Picking a text-to-image API for a SaaS app: REST, pricing, and safety

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<p>In the previous article you built an agent that generates on-brand copy with memory and context. But a social media post without an image is an invisible post.</p> <p>The

<p>How it works:</p> <p>Request arrives at an OpenAI-compatible endpoint<br /> Classifier detects task type + complexity<br /> Adaptive router picks the highest-scoring model for

<p>Most AI image workflows start with a prompt and end with a downloaded file. That is fine for a one-off experiment, but it breaks down as soon as a team needs to reproduce the

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<h2> TL;DR </h2> <p>Modern WebAssembly codecs (MozJPEG, libavif, OxiPNG/imagequant, libwebp, gifsicle, SVGO) now run fast enough in the browser that you can ship a real

<p>Storage fan-out changes the moderation answer: a customer-support photo may be retained as an original, normalized into another representation, sent through OCR, and cached

<p>Short answer: For cheap bulk CSV tagging, use an asynchronous LLM text classification API, estimate each tenant batch before it runs, and attach the eventual export to the same