{
  "aboutHtml": "<p>Gambaran keseluruhan: penerangan terperinci tentang bunyi</p><p>Qwen3-Omni-30B-A3B-Captioner ialah model penerangan audio khusus yang ditala halus daripada Qwen3-Omni-30B-A3B-Instruct. Ia menukar klip audio kepada huraian teks terperinci tentang perkara yang didengar. Qwen mereka bentuknya untuk bahan yang pelbagai, termasuk pertuturan, bunyi persekitaran, muzik, kesan sinematik dan campuran beberapa sumber bunyi. Ini menjadikannya berguna untuk menyediakan penerangan aset audio yang boleh dicari atau menilai lapisan bunyi dalam segmen media pendek.</p><p>Pemahaman pertuturan dan bunyi bukan pertuturan</p><p>Pembuat menerangkan analisis berbilang penutur, ungkapan berbilang bahasa, emosi suara dan niat yang dibayangkan oleh cara penyampaian. Contohnya melampaui transkrip: ia menerangkan bunyi suara, bahasa pertuturan dan suasana akustik sekeliling. Bagi audio bukan pertuturan, model menerangkan suasana persekitaran, bunyi dunia sebenar, lapisan muzik dan butiran dinamik dalam filem atau media.</p><p>Penerangan suasana hati, niat penutur atau konteks budaya ialah tafsiran bahan yang dapat didengar. Nilainya secara berasingan daripada pertuturan dan peristiwa bunyi yang boleh diperiksa secara langsung. Kapsyen boleh membantu penilai menyedari perubahan nada atau lapisan latar; ia bukan ukuran emosi peribadi seseorang atau bukti sumber fizikal bunyi yang samar.</p><p>Edisi Captioner dan kontrak inputnya</p><p>Checkpoint ini menggunakan satu giliran sahaja. Ia menerima tepat satu input audio bagi setiap inferens, tanpa prom teks, dan mengembalikan teks sahaja. Ia mengandungi komponen thinker untuk memahami audio; konfigurasi yang diterbitkan mematikan output audio secara jelas. Jangan pindahkan ciri perbualan, imej, video atau penjanaan pertuturan edisi Qwen3-Omni lain kepada Captioner hanya kerana namanya berkongsi keluarga yang sama.</p><p>Ketiadaan prom teks penting dalam amalan. Sediakan segmen audio yang mahu diterangkan dan hantar segmen itu sebagai keseluruhan tugas. Jangan tambah arahan untuk ringkasan tersuai, terjemahan, jawapan kepada penutur atau skema output. Jika aliran kerja memerlukan transformasi tersebut, ia tergolong dalam peringkat berasingan yang memproses penerangan yang dikembalikan, bukannya dianggap sebagai kawalan checkpoint penghasilan kapsyen ini.</p><p>Menyediakan audio yang berguna</p><p>Qwen mengesyorkan klip tidak melebihi 30 saat untuk penerangan terperinci. Ini ialah syor kualiti: audio yang terlalu panjang boleh mengurangkan persepsi butiran. Ia tidak dikemukakan sebagai ambang penolakan keras sejagat. Bagi rakaman lebih panjang, pilih segmen pendek yang bermakna sekitar peristiwa atau adegan yang dinilai. Simpan pengecam sumber dan masa mula di luar permintaan model supaya kapsyen yang dikembalikan dapat dikesan semula kepada rakaman asal kemudian.</p><p>Kekalkan lapisan bunyi yang relevan dengan soalan. Petikan berfokuskan suara masih seharusnya merangkumi latar apabila latar itu mempengaruhi penerangan yang dikehendaki; aset muzik atau kesan bunyi seharusnya mengekalkan peralihan pentingnya dan bukan dipotong pada sempadan sembarangan. Memproses klip secara berasingan membantu mengekalkan butiran setempat, tetapi tidak membuktikan kesinambungan automatik atau pemahaman seluruh rakaman merentas permintaan.</p><p>Kegunaan hasil teks</p><p>Panduan praktikal pembuat menunjukkan kapsyen yang menerangkan kandungan dan cara penyampaian pertuturan, kemudian adegan sekeliling; contoh lain menerangkan muzik, kesan, perubahan keamatan dan urutan peristiwa suara. Katalog audio boleh menyimpan teks yang dikembalikan bersama nama aset dan julat masa. Penilai media boleh menggunakannya sebagai draf log bunyi. Penyunting boleh membandingkan kapsyen dengan klip untuk mengenal pasti sama ada penerangan menangkap lapisan yang dikehendaki. Ini ialah contoh aplikasi, bukan bukti bahawa model telah mendengar mana-mana aset pengguna tertentu terlebih dahulu.</p><p>Output ialah kapsyen deskriptif, bukan janji transkrip kata demi kata, jadual pemisahan penutur, fail sari kata bercap masa atau runut bunyi terjana. Apabila kata-kata tepat yang dituturkan atau masa diperlukan, semak kapsyen berdasarkan audio dan gunakan aliran kerja khusus yang sesuai untuk artifak yang diperlukan. Penerangan yang kaya boleh merangkumi maklumat adegan atau genre yang disimpulkan, jadi kekalkan ketidakpastian apabila bunyi itu sendiri tidak mengenal pasti sumber secara jelas.</p><p>Contoh penjanaan dan had</p><p>Contoh kendiri pembuat menetapkan konteks model 32,768 token dan peruntukan penjanaan 16,384 token, dengan temperature 0.6, top_p 0.95 dan top_k 20. Panduan praktikalnya menggunakan peruntukan penjanaan 8,192 token dengan nilai pensampelan yang sama. Ini ialah konfigurasi contoh, bukan panjang kapsyen maksimum yang diisytiharkan secara berasingan. Konfigurasi teks asas menyenaraikan 65,536 kedudukan, yang tidak seharusnya ditukar menjadi jaminan tempoh audio.</p><p>Kod utiliti umum atau medan konfigurasi yang dikongsi dengan keluarga Omni tidak mengatasi kontrak jelas Captioner: satu audio, tiada teks input dan teks sahaja sebagai output. Hasil yang berguna ialah penerangan terperinci bagi adegan bunyi pendek; semak petikan pertuturan, bilangan penutur dan sumber bunyi yang disimpulkan sebelum menggunakannya sebagai rekod berwibawa.</p>",
  "aboutText": "Gambaran keseluruhan: penerangan terperinci tentang bunyi\n\nQwen3-Omni-30B-A3B-Captioner ialah model penerangan audio khusus yang ditala halus daripada Qwen3-Omni-30B-A3B-Instruct. Ia menukar klip audio kepada huraian teks terperinci tentang perkara yang didengar. Qwen mereka bentuknya untuk bahan yang pelbagai, termasuk pertuturan, bunyi persekitaran, muzik, kesan sinematik dan campuran beberapa sumber bunyi. Ini menjadikannya berguna untuk menyediakan penerangan aset audio yang boleh dicari atau menilai lapisan bunyi dalam segmen media pendek.\n\nPemahaman pertuturan dan bunyi bukan pertuturan\n\nPembuat menerangkan analisis berbilang penutur, ungkapan berbilang bahasa, emosi suara dan niat yang dibayangkan oleh cara penyampaian. Contohnya melampaui transkrip: ia menerangkan bunyi suara, bahasa pertuturan dan suasana akustik sekeliling. Bagi audio bukan pertuturan, model menerangkan suasana persekitaran, bunyi dunia sebenar, lapisan muzik dan butiran dinamik dalam filem atau media.\n\nPenerangan suasana hati, niat penutur atau konteks budaya ialah tafsiran bahan yang dapat didengar. Nilainya secara berasingan daripada pertuturan dan peristiwa bunyi yang boleh diperiksa secara langsung. Kapsyen boleh membantu penilai menyedari perubahan nada atau lapisan latar; ia bukan ukuran emosi peribadi seseorang atau bukti sumber fizikal bunyi yang samar.\n\nEdisi Captioner dan kontrak inputnya\n\nCheckpoint ini menggunakan satu giliran sahaja. Ia menerima tepat satu input audio bagi setiap inferens, tanpa prom teks, dan mengembalikan teks sahaja. Ia mengandungi komponen thinker untuk memahami audio; konfigurasi yang diterbitkan mematikan output audio secara jelas. Jangan pindahkan ciri perbualan, imej, video atau penjanaan pertuturan edisi Qwen3-Omni lain kepada Captioner hanya kerana namanya berkongsi keluarga yang sama.\n\nKetiadaan prom teks penting dalam amalan. Sediakan segmen audio yang mahu diterangkan dan hantar segmen itu sebagai keseluruhan tugas. Jangan tambah arahan untuk ringkasan tersuai, terjemahan, jawapan kepada penutur atau skema output. Jika aliran kerja memerlukan transformasi tersebut, ia tergolong dalam peringkat berasingan yang memproses penerangan yang dikembalikan, bukannya dianggap sebagai kawalan checkpoint penghasilan kapsyen ini.\n\nMenyediakan audio yang berguna\n\nQwen mengesyorkan klip tidak melebihi 30 saat untuk penerangan terperinci. Ini ialah syor kualiti: audio yang terlalu panjang boleh mengurangkan persepsi butiran. Ia tidak dikemukakan sebagai ambang penolakan keras sejagat. Bagi rakaman lebih panjang, pilih segmen pendek yang bermakna sekitar peristiwa atau adegan yang dinilai. Simpan pengecam sumber dan masa mula di luar permintaan model supaya kapsyen yang dikembalikan dapat dikesan semula kepada rakaman asal kemudian.\n\nKekalkan lapisan bunyi yang relevan dengan soalan. Petikan berfokuskan suara masih seharusnya merangkumi latar apabila latar itu mempengaruhi penerangan yang dikehendaki; aset muzik atau kesan bunyi seharusnya mengekalkan peralihan pentingnya dan bukan dipotong pada sempadan sembarangan. Memproses klip secara berasingan membantu mengekalkan butiran setempat, tetapi tidak membuktikan kesinambungan automatik atau pemahaman seluruh rakaman merentas permintaan.\n\nKegunaan hasil teks\n\nPanduan praktikal pembuat menunjukkan kapsyen yang menerangkan kandungan dan cara penyampaian pertuturan, kemudian adegan sekeliling; contoh lain menerangkan muzik, kesan, perubahan keamatan dan urutan peristiwa suara. Katalog audio boleh menyimpan teks yang dikembalikan bersama nama aset dan julat masa. Penilai media boleh menggunakannya sebagai draf log bunyi. Penyunting boleh membandingkan kapsyen dengan klip untuk mengenal pasti sama ada penerangan menangkap lapisan yang dikehendaki. Ini ialah contoh aplikasi, bukan bukti bahawa model telah mendengar mana-mana aset pengguna tertentu terlebih dahulu.\n\nOutput ialah kapsyen deskriptif, bukan janji transkrip kata demi kata, jadual pemisahan penutur, fail sari kata bercap masa atau runut bunyi terjana. Apabila kata-kata tepat yang dituturkan atau masa diperlukan, semak kapsyen berdasarkan audio dan gunakan aliran kerja khusus yang sesuai untuk artifak yang diperlukan. Penerangan yang kaya boleh merangkumi maklumat adegan atau genre yang disimpulkan, jadi kekalkan ketidakpastian apabila bunyi itu sendiri tidak mengenal pasti sumber secara jelas.\n\nContoh penjanaan dan had\n\nContoh kendiri pembuat menetapkan konteks model 32,768 token dan peruntukan penjanaan 16,384 token, dengan temperature 0.6, top_p 0.95 dan top_k 20. Panduan praktikalnya menggunakan peruntukan penjanaan 8,192 token dengan nilai pensampelan yang sama. Ini ialah konfigurasi contoh, bukan panjang kapsyen maksimum yang diisytiharkan secara berasingan. Konfigurasi teks asas menyenaraikan 65,536 kedudukan, yang tidak seharusnya ditukar menjadi jaminan tempoh audio.\n\nKod utiliti umum atau medan konfigurasi yang dikongsi dengan keluarga Omni tidak mengatasi kontrak jelas Captioner: satu audio, tiada teks input dan teks sahaja sebagai output. Hasil yang berguna ialah penerangan terperinci bagi adegan bunyi pendek; semak petikan pertuturan, bilangan penutur dan sumber bunyi yang disimpulkan sebelum menggunakannya sebagai rekod berwibawa.",
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      "practical_html": "<h3>Tugas praktikal</h3><p>Penerangan model memerlukan input audio, tetapi laluan yang dipilih menyatakan input teks. Contoh penjanaan sedia dijalankan tidak disediakan untuk ketidakpadanan ini.</p><p>Contoh teknikal dalam bahasa Inggeris</p><pre><code>Describe one short audio asset\n\nManufacturer workflow only: select one short audio clip whose sound layers need a description. Submit exactly that audio input with no text prompt through the documented manufacturer workflow. Keep the asset identifier outside the request. The selected Ailoot text-only route does not provide this audio-input workflow.</code></pre><h4>Hasil yang dijangka</h4><pre><code>A detailed text caption covering audible speech, background sounds, music and event order when present, with uncertain sound sources or intentions kept distinct from direct audible observations.</code></pre><h4>Semak hasil</h4><pre><code>Compare the caption with the same clip for sound sequence and sources; reconcile the Ailoot text-input mismatch before use. Do not send this preparation note as a text prompt.</code></pre>"
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">Al</span><h2 id=\"sheet-title\">Qwen3 Omni 30B A3B Captioner</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"Tutup\">×</button></div><div class=\"idline\"><span>Alibaba /</span><code>Qwen/Qwen3-Omni-30B-A3B-Captioner</code><button type=\"button\" id=\"copy-id\">Salin ID</button></div><nav class=\"card-jump-nav\" aria-label=\"Bahagian kad model\"><button type=\"button\" data-card-jump=\"overview\">Pengenalan</button><button type=\"button\" data-card-jump=\"methods\">Input &amp; kaedah</button><button type=\"button\" data-card-jump=\"pricing\">Pelan harga</button><button type=\"button\" data-card-jump=\"examples\">Contoh</button><button type=\"button\" data-card-jump=\"results\">Hasil</button><button type=\"button\" data-card-jump=\"aliases\">Alias</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"Kaedah API\"><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|Qwen%2FQwen3-Omni-30B-A3B-Captioner\">Chat</button><button type=\"button\" role=\"tab\" tabindex=\"-1\" aria-controls=\"card-method-content\" aria-selected=\"false\" id=\"card-method-tab-1\" data-card-method=\"Ultra|messages|/v1/messages|Qwen%2FQwen3-Omni-30B-A3B-Captioner\">Messages</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\">Pengenalan</h3><p class=\"mdesc-full\">Qwen3-Omni-30B-A3B-Captioner menerangkan pertuturan, muzik, bunyi persekitaran dan audio sinematik sebagai teks. Edisi satu giliran khusus ini menerima satu input audio tanpa prom teks; Qwen mengesyorkan klip tidak melebihi 30 saat untuk mengekalkan butiran halus.</p><dl class=\"card-io\" data-card-io><div><dt>Input yang diterima</dt><dd>Teks</dd></div><div><dt>Hasil</dt><dd>Teks</dd></div></dl><details class=\"card-about\"><summary>Tentang model</summary><p class=\"note-s\" data-model-method-boundary>Huraian ini merangkumi keupayaan model. Input, output dan pilihan yang tersedia di Ailoot disenaraikan di bawah untuk kaedah yang dipilih.</p><div class=\"mabout\" id=\"m-about\"><p>Gambaran keseluruhan: penerangan terperinci tentang bunyi</p><p>Qwen3-Omni-30B-A3B-Captioner ialah model penerangan audio khusus yang ditala halus daripada Qwen3-Omni-30B-A3B-Instruct. Ia menukar klip audio kepada huraian teks terperinci tentang perkara yang didengar. Qwen mereka bentuknya untuk bahan yang pelbagai, termasuk pertuturan, bunyi persekitaran, muzik, kesan sinematik dan campuran beberapa sumber bunyi. Ini menjadikannya berguna untuk menyediakan penerangan aset audio yang boleh dicari atau menilai lapisan bunyi dalam segmen media pendek.</p><p>Pemahaman pertuturan dan bunyi bukan pertuturan</p><p>Pembuat menerangkan analisis berbilang penutur, ungkapan berbilang bahasa, emosi suara dan niat yang dibayangkan oleh cara penyampaian. Contohnya melampaui transkrip: ia menerangkan bunyi suara, bahasa pertuturan dan suasana akustik sekeliling. Bagi audio bukan pertuturan, model menerangkan suasana persekitaran, bunyi dunia sebenar, lapisan muzik dan butiran dinamik dalam filem atau media.</p><p>Penerangan suasana hati, niat penutur atau konteks budaya ialah tafsiran bahan yang dapat didengar. Nilainya secara berasingan daripada pertuturan dan peristiwa bunyi yang boleh diperiksa secara langsung. Kapsyen boleh membantu penilai menyedari perubahan nada atau lapisan latar; ia bukan ukuran emosi peribadi seseorang atau bukti sumber fizikal bunyi yang samar.</p><p>Edisi Captioner dan kontrak inputnya</p><p>Checkpoint ini menggunakan satu giliran sahaja. Ia menerima tepat satu input audio bagi setiap inferens, tanpa prom teks, dan mengembalikan teks sahaja. Ia mengandungi komponen thinker untuk memahami audio; konfigurasi yang diterbitkan mematikan output audio secara jelas. Jangan pindahkan ciri perbualan, imej, video atau penjanaan pertuturan edisi Qwen3-Omni lain kepada Captioner hanya kerana namanya berkongsi keluarga yang sama.</p><p>Ketiadaan prom teks penting dalam amalan. Sediakan segmen audio yang mahu diterangkan dan hantar segmen itu sebagai keseluruhan tugas. Jangan tambah arahan untuk ringkasan tersuai, terjemahan, jawapan kepada penutur atau skema output. Jika aliran kerja memerlukan transformasi tersebut, ia tergolong dalam peringkat berasingan yang memproses penerangan yang dikembalikan, bukannya dianggap sebagai kawalan checkpoint penghasilan kapsyen ini.</p><p>Menyediakan audio yang berguna</p><p>Qwen mengesyorkan klip tidak melebihi 30 saat untuk penerangan terperinci. Ini ialah syor kualiti: audio yang terlalu panjang boleh mengurangkan persepsi butiran. Ia tidak dikemukakan sebagai ambang penolakan keras sejagat. Bagi rakaman lebih panjang, pilih segmen pendek yang bermakna sekitar peristiwa atau adegan yang dinilai. Simpan pengecam sumber dan masa mula di luar permintaan model supaya kapsyen yang dikembalikan dapat dikesan semula kepada rakaman asal kemudian.</p><p>Kekalkan lapisan bunyi yang relevan dengan soalan. Petikan berfokuskan suara masih seharusnya merangkumi latar apabila latar itu mempengaruhi penerangan yang dikehendaki; aset muzik atau kesan bunyi seharusnya mengekalkan peralihan pentingnya dan bukan dipotong pada sempadan sembarangan. Memproses klip secara berasingan membantu mengekalkan butiran setempat, tetapi tidak membuktikan kesinambungan automatik atau pemahaman seluruh rakaman merentas permintaan.</p><p>Kegunaan hasil teks</p><p>Panduan praktikal pembuat menunjukkan kapsyen yang menerangkan kandungan dan cara penyampaian pertuturan, kemudian adegan sekeliling; contoh lain menerangkan muzik, kesan, perubahan keamatan dan urutan peristiwa suara. Katalog audio boleh menyimpan teks yang dikembalikan bersama nama aset dan julat masa. Penilai media boleh menggunakannya sebagai draf log bunyi. Penyunting boleh membandingkan kapsyen dengan klip untuk mengenal pasti sama ada penerangan menangkap lapisan yang dikehendaki. Ini ialah contoh aplikasi, bukan bukti bahawa model telah mendengar mana-mana aset pengguna tertentu terlebih dahulu.</p><p>Output ialah kapsyen deskriptif, bukan janji transkrip kata demi kata, jadual pemisahan penutur, fail sari kata bercap masa atau runut bunyi terjana. Apabila kata-kata tepat yang dituturkan atau masa diperlukan, semak kapsyen berdasarkan audio dan gunakan aliran kerja khusus yang sesuai untuk artifak yang diperlukan. Penerangan yang kaya boleh merangkumi maklumat adegan atau genre yang disimpulkan, jadi kekalkan ketidakpastian apabila bunyi itu sendiri tidak mengenal pasti sumber secara jelas.</p><p>Contoh penjanaan dan had</p><p>Contoh kendiri pembuat menetapkan konteks model 32,768 token dan peruntukan penjanaan 16,384 token, dengan temperature 0.6, top_p 0.95 dan top_k 20. Panduan praktikalnya menggunakan peruntukan penjanaan 8,192 token dengan nilai pensampelan yang sama. Ini ialah konfigurasi contoh, bukan panjang kapsyen maksimum yang diisytiharkan secara berasingan. Konfigurasi teks asas menyenaraikan 65,536 kedudukan, yang tidak seharusnya ditukar menjadi jaminan tempoh audio.</p><p>Kod utiliti umum atau medan konfigurasi yang dikongsi dengan keluarga Omni tidak mengatasi kontrak jelas Captioner: satu audio, tiada teks input dan teks sahaja sebagai output. Hasil yang berguna ialah penerangan terperinci bagi adegan bunyi pendek; semak petikan pertuturan, bilangan penutur dan sumber bunyi yang disimpulkan sebelum menggunakannya sebagai rekod berwibawa.</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Tersedia di Ailoot · input &amp; kaedah</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>Input</dt><dd><code>text</code></dd></div><div><dt>Output</dt><dd><code>text</code></dd></div><div><dt>Format output</dt><dd>json atau SSE</dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>Medan</th><th>Jenis</th><th>Keperluan</th><th>Nilai &amp; had</th><th>Lalai</th></tr></thead><tbody><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Qwen/Qwen3-Omni-30B-A3B-Captioner</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">messages</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>message[]</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Item minimum: 1</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">messages[].role</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Contoh: system, user, assistant, tool, function</div><div>Syarat: Peranan ini diwakili secara eksplisit oleh jenis keserasian dalam kod sumber; set peranan model yang tepat kekal khusus untuk setiap model.</div><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">messages[].content</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string|content_part[]|null</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">messages[].tool_calls</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>tool_call[]</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">messages[].tool_call_id</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Terpakai apabila: role=tool; gunakan ID sebenar yang dipulangkan</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">messages[].name</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">messages[].reasoning_content</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Terpakai apabila: Hantar semula penaakulan sebenar yang dipulangkan apabila model ini menggunakannya</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">messages[].reasoning_details</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>object|array</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">max_tokens</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>integer</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Minimum: 1</div><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">max_completion_tokens</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>integer</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Minimum: 1</div><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">stream</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>boolean</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"known\"><span class=\"card-cell-label\">Lalai</span>false</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">stream_options.include_usage</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>boolean</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">temperature</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>number</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">top_p</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>number</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">stop</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string|string[]</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">tools</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>function_tool[]</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">tools[].type</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>function</div><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">tools[].function.name</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Terpakai apabila: alat fungsi dibekalkan</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">tools[].function.description</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">tools[].function.parameters</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>JSON_schema</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">tool_choice</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string|object</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">parallel_tool_calls</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>boolean</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">response_format</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>object</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">reasoning_effort</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">reasoning</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>object</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">service_tier</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_compatibility\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">instructions</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Medan keserasian</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">functions</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>function[]</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">function_call</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string|object</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">prompt_cache_options</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>object</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div class=\"note-s\">Bergantung pada model</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">modalities</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string[]</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>text</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">provider</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>object</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Syarat: provider.options ditolak pada laluan teks Ultra ini</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">cache_control.ttl</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Syarat: 1h ditolak pada lokasi cache prompt yang digunakan</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr></tbody></table></div><details class=\"card-about\" data-material-combinations><summary>Gabungan bahan input</summary><p class=\"note-s\"><b>Teks</b> · Teks UTF8</p><p class=\"note-s\"><code>messages[].content</code></p></details><details class=\"note-s\" data-method-contract><summary>Parameter kaedah dan kitar hayat</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>Parameter</th><th>Kontrak</th></tr></thead><tbody><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>content_type</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>application/json</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>required</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>model, messages</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>material_types</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>text</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>messages</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>tatasusunan mesej dengan struktur role/content</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>file_material</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>dokumen UTF-8 sebenar dimasukkan sebagai teks literal; ID fail tidak diandaikan</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>optional_controls</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>stream, temperature, top_p, stop, max_tokens, max_completion_tokens, reasoning, response_format, tools, tool_choice</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>control_scope</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>khusus model; alat fungsi pengguna berbeza daripada alat yang dihoskan</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>output_modalities</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>text</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>hosted_operations</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>false</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>multimodal_input_binding</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>null</td></tr></tbody></table></div><p>Kitar hayat: <code>synchronous_or_streamed</code></p><p class=\"note-s\">Hantar ID model yang tepat bersama messages.</p><p class=\"note-s\">Panjang konteks bukan had output.</p><p class=\"note-s\">Fail teks boleh membekalkan teks literal; input imej/audio/objek fail memerlukan pengikatan tepat.</p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">Pelan harga</h3><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>Rujukan tarif tidak menambah pilihan permintaan. Parameter yang disokong disenaraikan untuk kaedah yang dipilih.</p><dl data-price-conditions><dt>Mod pantas</dt><dd>Tidak dinyatakan <span class=\"note-s\">Apabila mod pantas dipilih</span></dd><dt>Mod flex</dt><dd>Tidak dinyatakan <span class=\"note-s\">Apabila mod flex dipilih</span></dd><dt>Usaha penaakulan maksimum</dt><dd>Tidak dinyatakan <span class=\"note-s\">Apabila usaha penaakulan maksimum menggunakan pelarasan default</span></dd></dl></div><div data-declared-tariff-pricing><h4>Kadar Ailoot</h4><h4>Harga mengikut konfigurasi</h4><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Konfigurasi</th><th>Jadual kadar</th><th>Caj</th></tr></thead><tbody><tr><th data-cell-label=\"Konfigurasi\" scope=\"row\"><span class=\"card-cell-label\">Konfigurasi</span>Kadar asas token</th><td data-cell-label=\"Jadual kadar\"><span class=\"card-cell-label\">Jadual kadar</span>Kadar asas</td><td data-cell-label=\"Caj\"><span class=\"card-cell-label\">Caj</span><div><span>Input · Token input</span> <b>$0.0002</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Output · Token output</span> <b>$0.0008</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Bacaan cache</span> <b>$0</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Penulisan cache</span> <b>$0</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Penulisan cache, 1 jam</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot merizabkan anggaran amaun sebelum permintaan. Selepas hasil diterima, caj akhir diselesaikan berdasarkan penggunaan terukur. Penyelesaian caj penstriman menggunakan rekod penggunaan akhir. <a href=\"/docs/ms/billing/reserve/\">Cara rizab dan penyelesaian caj berfungsi →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">Contoh permintaan</h3><p class=\"note-s\" data-native-input-conflict=\"audio-text\">Penerangan model memerlukan input audio, tetapi laluan yang dipilih menyatakan input teks. Contoh penjanaan sedia dijalankan tidak disediakan untuk ketidakpadanan ini.</p><p><code>manufacturer: audio → text</code></p><p><code>route: text → text</code></p></section><section class=\"card-section\" data-card-section=\"results\"><h3 tabindex=\"-1\">Terima dan simpan hasil</h3><h4>Ailoot Ultra · OpenAI Chat</h4><p class=\"note-s\">json atau SSE</p><div class=\"card-result-process\" data-all-results><h5>Simpan semua hasil yang selesai</h5><p class=\"note-s\">Simpan setiap respons lengkap, fail dan bahagian kandungan yang dikembalikan.</p><p class=\"note-s\">Kekalkan setiap pilihan jawapan bersama kandungan, panggilan alat dan penaakulannya. Dalam SSE, gabungkan delta mengikut indeks pilihan jawapan/alat dan kekalkan sebab penamatan akhir serta data penggunaan.</p></div><div class=\"card-result-process\" data-unknown-recovery><h5>Jika respons asal perlu disemak</h5><p class=\"note-s\">Kekalkan ID permintaan/respons dan pengepala. Tiada URL umum bagi pengambilan tugas teks dibekalkan.</p></div><details class=\"card-about\" data-output-fields><summary>Medan respons</summary><div class=\"tw\" data-card-table=\"output\"><table><thead><tr><th>Medan</th><th>Jenis</th></tr></thead><tbody><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">choices[].index</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>integer</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">choices[].message.content</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>string|null</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">choices[].message.tool_calls</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>tool_call[]</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">choices[].message.reasoning_content</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>string</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">choices[].message.reasoning_details</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>object|array</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">choices[].finish_reason</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>string|null</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">usage</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>object</td></tr></tbody></table></div></details><details class=\"card-about\" data-method-errors><summary>Ralat dan langkah seterusnya</summary><div class=\"tw\" data-card-table=\"errors\"><table><thead><tr><th>Respons</th><th>Syarat</th><th>Langkah seterusnya</th></tr></thead><tbody><tr><th data-cell-label=\"Respons\" scope=\"row\"><span class=\"card-cell-label\">Respons</span>400 · <code>invalid_request_error</code></th><td data-cell-label=\"Syarat\"><span class=\"card-cell-label\">Syarat</span>Medan wajib, perwakilan bahan atau nilai parameter tidak sah</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Betulkan medan yang ditunjukkan sebelum permintaan penciptaan baharu.</td></tr></tbody></table></div></details></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">Alias</h3><h4>Alias model</h4><p class=\"note-s\"><span data-model-alias-route=\"Ultra\"><b>Ailoot Ultra</b> <a href=\"#m=Qwen%2FQwen3-Omni-30B-A3B-Captioner&amp;route=Ultra&amp;caller=Qwen%2FQwen3-Omni-30B-A3B-Captioner&amp;fmt=chat\"><code>Qwen/Qwen3-Omni-30B-A3B-Captioner</code></a></span></p><h4>Alias laluan kaedah</h4><p class=\"note-s\">Gunakan laluan kaedah yang dipaparkan di atas.</p><h4>ID pemanggil berkaitan</h4><p class=\"note-s\"><a href=\"#m=Qwen%2FQwen3-Omni-30B-A3B-Captioner&amp;route=Ultra&amp;caller=Qwen%2FQwen3-Omni-30B-A3B-Captioner&amp;fmt=chat\"><code>Qwen/Qwen3-Omni-30B-A3B-Captioner</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
        "fmt": "chat",
        "http": "POST",
        "path": "/v1/chat/completions",
        "request_model_id": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|chat|/v1/chat/completions|Qwen%2FQwen3-Omni-30B-A3B-Captioner",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "cache_read": 0,
        "cache_write": 0,
        "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": "Medan wajib, perwakilan bahan atau nilai parameter tidak sah",
                "http_status": 400,
                "recovery": "Betulkan medan yang ditunjukkan sebelum permintaan penciptaan baharu.",
                "type": "invalid_request_error"
              }
            ],
            "hints": [
              "Model context is not an output cap.",
              "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.",
              "Tool calls propose actions; the client application returns actual observations with the returned call ID.",
              "Guarded canonical keys must occur once; duplicate or case-varied model/tools/cap fields are rejected."
            ],
            "ignored_fields": [],
            "lifecycle": {
              "create": {
                "http": "POST",
                "path": "/v1/chat/completions"
              },
              "job_read": null,
              "mode": "synchronous_or_streamed",
              "unknown": "Kekalkan ID permintaan/respons dan pengepala. Tiada URL umum bagi pengambilan tugas teks dibekalkan."
            },
            "material_combinations": [
              {
                "mode": "text",
                "representation": "messages[].content",
                "required_material": "Teks UTF8"
              }
            ],
            "operation_modes": [
              "conversation",
              "function_tool_continuation",
              "streaming"
            ],
            "outputs": {
              "all_results": "Kekalkan setiap pilihan jawapan bersama kandungan, panggilan alat dan penaakulannya. Dalam SSE, gabungkan delta mengikut indeks pilihan jawapan/alat dan kekalkan sebab penamatan akhir serta data penggunaan.",
              "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 atau SSE"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "Qwen/Qwen3-Omni-30B-A3B-Captioner"
                ],
                "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",
                "conditions": "Peranan ini diwakili secara eksplisit oleh jenis keserasian dalam kod sumber; set peranan model yang tepat kekal khusus untuk setiap model.",
                "default": null,
                "default_known": false,
                "enum": [
                  "system",
                  "user",
                  "assistant",
                  "tool",
                  "function"
                ],
                "enum_exhaustive": false,
                "enum_known": true,
                "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|content_part[]|null"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].tool_calls",
                "required": false,
                "type": "tool_call[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].tool_call_id",
                "required": false,
                "type": "string",
                "when": "role=tool; gunakan ID sebenar yang dipulangkan"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].name",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].reasoning_content",
                "required": false,
                "type": "string",
                "when": "Hantar semula penaakulan sebenar yang dipulangkan apabila model ini menggunakannya"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].reasoning_details",
                "required": false,
                "type": "object|array"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "minimum": 1,
                "name": "max_tokens",
                "required": false,
                "type": "integer"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "minimum": 1,
                "name": "max_completion_tokens",
                "required": false,
                "type": "integer"
              },
              {
                "availability": "source_interface",
                "default": false,
                "default_known": true,
                "enum": null,
                "enum_known": false,
                "name": "stream",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "stream_options.include_usage",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "temperature",
                "required": false,
                "type": "number"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "top_p",
                "required": false,
                "type": "number"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "stop",
                "required": false,
                "type": "string|string[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools",
                "required": false,
                "type": "function_tool[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": [
                  "function"
                ],
                "enum_known": true,
                "name": "tools[].type",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.name",
                "required": true,
                "type": "string",
                "when": "alat fungsi dibekalkan"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.description",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.parameters",
                "required": false,
                "type": "JSON_schema"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tool_choice",
                "required": false,
                "type": "string|object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "parallel_tool_calls",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "response_format",
                "required": false,
                "type": "object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "reasoning_effort",
                "required": false,
                "type": "string"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "reasoning",
                "required": false,
                "type": "object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "service_tier",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_compatibility",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "instructions",
                "required": false,
                "type": "string"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "functions",
                "required": false,
                "type": "function[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "function_call",
                "required": false,
                "type": "string|object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "prompt_cache_options",
                "required": false,
                "type": "object"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "text"
                ],
                "enum_known": true,
                "name": "modalities",
                "required": false,
                "type": "string[]"
              },
              {
                "availability": "source_interface",
                "conditions": "provider.options ditolak pada laluan teks Ultra ini",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "provider",
                "required": false,
                "type": "object"
              },
              {
                "availability": "source_interface",
                "conditions": "1h ditolak pada lokasi cache prompt yang digunakan",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "cache_control.ttl",
                "required": false,
                "type": "string"
              }
            ],
            "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.",
            "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": [
            "Hantar ID model yang tepat bersama messages.",
            "Panjang konteks bukan had output.",
            "Fail teks boleh membekalkan teks literal; input imej/audio/objek fail memerlukan pengikatan tepat."
          ],
          "input": {
            "content_type": "application/json",
            "control_scope": "khusus model; alat fungsi pengguna berbeza daripada alat yang dihoskan",
            "file_material": "dokumen UTF-8 sebenar dimasukkan sebagai teks literal; ID fail tidak diandaikan",
            "hosted_operations": false,
            "material_types": [
              "text"
            ],
            "messages": "tatasusunan mesej dengan struktur role/content",
            "multimodal_input_binding": null,
            "optional_controls": [
              "stream",
              "temperature",
              "top_p",
              "stop",
              "max_tokens",
              "max_completion_tokens",
              "reasoning",
              "response_format",
              "tools",
              "tool_choice"
            ],
            "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": [],
          "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": "Kadar asas token",
            "units": [
              {
                "amount": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000002",
                "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": "0.0008000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000008",
                "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",
                "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",
                "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",
                "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",
                "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\": \"Qwen/Qwen3-Omni-30B-A3B-Captioner\", \"messages\": [{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}]}')\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='Qwen/Qwen3-Omni-30B-A3B-Captioner',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}])\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"
          },
          {
            "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\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)\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\nwith client.chat.completions.stream(model='Qwen/Qwen3-Omni-30B-A3B-Captioner',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n    with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n        for event in stream:\n            payload=event.to_dict(mode=\"json\")\n            log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_completion()\n    save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n",
            "label": "Python SDK streaming · all events",
            "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": 0.2,
        "input": [
          "text"
        ],
        "label": "OpenAI Chat",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "out": 0.8,
        "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000002",
                "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": "0.0008000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000008",
                "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",
                "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",
                "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",
                "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",
                "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": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": "0.0002000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.0000002",
            "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": "0.0008000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.0000008",
            "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",
            "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",
            "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",
            "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",
            "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"
          }
        ]
      }
    },
    {
      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">Al</span><h2 id=\"sheet-title\">Qwen3 Omni 30B A3B Captioner</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"Tutup\">×</button></div><div class=\"idline\"><span>Alibaba /</span><code>Qwen/Qwen3-Omni-30B-A3B-Captioner</code><button type=\"button\" id=\"copy-id\">Salin ID</button></div><nav class=\"card-jump-nav\" aria-label=\"Bahagian kad model\"><button type=\"button\" data-card-jump=\"overview\">Pengenalan</button><button type=\"button\" data-card-jump=\"methods\">Input &amp; kaedah</button><button type=\"button\" data-card-jump=\"pricing\">Pelan harga</button><button type=\"button\" data-card-jump=\"examples\">Contoh</button><button type=\"button\" data-card-jump=\"results\">Hasil</button><button type=\"button\" data-card-jump=\"aliases\">Alias</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"Kaedah API\"><button type=\"button\" role=\"tab\" tabindex=\"-1\" aria-controls=\"card-method-content\" aria-selected=\"false\" id=\"card-method-tab-0\" data-card-method=\"Ultra|chat|/v1/chat/completions|Qwen%2FQwen3-Omni-30B-A3B-Captioner\">Chat</button><button type=\"button\" role=\"tab\" tabindex=\"0\" aria-controls=\"card-method-content\" aria-selected=\"true\" id=\"card-method-tab-1\" data-card-method=\"Ultra|messages|/v1/messages|Qwen%2FQwen3-Omni-30B-A3B-Captioner\">Messages</button></div><div id=\"card-method-content\" role=\"tabpanel\" aria-labelledby=\"card-method-tab-1\"><section class=\"card-section\" data-card-section=\"overview\"><h3 tabindex=\"-1\">Pengenalan</h3><p class=\"mdesc-full\">Qwen3-Omni-30B-A3B-Captioner menerangkan pertuturan, muzik, bunyi persekitaran dan audio sinematik sebagai teks. Edisi satu giliran khusus ini menerima satu input audio tanpa prom teks; Qwen mengesyorkan klip tidak melebihi 30 saat untuk mengekalkan butiran halus.</p><dl class=\"card-io\" data-card-io><div><dt>Input yang diterima</dt><dd>Teks</dd></div><div><dt>Hasil</dt><dd>json · sse</dd></div></dl><details class=\"card-about\"><summary>Tentang model</summary><p class=\"note-s\" data-model-method-boundary>Huraian ini merangkumi keupayaan model. Input, output dan pilihan yang tersedia di Ailoot disenaraikan di bawah untuk kaedah yang dipilih.</p><div class=\"mabout\" id=\"m-about\"><p>Gambaran keseluruhan: penerangan terperinci tentang bunyi</p><p>Qwen3-Omni-30B-A3B-Captioner ialah model penerangan audio khusus yang ditala halus daripada Qwen3-Omni-30B-A3B-Instruct. Ia menukar klip audio kepada huraian teks terperinci tentang perkara yang didengar. Qwen mereka bentuknya untuk bahan yang pelbagai, termasuk pertuturan, bunyi persekitaran, muzik, kesan sinematik dan campuran beberapa sumber bunyi. Ini menjadikannya berguna untuk menyediakan penerangan aset audio yang boleh dicari atau menilai lapisan bunyi dalam segmen media pendek.</p><p>Pemahaman pertuturan dan bunyi bukan pertuturan</p><p>Pembuat menerangkan analisis berbilang penutur, ungkapan berbilang bahasa, emosi suara dan niat yang dibayangkan oleh cara penyampaian. Contohnya melampaui transkrip: ia menerangkan bunyi suara, bahasa pertuturan dan suasana akustik sekeliling. Bagi audio bukan pertuturan, model menerangkan suasana persekitaran, bunyi dunia sebenar, lapisan muzik dan butiran dinamik dalam filem atau media.</p><p>Penerangan suasana hati, niat penutur atau konteks budaya ialah tafsiran bahan yang dapat didengar. Nilainya secara berasingan daripada pertuturan dan peristiwa bunyi yang boleh diperiksa secara langsung. Kapsyen boleh membantu penilai menyedari perubahan nada atau lapisan latar; ia bukan ukuran emosi peribadi seseorang atau bukti sumber fizikal bunyi yang samar.</p><p>Edisi Captioner dan kontrak inputnya</p><p>Checkpoint ini menggunakan satu giliran sahaja. Ia menerima tepat satu input audio bagi setiap inferens, tanpa prom teks, dan mengembalikan teks sahaja. Ia mengandungi komponen thinker untuk memahami audio; konfigurasi yang diterbitkan mematikan output audio secara jelas. Jangan pindahkan ciri perbualan, imej, video atau penjanaan pertuturan edisi Qwen3-Omni lain kepada Captioner hanya kerana namanya berkongsi keluarga yang sama.</p><p>Ketiadaan prom teks penting dalam amalan. Sediakan segmen audio yang mahu diterangkan dan hantar segmen itu sebagai keseluruhan tugas. Jangan tambah arahan untuk ringkasan tersuai, terjemahan, jawapan kepada penutur atau skema output. Jika aliran kerja memerlukan transformasi tersebut, ia tergolong dalam peringkat berasingan yang memproses penerangan yang dikembalikan, bukannya dianggap sebagai kawalan checkpoint penghasilan kapsyen ini.</p><p>Menyediakan audio yang berguna</p><p>Qwen mengesyorkan klip tidak melebihi 30 saat untuk penerangan terperinci. Ini ialah syor kualiti: audio yang terlalu panjang boleh mengurangkan persepsi butiran. Ia tidak dikemukakan sebagai ambang penolakan keras sejagat. Bagi rakaman lebih panjang, pilih segmen pendek yang bermakna sekitar peristiwa atau adegan yang dinilai. Simpan pengecam sumber dan masa mula di luar permintaan model supaya kapsyen yang dikembalikan dapat dikesan semula kepada rakaman asal kemudian.</p><p>Kekalkan lapisan bunyi yang relevan dengan soalan. Petikan berfokuskan suara masih seharusnya merangkumi latar apabila latar itu mempengaruhi penerangan yang dikehendaki; aset muzik atau kesan bunyi seharusnya mengekalkan peralihan pentingnya dan bukan dipotong pada sempadan sembarangan. Memproses klip secara berasingan membantu mengekalkan butiran setempat, tetapi tidak membuktikan kesinambungan automatik atau pemahaman seluruh rakaman merentas permintaan.</p><p>Kegunaan hasil teks</p><p>Panduan praktikal pembuat menunjukkan kapsyen yang menerangkan kandungan dan cara penyampaian pertuturan, kemudian adegan sekeliling; contoh lain menerangkan muzik, kesan, perubahan keamatan dan urutan peristiwa suara. Katalog audio boleh menyimpan teks yang dikembalikan bersama nama aset dan julat masa. Penilai media boleh menggunakannya sebagai draf log bunyi. Penyunting boleh membandingkan kapsyen dengan klip untuk mengenal pasti sama ada penerangan menangkap lapisan yang dikehendaki. Ini ialah contoh aplikasi, bukan bukti bahawa model telah mendengar mana-mana aset pengguna tertentu terlebih dahulu.</p><p>Output ialah kapsyen deskriptif, bukan janji transkrip kata demi kata, jadual pemisahan penutur, fail sari kata bercap masa atau runut bunyi terjana. Apabila kata-kata tepat yang dituturkan atau masa diperlukan, semak kapsyen berdasarkan audio dan gunakan aliran kerja khusus yang sesuai untuk artifak yang diperlukan. Penerangan yang kaya boleh merangkumi maklumat adegan atau genre yang disimpulkan, jadi kekalkan ketidakpastian apabila bunyi itu sendiri tidak mengenal pasti sumber secara jelas.</p><p>Contoh penjanaan dan had</p><p>Contoh kendiri pembuat menetapkan konteks model 32,768 token dan peruntukan penjanaan 16,384 token, dengan temperature 0.6, top_p 0.95 dan top_k 20. Panduan praktikalnya menggunakan peruntukan penjanaan 8,192 token dengan nilai pensampelan yang sama. Ini ialah konfigurasi contoh, bukan panjang kapsyen maksimum yang diisytiharkan secara berasingan. Konfigurasi teks asas menyenaraikan 65,536 kedudukan, yang tidak seharusnya ditukar menjadi jaminan tempoh audio.</p><p>Kod utiliti umum atau medan konfigurasi yang dikongsi dengan keluarga Omni tidak mengatasi kontrak jelas Captioner: satu audio, tiada teks input dan teks sahaja sebagai output. Hasil yang berguna ialah penerangan terperinci bagi adegan bunyi pendek; semak petikan pertuturan, bilangan penutur dan sumber bunyi yang disimpulkan sebelum menggunakannya sebagai rekod berwibawa.</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Tersedia di Ailoot · input &amp; kaedah</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · Anthropic Messages</b> <code>POST /v1/messages</code></summary><dl class=\"method-capabilities\"><div><dt>Input</dt><dd><code>text</code></dd></div><div><dt>Output</dt><dd><code>json</code>, <code>sse</code></dd></div><div><dt>Format output</dt><dd>JSON atau SSE</dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>Medan</th><th>Jenis</th><th>Keperluan</th><th>Nilai &amp; had</th><th>Lalai</th></tr></thead><tbody><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Qwen/Qwen3-Omni-30B-A3B-Captioner</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">messages</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>message[]</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">messages[].role</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>user, assistant</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">messages[].content</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">max_tokens</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>integer</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">stream</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>boolean</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"known\"><span class=\"card-cell-label\">Lalai</span>false</td></tr></tbody></table></div><details class=\"card-about\" data-material-combinations><summary>Gabungan bahan input</summary><p class=\"note-s\"><b>Teks</b> · Teks UTF-8</p><p class=\"note-s\"><code>rentetan messages[].content</code></p></details><details class=\"note-s\" data-method-contract><summary>Parameter kaedah dan kitar hayat</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>Parameter</th><th>Kontrak</th></tr></thead><tbody><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>content_type</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>application/json</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>required</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>model, messages, max_tokens</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>optional_controls</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>stream</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>material_types</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>text</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>text_file_material</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>Baca dokumen UTF-8 sebenar dan letakkan teksnya dalam rentetan input atau kandungan mesej yang ditunjukkan.</td></tr></tbody></table></div><p>Kitar hayat: <code>synchronous_or_streamed</code></p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">Pelan harga</h3><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>Rujukan tarif tidak menambah pilihan permintaan. Parameter yang disokong disenaraikan untuk kaedah yang dipilih.</p><dl data-price-conditions><dt>Mod pantas</dt><dd>Tidak dinyatakan <span class=\"note-s\">Apabila mod pantas dipilih</span></dd><dt>Mod flex</dt><dd>Tidak dinyatakan <span class=\"note-s\">Apabila mod flex dipilih</span></dd><dt>Usaha penaakulan maksimum</dt><dd>Tidak dinyatakan <span class=\"note-s\">Apabila usaha penaakulan maksimum menggunakan pelarasan default</span></dd></dl></div><div data-declared-tariff-pricing><h4>Kadar Ailoot</h4><h4>Harga mengikut konfigurasi</h4><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Konfigurasi</th><th>Jadual kadar</th><th>Caj</th></tr></thead><tbody><tr><th data-cell-label=\"Konfigurasi\" scope=\"row\"><span class=\"card-cell-label\">Konfigurasi</span>Kadar asas token</th><td data-cell-label=\"Jadual kadar\"><span class=\"card-cell-label\">Jadual kadar</span>Kadar asas</td><td data-cell-label=\"Caj\"><span class=\"card-cell-label\">Caj</span><div><span>Input · Token input</span> <b>$0.0002</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Output · Token output</span> <b>$0.0008</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Bacaan cache</span> <b>$0</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Penulisan cache</span> <b>$0</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Penulisan cache, 1 jam</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot merizabkan anggaran amaun sebelum permintaan. Selepas hasil diterima, caj akhir diselesaikan berdasarkan penggunaan terukur. Penyelesaian caj penstriman menggunakan rekod penggunaan akhir. <a href=\"/docs/ms/billing/reserve/\">Cara rizab dan penyelesaian caj berfungsi →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">Contoh permintaan</h3><p class=\"note-s\" data-native-input-conflict=\"audio-text\">Penerangan model memerlukan input audio, tetapi laluan yang dipilih menyatakan input teks. Contoh penjanaan sedia dijalankan tidak disediakan untuk ketidakpadanan ini.</p><p><code>manufacturer: audio → text</code></p><p><code>route: text → json, sse</code></p></section><section class=\"card-section\" data-card-section=\"results\"><h3 tabindex=\"-1\">Terima dan simpan hasil</h3><h4>Ailoot Ultra · Anthropic Messages</h4><p class=\"note-s\">JSON atau SSE</p><div class=\"card-result-process\" data-all-results><h5>Simpan semua hasil yang selesai</h5><p class=\"note-s\">Simpan setiap respons lengkap, fail dan bahagian kandungan yang dikembalikan.</p><p class=\"note-s\">Kekalkan semua blok kandungan, tandatangan penaakulan dan ID penggunaan alat sebenar. Gabungkan semua delta blok SSE; blok teks pertama bukan keseluruhan output.</p></div><div class=\"card-result-process\" data-unknown-recovery><h5>Jika respons asal perlu disemak</h5><p class=\"note-s\">Kekalkan ID permintaan/respons dan pengepala. Tiada URL umum bagi pengambilan tugas teks dibekalkan.</p></div><details class=\"card-about\" data-output-fields><summary>Medan respons</summary><div class=\"tw\" data-card-table=\"output\"><table><thead><tr><th>Medan</th><th>Jenis</th></tr></thead><tbody><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">id</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>string</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>string</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">content[]</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>text|thinking|tool_use|other content block</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">stop_reason</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>string|null</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">usage</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>object</td></tr></tbody></table></div></details><details class=\"card-about\" data-method-errors><summary>Ralat dan langkah seterusnya</summary><div class=\"tw\" data-card-table=\"errors\"><table><thead><tr><th>Respons</th><th>Syarat</th><th>Langkah seterusnya</th></tr></thead><tbody><tr><th data-cell-label=\"Respons\" scope=\"row\"><span class=\"card-cell-label\">Respons</span>400 · <code>invalid_request_error</code></th><td data-cell-label=\"Syarat\"><span class=\"card-cell-label\">Syarat</span>Medan wajib, perwakilan bahan atau nilai parameter tidak sah</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Betulkan medan yang ditunjukkan sebelum permintaan penciptaan baharu.</td></tr></tbody></table></div></details></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">Alias</h3><h4>Alias model</h4><p class=\"note-s\"><span data-model-alias-route=\"Ultra\"><b>Ailoot Ultra</b> <a href=\"#m=Qwen%2FQwen3-Omni-30B-A3B-Captioner&amp;route=Ultra&amp;caller=Qwen%2FQwen3-Omni-30B-A3B-Captioner&amp;fmt=messages\"><code>Qwen/Qwen3-Omni-30B-A3B-Captioner</code></a></span></p><h4>Alias laluan kaedah</h4><p class=\"note-s\">Gunakan laluan kaedah yang dipaparkan di atas.</p><h4>ID pemanggil berkaitan</h4><p class=\"note-s\"><a href=\"#m=Qwen%2FQwen3-Omni-30B-A3B-Captioner&amp;route=Ultra&amp;caller=Qwen%2FQwen3-Omni-30B-A3B-Captioner&amp;fmt=messages\"><code>Qwen/Qwen3-Omni-30B-A3B-Captioner</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
        "fmt": "messages",
        "http": "POST",
        "path": "/v1/messages",
        "request_model_id": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|messages|/v1/messages|Qwen%2FQwen3-Omni-30B-A3B-Captioner",
      "ordinal": 1,
      "rawMethod": {
        "available": null,
        "cache_read": 0,
        "cache_write": 0,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "authentication": {
              "api_key_source": "AILOOT_API_KEY",
              "headers": [
                "Authorization: Bearer",
                "x-api-key",
                "anthropic-version"
              ],
              "version_example": "2023-06-01"
            },
            "errors": [
              {
                "code": null,
                "condition": "Medan wajib, perwakilan bahan atau nilai parameter tidak sah",
                "http_status": 400,
                "recovery": "Betulkan medan yang ditunjukkan sebelum permintaan penciptaan baharu.",
                "type": "invalid_request_error"
              }
            ],
            "example_body": {
              "max_tokens": 128,
              "messages": [
                {
                  "content": "Summarize the incident report.",
                  "role": "user"
                }
              ],
              "model": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
              "stream": false
            },
            "lifecycle": {
              "create": {
                "http": "POST",
                "path": "/v1/messages"
              },
              "job_read": null,
              "mode": "synchronous_or_streamed",
              "unknown": "Kekalkan ID permintaan/respons dan pengepala. Tiada URL umum bagi pengambilan tugas teks dibekalkan."
            },
            "material_combinations": [
              {
                "mode": "text",
                "representation": "rentetan messages[].content",
                "required_material": "Teks UTF-8"
              }
            ],
            "operation_modes": [
              "synchronous_json",
              "streamed_SSE"
            ],
            "outputs": {
              "all_results": "Kekalkan semua blok kandungan, tandatangan penaakulan dan ID penggunaan alat sebenar. Gabungkan semua delta blok SSE; blok teks pertama bukan keseluruhan output.",
              "family": "protocol",
              "fields": [
                {
                  "description": null,
                  "name": "id",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "model",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "content[]",
                  "type": "text|thinking|tool_use|other content block"
                },
                {
                  "description": null,
                  "name": "stop_reason",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": "object"
                }
              ],
              "format": "JSON atau SSE"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "Qwen/Qwen3-Omni-30B-A3B-Captioner"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages",
                "required": true,
                "type": "message[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "user",
                  "assistant"
                ],
                "enum_known": true,
                "name": "messages[].role",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].content",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "max_tokens",
                "required": true,
                "type": "integer"
              },
              {
                "availability": "source_interface",
                "default": false,
                "default_known": true,
                "enum": null,
                "enum_known": false,
                "name": "stream",
                "required": false,
                "type": "boolean"
              }
            ],
            "profile_binding": "Documented current stock Messages bridge; optional model capabilities are separate from this minimal text request.",
            "request_schema": {
              "additionalProperties": false,
              "properties": {
                "max_tokens": {
                  "minimum": 1,
                  "type": "integer"
                },
                "messages": {
                  "items": {
                    "additionalProperties": false,
                    "properties": {
                      "content": {
                        "oneOf": [
                          {
                            "type": "string"
                          },
                          {
                            "items": {
                              "oneOf": [
                                {
                                  "properties": {
                                    "text": {
                                      "type": "string"
                                    },
                                    "type": {
                                      "const": "text"
                                    }
                                  },
                                  "required": [
                                    "type",
                                    "text"
                                  ],
                                  "type": "object"
                                },
                                {
                                  "properties": {
                                    "source": {
                                      "oneOf": [
                                        {
                                          "properties": {
                                            "type": {
                                              "const": "url"
                                            },
                                            "url": {
                                              "type": "string"
                                            }
                                          },
                                          "required": [
                                            "type",
                                            "url"
                                          ],
                                          "type": "object"
                                        },
                                        {
                                          "properties": {
                                            "data": {
                                              "type": "string"
                                            },
                                            "media_type": {
                                              "type": "string"
                                            },
                                            "type": {
                                              "const": "base64"
                                            }
                                          },
                                          "required": [
                                            "type",
                                            "media_type",
                                            "data"
                                          ],
                                          "type": "object"
                                        }
                                      ]
                                    },
                                    "type": {
                                      "const": "image"
                                    }
                                  },
                                  "required": [
                                    "type",
                                    "source"
                                  ],
                                  "type": "object"
                                }
                              ]
                            },
                            "type": "array"
                          }
                        ]
                      },
                      "role": {
                        "enum": [
                          "user",
                          "assistant"
                        ],
                        "type": "string"
                      }
                    },
                    "required": [
                      "role",
                      "content"
                    ],
                    "type": "object"
                  },
                  "minItems": 1,
                  "type": "array"
                },
                "model": {
                  "enum": [
                    "Qwen/Qwen3-Omni-30B-A3B-Captioner"
                  ],
                  "type": "string"
                },
                "stream": {
                  "default": false,
                  "type": "boolean"
                }
              },
              "required": [
                "model",
                "messages",
                "max_tokens"
              ],
              "type": "object"
            },
            "schema_template": {
              "max_tokens": 128,
              "messages": [
                {
                  "content": "Summarize the incident report.",
                  "role": "user"
                }
              ],
              "model": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
              "stream": false
            },
            "unsupported": [
              "No query API key.",
              "Hosted/server-side tools and model-specific optional controls are not part of this minimal family example."
            ]
          },
          "input": {
            "content_type": "application/json",
            "material_types": [
              "text"
            ],
            "optional_controls": [
              "stream"
            ],
            "required": [
              "model",
              "messages",
              "max_tokens"
            ],
            "text_file_material": "Baca dokumen UTF-8 sebenar dan letakkan teksnya dalam rentetan input atau kandungan mesej yang ditunjukkan."
          },
          "lifecycle": {
            "create": {
              "http": "POST",
              "path": "/v1/messages"
            },
            "job_read": null,
            "mode": "synchronous_or_streamed",
            "unknown": "Keep request/response IDs and headers. No generic text job retrieval URL is supplied."
          },
          "manufacturer_capability": null,
          "method": {
            "http": "POST",
            "path": "/v1/messages"
          },
          "output": {
            "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.",
            "family": "protocol",
            "format": "JSON or SSE"
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Kadar asas token",
            "units": [
              {
                "amount": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000002",
                "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": "0.0008000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000008",
                "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",
                "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",
                "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",
                "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",
                "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": "{\n  \"model\": \"Qwen/Qwen3-Omni-30B-A3B-Captioner\",\n  \"max_tokens\": 128,\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"Summarize the incident report.\"\n    }\n  ],\n  \"stream\": false\n}",
            "label": "Complete minimal JSON body",
            "language": "json"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'Qwen/Qwen3-Omni-30B-A3B-Captioner', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -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\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n",
            "label": "curl · use your UTF-8 document",
            "language": "bash"
          },
          {
            "code": "import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'Qwen/Qwen3-Omni-30B-A3B-Captioner', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n    raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n    with urlopen(request, timeout=120) as response:\n        raw = response.read()\n        Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n    Path('result.json').write_bytes(error.read())\n    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n    raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n",
            "label": "Python · save the complete result",
            "language": "python"
          }
        ],
        "family": "anthropic",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "messages",
        "http": "POST",
        "in": 0.2,
        "input": [
          "text"
        ],
        "label": "Anthropic Messages",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "out": 0.8,
        "output": [
          "json",
          "sse"
        ],
        "path": "/v1/messages",
        "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000002",
                "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": "0.0008000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000008",
                "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",
                "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",
                "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",
                "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",
                "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": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": "0.0002000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.0000002",
            "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": "0.0008000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.0000008",
            "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",
            "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",
            "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",
            "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",
            "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": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
  "nativeProvenance": {
    "input_facts_canonical_sha256": "c917aa07a232c1aeb370c16663f49eb41ffc484f3f450671a501d2b971552db1",
    "input_html_sha256": "0169fcf8c1094df433b8383b5a426a39c1210bbe0b0225e83854e018710ec9c5",
    "private_audit_sha256": "52ee7eb34329d78f0aaee200c20e1f82d81756da91d5f8d31b12d9da03ce37a9",
    "role": "historical-normalized-input-audit-hashes",
    "schema": "ailoot-native-model-provenance-v2"
  },
  "page": {
    "canonical": "https://ailoot.ai/models/ms/qwen-qwen3-omni-30b-a3b-captioner/",
    "description": "Qwen3-Omni-30B-A3B-Captioner menerangkan pertuturan, muzik, bunyi persekitaran dan audio sinematik sebagai teks. Edisi satu giliran khusus ini menerima satu input audio tanpa prom teks; Qwen mengesyorkan klip tidak melebihi 30 saat untuk mengekalkan butiran halus.",
    "locale": "ms",
    "md_url": "https://ailoot.ai/models/ms/qwen-qwen3-omni-30b-a3b-captioner/index.md",
    "title": "Qwen3 Omni 30B A3B Captioner — Ailoot",
    "url": "https://ailoot.ai/models/ms/qwen-qwen3-omni-30b-a3b-captioner/"
  },
  "practicalHtml": "<h3>Tugas praktikal</h3><p>Penerangan model memerlukan input audio, tetapi laluan yang dipilih menyatakan input teks. Contoh penjanaan sedia dijalankan tidak disediakan untuk ketidakpadanan ini.</p><p>Contoh teknikal dalam bahasa Inggeris</p><pre><code>Describe one short audio asset\n\nManufacturer workflow only: select one short audio clip whose sound layers need a description. Submit exactly that audio input with no text prompt through the documented manufacturer workflow. Keep the asset identifier outside the request. The selected Ailoot text-only route does not provide this audio-input workflow.</code></pre><h4>Hasil yang dijangka</h4><pre><code>A detailed text caption covering audible speech, background sounds, music and event order when present, with uncertain sound sources or intentions kept distinct from direct audible observations.</code></pre><h4>Semak hasil</h4><pre><code>Compare the caption with the same clip for sound sequence and sources; reconcile the Ailoot text-input mismatch before use. Do not send this preparation note as a text prompt.</code></pre>",
  "practicalText": "Tugas praktikal Penerangan model memerlukan input audio, tetapi laluan yang dipilih menyatakan input teks. Contoh penjanaan sedia dijalankan tidak disediakan untuk ketidakpadanan ini. Contoh teknikal dalam bahasa Inggeris Describe one short audio asset Manufacturer workflow only: select one short audio clip whose sound layers need a description. Submit exactly that audio input with no text prompt through the documented manufacturer workflow. Keep the asset identifier outside the request. The selected Ailoot text-only route does not provide this audio-input workflow. Hasil yang dijangka A detailed text caption covering audible speech, background sounds, music and event order when present, with uncertain sound sources or intentions kept distinct from direct audible observations. Semak hasil Compare the caption with the same clip for sound sequence and sources; reconcile the Ailoot text-input mismatch before use. Do not send this preparation note as a text prompt.",
  "rawModel": {
    "about": "Gambaran keseluruhan: penerangan terperinci tentang bunyi\n\nQwen3-Omni-30B-A3B-Captioner ialah model penerangan audio khusus yang ditala halus daripada Qwen3-Omni-30B-A3B-Instruct. Ia menukar klip audio kepada huraian teks terperinci tentang perkara yang didengar. Qwen mereka bentuknya untuk bahan yang pelbagai, termasuk pertuturan, bunyi persekitaran, muzik, kesan sinematik dan campuran beberapa sumber bunyi. Ini menjadikannya berguna untuk menyediakan penerangan aset audio yang boleh dicari atau menilai lapisan bunyi dalam segmen media pendek.\n\nPemahaman pertuturan dan bunyi bukan pertuturan\n\nPembuat menerangkan analisis berbilang penutur, ungkapan berbilang bahasa, emosi suara dan niat yang dibayangkan oleh cara penyampaian. Contohnya melampaui transkrip: ia menerangkan bunyi suara, bahasa pertuturan dan suasana akustik sekeliling. Bagi audio bukan pertuturan, model menerangkan suasana persekitaran, bunyi dunia sebenar, lapisan muzik dan butiran dinamik dalam filem atau media.\n\nPenerangan suasana hati, niat penutur atau konteks budaya ialah tafsiran bahan yang dapat didengar. Nilainya secara berasingan daripada pertuturan dan peristiwa bunyi yang boleh diperiksa secara langsung. Kapsyen boleh membantu penilai menyedari perubahan nada atau lapisan latar; ia bukan ukuran emosi peribadi seseorang atau bukti sumber fizikal bunyi yang samar.\n\nEdisi Captioner dan kontrak inputnya\n\nCheckpoint ini menggunakan satu giliran sahaja. Ia menerima tepat satu input audio bagi setiap inferens, tanpa prom teks, dan mengembalikan teks sahaja. Ia mengandungi komponen thinker untuk memahami audio; konfigurasi yang diterbitkan mematikan output audio secara jelas. Jangan pindahkan ciri perbualan, imej, video atau penjanaan pertuturan edisi Qwen3-Omni lain kepada Captioner hanya kerana namanya berkongsi keluarga yang sama.\n\nKetiadaan prom teks penting dalam amalan. Sediakan segmen audio yang mahu diterangkan dan hantar segmen itu sebagai keseluruhan tugas. Jangan tambah arahan untuk ringkasan tersuai, terjemahan, jawapan kepada penutur atau skema output. Jika aliran kerja memerlukan transformasi tersebut, ia tergolong dalam peringkat berasingan yang memproses penerangan yang dikembalikan, bukannya dianggap sebagai kawalan checkpoint penghasilan kapsyen ini.\n\nMenyediakan audio yang berguna\n\nQwen mengesyorkan klip tidak melebihi 30 saat untuk penerangan terperinci. Ini ialah syor kualiti: audio yang terlalu panjang boleh mengurangkan persepsi butiran. Ia tidak dikemukakan sebagai ambang penolakan keras sejagat. Bagi rakaman lebih panjang, pilih segmen pendek yang bermakna sekitar peristiwa atau adegan yang dinilai. Simpan pengecam sumber dan masa mula di luar permintaan model supaya kapsyen yang dikembalikan dapat dikesan semula kepada rakaman asal kemudian.\n\nKekalkan lapisan bunyi yang relevan dengan soalan. Petikan berfokuskan suara masih seharusnya merangkumi latar apabila latar itu mempengaruhi penerangan yang dikehendaki; aset muzik atau kesan bunyi seharusnya mengekalkan peralihan pentingnya dan bukan dipotong pada sempadan sembarangan. Memproses klip secara berasingan membantu mengekalkan butiran setempat, tetapi tidak membuktikan kesinambungan automatik atau pemahaman seluruh rakaman merentas permintaan.\n\nKegunaan hasil teks\n\nPanduan praktikal pembuat menunjukkan kapsyen yang menerangkan kandungan dan cara penyampaian pertuturan, kemudian adegan sekeliling; contoh lain menerangkan muzik, kesan, perubahan keamatan dan urutan peristiwa suara. Katalog audio boleh menyimpan teks yang dikembalikan bersama nama aset dan julat masa. Penilai media boleh menggunakannya sebagai draf log bunyi. Penyunting boleh membandingkan kapsyen dengan klip untuk mengenal pasti sama ada penerangan menangkap lapisan yang dikehendaki. Ini ialah contoh aplikasi, bukan bukti bahawa model telah mendengar mana-mana aset pengguna tertentu terlebih dahulu.\n\nOutput ialah kapsyen deskriptif, bukan janji transkrip kata demi kata, jadual pemisahan penutur, fail sari kata bercap masa atau runut bunyi terjana. Apabila kata-kata tepat yang dituturkan atau masa diperlukan, semak kapsyen berdasarkan audio dan gunakan aliran kerja khusus yang sesuai untuk artifak yang diperlukan. Penerangan yang kaya boleh merangkumi maklumat adegan atau genre yang disimpulkan, jadi kekalkan ketidakpastian apabila bunyi itu sendiri tidak mengenal pasti sumber secara jelas.\n\nContoh penjanaan dan had\n\nContoh kendiri pembuat menetapkan konteks model 32,768 token dan peruntukan penjanaan 16,384 token, dengan temperature 0.6, top_p 0.95 dan top_k 20. Panduan praktikalnya menggunakan peruntukan penjanaan 8,192 token dengan nilai pensampelan yang sama. Ini ialah konfigurasi contoh, bukan panjang kapsyen maksimum yang diisytiharkan secara berasingan. Konfigurasi teks asas menyenaraikan 65,536 kedudukan, yang tidak seharusnya ditukar menjadi jaminan tempoh audio.\n\nKod utiliti umum atau medan konfigurasi yang dikongsi dengan keluarga Omni tidak mengatasi kontrak jelas Captioner: satu audio, tiada teks input dan teks sahaja sebagai output. Hasil yang berguna ialah penerangan terperinci bagi adegan bunyi pendek; semak petikan pertuturan, bilangan penutur dan sumber bunyi yang disimpulkan sebelum menggunakannya sebagai rekod berwibawa.",
    "alias_of": null,
    "aliases": [],
    "author": "Alibaba",
    "available": null,
    "canonical_model": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
    "capabilities": {
      "context_length": 64000,
      "manufacturer_input": [],
      "manufacturer_output": []
    },
    "card_routes": [
      {
        "label": "Ultra",
        "rates": [
          {
            "amount": "0.0002000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.0000002",
            "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": "0.0008000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.0000008",
            "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": "Maklumat lengkap tentang harga konfigurasi terdapat dalam butiran."
      }
    ],
    "ctx": null,
    "display_name": "Qwen3 Omni 30B A3B Captioner",
    "entity_type": "model",
    "formats": [
      "chat",
      "messages"
    ],
    "id": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
    "input": [
      "text"
    ],
    "kind": "text",
    "max_out": null,
    "methods": [
      {
        "available": null,
        "cache_read": 0,
        "cache_write": 0,
        "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": "Medan wajib, perwakilan bahan atau nilai parameter tidak sah",
                "http_status": 400,
                "recovery": "Betulkan medan yang ditunjukkan sebelum permintaan penciptaan baharu.",
                "type": "invalid_request_error"
              }
            ],
            "hints": [
              "Model context is not an output cap.",
              "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.",
              "Tool calls propose actions; the client application returns actual observations with the returned call ID.",
              "Guarded canonical keys must occur once; duplicate or case-varied model/tools/cap fields are rejected."
            ],
            "ignored_fields": [],
            "lifecycle": {
              "create": {
                "http": "POST",
                "path": "/v1/chat/completions"
              },
              "job_read": null,
              "mode": "synchronous_or_streamed",
              "unknown": "Kekalkan ID permintaan/respons dan pengepala. Tiada URL umum bagi pengambilan tugas teks dibekalkan."
            },
            "material_combinations": [
              {
                "mode": "text",
                "representation": "messages[].content",
                "required_material": "Teks UTF8"
              }
            ],
            "operation_modes": [
              "conversation",
              "function_tool_continuation",
              "streaming"
            ],
            "outputs": {
              "all_results": "Kekalkan setiap pilihan jawapan bersama kandungan, panggilan alat dan penaakulannya. Dalam SSE, gabungkan delta mengikut indeks pilihan jawapan/alat dan kekalkan sebab penamatan akhir serta data penggunaan.",
              "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 atau SSE"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "Qwen/Qwen3-Omni-30B-A3B-Captioner"
                ],
                "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",
                "conditions": "Peranan ini diwakili secara eksplisit oleh jenis keserasian dalam kod sumber; set peranan model yang tepat kekal khusus untuk setiap model.",
                "default": null,
                "default_known": false,
                "enum": [
                  "system",
                  "user",
                  "assistant",
                  "tool",
                  "function"
                ],
                "enum_exhaustive": false,
                "enum_known": true,
                "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|content_part[]|null"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].tool_calls",
                "required": false,
                "type": "tool_call[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].tool_call_id",
                "required": false,
                "type": "string",
                "when": "role=tool; gunakan ID sebenar yang dipulangkan"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].name",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].reasoning_content",
                "required": false,
                "type": "string",
                "when": "Hantar semula penaakulan sebenar yang dipulangkan apabila model ini menggunakannya"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].reasoning_details",
                "required": false,
                "type": "object|array"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "minimum": 1,
                "name": "max_tokens",
                "required": false,
                "type": "integer"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "minimum": 1,
                "name": "max_completion_tokens",
                "required": false,
                "type": "integer"
              },
              {
                "availability": "source_interface",
                "default": false,
                "default_known": true,
                "enum": null,
                "enum_known": false,
                "name": "stream",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "stream_options.include_usage",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "temperature",
                "required": false,
                "type": "number"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "top_p",
                "required": false,
                "type": "number"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "stop",
                "required": false,
                "type": "string|string[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools",
                "required": false,
                "type": "function_tool[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": [
                  "function"
                ],
                "enum_known": true,
                "name": "tools[].type",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.name",
                "required": true,
                "type": "string",
                "when": "alat fungsi dibekalkan"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.description",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.parameters",
                "required": false,
                "type": "JSON_schema"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tool_choice",
                "required": false,
                "type": "string|object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "parallel_tool_calls",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "response_format",
                "required": false,
                "type": "object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "reasoning_effort",
                "required": false,
                "type": "string"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "reasoning",
                "required": false,
                "type": "object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "service_tier",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_compatibility",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "instructions",
                "required": false,
                "type": "string"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "functions",
                "required": false,
                "type": "function[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "function_call",
                "required": false,
                "type": "string|object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "prompt_cache_options",
                "required": false,
                "type": "object"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "text"
                ],
                "enum_known": true,
                "name": "modalities",
                "required": false,
                "type": "string[]"
              },
              {
                "availability": "source_interface",
                "conditions": "provider.options ditolak pada laluan teks Ultra ini",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "provider",
                "required": false,
                "type": "object"
              },
              {
                "availability": "source_interface",
                "conditions": "1h ditolak pada lokasi cache prompt yang digunakan",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "cache_control.ttl",
                "required": false,
                "type": "string"
              }
            ],
            "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.",
            "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": [
            "Hantar ID model yang tepat bersama messages.",
            "Panjang konteks bukan had output.",
            "Fail teks boleh membekalkan teks literal; input imej/audio/objek fail memerlukan pengikatan tepat."
          ],
          "input": {
            "content_type": "application/json",
            "control_scope": "khusus model; alat fungsi pengguna berbeza daripada alat yang dihoskan",
            "file_material": "dokumen UTF-8 sebenar dimasukkan sebagai teks literal; ID fail tidak diandaikan",
            "hosted_operations": false,
            "material_types": [
              "text"
            ],
            "messages": "tatasusunan mesej dengan struktur role/content",
            "multimodal_input_binding": null,
            "optional_controls": [
              "stream",
              "temperature",
              "top_p",
              "stop",
              "max_tokens",
              "max_completion_tokens",
              "reasoning",
              "response_format",
              "tools",
              "tool_choice"
            ],
            "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": [],
          "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": "Kadar asas token",
            "units": [
              {
                "amount": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000002",
                "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": "0.0008000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000008",
                "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",
                "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",
                "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",
                "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",
                "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\": \"Qwen/Qwen3-Omni-30B-A3B-Captioner\", \"messages\": [{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}]}')\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='Qwen/Qwen3-Omni-30B-A3B-Captioner',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}])\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"
          },
          {
            "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\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)\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\nwith client.chat.completions.stream(model='Qwen/Qwen3-Omni-30B-A3B-Captioner',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n    with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n        for event in stream:\n            payload=event.to_dict(mode=\"json\")\n            log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_completion()\n    save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n",
            "label": "Python SDK streaming · all events",
            "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": 0.2,
        "input": [
          "text"
        ],
        "label": "OpenAI Chat",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "out": 0.8,
        "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000002",
                "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": "0.0008000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000008",
                "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",
                "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",
                "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",
                "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",
                "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": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": "0.0002000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.0000002",
            "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": "0.0008000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.0000008",
            "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",
            "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",
            "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",
            "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",
            "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"
          }
        ]
      },
      {
        "available": null,
        "cache_read": 0,
        "cache_write": 0,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "authentication": {
              "api_key_source": "AILOOT_API_KEY",
              "headers": [
                "Authorization: Bearer",
                "x-api-key",
                "anthropic-version"
              ],
              "version_example": "2023-06-01"
            },
            "errors": [
              {
                "code": null,
                "condition": "Medan wajib, perwakilan bahan atau nilai parameter tidak sah",
                "http_status": 400,
                "recovery": "Betulkan medan yang ditunjukkan sebelum permintaan penciptaan baharu.",
                "type": "invalid_request_error"
              }
            ],
            "example_body": {
              "max_tokens": 128,
              "messages": [
                {
                  "content": "Summarize the incident report.",
                  "role": "user"
                }
              ],
              "model": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
              "stream": false
            },
            "lifecycle": {
              "create": {
                "http": "POST",
                "path": "/v1/messages"
              },
              "job_read": null,
              "mode": "synchronous_or_streamed",
              "unknown": "Kekalkan ID permintaan/respons dan pengepala. Tiada URL umum bagi pengambilan tugas teks dibekalkan."
            },
            "material_combinations": [
              {
                "mode": "text",
                "representation": "rentetan messages[].content",
                "required_material": "Teks UTF-8"
              }
            ],
            "operation_modes": [
              "synchronous_json",
              "streamed_SSE"
            ],
            "outputs": {
              "all_results": "Kekalkan semua blok kandungan, tandatangan penaakulan dan ID penggunaan alat sebenar. Gabungkan semua delta blok SSE; blok teks pertama bukan keseluruhan output.",
              "family": "protocol",
              "fields": [
                {
                  "description": null,
                  "name": "id",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "model",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "content[]",
                  "type": "text|thinking|tool_use|other content block"
                },
                {
                  "description": null,
                  "name": "stop_reason",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": "object"
                }
              ],
              "format": "JSON atau SSE"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "Qwen/Qwen3-Omni-30B-A3B-Captioner"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages",
                "required": true,
                "type": "message[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "user",
                  "assistant"
                ],
                "enum_known": true,
                "name": "messages[].role",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].content",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "max_tokens",
                "required": true,
                "type": "integer"
              },
              {
                "availability": "source_interface",
                "default": false,
                "default_known": true,
                "enum": null,
                "enum_known": false,
                "name": "stream",
                "required": false,
                "type": "boolean"
              }
            ],
            "profile_binding": "Documented current stock Messages bridge; optional model capabilities are separate from this minimal text request.",
            "request_schema": {
              "additionalProperties": false,
              "properties": {
                "max_tokens": {
                  "minimum": 1,
                  "type": "integer"
                },
                "messages": {
                  "items": {
                    "additionalProperties": false,
                    "properties": {
                      "content": {
                        "oneOf": [
                          {
                            "type": "string"
                          },
                          {
                            "items": {
                              "oneOf": [
                                {
                                  "properties": {
                                    "text": {
                                      "type": "string"
                                    },
                                    "type": {
                                      "const": "text"
                                    }
                                  },
                                  "required": [
                                    "type",
                                    "text"
                                  ],
                                  "type": "object"
                                },
                                {
                                  "properties": {
                                    "source": {
                                      "oneOf": [
                                        {
                                          "properties": {
                                            "type": {
                                              "const": "url"
                                            },
                                            "url": {
                                              "type": "string"
                                            }
                                          },
                                          "required": [
                                            "type",
                                            "url"
                                          ],
                                          "type": "object"
                                        },
                                        {
                                          "properties": {
                                            "data": {
                                              "type": "string"
                                            },
                                            "media_type": {
                                              "type": "string"
                                            },
                                            "type": {
                                              "const": "base64"
                                            }
                                          },
                                          "required": [
                                            "type",
                                            "media_type",
                                            "data"
                                          ],
                                          "type": "object"
                                        }
                                      ]
                                    },
                                    "type": {
                                      "const": "image"
                                    }
                                  },
                                  "required": [
                                    "type",
                                    "source"
                                  ],
                                  "type": "object"
                                }
                              ]
                            },
                            "type": "array"
                          }
                        ]
                      },
                      "role": {
                        "enum": [
                          "user",
                          "assistant"
                        ],
                        "type": "string"
                      }
                    },
                    "required": [
                      "role",
                      "content"
                    ],
                    "type": "object"
                  },
                  "minItems": 1,
                  "type": "array"
                },
                "model": {
                  "enum": [
                    "Qwen/Qwen3-Omni-30B-A3B-Captioner"
                  ],
                  "type": "string"
                },
                "stream": {
                  "default": false,
                  "type": "boolean"
                }
              },
              "required": [
                "model",
                "messages",
                "max_tokens"
              ],
              "type": "object"
            },
            "schema_template": {
              "max_tokens": 128,
              "messages": [
                {
                  "content": "Summarize the incident report.",
                  "role": "user"
                }
              ],
              "model": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
              "stream": false
            },
            "unsupported": [
              "No query API key.",
              "Hosted/server-side tools and model-specific optional controls are not part of this minimal family example."
            ]
          },
          "input": {
            "content_type": "application/json",
            "material_types": [
              "text"
            ],
            "optional_controls": [
              "stream"
            ],
            "required": [
              "model",
              "messages",
              "max_tokens"
            ],
            "text_file_material": "Baca dokumen UTF-8 sebenar dan letakkan teksnya dalam rentetan input atau kandungan mesej yang ditunjukkan."
          },
          "lifecycle": {
            "create": {
              "http": "POST",
              "path": "/v1/messages"
            },
            "job_read": null,
            "mode": "synchronous_or_streamed",
            "unknown": "Keep request/response IDs and headers. No generic text job retrieval URL is supplied."
          },
          "manufacturer_capability": null,
          "method": {
            "http": "POST",
            "path": "/v1/messages"
          },
          "output": {
            "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.",
            "family": "protocol",
            "format": "JSON or SSE"
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Kadar asas token",
            "units": [
              {
                "amount": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000002",
                "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": "0.0008000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000008",
                "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",
                "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",
                "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",
                "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",
                "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": "{\n  \"model\": \"Qwen/Qwen3-Omni-30B-A3B-Captioner\",\n  \"max_tokens\": 128,\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"Summarize the incident report.\"\n    }\n  ],\n  \"stream\": false\n}",
            "label": "Complete minimal JSON body",
            "language": "json"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'Qwen/Qwen3-Omni-30B-A3B-Captioner', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -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\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n",
            "label": "curl · use your UTF-8 document",
            "language": "bash"
          },
          {
            "code": "import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'Qwen/Qwen3-Omni-30B-A3B-Captioner', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n    raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n    with urlopen(request, timeout=120) as response:\n        raw = response.read()\n        Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n    Path('result.json').write_bytes(error.read())\n    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n    raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n",
            "label": "Python · save the complete result",
            "language": "python"
          }
        ],
        "family": "anthropic",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "messages",
        "http": "POST",
        "in": 0.2,
        "input": [
          "text"
        ],
        "label": "Anthropic Messages",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "out": 0.8,
        "output": [
          "json",
          "sse"
        ],
        "path": "/v1/messages",
        "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000002",
                "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": "0.0008000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000008",
                "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",
                "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",
                "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",
                "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",
                "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": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": "0.0002000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.0000002",
            "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": "0.0008000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.0000008",
            "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",
            "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",
            "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",
            "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",
            "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_aliases": [
      {
        "canonical_model_id": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
        "request_model_id": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
        "route_label": "Ultra"
      }
    ],
    "name": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
    "price": {
      "in": 0.2,
      "in_label": null,
      "out": 0.8,
      "out_label": null,
      "scope_label": "Token rates",
      "sort_in": 0.2,
      "sort_out": 0.8,
      "varies": false
    },
    "public_id": "Qwen/Qwen3-Omni-30B-A3B-Captioner",
    "short": "Qwen3-Omni-30B-A3B-Captioner menerangkan pertuturan, muzik, bunyi persekitaran dan audio sinematik sebagai teks. Edisi satu giliran khusus ini menerima satu input audio tanpa prom teks; Qwen mengesyorkan klip tidak melebihi 30 saat untuk mengekalkan butiran halus."
  },
  "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
        },
        {
          "contract_json_pointer": "/methods/1/rawMethod/contract",
          "html_json_pointer": "/methods/1/html",
          "method_ordinal": 1
        }
      ],
      "role": "current-semantic-reference"
    },
    "raw_input": {
      "examples_role": "historical-input-not-current-ready-examples",
      "json_pointers": [
        "/rawModel",
        "/methods/0/rawMethod",
        "/methods/1/rawMethod"
      ],
      "role": "historical-owner-input"
    },
    "schema": "ailoot-native-model-representations-v1"
  },
  "schema": "ailoot-static-model-facts-v1",
  "schema_version": 1,
  "shortText": "Qwen3-Omni-30B-A3B-Captioner menerangkan pertuturan, muzik, bunyi persekitaran dan audio sinematik sebagai teks. Edisi satu giliran khusus ini menerima satu input audio tanpa prom teks; Qwen mengesyorkan klip tidak melebihi 30 saat untuk mengekalkan butiran halus.",
  "source": {
    "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1",
    "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036",
    "raw_model_json_sha256": "e62942c96b5c544e7bd4ca6231b414a7b87827f801d425126776726f30633f92",
    "renderer_sha256": "1dab5ba62521e9568c8b7c82005622cabbf330a075df7cce1f83274a04009460"
  },
  "sourceRevision": "44184bc87352ab3052acc005baed60a931b0d663452a0b12dc38df7bfa12e7be"
}