ModAPISTROUBLESHOOTING · ERROR FAQ
GPT Image Content Policy Violations: Full Troubleshooting Guide
GPT image tools review two inputs, not one: the prompt and every image you upload. Most "content policy violation" surprises in gpt-image workflows come from the upload side — a reference photo carries content the prompt never mentioned. This guide covers the triggers specific to image generation and editing, a pre-check list for uploads, an editing strategy (inpaint, don't regenerate) that recovers blocked edits, and how repeated violations actually affect your account. For the API path, the last section shows filter errors you can branch on, via Nano Banana Pro on ModAPIS — an OpenAI Images-compatible endpoint away.
Image-specific triggers (including the upload side)
- Reference images containing identifiable people, logos, or artwork the prompt then "restyles".
- Photo-realistic uploads of minors in any context — the strictest line there is.
- Violence-adjacent source material: injury photos, weapons in-frame, accident scenes.
- Before/after medical or body-modification pairs, which read as outcome claims.
- Screenshots with other people's content, names, or messages visible.
Pre-check list for uploads
- Crop to the subject — remove bystanders, backgrounds, and screens you don't need.
- Blur or patch visible faces of non-subjects before uploading.
- Strip logos and brand marks from garments and objects.
- Prefer your own or licensed photos over anything scraped.
- If the edit target is a person, keep clothing, pose, and setting uncontroversial.
Editing strategy: inpaint instead of regenerate
When a full-image regeneration trips the filter, the violation is often one region — a face in the corner, a logo on a shirt. Mask-based local repaint sends only that region for re-generation, keeps the rest of the image untouched, and passes review far more often, because the model never re-interprets the innocent 90% of the frame. Nano Banana Pro's editing API takes an image plus a mask plus an instruction, which maps exactly onto this pattern.
Repeat violations and cooldown reality
One refusal costs nothing. Several refusals of the same category inside an hour tighten the session filter — prompts that passed an hour ago start failing. The practical cooldown is behavioral, not punitive: stop for a few hours, rewrite the recurring clause, and the baseline resets. Account-level warnings appear only for sustained, clearly intentional policy pushes, and they show up in account settings, not as image errors.
API alternative: OpenAI-compatible image editing
ModAPIS exposes image generation and editing behind an OpenAI Images-compatible interface — existing SDK code works after changing the base URL, so a blocked-prompt handler can be a try/catch around a structured filter error rather than a human reading prose. Failed generations are not charged. See the quickstart, the broader content policy guide, or the API filter-handling guide for the engineering side.