AI & Automation
OpenAI API Integration Services
Integrating the OpenAI API into a real application is more than sending a prompt and displaying the response — it involves managing context windows, parsing structured output reliably, handling function calling for actions the model should trigger, and controlling cost as usage scales.
I integrate the API into existing Node.js and Next.js applications, treating error handling and cost monitoring as core requirements rather than something to add after launch.
What's Included
- checkChat completions with proper streaming for responsive UI
- checkStructured output (JSON mode / function calling) for responses your app can parse reliably
- checkContext management for conversations that need memory across turns
- checkRate limit and error handling, including retries with backoff
- checkCost tracking per request or per user
Function Calling
Function calling lets the model decide when to trigger a specific action in your app — looking up an order, scheduling an appointment — by returning structured arguments instead of free text you'd have to parse. This is what turns a chatbot from something that only talks into something that can actually do things inside your application.
Frequently Asked Questions
Which OpenAI model should I use?add
Depends on the task's complexity and cost sensitivity — a smaller, faster model is often sufficient and cheaper for classification or extraction tasks, while more complex reasoning tasks benefit from a larger model. I test against the actual task rather than defaulting to the most expensive option.
How do you keep API costs predictable?add
Setting per-user or per-feature usage limits, caching responses where the same query repeats, and choosing the smallest model that reliably handles the task — cost scales directly with tokens processed, so trimming unnecessary context matters.
What is function calling used for?add
Letting the model trigger real actions — querying a database, calling another API — by returning structured arguments matching a function signature you define, rather than free-text output your app would have to parse and guess at.