FreyaVideo outlines image API acceptance test beyond basic task success

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A technical note from FreyaVideo emphasizes that image generation API acceptance tests should verify more than just successful task completion. The note, prepared with AI assistance and based on integration records, outlines three separate checks: request acceptance, decoded output properties, and image usefulness for intended layouts. It provides examples from integration with Nano Banana 2.1 where requested specifications differed from actual outputs, such as aspect ratio deviations. The document warns that technical success does not guarantee usable images and advises recording multiple verification fields, including credits and provider invoices. These tests are presented as internal worksheets, not independent quality rankings.

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