Search Results for "brain"
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Showing 303 open source projects for "brain"
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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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Catch Bugs Before Your Customers DoMove from alert to fix before users notice. AppSignal monitors errors, performance bottlenecks, host health, and uptime—all from one dashboard. Instant notifications on deployments, anomaly triggers for memory spikes or error surges, and seamless log management. Works out of the box with Rails, Django, Express, Phoenix, Next.js, and dozens more. Starts at $23/month with no hidden fees.
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My Brain
Open-source, All-in-one productivity app for Tasks, Notes, Calendar
My Brain is an Open source, All-in-one productivity app for Tasks, Notes, Calendars, Diary, and Bookmarks. Private with no data collection and no internet permission at all. Create tasks with priority, sub-tasks, descriptions, and due dates and reminders. Create Notes that support markdown which enables you to use Headers, lists, links, etc. -
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CBIG
Computational Brain Imaging Group tools
Brain parcellation tools (e.g., Yeo networks, Schaefer parcellations) for cortical mapping. -
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second-brain-ai-assistant-course
Learn to build your Second Brain AI assistant with LLMs
The Second Brain AI Assistant Course is an open-source educational project designed to teach developers how to build a personal AI assistant that interacts with a user’s knowledge base. The course provides a structured curriculum that walks learners through the architecture and implementation of a production-ready AI system powered by large language models. -
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Brain Teaser
A fifteen-like game.
This computer game is based on BrainTeaser by Wim Nijland. Choose digits from 1 to 9, split by reaction method into three groups: 1-3-7-9, 2-4-6-8, and 5. The goal is to display all digits except 5, avoiding the field clearing and counter overflow. -
Gemini 3 and 200+ AI Models on One PlatformBuild generative AI apps with Vertex AI. Switch between models without switching platforms.
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hashcat
World's fastest and most advanced password recovery utility
...Please remember to use 7z x when unpacking the archive from the command line to ensure full file paths remain intact. Multi-Device-Types (Utilizing mixed device types in same system). Supports password candidate brain functionality. Supports distributed cracking networks (using overlay). Supports interactive pause / resume. Supports sessions. Supports restore. Supports reading password candidates from file and stdin. Supports hex-salt and hex-charset. Supports automatic performance tuning. Supports automatic keyspace ordering markov-chains. -
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Quivr
Your Second Brain supercharged by Generative AI
Quivr, your second brain, utilizes the power of GenerativeAI to store and retrieve unstructured information. Think of it as Obsidian, but turbocharged with AI capabilities. -
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pydantic
Data parsing and validation using Python type hints
Data validation and settings management using Python type hinting. Fast and extensible, pydantic plays nicely with your linters/IDE/brain. Define how data should be in pure, canonical Python 3.6+; validate it with pydantic. id is of type int; the annotation-only declaration tells pydantic that this field is required. Strings, bytes or floats will be coerced to ints if possible; otherwise an exception will be raised. name is inferred as a string from the provided default; because it has a default, it is not required. signup_ts is a datetime field which is not required (and takes the value None if it's not supplied). pydantic will process either a unix timestamp int (e.g. 1496498400) or a string representing the date & time. friends uses python's typing system, and requires a list of integers. ... -
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Clipboard
Your new smart clipboard manager
Your second brain that remembers anything, anytime, anywhere. The Clipboard Project (CB for short) is the oh-so-awesome clipboard manager that's just like a second brain. It's fast and lightweight, feature-packed, and super user-friendly. Anyone can use CB - no matter who you are or what you're working on, from web developers to your Average Joe and even to your grandma. -
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Khoj
An AI personal assistant for your digital brain
...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. -
Try Google Cloud Risk-Free With $300 in CreditUse your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
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Controllable-RAG-Agent
This repository provides an advanced RAG
Controllable-RAG-Agent is an advanced Retrieval-Augmented Generation (RAG) system designed specifically for complex, multi-step question answering over your own documents. Instead of relying solely on simple semantic search, it builds a deterministic control graph that acts as the “brain” of the agent, orchestrating planning, retrieval, reasoning, and verification across many steps. The pipeline ingests PDFs, splits them into chapters, cleans and preprocesses text, then constructs vector stores for fine-grained chunks, chapter summaries, and book quotes to support nuanced queries. At query time, it anonymizes entities, creates a high-level plan, de-anonymizes and expands that plan into concrete retrieval or reasoning tasks, and executes them in sequence while continuously revising the plan. ... -
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The Pope Bot
Autonomous AI agent that you can configure and build
...It’s designed so that every action taken by the agent is logged as a git commit, giving users complete visibility into what the agent did, why it did it, and when, which makes actions auditable and reversible. The framework treats the repository itself as the agent’s “brain,” and GitHub Actions serve as the compute layer, enabling tasks to run securely without exposing sensitive API keys to the underlying AI. The system integrates with messaging platforms like Telegram, where users can interact with the bot, trigger actions, or receive notifications, and supports scheduling and automation through patterns of request handling. -
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elm-format
elm-format formats Elm source code
...It makes code easier to write, because you never have to worry about minor formatting concerns while powering out new code. It makes code easier to read, because there are no longer distracting minor stylistic differences between different code bases. As such, your brain can map more efficiently from source to mental model. It makes code easier to maintain because you can no longer have diffs related only to formatting; every diff necessarily involves a material change. It saves your team time debating how to format things because there is a standard tool that formats everything the same way. It saves you time because you don't have to nitpick over formatting details of your code. -
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EEGLAB
EEGLAB is an open source signal processing environment
EEGLAB is an open source, MATLAB-based interactive environment for analyzing electrophysiological signals such as EEG and MEG. It incorporates powerful tools for data import, preprocessing, independent component analysis (ICA), time-frequency analysis, artifact rejection, and visualization—all within a GUI framework that also supports scripting and plugin extensions. EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and Octave (command... -
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Logseq
A privacy-first, open-source platform for knowledge management
...No data lock-in, no proprietary formats, you can edit the same Markdown/Org-mode file with any tools at the same time. Connect your [[ideas]] and [[thoughts]] with Logseq. Your knowledge graph grows just as your brain generates and connects neurons from new knowledge and ideas. -
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QuivrHQ
Opiniated RAG for integrating GenAI in your apps
Quivr is an open-source platform that leverages Retrieval-Augmented Generation (RAG) to integrate Generative AI into applications. It serves as a "second brain," enabling users to build powerful AI-driven assistants that can process and retrieve information efficiently. Quivr supports various large language models and vector stores, providing flexibility and customization for developers. -
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NoteDiscovery
Your Self-Hosted Knowledge Base
...The interface is modern and responsive, offering themes, tags, interactive note browsing, and visualization tools like graph views for connected ideas, which makes it suitable for personal “second brain” systems or team wikis. Users benefit from features like fast search, outline navigation, favorites, and plugin extensibility, and the platform works well across devices thanks to its responsive design. -
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MaxKB
Open-source platform for building enterprise-grade agents
MaxKB (Max Knowledge Brain) is an open-source platform for building enterprise-grade AI agents with strong knowledge retrieval, RAG pipelines, and workflow orchestration. It focuses on practical deployments such as customer support, internal knowledge bases, research assistants, and education, bundling tools for data ingestion, chunking, embedding, retrieval, and answer synthesis. -
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FieldTrip
The MATLAB toolbox for MEG, EEG and iEEG analysis
FieldTrip is the MATLAB software toolbox for MEG, EEG and iEEG analysis, which is released free of charge as open source software under the GNU general public license. FieldTrip is developed by members and collaborators of the Donders Institute for Brain, Cognition, and Behaviour at Radboud University, Nijmegen, the Netherlands. The toolbox offers advanced analysis methods of MEG, EEG, and invasive electrophysiological data, such as time-frequency analysis, source reconstruction using dipoles, distributed sources and beamformers and non-parametric statistical testing. It supports the data formats of all major MEG systems (CTF, Neuromag/Elekta/Megin, BTi/4D, Yokogawa/Ricoh, FieldLine) and of most popular EEG systems, and new formats can be added easily. ... -
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Swift Guide
Swift Featured Projects in brain Mapping
SwiftGuide is a comprehensive, community-maintained guide to the Swift programming language, designed to serve as both a learning resource and a handy reference. It covers all major language aspects: syntax, control flow, functions, closures, generics, protocols, extensions, memory management, concurrency, and the standard library. Each topic typically includes clear explanations, annotated code snippets, and tips for best practices, helping readers understand both how features work and how... -
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Pal
A personal context-agent that learns how you work
Pal is an open-source AI personal agent built within the Agno ecosystem that functions as an intelligent digital assistant designed to learn from user activity over time. The system acts as an AI-powered “second brain” capable of capturing, organizing, and retrieving personal knowledge such as notes, bookmarks, research findings, people, and meeting information. Instead of acting as a simple chatbot, Pal continuously builds a structured database of a user’s knowledge and context so it can answer questions, recall information, and assist with future tasks more effectively. ... -
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Neuroglancer
WebGL-based viewer for volumetric data
...It allows users to interactively view arbitrary 2D and 3D cross-sections of volumetric data alongside 3D meshes and skeleton models, enabling precise examination of neural structures and biological imaging results. Its multi-pane interface synchronizes multiple orthogonal views with a central 3D viewport, making it ideal for analyzing complex brain imaging data such as connectomics datasets. Neuroglancer operates entirely client-side, fetching data over HTTP in a variety of supported formats including Neuroglancer precomputed, N5, Zarr, and NIfTI, among others. The viewer is built with a multi-threaded architecture, separating rendering and data processing to ensure smooth performance even with massive datasets. ... -
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LingBot-VLA
A Pragmatic VLA Foundation Model
LingBot-VLA is an open-source Vision-Language-Action (VLA) foundational AI model designed to serve as a general “brain” for real-world robotic manipulation by grounding multimodal perception and language into actionable motions. It has been pretrained on tens of thousands of hours of real robotic interaction data across multiple robot platforms, which enables it to generalize well to diverse morphologies and tasks without needing extensive retraining on each new bot. -
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snntorch
Deep and online learning with spiking neural networks in Python
...Spiking neural networks are biologically inspired models that communicate through discrete spike events rather than continuous activation values, making them closer to how neurons operate in the brain. The library extends PyTorch’s tensor computation capabilities to support gradient-based learning for networks composed of spiking neurons. This allows researchers to train spiking neural models using familiar deep learning workflows while taking advantage of GPU acceleration and automatic differentiation. snnTorch provides implementations of common spiking neuron models, surrogate gradient training methods, and utilities for handling temporal neural dynamics. ... -
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Daptin
Daptin - Backend As A Service - GraphQL/JSON-API Headless CMS
Take the API overhead out of your brain with Daptin. Complete granular access to your data over the network. A single binary to power up your application. Database-backed persistence, 3NF normalized tables. JSON API/GraphQL for CRUD apis. User and group management and access control. Social login with OAuth: tested with google, github, LinkedIn. Actions for abstracting out business flows. -
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type-challenges
Collection of TypeScript type challenges with online judge
...Each challenge is a miniature kata where you implement types that transform other types—parsing strings, inferring tuples, mapping unions—without writing any runtime code. Problems are arranged from warm-ups to brain-twisters, letting developers build intuition about distributive conditional types, inference in extends, variance, and other corner cases of the type system. The repository includes tests for each puzzle so you get immediate, compiler-driven feedback when your solution is correct. As a result, it doubles as both training material and a living reference for advanced patterns used in real libraries. ...
