{
  "aboutHtml": "<p>BGE Reranker v2 M3 是以 BGE-M3 為基礎的多語言相關性模型。它同時接收查詢與候選段落，傳回表示兩者關聯程度的分數。BAAI 將此版本定位為高效率的多語言重排序模型，包括適合中文與英文檢索，供搜尋應用程式進一步調整既有候選清單。</p><h4>根據查詢與段落配對評估相關性</h4><p>交叉編碼器會共同處理兩段文字，讓內容在產生相關性分數前互相作用。這與嵌入模型不同；嵌入模型分別編碼文字，供可重複使用的向量比較。重排序模型輸出的是特定配對的純量分數，而非文件向量或文字回答。</p><p>在初步搜尋選出可能相關的段落後使用此模型。將問題與每個候選段落配對，再依所得分數排序候選。這讓更細緻的比較集中於可管理的短名單，避免要求交叉編碼器檢視大型集合中的每個段落。</p><h4>v2 M3 版本</h4><p>製造商將 BGE-M3 列為基礎模型，並將多語言支援列為主要特色。在 v2 重排序系列中，M3 是高效率的多語言選項；以 Gemma 為基礎的版本與層選擇版本是不同模型，實作選擇也不同。此處的 M3 名稱不代表重排序模型會傳回原始嵌入模型的稠密、稀疏及多向量嵌入。</p><p>選擇應用程式需要的結果時，這項區別很重要。要表示與搜尋文件集合，應選擇嵌入模型。已有候選文字、需要判定哪個段落最切合目前查詢時，則選擇此重排序模型。</p><h4>準備能有效排序的候選資料</h4><p>提供實際問題，以及解讀所需的完整候選文字。若標題或附近定義會影響段落意義，應一併保留。公布的 Transformers 範例會將查詢與段落一起轉為 token，啟用截斷並設為 max_length=512。這是範例設定，而非整個模型的通用限制。將問題與必要佐證保留在選定的配對額度內，並檢查截斷移除了哪些內容。即使結果提到與查詢相同的產品，若談的是錯誤操作或條件，仍可能不相關；評估檢索品質時，準備能區分這些情況的範例。</p><p>文件助理應保留候選識別碼與對應文字，為問題與段落配對評分，再將選定的原始段落交給回答步驟。這樣回答模型會收到佐證，而不是缺少來源的相關性分數。這是檢索工作流程的示例；重排序模型本身不會搜尋外部集合，也不會撰寫回答。</p><h4>讀取與正規化分數</h4><p>製造商傳回原始相關性分數，數值越高表示越接近查詢。文件記載的選用正規化會套用 sigmoid 函數，將分數置於 0 至 1 之間。正規化分數的範圍便於使用，但僅靠這項轉換，無法確立候選正確性的校準機率。</p><p>以工作負載中具代表性的查詢與段落配對選擇排序或篩選門檻。納入具有相同關鍵字但回答不同問題的段落，以及措辭不同但相關的段落。這樣選定門檻才對正在搜尋的集合有意義。</p><p>Ailoot API 專案應定義最終上下文應包含哪些內容，以及能有效檢視多少候選。實用結果是為應用程式下一步提供排序更佳的佐證集合。將此版本的相關性輸出，與文件嵌入、生成文章，以及其他重排序模型記載的層選擇控制分開。</p>",
  "aboutText": "BGE Reranker v2 M3 是以 BGE-M3 為基礎的多語言相關性模型。它同時接收查詢與候選段落，傳回表示兩者關聯程度的分數。BAAI 將此版本定位為高效率的多語言重排序模型，包括適合中文與英文檢索，供搜尋應用程式進一步調整既有候選清單。\n\n### 根據查詢與段落配對評估相關性\n\n交叉編碼器會共同處理兩段文字，讓內容在產生相關性分數前互相作用。這與嵌入模型不同；嵌入模型分別編碼文字，供可重複使用的向量比較。重排序模型輸出的是特定配對的純量分數，而非文件向量或文字回答。\n\n在初步搜尋選出可能相關的段落後使用此模型。將問題與每個候選段落配對，再依所得分數排序候選。這讓更細緻的比較集中於可管理的短名單，避免要求交叉編碼器檢視大型集合中的每個段落。\n\n### v2 M3 版本\n\n製造商將 BGE-M3 列為基礎模型，並將多語言支援列為主要特色。在 v2 重排序系列中，M3 是高效率的多語言選項；以 Gemma 為基礎的版本與層選擇版本是不同模型，實作選擇也不同。此處的 M3 名稱不代表重排序模型會傳回原始嵌入模型的稠密、稀疏及多向量嵌入。\n\n選擇應用程式需要的結果時，這項區別很重要。要表示與搜尋文件集合，應選擇嵌入模型。已有候選文字、需要判定哪個段落最切合目前查詢時，則選擇此重排序模型。\n\n### 準備能有效排序的候選資料\n\n提供實際問題，以及解讀所需的完整候選文字。若標題或附近定義會影響段落意義，應一併保留。公布的 Transformers 範例會將查詢與段落一起轉為 token，啟用截斷並設為 max_length=512。這是範例設定，而非整個模型的通用限制。將問題與必要佐證保留在選定的配對額度內，並檢查截斷移除了哪些內容。即使結果提到與查詢相同的產品，若談的是錯誤操作或條件，仍可能不相關；評估檢索品質時，準備能區分這些情況的範例。\n\n文件助理應保留候選識別碼與對應文字，為問題與段落配對評分，再將選定的原始段落交給回答步驟。這樣回答模型會收到佐證，而不是缺少來源的相關性分數。這是檢索工作流程的示例；重排序模型本身不會搜尋外部集合，也不會撰寫回答。\n\n### 讀取與正規化分數\n\n製造商傳回原始相關性分數，數值越高表示越接近查詢。文件記載的選用正規化會套用 sigmoid 函數，將分數置於 0 至 1 之間。正規化分數的範圍便於使用，但僅靠這項轉換，無法確立候選正確性的校準機率。\n\n以工作負載中具代表性的查詢與段落配對選擇排序或篩選門檻。納入具有相同關鍵字但回答不同問題的段落，以及措辭不同但相關的段落。這樣選定門檻才對正在搜尋的集合有意義。\n\nAiloot API 專案應定義最終上下文應包含哪些內容，以及能有效檢視多少候選。實用結果是為應用程式下一步提供排序更佳的佐證集合。將此版本的相關性輸出，與文件嵌入、生成文章，以及其他重排序模型記載的層選擇控制分開。",
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    {
      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">•</span><h2 id=\"sheet-title\">bge-reranker-v2-m3</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"關閉\">×</button></div><div class=\"idline\"><span>BAAI /</span><code>bge-reranker-v2-m3</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|rerank|/v1/rerank|bge-reranker-v2-m3\">重新排序</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\">BAAI 的多語言交叉編碼器，用來依查詢為候選段落排序。它一起讀取每組查詢與段落，回傳相關性分數，精煉搜尋候選清單，不會生成答案或建立文件嵌入。</p><dl class=\"card-io\" data-card-io><div><dt>接受的輸入</dt><dd>文字</dd></div><div><dt>結果</dt><dd>已排序結果</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\"><p>BGE Reranker v2 M3 是以 BGE-M3 為基礎的多語言相關性模型。它同時接收查詢與候選段落，傳回表示兩者關聯程度的分數。BAAI 將此版本定位為高效率的多語言重排序模型，包括適合中文與英文檢索，供搜尋應用程式進一步調整既有候選清單。</p><h4>根據查詢與段落配對評估相關性</h4><p>交叉編碼器會共同處理兩段文字，讓內容在產生相關性分數前互相作用。這與嵌入模型不同；嵌入模型分別編碼文字，供可重複使用的向量比較。重排序模型輸出的是特定配對的純量分數，而非文件向量或文字回答。</p><p>在初步搜尋選出可能相關的段落後使用此模型。將問題與每個候選段落配對，再依所得分數排序候選。這讓更細緻的比較集中於可管理的短名單，避免要求交叉編碼器檢視大型集合中的每個段落。</p><h4>v2 M3 版本</h4><p>製造商將 BGE-M3 列為基礎模型，並將多語言支援列為主要特色。在 v2 重排序系列中，M3 是高效率的多語言選項；以 Gemma 為基礎的版本與層選擇版本是不同模型，實作選擇也不同。此處的 M3 名稱不代表重排序模型會傳回原始嵌入模型的稠密、稀疏及多向量嵌入。</p><p>選擇應用程式需要的結果時，這項區別很重要。要表示與搜尋文件集合，應選擇嵌入模型。已有候選文字、需要判定哪個段落最切合目前查詢時，則選擇此重排序模型。</p><h4>準備能有效排序的候選資料</h4><p>提供實際問題，以及解讀所需的完整候選文字。若標題或附近定義會影響段落意義，應一併保留。公布的 Transformers 範例會將查詢與段落一起轉為 token，啟用截斷並設為 max_length=512。這是範例設定，而非整個模型的通用限制。將問題與必要佐證保留在選定的配對額度內，並檢查截斷移除了哪些內容。即使結果提到與查詢相同的產品，若談的是錯誤操作或條件，仍可能不相關；評估檢索品質時，準備能區分這些情況的範例。</p><p>文件助理應保留候選識別碼與對應文字，為問題與段落配對評分，再將選定的原始段落交給回答步驟。這樣回答模型會收到佐證，而不是缺少來源的相關性分數。這是檢索工作流程的示例；重排序模型本身不會搜尋外部集合，也不會撰寫回答。</p><h4>讀取與正規化分數</h4><p>製造商傳回原始相關性分數，數值越高表示越接近查詢。文件記載的選用正規化會套用 sigmoid 函數，將分數置於 0 至 1 之間。正規化分數的範圍便於使用，但僅靠這項轉換，無法確立候選正確性的校準機率。</p><p>以工作負載中具代表性的查詢與段落配對選擇排序或篩選門檻。納入具有相同關鍵字但回答不同問題的段落，以及措辭不同但相關的段落。這樣選定門檻才對正在搜尋的集合有意義。</p><p>Ailoot API 專案應定義最終上下文應包含哪些內容，以及能有效檢視多少候選。實用結果是為應用程式下一步提供排序更佳的佐證集合。將此版本的相關性輸出，與文件嵌入、生成文章，以及其他重排序模型記載的層選擇控制分開。</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 · 重新排序</b> <code>POST /v1/rerank</code></summary><dl class=\"method-capabilities\"><div><dt>輸入</dt><dd><code>text</code></dd></div><div><dt>輸出</dt><dd><code>rerank</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>bge-reranker-v2-m3</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\">query</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></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\">documents</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>必填</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, documents</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</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>material_conditions</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>請設定實際查詢內容，並提供包含原始文字文件的非空陣列。結果索引會指向該原始陣列。</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/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 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>Ailoot 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>計費單位</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=\"計費單位\"><span class=\"card-cell-label\">計費單位</span>—</td><td data-cell-label=\"費用\"><span class=\"card-cell-label\">費用</span><div><span>輸入 · 輸入 Token</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸出 · 輸出 Token</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 讀取快取</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 寫入快取</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 寫入快取，1 小時</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>總詞元</th><td data-cell-label=\"費率表\"><span class=\"card-cell-label\">費率表</span>—</td><td data-cell-label=\"計費單位\"><span class=\"card-cell-label\">計費單位</span>/ 1K Token</td><td data-cell-label=\"費用\"><span class=\"card-cell-label\">費用</span><div><span>輸入 · 總詞元</span> <b>$0.00004</b> <span class=\"price-unit\">/ 1K Token</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot 會在請求前預留估算金額。取得結果後，依實測用量結算最終費用。串流結算採用最終用量紀錄。<a href=\"/docs/zh-hant-tw/billing/reserve/\">預留金額與結算的運作方式 →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">請求範例</h3><h4>Ailoot Ultra · 重新排序</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"程式碼版本\"><button class=\"cg-tab\" id=\"model-code-1089-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-1089-panel-0\" aria-selected=\"true\" tabindex=\"0\">使用實際輸入並保留完整結果</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"複製程式碼\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-1089-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-1089-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\n: &quot;${AILOOT_QUERY:?Set the actual documented input value}&quot;\nexport AILOOT_QUERY\n: &quot;${AILOOT_DOCUMENTS_JSON:?Set the actual documented input value}&quot;\nexport AILOOT_DOCUMENTS_JSON\npython3 - &lt;&lt;&#39;PY_REQUEST&#39;\nimport json,os\nfrom pathlib import Path\nrequest={&#39;model&#39;: &#39;bge-reranker-v2-m3&#39;, &#39;query&#39;: &#39;${ACTUAL_QUERY}&#39;, &#39;documents&#39;: &#39;${ACTUAL_DOCUMENTS}&#39;}\nrequest[&#39;query&#39;]=os.environ[&#39;AILOOT_QUERY&#39;]\nrequest[&#39;documents&#39;]=json.loads(os.environ[&#39;AILOOT_DOCUMENTS_JSON&#39;])\nPath(&#39;request.json&#39;).write_text(json.dumps(request,ensure_ascii=False),encoding=&#39;utf-8&#39;)\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/rerank \\\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 response.bin\n# Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.\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 · 重新排序</h4><p class=\"note-s\">完整的原始原生 JSON 結果，含已設定的回應模型、原始文件索引、相關性分數、文件字串與原生詞元用量。請保留每個實際結果與用量欄位。</p><ul class=\"card-result-paths\"><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><div class=\"card-result-process\" data-all-results><h5>保留所有已完成的結果</h5><p class=\"note-s\">請保留所有完整傳回的回應、檔案與內容區塊。</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\">請保留實際的 X-Client-Request-ID 與完整回應。請讀取原始自有資產及其完全相符的簽署內容 URL；切勿重新提交結果不明的建立請求。</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><th>含義</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>string</td><td data-cell-label=\"含義\"><span class=\"card-cell-label\">含義</span>已設定的 Source 取用端所要求的確切回應模型。</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">results[].index</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span>integer</td><td data-cell-label=\"含義\"><span class=\"card-cell-label\">含義</span>原始輸入文件的唯一索引。</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">results[].relevance_score</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span>number</td><td data-cell-label=\"含義\"><span class=\"card-cell-label\">含義</span>有限值的相關性分數。</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">results[].document</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span>string</td><td data-cell-label=\"含義\"><span class=\"card-cell-label\">含義</span>此已設定的回應取用端所需的原始文字文件。</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.total_tokens</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span>integer</td><td data-cell-label=\"含義\"><span class=\"card-cell-label\">含義</span>目前已接受費率所要求的有限且非負原生詞元數。</td></tr></tbody></table></div></details><details class=\"card-about\" data-method-errors><summary>錯誤與後續步驟</summary><div class=\"tw\" data-card-table=\"errors\"><table><thead><tr><th>回應</th><th>條件</th><th>下一步</th></tr></thead><tbody><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>400 · <code>invalid_request_error</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>JSON 本文或明確的標準模型 ID 無效。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留回應，並修正指出的請求欄位。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>401 · <code>authentication_error</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>Ailoot API 金鑰無效。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請使用您已獲授權的 Ailoot API 金鑰。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>403 · <code>permission_error</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>此金鑰群組未獲准使用該方法。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留回傳的錯誤詳細資訊。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>404 · <code>not_found_error</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>所選方法沒有獲准使用的路由。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留回傳的錯誤詳細資訊。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>422 · <code>price_unavailable</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>已接受的費率無法取得其所需的輸入數量或界限。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留回應，並使用已接受費率所要求的輸入表示方式。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>503 · <code></code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>所需的儲存系統、路由、方法價格或預留額度無法使用。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留完整的原始回應。預留額度狀態不明並不代表可以重新提交。</td></tr><tr><th data-cell-label=\"回應\" scope=\"row\"><span class=\"card-cell-label\">回應</span>502 · <code>billing_requires_check</code></th><td data-cell-label=\"條件\"><span class=\"card-cell-label\">條件</span>原始結果、用量或結算需要查核。</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>請保留實際的請求 ID 與原始回應。請讀取現有的自有紀錄，切勿重新提交建立請求。</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=bge-reranker-v2-m3&amp;route=Ultra&amp;caller=bge-reranker-v2-m3&amp;fmt=rerank\"><code>bge-reranker-v2-m3</code></a></span></p><h4>方法路徑別名</h4><p class=\"note-s\">請使用上方列出的 API 方法路徑。</p><h4>相關呼叫用 ID</h4><p class=\"note-s\"><a href=\"#m=bge-reranker-v2-m3&amp;route=Ultra&amp;caller=bge-reranker-v2-m3&amp;fmt=rerank\"><code>bge-reranker-v2-m3</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "bge-reranker-v2-m3",
        "fmt": "rerank",
        "http": "POST",
        "path": "/v1/rerank",
        "request_model_id": "bge-reranker-v2-m3",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|rerank|/v1/rerank|bge-reranker-v2-m3",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "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.",
            "errors": [
              {
                "code": null,
                "condition": "JSON 本文或明確的標準模型 ID 無效。",
                "http_status": 400,
                "recovery": "請保留回應，並修正指出的請求欄位。",
                "type": "invalid_request_error"
              },
              {
                "code": null,
                "condition": "Ailoot API 金鑰無效。",
                "http_status": 401,
                "recovery": "請使用您已獲授權的 Ailoot API 金鑰。",
                "type": "authentication_error"
              },
              {
                "code": null,
                "condition": "此金鑰群組未獲准使用該方法。",
                "http_status": 403,
                "recovery": "請保留回傳的錯誤詳細資訊。",
                "type": "permission_error"
              },
              {
                "code": null,
                "condition": "所選方法沒有獲准使用的路由。",
                "http_status": 404,
                "recovery": "請保留回傳的錯誤詳細資訊。",
                "type": "not_found_error"
              },
              {
                "code": null,
                "condition": "已接受的費率無法取得其所需的輸入數量或界限。",
                "http_status": 422,
                "recovery": "請保留回應，並使用已接受費率所要求的輸入表示方式。",
                "type": "price_unavailable"
              },
              {
                "code": null,
                "condition": "所需的儲存系統、路由、方法價格或預留額度無法使用。",
                "http_status": 503,
                "recovery": "請保留完整的原始回應。預留額度狀態不明並不代表可以重新提交。",
                "type": null
              },
              {
                "code": null,
                "condition": "原始結果、用量或結算需要查核。",
                "http_status": 502,
                "recovery": "請保留實際的請求 ID 與原始回應。請讀取現有的自有紀錄，切勿重新提交建立請求。",
                "type": "billing_requires_check"
              }
            ],
            "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 content URL"
                }
              ],
              "dedicated_method_polling_or_cancel": false,
              "mode": "synchronous_result_then_owned_library",
              "original_POST_adds_task_envelope": false,
              "status": [],
              "unknown": "請保留實際的 X-Client-Request-ID 與完整回應。請讀取原始自有資產及其完全相符的簽署內容 URL；切勿重新提交結果不明的建立請求。"
            },
            "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": "rerank",
              "fields": [
                {
                  "description": "已設定的 Source 取用端所要求的確切回應模型。",
                  "name": "model",
                  "type": "string"
                },
                {
                  "description": "原始輸入文件的唯一索引。",
                  "name": "results[].index",
                  "type": "integer"
                },
                {
                  "description": "有限值的相關性分數。",
                  "name": "results[].relevance_score",
                  "type": "number"
                },
                {
                  "description": "此已設定的回應取用端所需的原始文字文件。",
                  "name": "results[].document",
                  "type": "string"
                },
                {
                  "description": "目前已接受費率所要求的有限且非負原生詞元數。",
                  "name": "usage.total_tokens",
                  "type": "integer"
                }
              ],
              "result": "完整的原始原生 JSON 結果，含已設定的回應模型、原始文件索引、相關性分數、文件字串與原生詞元用量。請保留每個實際結果與用量欄位。"
            },
            "parameters": [
              {
                "default_known": false,
                "enum": [
                  "bge-reranker-v2-m3"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "query",
                "required": false,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "documents",
                "required": true,
                "type": "array"
              }
            ],
            "request_schema": {
              "properties": {
                "documents": {
                  "items": {
                    "type": "string"
                  },
                  "minItems": 1,
                  "type": "array"
                },
                "model": {
                  "enum": [
                    "bge-reranker-v2-m3"
                  ],
                  "type": "string"
                },
                "query": {
                  "type": "string"
                }
              },
              "required": [
                "model",
                "documents"
              ],
              "type": "object"
            },
            "schema_template": {
              "actual_file_preparation_required": false,
              "body": {
                "documents": "${ACTUAL_DOCUMENTS}",
                "model": "bge-reranker-v2-m3",
                "query": "${ACTUAL_QUERY}"
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "content_type": "application/json",
            "material_conditions": [
              "請設定實際查詢內容，並提供包含原始文字文件的非空陣列。結果索引會指向該原始陣列。"
            ],
            "material_types": [
              "text"
            ],
            "required": [
              "model",
              "documents"
            ]
          },
          "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 content URL"
              }
            ],
            "dedicated_method_polling_or_cancel": false,
            "mode": "synchronous_result_then_owned_library",
            "original_POST_adds_task_envelope": false,
            "status": [],
            "unknown": "Retain the actual X-Client-Request-ID and complete response. Read the original owned assets and their exact signed content URLs; never resubmit an uncertain creation."
          },
          "method": {
            "http": "POST",
            "path": "/v1/rerank"
          },
          "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": "rerank",
            "fields": [
              {
                "description": "Exact response model required by the configured Source consumer.",
                "name": "model",
                "type": "string"
              },
              {
                "description": "Unique original input document index.",
                "name": "results[].index",
                "type": "integer"
              },
              {
                "description": "Finite relevance score.",
                "name": "results[].relevance_score",
                "type": "number"
              },
              {
                "description": "Original text document required by this configured response consumer.",
                "name": "results[].document",
                "type": "string"
              },
              {
                "description": "Finite nonnegative native token count required by the current accepted tariff.",
                "name": "usage.total_tokens",
                "type": "integer"
              }
            ],
            "result": "Complete original native JSON result with the configured response model, original document indices, relevance scores, document strings and native token usage. Retain every actual result and usage field."
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "/ 1K tokens"
            },
            "label": "total token",
            "units": [
              {
                "amount": "0.00004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "total_token",
                "label": "total token",
                "native_amount_usd_per_unit": "0.00000004",
                "native_quantity": 1,
                "native_unit": "total_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "total_token"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_QUERY:?Set the actual documented input value}\"\nexport AILOOT_QUERY\n: \"${AILOOT_DOCUMENTS_JSON:?Set the actual documented input value}\"\nexport AILOOT_DOCUMENTS_JSON\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\nrequest={'model': 'bge-reranker-v2-m3', 'query': '${ACTUAL_QUERY}', 'documents': '${ACTUAL_DOCUMENTS}'}\nrequest['query']=os.environ['AILOOT_QUERY']\nrequest['documents']=json.loads(os.environ['AILOOT_DOCUMENTS_JSON'])\nPath('request.json').write_text(json.dumps(request,ensure_ascii=False),encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/rerank \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o response.bin\n# Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.\n",
            "label": "Use actual input and retain the complete result",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "rerank",
        "hints": [
          "Set your actual query and nonempty array of original text documents. Result indices refer to that original array.",
          "The minimum example omits top_n, return_documents, instruct and other optional controls.",
          "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"
        ],
        "label": "重新排序",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "native_endpoint": "rerank",
        "out": null,
        "output": [
          "rerank"
        ],
        "path": "/v1/rerank",
        "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": "per_request",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null,
          "unit_prices": {
            "total_token": 4e-08
          }
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "/ 1K tokens"
            },
            "label": "total token",
            "units": [
              {
                "amount": "0.00004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "total_token",
                "label": "total token",
                "native_amount_usd_per_unit": "0.00000004",
                "native_quantity": 1,
                "native_unit": "total_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "total_token"
              }
            ]
          }
        ],
        "request_model_id": "bge-reranker-v2-m3",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "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": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "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": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "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": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "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": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "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": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          },
          {
            "amount": "0.00004000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "total_token",
            "label": "total token",
            "native_amount_usd_per_unit": "0.00000004",
            "native_quantity": 1,
            "native_unit": "total_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "total_token"
          }
        ]
      }
    }
  ],
  "model_id": "bge-reranker-v2-m3",
  "nativeProvenance": {
    "input_facts_canonical_sha256": "ef900f3312ea80d0aba6075ec348d633258d2652a4eea74c4b7073a23356e2c5",
    "input_html_sha256": "764b83e7ca067ac582bb168801624b2521b8eee96831d0d10da21cb4101a46d8",
    "private_audit_sha256": "3d7ce80fbe8055ccdea5e22ea93c0cfeefb890728859fa5c4c2f6f87de719700",
    "role": "historical-normalized-input-audit-hashes",
    "schema": "ailoot-native-model-provenance-v2"
  },
  "page": {
    "canonical": "https://ailoot.ai/models/zh-hant-tw/bge-reranker-v2-m3/",
    "description": "BAAI 的多語言交叉編碼器，用來依查詢為候選段落排序。它一起讀取每組查詢與段落，回傳相關性分數，精煉搜尋候選清單，不會生成答案或建立文件嵌入。",
    "locale": "zh-hant-tw",
    "md_url": "https://ailoot.ai/models/zh-hant-tw/bge-reranker-v2-m3/index.md",
    "title": "bge-reranker-v2-m3 — Ailoot",
    "url": "https://ailoot.ai/models/zh-hant-tw/bge-reranker-v2-m3/"
  },
  "rawModel": {
    "about": "BGE Reranker v2 M3 是以 BGE-M3 為基礎的多語言相關性模型。它同時接收查詢與候選段落，傳回表示兩者關聯程度的分數。BAAI 將此版本定位為高效率的多語言重排序模型，包括適合中文與英文檢索，供搜尋應用程式進一步調整既有候選清單。\n\n### 根據查詢與段落配對評估相關性\n\n交叉編碼器會共同處理兩段文字，讓內容在產生相關性分數前互相作用。這與嵌入模型不同；嵌入模型分別編碼文字，供可重複使用的向量比較。重排序模型輸出的是特定配對的純量分數，而非文件向量或文字回答。\n\n在初步搜尋選出可能相關的段落後使用此模型。將問題與每個候選段落配對，再依所得分數排序候選。這讓更細緻的比較集中於可管理的短名單，避免要求交叉編碼器檢視大型集合中的每個段落。\n\n### v2 M3 版本\n\n製造商將 BGE-M3 列為基礎模型，並將多語言支援列為主要特色。在 v2 重排序系列中，M3 是高效率的多語言選項；以 Gemma 為基礎的版本與層選擇版本是不同模型，實作選擇也不同。此處的 M3 名稱不代表重排序模型會傳回原始嵌入模型的稠密、稀疏及多向量嵌入。\n\n選擇應用程式需要的結果時，這項區別很重要。要表示與搜尋文件集合，應選擇嵌入模型。已有候選文字、需要判定哪個段落最切合目前查詢時，則選擇此重排序模型。\n\n### 準備能有效排序的候選資料\n\n提供實際問題，以及解讀所需的完整候選文字。若標題或附近定義會影響段落意義，應一併保留。公布的 Transformers 範例會將查詢與段落一起轉為 token，啟用截斷並設為 max_length=512。這是範例設定，而非整個模型的通用限制。將問題與必要佐證保留在選定的配對額度內，並檢查截斷移除了哪些內容。即使結果提到與查詢相同的產品，若談的是錯誤操作或條件，仍可能不相關；評估檢索品質時，準備能區分這些情況的範例。\n\n文件助理應保留候選識別碼與對應文字，為問題與段落配對評分，再將選定的原始段落交給回答步驟。這樣回答模型會收到佐證，而不是缺少來源的相關性分數。這是檢索工作流程的示例；重排序模型本身不會搜尋外部集合，也不會撰寫回答。\n\n### 讀取與正規化分數\n\n製造商傳回原始相關性分數，數值越高表示越接近查詢。文件記載的選用正規化會套用 sigmoid 函數，將分數置於 0 至 1 之間。正規化分數的範圍便於使用，但僅靠這項轉換，無法確立候選正確性的校準機率。\n\n以工作負載中具代表性的查詢與段落配對選擇排序或篩選門檻。納入具有相同關鍵字但回答不同問題的段落，以及措辭不同但相關的段落。這樣選定門檻才對正在搜尋的集合有意義。\n\nAiloot API 專案應定義最終上下文應包含哪些內容，以及能有效檢視多少候選。實用結果是為應用程式下一步提供排序更佳的佐證集合。將此版本的相關性輸出，與文件嵌入、生成文章，以及其他重排序模型記載的層選擇控制分開。",
    "alias_of": null,
    "aliases": [],
    "author": "BAAI",
    "capabilities": {
      "context_length": 0,
      "manufacturer_input": [],
      "manufacturer_output": []
    },
    "card_routes": [
      {
        "label": "Ultra",
        "rates": [
          {
            "amount": "0.00004000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "total_token",
            "label": "total token",
            "native_amount_usd_per_unit": "0.00000004",
            "native_quantity": 1,
            "native_unit": "total_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "total_token"
          }
        ],
        "summary": "完整的設定價格資訊請見詳細資料。"
      }
    ],
    "ctx": null,
    "formats": [
      "rerank"
    ],
    "id": "bge-reranker-v2-m3",
    "input": [
      "text"
    ],
    "kind": "text",
    "max_out": null,
    "methods": [
      {
        "available": null,
        "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.",
            "errors": [
              {
                "code": null,
                "condition": "JSON 本文或明確的標準模型 ID 無效。",
                "http_status": 400,
                "recovery": "請保留回應，並修正指出的請求欄位。",
                "type": "invalid_request_error"
              },
              {
                "code": null,
                "condition": "Ailoot API 金鑰無效。",
                "http_status": 401,
                "recovery": "請使用您已獲授權的 Ailoot API 金鑰。",
                "type": "authentication_error"
              },
              {
                "code": null,
                "condition": "此金鑰群組未獲准使用該方法。",
                "http_status": 403,
                "recovery": "請保留回傳的錯誤詳細資訊。",
                "type": "permission_error"
              },
              {
                "code": null,
                "condition": "所選方法沒有獲准使用的路由。",
                "http_status": 404,
                "recovery": "請保留回傳的錯誤詳細資訊。",
                "type": "not_found_error"
              },
              {
                "code": null,
                "condition": "已接受的費率無法取得其所需的輸入數量或界限。",
                "http_status": 422,
                "recovery": "請保留回應，並使用已接受費率所要求的輸入表示方式。",
                "type": "price_unavailable"
              },
              {
                "code": null,
                "condition": "所需的儲存系統、路由、方法價格或預留額度無法使用。",
                "http_status": 503,
                "recovery": "請保留完整的原始回應。預留額度狀態不明並不代表可以重新提交。",
                "type": null
              },
              {
                "code": null,
                "condition": "原始結果、用量或結算需要查核。",
                "http_status": 502,
                "recovery": "請保留實際的請求 ID 與原始回應。請讀取現有的自有紀錄，切勿重新提交建立請求。",
                "type": "billing_requires_check"
              }
            ],
            "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 content URL"
                }
              ],
              "dedicated_method_polling_or_cancel": false,
              "mode": "synchronous_result_then_owned_library",
              "original_POST_adds_task_envelope": false,
              "status": [],
              "unknown": "請保留實際的 X-Client-Request-ID 與完整回應。請讀取原始自有資產及其完全相符的簽署內容 URL；切勿重新提交結果不明的建立請求。"
            },
            "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": "rerank",
              "fields": [
                {
                  "description": "已設定的 Source 取用端所要求的確切回應模型。",
                  "name": "model",
                  "type": "string"
                },
                {
                  "description": "原始輸入文件的唯一索引。",
                  "name": "results[].index",
                  "type": "integer"
                },
                {
                  "description": "有限值的相關性分數。",
                  "name": "results[].relevance_score",
                  "type": "number"
                },
                {
                  "description": "此已設定的回應取用端所需的原始文字文件。",
                  "name": "results[].document",
                  "type": "string"
                },
                {
                  "description": "目前已接受費率所要求的有限且非負原生詞元數。",
                  "name": "usage.total_tokens",
                  "type": "integer"
                }
              ],
              "result": "完整的原始原生 JSON 結果，含已設定的回應模型、原始文件索引、相關性分數、文件字串與原生詞元用量。請保留每個實際結果與用量欄位。"
            },
            "parameters": [
              {
                "default_known": false,
                "enum": [
                  "bge-reranker-v2-m3"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "query",
                "required": false,
                "type": "string"
              },
              {
                "default_known": false,
                "enum_known": false,
                "name": "documents",
                "required": true,
                "type": "array"
              }
            ],
            "request_schema": {
              "properties": {
                "documents": {
                  "items": {
                    "type": "string"
                  },
                  "minItems": 1,
                  "type": "array"
                },
                "model": {
                  "enum": [
                    "bge-reranker-v2-m3"
                  ],
                  "type": "string"
                },
                "query": {
                  "type": "string"
                }
              },
              "required": [
                "model",
                "documents"
              ],
              "type": "object"
            },
            "schema_template": {
              "actual_file_preparation_required": false,
              "body": {
                "documents": "${ACTUAL_DOCUMENTS}",
                "model": "bge-reranker-v2-m3",
                "query": "${ACTUAL_QUERY}"
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "content_type": "application/json",
            "material_conditions": [
              "請設定實際查詢內容，並提供包含原始文字文件的非空陣列。結果索引會指向該原始陣列。"
            ],
            "material_types": [
              "text"
            ],
            "required": [
              "model",
              "documents"
            ]
          },
          "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 content URL"
              }
            ],
            "dedicated_method_polling_or_cancel": false,
            "mode": "synchronous_result_then_owned_library",
            "original_POST_adds_task_envelope": false,
            "status": [],
            "unknown": "Retain the actual X-Client-Request-ID and complete response. Read the original owned assets and their exact signed content URLs; never resubmit an uncertain creation."
          },
          "method": {
            "http": "POST",
            "path": "/v1/rerank"
          },
          "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": "rerank",
            "fields": [
              {
                "description": "Exact response model required by the configured Source consumer.",
                "name": "model",
                "type": "string"
              },
              {
                "description": "Unique original input document index.",
                "name": "results[].index",
                "type": "integer"
              },
              {
                "description": "Finite relevance score.",
                "name": "results[].relevance_score",
                "type": "number"
              },
              {
                "description": "Original text document required by this configured response consumer.",
                "name": "results[].document",
                "type": "string"
              },
              {
                "description": "Finite nonnegative native token count required by the current accepted tariff.",
                "name": "usage.total_tokens",
                "type": "integer"
              }
            ],
            "result": "Complete original native JSON result with the configured response model, original document indices, relevance scores, document strings and native token usage. Retain every actual result and usage field."
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "/ 1K tokens"
            },
            "label": "total token",
            "units": [
              {
                "amount": "0.00004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "total_token",
                "label": "total token",
                "native_amount_usd_per_unit": "0.00000004",
                "native_quantity": 1,
                "native_unit": "total_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "total_token"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_QUERY:?Set the actual documented input value}\"\nexport AILOOT_QUERY\n: \"${AILOOT_DOCUMENTS_JSON:?Set the actual documented input value}\"\nexport AILOOT_DOCUMENTS_JSON\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\nrequest={'model': 'bge-reranker-v2-m3', 'query': '${ACTUAL_QUERY}', 'documents': '${ACTUAL_DOCUMENTS}'}\nrequest['query']=os.environ['AILOOT_QUERY']\nrequest['documents']=json.loads(os.environ['AILOOT_DOCUMENTS_JSON'])\nPath('request.json').write_text(json.dumps(request,ensure_ascii=False),encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/rerank \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o response.bin\n# Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.\n",
            "label": "Use actual input and retain the complete result",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "rerank",
        "hints": [
          "Set your actual query and nonempty array of original text documents. Result indices refer to that original array.",
          "The minimum example omits top_n, return_documents, instruct and other optional controls.",
          "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"
        ],
        "label": "重新排序",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "native_endpoint": "rerank",
        "out": null,
        "output": [
          "rerank"
        ],
        "path": "/v1/rerank",
        "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": "per_request",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null,
          "unit_prices": {
            "total_token": 4e-08
          }
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "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": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "quoted_unit": "/ 1K tokens"
            },
            "label": "total token",
            "units": [
              {
                "amount": "0.00004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "total_token",
                "label": "total token",
                "native_amount_usd_per_unit": "0.00000004",
                "native_quantity": 1,
                "native_unit": "total_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "total_token"
              }
            ]
          }
        ],
        "request_model_id": "bge-reranker-v2-m3",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "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": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "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": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "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": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "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": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "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": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          },
          {
            "amount": "0.00004000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "total_token",
            "label": "total token",
            "native_amount_usd_per_unit": "0.00000004",
            "native_quantity": 1,
            "native_unit": "total_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "total_token"
          }
        ]
      }
    ],
    "model_aliases": [
      {
        "canonical_model_id": "bge-reranker-v2-m3",
        "request_model_id": "bge-reranker-v2-m3",
        "route_label": "Ultra"
      }
    ],
    "name": "bge-reranker-v2-m3",
    "price": {
      "in": null,
      "in_label": null,
      "out": null,
      "out_label": null,
      "sort_in": null,
      "sort_out": null,
      "varies": true
    },
    "short": "BAAI 的多語言交叉編碼器，用來依查詢為候選段落排序。它一起讀取每組查詢與段落，回傳相關性分數，精煉搜尋候選清單，不會生成答案或建立文件嵌入。"
  },
  "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": "BAAI 的多語言交叉編碼器，用來依查詢為候選段落排序。它一起讀取每組查詢與段落，回傳相關性分數，精煉搜尋候選清單，不會生成答案或建立文件嵌入。",
  "source": {
    "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1",
    "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036",
    "raw_model_json_sha256": "534b01b37d81ac8ffd804c6c2b89cab3e75003bd1c88f712cc055570f9d60c67",
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