Showing 16378 open source projects for "pam-python"

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  • 1
    OpenAGI

    OpenAGI

    When LLM Meets Domain Experts

    OpenAGI is a package for AI agent creation designed to connect large language models with domain-specific tools and workflows in the AIOS (AI Operating System) ecosystem. It provides a structured Python framework, pyopenagi, for defining agents as modular units that encapsulate execution logic, configuration, and dependency metadata. Agents are organized in a well-defined folder structure that includes code (agent.py), configuration (config.json), and extra requirements (meta_requirements.txt), which makes them easy to package, share, and reuse. ...
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  • 2
    USO

    USO

    Open-sourced unified customization model

    ...By decoupling style and subject, USO enables reuse of learned style/style-embeddings across different subjects, or vice versa, which makes generation more modular and controllable. The project provides tooling (in Python) including inference and workflow scripts, example configurations, and support for generation pipelines; and as of 2025, USO is also natively supported in some mainstream generative-art UI pipelines (e.g. ComfyUI) to ease adoption.
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  • 3
    MLX-Audio

    MLX-Audio

    A text-to-speech, speech-to-text and speech-to-speech library

    ...Because it uses MLX and targets Apple Silicon, inference is fast and can take advantage of hardware acceleration and quantization for efficient on-device performance. The project provides a straightforward CLI (mlx_audio.tts.generate) as well as a Python API for programmatic generation of audio, including parameters for voice choice, speed, language hints, output format, and sample rate. It includes examples such as audiobook generation to demonstrate long-form synthesis and joined audio segments. On top of that, MLX-Audio offers a modern web interface powered by FastAPI, with real-time waveform and 3D visualizations, file upload, and audio management.
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  • 4
    Positron

    Positron

    Positron, a next-generation data science IDE

    Positron is a next-generation integrated development environment (IDE) created by Posit PBC (formerly RStudio Inc) specifically tailored for data science workflows in Python, R, and multi-language ecosystems. It aims to unify exploratory data analysis, production code, and data-app authoring in a single environment so that data scientists move from “question → insight → application” without switching tools. Built on the open-source Code-OSS foundation, Positron provides a familiar coding experience along with specialized panes and tooling for variable inspection, data-frame viewing, plotting previews, and interactive consoles designed for analytical work. ...
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  • 5
    AWS SDK for pandas

    AWS SDK for pandas

    Easy integration with Athena, Glue, Redshift, Timestream, Neptune

    ...The library abstracts efficient patterns like partitioning, compression, and vectorized I/O so you get performant data lake operations without hand-rolling boilerplate. It also supports Redshift, OpenSearch, and other services, enabling ETL tasks that blend SQL engines and Python transformations. Operational helpers handle IAM, sessions, and concurrency while exposing knobs for encryption, versioning, and catalog consistency. The result is a productive workflow that keeps your analytics in Python while leveraging AWS-native storage and query engines at scale.
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  • 6
    YAPF

    YAPF

    A formatter for Python files

    YAPF is a Python code formatter that automatically rewrites source to match a chosen style, using a clang-format–inspired algorithm to search for the “best” layout under your rules. Instead of relying on a fixed set of heuristics, it explores formatting decisions and chooses the lowest-cost result, aiming to produce code a human would write when following a style guide.
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  • 7
    deepdoctection

    deepdoctection

    A Repo For Document AI

    DeepDoctection is a document AI framework that applies deep learning techniques to analyze and extract structured data from scanned documents, PDFs, and images. deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated frameworks for fine-tuning, evaluating and running models. ...
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  • 8
    Atomic Agents

    Atomic Agents

    Building AI agents, atomically

    ...The framework provides a set of tools and agents that can be combined to create powerful applications. It is built on top of Instructor and leverages the power of Pydantic for data and schema validation and serialization. All logic and control flows are written in Python, enabling developers to apply familiar best practices and workflows from traditional software development without compromising flexibility or clarity.
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  • 9
    smolagents

    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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  • 10
    OAuthLib

    OAuthLib

    A generic, spec-compliant, thorough implementation of the OAuth

    A generic, spec-compliant, thorough implementation of the OAuth request-signing logic for Python 3.8+. OAuthLib is a framework which implements the logic of OAuth1 or OAuth2 without assuming a specific HTTP request object or web framework. 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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  • 11
    PyQuil

    PyQuil

    A Python library for quantum programming using Quil

    PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. PyQuil serves three main functions. PyQuil has a ton of other features, which you can learn more about in the docs. However, you can also keep reading below to get started with running your first quantum program. Without installing anything, you can quickly get started with quantum programming by exploring our interactive Jupyter Notebook tutorials and examples. ...
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  • 12
    Translate Toolkit

    Translate Toolkit

    Useful localization tools with Python API for building localization

    The localization engineers' Swiss Army Knife. Use it to convert, count, manipulate, review and debug texts. Tools that you can expand, adapt, and grow. Convert between a number of localization, translation and software formats. Allowing you and your translators to work on industry-standard translation formats. Search for pattern matches. Run tests that adapt to languages and source projects. Extract terminology. A large toolset to allow you to increase localization quality. The code is...
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  • 13
    Pretty Jupyter

    Pretty Jupyter

    Creates dynamic html report from jupyter notebook.

    Pretty Jupyter is an easy-to-use package that allows to create beautiful & dynamic HTML reports. Most of the features require little to no work to get working and greatly improve the quality of the output report, or even the developer’s comfort when creating the report. For example, tabs make some visualizations much more comfortable. The features are integrated directly into the output page, therefore there is no need to have an interpreter running in the backend. This makes the HTML easily...
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  • 14
    SuperDuperDB

    SuperDuperDB

    Integrate, train and manage any AI models and APIs with your database

    Build and manage AI applications easily without needing to move your data to complex pipelines and specialized vector databases. Integrate AI and vector search directly with your database including real-time inference and model training. Just using Python. A single scalable deployment of all your AI models and APIs which is automatically kept up-to-date as new data is processed immediately. No need to introduce an additional database and duplicate your data to use vector search and build on top of it. SuperDuperDB enables vector search in your existing database. Integrate and combine models from Sklearn, PyTorch, HuggingFace with AI APIs such as OpenAI to build even the most complex AI applications and workflows. ...
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  • 15
    ChatGPT Academic

    ChatGPT Academic

    ChatGPT extension for scientific research work

    ChatGPT extension for scientific research work, specially optimized academic paper polishing experience, supports custom shortcut buttons, supports custom function plug-ins, supports markdown table display, double display of Tex formulas, complete code display function, new local Python/C++/Go project tree Analysis function/Project source code self-translation ability, newly added PDF and Word document batch summary function/PDF paper full-text translation function. All buttons are dynamically generated by reading functional.py, you can add custom functions at will, and liberate the pasteboard. Support for markdown tables output by GPT. ...
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  • 16
    django-webpack-loader

    django-webpack-loader

    Transparently use webpack with django

    Use webpack to generate your static bundles without django's static files or opaque wrappers. Django webpack loader consumes the output generated by webpack-bundle-tracker and lets you use the generated bundles in Django. Test cases cover Django>=2.0 on Python>=3.5. 100% code coverage is the target so we can be sure everything works anytime. It should probably work on older versions of Django as well but the package does not ship any test cases for them. Before configuring django-webpack-loader, let's first configure what's necessary on the webpack-bundle-tracker side. Update your Webpack configuration file (it's usually on webpack.config.js in the project root). ...
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  • 17
    Django OAuth Toolkit

    Django OAuth Toolkit

    OAuth2 goodies for the Djangonauts!

    ...OAuth is an open standard for access delegation, commonly used as a way for Internet users to grant websites or applications access to their information on other websites but without giving them the passwords. Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. Built by experienced developers, it takes care of much of the hassle of Web development, so you can focus on writing your app without needing to reinvent the wheel. Your Django app exposes a web API you want to protect with OAuth2 authentication. You need to implement an OAuth2 authorization server to provide tokens management for your infrastructure.
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  • 18
    TorchMetrics

    TorchMetrics

    Machine learning metrics for distributed, scalable PyTorch application

    ...Automatic synchronization between multiple devices. Metric arithmetic. Similar to torch.nn, most metrics have both a module-based and a functional version. The functional versions are simple python functions that as input take torch.tensors and return the corresponding metric as a torch.tensor.
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  • 19
    ktrain

    ktrain

    ktrain is a Python library that makes deep learning AI more accessible

    ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners.
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  • 20
    Audiomentations

    Audiomentations

    A Python library for audio data augmentation

    A Python library for audio data augmentation. Inspired by albumentations. Useful for deep learning. Runs on CPU. Supports mono audio and multichannel audio. Can be integrated in training pipelines in e.g. Tensorflow/Keras or Pytorch. Has helped people get world-class results in Kaggle competitions. Is used by companies making next-generation audio products.
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  • 21
    TorchRec

    TorchRec

    Pytorch domain library for recommendation systems

    TorchRec is a PyTorch domain library built to provide common sparsity & parallelism primitives needed for large-scale recommender systems (RecSys). It allows authors to train models with large embedding tables sharded across many GPUs. Parallelism primitives that enable easy authoring of large, performant multi-device/multi-node models using hybrid data-parallelism/model-parallelism. The TorchRec sharder can shard embedding tables with different sharding strategies including data-parallel,...
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  • 22
    PennyLane

    PennyLane

    A cross-platform Python library for differentiable programming

    A cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural network. Built-in automatic differentiation of quantum circuits, using the near-term quantum devices directly. You can combine multiple quantum devices with classical processing arbitrarily! Support for hybrid quantum and classical models, and compatible with existing machine learning libraries.
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  • 23
    Oppia

    Oppia

    A free, online learning platform to make quality education accessible

    ...In addition to developing the Oppia platform, the team is also developing and piloting a set of free and effective lessons on basic mathematics. These lessons are targeted at learners who lack access to educational resources. Oppia is written using Python and AngularJS, and is built on top of Google App Engine.
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  • 24
    Vedo

    Vedo

    A python module for scientific analysis of 3D data

    A lightweight and powerful python module for scientific analysis and visualization of 3d objects. Inspired by the vpython manifesto "3D programming for ordinary mortals", vedo makes it easy to work with 3D pointclouds, meshes and volumes, in just a few lines of code, even for less experienced programmers. vedo is based on VTK and numpy, with no other dependencies.
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  • 25
    Autograd

    Autograd

    Efficiently computes derivatives of numpy code

    Autograd can automatically differentiate native Python and Numpy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily. ...
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