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  "aboutHtml": "<p>Claude Sonnet 4.5 是 Anthropic 偏重軟體開發、複雜代理任務與電腦操作的 Sonnet 版本，也改善推理與數學。它接收文字與圖片，產生文字。發布說明描述跨多步驟持續工作、程式碼理解，以及涉及較廣專案而非單一獨立函式的修改。實用簡報會指出必要行為、相關來源資料與交付成品：修補程式提案、實作說明、文件分析或結構化答案。</p><p>軟體工作請提供專案限制、相關檔案或摘錄、觀察到的錯誤，以及預期結果的具體範例。要求提供受影響程式碼，說明提議修改如何處理該範例。開發者將此模型定位於建構代理與透過工具進行開發任務。周邊應用程式讀取及編輯檔案、執行命令或檢查，並回傳實際輸出；模型依這些證據推理。最終報告應區分修改提案與已完成檢查。</p><p>電腦操作是其視覺與代理能力的另一種應用。Anthropic 發布示範透過連接環境與瀏覽器互動、瀏覽頁面及處理試算表。視覺簡報可提供截圖、指出目標，並定義應用程式允許哪些操作。應用程式再執行選定互動，回傳改變後畫面或其他結果。同樣地，模型可為文件、試算表與投影片準備內容及程式碼，由環境產生完成檔案。文字與圖片理解不代表模型是原生圖片或音訊生成器。</p><p>確切的開發者規格列出 200K 詞元上下文視窗，以及最多 64K 輸出詞元。可靠知識截止為 2025 年 1 月，與頁面列出的較晚訓練資料截止不同。長輸入應清楚保留文件邊界、頁面標籤、單位與程式碼識別碼，並為所需答案及推理預留空間。開發者也記載此版本的上下文感知，因此支援的流程會追蹤對話剩餘空間。這有助於在視窗內管理持續任務，但不會把視窗改成後來 Sonnet 版本的較大容量。</p><p>Sonnet 4.5 支援一般回應與手動延伸思考。後者以 budget_tokens 設定可見答案之前內部推理的目標。文件記載的最小值為 1,024 詞元，預算通常必須低於 max_tokens，因為思考與最終答案共用生成額度。預算是目標，不承諾恰好消耗該詞元數。此版本沒有後來 Sonnet 模型所述的自適應思考模式或 effort 控制。請選擇所需分析深度，並為可用的最終答案保留足夠額度。</p><p>開發者的交錯思考 beta，讓 Sonnet 4.5 在同一輪的工具呼叫之間推理，利用回傳觀察決定下一步。它需要支援的 Messages 流程中所記載的 beta 功能。這種情況下，思考預算可超過 max_tokens，因為它涵蓋同一助理輪次中的多個思考區塊。回傳工具結果時，應原封不動帶回相關思考內容，包括簽章；編輯內容會使其失效。因此，研究或除錯任務可在提議檢查、實際回傳結果與更新分析之間交替，不把文字提案當成完成動作。</p><p>視覺資料方面，開發者支援 JPEG、PNG、GIF 與 WebP，動畫只使用第一格。此版本使用的標準原生圖片級別，長邊上限為 1,568 像素，視覺詞元上限為 1,568；較大圖片會縮小。開發者圖片指南為 200K 上下文模型列出每次 API 請求最多 100 張圖片，但圖片及整體請求大小條件可能更早達到。實際可行時，將圖片放在問題前，為多張圖片加標籤，並保留小字或圖表標籤。指南建議清楚圖片，以及足以解讀可見細節的周邊上下文。</p><p>上下文編輯與記憶工具隨此模型一同引入，以支援較長代理流程。這些是應用程式支援的方式，用來保留有用狀態或移除舊工具資料；不是無限模型記憶，也不是後來的伺服器壓縮功能。多階段任務應保留已作決策、待解問題，以及下一步所需證據。Anthropic 也描述了更能抵抗外部內容中的隱藏指令，同時指出模型特定分類器有時會標記無害資料。實用結果仍是連結提供證據、可供審查的成品，並讓確切 Sonnet 4.5 模式及限制與後來版本分開。</p>",
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">A</span><h2 id=\"sheet-title\">Anthropic: Claude Sonnet 4.5</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"關閉\">×</button></div><div class=\"idline\"><span>Anthropic /</span><code>claude-sonnet-4-5-20250929-thinking</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|chat|/v1/chat/completions|claude-sonnet-4-5-20250929-thinking\">Chat</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\">Claude Sonnet 4.5 是 Anthropic 的文字與圖片模型，適用於軟體開發、複雜代理、電腦操作與分析工作。它支援直接回應或手動延伸思考，文件記載的 beta 流程可在工具呼叫之間推理。</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>文字</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>Claude Sonnet 4.5 是 Anthropic 偏重軟體開發、複雜代理任務與電腦操作的 Sonnet 版本，也改善推理與數學。它接收文字與圖片，產生文字。發布說明描述跨多步驟持續工作、程式碼理解，以及涉及較廣專案而非單一獨立函式的修改。實用簡報會指出必要行為、相關來源資料與交付成品：修補程式提案、實作說明、文件分析或結構化答案。</p><p>軟體工作請提供專案限制、相關檔案或摘錄、觀察到的錯誤，以及預期結果的具體範例。要求提供受影響程式碼，說明提議修改如何處理該範例。開發者將此模型定位於建構代理與透過工具進行開發任務。周邊應用程式讀取及編輯檔案、執行命令或檢查，並回傳實際輸出；模型依這些證據推理。最終報告應區分修改提案與已完成檢查。</p><p>電腦操作是其視覺與代理能力的另一種應用。Anthropic 發布示範透過連接環境與瀏覽器互動、瀏覽頁面及處理試算表。視覺簡報可提供截圖、指出目標，並定義應用程式允許哪些操作。應用程式再執行選定互動，回傳改變後畫面或其他結果。同樣地，模型可為文件、試算表與投影片準備內容及程式碼，由環境產生完成檔案。文字與圖片理解不代表模型是原生圖片或音訊生成器。</p><p>確切的開發者規格列出 200K 詞元上下文視窗，以及最多 64K 輸出詞元。可靠知識截止為 2025 年 1 月，與頁面列出的較晚訓練資料截止不同。長輸入應清楚保留文件邊界、頁面標籤、單位與程式碼識別碼，並為所需答案及推理預留空間。開發者也記載此版本的上下文感知，因此支援的流程會追蹤對話剩餘空間。這有助於在視窗內管理持續任務，但不會把視窗改成後來 Sonnet 版本的較大容量。</p><p>Sonnet 4.5 支援一般回應與手動延伸思考。後者以 budget_tokens 設定可見答案之前內部推理的目標。文件記載的最小值為 1,024 詞元，預算通常必須低於 max_tokens，因為思考與最終答案共用生成額度。預算是目標，不承諾恰好消耗該詞元數。此版本沒有後來 Sonnet 模型所述的自適應思考模式或 effort 控制。請選擇所需分析深度，並為可用的最終答案保留足夠額度。</p><p>開發者的交錯思考 beta，讓 Sonnet 4.5 在同一輪的工具呼叫之間推理，利用回傳觀察決定下一步。它需要支援的 Messages 流程中所記載的 beta 功能。這種情況下，思考預算可超過 max_tokens，因為它涵蓋同一助理輪次中的多個思考區塊。回傳工具結果時，應原封不動帶回相關思考內容，包括簽章；編輯內容會使其失效。因此，研究或除錯任務可在提議檢查、實際回傳結果與更新分析之間交替，不把文字提案當成完成動作。</p><p>視覺資料方面，開發者支援 JPEG、PNG、GIF 與 WebP，動畫只使用第一格。此版本使用的標準原生圖片級別，長邊上限為 1,568 像素，視覺詞元上限為 1,568；較大圖片會縮小。開發者圖片指南為 200K 上下文模型列出每次 API 請求最多 100 張圖片，但圖片及整體請求大小條件可能更早達到。實際可行時，將圖片放在問題前，為多張圖片加標籤，並保留小字或圖表標籤。指南建議清楚圖片，以及足以解讀可見細節的周邊上下文。</p><p>上下文編輯與記憶工具隨此模型一同引入，以支援較長代理流程。這些是應用程式支援的方式，用來保留有用狀態或移除舊工具資料；不是無限模型記憶，也不是後來的伺服器壓縮功能。多階段任務應保留已作決策、待解問題，以及下一步所需證據。Anthropic 也描述了更能抵抗外部內容中的隱藏指令，同時指出模型特定分類器有時會標記無害資料。實用結果仍是連結提供證據、可供審查的成品，並讓確切 Sonnet 4.5 模式及限制與後來版本分開。</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 · OpenAI Chat</b> <code>POST /v1/chat/completions</code></summary><dl class=\"method-capabilities\"><div><dt>輸入</dt><dd><code>text</code></dd></div><div><dt>輸出</dt><dd><code>text</code></dd></div><div><dt>輸出格式</dt><dd>json 或 SSE</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 data-parameter-availability=\"source_interface\"><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>claude-sonnet-4-5-20250929-thinking</div></td><td data-cell-label=\"預設值\" data-default=\"unspecified\"><span class=\"card-cell-label\">預設值</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">messages</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>message[]</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>項目數下限: 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 data-parameter-availability=\"model_dependent\"><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">messages[].role</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 class=\"note-s\">依模型而定</div></td><td data-cell-label=\"預設值\" data-default=\"unspecified\"><span class=\"card-cell-label\">預設值</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">messages[].content</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>適用條件: 文字對話</div></td><td data-cell-label=\"預設值\" data-default=\"unspecified\"><span class=\"card-cell-label\">預設值</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">stream</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span><code>boolean</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=\"known\"><span class=\"card-cell-label\">預設值</span>false</td></tr></tbody></table></div><details class=\"card-about\" data-material-combinations><summary>輸入素材組合</summary><p class=\"note-s\"><b>文字</b> · UTF8 文字</p><p class=\"note-s\"><code>messages[].content</code></p></details><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, messages</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>messages</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>具有 role/content 結構的訊息陣列</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>file_material</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>實際 UTF-8 文件以原文文字插入；不推定檔案 ID</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>optional_controls</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>stream</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>control_scope</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>文字對話；stream 是布林值，預設為 false。</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>output_modalities</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>hosted_operations</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>false</td></tr><tr><th data-cell-label=\"參數\" scope=\"row\"><span class=\"card-cell-label\">參數</span><code>multimodal_input_binding</code></th><td data-cell-label=\"規格\"><span class=\"card-cell-label\">規格</span>null</td></tr></tbody></table></div><p>方法別名： <code>/chat/completions</code></p><p>生命週期： <code>synchronous_or_streamed</code></p><p class=\"note-s\">將確切模型 ID 與 messages 一併送出。</p><p class=\"note-s\">上下文長度不是輸出上限。</p><p class=\"note-s\">文字檔案可提供原文文字；圖片／音訊／檔案物件輸入需要精確綁定。</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><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>設定</th><th>費率表</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>詞元基本費率</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=\"費用\"><span class=\"card-cell-label\">費用</span><div><span>輸入 · 輸入 Token</span> <b>$0.006</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸出 · 輸出 Token</span> <b>$0.03</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 讀取快取</span> <b>$0.0006</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 寫入快取</span> <b>$0.0075</b> <span class=\"price-unit\">/ 1K Token</span></div><div><span>輸入 · 寫入快取，1 小時</span> <b>—</b> <span class=\"price-unit\">/ 1K Token</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot 會在請求前預留估算金額。取得結果後，依實測用量結算最終費用。串流結算採用最終用量紀錄。<a href=\"/docs/zh-hant-tw/billing/reserve/\">預留金額與結算的運作方式 →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">請求範例</h3><h4>Ailoot Ultra · OpenAI Chat</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"程式碼版本\"><button class=\"cg-tab\" id=\"model-code-1172-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-1172-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl</button><button class=\"cg-tab\" id=\"model-code-1172-tab-1\" role=\"tab\" type=\"button\" aria-controls=\"model-code-1172-panel-1\" aria-selected=\"false\" tabindex=\"-1\">Python SDK</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"複製程式碼\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-1172-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-1172-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\npython3 - &lt;&lt;&#39;PY_REQUEST&#39;\nimport json,os\nfrom pathlib import Path\np=json.loads(&#39;{&quot;model&quot;:&quot;claude-sonnet-4-5-20250929-thinking&quot;,&quot;messages&quot;:[{&quot;role&quot;:&quot;user&quot;,&quot;content&quot;:&quot;hello&quot;}],&quot;stream&quot;:false}&#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/chat/completions \\\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 json\nfrom pathlib import Path\nr=json.loads(Path(&quot;result.json&quot;).read_text())\nfor x in r.get(&quot;choices&quot;,[]):\n    if x.get(&quot;message&quot;,{}).get(&quot;content&quot;): print(x[&quot;message&quot;][&quot;content&quot;])\nPY_RESULT\n</code></pre></div><div class=\"cg-pane\" id=\"model-code-1172-panel-1\" role=\"tabpanel\" aria-labelledby=\"model-code-1172-tab-1\" hidden><pre data-lang=\"python\"><code>from openai import OpenAI\nimport os\n\nif not os.environ.get(&quot;AILOOT_API_KEY&quot;, &quot;&quot;).strip(): raise SystemExit(&quot;Set AILOOT_API_KEY before making a request&quot;)\nclient=OpenAI(base_url=&quot;https://api.ailoot.ai/v1&quot;,api_key=os.environ[&quot;AILOOT_API_KEY&quot;],max_retries=0)\nresult=client.chat.completions.create(model=&quot;claude-sonnet-4-5-20250929-thinking&quot;, messages=[{&quot;role&quot;:&quot;user&quot;,&quot;content&quot;:&quot;hello&quot;}], stream=False)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=&quot;result&quot;):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + &quot;.json&quot;).write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=&quot;utf-8&quot;)\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b&quot;-_&quot;, validate=True)\n        ext = &quot;png&quot; if raw.startswith(b&quot;\\x89PNG\\r\\n\\x1a\\n&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 suffix\n        file = Path(stem + &quot;-&quot; + label + &quot;.&quot; + ext)\n        file.write_bytes(raw)\n        print(&quot;Saved&quot;, file)\n    for index, block in enumerate(data.get(&quot;content&quot;) or []):\n        print(&quot;Content&quot;, index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get(&quot;choices&quot;) or []:\n        print(&quot;Choice&quot;, choice.get(&quot;index&quot;), json.dumps(choice.get(&quot;message&quot;, choice.get(&quot;delta&quot;, {})), ensure_ascii=False))\n    for index, item in enumerate(data.get(&quot;output&quot;) or []):\n        print(&quot;Output&quot;, index, json.dumps(item, ensure_ascii=False))\n        if item.get(&quot;type&quot;) == &quot;image_generation_call&quot; and item.get(&quot;result&quot;):\n            save_blob(item[&quot;result&quot;], item.get(&quot;output_format&quot;) or &quot;bin&quot;, &quot;output-&quot; + str(index))\n    for ci, candidate in enumerate(data.get(&quot;candidates&quot;) or []):\n        for pi, part in enumerate((candidate.get(&quot;content&quot;) or {}).get(&quot;parts&quot;) or []):\n            print(&quot;Candidate/part&quot;, ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get(&quot;inlineData&quot;) or part.get(&quot;inline_data&quot;)\n            if blob and blob.get(&quot;data&quot;):\n                mime = blob.get(&quot;mimeType&quot;) or blob.get(&quot;mime_type&quot;)\n                suffix = {&quot;image/png&quot;:&quot;png&quot;, &quot;image/jpeg&quot;:&quot;jpg&quot;, &quot;image/webp&quot;:&quot;webp&quot;, &quot;audio/wav&quot;:&quot;wav&quot;, &quot;audio/mpeg&quot;:&quot;mp3&quot;, &quot;video/mp4&quot;:&quot;mp4&quot;}.get(mime, &quot;bin&quot;)\n                save_blob(blob[&quot;data&quot;], suffix, &quot;candidate-&quot; + str(ci) + &quot;-part-&quot; + str(pi))\n\nsave_result(result.to_dict(mode=&quot;json&quot;))\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 · OpenAI Chat</h4><p class=\"note-s\">json 或 SSE</p><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\">保留每個候選項及其內容／工具呼叫／推理。SSE 中依候選項／工具索引組合增量，保留最終完成原因與用量。</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\">保留請求／回應 ID 與標頭。未提供通用的文字工作擷取 URL。</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\">choices[].index</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span>integer</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">choices[].message.content</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span>string|null</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">choices[].message.tool_calls</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span>tool_call[]</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">choices[].message.reasoning_content</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span>string</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">choices[].message.reasoning_details</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span>object|array</td></tr><tr><th data-cell-label=\"欄位\" scope=\"row\"><span class=\"card-cell-label\">欄位</span><code class=\"card-field-name\">choices[].finish_reason</code></th><td data-cell-label=\"類型\" data-field-type><span class=\"card-cell-label\">類型</span>string|null</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>object</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>必要欄位、素材表示方式或參數值無效</td><td data-cell-label=\"下一步\"><span class=\"card-cell-label\">下一步</span>提出新的建立請求前，先修正指定欄位。</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=claude-sonnet-4-5-20250929-thinking&amp;route=Ultra&amp;caller=claude-sonnet-4-5-20250929-thinking&amp;fmt=chat\"><code>claude-sonnet-4-5-20250929-thinking</code></a></span></p><h4>方法路徑別名</h4><p class=\"note-s\"><code>/chat/completions</code></p><h4>相關呼叫用 ID</h4><p class=\"note-s\"><a href=\"#m=claude-sonnet-4-5-20250929-thinking&amp;route=Ultra&amp;caller=claude-sonnet-4-5-20250929-thinking&amp;fmt=chat\"><code>claude-sonnet-4-5-20250929-thinking</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "claude-sonnet-4-5-20250929-thinking",
        "fmt": "chat",
        "http": "POST",
        "path": "/v1/chat/completions",
        "request_model_id": "claude-sonnet-4-5-20250929-thinking",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|chat|/v1/chat/completions|claude-sonnet-4-5-20250929-thinking",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "cache_read": 0.6,
        "cache_write": 7.5,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.",
            "authentication": {
              "api_key_source": "AILOOT_API_KEY",
              "header": "Authorization: Bearer"
            },
            "errors": [
              {
                "code": null,
                "condition": "必要欄位、素材表示方式或參數值無效",
                "http_status": 400,
                "recovery": "提出新的建立請求前，先修正指定欄位。",
                "type": "invalid_request_error"
              }
            ],
            "hints": [
              "Model context is not an output cap.",
              "Send the conversation as text messages. Stream must be a boolean; omitted stream defaults to false."
            ],
            "ignored_fields": [],
            "lifecycle": {
              "create": {
                "http": "POST",
                "path": "/v1/chat/completions"
              },
              "job_read": null,
              "mode": "synchronous_or_streamed",
              "unknown": "保留請求／回應 ID 與標頭。未提供通用的文字工作擷取 URL。"
            },
            "material_combinations": [
              {
                "mode": "text",
                "representation": "messages[].content",
                "required_material": "UTF8 文字"
              }
            ],
            "operation_modes": [
              "conversation"
            ],
            "outputs": {
              "all_results": "保留每個候選項及其內容／工具呼叫／推理。SSE 中依候選項／工具索引組合增量，保留最終完成原因與用量。",
              "family": "text",
              "fields": [
                {
                  "description": null,
                  "name": "choices[].index",
                  "type": "integer"
                },
                {
                  "description": null,
                  "name": "choices[].message.content",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "choices[].message.tool_calls",
                  "type": "tool_call[]"
                },
                {
                  "description": null,
                  "name": "choices[].message.reasoning_content",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "choices[].message.reasoning_details",
                  "type": "object|array"
                },
                {
                  "description": null,
                  "name": "choices[].finish_reason",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": "object"
                }
              ],
              "format": "json 或 SSE"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "claude-sonnet-4-5-20250929-thinking"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "min_items": 1,
                "name": "messages",
                "required": true,
                "type": "message[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].role",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].content",
                "required": false,
                "type": "string",
                "when": "文字對話"
              },
              {
                "availability": "source_interface",
                "default": false,
                "default_known": true,
                "enum": null,
                "enum_known": false,
                "name": "stream",
                "required": false,
                "type": "boolean"
              }
            ],
            "profile_binding": "Text conversation at the exact model ID and method path.",
            "unsupported": [
              "additional models/models list",
              "plugins",
              "route",
              "hosted tools; ordinary client function tools remain separate",
              "non-text output modalities",
              "provider.options overrides",
              "one-hour prompt-cache TTL"
            ]
          },
          "hints": [
            "將確切模型 ID 與 messages 一併送出。",
            "上下文長度不是輸出上限。",
            "文字檔案可提供原文文字；圖片／音訊／檔案物件輸入需要精確綁定。"
          ],
          "input": {
            "content_type": "application/json",
            "control_scope": "文字對話；stream 是布林值，預設為 false。",
            "file_material": "實際 UTF-8 文件以原文文字插入；不推定檔案 ID",
            "hosted_operations": false,
            "material_types": [
              "text"
            ],
            "messages": "具有 role/content 結構的訊息陣列",
            "multimodal_input_binding": null,
            "optional_controls": [
              "stream"
            ],
            "output_modalities": [
              "text"
            ],
            "required": [
              "model",
              "messages"
            ]
          },
          "lifecycle": {
            "mode": "synchronous_or_streamed",
            "unknown": "preserve original request id; no generic chat job retrieval path"
          },
          "manufacturer_capability": null,
          "method": {
            "http": "POST",
            "path": "/v1/chat/completions"
          },
          "method_aliases": [
            "/chat/completions"
          ],
          "operation_modes": [
            "text_chat"
          ],
          "output": {
            "content": "choices[].message.content or stream delta",
            "family": "text",
            "format": "json or supported SSE",
            "tool_calls": "retain actual returned function calls"
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "詞元基本費率",
            "units": [
              {
                "amount": "0.006000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000006",
                "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": "0.03000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00003",
                "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": "0.0006000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000006",
                "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": "0.0075000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.0000075",
                "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"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\":\"claude-sonnet-4-5-20250929-thinking\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}],\"stream\":false}')\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/chat/completions \\\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 json\nfrom pathlib import Path\nr=json.loads(Path(\"result.json\").read_text())\nfor x in r.get(\"choices\",[]):\n    if x.get(\"message\",{}).get(\"content\"): print(x[\"message\"][\"content\"])\nPY_RESULT\n",
            "label": "curl · retained exact creation",
            "language": "bash"
          },
          {
            "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nresult=client.chat.completions.create(model=\"claude-sonnet-4-5-20250929-thinking\", messages=[{\"role\":\"user\",\"content\":\"hello\"}], stream=False)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n        ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n        file = Path(stem + \"-\" + label + \".\" + ext)\n        file.write_bytes(raw)\n        print(\"Saved\", file)\n    for index, block in enumerate(data.get(\"content\") or []):\n        print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get(\"choices\") or []:\n        print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get(\"output\") or []):\n        print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n        if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n            save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n    for ci, candidate in enumerate(data.get(\"candidates\") or []):\n        for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n            print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n            if blob and blob.get(\"data\"):\n                mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n                suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n                save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(result.to_dict(mode=\"json\"))\n",
            "label": "Python SDK · all choices",
            "language": "python"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "chat",
        "hints": [
          "Send exact model ID with messages.",
          "Context length is not an output cap.",
          "A text file may supply literal text; image/audio/file-object inputs need exact binding."
        ],
        "http": "POST",
        "in": 6,
        "input": [
          "text"
        ],
        "label": "OpenAI Chat",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [
          "/chat/completions"
        ],
        "out": 30,
        "output": [
          "text"
        ],
        "path": "/v1/chat/completions",
        "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": "token",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0.006000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000006",
                "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": "0.03000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00003",
                "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": "0.0006000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000006",
                "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": "0.0075000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.0000075",
                "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"
              }
            ]
          }
        ],
        "request_model_id": "claude-sonnet-4-5-20250929-thinking",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": "0.006000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.000006",
            "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": "0.03000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.00003",
            "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": "0.0006000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": "0.0000006",
            "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": "0.0075000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": "0.0000075",
            "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"
          }
        ]
      }
    }
  ],
  "model_id": "claude-sonnet-4-5-20250929-thinking",
  "nativeProvenance": {
    "input_facts_canonical_sha256": "087dc8fdc44dbb5c4b243d1face856a6934ffa225542f9d9f5cd53d4f36c73d6",
    "input_html_sha256": "a427bf58006e44e17d2e6419f11b7adb2dd7140c05f0549560146a0146cb6ad9",
    "private_audit_sha256": "dbbb45630a0b5fb17cc96ba8bcbece475acacc8f89dc34c894e9f91d2c1101da",
    "role": "historical-normalized-input-audit-hashes",
    "schema": "ailoot-native-model-provenance-v2"
  },
  "page": {
    "canonical": "https://ailoot.ai/models/zh-hant-tw/claude-sonnet-4-5-20250929-thinking/",
    "description": "Claude Sonnet 4.5 是 Anthropic 的文字與圖片模型，適用於軟體開發、複雜代理、電腦操作與分析工作。它支援直接回應或手動延伸思考，文件記載的 beta 流程可在工具呼叫之間推理。",
    "locale": "zh-hant-tw",
    "md_url": "https://ailoot.ai/models/zh-hant-tw/claude-sonnet-4-5-20250929-thinking/index.md",
    "title": "Anthropic: Claude Sonnet 4.5 — Ailoot",
    "url": "https://ailoot.ai/models/zh-hant-tw/claude-sonnet-4-5-20250929-thinking/"
  },
  "rawModel": {
    "about": "Claude Sonnet 4.5 是 Anthropic 偏重軟體開發、複雜代理任務與電腦操作的 Sonnet 版本，也改善推理與數學。它接收文字與圖片，產生文字。發布說明描述跨多步驟持續工作、程式碼理解，以及涉及較廣專案而非單一獨立函式的修改。實用簡報會指出必要行為、相關來源資料與交付成品：修補程式提案、實作說明、文件分析或結構化答案。\n\n軟體工作請提供專案限制、相關檔案或摘錄、觀察到的錯誤，以及預期結果的具體範例。要求提供受影響程式碼，說明提議修改如何處理該範例。開發者將此模型定位於建構代理與透過工具進行開發任務。周邊應用程式讀取及編輯檔案、執行命令或檢查，並回傳實際輸出；模型依這些證據推理。最終報告應區分修改提案與已完成檢查。\n\n電腦操作是其視覺與代理能力的另一種應用。Anthropic 發布示範透過連接環境與瀏覽器互動、瀏覽頁面及處理試算表。視覺簡報可提供截圖、指出目標，並定義應用程式允許哪些操作。應用程式再執行選定互動，回傳改變後畫面或其他結果。同樣地，模型可為文件、試算表與投影片準備內容及程式碼，由環境產生完成檔案。文字與圖片理解不代表模型是原生圖片或音訊生成器。\n\n確切的開發者規格列出 200K 詞元上下文視窗，以及最多 64K 輸出詞元。可靠知識截止為 2025 年 1 月，與頁面列出的較晚訓練資料截止不同。長輸入應清楚保留文件邊界、頁面標籤、單位與程式碼識別碼，並為所需答案及推理預留空間。開發者也記載此版本的上下文感知，因此支援的流程會追蹤對話剩餘空間。這有助於在視窗內管理持續任務，但不會把視窗改成後來 Sonnet 版本的較大容量。\n\nSonnet 4.5 支援一般回應與手動延伸思考。後者以 budget_tokens 設定可見答案之前內部推理的目標。文件記載的最小值為 1,024 詞元，預算通常必須低於 max_tokens，因為思考與最終答案共用生成額度。預算是目標，不承諾恰好消耗該詞元數。此版本沒有後來 Sonnet 模型所述的自適應思考模式或 effort 控制。請選擇所需分析深度，並為可用的最終答案保留足夠額度。\n\n開發者的交錯思考 beta，讓 Sonnet 4.5 在同一輪的工具呼叫之間推理，利用回傳觀察決定下一步。它需要支援的 Messages 流程中所記載的 beta 功能。這種情況下，思考預算可超過 max_tokens，因為它涵蓋同一助理輪次中的多個思考區塊。回傳工具結果時，應原封不動帶回相關思考內容，包括簽章；編輯內容會使其失效。因此，研究或除錯任務可在提議檢查、實際回傳結果與更新分析之間交替，不把文字提案當成完成動作。\n\n視覺資料方面，開發者支援 JPEG、PNG、GIF 與 WebP，動畫只使用第一格。此版本使用的標準原生圖片級別，長邊上限為 1,568 像素，視覺詞元上限為 1,568；較大圖片會縮小。開發者圖片指南為 200K 上下文模型列出每次 API 請求最多 100 張圖片，但圖片及整體請求大小條件可能更早達到。實際可行時，將圖片放在問題前，為多張圖片加標籤，並保留小字或圖表標籤。指南建議清楚圖片，以及足以解讀可見細節的周邊上下文。\n\n上下文編輯與記憶工具隨此模型一同引入，以支援較長代理流程。這些是應用程式支援的方式，用來保留有用狀態或移除舊工具資料；不是無限模型記憶，也不是後來的伺服器壓縮功能。多階段任務應保留已作決策、待解問題，以及下一步所需證據。Anthropic 也描述了更能抵抗外部內容中的隱藏指令，同時指出模型特定分類器有時會標記無害資料。實用結果仍是連結提供證據、可供審查的成品，並讓確切 Sonnet 4.5 模式及限制與後來版本分開。",
    "alias_of": null,
    "aliases": [],
    "author": "Anthropic",
    "available": null,
    "canonical_model": "claude-sonnet-4-5-20250929-thinking",
    "capabilities": {
      "context_length": 1000000,
      "manufacturer_input": [
        "text",
        "image",
        "file"
      ],
      "manufacturer_output": [
        "text"
      ]
    },
    "card_routes": [
      {
        "label": "Ultra",
        "rates": [
          {
            "amount": "0.006000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.000006",
            "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": "0.03000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.00003",
            "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"
          }
        ],
        "summary": "完整的設定價格資訊請見詳細資料。"
      }
    ],
    "ctx": null,
    "entity_type": "model",
    "formats": [
      "chat"
    ],
    "id": "claude-sonnet-4-5-20250929-thinking",
    "input": [
      "text"
    ],
    "kind": "text",
    "max_out": null,
    "methods": [
      {
        "available": null,
        "cache_read": 0.6,
        "cache_write": 7.5,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.",
            "authentication": {
              "api_key_source": "AILOOT_API_KEY",
              "header": "Authorization: Bearer"
            },
            "errors": [
              {
                "code": null,
                "condition": "必要欄位、素材表示方式或參數值無效",
                "http_status": 400,
                "recovery": "提出新的建立請求前，先修正指定欄位。",
                "type": "invalid_request_error"
              }
            ],
            "hints": [
              "Model context is not an output cap.",
              "Send the conversation as text messages. Stream must be a boolean; omitted stream defaults to false."
            ],
            "ignored_fields": [],
            "lifecycle": {
              "create": {
                "http": "POST",
                "path": "/v1/chat/completions"
              },
              "job_read": null,
              "mode": "synchronous_or_streamed",
              "unknown": "保留請求／回應 ID 與標頭。未提供通用的文字工作擷取 URL。"
            },
            "material_combinations": [
              {
                "mode": "text",
                "representation": "messages[].content",
                "required_material": "UTF8 文字"
              }
            ],
            "operation_modes": [
              "conversation"
            ],
            "outputs": {
              "all_results": "保留每個候選項及其內容／工具呼叫／推理。SSE 中依候選項／工具索引組合增量，保留最終完成原因與用量。",
              "family": "text",
              "fields": [
                {
                  "description": null,
                  "name": "choices[].index",
                  "type": "integer"
                },
                {
                  "description": null,
                  "name": "choices[].message.content",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "choices[].message.tool_calls",
                  "type": "tool_call[]"
                },
                {
                  "description": null,
                  "name": "choices[].message.reasoning_content",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "choices[].message.reasoning_details",
                  "type": "object|array"
                },
                {
                  "description": null,
                  "name": "choices[].finish_reason",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": "object"
                }
              ],
              "format": "json 或 SSE"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "claude-sonnet-4-5-20250929-thinking"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "min_items": 1,
                "name": "messages",
                "required": true,
                "type": "message[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].role",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].content",
                "required": false,
                "type": "string",
                "when": "文字對話"
              },
              {
                "availability": "source_interface",
                "default": false,
                "default_known": true,
                "enum": null,
                "enum_known": false,
                "name": "stream",
                "required": false,
                "type": "boolean"
              }
            ],
            "profile_binding": "Text conversation at the exact model ID and method path.",
            "unsupported": [
              "additional models/models list",
              "plugins",
              "route",
              "hosted tools; ordinary client function tools remain separate",
              "non-text output modalities",
              "provider.options overrides",
              "one-hour prompt-cache TTL"
            ]
          },
          "hints": [
            "將確切模型 ID 與 messages 一併送出。",
            "上下文長度不是輸出上限。",
            "文字檔案可提供原文文字；圖片／音訊／檔案物件輸入需要精確綁定。"
          ],
          "input": {
            "content_type": "application/json",
            "control_scope": "文字對話；stream 是布林值，預設為 false。",
            "file_material": "實際 UTF-8 文件以原文文字插入；不推定檔案 ID",
            "hosted_operations": false,
            "material_types": [
              "text"
            ],
            "messages": "具有 role/content 結構的訊息陣列",
            "multimodal_input_binding": null,
            "optional_controls": [
              "stream"
            ],
            "output_modalities": [
              "text"
            ],
            "required": [
              "model",
              "messages"
            ]
          },
          "lifecycle": {
            "mode": "synchronous_or_streamed",
            "unknown": "preserve original request id; no generic chat job retrieval path"
          },
          "manufacturer_capability": null,
          "method": {
            "http": "POST",
            "path": "/v1/chat/completions"
          },
          "method_aliases": [
            "/chat/completions"
          ],
          "operation_modes": [
            "text_chat"
          ],
          "output": {
            "content": "choices[].message.content or stream delta",
            "family": "text",
            "format": "json or supported SSE",
            "tool_calls": "retain actual returned function calls"
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "詞元基本費率",
            "units": [
              {
                "amount": "0.006000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000006",
                "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": "0.03000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00003",
                "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": "0.0006000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000006",
                "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": "0.0075000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.0000075",
                "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"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\":\"claude-sonnet-4-5-20250929-thinking\",\"messages\":[{\"role\":\"user\",\"content\":\"hello\"}],\"stream\":false}')\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/chat/completions \\\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 json\nfrom pathlib import Path\nr=json.loads(Path(\"result.json\").read_text())\nfor x in r.get(\"choices\",[]):\n    if x.get(\"message\",{}).get(\"content\"): print(x[\"message\"][\"content\"])\nPY_RESULT\n",
            "label": "curl · retained exact creation",
            "language": "bash"
          },
          {
            "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nresult=client.chat.completions.create(model=\"claude-sonnet-4-5-20250929-thinking\", messages=[{\"role\":\"user\",\"content\":\"hello\"}], stream=False)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n        ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n        file = Path(stem + \"-\" + label + \".\" + ext)\n        file.write_bytes(raw)\n        print(\"Saved\", file)\n    for index, block in enumerate(data.get(\"content\") or []):\n        print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get(\"choices\") or []:\n        print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get(\"output\") or []):\n        print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n        if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n            save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n    for ci, candidate in enumerate(data.get(\"candidates\") or []):\n        for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n            print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n            if blob and blob.get(\"data\"):\n                mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n                suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n                save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(result.to_dict(mode=\"json\"))\n",
            "label": "Python SDK · all choices",
            "language": "python"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "chat",
        "hints": [
          "Send exact model ID with messages.",
          "Context length is not an output cap.",
          "A text file may supply literal text; image/audio/file-object inputs need exact binding."
        ],
        "http": "POST",
        "in": 6,
        "input": [
          "text"
        ],
        "label": "OpenAI Chat",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [
          "/chat/completions"
        ],
        "out": 30,
        "output": [
          "text"
        ],
        "path": "/v1/chat/completions",
        "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": "token",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0.006000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000006",
                "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": "0.03000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00003",
                "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": "0.0006000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
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