Unveiling the Mystery of MIDV-682: A Comprehensive Overview
| # | Requirement | Acceptance Criteria |
|---|-------------|----------------------|
| FR‑1 | Model Loading – The system must load the vision model lazily on the first upload page visit. | • Model size ≤ 10 MB (compressed).
• Loading indicator appears and disappears within 2 s on a typical 4G connection. |
| FR‑2 | Tag Generation – Generate up to 10 most confident tags per asset. | • Tags have confidence ≥ 0.55.
• Tags are sorted descending by confidence. |
| FR‑3 | Taxonomy Filtering – Only tags that belong to the approved taxonomy (configured via admin UI) are displayed. | • If a tag is not in the taxonomy, it is silently dropped.
• Admin can add/remove taxonomy entries without redeploying the frontend. |
| FR‑4 | User Interaction – Users can accept, remove, or edit each suggested tag. | • Clicking a checkbox toggles “accepted”.
• Inline text editing updates the tag instantly.
• “Add custom tag” button always available. |
| FR‑5 | Persistence – Final tag list is saved to the asset’s metadata on “Save”. | • API call returns 200 OK.
• Tags appear in the asset details view immediately after save. |
| FR‑6 | Performance – Tag generation must complete within 3 seconds for images ≤ 5 MB and videos ≤ 15 seconds for videos ≤ 30 seconds long. | • Measured on Chrome 119 (desktop) and Safari iOS 17. |
| FR‑7 | Privacy – No image data is transmitted to third‑party services. | • Network tab shows no outbound requests to external AI endpoints during tag generation. |
| FR‑8 | Fallback – If model loading fails, the UI gracefully degrades to manual tagging only. | • Error banner with “Retry” button appears.
• Existing manual tagging flow remains functional. | MIDV-682
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