SHABAN-AI provides a WhatsApp bot built on the Baileys library. This JavaScript project supports WhatsApp's Multi-Device mode, allowing operation across linked devices without a phone connection after initial pairing. Released in beta as version 5, it targets users seeking a lightweight, deployable bot for messaging automation. The repository at botkeeda/SHABAN-AI has 16 stars and emphasizes speed and stability through its Baileys foundation. A demo runs at mr-shaban.vercel.app.

The bot exists to simplify WhatsApp interactions via scripts, common for group management, replies, or custom commands in open-source bot ecosystems. Developers behind it, listed as Team Bandaheali, position it as "Mr Shaban," with visuals and badges highlighting Node.js power and recent Baileys integration.

Core features

SHABAN-AI sticks to essentials for a Baileys-based WhatsApp bot:

  • Multi-Device support: Connects via WhatsApp's official pairing code, scanned through a web interface called SHABAN-MD Pairing Web.
  • Baileys latest: Uses the current multi-device version of Baileys, a Socket.IO-based WhatsApp Web API reverse-engineered in JavaScript.
  • Node.js runtime: Runs server-side with Node.js, suited for deployment on platforms like VPS or PaaS.
  • Stability focus: Badges and descriptions note enhancements for reliable operation, though specifics depend on session handling in Baileys.
  • Customizable settings: Requires environment variables under a "Setting" configuration for bot behavior.

These align with standard Baileys bots, where core logic handles messages, media, and groups without proprietary WhatsApp APIs.

Getting it running

Deployment centers on forking the repository and hosting it on a Node.js-compatible platform. No local npm install instructions appear in the README; it's geared for cloud or VPS setups.

Start by starring and forking the repo:

  1. Visit github.com/botkeeda/SHABAN-AI/fork to create your copy.

Next, choose a deployment method—options include Heroku, Railway, Koyeb, Render, VPS, KataBump, or bot hosting services. Common steps across platforms:

  • Clone or access your forked repo.
  • Configure environment variables labeled "Setting" (exact vars not listed in README; check repo files like .env.example or config.js post-fork).
  • Deploy via platform-specific buttons (e.g., Railway's "Deploy" from GitHub) or manual setup: git clone, npm install (assumed for Node.js deps), then start with node index.js or equivalent.

After deployment, link the bot using the SHABAN-MD Pairing Web. This generates a QR code or pairing code for WhatsApp's device linking—scan from the WhatsApp app under Linked Devices.

Repo stats offer clues on scale: last commit recent, size modest (badge shows repo size), suiting quick deploys. Profile views and followers track botkeeda's activity. For VPS, expect standard Node.js setup:

git clone https://github.com/YOURUSERNAME/SHABAN-AI.git
cd SHABAN-AI
npm install
# Edit settings vars in .env or config
node .  # Or bot start script

Use PM2 or systemd for persistence: pm2 start index.js --name shaban-ai. Platforms like Render auto-handle builds from package.json.

Troubleshooting follows Baileys norms: clear sessions on restarts, monitor logs for auth errors. Multi-device avoids phone dependency post-pairing.

Who this is for

SHABAN-AI fits developers or hobbyists building WhatsApp automations without deep WhatsApp expertise. It serves group admins needing broadcast replies, fun command bots, or API wrappers for external services. Self-hosters on free tiers (Railway hobby, Render free) get quick starts, as forking bypasses original repo locks.

Use cases include:

  • Personal bots for reminders or polls in family chats.
  • Community tools for moderation, like auto-welcome messages.
  • Integrations with other Node.js scripts, leveraging Baileys events for incoming messages.

Node.js familiarity helps tweak features; beginners stick to deployment. Small scale (16 stars) means active maintenance from botkeeda, but expect community contributions via forks. Not for production-scale bots handling thousands of messages—Baileys can hit rate limits.

How it compares

Other Baileys bots like WhatsApp-Web.js or forks such as LiberaChat offer similar multi-device WhatsApp access. SHABAN-AI differentiates via its deploy-focused README, with platform buttons and styled pairing. Heavier alternatives like BotWA or Secktor add plugins out-of-box but bloat repo size.

Compared to non-Baileys options:

  • Official WhatsApp Business API requires approval and fees; SHABAN-AI stays free/open.
  • Venom-Bot (Puppeteer-based) needs browser overhead, slower than Baileys' socket efficiency.

At 16 stars, it's lighter than popular bots (e.g., SadBoi hours at 1k+ stars), trading features for simplicity. If needing AI integration (name hints at it, but README shows none), pair with external APIs like OpenAI via custom code.

Repo and resources

The project remains in beta V.5, with visuals like glowing badges and a central bot image emphasizing aesthetics. Track updates via GitHub badges: followers, last commit, repo size. Forking enables private tweaks.

For similar bots, scan Baileys ecosystem on GitHub. Source at github.com/botkeeda/SHABAN-AI; demo at mr-shaban.vercel.app. Larger teams might outgrow it; solo deployers find it direct.

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