Open Source Python Software - Page 31
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Browse free open source Python Software and projects below. Use the toggles on the left to filter open source Python Software by OS, license, language, programming language, and project status.
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An open source framework for LC-MS based proteomics and metabolomics. OpenMS offers data structures and algorithms for the processing of mass spectrometry data. The library is written in C++. Our source code and wiki lives on GitHub (https://github.com/OpenMS/OpenMS).
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AirLLM
AirLLM 70B inference with single 4GB GPU
AirLLM is an open source Python library that enables extremely large language models to run on consumer hardware with very limited GPU memory. The project addresses one of the main barriers to local LLM experimentation by introducing a memory-efficient inference technique that loads model layers sequentially rather than storing the entire model in GPU memory. This layer-wise inference approach allows models with tens of billions of parameters to run on devices with only a few gigabytes of VRAM. AirLLM preprocesses model weights so that each transformer layer can be loaded independently during computation, reducing the memory footprint while still performing full inference. As a result, developers can experiment with models that previously required specialized high-end GPUs. -
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AudioCraft
Audiocraft is a library for audio processing and generation
AudioCraft is a PyTorch library for text-to-audio and text-to-music generation, packaging research models and tooling for training and inference. It includes MusicGen for music generation conditioned on text (and optionally melody) and AudioGen for text-conditioned sound effects and environmental audio. Both models operate over discrete audio tokens produced by a neural codec (EnCodec), which acts like a tokenizer for waveforms and enables efficient sequence modeling. The repo provides inference scripts, checkpoints, and simple Python APIs so you can generate clips from prompts or incorporate the models into applications. It also contains training code and recipes, so researchers can fine-tune on custom data or explore new objectives without building infrastructure from scratch. Example notebooks, CLI tools, and audio utilities help with prompt design, conditioning on reference audio, and post-processing to produce ready-to-share outputs. -
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ChatGLM-6B
ChatGLM-6B: An Open Bilingual Dialogue Language Model
ChatGLM-6B is an open bilingual (Chinese + English) conversational language model based on the GLM architecture, with approximately 6.2 billion parameters. The project provides inference code, demos (command line, web, API), quantization support for lower memory deployment, and tools for finetuning (e.g., via P-Tuning v2). It is optimized for dialogue and question answering with a balance between performance and deployability in consumer hardware settings. Support for quantized inference (INT4, INT8) to reduce GPU memory requirements. Automatic mode switching between precision/memory tradeoffs (full/quantized). -
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Clawith
OpenClaw for Teams
Clawith is an AI-driven agent system focused on enabling intelligent task execution, coordination, and interaction across complex environments. It is designed to function as a control layer where agents can perform actions, manage workflows, and respond dynamically to changing conditions. The system likely emphasizes integration with external tools and services, allowing agents to extend their capabilities beyond internal reasoning. Its architecture suggests support for multi-agent collaboration, enabling distributed problem-solving and task delegation. It may also include monitoring and control features to ensure that agent behavior remains aligned with user goals. The project reflects a broader trend toward building AI systems that act as autonomous operators rather than passive assistants. Overall, Clawith serves as a foundation for building advanced, action-oriented AI workflows. -
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Digital Forensics Guide
Learn all about Digital Forensics and Computer Forensics
The Digital Forensics Guide repository is a comprehensive, structured reference for investigators, analysts, students, and cybersecurity professionals interested in digital forensics principles, tools, methodologies, and workflows. It organizes foundational topics such as evidence acquisition, disk and memory analysis, file system structures, network forensics, artifact extraction, timeline generation, and reporting into digestible modules that help build core competency. Alongside conceptual explanations, the guide includes practical examples with widely used tools (like Autopsy, Volatility, Sleuth Kit, and network analysis suites), illustrating how investigations proceed from initial data capture to final analysis. The goal is to provide both a learning path and a quick reference for real-world casework, bridging the gap between academic theory and operational practice. -
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Eigent
The Open Source Cowork Desktop to Unlock Your Exceptional Productivity
Eigent is an open-source cowork desktop application designed to help you build, manage, and deploy a custom AI workforce. It enables multiple specialized AI agents to collaborate in parallel, turning complex workflows into automated, end-to-end tasks. Built on the CAMEL-AI multi-agent framework, Eigent emphasizes productivity, flexibility, and transparent system design. You can run Eigent fully locally for maximum privacy and data control, or choose a cloud-connected experience for quick access. The platform supports a wide range of AI models and integrates powerful tools through the Model Context Protocol (MCP). With human-in-the-loop controls and enterprise-ready features, Eigent balances automation with oversight and security. -
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GHunt
Offensive Google framework
GHunt (v2) is an offensive Google framework, designed to evolve efficiently. It's currently focused on OSINT, but any use related with Google is possible. It will automatically use venvs to avoid dependency conflicts with other projects. First, launch the listener by doing ghunt login and choose between 1 of the 2 first methods. Put GHunt on listening mode (currently not compatible with docker) Paste base64-encoded cookies. Enter manually all cookies. The development of this extension has followed Firefox guidelines to use the Promise-based WebExtension/BrowserExt API being standardized by the W3 Browser Extensions group, and is using webextension-polyfill to provide cross-browser compatibility with no changes. -
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GPT4Free
The official gpt4free repository
gpt4free is an open-source project offering free, unrestricted access to GPT‑4–style language models without requiring an API key. The repository includes scripts and server implementations designed to replicate OpenAI’s GPT‑4 API behavior by leveraging publicly available or self-hosted models. It’s licensed under GPL‑v3. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Generative AI for Beginners (Version 3)
21 Lessons, Get Started Building with Generative AI
Generative AI for Beginners is a 21-lesson course by Microsoft Cloud Advocates that teaches the fundamentals of building generative AI applications in a practical, project-oriented way. Lessons are split into “Learn” modules for core concepts and “Build” modules with hands-on code in Python and TypeScript, so you can jump in at any point that matches your goals. The course covers everything from model selection, prompt engineering, and chat/text/image app patterns to secure development practices and UX for AI. It also walks through modern application techniques such as function calling, RAG with vector databases, working with open source models, agents, fine-tuning, and using SLMs. Each lesson includes a short video, a written guide, runnable samples for Azure OpenAI, the GitHub Marketplace Model Catalog, and the OpenAI API, plus a “Keep Learning” section for deeper study. -
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HackerRepo.org
Collection of cybersecurity-related references, scripts, tools, code
HackerRepo is a massive curated repository that aggregates thousands of cybersecurity, ethical hacking, and digital forensics resources into a single structured knowledge base. The project is designed as a companion learning hub for security professionals, penetration testers, and researchers who want organized access to tools, references, and training material. It spans both offensive and defensive security topics, including exploit development, threat hunting, reverse engineering, AI security, and bug bounty methodologies. The repository is continuously maintained and categorized into specialized directories so users can quickly locate relevant learning material or utilities. Rather than being a single tool, it functions as an extensive reference library that supports skill development across the entire cybersecurity lifecycle. Overall, h4cker serves as a comprehensive open knowledge repository for practitioners building or expanding professional security expertise. -
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Khoj
An AI personal assistant for your digital brain
Get more done with your open-source AI personal assistant. Khoj is a desktop application to search and chat with your notes, documents, and images. It is an offline-first, open-source AI personal assistant that is accessible from Emacs, Obsidian or your Web browser. Khoj is a thinking tool that is transparent, fun, and easy to engage with. You can build faster and better by using Khoj to search and reason across all your data sources. Khoj learns from your notes and documents to function as an extension of your brain. So that you can stay focused on doing what matters. Khoj started with the founding principle that a personal assistant be understandable, accessible and hackable. This means you can always customize and self-host your Khoj on your own machines. -
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KickThemOut
Kick devices off your network by performing an ARP Spoof attack
KickThemOut is a Python-based local network testing tool that demonstrates how ARP spoofing can remove selected devices from a local area network. It is intended for educational and authorized environments, not for disrupting networks without permission. The tool can scan a local network, identify connected devices, and let the user choose specific targets or all available targets. It supports interactive use as well as command-line options for scanning, targeting, packet rate configuration, and version or help output. The project is not compatible with Windows and is documented for systems such as Debian, macOS, and Arch-based Linux. Its README also includes a clear disclaimer that the tool should not be used with malicious intent. -
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LLaMA Models
Utilities intended for use with Llama models
This repository serves as the central hub for the Llama foundation model family, consolidating model cards, licenses and use policies, and utilities that support inference and fine-tuning across releases. It ties together other stack components (like safety tooling and developer SDKs) and provides canonical references for model variants and their intended usage. The project’s issues and releases reflect an actively used coordination point for the ecosystem, where guidance, utilities, and compatibility notes are published. It complements separate repos that carry code and demos (for example inference kernels or cookbook content) by keeping authoritative metadata and specs here. Model lineages and size variants are documented externally (e.g., Llama 3.x and beyond), with this repo providing the “single source of truth” links and utilities. In practice, teams use llama-models as a reference when selecting variants, aligning licenses, and wiring in helper scripts for deployment. -
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Mastering Bitcoin
Mastering Bitcoin 3rd Edition - Programming the Open Blockchain
The bitcoinbook repository contains the source code for Mastering Bitcoin, the authoritative open-source book by Andreas M. Antonopoulos on Bitcoin and cryptocurrency technologies. Written in a collaborative and continuously updated format using Markdown and AsciiDoc, the book serves as a comprehensive technical guide for developers, engineers, and system architects who want to understand how Bitcoin works. It covers the protocol, cryptography, peer-to-peer architecture, wallets, mining, and application development. -
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Microsoft Azure CLI
Azure command-line interface
A great cloud needs great tools; we're excited to introduce Azure CLI, our next-generation multi-platform command-line experience for Azure. Take a test run now from Azure Cloud Shell! We support tab completion for groups, commands, and some parameters. You can use the --query parameter and the JMESPath query syntax to customize your output. With the Azure CLI Tools Visual Studio Code extension, you can create .azcli files and use these features. IntelliSense for commands and their arguments. Snippets for commands, inserting required arguments automatically. Run the current command in the integrated terminal. Run the current command and show its output in a side-by-side editor. Show documentation on mouse hover. Display current subscription and defaults in the status bar. The software may collect information about you and your use of the software and send it to Microsoft. Microsoft may use this information to provide services and improve our products and services. -
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Music Assistant
Music Assistant is a free, opensource Media library manager
Music Assistant Server is the core backend for Music Assistant, a free and open-source music library manager for local and online music sources. It connects streaming services, local files, metadata providers, and many speaker ecosystems into one centralized music system. The server is designed to run on an always-on device such as a Raspberry Pi, NAS, Intel NUC, or similar home server. It can work as a standalone product, but it is especially tailored for Home Assistant users who want automation, voice control, and smart-home playback workflows. Music Assistant supports features such as library matching, metadata enrichment, gapless playback, crossfade, volume normalization, synchronized playback, announcements, and queue transfers. It is a strong choice for users who want one organized media layer across different music services and playback devices. -
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Numba
NumPy aware dynamic Python compiler using LLVM
Numba is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code. Numba translates Python functions to optimized machine code at runtime using the industry-standard LLVM compiler library. Numba-compiled numerical algorithms in Python can approach the speeds of C or FORTRAN. You don't need to replace the Python interpreter, run a separate compilation step, or even have a C/C++ compiler installed. Just apply one of the Numba decorators to your Python function, and Numba does the rest. Numba is designed to be used with NumPy arrays and functions. Numba generates specialized code for different array data types and layouts to optimize performance. Special decorators can create universal functions that broadcast over NumPy arrays just like NumPy functions do. Numba also works great with Jupyter notebooks for interactive computing, and with distributed execution frameworks, like Dask and Spark. -
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OpenAI Harmony
Renderer for the harmony response format to be used with gpt-oss
Harmony is a response format developed by OpenAI for use with the gpt-oss model series. It defines a structured way for language models to produce outputs, including regular text, reasoning traces, tool calls, and structured data. By mimicking the OpenAI Responses API, Harmony provides developers with a familiar interface while enabling more advanced capabilities such as multiple output channels, instruction hierarchies, and tool namespaces. The format is essential for ensuring gpt-oss models operate correctly, as they are trained to rely on this structure for generating and organizing their responses. For users accessing gpt-oss through third-party providers like HuggingFace, Ollama, or vLLM, Harmony formatting is handled automatically, but developers building custom inference setups must implement it directly. With its flexible design, Harmony serves as the foundation for creating more interpretable, controlled, and extensible interactions with open-weight language models. -
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OpenBB Terminal
Investment research for everyone, anywhere
Fully written in python which is one of the most used programming languages due to its simplified syntax and shallow learning curve. It is the first time in history that users, regardless of their background, can so easily add features to an investment research platform. The MIT Open Source license allows any user to fork the project to either add features to the broader community or create their own customized terminal version. The terminal allows for users to import their own proprietary datasets to use on our econometric menu. In addition, users are allowed to export any type of data to any type of format whether that is raw data in Excel or an image in PNG. This is ideal for finance content creation. Create notebook templates (through papermill) which can be run on different tickers. This level of automation allows to speed up the development of your investment thesis and reduce human error. -
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OpenMythos
A theoretical reconstruction of the Claude Mythos architecture
OpenMythos is an experimental, open-source implementation that attempts to reconstruct a hypothesized architecture behind advanced language models using a design called a Recurrent-Depth Transformer. The project explores the idea that instead of stacking hundreds of unique transformer layers, a smaller set of layers can be reused iteratively during inference to achieve deeper reasoning without increasing parameter count. It divides computation into three main stages, including a pre-processing phase, a looped recurrent reasoning block, and a final output refinement stage, creating a structured pipeline for inference. The architecture incorporates advanced techniques such as mixture-of-experts routing, adaptive computation time, and multiple attention mechanisms to dynamically allocate compute where needed. It is highly configurable through a centralized configuration system, allowing experimentation with different architectural parameters such as loop depth, attention type. -
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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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PDFium Library
Project to compile PDFium library to multiple platforms
Project to compile PDFium library to multiple platforms. PDFium project is from Google and I only patch it to compile to all platforms. -
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PasteMD
Paste Markdown and AI responses into Word Excel instantly fast
PasteMD is a lightweight desktop utility designed to streamline the process of transferring formatted content from the clipboard into office applications such as Word, WPS, and Excel. It primarily targets users who frequently copy content from AI chat tools or web pages and encounter formatting issues, especially with Markdown, tables, and LaTeX formulas. PasteMD operates from the system tray and monitors clipboard content, automatically converting Markdown or HTML into properly formatted documents using Pandoc. With a single global hotkey, users can paste structured content directly into the active application without manual cleanup or reformatting. It includes intelligent detection mechanisms that distinguish between Markdown tables, rich HTML content, and plain text, ensuring the correct output format is used for each target application. PasteMD also introduces extensible workflows that allow users to configure different paste behaviors. -
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Pix2Text
Open-Source Python3 tool for recognizing layouts, tables, and math
An Open-Source Python3 tool for recognizing layouts, tables, math formulas, and text in images, converting them into Markdown format. A free alternative to Mathpix, empowering seamless conversion of visual content into text-based representations. 80+ languages are supported. Pix2Text (P2T) aims to be a free and open-source Python alternative to Mathpix, and it can already accomplish Mathpix's core functionality. Pix2Text (P2T) can recognize layouts, tables, images, text, and mathematical formulas, and integrate all of these contents into Markdown format. P2T can also convert an entire PDF file (which can contain scanned images or any other format) into Markdown format.
