Open Source Python Software - Page 65
Sort By:
Python Software
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.
-
99.99% Uptime for MySQL and PostgreSQL DatabasesCloud SQL Enterprise Plus delivers near-zero downtime with 35 days of point-in-time recovery. Supports MySQL, PostgreSQL, and SQL Server.
-
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
1
Omnigent
A meta-harness for all your AI agents
Omnigent is a meta-harness for managing many AI agents through one shared layer. It works with Claude Code, Codex, Cursor, Pi, and custom YAML-defined agents, so users can swap or combine agent runtimes without rebuilding their workflows. Sessions can move across terminal, browser, desktop, and mobile interfaces while keeping messages, files, terminals, and subagents in sync. The platform supports collaboration, shared live sessions, co-driving, conversation forking, and remote access from deployed servers. It also includes policy controls for approvals, tool access, spending limits, sandboxing, and server-wide governance. Omnigent is useful for teams and power users who want multi-agent supervision, safer execution, and flexible access from different devices. -
2
OneFileLLM
Specify a github or local repo, github pull request
OneFileLLM is an open-source project designed to simplify the distribution and execution of large language model applications by packaging them into a single portable file. The concept behind the project is to eliminate the complexity normally associated with deploying AI systems, which often require multiple dependencies, frameworks, and configuration steps. Instead, the entire runtime environment, model interface, and application logic are bundled together into a single executable artifact. This design allows developers to share AI tools in a format that can be easily distributed and executed across different machines without complicated installation procedures. Such packaging strategies help make AI software easier to use in educational settings, demonstrations, and lightweight deployments. -
3
Onyx
Gen-AI Chat for Teams
Onyx is an AI platform designed to integrate seamlessly with your company's documents, applications, and team members. It offers a feature-rich chat interface and supports integration with various Large Language Models (LLMs). Onyx ensures synchronized knowledge and access controls across over 40 connectors, including Google Drive, Slack, Confluence, and Salesforce. Users can create custom AI agents with unique prompts and actions, and deploy Onyx securely on various platforms, from laptops to cloud services. -
4
Open source games
A list of open source games
Open Source Games is an open-source, community-maintained directory of video games with publicly available source code. It also includes open-source recreations of commercial games and classic gaming experiences. The repository organizes projects into categories such as action, adventure, puzzle, racing, role-playing, strategy, simulation, and platform games. Each entry provides a project name and links to relevant source repositories or websites. Developers can explore game implementations to study programming techniques, graphics engines, and gameplay systems. Players can discover independently developed games and community-driven alternatives to commercial titles. The collection also references related game directories for broader exploration. Its collaborative structure allows contributors to recommend additional projects and maintain existing listings. -
Paessler - Monitor Your Whole Network in MinutesWaiting weeks for a monitoring rollout isn't an option when infrastructure doesn't stop running. PRTG's auto-discovery scans your network and suggests from over 200 pre-configured sensor types, so you're watching servers, applications and devices within minutes, not after a multi-week deployment. Enterprise-strength monitoring, without the enterprise complexity. Start your free trial today.
-
5
OpenAI Agents (Python)
A lightweight, powerful framework for multi-agent workflows
openai-agents-python is a library developed by OpenAI to simplify the process of creating and running agents that interact with tools and APIs using OpenAI models. It provides abstractions for tool usage, memory management, and agent workflows, enabling developers to define function-calling agents that reason through multi-step tasks. Ideal for building custom AI workflows, the library supports dynamic tool definitions and contextual memory handling. -
6
OpenAI Agents SDK
A lightweight, powerful framework for multi-agent workflows
The OpenAI Agents Python SDK is a powerful yet lightweight framework for developing multi-agent workflows. This framework enables developers to create and manage agents that can coordinate tasks autonomously, using a set of instructions, tools, guardrails, and handoffs. The SDK allows users to configure workflows in which agents can pass control to other agents as necessary, ensuring dynamic task management. It also includes a built-in tracing system for tracking, debugging, and optimizing agent activities. -
7
OpenAdapt
Open Source Generative Process Automation
OpenAdapt is the open source software adapter between Large Multimodal Models (LMMs) and traditional desktop and web Graphical User Interfaces (GUIs). OpenAdapt learns to automate your desktop and web workflows by observing your demonstrations. Spend less time on repetitive tasks and more on work that truly matters. Boost team productivity in HR operations. Automate candidate sourcing using LinkedIn Recruiter, LinkedIn Talent Solutions, GetProspect, Reply.io, outreach.io, Gmail/Outlook, and more. Streamline legal procedures and case management. Automate tasks like generating legal documents, managing contracts, tracking cases, and conducting legal research with LexisNexis, Westlaw, Adobe Acrobat, Microsoft Excel, and more. -
8
OpenCLIP
An open source implementation of CLIP
The goal of this repository is to enable training models with contrastive image-text supervision and to investigate their properties such as robustness to distribution shift. Our starting point is an implementation of CLIP that matches the accuracy of the original CLIP models when trained on the same dataset. Specifically, a ResNet-50 model trained with our codebase on OpenAI's 15 million image subset of YFCC achieves 32.7% top-1 accuracy on ImageNet. OpenAI's CLIP model reaches 31.3% when trained on the same subset of YFCC. For ease of experimentation, we also provide code for training on the 3 million images in the Conceptual Captions dataset, where a ResNet-50x4 trained with our codebase reaches 22.2% top-1 ImageNet accuracy. This codebase is work in progress, and we invite all to contribute in making it more accessible and useful. In the future, we plan to add support for TPU training and release larger models. We hope this codebase facilitates and promotes further research. -
9
OpenSmash-Ultimate
Super Smash Bros. Ultimate native PC program by static recompilation
OpenSmash-Ultimate is a free, open-source project that brings Nintendo's Super Smash Bros. Ultimate to PC through static recompilation technology rather than traditional console emulation. Created by merging the WindowSmash and ssbu-recomp projects, the software translates the game's original ARM64 code into native x86-64 executable code and provides a custom runtime that replaces Nintendo Switch system functionality. OpenSmash-Ultimate aims to support the complete Super Smash Bros. Ultimate experience, including game modes, downloadable fighters, stages, music, and cinematics, using files extracted from a user's own Nintendo Switch. The project includes an integrated launcher, mod manager, customizable controller settings, and graphics options supporting Direct3D 11, Vulkan, and Metal. It also features experimental online multiplayer capabilities, including private rooms, LAN connections, direct and relay networking, and rollback netcode for competitive matches. -
Save Up to 91% on Cloud Compute With Spot VMsRun batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
-
10
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. -
11
PDFSticher
Code repository for PDFStitcher, a utility to stitch together PDFs
The open source PDF stitching software for sewists, by sewists. PDFSticher is a utility for stitching together many PDF pages from one document into a single page. This is also called "N-Up" or page imposition. This program was created in order to convert sewing patterns into a convenient format for projecting, though it could be used to stitch together any PDF. Since version 0.4, it is also possible to select layers for inclusion/exclusion in the final output. Additionally, line properties can be modified for each layer if the input PDF is compatible. -
12
PDM
A modern Python package and dependency manager
PDM (Python Development Master) is a modern Python package and dependency manager that adheres to the latest PEP standards. It emphasizes a declarative approach to project configuration using pyproject.toml, facilitating reproducible builds and streamlined workflows. PDM's focus on simplicity and compliance with Python's evolving ecosystem makes it a valuable tool for developers seeking modern project management solutions. -
13
PandasAI
PandasAI is a Python library that integrates generative AI
PandasAI is a Python library that adds Generative AI capabilities to pandas, the popular data analysis and manipulation tool. It is designed to be used in conjunction with pandas, and is not a replacement for it. PandasAI makes pandas (and all the most used data analyst libraries) conversational, allowing you to ask questions to your data in natural language. For example, you can ask PandasAI to find all the rows in a DataFrame where the value of a column is greater than 5, and it will return a DataFrame containing only those rows. -
14
Pathway AI Pipelines
Ready-to-run cloud templates for RAG
Pathway AI Pipelines is a collection of ready-to-deploy AI pipeline templates designed to help developers rapidly build production-grade retrieval-augmented generation and enterprise search applications. The project provides end-to-end examples that connect live data sources to LLM workflows, enabling applications to stay synchronized with continuously changing information. It supports numerous connectors including local files, Google Drive, SharePoint, Kafka, PostgreSQL, and real-time APIs, making it suitable for enterprise data environments. The templates include built-in indexing, vector search, hybrid search, and caching capabilities that remove the need to assemble separate infrastructure components. Developers can run the applications locally or deploy them to cloud platforms using Docker with minimal setup. Overall, llm-app functions as a practical accelerator for teams building real-time, production-ready AI knowledge systems. -
15
PlaystoreDownloader
A command line tool to download Android applications
A command line tool to download Android applications directly from the Google Play Store by specifying their package name (an initial one-time configuration is required) PlaystoreDownloader is a tool for downloading Android applications directly from the Google Play Store. After an initial (one-time) configuration, applications can be downloaded by specifying their package name. There are two ways of getting a working copy of PlaystoreDownloader on your own computer: either by using Docker or by using directly the source code in a Python 3 environment. In both cases, the first thing to do is to get a local copy of this repository, so open up a terminal in the directory where you want to save the project and clone the repository. Apart from valid Google Play Store credentials, the only requirement of this project is a working Python 3 (at least 3.7) installation and pipenv (for dependency management). -
16
Poetry
Python packaging and dependency management made easy
Poetry is a comprehensive Python dependency management and packaging tool that streamlines project setup and maintenance. By consolidating various configuration files into a single pyproject.toml, it simplifies the management of dependencies, virtual environments, and package publishing. Poetry ensures consistency across development environments and facilitates the creation of reproducible builds, making it an essential tool for Python developers seeking efficiency and reliability. -
17
PraisonAI
PraisonAI application combines AutoGen and CrewAI or similar framework
PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customization, and efficient human-agent collaboration. Chat with your ENTIRE Codebase. Praison AI, leveraging both AutoGen and CrewAI or any other agent framework, represents a low-code, centralized framework designed to simplify the creation and orchestration of multi-agent systems for various LLM applications, emphasizing ease of use, customization, and human-agent interaction. -
18
Prometheus-Eval
Evaluate your LLM's response with Prometheus and GPT4
Prometheus-Eval is an open-source framework designed to evaluate the outputs of large language models using specialized evaluator models known as Prometheus. The project provides tools, datasets, and scripts that allow developers and researchers to measure the quality of LLM responses through automated scoring rather than relying solely on human evaluators. It implements an “LLM-as-a-judge” approach in which a dedicated language model analyzes instruction–response pairs and assigns scores or rankings based on predefined evaluation criteria. The repository includes a Python package that provides a straightforward interface for running evaluations and integrating them into model development pipelines. It also provides training data and utilities for fine-tuning evaluator models so they can assess outputs according to custom scoring rubrics such as helpfulness, accuracy, or style. -
19
Prophet
Tool for producing high quality forecasts for time series data
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. Prophet is used in many applications across Facebook for producing reliable forecasts for planning and goal setting. We’ve found it to perform better than any other approach in the majority of cases. We fit models in Stan so that you get forecasts in just a few seconds. Get a reasonable forecast on messy data with no manual effort. Prophet is robust to outliers, missing data, and dramatic changes in your time series. -
20
PyMdown Extensions
Extensions for Python Markdown
PyMdown Extensions is a collection of extensions for Python Markdown. They were originally written to make writing documentation more enjoyable. They cover a wide range of solutions, and while not every extension is needed by all people, there is usually at least one useful extension for everybody. All extensions are found under the module namespace of pymdownx. Assuming we wanted to specify the use of the MagicLink extension, we would include it in Python Markdown. -
21
Pydantic Logfire
Python observability platform for tracing apps, metrics, and logs
Pydantic Logfire is an observability platform designed to help developers monitor, analyze, and understand the behavior of their applications in real time. It is built by the team behind Pydantic and follows a philosophy of combining powerful capabilities with ease of use, making it accessible to entire engineering teams. Pydantic Logfire provides deep visibility into application performance by capturing traces, metrics, and logs through an OpenTelemetry-based architecture. It is particularly strong in Python environments, offering detailed insights into Python objects, event loops, database queries, and validation flows. Logfire also integrates closely with Pydantic models, enabling developers to inspect and analyze how data moves through validation layers. In addition to traditional observability, it supports modern AI and LLM-based applications by tracing full request lifecycles, including model calls and external dependencies. -
22
Python Progressbar
Progressbar 2 - A progress bar for Python 2 and Python 3
A text progress bar is typically used to display the progress of a long-running operation, providing a visual cue that processing is underway. The progressbar is based on the old Python progressbar package that was published on the now-defunct Google Code. Since that project was completely abandoned by its developer and the developer did not respond to my email, I decided to fork the package. This package is still backward compatible with the original progressbar package so you can safely use it as a drop-in replacement for existing projects. The ProgressBar class manages the current progress, and the format of the line is given by a number of widgets. A widget is an object that may display differently depending on the state of the progress bar. -
23
QuantDinger
AI-driven, local-first quantitative trading platform for research
QuantDinger is a local-first, open-source quantitative trading platform designed to bring AI-assisted analysis, strategy development, backtesting, and live execution into a self-hosted workspace where data and API credentials remain under your control. Unlike cloud-locked quant services, it lets users run the entire trading workflow on their own infrastructure using Docker, with a PostgreSQL database backend, a Python backend API, and a web frontend UI that supports visualization and strategy management. Traders and researchers can develop custom strategies in Python, run historical backtests, analyze performance, and connect to supported exchanges for live trading, making it suitable for equities, crypto, forex, and futures markets in a local environment. QuantDinger also incorporates optional AI features via external APIs, assisting in tasks like strategy ideation or interpreting market indicators, but strategy logic remains inspectable and transparent in code. -
24
Quod Libet
Music player and music library manager for Linux, Windows, and macOS
Quod Libet is a cross-platform audio/music management program. It provides many ways to view your local library, and supports streaming audio and feeds (podcasts, etc). It has extremely flexible metadata editing and searching capabilities. With over 90 plugins included, you can extend and integrate with almost anything, or write your own! Ex Falso is a bare-bones tag editor with the same editing interface as Quod Libet. Quod Libet is a GTK+-based audio player written in Python, using the Mutagen tagging library. It’s designed around the idea that you know how to organize your music better than we do. It lets you make playlists based on regular expressions (don’t worry, regular searches work too). It lets you display and edit any tags you want in the file, for all the file formats it supports. Unlike some, Quod Libet will scale to libraries with tens of thousands of songs. It also supports most of the features you’d expect from a modern media player. -
25
Qwen2.5-Omni
Capable of understanding text, audio, vision, video
Qwen2.5-Omni is an end-to-end multimodal flagship model in the Qwen series by Alibaba Cloud, designed to process multiple modalities (text, images, audio, video) and generate responses both as text and natural speech in streaming real-time. It supports “Thinker-Talker” architecture, and introduces innovations for aligning modalities over time (for example synchronizing video/audio), robust speech generation, and low-VRAM/quantized versions to make usage more accessible. It holds state-of-the-art performance in many multimodal benchmarks, particularly spoken language understanding, audio reasoning, image/video understanding, etc. Very strong benchmark performance across modalities (audio understanding, speech recognition, image/video reasoning) and often outperforming or matching single-modality models at a similar scale. Real-time streaming responses, including natural speech synthesis (text-to-speech) and chunked inputs for low latency interaction.
