Search Results for "write" - Page 5
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Showing 416 open source projects for "write"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Marvin
A batteries-included library for building AI-powered software
...These functions differ from conventional ones in that they don’t rely on source code, but instead generate their outputs on-demand through AI. With AI functions, you don't have to write complex code for tasks like extracting entities from web pages, scoring sentiment, or categorizing items in your database. Just describe your needs, call the function, and you're done. AI functions work with native data types, so you can seamlessly integrate them into any codebase and chain them into sophisticated pipelines. In addition to AI functions, Marvin also introduces more flexible bots. ... -
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ThetaGang
ThetaGang is an IBKR bot for collecting money
...ThetaGang will try to acquire your desired allocation of each stock or ETF according to the weights you specify in the config. To acquire the positions, the script will write puts when conditions are met. -
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thumbor
An open-source photo thumbnail service by globo.com
Open-source smart on-demand image cropping, resizing and filters. Thumbor is a smart imaging service. It enables on-demand crop, resizing and flipping of images. It features a very smart detection of important points in the image for better cropping and resizing, using state-of-the-art face and feature detection algorithms (more on that in Detection Algorithms). Save time and money in your company with Thumbor. With the most advanced face detection technology, Thumbor ensure you to have the... -
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SimpleMem
SimpleMem: Efficient Lifelong Memory for LLM Agents
...It provides easy-to-use APIs for storing structured memory entries, querying those memories using semantic search, and retrieving context to augment prompt inputs for downstream processing. Unlike monolithic systems where memory management is ad-hoc, SimpleMem formalizes a memory lifecycle—write, index, retrieve, refine—so applications can handle user history, document collections, or dynamic contextual state systematically. It supports customizable embedding models, efficient vector indexes, and relevance weighting, making it practical for building assistants, personal agents, or domain-specific retrieval systems that need persistent knowledge. -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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Bytewax
Python Stream Processing
...Because Bytewax couples the stream and event processing capabilities of Flink, Spark, and Kafka Streams with the friendly and familiar interface of Python, you can re-use the Python libraries you already know and love. Connect data sources, run stateful transformations, and write to various downstream systems with built-in connectors or existing Python libraries. Bytewax is a Python framework and Rust distributed processing engine that uses a dataflow computational model to provide parallelizable stream processing and event processing capabilities similar to Flink, Spark, and Kafka Streams. You can use Bytewax for a variety of workloads from moving data à la Kafka Connect style all the way to advanced online machine learning workloads. ... -
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Core ML Tools
Core ML tools contain supporting tools for Core ML model conversion
Use Core ML Tools (coremltools) to convert machine learning models from third-party libraries to the Core ML format. This Python package contains the supporting tools for converting models from training libraries. Core ML is an Apple framework to integrate machine learning models into your app. Core ML provides a unified representation for all models. Your app uses Core ML APIs and user data to make predictions, and to fine-tune models, all on the user’s device. Core ML optimizes on-device... -
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Kubernetes Operator Pythonic Framework
A Python framework to write Kubernetes operators in just a few lines
Kopf —Kubernetes Operator Pythonic Framework— is a framework and a library to make Kubernetes operator's development easier, just in a few lines of Python code. The main goal is to bring the Domain-Driven Design to the infrastructure level, with Kubernetes being an orchestrator/database of the domain objects (custom resources), and the operators containing the domain logic (with no or minimal infrastructure logic). The project was originally started as zalando-incubator/kopf in March 2019,... -
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SDGym
Benchmarking synthetic data generation methods
...You also customize the process to include your own work. Select any of the publicly available datasets from the SDV project, or input your own data. Choose from any of the SDV synthesizers and baselines. Or write your own custom machine learning model. In addition to performance and memory usage, you can also measure synthetic data quality and privacy through a variety of metrics. Install SDGym using pip or conda. We recommend using a virtual environment to avoid conflicts with other software on your device. -
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HumbleUI
Clojure Desktop UI framework
...(Note: while there is a repository, I did not find a detailed README in my search to fully confirm all capabilities.) Electron is a great landmark. Normal shortcuts, icon, its own window, file system access, notifications, OS integrations. Write once, run everywhere is no longer rejected by users. Performant enough not to noticeably lag. -
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borb
borb is a library for reading, creating and manipulating PDF files
borb is a library for creating and manipulating PDF files in python. borb is a pure python library to read, write, and manipulate PDF documents. It represents a PDF document as a JSON-like data structure of nested lists, dictionaries and primitives (numbers, string, booleans, etc) This is currently a one-man project, so the focus will always be to support those use-cases that are more common in favor of those that are rare. -
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SageMaker Training Toolkit
Train machine learning models within Docker containers
...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. Write a training script (eg. train.py). Define a container with a Dockerfile that includes the training script and any dependencies. -
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nbdev
Create delightful software with Jupyter Notebooks
nbdev is a notebook-driven development platform (by fast.ai/AnswerDotAI) enabling you to write code, tests, documentation, and deploy software, all from Jupyter Notebooks. It provides a unified literate programming workflow where you can tag notebook cells for export to Python modules, auto-generate documentation via Quarto (and host it on GitHub Pages), run tests embedded in notebooks, manage clean notebooks with Git-friendly metadata hooks, and seamlessly publish packages to PyPI/conda, all while keeping source and documentation in sync. -
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OAuthLib
A generic, spec-compliant, thorough implementation of the OAuth
...Use it to graft OAuth client support onto your favorite HTTP library, or provide support onto your favourite web framework. If you're a maintainer of such a library, write a thin veneer on top of OAuthLib and get OAuth support for very little effort. -
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AICodeBot
AI-powered tool for developers, simplifying coding tasks
...Perform code reviews, create helpful commit messages, debug problems, and help you think through building new features. A team member that accelerates the pace of development and helps you write better code. We've planned to build out multiple different interfaces for interacting with AICodeBot. To start, it's a command-line tool that you can install and run in your terminal and a GitHub Action for Code Reviews. This project was built before AI Coding Assistants were cool. As such, much of the functionality has been replicated in various IDEs. ... -
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Union Pandera
Light-weight, flexible, expressive statistical data testing library
The open-source framework for precision data testing for data scientists and ML engineers. Pandera provides a simple, flexible, and extensible data-testing framework for validating not only your data but also the functions that produce them. A simple, zero-configuration data testing framework for data scientists and ML engineers seeking correctness. Access a comprehensive suite of built-in tests, or easily create your own validation rules for your specific use cases. Validate the functions... -
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dynaconf
Configuration Management for Python
...Built-in support for Hashicorp Vault and Redis as settings and secrets storage. Built-in extensions for Django and Flask web frameworks. CLI for common operations such as init, list, write, validate, export. On your own code you import and use settings object imported from your config.py file. Dynaconf prioritizes the use of environment variables and you can optionally store settings in Settings Files using any of toml|yaml|json|ini|py extension. -
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Eel
A Python library for making simple Electron-like HTML/JS GUI apps
...There are several options for making GUI apps in Python, but if you want to use HTML/JS (in order to use jQueryUI or Bootstrap, for example) then you generally have to write a lot of boilerplate code to communicate from the Client (Javascript) side to the Server (Python) side. -
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Kedro
A Python framework for creating reproducible, maintainable code
...Standardises team workflows; the modular structure of Kedro facilitates a higher level of collaboration when teams solve problems together. Makes a seamless transition from development to production, as you can write quick, throw-away exploratory code and transition to maintainable, easy-to-share, code experiments quickly. Puts the "engineering" back into data science because it borrows concepts from software engineering and applies them to machine-learning code. It is the foundation for clean, data science code. -
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nanocode
Minimal Claude Code alternative. Single Python file, zero dependencies
...It implements a full agentic loop where the model can reason, decide when to use tools, execute those tools, and iterate until producing a final answer, making it useful for simple AI-assisted coding workflows. It includes a set of integrated tools such as read, write, edit, glob, grep, and bash that let the agent interact with the file system and shell commands directly from the terminal, and it keeps a conversation history with colored terminal output for readability. The project exemplifies how lightweight architectures can still support practical agent workflows without complex infrastructure, making it suitable for developers exploring agent frameworks or building custom coding assistants. -
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Testinfra
Testinfra test your infrastructures
With Testinfra you can write unit tests in Python to test the actual state of your servers configured by management tools like Salt, Ansible, Puppet, Chef and so on. Testinfra aims to be a Serverspec equivalent in python and is written as a plugin to the powerful Pytest test engine. By default Testinfra launches tests on the local machines, but you can also test remotes systems using paramiko. -
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Google Open Source Project Style Guide
Chinese version of Google open source project style guide
Each larger open source project has its own style guide, a series of conventions on how to write code for the project (sometimes more arbitrary). When all the code maintains a consistent style, it is more important when understanding large code bases. easy. The meaning of "style" covers a wide range, from "variables use camelCase" to "never use global variables" to "never use exceptions". The English version of the project maintains the programming style guidelines used in Google. ... -
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AWS IoT Device SDK for Python
SDK for connecting to AWS IoT from a device using Python
The AWS IoT Device SDK for Python allows developers to write Python script to use their devices to access the AWS IoT platform through MQTT or MQTT over the WebSocket protocol. By connecting their devices to AWS IoT, users can securely work with the message broker, rules, and the device shadow (sometimes referred to as a thing shadow) provided by AWS IoT and with other AWS services like AWS Lambda, Amazon Kinesis, Amazon S3, and more. -
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SERA CLI
A tool to use the Ai2 Open Coding Agents Soft-Verified Agents
SERA CLI is a command-line tool created by AllenAI to enable developers to interact with the SERA (Soft-Verified Efficient Repository Agents) model family using Claude Code as the execution front end. It provides a convenient interface for deploying, testing, and using SERA models without needing to write scaffold code from scratch, acting as both a proxy and utility wrapper to simplify workflows that involve large agent models. Through sera-cli, users can connect to local or cloud-hosted SERA deployments, including via Modal for quick GPU provisioning and model caching, which helps accelerate experiments. The project is targeted at practitioners and researchers in the AI space who need a flexible but powerful CLI interface for model invocation, endpoint configuration, and integration with development pipelines. -
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Motor
The async Python driver for MongoDB and Tornado or asyncio
...Built on top of Python’s Tornado and asyncio frameworks, Motor lets you issue database operations without blocking the event loop, enabling concurrency in web servers, real-time systems, and microservices. It provides a familiar API surface similar to the official synchronous PyMongo driver, so you can migrate or write MongoDB code in Python without having to learn a completely new interface. Because it integrates with popular async ecosystems like FastAPI, Sanic, and aiohttp, Motor is a natural fit for modern async Python stacks where throughput and responsiveness matter. It also supports change streams, grid file system (GridFS), and the full range of CRUD and aggregation operations available in MongoDB. -
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TorchRL
A modular, primitive-first, python-first PyTorch library
...The code is aimed at supporting research in RL. Most of it is written in Python in a highly modular way, such that researchers can easily swap components, transform them, or write new ones with little effort.