Hubs in SwarmZero
Last updated
Was this helpful?
Last updated
Was this helpful?
SwarmZero is a decentralized AI platform designed to leverage distributed computing resources for running AI models and agents. The platform is structured into three main hubs: the Agent Hub, the Model Hub, and the Research Hub.
Each hub serves a unique purpose in the ecosystem, providing specialized services and capabilities for users and contributors. This documentation provides an overview of the platform and detailed sections for each of the three hubs.
The Agent Hub is the entry point of SwarmZero, where AI agents are deployed, managed, and interacted with by users. It provides a flexible and scalable environment for running various types of AI agents, from chatbots to complex data processing tools.
Agent Deployment: Easily deploy AI agents using Docker containers.
API Interaction: Interact with agents through a RESTful API.
Observability: Monitor agent performance, API successes/failures, system metrics, and logs.
Chat History: Store and retrieve chat history with integrated database support.
Hive Agent Server: Exposes resources for chatting with an LLM and for data storage and management.
Hive Agent Client: Used by agent containers to make API calls to the Hive Agent Server.
The Model Hub is designed to facilitate the training, sharing, deployment, and fine-tuning of AI models. It allows users to contribute their models to the network, and others to utilize these models for their own agents or applications.
Model Repository: Store and manage AI models.
Model Fine-Tuning: Fine-tune models to specific tasks or datasets.
Decentralized Compute: Utilize distributed resources for model training and inference.
The Research Hub fosters collaboration and innovation by providing a platform for sharing research, datasets, and experimental results. It aims to accelerate AI advancements through open science and community-driven projects.
Research Publications: Share and access research papers and articles.
Dataset Repository: Contribute and utilize datasets for training and evaluation.
Experiment Tracking: Track experiments, including configurations, results, and reproducibility.
By utilizing the features and components of SwarmZero.ai, developers can efficiently build, deploy, and manage AI agents, models, and research projects in a decentralized and collaborative environment.
For further details, please refer to the specific documentation for each hub or contact the SwarmZero.ai support team.
