Search Results for "framework python" - Page 2
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Showing 1164 open source projects for "framework python"
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Upsonic
The most reliable AI agent framework that supports MCP
Upsonic is a reliability-focused AI agent framework designed for real-world applications. It enables the development of trusted agent workflows within organizations by incorporating advanced reliability features, such as verification layers and output evaluation systems. The framework supports the Model Context Protocol (MCP), facilitating integration with various tools and enhancing agent capabilities. -
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LAMDA
Android reverse engineering & automation framework
Android reverse engineering & automation framework. The most powerful Android capture/reverse/HOOK & cloud phone/remote desktop/automation framework in history, your work has never been so easy and fast. LAMDA is an auxiliary framework for reverse engineering and automation. It is designed to reduce the time and trivial problems of security analysts and application testers. It replaces a large number of manual operations with a programmed interface. It is not a single-function framework... -
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Woke
Woke is a Python-based development and testing framework for Solidity
Woke is a Python-based development and testing framework for Solidity. A testing framework for Solidity smart contracts with Python-native equivalents of Solidity types and blazing-fast execution. A property-based fuzzer for Solidity smart contracts that allows testers to write their fuzz tests in Python. See examples and documentation for more information. Fuzzer builds on top of the testing framework and allows efficient fuzz testing of Solidity smart contracts. Woke implements an LSP server... -
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Amazon Braket PennyLane Plugin
A plugin for allowing Xanadu PennyLane to use Amazon Braket devices
The Amazon Braket PennyLane plugin offers two Amazon Braket quantum devices to work with PennyLane. 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. PennyLane is a machine learning library for optimization and automatic differentiation of hybrid quantum-classical computations. Once the Pennylane-Braket plugin is installed, the provided Braket devices can be accessed straight... -
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AWS Deep Learning Containers
A set of Docker images for training and serving models in TensorFlow
AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet. Deep Learning Containers provide optimized environments with TensorFlow and MXNet, Nvidia CUDA (for GPU instances), and Intel MKL (for CPU instances) libraries and are available in the Amazon Elastic Container Registry (Amazon ECR). The AWS DLCs are used in Amazon SageMaker as the default vehicles for your SageMaker jobs such as training, inference,... -
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smolagents
Agents write python code to call tools and orchestrate other agents
This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents. -
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AIOHTTP
Asynchronous HTTP client/server framework for asyncio and Python
Asynchronous HTTP Client/Server for asyncio and Python. AIOHTTP supports both client and server side of HTTP protocol. A long awaited new feature is tracing client request life cycle to figure out when and why client request spends a time waiting for connection establishment, getting server response headers etc. Now it is possible by registering special signal handlers on every request processing stage. The main change is dropping yield from support and using async/await everywhere. Farewell... -
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Rasa
Open source machine learning framework to automate text conversations
Rasa is an open source machine learning framework to automate text-and voice-based conversations. With Rasa, you can build contextual assistants on Facebook Messenger, Slack, Google Hangouts, Webex Teams, Microsoft Bot Framework, Rocket.Chat, Mattermost, Telegram, and Twilio or on your own custom conversational channels. Rasa helps you build contextual assistants capable of having layered conversations with lots of back-and-forths. In order for a human to have a meaningful exchange... -
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AIOGram
Framework for Telegram Bot API written in Python 3.7 with asyncio
aiogram is modern and fully asynchronous framework for Telegram Bot API written in Python with asyncio and aiohttp. It helps you to make your bots faster and simpler. Is a pretty simple and fully asynchronous framework for Telegram Bot API written in Python 3.7 with asyncio and aiohttp. -
Picsart Enterprise Background Removal API for Stunning eCommerce VisualsWith our Remove Background API tool, you can access the transformative capabilities of automation , which will allow you to turn any photo asset into compelling product imagery. With elevated visuals quality on your digital platforms, you can captivate your audience, and therefore achieve higher engagement and sales.
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Agent Zero
Agent Zero AI framework
Agent Zero is not a predefined agentic framework. It is designed to be dynamic, organically growing, and learning as you use it. Agent Zero is fully transparent, readable, comprehensible, customizable and interactive. Agent Zero uses the computer as a tool to accomplish its (your) tasks. Agents can communicate with their superiors and subordinates, asking questions, giving instructions, and providing guidance. Instruct your agents in the system prompt on how to communicate effectively... -
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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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OpenAI Agents SDK
A lightweight, powerful framework for multi-agent workflows
The OpenAI Agents Python SDK is a powerful yet lightweight framework for developing multi-agent workflows. This framework enables developers to create and manage agents that can coordinate tasks autonomously, using a set of instructions, tools, guardrails, and handoffs. The SDK allows users to configure workflows in which agents can pass control to other agents as necessary, ensuring dynamic task management. It also includes a built-in tracing system for tracking, debugging, and optimizing... -
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Agent S2
Agent S: an open agentic framework that uses computers like a human
Simular's Agent S2 represents a leap forward in the development of computer-use agents, capable of autonomously interacting with a range of devices and interfaces. By integrating specialized AI models, Agent S2 delivers state-of-the-art performance, whether on desktop systems or smartphones. Through modular architecture, it efficiently handles complex tasks, such as navigating UIs, performing low-level actions like text selection, and executing high-level strategies like planning.... -
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SeleniumBase
A framework for browser automation and testing with Selenium
SeleniumBase automatically handles common WebDriver actions such as launching web browsers before tests, saving screenshots during failures, and closing web browsers after tests. SeleniumBase lets you customize test runs from the command line. SeleniumBase uses simple syntax for commands. pytest includes automatic test discovery. If you don't specify a specific file or folder to run, pytest will automatically search through all subdirectories for tests to run. No More Flaky Tests!... -
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Advanced Alchemy
A carefully crafted, thoroughly tested, optimized companion library
advanced-alchemy is an opinionated ORM toolkit built on SQLAlchemy and designed for integration with the Litestar web framework. It simplifies common ORM patterns such as CRUD, pagination, and async support while providing extensibility and best practices out of the box. It’s designed to accelerate backend development for modern Python web apps. -
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ContextGem
ContextGem: Effortless LLM extraction from documents
ContextGem is an open-source framework designed to simplify the extraction of structured data and insights from documents using large language models (LLMs). It provides a flexible, intuitive API that minimizes boilerplate code, enabling developers to build complex extraction workflows efficiently. ContextGem supports various document formats and integrates with multiple LLM providers, making it a versatile tool for tasks like contract analysis, anomaly detection, and information retrieval. -
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Manim
A community-maintained Python framework for creating animations
A community-maintained Python library for creating mathematical animations. Manim is a free and open-source project originally written by Grant Sanderson. It is now maintained by the Manim Community and permissively released under the MIT license. Manim was originally created by Grant Sanderson as a personal project and for use in his YouTube channel, 3Blue1Brown. As his channel gained popularity, many grew to like the style of his animations and wanted to use manim for their own projects... -
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Open Autonomy
A framework for the creation of autonomous agent services
Open Autonomy is a framework that enables the development of autonomous economic agents (AEAs) capable of operating independently in various economic contexts. -
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Letta
Letta (formerly MemGPT) is a framework for creating LLM services
Letta is an AI-powered task automation framework designed to handle workflow automation, natural language commands, and AI-driven decision-making. -
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Axolotl
Go ahead and axolotl questions
Axolotl is a powerful and flexible framework for fine-tuning large language models on custom datasets. Built for researchers and developers, Axolotl simplifies the process of adapting LLMs for specific tasks, including chat, code generation, and instruction following. It supports a wide variety of model architectures and offers out-of-the-box optimization strategies for efficient training. -
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LLaMA-Factory
Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)
LLaMA-Factory is a fine-tuning and training framework for Meta's LLaMA language models. It enables researchers and developers to train and customize LLaMA models efficiently using advanced optimization techniques. -
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Self-Operating Computer
A framework to enable multimodal models to operate a computer
The Self-Operating Computer Framework is an innovative system that enables multimodal models to autonomously operate a computer by interpreting the screen and executing mouse and keyboard actions to achieve specified objectives. This framework is compatible with various multimodal models and currently integrates with GPT-4o, o1, Gemini Pro Vision, Claude 3, and LLaVa. Notably, it was the first known project to implement a multimodal model capable of viewing and controlling a computer screen... -
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Mosec
A high-performance ML model serving framework, offers dynamic batching
Mosec is a high-performance and flexible model-serving framework for building ML model-enabled backend and microservices. It bridges the gap between any machine learning models you just trained and the efficient online service API. -
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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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pep484 stubs for Django
PEP-484 stubs for Django
This package contains type stubs and a custom mypy plugin to provide more precise static types and type inference for Django framework. Django uses some Python "magic" that makes having precise types for some code patterns problematic. This is why we need this project. The final goal is to be able to get precise types for the most common patterns. We are independent from Django at the moment. There's a proposal to merge our project into the Django itself. You can show your support by liking...
