Repository History
17 repositories tagged with Framework
vidgear: High-Performance Cross-Platform Video Processing Framework in Python
vidgear is a high-performance, cross-platform Python framework for advanced video processing. It provides a comprehensive, multi-threaded, and asyncio API for real-time video capture, writing, streaming, and network transfer. This framework simplifies complex media operations, enabling developers to build robust applications with ease.
Grab: A Powerful Python Web Scraping Framework
Grab is a robust Python web scraping framework designed to simplify complex data extraction tasks. It provides comprehensive tools for handling network requests, processing scraped content, and managing asynchronous operations through its powerful Spider component. Developers can leverage features like automatic cookie support, HTTP/SOCKS proxies, and XPath queries for efficient web data collection.
Awesome Pyramid: A Curated List of Pyramid Apps, Projects, and Resources
Awesome Pyramid is a meticulously curated list designed for developers working with the Pyramid web framework. It compiles a wide array of applications, projects, and valuable resources, making it an essential guide for discovering tools and examples. Inspired by the popular awesome-python list, this repository helps users navigate the Pyramid ecosystem efficiently.
Masonite: The Modern and Developer-Centric Python Web Framework
Masonite is a Python web framework known for its modern and developer-centric approach, offering features like ORM, mail, queues, and task scheduling. This repository, however, is no longer maintained, with active development continuing under `masonitedev/masonite`. It served as the foundation for Masonite versions up to 4.x.
Django Channels: Developer-Friendly Asynchrony for Django
Django Channels extends Django to bring powerful asynchronous capabilities, including WebSockets and long-poll HTTP, to your projects. It integrates seamlessly using familiar Django design patterns, offering a flexible framework for building real-time applications. As an official Django Project, it ensures robust support and continuous development.
LazyLLM: Low-Code Development for Multi-Agent LLM Applications
LazyLLM offers a low-code development tool designed for building multi-agent LLM applications with ease. It simplifies the creation of complex AI applications, providing a streamlined workflow for rapid prototyping, data feedback, and iterative optimization. Developers can leverage its extensive features for deployment, cross-platform compatibility, and efficient model fine-tuning.
Agentarium: A Python Framework for AI Agent Simulations
Agentarium is an open-source Python framework designed for creating and managing simulations with AI-powered agents. It offers an intuitive platform for designing complex, interactive environments where agents can act, learn, and evolve. This powerful tool simplifies the orchestration of multiple AI agents and their interactions.
EasyJailbreak: A Python Framework for Adversarial LLM Jailbreak Prompts
EasyJailbreak is an intuitive Python framework designed for generating adversarial jailbreak prompts for Large Language Models (LLMs). It provides a structured approach to decompose the jailbreaking process into iterative steps, offering components for mutation, attack, and evaluation. This tool is ideal for researchers and developers focused on LLM security and understanding model vulnerabilities.
Otto: Intelligent Automation and LLM Integration for Frappe Framework
Otto is an early-stage Frappe Framework application designed to bring intelligent automation and large language model (LLM) capabilities to the Frappe ecosystem. It serves as both a standalone app for task automation and a library for seamless LLM integration within custom Frappe applications. This project aims to empower Frappe users with advanced AI functionalities for various business processes.
Univer: Build AI-Native Spreadsheets with a Full-Stack Framework
Univer is an isomorphic, full-stack framework designed for creating and editing spreadsheets, documents, and presentations across web and server environments. It empowers developers to build AI-native applications, offering high performance, extensibility, and seamless integration into existing projects. With its robust feature set and plug-in architecture, Univer provides a powerful foundation for modern office suite functionalities.
Qwen-Agent: A Comprehensive Framework for LLM Applications and Agent Development
Qwen-Agent is a powerful framework designed for developing advanced Large Language Model (LLM) applications, built upon Qwen models. It offers robust capabilities including function calling, a code interpreter, RAG, and multi-context protocol (MCP) support. The framework enables developers to create sophisticated AI agents with planning, tool usage, and memory features, serving as the backend for applications like Qwen Chat.
Cheshire Cat AI Core: An AI Agent Microservice Framework
Cheshire Cat AI Core is an open-source framework designed for building custom AI agents as microservices. It offers an API-first approach, enabling easy integration of conversational layers into applications with WebSocket chat and a customizable REST API. Key features include built-in RAG with Qdrant, extensibility via plugins, function calling, and full Dockerization for straightforward deployment.