Chatbots are surprisingly easy to trick. Moving an LLM application past prototyping means wrestling with security issues like prompt injection, token cost overhead, and strict infrastructure constraints.
Here is how you can build and deploy a protected version on Upsun:
The problem: Simple context stuffing (loading documentation directly into the prompt) makes your LLM vulnerable to malicious user overrides and sudden token cost spikes.
The fix: This tutorial builds a Node.js app using LangChain and OpenAI, pairing it with immediate input validation, rate limiting, and output filtering to keep the model in its lane.
Why it matters: You get a secure, web-accessible chat interface with streaming responses that deploys directly to Upsun with a single push, stripping out the deployment complexity.
Ready to implement prompt injection defense and see the full code walkthrough?
Check out the full tutorial here 👉
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