Showing 751 open source projects for "python framework"

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  • 1
    Giskard

    Giskard

    Collaborative & Open-Source Quality Assurance for all AI models

    The testing framework dedicated to ML models, from tabular to LLMs. Giskard is an open-source testing framework dedicated to ML models, from tabular models to LLMs. Testing Machine Learning applications can be tedious. Since ML models depend on data, testing scenarios depend on the domain specificities and are often infinite. At Giskard, we believe that Machine Learning needs its own testing framework. Created by ML engineers for ML engineers, Giskard enables you to scan your model to find...
    Downloads: 1 This Week
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  • 2
    Self-Operating Computer

    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....
    Downloads: 8 This Week
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  • 3
    AgentForge

    AgentForge

    Extensible AGI Framework

    AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications.
    Downloads: 13 This Week
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  • 4
    FastMCP

    FastMCP

    The fast, Pythonic way to build Model Context Protocol servers

    FastMCP is a fast, Pythonic framework for building servers and clients using the Model Context Protocol (MCP). It abstracts away protocol complexity like serialization, validation, and error handling, letting developers focus entirely on their business logic. With simple decorators, you can expose Python functions as tools, resources, or prompts that AI agents can safely and efficiently use.
    Downloads: 2 This Week
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    CrewAI

    CrewAI

    Framework for orchestrating role-playing, autonomous AI agents

    Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. The power of AI collaboration has too much to offer. CrewAI is designed to enable AI agents to assume roles, share goals, and operate in a cohesive unit - much like a well-oiled crew. Whether you're building a smart assistant platform, an automated customer service ensemble, or a multi-agent research team, CrewAI...
    Downloads: 20 This Week
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  • 6
    IVY

    IVY

    The Unified Machine Learning Framework

    Take any code that you'd like to include. For example, an existing TensorFlow model, and some useful functions from both PyTorch and NumPy libraries. Choose any framework for writing your higher-level pipeline, including data loading, distributed training, analytics, logging, visualization etc. Choose any backend framework which should be used under the hood, for running this entire pipeline. Choose the most appropriate device or combination of devices for your needs. DeepMind releases an...
    Downloads: 0 This Week
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  • 7
    Agent S

    Agent S

    Agent S: an open agentic framework that uses computers like a human

    Agent S is an open-source agentic framework designed to enable autonomous computer use through an Agent-Computer Interface (ACI). Built to operate graphical user interfaces like a human, it allows AI agents to perceive screens, reason about tasks, and execute actions across macOS, Windows, and Linux systems. The latest version, Agent S3, surpasses human-level performance on the OSWorld benchmark, demonstrating state-of-the-art results in complex multi-step computer tasks. Agent S combines...
    Downloads: 12 This Week
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  • 8
    NoneBot

    NoneBot

    Asynchronous multi-platform robot framework written in Python

    ...Asynchronous priority development to improve operational efficiency. Simple and clear dependency injection system, built-in dependency functions reduce user code. NoneBot2 is a modern, cross-platform, and extensible Python chatbot framework. It is based on Python's type annotations and asynchronous features, and can provide convenient and flexible support for your needs. NoneBot2 is written based on Python asyncio , and has a certain degree of synchronous function compatibility based on the asynchronous mechanism. NoneBot2 provides an easy-to-use, interactive command-line tool -- nb-cli, making it easier to get started with NoneBot2 for the first time. ...
    Downloads: 1 This Week
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  • 9
    mosaicml composer

    mosaicml composer

    Supercharge Your Model Training

    composer is a deep learning training framework built on PyTorch and designed to make large-scale model training more efficient, scalable, and customizable. At the center of the project is a highly optimized Trainer abstraction that simplifies the management of training loops, parallelization, metrics, logging, and data loading. The framework is intended for modern workloads that may span anything from a single GPU to very large distributed training environments, which makes it suitable for...
    Downloads: 7 This Week
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  • 10
    LightAutoML

    LightAutoML

    Fast and customizable framework for automatic ML model creation

    LightAutoML is an automated machine learning (AutoML) framework optimized for efficient model training and hyperparameter tuning, focusing on both tabular and text data.
    Downloads: 0 This Week
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  • 11
    II Agent

    II Agent

    A new open-source framework to build and deploy intelligent agents

    II-Agent is an open-source intelligent assistant framework designed to automate complex workflows across multiple domains using large language models and external tools. The platform allows users to interact with multiple AI models within a single environment while connecting those models to external services and knowledge sources. Through a unified interface, users can switch between models, access specialized tools, and execute tasks that require information retrieval, code execution, or...
    Downloads: 5 This Week
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  • 12
    bitnet.cpp

    bitnet.cpp

    Official inference framework for 1-bit LLMs

    bitnet.cpp is the official open-source inference framework and ecosystem designed to enable ultra-efficient execution of 1-bit large language models (LLMs), which quantize most model parameters to ternary values (-1, 0, +1) while maintaining competitive performance with full-precision counterparts. At its core is bitnet.cpp, a highly optimized C++ backend that supports fast, low-memory inference on both CPUs and GPUs, enabling models such as BitNet b1.58 to run without requiring enormous...
    Downloads: 5 This Week
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  • 13
    STORM

    STORM

    An LLM-powered knowledge curation system that researches topics

    STORM is an open-source virtual assistant framework developed by Stanford's OVAL lab. It is designed for creating natural language interfaces and assistants that can interact with APIs, databases, and services in a modular way.
    Downloads: 9 This Week
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  • 14
    MetaGPT

    MetaGPT

    The Multi-Agent Framework

    The Multi-Agent Framework: Given one line Requirement, return PRD, Design, Tasks, Repo. Assign different roles to GPTs to form a collaborative software entity for complex tasks. MetaGPT takes a one-line requirement as input and outputs user stories / competitive analysis/requirements/data structures / APIs / documents, etc. Internally, MetaGPT includes product managers/architects/project managers/engineers. It provides the entire process of a software company along with carefully orchestrated SOPs.
    Downloads: 17 This Week
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  • 15
    CLI-Anything

    CLI-Anything

    Making ALL Software Agent-Native

    CLI-Anything is a framework designed to transform traditional software applications into agent-native command-line interfaces that can be directly controlled by AI systems. It is built on the idea that the command-line interface is the most universal, structured, and composable interface for both humans and AI agents, enabling deterministic and predictable execution of workflows. The system provides a methodology and tooling for generating CLI wrappers around existing applications, allowing...
    Downloads: 6 This Week
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  • 16
    MONAI

    MONAI

    AI Toolkit for Healthcare Imaging

    The MONAI framework is the open-source foundation being created by Project MONAI. MONAI is a freely available, community-supported, PyTorch-based framework for deep learning in healthcare imaging. It provides domain-optimized foundational capabilities for developing healthcare imaging training workflows in a native PyTorch paradigm. Project MONAI also includes MONAI Label, an intelligent open source image labeling and learning tool that helps researchers and clinicians collaborate, create...
    Downloads: 7 This Week
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  • 17
    AgentRun

    AgentRun

    The easiest, and fastest way to run AI-generated Python code safely

    AgentRun is a framework for building autonomous AI agents capable of executing complex tasks with minimal human intervention. It provides a structured environment for defining agent behaviors, managing workflows, and integrating AI models to achieve specific goals.
    Downloads: 7 This Week
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  • 18
    IntentKit

    IntentKit

    An open and fair framework for everyone to build AI agents

    IntentKit is a natural language understanding (NLU) library focused on intent recognition and entity extraction, enabling developers to build conversational AI applications.
    Downloads: 8 This Week
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  • 19
    PaperAI

    PaperAI

    Semantic search and workflows for medical/scientific papers

    PaperAI is an open-source framework for searching and analyzing scientific papers, particularly useful for researchers looking to extract insights from large-scale document collections.
    Downloads: 8 This Week
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  • 20
    C3

    C3

    The goal of CLAIMED is to enable low-code/no-code rapid prototyping

    C3 is an open-source framework designed to simplify the development and deployment of data science and machine learning workflows through reusable components and low-code development techniques. The framework focuses on enabling rapid prototyping while maintaining a path to production through automated CI/CD integration. CLAIMED provides a component-based architecture where data processing steps, models, and workflows can be packaged into reusable operators. These operators can be...
    Downloads: 4 This Week
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  • 21
    Agentic Context Engine

    Agentic Context Engine

    Make your agents learn from experience

    Agentic Context Engine (ACE) is an open-source framework designed to help AI agents improve their performance by learning from their own execution history. Instead of relying solely on model training or fine-tuning, the framework focuses on structured context engineering, allowing agents to accumulate knowledge from past successes and failures during task execution. The system treats context as a dynamic “playbook” that evolves over time through a process of generation, reflection, and...
    Downloads: 4 This Week
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  • 22
    Synthetic Data Generator

    Synthetic Data Generator

    SDG is a specialized framework

    Synthetic Data Generator is an open-source framework designed to generate high-quality synthetic tabular datasets that replicate the statistical characteristics of real data while avoiding privacy risks. The platform enables developers and data scientists to create artificial datasets that preserve important relationships between variables without containing sensitive personal information. This makes the generated data suitable for tasks such as machine learning model training, testing...
    Downloads: 4 This Week
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  • 23
    caveman

    caveman

    Why use many token when few token do trick

    Caveman is a lightweight and experimental project focused on simplifying backend or full-stack development workflows through minimalistic abstractions and rapid prototyping principles. It is designed to reduce the complexity of modern frameworks by offering a stripped-down approach that prioritizes speed, clarity, and ease of use. The project often serves as a foundation for developers who want to build applications quickly without being constrained by heavy conventions or extensive...
    Downloads: 4 This Week
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  • 24
    pyAudioAnalysis

    pyAudioAnalysis

    Python Audio Analysis Library: Feature Extraction, Classification

    ...Because the library integrates machine learning algorithms with signal processing tools, it enables researchers to develop complete audio analysis pipelines using a single framework.
    Downloads: 0 This Week
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  • 25
    DOLMA

    DOLMA

    Data and tools for generating and inspecting OLMo pre-training data

    DOLMA (Data Optimization and Learning for Model Alignment) is a framework designed to manage large-scale datasets for training and fine-tuning language models efficiently.
    Downloads: 7 This Week
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