Fix Your AI-Built OpenAI API Integration
API for GPT models, embeddings, and image generation. AI tools expose API keys client-side, skip streaming error handling, and generate deprecated model references.
Common OpenAI API issues we find
Problems specific to AI-generated OpenAI API integrations.
API key exposed in client-side code
AI-generated code calls the OpenAI API directly from the browser using NEXT_PUBLIC_ prefixed environment variables, exposing your API key to every visitor.
No rate limiting or cost controls on proxy endpoint
Generated server-side proxy endpoints call OpenAI without rate limiting, allowing users to make unlimited requests and run up thousands of dollars in API costs.
Streaming response not handled correctly
AI tools implement chat streaming but don't properly handle stream errors, connection drops, or the [DONE] sentinel, causing hanging requests or missing response content.
Using deprecated models or API parameters
Generated code references deprecated models (text-davinci-003, gpt-3.5-turbo-0301) or uses removed parameters, causing API errors or degraded performance.
No token counting or context window management
AI tools send entire conversation histories without counting tokens, hitting context window limits and causing silent truncation or API errors on long conversations.
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Frequently asked questions
How do I prevent my OpenAI API key from being exposed?
Never call the OpenAI API from the browser. Create a server-side API route that proxies requests, add authentication, and implement per-user rate limiting. AI tools frequently expose the key by prefixing it with NEXT_PUBLIC_ or embedding it in client-side fetch calls.
Why is my AI-generated OpenAI streaming implementation breaking?
Common issues include not handling the ReadableStream correctly, missing error events in the stream, not parsing SSE data format properly, and failing to detect the [DONE] message. We fix the full streaming pipeline from API call to UI render.
How do I control costs on my OpenAI-powered feature?
AI tools create open proxy endpoints with no controls. You need per-user rate limiting, max token limits per request, input length validation, usage tracking per user, and spending alerts in the OpenAI dashboard. We implement all of these cost guardrails.
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