Open Source Python Software - Page 43
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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.
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DeepCode
DeepCode: Open Agentic Coding
DeepCode is an agentic coding platform built around a multi-agent architecture that turns high-level inputs, including research papers, documents, and natural-language requirements, into working software artifacts. It positions itself as an “open agentic coding” system that can handle tasks like paper-to-code reproduction, frontend generation, and backend implementation by decomposing problems into structured steps and coordinating specialized agents. The system description highlights an orchestration layer that plans, assigns subtasks, and adapts strategies as complexity changes, rather than relying on a single monolithic prompt. It also describes document parsing capabilities aimed at extracting algorithmic and mathematical details from technical materials, translating them into implementable specifications and code. -
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DeepTutor
AI-Powered Personalized Learning Assistant
DeepTutor is an AI-powered tutoring and learning assistant framework designed to automatically teach, explain, and reinforce academic or technical concepts in depth according to a learner’s specific needs. It goes beyond simple Q&A by constructing multi-stage educational narratives, breaking down complex topics into sequenced “lesson steps,” and offering prompts, examples, and exercises that build on each other in a logical curriculum. The core architecture combines LLM-based reasoning with structured pedagogy modules so that explanations accommodate different learning styles and address misconceptions in follow-up responses. DeepTutor supports retrieval of external references, definitions, and diagrams so responses are grounded in authoritative content and not just generative text, and it includes internal checks to ensure accuracy and conceptual consistency. -
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Diffusers
State-of-the-art diffusion models for image and audio generation
Diffusers is the go-to library for state-of-the-art pretrained diffusion models for generating images, audio, and even 3D structures of molecules. Whether you're looking for a simple inference solution or training your own diffusion models, Diffusers is a modular toolbox that supports both. Our library is designed with a focus on usability over performance, simple over easy, and customizability over abstractions. State-of-the-art diffusion pipelines that can be run in inference with just a few lines of code. Interchangeable noise schedulers for different diffusion speeds and output quality. Pretrained models that can be used as building blocks, and combined with schedulers, for creating your own end-to-end diffusion systems. We recommend installing Diffusers in a virtual environment from PyPi or Conda. For more details about installing PyTorch and Flax, please refer to their official documentation. -
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DocuBrowse
This does for Documents what repo-browser does for repos
DocuBrowse is a local AI-powered document search engine for personal or professional file collections. It indexes documents such as PDFs, Word files, spreadsheets, presentations, ebooks, HTML, text, and Markdown. The system combines SQLite FTS5 keyword search with local semantic embeddings for meaning-based retrieval. Users can click search results to generate an AI synopsis before opening the original file. It runs entirely on the user’s machine with Ollama models, so it does not require accounts, API keys, internet access, or per-query cloud costs. It also includes PII detection, multiple document directories, tag filtering, duplicate cleanup, and packaged installers for Linux, Windows, and macOS. -
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ECommerceCrawlers
Collection of Python ecommerce and website crawler examples projects
ECommerceCrawlers is a collection of practical Python web crawler projects designed to gather data from a variety of ecommerce platforms, websites, and online services. It aggregates many independent crawler examples created by contributors and organized into separate subprojects that target specific sites or data sources. These examples demonstrate how to build and operate web scrapers capable of collecting structured information such as product listings, news content, job postings, social media data, and other publicly available web data. It aims to help developers understand the full workflow of web scraping, including request simulation, data extraction, storage, and handling anti-scraping techniques. It includes crawlers for platforms such as ecommerce marketplaces, blogging platforms, recruitment sites, and social networks, providing real-world practice scenarios. Developers can study the individual project documentation to understand the analysis process. -
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ElevenLabs Python
The official Python SDK for the ElevenLabs API
elevenlabs-python is the official Python SDK for the ElevenLabs API, giving developers a convenient way to access ElevenLabs’ high-quality, lifelike voices. The library wraps the HTTP API into a typed Python client, so you can perform text-to-speech, streaming, voice cloning, voice management, and agents-related operations with simple method calls. It exposes ElevenLabs’ main models such as Eleven Multilingual v2, Eleven Flash v2.5, and Eleven Turbo v2.5, each targeting different trade-offs between latency, cost, and quality. The SDK is designed for quick setup: after installing the package and setting an API key, you can generate speech in multiple languages and play or process the resulting audio bytes. It includes helper utilities (like play and stream) so you can either play audio locally or integrate it into your own playback or networking pipeline. -
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Every Code
Local AI coding agent CLI with multi-agent orchestration tools
Every Code (often referred to simply as Code) is a fast, local AI-powered coding agent designed to run directly in the terminal environment. It is a community-driven fork of the Codex CLI, with a strong emphasis on improving real-world developer ergonomics and workflows. Every Code enhances the traditional coding assistant model by introducing multi-agent orchestration, allowing multiple AI agents to collaborate, compare solutions, and refine outputs in parallel. It supports integration with various AI providers, enabling users to route tasks across different models depending on their needs. Every Code also includes browser integration and automation capabilities, extending its usefulness beyond simple code generation into more complex development tasks. Customization is a key focus, with support for theming, configurable settings, and reasoning controls that allow developers to fine-tune how the agent behaves. -
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FastHTML
The fastest way to create an HTML app
Built on solid web foundations, not the latest fads - with FastHTML you can get started on anything from simple dashboards to scalable web applications in minutes. -
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Frappe
Low code web framework for real world applications
Frappe is a full-stack, low-code web framework written in Python and JavaScript, used to build scalable and modular enterprise applications. It powers ERPNext and includes tools for REST APIs, user management, document modeling, workflows, and real-time updates. Frappe uses a "model-view-controller" approach with its own ORM and frontend system, enabling rapid development without sacrificing control or performance. -
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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GPT PILOT
The first real AI developer
GPT PILOT is an open-source AI developer assistant designed to build full applications by collaborating with a human developer throughout the software lifecycle. Unlike simple autocomplete tools, it aims to function as a true AI engineer that can generate features, set up environments, debug code, and request feedback when necessary. The system works by asking clarifying questions, producing product requirements, and then implementing the application step by step while the user supervises. It powers the Pythagora VS Code extension and relies on coordinated AI agents that mimic roles in a real development workflow. GPT Pilot is intended to automate the majority of routine coding work while leaving strategic decisions and final review to the human developer. Overall, the project represents an ambitious attempt to move from AI coding assistance toward semi-autonomous software development. -
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GPTme
Your agent in your terminal, equipped with local tools
GPTMe is a personal AI chatbot designed for self-reflection, journaling, and productivity, using GPT models to generate personalized insights and responses. -
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Griptape
Python framework for AI workflows and pipelines with chain of thought
The Griptape framework provides developers with the ability to create AI systems that operate across two dimensions: predictability and creativity. For predictability, Griptape enforces structures like sequential pipelines, DAG-based workflows, and long-term memory. To facilitate creativity, Griptape safely prompts LLMs with tools (keeping output data off prompt by using short-term memory), which connects them to external APIs and data stores. The framework allows developers to transition between those two dimensions effortlessly based on their use case. Griptape not only helps developers harness the potential of LLMs but also enforces trust boundaries, schema validation, and tool activity-level permissions. By doing so, Griptape maximizes LLMs’ reasoning while adhering to strict policies regarding their capabilities. -
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H4X-Tools
A modular, terminal-based toolkit for OSINT, reconnaissance
H4X-Tools is a modular, terminal-based toolkit for OSINT, reconnaissance, and scraping workflows. It is built in Python and runs on Linux and Windows. The project organizes multiple research utilities behind an interactive menu and direct command-line options. Its tools cover areas such as Instagram profile research, web reconnaissance, phone lookup, IP lookup, username search, email search, leak intelligence, port scanning, WHOIS lookup, web scraping, directory discovery, Bluetooth scanning, and local user enumeration. The toolkit is designed to be extensible, so contributors can add new tools by creating modules that follow its BaseTool structure. It is intended for educational and authorized security research only, not for use against systems or accounts without permission. -
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Hello-Agents
Building an Intelligent Agent from Scratch
Hello Agents is an open educational project designed to teach developers how to understand, design, and build AI-native agents from the ground up through structured tutorials and practical examples. The project focuses on guiding learners beyond superficial framework usage toward deeper comprehension of agent architecture, reasoning loops, and real-world implementation patterns. It walks users through core concepts such as ReAct-style reasoning, tool usage, memory handling, and multi-step task execution, enabling hands-on experimentation with modern LLM-powered agent systems. The repository is structured as a progressive learning path, combining theory, exercises, and runnable code so users can incrementally build more capable agents. Its goal is to demystify agent engineering and help developers move from simple prompt scripts to robust autonomous systems. -
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Heretic
Fully automatic censorship removal for language models
Heretic is an open-source Python tool that automatically removes the built-in censorship or “safety alignment” from transformer-based language models so they respond to a broader range of prompts with fewer refusals. It works by applying directional ablation techniques and a parameter optimization strategy to adjust internal model behaviors without expensive post-training or altering the core capabilities. Designed for researchers and advanced users, Heretic makes it possible to study and experiment with uncensored model responses in a reproducible, automated way. The project can decensor many popular dense and some mixture-of-experts (MoE) models, supporting workflows that would otherwise require manual tuning. Beyond simple decensoring, Heretic includes research-oriented options for analyzing model internals and interpretability data. -
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HunyuanImage-3.0
A Powerful Native Multimodal Model for Image Generation
HunyuanImage-3.0 is a powerful, native multimodal text-to-image generation model released by Tencent’s Hunyuan team. It unifies multimodal understanding and generation in a single autoregressive framework, combining text and image modalities seamlessly rather than relying on separate image-only diffusion components. It uses a Mixture-of-Experts (MoE) architecture with many expert subnetworks to scale efficiently, deploying only a subset of experts per token, which allows large parameter counts without linear inference cost explosion. The model is intended to be competitive with closed-source image generation systems, aiming for high fidelity, prompt adherence, fine detail, and even “world knowledge” reasoning (i.e. leveraging context, semantics, or common sense in generation). The GitHub repo includes code, scripts, model loading instructions, inference utilities, prompt handling, and integration with standard ML tooling (e.g. Hugging Face / Transformers). -
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Ideogram 4
Open image model at the forefront of design
Ideogram 4 is an open-weight text-to-image model focused on high-quality visual generation, design control, and accurate text rendering inside images. It is built for users who need more than generic image generation, especially when layout, typography, composition, color, and language understanding matter. The project introduces a structured JSON prompting workflow that gives creators more explicit control over scene details and visual constraints. It can also accept plain-text prompts, making it accessible to users who prefer a simpler generation style. Ideogram 4 is especially useful for design-heavy outputs such as posters, ads, mockups, branded graphics, and images that include readable text. Its main value is combining open model access with professional-level control over image structure and visual direction. -
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Insanely Fast Whisper
An opinionated CLI to transcribe Audio files w/ Whisper on-device
Insanely Fast Whisper is a high-performance command-line tool designed to dramatically accelerate speech-to-text transcription using OpenAI’s Whisper models on local hardware. It leverages modern optimizations such as batch processing, mixed precision, and advanced attention mechanisms like Flash Attention to significantly reduce inference time while maintaining high transcription accuracy. The project is built on top of the Transformers ecosystem and integrates with libraries such as Optimum to maximize GPU efficiency. It is specifically engineered for environments with CUDA-enabled GPUs or Apple Silicon devices, allowing users to process hours of audio in minutes or even seconds depending on hardware capabilities. The tool provides a streamlined CLI interface, making it easy to run transcription tasks on local files or URLs without needing to write custom code. It supports multiple Whisper model variants, including distilled versions for faster inference with minimal accuracy loss. -
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Inter
The Inter font family
Inter is a typeface carefully crafted & designed for computer screens. Inter features a tall x-height to aid in readability of mixed-case and lower-case text. Several OpenType features are provided as well, like contextual alternates that adjusts punctuation depending on the shape of surrounding glyphs, slashed zero for when you need to disambiguate "0" from "o", tabular numbers, etc. Using Inter is as easy as downloading & installing the font files. There's of course no absolute right or wrong when it comes to expressing yourself with typography, but Inter Dynamic Metrics provides guidelines for good typography. You simply provide the optical font size, and the tracking and leading is calculated for you to produce the best results. Inter is a free and open source font family. You are free to use this font in almost any way imaginable. Inter comes with many OpenType features that can be used to tailor functionality and aesthetics to your specific needs. -
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Jarvis Python AI Assistant
Python AI assistant
Jarvis is a voice commanding assistant service in Python 3.8 It can recognize human speech, talk to user and execute basic commands. Opens a web page (e.g 'Jarvis open youtube') Play music in Youtube (e.g 'Jarvis play mozart') Increase/decrease the speakers master volume (also can set max/mute speakers volume) (e.g 'Jarvis volume up!') Opens libreoffice suite applications (calc, writer, impress) (e.g 'Jarvis open calc') Tells about something, by searching on the internet (e.g 'Jarvis tells me about oranges') Tells the weather for a place (e.g 'Jarvis tell_the_skills me the weather in London') Tells the current time and/or date (e.g 'Jarvis tell me time or date') Set an alarm (e.g 'Jarvis create a new alarm') Tells the internet speed (ping, uplink and downling) (e.g 'Jarvis tell_the_skills me the internet speed') Tells the internet availability (e.g 'Jarvis is the internet connection ok?') Tells the daily news (e.g 'Jarvis tell me today news') -
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Kaggle CLI
The official CLI to interact with Kaggle
Kaggle CLI is Kaggle’s official command-line interface for interacting with the Kaggle platform from a terminal. It lets users authenticate, search resources, download files, submit competition entries, manage datasets, work with models, run notebooks, and read discussion content without relying only on the web interface. The tool is useful for data scientists who want to automate Kaggle workflows inside scripts, CI jobs, notebooks, or reproducible local environments. It supports both traditional API-token authentication and an OAuth login flow, which makes it more flexible for different usage patterns. kaggle-cli is especially practical when working with large datasets or repeated competition submissions that would be slow to handle manually. Its main value is turning Kaggle’s web-based data science platform into a scriptable developer workflow. -
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Kale
Kubeflow’s superfood for Data Scientists
KALE (Kubeflow Automated pipeLines Engine) is a project that aims at simplifying the Data Science experience of deploying Kubeflow Pipelines workflows. Kubeflow is a great platform for orchestrating complex workflows on top Kubernetes and Kubeflow Pipeline provides the mean to create reusable components that can be executed as part of workflows. The self-service nature of Kubeflow make it extremely appealing for Data Science use, at it provides an easy access to advanced distributed jobs orchestration, re-usability of components, Jupyter Notebooks, rich UIs and more. Still, developing and maintaining Kubeflow workflows can be hard for data scientists, who may not be experts in working orchestration platforms and related SDKs. Additionally, data science often involve processes of data exploration, iterative modelling and interactive environments (mostly Jupyter notebook). -
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Knowledge Work Plugins
Open source repository of plugins intended for knowledge workers
Knowledge Work Plugins is Anthropic’s open-source repository of plugin-style Markdown packs for knowledge-work use cases in Claude Cowork and related Claude Code workflows. It is designed to give AI assistants structured domain instructions rather than relying on generic chat behavior. The repository includes plugins for practical office, research, legal, and business workflows, with each plugin stored as editable Markdown. This makes the system easy to inspect, fork, customize, and adapt to an organization’s own process. Its goal is to help agents perform repeatable knowledge work with clearer expectations, domain constraints, and workflow patterns. The project is best suited for teams that want reusable AI work instructions without building a full application around them. -
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Kronos
A Foundation Model for the Language of Financial Markets
Kronos is a specialized open-source foundation model designed for analyzing and predicting financial market data using time-series representations of candlestick patterns. It is built as a decoder-only Transformer model trained specifically on K-line data, which captures open, high, low, close, and volume information across multiple global exchanges. The system introduces a novel tokenization approach that converts continuous financial data into discrete tokens, enabling the model to process market behavior similarly to language. This allows Kronos to perform a variety of quantitative tasks such as forecasting, pattern recognition, and anomaly detection within financial datasets. It is optimized for the noisy and complex nature of market data, distinguishing it from general-purpose time-series models. The project includes multiple pre-trained model sizes and tools for fine-tuning, making it adaptable to different computational constraints and use cases. -
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LLM Council
LLM Council works together to answer your hardest questions
LLM Council is a creative open-source web application by Andrej Karpathy that lets you consult multiple large language models together to answer questions more reliably than querying a single model. Instead of relying on one provider, this application sends your query simultaneously to several LLMs supported via OpenRouter, collects each model’s independent response, and then orchestrates a multi-stage evaluation where the models critique and rank each other’s outputs anonymously. After this peer-review process, a designated “Chairman” model synthesizes a final consolidated answer drawing on the strengths and insights of all participants. The interface looks like a familiar chat app but under the hood it implements this ensemble and consensus workflow to reduce bias and leverage diverse reasoning styles.
