Showing 17428 open source projects for "source"

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  • 1
    rLLM

    rLLM

    Democratizing Reinforcement Learning for LLMs

    rLLM is an open-source framework for building and training post-training language agents via reinforcement learning — that is, using reinforcement signals to fine-tune or adapt language models (LLMs) into customizable agents for real-world tasks. With rLLM, developers can define custom “agents” and “environments,” and then train those agents via reinforcement learning workflows, possibly surpassing what vanilla fine-tuning or supervised learning might provide.
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  • 2
    openbench

    openbench

    Provider-agnostic, open-source evaluation infrastructure

    openbench is an open-source, provider-agnostic evaluation infrastructure designed to run standardized, reproducible benchmarks on large language models (LLMs), enabling fair comparison across different model providers. It bundles dozens of evaluation suites — covering knowledge, reasoning, math, code, science, reading comprehension, long-context recall, graph reasoning, and more — so users don’t need to assemble disparate datasets themselves.
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  • 3
    PokeeResearch-7B

    PokeeResearch-7B

    Pokee Deep Research Model Open Source Repo

    PokeeResearchOSS provides an open-source, agentic “deep research” model centered on a 7B backbone that can browse, read, and synthesize current information from the web. Instead of relying only on static training data, the agent performs searches, visits pages, and extracts evidence before forming answers to complex queries. It is built to operate end-to-end: planning a research strategy, gathering sources, reasoning over conflicting claims, and writing a grounded response.
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  • 4
    Web Dev for Beginners

    Web Dev for Beginners

    About 24 Lessons, 12 Weeks, Get Started as a Web Developer

    Web-Dev-For-Beginners is Microsoft’s open source, project-based curriculum for learning web development from scratch. Designed as a 12-week, 24-lesson course, it covers HTML, CSS, and JavaScript fundamentals through hands-on projects like terrariums, browser extensions, and space games. Each lesson includes a mix of pre-lecture quizzes, written content, assignments, challenges, and post-lecture quizzes to reinforce learning.
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  • 5
    The Algorithms Python

    The Algorithms Python

    All Algorithms implemented in Python

    The Algorithms-Python project is a comprehensive collection of Python implementations for a wide range of algorithms and data structures. It serves primarily as an educational resource for learners and developers who want to understand how algorithms work under the hood. Each implementation is designed with clarity in mind, favoring readability and comprehension over performance optimization. The project covers various domains including mathematics, cryptography, machine learning, sorting,...
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  • 6
    MemU

    MemU

    MemU is an open-source memory framework for AI companions

    MemU is an agentic memory layer for LLM applications, specifically designed for AI companions. Transform your memory into an intelligent file system that automatically organizes, connects, and evolves with your memories. Simple, fast, and reliable memory infrastructure for AI applications. Powerful tools and dedicated support to scale your AI applications with confidence. Full proprietary features, commercial usage rights, and white-labeling options for your enterprise needs. SSO/RBAC...
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  • 7
    Portia SDK Python

    Portia SDK Python

    Portia Labs Python SDK for building agentic workflows

    portia‑sdk‑python is an open-source Python SDK by Portia Labs for creating reliable, stateful, authenticated multi-agent AI workflows. It supports tool-backed agents capable of real-world interactions—like web browsing, API access, and human-in-the-loop clarifications—while maintaining transparency and auditability through structured plans and execution hooks. Designed for production environments, the SDK integrates with local or cloud LLMs (e.g.
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  • 8
    Lithops

    Lithops

    A multi-cloud framework for big data analytics

    Lithops is an open-source serverless computing framework that enables transparent execution of Python functions across multiple cloud providers and on-prem infrastructure. It abstracts cloud providers like IBM Cloud, AWS, Azure, and Google Cloud into a unified interface and turns your Python functions into scalable, event-driven workloads. Lithops is ideal for data processing, ML inference, and embarrassingly parallel workloads, giving you the power of FaaS (Function-as-a-Service) without vendor lock-in. ...
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  • 9
    Godot RL Agents

    Godot RL Agents

    An Open Source package that allows video game creators

    godot_rl_agents is a reinforcement learning integration for the Godot game engine. It allows AI agents to learn how to interact with and play Godot-based games using RL algorithms. The toolkit bridges Godot with Python-based RL libraries like Stable-Baselines3, making it possible to create complex and visually rich RL environments natively in Godot.
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  • 10
    Lingua-Py

    Lingua-Py

    The most accurate natural language detection library for Python

    Its task is simple: It tells you which language some text is written in. This is very useful as a preprocessing step for linguistic data in natural language processing applications such as text classification and spell checking. Other use cases, for instance, might include routing e-mails to the right geographically located customer service department, based on the e-mails' languages. Language detection is often done as part of large machine learning frameworks or natural language processing...
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  • 11
    TruLens

    TruLens

    Evaluation and Tracking for LLM Experiments

    TruLens is an open-source Python library designed to systematically evaluate and track Large Language Model (LLM) applications. It provides fine-grained instrumentation, feedback functions, and a user interface to compare and iterate on app versions, facilitating rapid development and improvement of LLM-based applications. Programmatic tools that assess the quality of inputs, outputs, and intermediate results from LLM applications, enabling scalable evaluation.
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  • 12
    SageMaker Python SDK

    SageMaker Python SDK

    Training and deploying machine learning models on Amazon SageMaker

    SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the SDK, you can train and deploy models using popular deep learning frameworks Apache MXNet and TensorFlow. You can also train and deploy models with Amazon algorithms, which are scalable implementations of core machine learning algorithms that are optimized for SageMaker and GPU training.
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  • 13
    OpenLIT

    OpenLIT

    OpenLIT is an open-source LLM Observability tool

    OpenLIT is an OpenTelemetry-native tool designed to help developers gain insights into the performance of their LLM applications in production. It automatically collects LLM input and output metadata and monitors GPU performance for self-hosted LLMs. OpenLIT makes integrating observability into GenAI projects effortless with just a single line of code. Whether you're working with popular LLM providers such as OpenAI and HuggingFace, or leveraging vector databases like ChromaDB, OpenLIT...
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  • 14
    Maestral

    Maestral

    Open-source Dropbox client for macOS and Linux

    Maestral is a lightweight Dropbox client for macOS and Linux. It provides powerful command line tools, supports gitignore patterns to exclude local files from syncing, and allows syncing multiple Dropbox accounts. The CLI allows configuring an unlimited number of Dropbox accounts. Just pass a new config name when linking a new account. More fine-grained controls in the GUI and command line interface allow excluding individual files with selective sync. Maestral is not an official Dropbox...
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  • 15
    Qtile

    Qtile

    A full-featured, hackable tiling window manager written in Python

    A full-featured, hackable tiling window manager written and configured in Python. Optimize your workflow by configuring your environment to fit how you work. Efficiently use screen real-estate by automatically arranging windows with minimal visual cruft. Save your wrists from RSI by ditching the mouse and driving with the keyboard. Qtile is simple, small, and extensible. It's easy to write your own layouts, widgets, and built-in commands. Qtile is written and configured entirely in Python....
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  • 16
    OpenFermion

    OpenFermion

    The electronic structure package for quantum computers

    OpenFermion is an open source library for compiling and analyzing quantum algorithms to simulate fermionic systems, including quantum chemistry. Among other functionalities, this version features data structures and tools for obtaining and manipulating representations of fermionic and qubit Hamiltonians. For more information, see our release paper. Currently, OpenFermion is tested on Mac, Windows, and Linux.
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  • 17
    LinkChecker

    LinkChecker

    Check links in web documents or full websites

    ...The version in the pip repository may be old, to find out how to get the latest code, plus platform-specific information and other advice see doc/install.txt in the source code archive. If you do not want to install any additional libraries/dependencies you can use the Docker image which is published on GitHub Packages.
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  • 18
    rich

    rich

    Rich is a Python library for rich text and beautiful formatting

    The Rich API makes it easy to add color and style to terminal output. Rich can also render pretty tables, progress bars, markdown, syntax highlighted source code, tracebacks, and more, out of the box. Rich is a Python library for rich text and beautiful formatting in the terminal. Rich works with Linux, OSX, and Windows. True color/emoji works with new Windows Terminal, classic terminal is limited to 16 colors. Rich requires Python 3.7 or later. Effortlessly add rich output to your application, you can import the rich print method, which has the same signature as the builtin Python function. ...
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  • 19
    Petastorm

    Petastorm

    Petastorm library enables single machine or distributed training

    Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code. Petastorm is an open-source data access library developed at Uber ATG. This library enables single machine or distributed training and evaluation of deep learning models directly from datasets in Apache Parquet format. Petastorm supports popular Python-based machine learning (ML) frameworks such as Tensorflow, PyTorch, and PySpark. It can also be used from pure Python code. ...
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  • 20
    wemake-python-styleguide

    wemake-python-styleguide

    The strictest and most opinionated python linter ever!

    Welcome to the strictest and most opinionated Python linter ever. wemake-python-styleguide is actually a flake8 plugin with some other plugins as dependencies. Ensures consistency - no matter who works on it, the end product will always be the same dependable code. Helps avoid potential bugs - strict rules make sure that you don't make common mistakes. Efficient code reviews - each piece of code has a similar familiar style and syntax. If it passes all the checks, there's little left to...
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  • 21
    Buildbot

    Buildbot

    Python-based continuous integration testing framework

    Buildbot is an open-source framework for automating software build, test, and release processes. At its core, Buildbot is a job scheduling system: it queues jobs, executes the jobs when the required resources are available, and reports the results. Your Buildbot installation has one or more masters and a collection of workers. The masters monitor source-code repositories for changes, coordinate the activities of the workers, and report results to users and developers. ...
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  • 22
    statsmodels

    statsmodels

    Statsmodels, statistical modeling and econometrics in Python

    ...An extensive list of result statistics are available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all of the one-parameter exponential family distributions. Markov switching models (MSAR), also known as Hidden Markov Models (HMM). Vector autoregressive models, VAR and structural VAR. Vector error correction model, VECM. Robust linear models with support for several M-estimators. statsmodels supports specifying models using R-style formulas and pandas DataFrames.
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  • 23
    Pwntools

    Pwntools

    CTF framework and exploit development library

    Pwntools is a CTF framework and exploit development library. Written in Python, it is designed for rapid prototyping and development, and intended to make exploit writing as simple as possible. Whether you’re using it to write exploits, or as part of another software project will dictate how you use it. Historically pwntools was used as a sort of exploit-writing DSL. Simply doing from pwn import in a previous version of pwntools would bring all sorts of nice side-effects. This version...
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  • 24
    GELab-Zero

    GELab-Zero

    GUI Exploration Lab. One of the best GUI agent solutions

    ...Because GELab-Zero is fully open-source and doesn’t require external services, it offers privacy and control: everything runs locally under your control. The project provides a lightweight base model (4B parameters in its public release) that can run on modest hardware (depending on quantization), making it more accessible than many large-scale AI solutions.
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  • 25
    Hypothesis

    Hypothesis

    The property-based testing library for Python

    Hypothesis is a powerful library for property-based testing in Python. Instead of writing specific test cases, users define properties and Hypothesis generates random inputs to uncover edge cases and bugs. It integrates with unittest and pytest, shrinking failing examples to minimal reproducible cases. Widely adopted in production systems, Hypothesis boosts code reliability by exploring input spaces far beyond manually crafted tests.
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