Search Results for "create" - Page 14
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Showing 1307 open source projects for "create"
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$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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MCP UI
SDK for building interactive UI components over MCP for AI tools
mcp-ui is a software development kit designed to bring interactive user interface capabilities to applications built on the Model Context Protocol (MCP). It enables developers to create rich, dynamic UI components that can be delivered from an MCP server and rendered seamlessly by a compatible client. Instead of returning only text responses, tools can provide structured UI resources such as HTML or remote-rendered components, allowing more engaging and functional interactions. mcp-ui introduces a standardized approach where tools and their associated interfaces are linked through metadata, enabling clients to automatically discover and display the correct UI. ... -
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BackAnt CLI
Let your AI agent create clean, easy to maintain flask backends
BackAnt CLI is an AI-native backend scaffolding tool designed to generate production-ready Flask APIs from a JSON specification or a small set of CLI commands. Its main goal is to reduce the repetitive work involved in setting up layered backend projects by generating key application components automatically rather than forcing developers to assemble them by hand. The tool creates a structured backend architecture that includes routes, services, repositories, models, startup files, Docker... -
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AutoAgent
AutoAgent: Fully-Automated and Zero-Code LLM Agent Framework
AutoAgent is a fully automated, zero-code LLM agent framework that lets users create agents and workflows using natural language instead of manual coding and configuration. It is structured around modes that cover both “use” and “build” scenarios: a user mode for running a ready-made multi-agent research assistant, plus editors for creating individual agents or multi-agent workflows from conversational requirements. -
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Flama
Fire up your models with the flame
Flama is a python library which establishes a standard framework for development and deployment of APIs with special focus on machine learning (ML). The main aim of the framework is to make ridiculously simple the deployment of ML APIs, simplifying (when possible) the entire process to a single line of code. The library builds on Starlette, and provides an easy-to-learn philosophy to speed up the building of highly performant GraphQL, REST and ML APIs. Besides, it comprises an ideal solution... -
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Letterboxd Recommendations
Scraping publicly-accessible Letterboxd data for movie recommendations
...A user's "star" ratings are scraped from their Letterboxd profile and assigned numerical ratings from 1 to 10 (accounting for half stars). Their ratings are then combined with a sample of ratings from the top 4000 most active users on the site to create a collaborative filtering recommender model using singular value decomposition (SVD). All movies in the full dataset that the user has not rated are run through the model for predicted scores and the items with the top predicted scores are returned. Due to constraints in time and computing power, the maximum sample size that a user is allowed to select is 500,000 samples, though there are over five million ratings in the full dataset from the top 4000 Letterboxd users alone. -
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Django Wiki
A wiki system with complex functionality for simple integration
...While Markdown's syntax has been influenced by several existing text-to-HTML filters -- including Setext, atx, Textile, reStructuredText, Grutatext, and EtText -- the single biggest source of inspiration for Markdown's syntax is the format of plain text email. In order to customize the wiki, best idea is to override templates and create your own template tags. Do not make your own hard copy of this repository in order to fiddle with internal parts of the wiki -- this strategy will lead you to lose out on future updates with highly improved features and plugins. Possibly security updates as well! -
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Thinc
A refreshing functional take on deep learning
...We wrote the new version to let users compose, configure and deploy custom models built with their favorite framework. Switch between PyTorch, TensorFlow and MXNet models without changing your application, or even create mutant hybrids using zero-copy array interchange. Develop faster and catch bugs sooner with sophisticated type checking. Trying to pass a 1-dimensional array into a model that expects two dimensions? That’s a type error. Your editor can pick it up as the code leaves your fingers. -
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Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase,... -
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wemake-python-styleguide
The strictest and most opinionated python linter ever!
Welcome to the strictest and most opinionated Python linter ever. wemake-python-styleguide is actually a flake8 plugin with some other plugins as dependencies. Ensures consistency - no matter who works on it, the end product will always be the same dependable code. Helps avoid potential bugs - strict rules make sure that you don't make common mistakes. Efficient code reviews - each piece of code has a similar familiar style and syntax. If it passes all the checks, there's little left to... -
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Open Vision Agents by Stream
Build Vision Agents quickly with any model or video provider
...It focuses on combining video understanding models, such as YOLO and Roboflow based detectors, with real time large language models like OpenAI Realtime and Gemini Live to create interactive experiences. The framework uses Stream’s ultra low latency edge network so agents can join sessions quickly and maintain very low audio and video latency while processing frames and generating responses. Developers work with an agent abstraction that connects video edge providers, LLMs, and processors into pipelines, making it easier to orchestrate tasks like object detection, pose estimation, and conversational guidance. ... -
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Otter-Grader
A Python and R autograding solution
Otter Grader is a light-weight, modular open-source autograder developed by the Data Science Education Program at UC Berkeley. It is designed to work with classes at any scale by abstracting away the autograding internals in a way that is compatible with any instructor's assignment distribution and collection pipeline. Otter supports local grading through parallel Docker containers, grading using the autograder platforms of 3rd party learning management systems (LMSs), the deployment of an... -
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Jittor
Jittor is a high-performance deep learning framework
...Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. Jittor'op is similar to NumPy. Let's try some operations. We create Var a and b via operation jt.float32, and add them. Printing those variables shows they have the same shape and dtype. -
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NVIDIA NeMo
Toolkit for conversational AI
...Each collection consists of prebuilt modules that include everything needed to train on your data. Every module can easily be customized, extended, and composed to create new conversational AI model architectures. Conversational AI architectures are typically large and require a lot of data and compute for training. NeMo uses PyTorch Lightning for easy and performant multi-GPU/multi-node mixed-precision training. Supported models: Jasper, QuartzNet, CitriNet, Conformer-CTC, Conformer-Transducer, Squeezeformer-CTC, Squeezeformer-Transducer, ContextNet, LSTM-Transducer (RNNT), LSTM-CTC. ... -
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status-react
A free (libre) open source, mobile OS for Ethereum
...That's right, no middle men and go-Ethereum running directly on your device. We believe in a medium of pure free trade, economies with fair, permission-less access and a world without intermediaries. We want to create policies that can exist between friends or scale globally, we want to communicate securely and be uninhibited by legacy systems. Safely send, store and receive cryptocurrencies including ERC20 and ERC721 tokens with the Status crypto wallet. Only you hold the keys to your funds. Status' intuitive design protects you and your funds from attacks. ... -
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txtai
Build AI-powered semantic search applications
txtai executes machine-learning workflows to transform data and build AI-powered semantic search applications. Traditional search systems use keywords to find data. Semantic search applications have an understanding of natural language and identify results that have the same meaning, not necessarily the same keywords. Backed by state-of-the-art machine learning models, data is transformed into vector representations for search (also known as embeddings). Innovation is happening at a rapid... -
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Ansible-lint
Best practices checker for Ansible
Ansible Lint is a command-line tool for linting playbooks, roles and collections aimed towards any Ansible users. Its main goal is to promote proven practices, patterns and behaviors while avoiding common pitfalls that can easily lead to bugs or make code harder to maintain. Ansible lint is also supposed to help users upgrade their code to work with newer versions of Ansible. Due to this reason we recommend using it with the newest version of Ansible, even if the version used in production... -
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Django Bootstrap Modal Forms
A Django plugin for creating AJAX driven forms in Bootstrap modal
A Django plugin for creating AJAX-driven forms in Bootstrap modal. This repository includes Dockerfile and docker-compose.yml files so you can easily setup and start to experiment with django-bootstrap-modal-forms running inside of a container on your local machine. Any changes you make in bootstrap_modal_forms, examples and test folders are reflected in the container (see docker-compose.yml) and the data stored in the sqlite3 database are persistent even if you remove the stopped container.... -
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Dream Textures
Stable Diffusion built-in to Blender
Create textures, concept art, background assets, and more with a simple text prompt. Use the 'Seamless' option to create textures that tile perfectly with no visible seam. Texture entire scenes with 'Project Dream Texture' and depth to image. Re-style animations with the Cycles render pass. Run the models on your machine to iterate without slowdowns from a service. -
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PyScaffold
Python project template generator with batteries included
PyScaffold is a project generator for bootstrapping high-quality Python packages, ready to be shared on PyPI and installable via pip. It is easy to use and encourages the adoption of the best tools and practices of the Python ecosystem, helping you and your team to stay sane, happy and productive. The best part? It is stable and has been used by thousands of developers for over half a decade! Checkout out this demo project, which was set up using PyScaffold and if you are still not convinced... -
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RAPTOR
The official implementation of RAPTOR
...Traditional RAG systems typically retrieve small text chunks independently, which can limit a model’s ability to understand broader document context. RAPTOR addresses this limitation by recursively embedding, clustering, and summarizing documents to create a tree-structured hierarchy of information. Each level of the tree represents summaries at different levels of abstraction, allowing retrieval to operate at both detailed and high-level conceptual layers. During inference, the system can navigate this hierarchical representation to retrieve information that best matches the user’s query while preserving broader contextual understanding. ... -
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ipychart
The power of Chart.js with Python
Create charts with Python in a very similar way to creating charts using Chart.js. The charts created are fully configurable, interactive, and modular and are displayed directly in the output of the cells of your jupyter notebook environment. Charts are fully interactive, you can hover it to display tooltips and select the information you want to see directly from the output cell of your notebook. -
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Tiny 11 Releases
Automated tools for creating streamlined Windows 11 images with CI/CD.
Tiny11 Automated Builder: Build Tiny11, Build Tiny11 Core and Build Nano11 Automated tools for creating streamlined Windows 11 images with CI/CD support. 📋 Overview Tiny11 Automated Builder provides PowerShell scripts to create minimized Windows 11 ISO images by removing bloatware, disabling telemetry, and optimizing system components. -
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BedrockLaunch
A fully functional Minecraft Bedrock Edition launcher
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IP-XACT 2009/2014 Platform
Smart GUI/Commandline tools to create IP-XACT( 2009/2014) files
Smart GUI to create or update IP-XACT often needed for the IP packaging. It has capability create Bus Definitions from scratch to populate BusDef library. One can create IP-XACT Component, Design or Registers by importing Ip in System Verilog/Verilog-95/VHDL, instantiate Bus Interfaces with proper port maps and attributes as needed. Smart GUI to create IP-XACT Registers, Memory Maps, Address Blocks for IP- has feature to import XLS or Verilog . ... -
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OpenDAN
OpenDAN is an open source Personal AI OS
OpenDAN is an open-source Personal AI OS , that consolidates various AI modules in one place for your personal use. The goal of OpenDAN (Open and Do Anything Now with AI) is to create a Personal AI OS , which provides a runtime environment for various Al modules as well as protocols for interoperability between them. With OpenDAN, users can securely collaborate with various AI modules using their private data to create powerful personal AI agents, such as butlers, lawyers, doctors, teachers, assistants, girl or boyfriends.
