๐๐ผ๐ ๐ ๐๐๐ถ๐น๐ ๐ฎ ๐ฆ๐ฒ๐ฐ๐๐ฟ๐ฒ ๐๐ ๐๐ฃ๐ ๐ฃ๐ฟ๐ผ๐ ๐
I build AI side projects. I always hit the same wall. I want to use AI on my frontend, but I cannot put API keys in the client.
A basic backend proxy is the answer. But my first attempts were messy and expensive.
If you put keys in the client, people steal them. If you have no rate limits, users drain your bank account. If you do not sanitize input, users trick your AI with prompt injection.
I stopped using simple redirects. I stopped using heavy enterprise gateways.
I built a small Node.js server with four specific rules:
- Request validation: I limit prompt length and clean the text.
- Rate limiting: I restrict requests per IP to prevent abuse.
- Response caching: I save identical answers for 5 minutes to save money.
- Cost logging: I track token usage to monitor my spending.
Here is the logic you should follow:
Rate limiting is mandatory. The internet is unpredictable. Even free tiers get abused quickly.
Cache smart. If two users ask the same thing, serve the cached version. If you build a real-time chat, use a shorter cache time.
Log everything. Track your tokens and error rates. Do not store sensitive user data in your logs.
Sanitize input. Strip out anything that looks like a system command.
If your app grows, move this logic to Cloudflare Workers. It runs globally and handles caching at the edge. For batch tasks, use a queue like AWS SQS to keep costs predictable.
Building a proxy is simple. Getting the details right is what saves your project.
What is your setup for AI APIs? Do you use a specific stack or a caching trick?
Source: https://dev.to/__c1b9e06dc90a7e0a676b/how-i-built-a-secure-ai-api-proxy-without-losing-my-sanity-b1n
Optional learning community: https://t.me/GyaanSetuAi