Documentation Index
Fetch the complete documentation index at: https://docs.boostgpt.co/llms.txt
Use this file to discover all available pages before exploring further.
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
Deploy to Vercel
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 });
}
2. Deploy
Deploy Router SDK
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();
2. Deploy to Railway
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
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
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
Next Steps
Error Handling
Handle errors gracefully