{
  "aboutHtml": "<h4>在 Krea 2 系列中快速探索</h4><p>Krea 2 Medium Turbo 是 Krea 以 Krea 2 Turbo 名稱介紹的生成版本。模型專屬介面將其識別為 Medium Turbo 變體，而 Krea 使用指南說明，它採用經蒸餾的取樣排程，減少生成圖片所需的工作量。Krea 將其定位為此系列中最快的選項，適合廣泛創意探索、表現性草圖、插畫與平面視覺方向。</p><p>當眼前目標是比較構想時，可使用此版本，例如封面的不同構圖、活動的視覺處理方式，或同一場景的不同插畫風格。簡潔而具體的起始需求，能讓比較更容易。例如：「一隻紅色摺紙鳥位於淺藍色書桌上方，鮮明的編輯插畫，強烈的午後陰影，簡單幾何形狀，直式構圖且下方保留明確留白。」探索視覺處理時，請維持主體與畫面框架，再進一步發展選定方向。</p><p>Krea 的版本指引建議，需要較穩定的插畫處理時選擇 Medium，照片感或原始紋理的最終方向則選擇 Large。Turbo 是獨立版本；之後改用另一個模型再處理，屬於另一次生成，並不是自動提升品質，也不是完全相同的接續處理。</p><h4>準備提示與視覺輸入</h4><p>模型的生成結構描述要求提供提示、長寬比與解析度。可選的圖生圖輸入，會從來源圖片開始生成，而不是從純雜訊開始。去噪強度範圍為 0 到 1：0 保留輸入，1 完全取代輸入，文件載明預設為 0.99。請仔細準備起始構圖，並描述應修改的內容；高強度允許大幅取代來源。</p><p>風格參考透過圖片提供外觀方向，而不是改變起始圖片的強度。模型專屬結構描述將來源圖片與風格參考的 URI 字串限制為 1,024 個字元。模型專屬請求結構描述最多接受十個參考，各參考的影響程度為 0 到 1，預設為 0.5。請選擇用途清楚的參考，例如配色、繪畫處理或光線方向。另一本 Krea 工作區指南說明，該介面最多可使用四個風格參考；準備兩種介面時，應分別遵循各自的限制。</p><p>情緒板將一致的視覺方向整理為可重複使用的輸入。請先建立情緒板，再於生成時使用既有識別碼。模型結構描述接受一個情緒板，影響程度為 0 到 1，預設為 0.23。經訓練的風格通常是 LoRA，屬於另一種輸入，透過識別碼與 -2 到 2 的強度選擇。來源圖片、風格參考、情緒板及經訓練的風格用途各不相同，請勿將它們視為能彼此替代、用來保留所有細節的方式。</p><h4>調整創意程度與三項視覺滑桿</h4><p>創意程度控制提示擴寫。Raw 會停用擴寫；low、medium 與 high 則改變在需求說明中加入多少詮釋。模型專屬結構描述預設為 low。比較精確需求時，可採用較克制的設定；若目的是發掘更廣泛的構想，則可增加詮釋程度。</p><p>Intensity、Complexity 與 Movement 是彼此獨立的整數滑桿，範圍為 -100 到 100，0 為中性。Intensity 控制從柔和到鮮明的處理；Complexity 控制從簡單構圖到密集細節；Movement 則調整姿勢、視覺能量與暗示的動態。這些滑桿可與參考及情緒板搭配使用，並與創意程度的提示擴寫分開。</p><p>對摺紙鳥需求，可先在其他設定不變時，比較乾淨構圖與細節較多的版本，再探索更強烈的視覺處理或更有活力的姿勢。每次只改一個控制項，並記錄可選種子、提示與參考組合。Movement 影響靜態圖片的特性；它不會生成鳥的動畫、鏡頭運動或影片序列。</p><h4>畫面、批次與完成的圖片</h4><p>模型專屬生成結構描述提供 1K 解析度級別與九種長寬比：1:1、4:3、3:2、16:9、2.35:1、4:5、3:4、2:3 及 9:16。Krea 的 Turbo 工作區指南也說明，一個批次最多可生成四張圖片。該批次設定屬於文件記載的工作區流程，與個別生成請求的結構描述不同。</p><p>生成前，請依預定用途選擇畫面框架。直式封面所需的主體與留白平衡，與橫式編輯圖片不同。請將生成級別與後續增強或完成版面的匯出分開看待。</p><p>Krea 文件記載的生成流程會回傳工作，其初始狀態可能為待處理。請追蹤工作直到完成，並取得生成圖片的位置。比較實際完成的候選圖像的構圖、形狀、紋理、配色與可見文字，再將選定圖片與其輸入及設定一起保存。若產物需要精確文字，請在完成的設計中配置或修正文字。</p><p>Turbo 的快速探索定位，不代表保證特定完成時間、完美文字或精確重建參考圖片。來源圖片強度與參考影響仍需要檢查成果。請運用此版本有效率地確立視覺方向、選定具體候選圖像，再依實際用途完成必要的細節、版面或製作修正。</p>",
  "aboutText": "### 在 Krea 2 系列中快速探索\n\nKrea 2 Medium Turbo 是 Krea 以 Krea 2 Turbo 名稱介紹的生成版本。模型專屬介面將其識別為 Medium Turbo 變體，而 Krea 使用指南說明，它採用經蒸餾的取樣排程，減少生成圖片所需的工作量。Krea 將其定位為此系列中最快的選項，適合廣泛創意探索、表現性草圖、插畫與平面視覺方向。\n\n當眼前目標是比較構想時，可使用此版本，例如封面的不同構圖、活動的視覺處理方式，或同一場景的不同插畫風格。簡潔而具體的起始需求，能讓比較更容易。例如：「一隻紅色摺紙鳥位於淺藍色書桌上方，鮮明的編輯插畫，強烈的午後陰影，簡單幾何形狀，直式構圖且下方保留明確留白。」探索視覺處理時，請維持主體與畫面框架，再進一步發展選定方向。\n\nKrea 的版本指引建議，需要較穩定的插畫處理時選擇 Medium，照片感或原始紋理的最終方向則選擇 Large。Turbo 是獨立版本；之後改用另一個模型再處理，屬於另一次生成，並不是自動提升品質，也不是完全相同的接續處理。\n\n### 準備提示與視覺輸入\n\n模型的生成結構描述要求提供提示、長寬比與解析度。可選的圖生圖輸入，會從來源圖片開始生成，而不是從純雜訊開始。去噪強度範圍為 0 到 1：0 保留輸入，1 完全取代輸入，文件載明預設為 0.99。請仔細準備起始構圖，並描述應修改的內容；高強度允許大幅取代來源。\n\n風格參考透過圖片提供外觀方向，而不是改變起始圖片的強度。模型專屬結構描述將來源圖片與風格參考的 URI 字串限制為 1,024 個字元。模型專屬請求結構描述最多接受十個參考，各參考的影響程度為 0 到 1，預設為 0.5。請選擇用途清楚的參考，例如配色、繪畫處理或光線方向。另一本 Krea 工作區指南說明，該介面最多可使用四個風格參考；準備兩種介面時，應分別遵循各自的限制。\n\n情緒板將一致的視覺方向整理為可重複使用的輸入。請先建立情緒板，再於生成時使用既有識別碼。模型結構描述接受一個情緒板，影響程度為 0 到 1，預設為 0.23。經訓練的風格通常是 LoRA，屬於另一種輸入，透過識別碼與 -2 到 2 的強度選擇。來源圖片、風格參考、情緒板及經訓練的風格用途各不相同，請勿將它們視為能彼此替代、用來保留所有細節的方式。\n\n### 調整創意程度與三項視覺滑桿\n\n創意程度控制提示擴寫。Raw 會停用擴寫；low、medium 與 high 則改變在需求說明中加入多少詮釋。模型專屬結構描述預設為 low。比較精確需求時，可採用較克制的設定；若目的是發掘更廣泛的構想，則可增加詮釋程度。\n\nIntensity、Complexity 與 Movement 是彼此獨立的整數滑桿，範圍為 -100 到 100，0 為中性。Intensity 控制從柔和到鮮明的處理；Complexity 控制從簡單構圖到密集細節；Movement 則調整姿勢、視覺能量與暗示的動態。這些滑桿可與參考及情緒板搭配使用，並與創意程度的提示擴寫分開。\n\n對摺紙鳥需求，可先在其他設定不變時，比較乾淨構圖與細節較多的版本，再探索更強烈的視覺處理或更有活力的姿勢。每次只改一個控制項，並記錄可選種子、提示與參考組合。Movement 影響靜態圖片的特性；它不會生成鳥的動畫、鏡頭運動或影片序列。\n\n### 畫面、批次與完成的圖片\n\n模型專屬生成結構描述提供 1K 解析度級別與九種長寬比：1:1、4:3、3:2、16:9、2.35:1、4:5、3:4、2:3 及 9:16。Krea 的 Turbo 工作區指南也說明，一個批次最多可生成四張圖片。該批次設定屬於文件記載的工作區流程，與個別生成請求的結構描述不同。\n\n生成前，請依預定用途選擇畫面框架。直式封面所需的主體與留白平衡，與橫式編輯圖片不同。請將生成級別與後續增強或完成版面的匯出分開看待。\n\nKrea 文件記載的生成流程會回傳工作，其初始狀態可能為待處理。請追蹤工作直到完成，並取得生成圖片的位置。比較實際完成的候選圖像的構圖、形狀、紋理、配色與可見文字，再將選定圖片與其輸入及設定一起保存。若產物需要精確文字，請在完成的設計中配置或修正文字。\n\nTurbo 的快速探索定位，不代表保證特定完成時間、完美文字或精確重建參考圖片。來源圖片強度與參考影響仍需要檢查成果。請運用此版本有效率地確立視覺方向、選定具體候選圖像，再依實際用途完成必要的細節、版面或製作修正。",
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">•</span><h2 id=\"sheet-title\">Krea: Krea 2 Medium Turbo</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"關閉\">×</button></div><div class=\"idline\"><span>Krea /</span><code>krea/krea-2-medium-turbo</code><button type=\"button\" id=\"copy-id\">複製 ID</button></div><nav class=\"card-jump-nav\" aria-label=\"模型卡片區段\"><button type=\"button\" data-card-jump=\"overview\">入門</button><button type=\"button\" data-card-jump=\"methods\">輸入與方法</button><button type=\"button\" data-card-jump=\"pricing\">方案</button><button type=\"button\" data-card-jump=\"examples\">範例</button><button type=\"button\" data-card-jump=\"results\">結果</button><button type=\"button\" data-card-jump=\"aliases\">別名</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"API 方法\"><button type=\"button\" role=\"tab\" tabindex=\"0\" aria-controls=\"card-method-content\" aria-selected=\"true\" id=\"card-method-tab-0\" data-card-method=\"Ultra|images|/v1/images/generations|krea%2Fkrea-2-medium-turbo\">圖片</button></div><div id=\"card-method-content\" role=\"tabpanel\" aria-labelledby=\"card-method-tab-0\"><section class=\"card-section\" data-card-section=\"overview\"><h3 tabindex=\"-1\">入門</h3><p class=\"mdesc-full\">Krea 2 Medium Turbo 是 Krea 的快速圖片生成版本，適合探索視覺構想及製作富有表現力的草稿。它將蒸餾取樣排程與文字、來源圖片及風格控制結合，可分別調整強度、複雜度與隱含動態。</p><dl class=\"card-io\" data-card-io><div><dt>接受的輸入</dt><dd>文字 · 圖片</dd></div><div><dt>結果</dt><dd>圖片</dd></div></dl><details class=\"card-about\"><summary>關於模型</summary><p class=\"note-s\" data-model-method-boundary>此說明介紹模型的能力。Ailoot 可用的輸入、輸出與選項，依所選方法列於下方。</p><div class=\"mabout\" id=\"m-about\"><h4>在 Krea 2 系列中快速探索</h4><p>Krea 2 Medium Turbo 是 Krea 以 Krea 2 Turbo 名稱介紹的生成版本。模型專屬介面將其識別為 Medium Turbo 變體，而 Krea 使用指南說明，它採用經蒸餾的取樣排程，減少生成圖片所需的工作量。Krea 將其定位為此系列中最快的選項，適合廣泛創意探索、表現性草圖、插畫與平面視覺方向。</p><p>當眼前目標是比較構想時，可使用此版本，例如封面的不同構圖、活動的視覺處理方式，或同一場景的不同插畫風格。簡潔而具體的起始需求，能讓比較更容易。例如：「一隻紅色摺紙鳥位於淺藍色書桌上方，鮮明的編輯插畫，強烈的午後陰影，簡單幾何形狀，直式構圖且下方保留明確留白。」探索視覺處理時，請維持主體與畫面框架，再進一步發展選定方向。</p><p>Krea 的版本指引建議，需要較穩定的插畫處理時選擇 Medium，照片感或原始紋理的最終方向則選擇 Large。Turbo 是獨立版本；之後改用另一個模型再處理，屬於另一次生成，並不是自動提升品質，也不是完全相同的接續處理。</p><h4>準備提示與視覺輸入</h4><p>模型的生成結構描述要求提供提示、長寬比與解析度。可選的圖生圖輸入，會從來源圖片開始生成，而不是從純雜訊開始。去噪強度範圍為 0 到 1：0 保留輸入，1 完全取代輸入，文件載明預設為 0.99。請仔細準備起始構圖，並描述應修改的內容；高強度允許大幅取代來源。</p><p>風格參考透過圖片提供外觀方向，而不是改變起始圖片的強度。模型專屬結構描述將來源圖片與風格參考的 URI 字串限制為 1,024 個字元。模型專屬請求結構描述最多接受十個參考，各參考的影響程度為 0 到 1，預設為 0.5。請選擇用途清楚的參考，例如配色、繪畫處理或光線方向。另一本 Krea 工作區指南說明，該介面最多可使用四個風格參考；準備兩種介面時，應分別遵循各自的限制。</p><p>情緒板將一致的視覺方向整理為可重複使用的輸入。請先建立情緒板，再於生成時使用既有識別碼。模型結構描述接受一個情緒板，影響程度為 0 到 1，預設為 0.23。經訓練的風格通常是 LoRA，屬於另一種輸入，透過識別碼與 -2 到 2 的強度選擇。來源圖片、風格參考、情緒板及經訓練的風格用途各不相同，請勿將它們視為能彼此替代、用來保留所有細節的方式。</p><h4>調整創意程度與三項視覺滑桿</h4><p>創意程度控制提示擴寫。Raw 會停用擴寫；low、medium 與 high 則改變在需求說明中加入多少詮釋。模型專屬結構描述預設為 low。比較精確需求時，可採用較克制的設定；若目的是發掘更廣泛的構想，則可增加詮釋程度。</p><p>Intensity、Complexity 與 Movement 是彼此獨立的整數滑桿，範圍為 -100 到 100，0 為中性。Intensity 控制從柔和到鮮明的處理；Complexity 控制從簡單構圖到密集細節；Movement 則調整姿勢、視覺能量與暗示的動態。這些滑桿可與參考及情緒板搭配使用，並與創意程度的提示擴寫分開。</p><p>對摺紙鳥需求，可先在其他設定不變時，比較乾淨構圖與細節較多的版本，再探索更強烈的視覺處理或更有活力的姿勢。每次只改一個控制項，並記錄可選種子、提示與參考組合。Movement 影響靜態圖片的特性；它不會生成鳥的動畫、鏡頭運動或影片序列。</p><h4>畫面、批次與完成的圖片</h4><p>模型專屬生成結構描述提供 1K 解析度級別與九種長寬比：1:1、4:3、3:2、16:9、2.35:1、4:5、3:4、2:3 及 9:16。Krea 的 Turbo 工作區指南也說明，一個批次最多可生成四張圖片。該批次設定屬於文件記載的工作區流程，與個別生成請求的結構描述不同。</p><p>生成前，請依預定用途選擇畫面框架。直式封面所需的主體與留白平衡，與橫式編輯圖片不同。請將生成級別與後續增強或完成版面的匯出分開看待。</p><p>Krea 文件記載的生成流程會回傳工作，其初始狀態可能為待處理。請追蹤工作直到完成，並取得生成圖片的位置。比較實際完成的候選圖像的構圖、形狀、紋理、配色與可見文字，再將選定圖片與其輸入及設定一起保存。若產物需要精確文字，請在完成的設計中配置或修正文字。</p><p>Turbo 的快速探索定位，不代表保證特定完成時間、完美文字或精確重建參考圖片。來源圖片強度與參考影響仍需要檢查成果。請運用此版本有效率地確立視覺方向、選定具體候選圖像，再依實際用途完成必要的細節、版面或製作修正。</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Ailoot 可用 · 輸入與方法</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · 圖片</b> <code>POST /v1/images/generations</code></summary><dl class=\"method-capabilities\"><div><dt>輸入</dt><dd><code>text</code>, <code>image</code></dd></div><div><dt>輸出</dt><dd><code>image</code></dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>欄位</th><th>類型</th><th>要求</th><th>值與限制</th><th>預設值</th></tr></thead><tbody><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>string</code></td><td data-cell-label=\"要求\"><span class=\"card-cell-label\">要求</span>必填</td><td data-cell-label=\"值與限制\"><span class=\"card-cell-label\">值與限制</span><div>krea/krea-2-medium-turbo</div></td><td data-cell-label=\"預設值\" data-default=\"unspecified\"><span class=\"card-cell-label\">預設值</span>—</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">prompt</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>string</code></td><td data-cell-label=\"要求\"><span class=\"card-cell-label\">要求</span>必填</td><td data-cell-label=\"值與限制\"><span class=\"card-cell-label\">值與限制</span><div>長度下限: 1</div></td><td data-cell-label=\"預設值\" data-default=\"unspecified\"><span class=\"card-cell-label\">預設值</span>—</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">resolution</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>string</code></td><td data-cell-label=\"要求\"><span class=\"card-cell-label\">要求</span>選填</td><td data-cell-label=\"值與限制\"><span class=\"card-cell-label\">值與限制</span><div>1K</div></td><td data-cell-label=\"預設值\" data-default=\"unspecified\"><span class=\"card-cell-label\">預設值</span>—</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">aspect_ratio</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>string</code></td><td data-cell-label=\"要求\"><span class=\"card-cell-label\">要求</span>選填</td><td data-cell-label=\"值與限制\"><span class=\"card-cell-label\">值與限制</span><div>1:1, 4:3, 3:2, 16:9, 4:5, 2:3, 9:16</div></td><td data-cell-label=\"預設值\" data-default=\"unspecified\"><span class=\"card-cell-label\">預設值</span>—</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">input_references</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>array</code></td><td data-cell-label=\"要求\"><span class=\"card-cell-label\">要求</span>選填</td><td data-cell-label=\"值與限制\"><span class=\"card-cell-label\">值與限制</span><div>項目數下限: 0</div><div>項目數上限: 1</div></td><td data-cell-label=\"預設值\" data-default=\"unspecified\"><span class=\"card-cell-label\">預設值</span>—</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">provider</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>object</code></td><td data-cell-label=\"要求\"><span class=\"card-cell-label\">要求</span>選填</td><td data-cell-label=\"值與限制\"><span class=\"card-cell-label\">值與限制</span></td><td data-cell-label=\"預設值\" data-default=\"unspecified\"><span class=\"card-cell-label\">預設值</span>—</td></tr></tbody></table></div><details class=\"note-s\" data-method-contract><summary>方法參數與生命週期</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>參數</th><th>規格</th></tr></thead><tbody><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>content_type</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>application/json</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>required</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>model, prompt</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>material_types</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>text, image</td></tr></tbody></table></div><p>生命週期： <code>synchronous_result_then_owned_library</code></p><p class=\"note-s\"><code>GET /v1/media/tasks/{task_id}</code> · 實際回傳的 task_id 或媒體庫紀錄</p><p class=\"note-s\"><code>GET /v1/media/assets/{asset_id}/content</code></p><p class=\"note-s\"><code>GET /v1/media/assets</code></p><p class=\"note-s\"><code>GET /v1/media/assets/{asset_id}</code></p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">方案</h3><div class=\"card-result-process\" data-billing-basis><h5>最終費用的計算方式</h5><p class=\"note-s\">顯示的費率用於在生成前估算費用。最終費用依原始生成作業記錄的成本計算。實測的輸出時間長度與預估數量並非最終計費數量。</p></div><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>費率資訊不會增加請求選項。支援的參數列於所選方法中。</p><dl data-price-conditions><dt>快速模式</dt><dd>未指定 <span class=\"note-s\">選取快速模式時</span></dd><dt>flex 模式</dt><dd>未指定 <span class=\"note-s\">選取 flex 模式時</span></dd><dt>最高推理強度</dt><dd>未指定 <span class=\"note-s\">最高推理強度採用 default 調整值時</span></dd></dl></div><div data-declared-tariff-pricing><h4>供比較的預估費率</h4><h4>各設定的價格</h4><p class=\"note-s\">請逐一核對各項費用與所列條件。每組互為替代選項的設定只套用一種費率。</p><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>設定</th><th>費率表</th><th>預估數量</th><th>費用</th></tr></thead><tbody><tr><th data-cell-label=\"設定\" scope=\"row\"><span class=\"card-cell-label\">設定</span>基礎 token 費率</th><td data-cell-label=\"費率表\"><span class=\"card-cell-label\">費率表</span>基本費率</td><td data-cell-label=\"預估數量\"><span class=\"card-cell-label\">預估數量</span>—</td><td data-cell-label=\"費用\"><span class=\"card-cell-label\">費用</span><div><span>輸入 · 輸入 Token · 僅供比較的估算</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸出 · 輸出 Token · 僅供比較的估算</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 讀取快取 · 僅供比較的估算</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 寫入快取 · 僅供比較的估算</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 寫入快取，1 小時 · 僅供比較的估算</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div></td></tr><tr><th data-cell-label=\"設定\" scope=\"row\"><span class=\"card-cell-label\">設定</span>預估生成費用</th><td data-cell-label=\"費率表\"><span class=\"card-cell-label\">費率表</span>—</td><td data-cell-label=\"預估數量\"><span class=\"card-cell-label\">預估數量</span>單次生成估算值</td><td data-cell-label=\"費用\"><span class=\"card-cell-label\">費用</span><div><span>輸出 · 預估生成費用 · 僅供比較的估算</span> <b>$0.03</b> <span class=\"price-unit\">生成前估算</span></div><p class=\"note-s\">此估算並非額外費用，也不是本次生成完成後的固定費率。</p></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot 會在請求前預留估算金額。取得結果後，依實測用量結算最終費用。串流結算採用最終用量紀錄。<a href=\"/docs/zh-hant-tw/billing/reserve/\">預留金額與結算的運作方式 →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">請求範例</h3><h4>Ailoot Ultra · 圖片</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"程式碼版本\"><button class=\"cg-tab\" id=\"model-code-1777-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-1777-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"複製程式碼\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-1777-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-1777-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\nexport AILOOT_API_KEY\npython3 - &lt;&lt;&#39;PY_REQUEST&#39;\nimport json,os\nfrom pathlib import Path\np={&#39;model&#39;: &#39;krea/krea-2-medium-turbo&#39;, &#39;prompt&#39;: &#39;a red panda astronaut floating in space, studio lighting&#39;}\n\nPath(&quot;request.json&quot;).write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -H &#39;Content-Type: application/json&#39; \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - &lt;&lt;&#39;PY_RESULT&#39;\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n    if not items: raise SystemExit(&quot;No completed images; retain the full response&quot;)\n    for index, item in enumerate(items):\n        encoded=item.get(&quot;b64_json&quot;)\n        uri=item.get(&quot;url&quot;, &quot;&quot;)\n        if not encoded and uri.startswith(&quot;data:image/&quot;):\n            header, separator, encoded=uri.partition(&quot;,&quot;)\n            if not separator or &quot;;base64&quot; not in header: raise SystemExit(&quot;Unsupported image data URI&quot;)\n        if encoded:\n            raw=base64.b64decode(encoded,validate=True)\n        elif uri:\n            uri=urljoin(&quot;https://api.ailoot.ai&quot;,uri)\n            parsed=urlsplit(uri)\n            if parsed.scheme!=&quot;https&quot; or not parsed.netloc or parsed.username or parsed.password:\n                raise SystemExit(&quot;Invalid returned image URL&quot;)\n            owned=parsed.netloc==&quot;api.ailoot.ai&quot; and parsed.path.startswith(&quot;/v1/media/assets/&quot;) and parsed.path.endswith(&quot;/content&quot;)\n            args=[&quot;curl&quot;,&quot;--fail-with-body&quot;,&quot;--silent&quot;,&quot;--show-error&quot;,uri]\n            if owned: args += [&quot;-H&quot;,&quot;Authorization: Bearer &quot;+os.environ[&quot;AILOOT_API_KEY&quot;]]\n            temporary=Path(f&quot;image-{index}.bin&quot;)\n            subprocess.run(args+[&quot;-o&quot;,str(temporary)],check=True)\n            raw=temporary.read_bytes()\n            temporary.unlink()\n        else: raise SystemExit(&quot;Image has neither bytes nor URL&quot;)\n        if not raw: raise SystemExit(&quot;Empty image result&quot;)\n        ext=&quot;png&quot; if raw.startswith(b&quot;\\x89PNG&quot;) else &quot;jpg&quot; if raw.startswith(b&quot;\\xff\\xd8&quot;) else &quot;webp&quot; if raw[:4]==b&quot;RIFF&quot; and raw[8:12]==b&quot;WEBP&quot; else &quot;svg&quot; if raw.lstrip().startswith((b&quot;&lt;svg&quot;,b&quot;&lt;?xml&quot;)) else &quot;bin&quot;\n        Path(f&quot;image-{index}.{ext}&quot;).write_bytes(raw)\n    print(&quot;Every returned image saved; complete response metadata retained&quot;)\nsave_images(json.loads(Path(&quot;result.json&quot;).read_text())[&quot;data&quot;])\nPY_RESULT\n</code></pre></div></div></div></section><section class=\"card-section\" data-card-section=\"results\"><h3 tabindex=\"-1\">接收並儲存結果</h3><h4>Ailoot Ultra · 圖片</h4><p class=\"note-s\">下載每張傳回的圖片，或儲存其 Base64 內容</p><ul class=\"card-result-paths\"><li><code>GET /v1/media/tasks/{task_id}</code></li><li><code>GET /v1/media/assets/{asset_id}/content</code></li><li><code>GET /v1/media/assets</code></li><li><code>GET /v1/media/assets/{asset_id}</code></li></ul><details class=\"card-about\"><summary>其他內容讀取方式</summary><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"程式碼版本\"><button class=\"cg-tab\" id=\"model-code-1778-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-1778-panel-0\" aria-selected=\"true\" tabindex=\"0\">讀取現有且屬於自己的素材</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"複製程式碼\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-1778-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-1778-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\n</code></pre></div></div></div></details><div class=\"card-result-process\" data-all-results><h5>保留所有已完成的結果</h5><p class=\"note-s\">請儲存每張已完成的圖片；從每個傳回的 URL 取得圖片，或解碼其 Base64 內容。</p><p class=\"note-s\">保留完整回應與標頭、所有實際輸出、原始回傳的識別碼，以及所有用量欄位。恢復原始作業時，請勿再次提交建立請求。</p></div><div class=\"card-result-process\" data-unknown-recovery><h5>需要檢查原始回應時</h5><p class=\"note-s\">保留回傳的 X-Client-Request-ID，以供核對。僅讀取實際回傳的 task_id/asset_id 值或自己擁有的媒體庫；請勿以作業 ID 組成任務 URL，也請勿重新提交建立請求。</p></div><details class=\"card-about\" data-output-fields><summary>回應欄位</summary><div class=\"tw\" data-card-table=\"output\"><table><thead><tr><th>欄位</th><th>類型</th></tr></thead><tbody><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">created</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span></td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">data[].url</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span></td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">data[].b64_json</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span></td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">usage</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span></td></tr></tbody></table></div></details></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">別名</h3><h4>模型別名</h4><p class=\"note-s\"><span data-model-alias-route=\"Ultra\"><b>Ailoot Ultra</b> <a href=\"#m=krea%2Fkrea-2-medium-turbo&amp;route=Ultra&amp;caller=krea%2Fkrea-2-medium-turbo&amp;fmt=images\"><code>krea/krea-2-medium-turbo</code></a></span></p><h4>方法路徑別名</h4><p class=\"note-s\"><code>/v1/images</code></p><h4>相關呼叫用 ID</h4><p class=\"note-s\"><a href=\"#m=krea%2Fkrea-2-medium-turbo&amp;route=Ultra&amp;caller=krea%2Fkrea-2-medium-turbo&amp;fmt=images\"><code>krea/krea-2-medium-turbo</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "krea/krea-2-medium-turbo",
        "fmt": "images",
        "http": "POST",
        "path": "/v1/images/generations",
        "request_model_id": "krea/krea-2-medium-turbo",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|images|/v1/images/generations|krea%2Fkrea-2-medium-turbo",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "billing_basis": {
          "basis": "original_invoice_usd",
          "description": "顯示的費率用於在生成前估算費用。最終費用依原始生成作業記錄的成本計算。實測的輸出時間長度與預估數量並非最終計費數量。",
          "forecast_quantity_is_estimate": true,
          "physical_output_is_billable_quantity": false,
          "version": "original_invoice_usd_v1"
        },
        "cache_read": null,
        "cache_write": null,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "lifecycle": {
              "assets": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets"
                },
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}"
                }
              ],
              "content": [
                {
                  "http": "GET",
                  "path": "/v1/media/assets/{asset_id}/content",
                  "url_source": "exact returned signed URL; never construct token"
                }
              ],
              "mode": "synchronous_result_then_owned_library",
              "operation_id_is_not_task_id": true,
              "status": [
                {
                  "http": "GET",
                  "id_source": "actual returned task_id or media library record",
                  "path": "/v1/media/tasks/{task_id}"
                }
              ],
              "unknown": "保留回傳的 X-Client-Request-ID，以供核對。僅讀取實際回傳的 task_id/asset_id 值或自己擁有的媒體庫；請勿以作業 ID 組成任務 URL，也請勿重新提交建立請求。"
            },
            "outputs": {
              "all_results": "保留完整回應與標頭、所有實際輸出、原始回傳的識別碼，以及所有用量欄位。恢復原始作業時，請勿再次提交建立請求。",
              "family": "image",
              "fields": [
                {
                  "description": null,
                  "name": "created",
                  "type": null
                },
                {
                  "description": null,
                  "name": "data[].url",
                  "type": null
                },
                {
                  "description": null,
                  "name": "data[].b64_json",
                  "type": null
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": null
                }
              ]
            },
            "parameters": [
              {
                "enum": [
                  "krea/krea-2-medium-turbo"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "min_length": 1,
                "name": "prompt",
                "required": true,
                "type": "string"
              },
              {
                "enum": [
                  "1K"
                ],
                "enum_known": true,
                "name": "resolution",
                "required": false,
                "type": "string"
              },
              {
                "enum": [
                  "1:1",
                  "4:3",
                  "3:2",
                  "16:9",
                  "4:5",
                  "2:3",
                  "9:16"
                ],
                "enum_known": true,
                "name": "aspect_ratio",
                "required": false,
                "type": "string"
              },
              {
                "items": {
                  "properties": {
                    "image_url": {
                      "properties": {
                        "url": {
                          "type": "string"
                        }
                      },
                      "required": [
                        "url"
                      ],
                      "type": "object"
                    },
                    "type": {
                      "const": "image_url"
                    }
                  },
                  "required": [
                    "type",
                    "image_url"
                  ],
                  "type": "object"
                },
                "maximum_items": 1,
                "minimum_items": 0,
                "name": "input_references",
                "required": false,
                "type": "array"
              },
              {
                "name": "provider",
                "required": false,
                "type": "object"
              }
            ],
            "request_schema": {
              "properties": {
                "aspect_ratio": {
                  "enum": [
                    "1:1",
                    "4:3",
                    "3:2",
                    "16:9",
                    "4:5",
                    "2:3",
                    "9:16"
                  ],
                  "type": "string"
                },
                "input_references": {
                  "items": {
                    "properties": {
                      "image_url": {
                        "properties": {
                          "url": {
                            "type": "string"
                          }
                        },
                        "required": [
                          "url"
                        ],
                        "type": "object"
                      },
                      "type": {
                        "const": "image_url"
                      }
                    },
                    "required": [
                      "type",
                      "image_url"
                    ],
                    "type": "object"
                  },
                  "maxItems": 1,
                  "minItems": 0,
                  "type": "array"
                },
                "model": {
                  "enum": [
                    "krea/krea-2-medium-turbo"
                  ],
                  "type": "string"
                },
                "prompt": {
                  "minLength": 1,
                  "type": "string"
                },
                "provider": {
                  "description": "Exact image provider preferences from the documented image request schema.",
                  "type": "object"
                },
                "resolution": {
                  "enum": [
                    "1K"
                  ],
                  "type": "string"
                }
              },
              "required": [
                "model",
                "prompt"
              ],
              "type": "object"
            },
            "schema_template": {
              "actual_file_preparation_required": false,
              "body": {
                "model": "krea/krea-2-medium-turbo",
                "prompt": "a red panda astronaut floating in space, studio lighting"
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "content_type": "application/json",
            "material_types": [
              "text",
              "image"
            ],
            "required": [
              "model",
              "prompt"
            ]
          },
          "lifecycle": {
            "assets": [
              {
                "http": "GET",
                "path": "/v1/media/assets"
              },
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}"
              }
            ],
            "content": [
              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}/content",
                "url_source": "exact returned signed URL; never construct token"
              }
            ],
            "mode": "synchronous_result_then_owned_library",
            "operation_id_is_not_task_id": true,
            "status": [
              {
                "http": "GET",
                "id_source": "實際回傳的 task_id 或媒體庫紀錄",
                "path": "/v1/media/tasks/{task_id}"
              }
            ],
            "unknown": "Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation."
          },
          "method": {
            "http": "POST",
            "path": "/v1/images/generations"
          },
          "output": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "family": "image",
            "fields": [
              {
                "description": null,
                "name": "created",
                "type": null
              },
              {
                "description": null,
                "name": "data[].url",
                "type": null
              },
              {
                "description": null,
                "name": "data[].b64_json",
                "type": null
              },
              {
                "description": null,
                "name": "usage",
                "type": null
              }
            ]
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "basis": "此估算並非額外費用，也不是本次生成完成後的固定費率。",
            "dimensions": {
              "forecast_quantity": "one generation estimate"
            },
            "label": "預估生成費用",
            "units": [
              {
                "amount": "0.03",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "forecast_usd",
                "label": "Estimated generation cost",
                "native_amount_usd_per_unit": "0.03",
                "native_quantity": 1,
                "public_unit_label": "estimate before generation",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "request_estimate"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np={'model': 'krea/krea-2-medium-turbo', 'prompt': 'a red panda astronaut floating in space, studio lighting'}\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n    if not items: raise SystemExit(\"No completed images; retain the full response\")\n    for index, item in enumerate(items):\n        encoded=item.get(\"b64_json\")\n        uri=item.get(\"url\", \"\")\n        if not encoded and uri.startswith(\"data:image/\"):\n            header, separator, encoded=uri.partition(\",\")\n            if not separator or \";base64\" not in header: raise SystemExit(\"Unsupported image data URI\")\n        if encoded:\n            raw=base64.b64decode(encoded,validate=True)\n        elif uri:\n            uri=urljoin(\"https://api.ailoot.ai\",uri)\n            parsed=urlsplit(uri)\n            if parsed.scheme!=\"https\" or not parsed.netloc or parsed.username or parsed.password:\n                raise SystemExit(\"Invalid returned image URL\")\n            owned=parsed.netloc==\"api.ailoot.ai\" and parsed.path.startswith(\"/v1/media/assets/\") and parsed.path.endswith(\"/content\")\n            args=[\"curl\",\"--fail-with-body\",\"--silent\",\"--show-error\",uri]\n            if owned: args += [\"-H\",\"Authorization: Bearer \"+os.environ[\"AILOOT_API_KEY\"]]\n            temporary=Path(f\"image-{index}.bin\")\n            subprocess.run(args+[\"-o\",str(temporary)],check=True)\n            raw=temporary.read_bytes()\n            temporary.unlink()\n        else: raise SystemExit(\"Image has neither bytes nor URL\")\n        if not raw: raise SystemExit(\"Empty image result\")\n        ext=\"png\" if raw.startswith(b\"\\x89PNG\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else \"svg\" if raw.lstrip().startswith((b\"<svg\",b\"<?xml\")) else \"bin\"\n        Path(f\"image-{index}.{ext}\").write_bytes(raw)\n    print(\"Every returned image saved; complete response metadata retained\")\nsave_images(json.loads(Path(\"result.json\").read_text())[\"data\"])\nPY_RESULT\n",
            "label": "curl · exact creation/save all outputs",
            "language": "bash"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\n",
            "label": "Read existing owned assets",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "images",
        "hints": [
          "Use the exact caller model ID and documented input representation.",
          "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again."
        ],
        "http": "POST",
        "in": null,
        "input": [
          "text",
          "image"
        ],
        "label": "圖片",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [
          "/v1/images"
        ],
        "native_endpoint": "images",
        "out": null,
        "output": [
          "image"
        ],
        "path": "/v1/images/generations",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "original_invoice_usd",
          "image_input_price": null,
          "image_output_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
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  "page": {
    "canonical": "https://ailoot.ai/models/zh-hant-tw/krea-krea-2-medium-turbo/",
    "description": "Krea 2 Medium Turbo 是 Krea 的快速圖片生成版本，適合探索視覺構想及製作富有表現力的草稿。它將蒸餾取樣排程與文字、來源圖片及風格控制結合，可分別調整強度、複雜度與隱含動態。",
    "locale": "zh-hant-tw",
    "md_url": "https://ailoot.ai/models/zh-hant-tw/krea-krea-2-medium-turbo/index.md",
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    "about": "### 在 Krea 2 系列中快速探索\n\nKrea 2 Medium Turbo 是 Krea 以 Krea 2 Turbo 名稱介紹的生成版本。模型專屬介面將其識別為 Medium Turbo 變體，而 Krea 使用指南說明，它採用經蒸餾的取樣排程，減少生成圖片所需的工作量。Krea 將其定位為此系列中最快的選項，適合廣泛創意探索、表現性草圖、插畫與平面視覺方向。\n\n當眼前目標是比較構想時，可使用此版本，例如封面的不同構圖、活動的視覺處理方式，或同一場景的不同插畫風格。簡潔而具體的起始需求，能讓比較更容易。例如：「一隻紅色摺紙鳥位於淺藍色書桌上方，鮮明的編輯插畫，強烈的午後陰影，簡單幾何形狀，直式構圖且下方保留明確留白。」探索視覺處理時，請維持主體與畫面框架，再進一步發展選定方向。\n\nKrea 的版本指引建議，需要較穩定的插畫處理時選擇 Medium，照片感或原始紋理的最終方向則選擇 Large。Turbo 是獨立版本；之後改用另一個模型再處理，屬於另一次生成，並不是自動提升品質，也不是完全相同的接續處理。\n\n### 準備提示與視覺輸入\n\n模型的生成結構描述要求提供提示、長寬比與解析度。可選的圖生圖輸入，會從來源圖片開始生成，而不是從純雜訊開始。去噪強度範圍為 0 到 1：0 保留輸入，1 完全取代輸入，文件載明預設為 0.99。請仔細準備起始構圖，並描述應修改的內容；高強度允許大幅取代來源。\n\n風格參考透過圖片提供外觀方向，而不是改變起始圖片的強度。模型專屬結構描述將來源圖片與風格參考的 URI 字串限制為 1,024 個字元。模型專屬請求結構描述最多接受十個參考，各參考的影響程度為 0 到 1，預設為 0.5。請選擇用途清楚的參考，例如配色、繪畫處理或光線方向。另一本 Krea 工作區指南說明，該介面最多可使用四個風格參考；準備兩種介面時，應分別遵循各自的限制。\n\n情緒板將一致的視覺方向整理為可重複使用的輸入。請先建立情緒板，再於生成時使用既有識別碼。模型結構描述接受一個情緒板，影響程度為 0 到 1，預設為 0.23。經訓練的風格通常是 LoRA，屬於另一種輸入，透過識別碼與 -2 到 2 的強度選擇。來源圖片、風格參考、情緒板及經訓練的風格用途各不相同，請勿將它們視為能彼此替代、用來保留所有細節的方式。\n\n### 調整創意程度與三項視覺滑桿\n\n創意程度控制提示擴寫。Raw 會停用擴寫；low、medium 與 high 則改變在需求說明中加入多少詮釋。模型專屬結構描述預設為 low。比較精確需求時，可採用較克制的設定；若目的是發掘更廣泛的構想，則可增加詮釋程度。\n\nIntensity、Complexity 與 Movement 是彼此獨立的整數滑桿，範圍為 -100 到 100，0 為中性。Intensity 控制從柔和到鮮明的處理；Complexity 控制從簡單構圖到密集細節；Movement 則調整姿勢、視覺能量與暗示的動態。這些滑桿可與參考及情緒板搭配使用，並與創意程度的提示擴寫分開。\n\n對摺紙鳥需求，可先在其他設定不變時，比較乾淨構圖與細節較多的版本，再探索更強烈的視覺處理或更有活力的姿勢。每次只改一個控制項，並記錄可選種子、提示與參考組合。Movement 影響靜態圖片的特性；它不會生成鳥的動畫、鏡頭運動或影片序列。\n\n### 畫面、批次與完成的圖片\n\n模型專屬生成結構描述提供 1K 解析度級別與九種長寬比：1:1、4:3、3:2、16:9、2.35:1、4:5、3:4、2:3 及 9:16。Krea 的 Turbo 工作區指南也說明，一個批次最多可生成四張圖片。該批次設定屬於文件記載的工作區流程，與個別生成請求的結構描述不同。\n\n生成前，請依預定用途選擇畫面框架。直式封面所需的主體與留白平衡，與橫式編輯圖片不同。請將生成級別與後續增強或完成版面的匯出分開看待。\n\nKrea 文件記載的生成流程會回傳工作，其初始狀態可能為待處理。請追蹤工作直到完成，並取得生成圖片的位置。比較實際完成的候選圖像的構圖、形狀、紋理、配色與可見文字，再將選定圖片與其輸入及設定一起保存。若產物需要精確文字，請在完成的設計中配置或修正文字。\n\nTurbo 的快速探索定位，不代表保證特定完成時間、完美文字或精確重建參考圖片。來源圖片強度與參考影響仍需要檢查成果。請運用此版本有效率地確立視覺方向、選定具體候選圖像，再依實際用途完成必要的細節、版面或製作修正。",
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        "summary": "完整的設定價格資訊請見詳細資料。"
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        "billing_basis": {
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              "unknown": "保留回傳的 X-Client-Request-ID，以供核對。僅讀取實際回傳的 task_id/asset_id 值或自己擁有的媒體庫；請勿以作業 ID 組成任務 URL，也請勿重新提交建立請求。"
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              {
                "http": "GET",
                "path": "/v1/media/assets/{asset_id}/content",
                "url_source": "exact returned signed URL; never construct token"
              }
            ],
            "mode": "synchronous_result_then_owned_library",
            "operation_id_is_not_task_id": true,
            "status": [
              {
                "http": "GET",
                "id_source": "實際回傳的 task_id 或媒體庫紀錄",
                "path": "/v1/media/tasks/{task_id}"
              }
            ],
            "unknown": "Keep the returned X-Client-Request-ID for reconciliation. Read only actual returned task_id/asset_id values or the owned media library; never build a task URL from the operation ID and never resubmit creation."
          },
          "method": {
            "http": "POST",
            "path": "/v1/images/generations"
          },
          "output": {
            "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.",
            "family": "image",
            "fields": [
              {
                "description": null,
                "name": "created",
                "type": null
              },
              {
                "description": null,
                "name": "data[].url",
                "type": null
              },
              {
                "description": null,
                "name": "data[].b64_json",
                "type": null
              },
              {
                "description": null,
                "name": "usage",
                "type": null
              }
            ]
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "basis": "此估算並非額外費用，也不是本次生成完成後的固定費率。",
            "dimensions": {
              "forecast_quantity": "one generation estimate"
            },
            "label": "預估生成費用",
            "units": [
              {
                "amount": "0.03",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "forecast_usd",
                "label": "Estimated generation cost",
                "native_amount_usd_per_unit": "0.03",
                "native_quantity": 1,
                "public_unit_label": "estimate before generation",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "request_estimate"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np={'model': 'krea/krea-2-medium-turbo', 'prompt': 'a red panda astronaut floating in space, studio lighting'}\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/images/generations \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport base64, json, os, subprocess\nfrom pathlib import Path\nfrom urllib.parse import urlsplit, urljoin\n\ndef save_images(items):\n    if not items: raise SystemExit(\"No completed images; retain the full response\")\n    for index, item in enumerate(items):\n        encoded=item.get(\"b64_json\")\n        uri=item.get(\"url\", \"\")\n        if not encoded and uri.startswith(\"data:image/\"):\n            header, separator, encoded=uri.partition(\",\")\n            if not separator or \";base64\" not in header: raise SystemExit(\"Unsupported image data URI\")\n        if encoded:\n            raw=base64.b64decode(encoded,validate=True)\n        elif uri:\n            uri=urljoin(\"https://api.ailoot.ai\",uri)\n            parsed=urlsplit(uri)\n            if parsed.scheme!=\"https\" or not parsed.netloc or parsed.username or parsed.password:\n                raise SystemExit(\"Invalid returned image URL\")\n            owned=parsed.netloc==\"api.ailoot.ai\" and parsed.path.startswith(\"/v1/media/assets/\") and parsed.path.endswith(\"/content\")\n            args=[\"curl\",\"--fail-with-body\",\"--silent\",\"--show-error\",uri]\n            if owned: args += [\"-H\",\"Authorization: Bearer \"+os.environ[\"AILOOT_API_KEY\"]]\n            temporary=Path(f\"image-{index}.bin\")\n            subprocess.run(args+[\"-o\",str(temporary)],check=True)\n            raw=temporary.read_bytes()\n            temporary.unlink()\n        else: raise SystemExit(\"Image has neither bytes nor URL\")\n        if not raw: raise SystemExit(\"Empty image result\")\n        ext=\"png\" if raw.startswith(b\"\\x89PNG\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4]==b\"RIFF\" and raw[8:12]==b\"WEBP\" else \"svg\" if raw.lstrip().startswith((b\"<svg\",b\"<?xml\")) else \"bin\"\n        Path(f\"image-{index}.{ext}\").write_bytes(raw)\n    print(\"Every returned image saved; complete response metadata retained\")\nsave_images(json.loads(Path(\"result.json\").read_text())[\"data\"])\nPY_RESULT\n",
            "label": "curl · exact creation/save all outputs",
            "language": "bash"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/media/assets \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -o owned-assets.json\n# Preserve every returned asset and follow its exact signed content URL. Do not construct a signed token.\n",
            "label": "Read existing owned assets",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "images",
        "hints": [
          "Use the exact caller model ID and documented input representation.",
          "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again."
        ],
        "http": "POST",
        "in": null,
        "input": [
          "text",
          "image"
        ],
        "label": "圖片",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [
          "/v1/images"
        ],
        "native_endpoint": "images",
        "out": null,
        "output": [
          "image"
        ],
        "path": "/v1/images/generations",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "original_invoice_usd",
          "image_input_price": null,
          "image_output_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": false,
                "estimate_only": true,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "basis": "This estimate is not an additional charge or a fixed rate for the completed generation.",
            "dimensions": {
              "forecast_quantity": "one generation estimate"
            },
            "label": "Estimated generation cost",
            "units": [
              {
                "amount": "0.03",
                "amount_unit": "usd_per_exact_native_unit",
                "billing_input": false,
                "estimate_only": true,
                "key": "forecast_usd",
                "label": "Estimated generation cost",
                "native_amount_usd_per_unit": "0.03",
                "native_quantity": 1,
                "public_unit_label": "estimate before generation",
                "quantity": 1,
                "quantity_is_estimate": true,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "request_estimate"
              }
            ]
          }
        ],
        "request_model_id": "krea/krea-2-medium-turbo",
        "route_label": "Ultra",
        "status_reads": [
          "GET /v1/media/tasks/{task_id}"
        ],
        "tiers": [],
        "units": [
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": false,
            "estimate_only": true,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          },
          {
            "amount": "0.03",
            "amount_unit": "usd_per_exact_native_unit",
            "billing_input": false,
            "estimate_only": true,
            "key": "forecast_usd",
            "label": "Estimated generation cost",
            "native_amount_usd_per_unit": "0.03",
            "native_quantity": 1,
            "public_unit_label": "estimate before generation",
            "quantity": 1,
            "quantity_is_estimate": true,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "request_estimate"
          }
        ]
      }
    ],
    "model_aliases": [
      {
        "canonical_model_id": "krea/krea-2-medium-turbo",
        "request_model_id": "krea/krea-2-medium-turbo",
        "route_label": "Ultra"
      }
    ],
    "name": "Krea: Krea 2 Medium Turbo",
    "price": {
      "estimate_only": true,
      "in": null,
      "in_label": null,
      "out": 0.03,
      "out_label": "estimate before generation",
      "scope_label": "Estimated generation cost",
      "sort_in": null,
      "sort_out": 0.03,
      "varies": false
    },
    "short": "Krea 2 Medium Turbo 是 Krea 的快速圖片生成版本，適合探索視覺構想及製作富有表現力的草稿。它將蒸餾取樣排程與文字、來源圖片及風格控制結合，可分別調整強度、複雜度與隱含動態。"
  },
  "renderer_schema": {
    "method_order": "Original DTO methods order; every exact route/format/path/caller survives.",
    "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers."
  },
  "representation": "exact-public-dto-and-native-renderer-html",
  "representationNotes": {
    "current_reference": {
      "about_json_pointer": "/aboutHtml",
      "methods": [
        {
          "contract_json_pointer": "/methods/0/rawMethod/contract",
          "html_json_pointer": "/methods/0/html",
          "method_ordinal": 0
        }
      ],
      "role": "current-semantic-reference"
    },
    "raw_input": {
      "examples_role": "historical-input-not-current-ready-examples",
      "json_pointers": [
        "/rawModel",
        "/methods/0/rawMethod"
      ],
      "role": "historical-owner-input"
    },
    "schema": "ailoot-native-model-representations-v1"
  },
  "schema": "ailoot-static-model-facts-v1",
  "schema_version": 1,
  "shortText": "Krea 2 Medium Turbo 是 Krea 的快速圖片生成版本，適合探索視覺構想及製作富有表現力的草稿。它將蒸餾取樣排程與文字、來源圖片及風格控制結合，可分別調整強度、複雜度與隱含動態。",
  "source": {
    "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1",
    "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036",
    "raw_model_json_sha256": "d352eb0c2c2822ec466dedbaee9aee6614dc6a2a44275bca3351bb2dbc78cad1",
    "renderer_sha256": "13a3fc1b22d07359278e2249d630bfc9bb9e6416c71ba53def933fb5a903660b"
  },
  "sourceRevision": "c7e093c562853e35d31ade585d5dab5a3c59e8d7230e47f970649f2f0197ba27"
}
