Open Source Python Software - Page 99
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.
-
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
-
1
VQGAN-CLIP web app
Local image generation using VQGAN-CLIP or CLIP guided diffusion
VQGAN-CLIP has been in vogue for generating art using deep learning. Searching the r/deepdream subreddit for VQGAN-CLIP yields quite a number of results. Basically, VQGAN can generate pretty high-fidelity images, while CLIP can produce relevant captions for images. Combined, VQGAN-CLIP can take prompts from human input, and iterate to generate images that fit the prompts. Thanks to the generosity of creators sharing notebooks on Google Colab, the VQGAN-CLIP technique has seen widespread circulation. However, for regular usage across multiple sessions, I prefer a local setup that can be started up rapidly. Thus, this simple Streamlit app for generating VQGAN-CLIP images on a local environment. Be advised that you need a beefy GPU with lots of VRAM to generate images large enough to be interesting. (Hello Quadro owners!). -
2
VSGAN
VapourSynth Single Image Super-Resolution Generative Adversarial
Single Image Super-Resolution Generative Adversarial Network (GAN) which uses the VapourSynth processing framework to handle input and output image data. Transform, Filter, or Enhance your input video, or the VSGAN result with VapourSynth, a Script-based NLE. You can chain models or re-run the model twice-over (or more). Have low VRAM? Don’t worry! The Network will be applied in quadrants of the image to reduce up-front VRAM usage. You can use any RGB video input, including float32 (e.g., RGBS) inputs. Using VapourSynth you can pass a Video directly to VSGAN, without any frame extraction needed. Any edit you make in the VapourSynth script with or without VSGAN can be re-used for any other video. VSGAN is released under the MIT License, ensuring it will stay free, with the ability to be used commercially. -
3
ValueCell
Community-driven, multi-agent platform for financial applications
ValueCell is a community-driven multi-agent AI platform focused on financial research, analysis, and decision-making that lets users leverage multiple specialized AI agents for tasks like data retrieval, investment research, strategy execution, and market tracking. The system brings together a suite of collaborative agents—such as research agents that gather and interpret fundamentals, strategy agents that implement trading logic, and news agents that deliver personalized updates—to help users make more informed financial decisions across stocks, crypto, and other markets. ValueCell supports integrations with multiple language model providers and market data sources, giving developers flexibility in customizing agents and incorporating external APIs to enhance insights. Sensitive user data is stored locally, a design choice that prioritizes privacy and security while still enabling rich analytic workflows. -
4
Vector AI
A platform for building vector based applications
Vector AI is a framework designed to make the process of building production-grade vector-based applications as quick and easily as possible. Create, store, manipulate, search and analyze vectors alongside json documents to power applications such as neural search, semantic search, personalized recommendations etc. Image2Vec, Audio2Vec, etc (Any data can be turned into vectors through machine learning). Store your vectors alongside documents without having to do a db lookup for metadata about the vectors. Enable searching of vectors and rich multimedia with vector similarity search. The backbone of many popular A.I use cases like reverse image search, recommendations, personalization, etc. There are scenarios where vector search is not as effective as traditional search, e.g. searching for skus. Vector AI lets you combine vector search with all the features of traditional search such as filtering, fuzzy search, and keyword matching to create an even more powerful search. -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
-
5
VibeVoice ComfyUI
ComfyUI integration for Microsoft's VibeVoice text-to-speech model
VibeVoice ComfyUI is a comprehensive wrapper that integrates Microsoft’s VibeVoice text-to-speech models directly into ComfyUI workflows. It exposes VibeVoice as a set of custom nodes so you can build single-speaker and multi-speaker voice generation pipelines visually, combining TTS with other audio or generative components. The integration supports high-quality single-speaker synthesis as well as scripted multi-speaker conversations, with optional voice cloning from audio samples for each speaker. It includes advanced control over generation parameters like attention backend, diffusion steps, sampling temperature, guidance scale, and quantization settings, allowing users to tune the trade-offs between quality, VRAM usage, and speed. The project also introduces first-class LoRA support, making it possible to fine-tune and load custom LoRA adapters that modify voice identity or style while keeping the base VibeVoice model intact. -
6
VideoChat
Real-time voice interactive digital human
VideoChat is a real-time voice-interactive “digital human” system that combines automatic speech recognition, large language models, text-to-speech, and talking-head generation into a single conversational pipeline. It supports both pure end-to-end voice solutions based on multimodal large language models (GLM-4-Voice feeding directly into talking-head generation) and a more traditional cascaded pipeline using ASR → LLM → TTS → talking head. It is built as a Gradio Python demo, exposing a web interface where users can talk to an animated avatar that lip-syncs to synthesized speech while responding intelligently. The system is customizable: you can define your own avatar appearance and voice, and it supports voice cloning so you can generate a new voice from a short 3–10 second reference sample. The tech stack integrates FunASR for speech recognition, Qwen for language understanding, multiple TTS engines like GPT-SoVITS, CosyVoice, or edge-tts, and MuseTalk for talking-head generation. -
7
Videomass
Videomass is a free, open source and cross-platform GUI for FFmpeg
Videomass is a free, open-source graphical interface for FFmpeg designed to make advanced video and audio processing accessible to both beginners and experienced users. Built in Python using wxPython, it provides a cross-platform environment for managing encoding, conversion, and editing tasks through a visual interface. The software supports multitasking operations, allowing users to process multiple media files simultaneously. It offers extensive configuration options while also providing presets to simplify common workflows. Videomass integrates closely with FFmpeg, exposing powerful capabilities such as transcoding, filtering, and format conversion without requiring command-line interaction. It also supports scripting and customization for more advanced use cases. Overall, it combines usability and flexibility into a comprehensive multimedia processing tool. -
8
VoiceSmith
[WIP] VoiceSmith makes training text to speech models easy
VoiceSmith makes it possible to train and infer on both single and multispeaker models without any coding experience. It fine-tunes a pretty solid text to speech pipeline based on a modified version of DelightfulTTS and UnivNet on your dataset. Both models were pretrained on a proprietary 5000 speaker dataset. It also provides some tools for dataset preprocessing like automatic text normalization. Windows (only CPU supported currently) or any Linux based operating system. If you want to run this on macOS you have to follow the steps in build from source in order to create the installer. This is untested since I don't currently own a Mac. NVIDIA GPU with CUDA support is highly recommended, you can train on CPU otherwise but it will take days if not weeks. VoiceSmith currently uses a two-stage modified DelightfulTTS and UnivNet pipeline. -
9
VulnX
Intelligent Bot, Shell can achieve automatic injection
vulnx, an intelligent Bot, Shell can achieve automatic injection, and help researchers detect security vulnerabilities in CMS systems. It can perform a quick CMS security detection, information collection (including sub-domain name, IP address, country information, organizational information and time zone, etc.), and vulnerability scanning. Vulnx is An Intelligent Bot Auto Shell Injector that detects vulnerabilities in multiple types of Cms, fast cms detection, information gathering, and vulnerability scanning of the target like subdomains, IP addresses, country, org, timezone, region, and more. Instead of injecting each and every shell manually as all the other tools do, VulnX analyses the target website checking the presence of a vulnerability if so the shell will be Injected by searching URLs with the dorks Tool. Detects CMS (wordpress, joomla, prestashop, drupal, opencart, magento, lokomedia). -
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.
-
10
WFGY 3.0
A tension reasoning engine over 131 S-class problems
WFGY is an experimental open-source reasoning framework designed to improve the reliability and interpretability of large language model outputs through structured reasoning layers. The project introduces a conceptual reasoning engine that analyzes complex problems by identifying semantic compression errors and residual assumptions within a system’s reasoning process. Its architecture treats reasoning failures as measurable signals that can be detected and analyzed rather than simply observed as incorrect answers. Different versions of the framework, including WFGY 1.0, 2.0, and 3.0, represent stages of development where early conceptual ideas evolved into more structured reasoning engines and diagnostic tools. The system maps reasoning tension across a large set of complex problems spanning domains such as mathematics, science, climate, finance, and artificial intelligence behavior. -
11
WYGIWYH
A simple but powerful self-hosted finance tracker
WYGIWYH (What You Get Is What You Have) is a self-hosted, principles-first personal finance tracker built for people who prefer a simple, intuitive approach to tracking money without complicated budgets or categories. Based on a philosophy that you should use what you earn each month for that month, it helps you understand where your funds go while keeping savings clearly separated so they aren’t accidentally dipped into for everyday expenses. The app supports multiple currencies, customizable transaction types, and built-in tools like dollar-cost averaging tracking to help you see investment activity alongside regular expenses, making it flexible for real world financial situations and global use. Its interface is designed to prioritize clarity and ease of entry, so you can quickly record and review spending without being overwhelmed by features you don’t need. -
12
Walle 2.0
Walle 2.0 web
Support multi-project, multi-environment one-click deployment and online, one-click quick rollback. Online order application, review, deployment, and real-time operation logs. Permissions, notifications, file fingerprints. Independent space resources like gitlab. Custom environment, environment variables. Project administrator, a notification mechanism, custom hooks in each process. Get through server management, grayscale release. Advanced gitlab-like user management mode. Online order application, review, grayscale release, real-time websocket. Walle allows users to release code and finally can not only choose jenkins! Support various web code releases, release and rollback of php, java, python, go and other codes can be completed with one click through the web. walle is a freely configurable project, more user-friendly, high-value, an open source online deployment system that supports git, multi-user, multi-language, multi-project, and multi-environment simultaneous deployment. -
13
Watchdog
Python library and shell utilities to monitor filesystem events
Python API library and shell utilities to monitor file system events. A simple program that uses watchdog to monitor directories specified as command-line arguments and logs events generated. Watchdog comes with an optional utility script called watchmedo. Please type watchmedo --help at the shell prompt to know more about this tool. You can use the shell-command subcommand to execute shell commands in response to events. watchmedo can read tricks.yaml files and execute tricks within them in response to file system events. Tricks are actually event handlers that subclass watchdog.tricks.Trick and are written by plugin authors. Trick classes are augmented with a few additional features that regular event handlers don't need. The directory containing the tricks.yaml file will be monitored. Each trick class is initialized with its corresponding keys in the tricks.yaml file as arguments and events are fed to an instance of this class as they arrive. -
14
WeChat Jump Game
WeChat "Jump Jump" Python Assist
WeChat Jump Game is a Python automation project for the WeChat mini game “Jump Jump.” It uses screenshots, image recognition, and distance estimation to calculate how long the screen should be pressed for each jump. The project was created as a technical experiment around a popular 2.5D timing game where the character must jump from one platform to another. It supports automatic play, allowing the script to detect positions and control jumps through connected-device tooling. The repository also includes explanations of the game logic, recognition approach, and platform-specific setup details. Its main value is demonstrating how Python, computer vision, and device automation can be combined to interact with a simple mobile game. -
15
WeKnora
LLM framework for document understanding and semantic retrieval
WeKnora is an open source framework developed for deep document understanding and semantic information retrieval using large language models. It focuses on analyzing complex and heterogeneous documents by combining multiple processing stages such as multimodal document parsing, vector indexing, and intelligent retrieval. It follows the Retrieval-Augmented Generation (RAG) paradigm, where relevant document segments are retrieved and used by language models to generate accurate, context-aware responses. This approach enables the system to provide more reliable answers by grounding model reasoning in the content of uploaded documents. WeKnora is designed with a modular architecture that separates components for document processing, search strategies, and model inference, allowing developers to customize or extend different parts of the pipeline. It supports knowledge base management and conversational question answering built on top of structured and unstructured documents. -
16
Weak-to-Strong
Implements weak-to-strong learning for training stronger ML models
Weak-to-Strong is an OpenAI research codebase that implements the concept of weak-to-strong generalization, as described in the accompanying paper. The project provides tools for training larger “strong” models using labels or guidance generated by smaller “weak” models. Its core functionality focuses on binary classification tasks, with support for fine-tuning pretrained language models and experimenting with different loss functions, including confidence-based auxiliary losses. The repository also includes a dedicated vision module for applying weak-to-strong training setups in computer vision, demonstrated with models such as AlexNet and DINO on ImageNet. Although the code is not fully production-tested, it reproduces qualitatively similar results to the experiments presented in the paper, especially when comparing large model size gaps. -
17
WebArena
Code repo for "WebArena to build Autonomous Agents
WebArena is a realistic web environment designed for building and testing autonomous agents, providing a platform for developing web-based AI agents. -
18
WizardLM
LLMs build upon Evol Insturct: WizardLM, WizardCoder, WizardMath
WizardLM empowers large pre-trained language models to follow complex instructions. We adopt the automatic evaluation framework based on GPT-4 proposed by FastChat to assess the performance of chatbot models. Evol-Instruct is a novel method using LLMs instead of humans to automatically mass-produce open-domain instructions of various difficulty levels and skills range, to improve the performance of LLMs. You can easily embark on your own evolutionary journey with the Evol Script we provide. -
19
XAgent
An Autonomous LLM Agent for Complex Task Solving
XAgent is an AI-driven autonomous agent framework capable of handling multi-step tasks across different domains. It enables AI agents to perform decision-making, task planning, and self-learning based on user-defined objectives, making it ideal for automation and research applications. -
20
Xfl
An Efficient and Easy-to-use Federated Learning Framework
XFL is a lightweight, high-performance federated learning framework supporting both horizontal and vertical FL. It integrates homomorphic encryption, DP, secure MPC, and optimizes network resilience. Compatible with major ML libraries and deployable via Docker or Conda. -
21
Xianyu Intelligent Monitor Bot
AI tool for real-time monitoring and analysis of Goofish listings
ai-goofish-monitor is an open source automation tool designed to monitor listings on the Goofish second-hand marketplace and analyze them using artificial intelligence. It combines browser automation with AI-based analysis to automatically search, collect, and evaluate newly posted items that match a user’s purchase criteria. It uses Playwright to simulate real user interactions with the marketplace, allowing the system to retrieve product data and track updates in near real time. ai-goofish-monitor can run multiple monitoring tasks simultaneously, each configured with specific keywords, price ranges, and filtering conditions. A built-in web management interface allows users to create tasks, review results, and manage monitoring rules without relying solely on command line tools. AI models analyze product descriptions, images, and seller information to determine whether a listing meets defined requirements and should be recommended to the user. -
22
Yark
Simple OSINT tool for archiving and browsing YouTube channels offline
Yark is an open source command-line tool designed to simplify the process of archiving YouTube channels for research, analysis, or personal preservation. The project focuses on OSINT (Open Source Intelligence) workflows by allowing users to collect and store videos, metadata, and thumbnails from a YouTube channel in a structured local archive. Instead of simply downloading individual videos, Yark creates a self-contained archive directory that includes metadata files and organized folders for media assets. This format allows users to maintain a historical record of a channel and track updates or changes over time. The tool also provides a local offline web interface that lets users browse and watch archived videos directly in their browser. Because archives are updated using timestamps, users can refresh an existing archive to add newly published content without recreating the entire dataset. Overall, Yark aims to make YouTube archiving and channel analysis easier. -
23
ZeroNet
Decentralized websites using Bitcoin crypto and BitTorrent network
Open, free and uncensorable websites, using Bitcoin cryptography and BitTorrent network. Your content distributed directly to other visitors without any central server. Uncensored: It's nowhere because it's everywhere! No hosting costs: Sites are served by visitors. Always accessible: No single point of failure. No configuration needed: Download, unpack and start using it. Decentralized domains using Namecoin cryptocurrency. Your account is protected by the same cryptography as your Bitcoin wallet. Page response time is not limited by your connection speed. Real-time updated, multi-user websites. Supports any modern browser on Windows, Linux or Mac platforms. You can easily hide your IP address using the Tor network. Browse the sites you're seeding even if your internet connection is down. Developed by the community for the community. We believe in open, free, and uncensored network and communication. -
24
Zerox OCR
PDF to Markdown with vision models
A dead simple way of OCR-ing a document for AI ingestion. Documents are meant to be a visual representation after all. With weird layouts, tables, charts, etc. The vision models just make sense. ZeroX is an open-source machine learning framework designed for fast experimentation and production deployment, optimized for speed and ease of use. -
25
Zeta
Build high-performance AI models with modular building blocks
zeta is a deep learning library focused on providing cutting-edge AI and neural network models with a strong emphasis on research-grade architectures. It includes state-of-the-art implementations for rapid experimentation and model building.
