Search Results for "python framework" - Page 6
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Showing 1765 open source projects for "python framework"
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asyncpg
A fast PostgreSQL Database Client Library for Python/asyncio
asyncpg is a high-performance PostgreSQL client library designed for Python's asyncio framework. It offers a clean and efficient implementation of the PostgreSQL server binary protocol, enabling developers to execute database operations asynchronously. This approach allows for scalable and responsive applications that can handle numerous concurrent database connections. -
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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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SIA
AI framework to autonomously improve the performance of any AI system
SIA is a self-improving AI framework designed to improve the performance of models or agents on benchmark tasks. It uses an iterative loop where a meta-agent creates or updates a task-specific target agent, while a feedback agent studies results and proposes improvements. The framework can refine both the harness around the task and the agent implementation itself. It is aimed at research and experimentation across tasks such as machine learning benchmarks, legal classification, code... -
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TensorFlow Quantum
Open-source Python framework for hybrid quantum-classical ml learning
TensorFlow Quantum is an open-source software framework designed for building and training hybrid quantum-classical machine learning models within the TensorFlow ecosystem. The framework enables researchers and developers to represent quantum circuits as data and integrate them directly into machine learning workflows. By combining classical deep learning techniques with quantum algorithms, the platform allows experimentation with quantum machine learning methods that may offer advantages... -
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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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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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Substra
Low-level Python library used to interact with a Substra network
An open-source framework supporting privacy-preserving, traceable federated learning and machine learning orchestration. Offers a Python SDK, high-level FL library (SubstraFL), and web UI to define datasets, models, tasks, and orchestrate secure, auditable collaborations. -
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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. The... -
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TapeAgents
A framework that facilitates all stages of LLM development
TapeAgents is a framework that facilitates all stages of the Large Language Model (LLM) agent development lifecycle, providing tools for building, testing, and deploying AI agents. -
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Google Antigravity SDK
Python library for building agents that leverages Google Antigravity
...It supports streaming responses, stateful sessions, custom Python tools, MCP server integration, hooks, policies, and event-driven triggers. The package relies on a compiled runtime binary distributed through platform-specific PyPI wheels, so installation from PyPI is required for normal use. Its main value is giving developers a structured Python framework for creating local, tool-using, multimodal, policy-controlled AI agents. -
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EvoAgentX
Self-evolving AI agent framework for automated workflows
EvoAgentX is an open source framework for building, evaluating, and continuously improving LLM-based agents and multi-agent workflows. It moves beyond static pipelines by introducing a self-evolving system where agents are automatically generated, tested, and optimised through iterative feedback. Developers can define goals in natural language, while the framework handles workflow creation, execution, and refinement. Its modular architecture supports layered components for agents, workflows,... -
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Cosmos-RL
Cosmos-RL is a flexible and scalable Reinforcement Learning framework
Cosmos-RL is a scalable reinforcement learning framework designed specifically for physical AI systems such as robotics, autonomous agents, and multimodal models. It provides a distributed training architecture that separates policy learning and environment rollout processes, enabling efficient and asynchronous reinforcement learning at scale. The framework supports multiple parallelism strategies, including tensor, pipeline, and data parallelism, allowing it to leverage large GPU clusters... -
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TNT
A lightweight library for PyTorch training tools and utilities
TNT is a lightweight training framework developed by Meta that simplifies the process of building and managing machine learning training loops using PyTorch. The project focuses on providing a flexible yet structured environment for implementing training pipelines without the complexity of large deep learning frameworks. It introduces modular abstractions that allow developers to organize training logic into reusable components such as trainers, evaluators, and callbacks. This design helps... -
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Oumi
Everything you need to build state-of-the-art foundation models
Oumi is an open-source framework that provides everything needed to build state-of-the-art foundation models, end-to-end. It aims to simplify the development of large-scale machine-learning models. -
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Agently 4
Build GenAI application quick and easy
Agently is a Python framework for building generative-AI (“GenAI”) applications; it focuses on enabling developers to orchestrate AI agents, workflows, and event-driven logic in a robust, reusable way. With Agently, one can define agents that call different models, chain tasks, trigger workflows based on events, and switch models with minimal code changes. -
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DrissionPage
Python based web automation tool. Powerful and elegant
DrissionPage is a Python-based automation framework that blends the capabilities of Selenium for browser automation with Requests-HTML for fast, headless web data extraction. It enables seamless switching between browser-controlled and headless HTTP sessions within the same interface. Ideal for web scraping, testing, and automation, DrissionPage is lightweight and highly efficient, offering more flexibility than standard Selenium or Requests usage alone. -
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robosuite
A Modular Simulation Framework and Benchmark for Robot Learning
Robosuite is a modular and extensible simulation framework for robotic manipulation tasks, built on top of MuJoCo. Developed by the ARISE Initiative, Robosuite offers a set of standardized benchmarks and customizable environments designed to advance research in robotic manipulation, control, and imitation learning. It emphasizes realistic simulations and ease of use for both single-task and multi-task learning. -
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Scrapy
A fast, high-level web crawling and web scraping framework
Scrapy is a fast, open source, high-level framework for crawling websites and extracting structured data from these websites. Portable and written in Python, it can run on Windows, Linux, macOS and BSD. Scrapy is powerful, fast and simple, and also easily extensible. Simply write the rules to extract the data, and add new functionality if you wish without having to touch the core. -
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AI Berkshire
AI-era Berkshire: a value investing research framework
AI Berkshire is an AI-assisted value investing research framework designed for Claude Code and Codex workflows. It turns the investment methods of Warren Buffett, Charlie Munger, Duan Yongping, and Li Lu into structured research agents. The project is meant to improve research depth, decision discipline, and analytical consistency compared with asking a general AI model for a one-off stock opinion. It uses parallel agent analysis, adversarial viewpoints, financial rigor checks, and... -
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Pixeltable
Data Infrastructure providing an approach to multimodal AI workloads
Pixeltable is an open-source Python data infrastructure framework designed to support the development of multimodal AI applications. The system provides a declarative interface for managing the entire lifecycle of AI data pipelines, including storage, transformation, indexing, retrieval, and orchestration of datasets. Unlike traditional architectures that require multiple tools such as databases, vector stores, and workflow orchestrators, Pixeltable unifies these functions within a table-based abstraction. ... -
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Orca Core
Core Python Controller of the ORCA Hand
Orca Core is the central Python control framework for the ORCA Hand, an open-source dexterous robotic hand designed to replicate human-like manipulation capabilities. It provides a high-level abstraction layer over the underlying hardware, allowing developers to interact with the robotic system through simplified joint-space commands rather than low-level motor instructions. -
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Alibi Detect
Algorithms for outlier, adversarial and drift detection
Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline detectors for tabular data, text, images and time series. Both TensorFlow and PyTorch backends are supported for drift detection. -
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Ludwig AI
Low-code framework for building custom LLMs, neural networks
Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed),... -
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Sanic
Async Python 3.6+ web server/framework
Build fast, run fast with Sanic! Sanic is a Python 3.6+ web server and web framework designed to go fast. It provides a way to get a highly performant HTTP server up and running fast, while also making it easy to build, expand, and eventually scale. Sanic aspires to be as simple as possible while delivering the performance that you require. It allows the usage of the async/await syntax added in Python 3.5, so your code is guaranteed to be non-blocking and speedy. ... -
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LOTUS
AI-Powered Data Processing: Use LOTUS to process all of your datasets
LOTUS is an open-source framework and query engine designed to enable efficient processing of structured and unstructured datasets using large language models. The system provides a declarative programming model that allows developers to express complex AI data operations using high-level commands rather than manually orchestrating model calls. It offers a Python interface with a Pandas-like API, making it familiar for data scientists and engineers already working with data analysis libraries. ...
