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Deployment Options

Vercel

Deploy serverless functions with zero config

Railway

Deploy with automatic scaling

AWS Lambda

Run on AWS serverless infrastructure

Docker

Containerize and deploy anywhere

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Deploy to Vercel

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1. Create API Route

Create api/chat.js: 
import { BoostGPT } from 'boostgpt';

const client = new BoostGPT({
  project_id: process.env.BOOSTGPT_PROJECT_ID,
  key: process.env.BOOSTGPT_API_KEY
});

export default async function handler(req, res) {
  if (req.method !== 'POST') {
    return res.status(405).json({ error: 'Method not allowed' });
  }

  const { message, bot_id } = req.body;

  const response = await client.chat({
    bot_id,
    message
  });

  if (response.err) {
    return res.status(500).json({ error: response.err });
  }

  return res.status(200).json({ response: response.response });
}

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2. Deploy

vercel --prod

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Deploy Router SDK

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1. Create Server

import { Router, DiscordAdapter } from '@boostgpt/router';

const router = new Router({
  apiKey: process.env.BOOSTGPT_API_KEY,
  projectId: process.env.BOOSTGPT_PROJECT_ID,
  defaultBotId: process.env.BOOSTGPT_BOT_ID,
  adapters: [
    new DiscordAdapter({
      discordToken: process.env.DISCORD_TOKEN
    })
  ]
});

await router.start();

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2. Deploy to Railway

railway up

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Environment Variables

Set these in your deployment platform: 
BOOSTGPT_PROJECT_ID=your_project_id
BOOSTGPT_API_KEY=your_api_key
BOOSTGPT_BOT_ID=your_bot_id

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Docker Deployment

FROM node:18-alpine

WORKDIR /app

COPY package*.json ./
RUN npm ci --production

COPY . .

CMD ["node", "index.js"]
Build and run: 
docker build -t boostgpt-bot .
docker run -e BOOSTGPT_API_KEY=key boostgpt-bot

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Best Practices

  • Always use environment variables for credentials
  • Implement proper error handling
  • Use health check endpoints
  • Monitor with logging services
  • Set up auto-scaling for high traffic

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Next Steps

Error Handling

Handle errors gracefully