**ZkAGI SDK Architecture**
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**Overview**
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The ZkAGI SDK is a comprehensive solution for developers to leverage GPU clusters, track user contributions and usage, run ML and LLM models, and ensure privacy preservation. This document outlines the architecture of the ZkAGI SDK, highlighting its key components, technologies, and benefits.

**Getting Started**
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To get started with the ZkAGI SDK, please refer to our README and Documentation for more information.

**Code Structure**
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The ZkAGI SDK is organized into the following directories:

- gpu: GPU cluster connection and management
- tracker: Contribution and usage tracking
- model: ML and LLM models API
- proof: Privacy-preserved infrastructure

**GPU Cluster Connection**
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The GPU class manages connections to the GPU cluster using SSH or another secure protocol. Ray is used for distributed computing, allowing for efficient task distribution across the cluster. Fabric handles remote connections to the cluster.

**Contribution and Usage Tracking**
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The Tracker class tracks user contributions, such as time spent on tasks and tasks completed, as well as usage metrics, including GPU hours used and data transferred. A reward system calculates rewards based on contributions and usage.

**ML and LLM Models API**
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The Model class provides an API for running ML and LLM models. Zero-Knowledge Proofs (ZkProofs) are generated internally to ensure privacy preservation.

**Privacy-Preserved Infrastructure**
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The Proof class integrates ZkProof generation, encryption, and decryption using secure protocols. This safeguards user data confidentiality.

**SDK Interface**
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The Frame class provides a simple interface for developers to access functionalities. The intuitive API allows developers to easily import and utilize the SDK.

**Technologies**
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The ZkAGI SDK utilizes the following technologies:

- Ray for distributed computing
- Fabric for secure remote connections to the GPU cluster

**Benefits**
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The ZkAGI SDK offers several benefits, including:

- Scalable and efficient GPU cluster connection and task distribution using Ray
- Accurate tracking of user contributions and usage
- Easy-to-use API for running ML and LLM models
- Robust privacy preservation through ZkProofs
- Intuitive SDK interface for developers
