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vercel-blob

Add Vercel Blob storage to your bot for persistent state, conversations, and logs. Uses JSON files stored in Vercel's object storage. Perfect for bots that need to remember state across sandbox restarts.

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Dépôt
opldotdev/clawnet-bot
Dernière activité de la source
5 février 2026 à 18:36
Langue détectée de SKILL.md
anglais
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SKILL.md
Instructions source · Aperçu en lecture seule
name
vercel-blob
description
Add Vercel Blob storage to your bot for persistent state, conversations, and logs. Uses JSON files stored in Vercel's object storage. Perfect for bots that need to remember state across sandbox restarts.
metadata
{"author":"b-open-io","version":"0.0.1","supports":["agent","bot"]}
# Vercel Blob Storage This skill adds Vercel Blob storage to your bot for persistent data across sandbox restarts. ## Storage Strategy Data is organized by bot name: ``` bots/{bot-name}/ ├── state.json # Bot state (counters, config, etc.) ├── config.json # Bot configuration ├── conversations/ │ ├── {session-id}.json # Individual conversation sessions │ └── ... └── logs/ └── {YYYY-MM-DD}.json # Daily log files ``` ## Setup Run the setup script: ```bash ./skills/vercel-blob/scripts/setup.sh ``` This creates a Vercel Blob store for your bot. ## API Endpoints Once added, your bot gets these endpoints: ### State Management - `GET /api/storage/state` - Load current state - `POST /api/storage/state` - Save state ### Conversations - `GET /api/storage/conversations` - List all conversations - `GET /api/storage/conversations/:id` - Load specific conversation - `POST /api/storage/conversations/:id` - Save conversation ### Logs - `POST /api/storage/log` - Append log entry - `GET /api/storage/logs` - Get recent logs ## Usage from Bot Code ```typescript // Save bot state await fetch('/api/storage/state', { method: 'POST', body: JSON.stringify({ lastRun: Date.now(), counter: 42, config: { theme: 'dark' } }) }); // Load state const state = await fetch('/api/storage/state').then(r => r.json()); // Log activity await fetch('/api/storage/log', { method: 'POST', body: JSON.stringify({ level: 'info', message: 'Bot started', metadata: { version: '1.0.0' } }) }); // Save conversation await fetch('/api/storage/conversations/session-123', { method: 'POST', body: JSON.stringify({ messages: [ { role: 'user', content: 'Hello!' }, { role: 'bot', content: 'Hi there!' } ] }) }); ``` ## Environment Variables Add to `.env.local`: ``` BLOB_READ_WRITE_TOKEN=your_token_here ``` ## How It Works 1. **Bot starts** → Automatically loads state from Blob 2. **During operation** → State saved periodically + on changes 3. **Bot stops** → Final state flush to Blob 4. **Next deployment** → State restored from Blob ## File Structure - `state.json` - Small, frequently updated (bot state) - `conversations/*.json` - Session-based (conversation history) - `logs/*.json` - Append-only (daily log files) ## Limitations - Max file size: 500MB - No SQL queries (file-based only) - List operations can be slow with many files - Best for: State, logs, config, small conversation histories ## Pricing - Free tier: 250MB storage, 1000 operations/month - See: https://vercel.com/pricing
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