Search Results for "i2b2 shared task"
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Showing 56 open source projects for "i2b2 shared task"
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OpenWork
An open-source alternative to Claude Cowork, powered by opencode
OpenWork is a framework for building decentralized collaborative work environments powered by AI and human contributions. At its core, the project enables contributors to define tasks, workflows, and goals that can be split, shared, and recombined across distributed nodes while agents and humans cooperate to advance progress. It offers structured templates for work items, decision logic for task allocation, and consensus mechanisms that let groups verify and validate results toward shared objectives. This project also includes moderation and reputation layers so that contributor trust and quality can be assessed and integrated into future task assignments. ... -
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Phproject
A high performance full-featured project management system
Phproject is a modular project management platform built with PHP. It includes task management, file sharing, time tracking, and calendars, making it a versatile tool for team productivity. Phproject is fully self-hosted and ideal for organizations needing a customizable, open-source project management solution. -
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CC Mirror
Create multiple isolated Claude Code variants with custom providers
...It also includes an interactive terminal UI for discovering, creating, and launching these isolated variants with a single command, making setup and switching effortless. For teams, cc-mirror’s team mode brings shared task storage and coordinated multi-agent workflows using shared goals and task lists that agents can collaborate on; this is useful for scaling up agentic coding across complex projects. -
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Alook
The collaboration layer for your AI workforce
Alook is an open-source, self-hosted platform for running local AI coding agents as a coordinated workforce. It lets users give agents defined roles, email addresses, task boards, calendars, and shared workflows so they can collaborate more like a real team. The platform connects local agents to external communication channels while keeping the actual agents and codebase running on the user’s own machine. It is designed for developers, solo founders, and teams that want multiple AI agents to handle development, operations, research, and routine work with clearer structure. ... -
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Claw3D
Claw3D is an open source 3D engine built on OpenClaw
...The system supports task assignment, progress tracking, and communication between agents, creating a representation of autonomous or semi-autonomous workflows. It can be self-hosted, giving users full control over deployment, customization, and scaling of their AI workspace. -
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Kanwas
Shared context board for teams and agents
Kanwas is an open-source shared context board built for teams and AI agents working together in the same workspace. It gives people and agents a common canvas where documents, evidence, decisions, notes, tasks, embeds, and outputs can live side by side. Instead of scattering context across chats, documents, and disconnected tools, Kanwas turns messy collaborative work into a shared visual environment that both humans and agents can read and update. The platform supports real-time... -
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super-agent-party
All-in-one AI companion! Desktop girlfriend + virtual streamer
...The platform is primarily intended as a research and demonstration environment for experimenting with agent collaboration strategies. Developers can use it to study coordination patterns, communication protocols, and task decomposition in multi-agent systems. -
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BroadcastChannel
BroadcastChannel to send data between different browser-tabs or nodejs
...It is tested across old browsers, modern browsers, Web Workers, iframes, and Node.js. It also includes leader election over channels, which helps multiple contexts decide which one should perform a shared task. It is useful for multi-tab synchronization, offline-first applications, shared state coordination, and browser apps that need to avoid duplicated background work. -
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Automa
A chrome extension for automating your browser by connecting blocks
...Try a workflow from the marketplace. There're dozens of workflows been shared by Automa users which you can add and customize. Auto-fill forms, do a repetitive task, take a screenshot, or scrape website data, the choice is yours. You can even schedule when the automation will execute! Browse the Automa marketplace where you can share and download workflows with others. -
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Cua
Open-source infrastructure for Computer-Use Agents. Sandboxes
...It introduces a declarative syntax for specifying build scripts, automation pipelines, environment setups, and project-specific commands so contributors don’t need to memorize disparate scripts or tooling across languages and ecosystems. Cua can also manage task dependencies, handle cross-platform invocations, and simplify complex workflows into simple aliases or compound commands that are easy to share in teams. By centralizing shared commands in a structured, documented config, it helps reduce errors, accelerates onboarding of new contributors, and keeps task definitions versioned with the codebase. ... -
11
METATRON
AI-powered penetration testing assistant using local LLM on linux
METATRON is a multi-agent AI orchestration framework designed to coordinate complex workflows across multiple intelligent agents. It provides a structured system for task delegation, communication, and collaboration between agents. The framework emphasizes scalability, allowing multiple agents to work together on large or complex problems. It includes mechanisms for managing context, memory, and execution flow across tasks. METATRON is particularly useful for building advanced AI systems... -
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Tutti
Where people and agents build in tune
Tutti is an open-source shared workspace for people working with multiple AI agents. It is built to reduce the copy-paste handoff problem between tools such as Claude Code, Codex, Canvas, and other agent systems. The workspace connects context, files, app outputs, conversations, and running tasks so agents can build on each other’s work. Users can reference previous conversations, files, tasks, and app results directly instead of re-explaining the project state. Tutti also includes an app... -
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Vikunja
The to-do app to organize your life
Vikunja is a modern to-do list and personal organization platform designed to help individuals and teams keep track of tasks, projects, and life goals in one place with intention and simplicity. It’s a self-hosted, open-source app with a backend API and frontend clients that let you create tasks, organize them into lists or projects, set due dates and priorities, and collaborate with teammates or family members. Unlike many simplistic check-off lists, Vikunja provides options for nested... -
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Oh My codeX (OMX)
Your codex is not alone. Add hooks, agent teams, HUDs
Oh My codeX (OMX) is a multi-agent orchestration layer designed to extend the capabilities of OpenAI Codex CLI by introducing structured teamwork, automation, and advanced workflow management. It addresses limitations in the base Codex environment, such as the lack of hooks, agent coordination, and persistent execution, by layering a shell-based system that enables richer interaction patterns. The project transforms a single AI coding assistant into a coordinated system of specialized agents... -
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colleague-skill
Transform a cold separation into a warm Skill
colleague-skill is a specialized agent skill designed to simulate a collaborative teammate within AI-driven workflows, enabling agents to behave more like human colleagues in problem-solving scenarios. The project focuses on enhancing interaction quality by introducing role-based behavior, contextual awareness, and cooperative task execution. It allows agents to provide suggestions, feedback, and alternative approaches, mimicking real-world collaboration dynamics. The system likely integrates with broader agent frameworks, enabling seamless inclusion in multi-agent environments. It emphasizes communication and coordination, ensuring that agents can contribute meaningfully to shared objectives. ... -
16
agent heroes
Generate, animate and schedule your AI characters
...The project emphasizes multi-agent systems where different agents are assigned roles, responsibilities, and tools, allowing them to interact and coordinate toward a shared objective. It provides abstractions for defining agent behavior, communication patterns, and task execution pipelines, enabling developers to build systems that go beyond simple prompt-response interactions. The framework is designed to integrate with modern large language models and external APIs, allowing agents to access tools, retrieve data, and perform actions dynamically. ... -
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OpenSpace
OpenSpace: Make Your Agents: Smarter, Low-Cost, Self-Evolving
OpenSpace is a self-evolving agent framework designed to improve the performance, efficiency, and collaboration of AI agents through continuous learning and shared knowledge. It introduces a system where agents develop reusable “skills” based on real task execution, allowing them to improve over time without retraining underlying models. The platform emphasizes collective intelligence, enabling multiple agents to share learned behaviors and benefit from each other’s experiences. It also focuses on cost efficiency by reducing redundant computations and reusing successful workflows, significantly lowering token usage in repeated tasks. ... -
18
CLIP
CLIP, Predict the most relevant text snippet given an image
CLIP (Contrastive Language-Image Pretraining) is a neural model that links images and text in a shared embedding space, allowing zero-shot image classification, similarity search, and multimodal alignment. It was trained on large sets of (image, caption) pairs using a contrastive objective: images and their matching text are pulled together in embedding space, while mismatches are pushed apart. Once trained, you can give it any text labels and ask it to pick which label best matches a given image—even without explicit training for that classification task. -
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StabilityMatrix
Multi-Platform Package Manager for Stable Diffusion
StabilityMatrix is a project that helps organize, evaluate, and compare generative AI models and their behavior across prompts, datasets, or configuration settings. It provides a framework to run experiments systematically—capturing inputs, model configurations, outputs, and metrics—so researchers and practitioners can reason about differences in quality, robustness, and failure modes. The repository often bundles tooling for automated prompt sweeping, scoring heuristics (such as diversity,... -
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Lingvo
Framework for building neural networks
Lingvo is a TensorFlow based framework focused on building and training sequence models, especially for language and speech tasks. It was originally developed for internal research and later open sourced to support reproducible experiments and shared model implementations. The framework provides a structured way to define models, input pipelines, and training configurations using a common interface for layers, which encourages reuse across different tasks. It has been used to implement state of the art architectures such as recurrent neural networks, Transformer models, variational autoencoder hybrids, and multi task systems. ... -
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Fluent Bit Plugin for CloudWatch Logs
A Fluent Bit output plugin for CloudWatch Logs
...This plugin uses the AWS SDK Go, and uses its default credential provider chain. If you are using the plugin on Amazon EC2 or Amazon ECS or Amazon EKS, the plugin will use your EC2 instance role or ECS Task role permissions or EKS IAM Roles for Service Accounts for pods. The plugin can also retrieve credentials from a shared credentials file, or from the standard AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_SESSION_TOKEN environment variables. A template in the form of $(variable) can be set in log_group_name or log_stream_name. variable can be a map key name in the log message. ... -
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Context Hub
Makes coding agents get smarter with every task
Context Hub is a curated documentation system built to help coding agents write more accurate code. It gives agents versioned, language-specific reference material instead of forcing them to rely on noisy web searches or stale model memory. The project includes a CLI called chub that agents can use to search for available docs, fetch specific API guidance, and request only the files they need. It also supports local annotations, allowing an agent to remember project-specific notes, pitfalls,... -
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Open Agents
An open source template for building cloud agents
...It focuses on enabling developers to create agents that can collaborate, execute tasks, and interact with tools in a structured environment. The framework provides abstractions for agent communication, task orchestration, and tool integration, allowing multiple agents to work together toward shared objectives. It emphasizes openness and interoperability, making it easier to integrate with different models, APIs, and external systems. The project also includes examples and templates that demonstrate how to build and deploy agents for real-world applications. ... -
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redshirt
Operating system
Redshirt is an experimental operating system written in Rust that explores new approaches to OS design by emphasizing asynchronous execution, message passing, and modularity. It is built around a microkernel-inspired architecture where components communicate through well-defined interfaces rather than relying on shared state. The system is designed to run on top of WebAssembly, using it as a portable and sandboxed execution layer for processes and services. Redshirt aims to rethink traditional operating system concepts by leveraging modern programming paradigms such as async/await and capability-based security. It includes components for task scheduling, device interaction, and system services, all implemented in a highly modular fashion. ... -
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spacy-transformers
Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy
spaCy supports a number of transfer and multi-task learning workflows that can often help improve your pipeline’s efficiency or accuracy. Transfer learning refers to techniques such as word vector tables and language model pretraining. These techniques can be used to import knowledge from raw text into your pipeline, so that your models are able to generalize better from your annotated examples. You can convert word vectors from popular tools like FastText and Gensim, or you can load in any...