, Scikit-Learn and many more! Define custom serving pipeline with pre-processing, post-processing and ensemble models. Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference... -
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Neuro SAN Studio
A playground for neuro-san
Neuro SAN Studio is a development environment and playground for building, testing, and deploying multi-agent AI systems using the Neuro SAN framework. It provides a hands-on interface where users can design agent networks, run experiments, and observe how multiple agents collaborate to solve complex tasks. The platform is built around a data-driven approach, where entire agent systems can be defined using configuration files rather than extensive code, making it accessible to both... -
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FATE
An industrial grade federated learning framework
FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms,... -
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SageMaker Spark Container
Docker image used to run data processing workloads
...The SageMaker Spark Container is a Docker image used to run batch data processing workloads on Amazon SageMaker using the Apache Spark framework. The container images in this repository are used to build the pre-built container images that are used when running Spark jobs on Amazon SageMaker using the SageMaker Python SDK. The pre-built images are available in the Amazon Elastic Container Registry (Amazon ECR), and this repository serves as a reference for those wishing to build their own customized Spark containers for use in Amazon SageMaker. -
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Kedro
A Python framework for creating reproducible, maintainable code
Kedro is an open sourced Python framework for creating maintainable and modular data science code. Provides the scaffolding to build more complex data and machine-learning pipelines. In addition, there's a focus on spending less time on the tedious "plumbing" required to maintain data science code; this means that you have more time to solve new problems. Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems... -
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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. This... -
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Connexion
Swagger/OpenAPI First framework for Python on top of Flask
Connexion is a framework on top of Flask that automagically handles HTTP requests defined using OpenAPI (formerly known as Swagger), supporting both v2.0 and v3.0 of the specification. Connexion allows you to write these specifications, then maps the endpoints to your Python functions. This is what makes it unique from other tools that generate the specification based on your Python code. You are free to describe your REST API with as much detail as you want and then Connexion guarantees... -
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AWS Chalice
Python Serverless Microframework for AWS
Chalice is a Python microframework for writing and deploying serverless applications on AWS with minimal ceremony. You define routes, event handlers, and background tasks in plain Python, and Chalice turns them into AWS Lambda functions wired to API Gateway, Amazon EventBridge schedulers, S3/SNS/SQS triggers, and more. A single command builds your app, bundles dependencies, generates infrastructure templates, and deploys to your account with sensible defaults. The framework includes local... -
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uwsgi-nginx-flask
Docker image with uWSGI and Nginx for Flask applications in Python
Image with uWSGI and Nginx for Flask apps in Python running in a single container. Docker image with uWSGI and Nginx for Flask web applications in Python running in a single container. Optionally using Alpine Linux. This Docker image allows you to create Flask web applications in Python that run with uWSGI and Nginx in a single container. The combination of uWSGI with Nginx is a common way to deploy Python Flask web applications. It is widely used in the industry and would give you decent... -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN... -
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Wifipumpkin3
Powerful framework for rogue access point attack
wifipumpkin3 is powerful framework for rogue access point attack, written in Python, that allow and offer to security researchers, red teamers and reverse engineers to mount a wireless network to conduct a man-in-the-middle attack. -
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towhee
Framework that is dedicated to making neural data processing
Towhee is an open-source machine-learning pipeline that helps you encode your unstructured data into embeddings. You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to... -
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pipeless
A computer vision framework to create and deploy apps in minutes
Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new... -
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LangChain Apps on Production with Jina
Langchain Apps on Production with Jina & FastAPI
Jina is an open-source framework for building scalable multi-modal AI apps on Production. LangChain is another open-source framework for building applications powered by LLMs. long-chain-serve helps you deploy your LangChain apps on Jina AI Cloud in a matter of seconds. You can benefit from the scalability and serverless architecture of the cloud without sacrificing the ease and convenience of local development. And if you prefer, you can also deploy your LangChain apps on your own... -
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Horovod
Distributed training framework for TensorFlow, Keras, PyTorch, etc.
...With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data processing and model training into a single pipeline. Once Horovod has been configured, the same infrastructure can be used to train models with any framework, making it easy to switch between TensorFlow, PyTorch, MXNet, and future frameworks as machine learning tech stacks continue to evolve. ... -
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Amazon Braket Strawberry Fields Plugin
An open source framework for using Amazon Braket devices
An open-source framework for using Amazon Braket devices with the Strawberry Fields photonic device programming library. This plugin provides a BraketEngine class for running photonic quantum circuits created in Strawberry Fields on the Amazon Braket service. The Amazon Braket Python SDK is an open source library that provides a framework to interact with quantum computing hardware devices and simulators through Amazon Braket. This plugin provides the classes BraketEngine for submitting... -
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linux-factory
Framework used to create custom debian linux operating systems
linux-factory is a utility designed to streamline the process of building and customizing Linux kernel images using a simple, scriptable environment. It provides a modular framework for configuring kernel options, applying patches, and generating bootable images, making it ideal for embedded developers, kernel hackers, and OS maintainers. With a strong emphasis on repeatability and automation, linux-factory reduces the manual overhead of compiling and deploying Linux kernels across various... -
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UnionML
Build and deploy machine learning microservices
Creating ML apps should be simple and frictionless. UnionML is an open-source Python framework built on top of Flyte™, unifying the complex ecosystem of ML tools into a single interface. Combine the tools that you love using a simple, standardized API so you can stop writing so much boilerplate and focus on what matters: the data and the models that learn from them. Fit the rich ecosystem of tools and frameworks into a common protocol for machine learning. Using industry-standard machine... -
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BEVFormer
Implementation of BEVFormer, a camera-only framework
3D visual perception tasks, including 3D detection and map segmentation based on multi-camera images, are essential for autonomous driving systems. In this work, we present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV... -
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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OpenPrompt
An Open-Source Framework for Prompt-Learning
Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks, which modifies the input text with a textual template and directly uses PLMs to conduct pre-trained tasks. OpenPrompt is a library built upon PyTorch and provides a standard, flexible and extensible framework to deploy the prompt-learning pipeline. OpenPrompt supports loading PLMs directly from huggingface transformers. In the future, we will also support PLMs implemented by other...
