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Rachasumanth
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cloud-storage

Synchronize Text2LLM project artifacts to Google Drive, Dropbox, and AWS S3.

Updated Feb 17, 2026
Search Tags:#oauth#backup#artifacts#sync#data persistence#cloud storage
One-click install
npx skills add https://github.com/Rachasumanth/text2llm001 --skill cloud-storage
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cloud-storage
Source: https://github.com/Rachasumanth/text2llm001/tree/main/workspace/skills/cloud-storage
Command: npx skills add https://github.com/Rachasumanth/text2llm001 --skill cloud-storage

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pydrive2, dropbox, msal, requests, mega.py, boto3, google-cloud-storage, azure-storage-blob, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill enables seamless synchronization of Text2LLM project artifacts to various cloud storage providers, ensuring data persistence and accessibility.

Core Features & Use Cases

  • Multi-Provider Support: Integrates with Google Drive, Dropbox, OneDrive, MEGA, AWS S3, Google Cloud Storage, and Azure Blob Storage.
  • Secure Authentication: Manages user-scoped OAuth and session tokens without storing raw credentials.
  • Resumable Uploads: Handles large file transfers with interruption recovery and integrity checks.
  • Quota Awareness: Monitors cloud storage quotas and provides early warnings for low space.
  • Use Case: Automatically back up your latest training checkpoints and model artifacts to Google Drive after each training epoch, with the ability to resume uploads if the connection drops.

Quick Start

Use the cloud-storage skill to sync the 'checkpoints/' directory to Google Drive.

Frequently Asked Questions about cloud-storage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I sync training checkpoints to Google Drive?▼

To sync training checkpoints to Google Drive, you use the cloud-storage skill to map your 'checkpoints/' directory and execute an automated synchronization process. It manages secure OAuth authentication and uploads artifacts directly to your selected provider.

Can I resume large model artifact uploads if my connection drops?▼

Yes, you can resume large model artifact uploads if your connection drops. The synchronization process handles resumable uploads with interruption recovery and performs integrity checks to ensure persistent data storage without restarting.

Does this approach support backing up artifacts to AWS S3 and Azure Blob Storage?▼

Yes, backing up artifacts supports AWS S3 and Azure Blob Storage, alongside Dropbox, OneDrive, MEGA, and Google Cloud Storage. You select your preferred backend, and the process handles provider-specific authentication and data persistence.

What Python libraries do I need to synchronize project artifacts to Dropbox?▼

To synchronize project artifacts to Dropbox, you need the 'dropbox' Python library installed. Other providers require specific dependencies like 'pydrive2' for Google Drive or 'boto3' for AWS S3 integration.

Why does my cloud storage backup fail when I exceed my quota?▼

Your cloud storage backup fails when exceeding quota because the process includes quota awareness that monitors storage limits. It provides early warnings for low space to prevent failed artifact transfers and ensure checkpoint management.

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