Search Results for "mind"
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Showing 111 open source projects for "mind"
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1
Amulet Map Editor
A new Minecraft world editor and converter
The new age Minecraft world editor and converter that supports every version since Java 1.12 and Bedrock 1.7. Amulet is a Minecraft world editor built from the ground up with the lessons learnt from previous editors in mind. The program works natively with the block state format introduced in 1.13 which enables editing of all world formats. Amulet is built on top of a world converter that converts all world data into a custom superset format. This means that all worlds can be modified in the same way rather than having custom logic for each world format. ... -
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Anything to NotebookLM
Multi-source content processor for NotebookLM
...It is built for users who want to convert articles, web pages, videos, PDFs, office files, podcasts, images, and search results into more usable study or presentation formats. The project uses natural-language commands, so the user can ask for a podcast, slide deck, mind map, report, quiz, flashcards, or infographic without manually building the workflow. It supports multilingual material, with especially strong use cases for Chinese and English content. The tool can process files locally, extract or transcribe content when needed, and hand the cleaned material to NotebookLM for generation. It is best suited for researchers, students, content curators, and knowledge workers who regularly turn scattered information into organized learning assets. -
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Anna’s Archive
Comprehensive search engine for books, papers, comics, magazines
...It relies heavily on technologies such as Elasticsearch for search functionality and MariaDB for structured data storage, enabling fast and efficient querying across massive datasets. The system is designed with redundancy and replication in mind, allowing distributed deployments and mirrored environments to handle high traffic and large data volumes. It also includes tooling for importing datasets, managing metadata, and maintaining structured archives using custom formats. -
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AI-Media2Doc
AI tool converting video/audio into structured documents instantly
AI-Media2Doc is a web-based application that uses large language models to convert video and audio content into structured, readable documents in a single workflow. It is designed to transform multimedia inputs into formats such as knowledge notes, summaries, mind maps, and social-style articles, making content easier to review and reuse. AI-Media2Doc emphasizes privacy by processing media locally in the browser using WebAssembly-based ffmpeg, ensuring that original video files are not uploaded externally. It separates client-side media handling from backend AI processing, reducing data exposure while still enabling transcription and document generation. ... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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5
Dispatcharr
Your Ultimate IPTV & Stream Management Companion
...It lets you import M3U/EPG sources, curate and organize them with filtering and grouping, and serve them reliably to clients like Plex, Jellyfin, and Emby with advanced proxying and failover support. Designed with both simple personal use and larger self-hosted setups in mind, Dispatcharr offers real-time streaming statistics, automated EPG matching, and a responsive interface that helps you manage your video on demand (VOD) content alongside live channels. The project has evolved from a personal tool to a collaborative open-source effort with beta-phase features including a dashboard, flexible proxy engine, and compatibility with multiple output formats. ... -
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Claude-Flow
The leading agent orchestration platform for Claude
Claude-Flow v2 Alpha is an advanced AI orchestration and automation framework designed for enterprise-grade, large-scale AI-driven development. It enables developers to coordinate multiple specialized AI agents in real time through a hive-mind architecture, combining swarm intelligence, neural reasoning, and a powerful set of 87 Modular Control Protocol (MCP) tools. The platform supports both quick swarm tasks and persistent multi-agent sessions known as hives, facilitating distributed AI collaboration with persistent contextual memory. At its core, Claude-Flow integrates Dynamic Agent Architecture (DAA) for self-organizing agent management, neural pattern recognition accelerated by WebAssembly SIMD, and a SQLite-based memory system for context retention and knowledge persistence across tasks. ... -
7
LTX-Video
Official repository for LTX-Video
...It provides runtime components that efficiently decode, encode, and manipulate video streams, frame buffers, and audio tracks while exposing a rich API for building customized editing features like transitions, effects, color grading, and keyframe automation. The toolkit is built with both real-time and offline workflows in mind, enabling applications from consumer editing to professional content creation and batch processing. Internally optimized for multi-core processors and hardware acceleration where available, LTX-Video makes it feasible to work with high-resolution content and complex timelines without sacrificing responsiveness. -
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notebooklm-py
Unofficial Python API and agentic skill for Google NotebookLM
...The project covers notebook management, source ingestion, conversational querying, research workflows, and sharing controls, while also enabling the generation of a wide range of study and media artifacts. These outputs include audio overviews, videos, slide decks, infographics, quizzes, flashcards, reports, data tables, and mind maps, with configurable formats and export options. -
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kotaemon
An open-source RAG-based tool for chatting with your documents
An open-source clean & customizable RAG UI for chatting with your documents. Built with both end users and developers in mind. This project serves as a functional RAG UI for both end users who want to do QA on their documents and developers who want to build their own RAG pipeline. -
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
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10
Procrastinate
PostgreSQL-based Task Queue for Python
...It allows you to schedule and execute background jobs using your existing database infrastructure, avoiding the need for additional queueing systems like Redis. Procrastinate is designed with simplicity, reliability, and observability in mind. -
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Authlib
The ultimate Python library in building OAuth, OpenID Connect
...Authlib is built from low level of specifications to high level of framework integrations. Security matters in Authlib. We have a section on security process at the very first begin. Authlib is created with sustainable maintainence in mind. Consider to buy a commercial plan. -
12
truffleHog
Searches through git repositories for high entropy strings and secrets
...TruffleHog is developed by a team entirely comprised of career security experts. Security is our passion and primary concern, and all features are developed with best practices in mind. TruffleHog enables you to track and manage secrets within our intuitive management interface, including links to exactly where secrets have been found. TruffleHog runs quietly in the background, continuously scanning your environment for secrets. -
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Claude Cookbooks
A collection of notebooks/recipes showcasing ways of using Claude
...The content is organized into thematic sections, allowing users to explore specific capabilities or integration patterns systematically. Designed with accessibility in mind, the examples are primarily written in Python but can be adapted to other languages. -
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Piccolo
A fast, user friendly ORM and query builder which supports asyncio
Piccolo is a modern, fast, and type-safe ORM for Python, designed with developer ergonomics in mind. It provides a clean syntax for defining schemas and building queries while supporting both sync and async execution. With built-in admin tools and rich introspection, Piccolo is suitable for web apps, APIs, and small-to-medium scale backends that prioritize clarity and speed. -
15
Flower
Flower: A Friendly Federated Learning Framework
...Flower allows for a wide range of different configurations depending on the needs of each individual use case. Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. Many components can be extended and overridden to build new state-of-the-art systems. Different machine learning frameworks have different strengths. Flower can be used with any machine learning framework, for example, PyTorch, TensorFlow, Hugging Face Transformers, PyTorch Lightning, scikit-learn, JAX, TFLite, MONAI, fastai, MLX, XGBoost, Pandas for federated analytics, or even raw NumPy for users who enjoy computing gradients by hand. -
16
I hate money
A simple shared budget manager web application
...It keeps track of who bought what, when, and for whom; and helps to settle the bills. I hate money is written in python, using the flask framework. It’s developed with ease of use in mind and is trying to keep things simple. Hope you (will) like it! The code is distributed under a BSD beerware derivative: if you meet the people in person and you want to pay them a craft beer, you are highly encouraged to do so. -
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The Algorithms Python
All Algorithms implemented in Python
...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, graph theory, and more. With contributions from a large global community, it continually grows and improves through collaboration and peer review. This repository is an ideal reference for students, educators, and developers seeking hands-on experience with algorithmic concepts in Python. -
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Tortoise ORM
Familiar asyncio ORM for python, built with relations in mind
Tortoise ORM is an easy-to-use asyncio ORM (Object Relational Mapper) for Python, inspired by Django's ORM. It is designed to work with asynchronous frameworks, providing a simple and familiar API for interacting with databases. Tortoise ORM supports various relational databases and is suitable for building high-performance web applications. -
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proxy.py
Utilize all available CPU cores for accepting new client connections
proxy.py is made with performance in mind. By default, proxy.py will try to utilize all available CPU cores to it for accepting new client connections. This is achieved by starting AcceptorPool which listens on configured server port. Then, AcceptorPool starts Acceptor processes (--num-acceptors) to accept incoming client connections. Alongside, if --threadless is enabled, ThreadlessPool is setup which starts Threadless processes (--num-workers) to handle the incoming client connections. ... -
20
LinkdAPI Python
Powerful, lightweight B2B Data API for enriching professional profiles
...It supports rapid development by abstracting low-level implementation details, allowing developers to focus on building features rather than managing connectivity. The project is designed with scalability in mind, making it suitable for both small applications and larger systems that require reliable API orchestration. It also emphasizes maintainability and clarity, ensuring that integrations remain consistent and easy to update over time. -
21
alive-progress
A new kind of Progress Bar, with real-time throughput, ETA
...Unlike traditional static progress indicators, it dynamically adjusts spinner speed and visual feedback based on actual throughput, giving users a more intuitive sense of activity. The library is designed with performance efficiency in mind, using multithreaded updates that minimize CPU overhead and terminal noise. It includes sophisticated ETA estimation powered by exponential smoothing algorithms, improving prediction accuracy for variable workloads. Developers can easily integrate it into scripts thanks to automatic logging hooks and flexible configuration options. ... -
22
Generative AI
Sample code and notebooks for Generative AI on Google Cloud
...The repository architecture is organised into folders like gemini/, search/, vision/, audio/, and rag-grounding/, which helps developers locate use cases by modality. It is licensed under Apache-2.0, opensourced and maintained by Google, meaning it's designed with enterprise-grade practices in mind. Overall, it serves as a practical entry point and reference library for building real-world generative AI systems on Google Cloud. -
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Pruna AI
Pruna is a model optimization framework built for developers
Pruna is an open-source, self-hostable AI inference engine designed to help teams deploy and manage large language models (LLMs) efficiently across private or hybrid infrastructures. Built with performance and developer ergonomics in mind, Pruna simplifies inference workflows by enabling multi-model orchestration, autoscaling, GPU resource allocation, and compatibility with popular open-source models. It is ideal for companies or teams looking to reduce reliance on external APIs while maintaining speed, cost-efficiency, and full control over their data and AI stack. ... -
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...As your data and ML workflows expand and demand more computing power, your workflow orchestration platform must keep up. If it’s not designed to scale, your platform will require constant monitoring and maintenance. Flyte was built with scalability in mind, ready to handle changing workloads and resource needs.
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Wemake Django Template
Bleeding edge django template focused on code quality and security
...The main idea of this project is to provide a fully configured template for django projects, where code quality, testing, documentation, security, and scalability are number one priorities. This template is a result of implementing our processes, it should not be considered as an independent part. When developing this template we had several goals in mind. Development environment should be bootstrapped easily, so we use docker-compose for that. Development should be consistent, so we use strict quality and style checks. Development, testing, and production should have the same environment, so again we develop, test, and run our apps in docker containers. Documentation and codebase are the only sources of truth. ...
