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  "aboutHtml": "<p>GPT-6 Luna dalam mod Decisions OpenAI menilai bukti yang diberikan dan mengembalikan jawapan berjenis tentangnya. Pengeluar mendokumenkan GPT-6 Luna sebagai model untuk antara muka keputusan khusus ini. Ia boleh menganggarkan sama ada syarat berlaku, memilih daripada pilihan tetap atau meletakkan input pada rubrik bertertib. Gunakan mod GPT-6 Luna ini apabila tugas memerlukan hasil keputusan yang ditakrifkan, bukannya respons bertulis.</p><h4>Input bersama, soalan dan jawapan bernama</h4><p>Permintaan pengeluar mengandungi model, input bersama dan tatasusunan questions. Input boleh berupa rentetan teks atau mesej pengguna dengan teks dan imej. Setiap soalan mempunyai nama unik, jenis, arahan dan sebarang pilihan atau tahap yang diperlukan. Tatasusunan jawapan mengulangi nama soalan, membolehkan hasil dikaitkan dengan syarat, kategori atau penarafan yang benar-benar diminta.</p><p>Untuk mesej sokongan, berikan mesej dan konteks yang berkaitan dengan keputusan seterusnya, kemudian namakan soalan berdasarkan medan yang diperlukan aliran kerja. Untuk petikan dokumen, sertakan teks yang menetapkan kriteria, bukannya rujukan tanpa sokongan kepada fail lebih besar. Takrifkan soalan berdasarkan fakta yang boleh diperhatikan dan pisahkan perkara bebas. Hasil berguna boleh menggabungkan kategori masalah dengan penarafan keparahan sambil mengekalkan takrif dan makna setiap jawapan.</p><h4>Predicate: menganggarkan sama ada syarat berlaku</h4><p>Soalan predicate mengembalikan kebarangkalian dari 0 hingga 1 bahawa syarat yang ditakrifkan adalah benar. Ia boleh menyemak kerelevanan petikan atau keadaan yang kelihatan dalam imej. Untuk foto produk, terangkan kecacatan kelihatan yang perlu diperiksa, seperti retak atau koyak, dan berikan imej bersama kriteria itu. Nilai tersebut ialah anggaran model; aplikasi memilih ambang yang digunakan untuk penandaan atau semakan.</p><p>Panduan Decisions OpenAI memerlukan data imej terenkod yang disertakan terus untuk endpoint ini. Alamat imej yang dihoskan dan pengecam fail bukan input imej yang disokong dalam kontrak yang didokumenkan itu. Kandungan teks dan imej boleh digabungkan dalam mesej pengguna supaya bukti visual dinilai bersama konteks bertulis yang berkaitan. Pastikan imej jelas dan syarat khusus; kebarangkalian untuk satu kecacatan yang dinyatakan bukan laporan pemeriksaan umum yang meliputi setiap masalah berkemungkinan.</p><h4>Choice: memilih satu nilai yang diberikan</h4><p>Soalan choice memilih daripada pilihan dengan nilai berbeza dan penerangan yang menjelaskan bila ia terpakai. Pilihan yang dikembalikan ialah salah satu nilai itu, bersama kebarangkalian setiap pilihan dan medan confidence berasingan. Untuk penghalaan, takrifkan kategori berdasarkan pasukan sebenar atau hasil yang tersedia dan sertakan pilihan other apabila set tidak meliputi setiap input. Pastikan kategori ini tanpa tertib: kedudukannya bukan skala keparahan.</p><p>Taklimat pengelasan praktikal boleh membezakan kecacatan produk, masalah akses dan permintaan umum. Terangkan sempadan kategori itu, bukannya hanya bergantung pada nama pendek. Gunakan pilihan yang dikembalikan sebagai label cadangan dan periksa taburan apabila beberapa makna masih munasabah. Hasil membekalkan pemilihan; aplikasi menentukan sama ada pemilihan itu patut mencetuskan penghalaan automatik atau semakan.</p><h4>Score: kedudukan rubrik berwajaran kebarangkalian</h4><p>Soalan score menggunakan tahap bertertib yang disusun daripada paling rendah hingga paling tinggi. Indeks tahap bermula pada 0 dan skor ialah purata indeks tersebut berwajaran kebarangkalian. Ia boleh berada di antara tahap. Untuk keparahan masalah, satu tahap boleh bermakna kesan kosmetik, satu lagi penyelesaian sementara yang boleh digunakan dan satu lagi sekatan sepenuhnya; takrifkan kriteria yang memisahkannya. Jawapan merangkumi kebarangkalian setiap tahap dan confidence bersama skor.</p><p>Skor jangkaan merumuskan taburan, bukannya memilih satu kategori. Kekalkan perbezaan itu apabila menggunakan hasil untuk penentuan keutamaan atau trend agregat. Paparan kategori tetap boleh menggunakan soalan choice. Confidence ialah medan berasingan yang dilaporkan bagi jawapan choice dan score; panduan tidak mentakrifkannya sebagai sama dengan kebarangkalian pilihan terpilih.</p><h4>Beberapa soalan dan keputusan yang bergantung</h4><p>Soalan bebas boleh berkongsi input dalam satu permintaan pengeluar, termasuk jenis soalan berbeza. Foto boleh menyokong predicate kecacatan dan pilihan kategori, atau mesej boleh menyokong penilaian kategori dan keparahan. Berikan arahan dan makna sendiri bagi setiap perkara. Apabila keputusan kemudian bergantung pada hasil terdahulu, pengeluar mengesyorkan permintaan berasingan supaya soalan kedua boleh menggunakan hasil itu secara jelas. Jangan menganggap susunan soalan dalam satu tatasusunan menjadikannya perbualan berurutan.</p><h4>Memilih output yang betul dan mentafsir had</h4><p>Decisions membekalkan hasil predicate, choice atau score yang ditakrifkan. Sebaliknya, jawapan boleh mempunyai jenis refusal; periksa jenisnya sebelum membaca kebarangkalian, pilihan atau skor. OpenAI membezakannya daripada penjanaan objek berasaskan skema sembarang atau penjelasan bertulis melalui Structured Outputs, dan daripada permintaan tindakan alat melalui function calling. Jawapan keputusan tidak patut dibentangkan sebagai alasan terjana atau bukti bahawa tindakan luaran berlaku. Output, penaakulan dan tetapan alat model sembang umum tidak secara automatik menjadi sebahagian daripada mod khusus ini.</p><p>Gunakan input berlabel yang mewakili tugas untuk menilai ambang penghalaan, penapisan dan semakan, dengan mengambil kira akibat positif palsu dan negatif palsu. Simpan perkaitan antara bukti, takrif soalan dan output berangka mentah supaya hasil kabur dapat diperiksa. Pastikan bukti bersama berkaitan dengan soalan bernama dan takrifkan setiap pilihan atau tahap rubrik dengan jelas sebelum menghantar tugas keputusan. Sediakan bukti dan jenis jawapan berdasarkan aliran kerja keputusan yang didokumenkan, dengan output ditafsirkan menurut tugas yang dinilainya.</p>",
  "aboutText": "GPT-6 Luna dalam mod Decisions OpenAI menilai bukti yang diberikan dan mengembalikan jawapan berjenis tentangnya. Pengeluar mendokumenkan GPT-6 Luna sebagai model untuk antara muka keputusan khusus ini. Ia boleh menganggarkan sama ada syarat berlaku, memilih daripada pilihan tetap atau meletakkan input pada rubrik bertertib. Gunakan mod GPT-6 Luna ini apabila tugas memerlukan hasil keputusan yang ditakrifkan, bukannya respons bertulis.\n\n### Input bersama, soalan dan jawapan bernama\n\nPermintaan pengeluar mengandungi model, input bersama dan tatasusunan questions. Input boleh berupa rentetan teks atau mesej pengguna dengan teks dan imej. Setiap soalan mempunyai nama unik, jenis, arahan dan sebarang pilihan atau tahap yang diperlukan. Tatasusunan jawapan mengulangi nama soalan, membolehkan hasil dikaitkan dengan syarat, kategori atau penarafan yang benar-benar diminta.\n\nUntuk mesej sokongan, berikan mesej dan konteks yang berkaitan dengan keputusan seterusnya, kemudian namakan soalan berdasarkan medan yang diperlukan aliran kerja. Untuk petikan dokumen, sertakan teks yang menetapkan kriteria, bukannya rujukan tanpa sokongan kepada fail lebih besar. Takrifkan soalan berdasarkan fakta yang boleh diperhatikan dan pisahkan perkara bebas. Hasil berguna boleh menggabungkan kategori masalah dengan penarafan keparahan sambil mengekalkan takrif dan makna setiap jawapan.\n\n### Predicate: menganggarkan sama ada syarat berlaku\n\nSoalan predicate mengembalikan kebarangkalian dari 0 hingga 1 bahawa syarat yang ditakrifkan adalah benar. Ia boleh menyemak kerelevanan petikan atau keadaan yang kelihatan dalam imej. Untuk foto produk, terangkan kecacatan kelihatan yang perlu diperiksa, seperti retak atau koyak, dan berikan imej bersama kriteria itu. Nilai tersebut ialah anggaran model; aplikasi memilih ambang yang digunakan untuk penandaan atau semakan.\n\nPanduan Decisions OpenAI memerlukan data imej terenkod yang disertakan terus untuk endpoint ini. Alamat imej yang dihoskan dan pengecam fail bukan input imej yang disokong dalam kontrak yang didokumenkan itu. Kandungan teks dan imej boleh digabungkan dalam mesej pengguna supaya bukti visual dinilai bersama konteks bertulis yang berkaitan. Pastikan imej jelas dan syarat khusus; kebarangkalian untuk satu kecacatan yang dinyatakan bukan laporan pemeriksaan umum yang meliputi setiap masalah berkemungkinan.\n\n### Choice: memilih satu nilai yang diberikan\n\nSoalan choice memilih daripada pilihan dengan nilai berbeza dan penerangan yang menjelaskan bila ia terpakai. Pilihan yang dikembalikan ialah salah satu nilai itu, bersama kebarangkalian setiap pilihan dan medan confidence berasingan. Untuk penghalaan, takrifkan kategori berdasarkan pasukan sebenar atau hasil yang tersedia dan sertakan pilihan other apabila set tidak meliputi setiap input. Pastikan kategori ini tanpa tertib: kedudukannya bukan skala keparahan.\n\nTaklimat pengelasan praktikal boleh membezakan kecacatan produk, masalah akses dan permintaan umum. Terangkan sempadan kategori itu, bukannya hanya bergantung pada nama pendek. Gunakan pilihan yang dikembalikan sebagai label cadangan dan periksa taburan apabila beberapa makna masih munasabah. Hasil membekalkan pemilihan; aplikasi menentukan sama ada pemilihan itu patut mencetuskan penghalaan automatik atau semakan.\n\n### Score: kedudukan rubrik berwajaran kebarangkalian\n\nSoalan score menggunakan tahap bertertib yang disusun daripada paling rendah hingga paling tinggi. Indeks tahap bermula pada 0 dan skor ialah purata indeks tersebut berwajaran kebarangkalian. Ia boleh berada di antara tahap. Untuk keparahan masalah, satu tahap boleh bermakna kesan kosmetik, satu lagi penyelesaian sementara yang boleh digunakan dan satu lagi sekatan sepenuhnya; takrifkan kriteria yang memisahkannya. Jawapan merangkumi kebarangkalian setiap tahap dan confidence bersama skor.\n\nSkor jangkaan merumuskan taburan, bukannya memilih satu kategori. Kekalkan perbezaan itu apabila menggunakan hasil untuk penentuan keutamaan atau trend agregat. Paparan kategori tetap boleh menggunakan soalan choice. Confidence ialah medan berasingan yang dilaporkan bagi jawapan choice dan score; panduan tidak mentakrifkannya sebagai sama dengan kebarangkalian pilihan terpilih.\n\n### Beberapa soalan dan keputusan yang bergantung\n\nSoalan bebas boleh berkongsi input dalam satu permintaan pengeluar, termasuk jenis soalan berbeza. Foto boleh menyokong predicate kecacatan dan pilihan kategori, atau mesej boleh menyokong penilaian kategori dan keparahan. Berikan arahan dan makna sendiri bagi setiap perkara. Apabila keputusan kemudian bergantung pada hasil terdahulu, pengeluar mengesyorkan permintaan berasingan supaya soalan kedua boleh menggunakan hasil itu secara jelas. Jangan menganggap susunan soalan dalam satu tatasusunan menjadikannya perbualan berurutan.\n\n### Memilih output yang betul dan mentafsir had\n\nDecisions membekalkan hasil predicate, choice atau score yang ditakrifkan. Sebaliknya, jawapan boleh mempunyai jenis refusal; periksa jenisnya sebelum membaca kebarangkalian, pilihan atau skor. OpenAI membezakannya daripada penjanaan objek berasaskan skema sembarang atau penjelasan bertulis melalui Structured Outputs, dan daripada permintaan tindakan alat melalui function calling. Jawapan keputusan tidak patut dibentangkan sebagai alasan terjana atau bukti bahawa tindakan luaran berlaku. Output, penaakulan dan tetapan alat model sembang umum tidak secara automatik menjadi sebahagian daripada mod khusus ini.\n\nGunakan input berlabel yang mewakili tugas untuk menilai ambang penghalaan, penapisan dan semakan, dengan mengambil kira akibat positif palsu dan negatif palsu. Simpan perkaitan antara bukti, takrif soalan dan output berangka mentah supaya hasil kabur dapat diperiksa. Pastikan bukti bersama berkaitan dengan soalan bernama dan takrifkan setiap pilihan atau tahap rubrik dengan jelas sebelum menghantar tugas keputusan. Sediakan bukti dan jenis jawapan berdasarkan aliran kerja keputusan yang didokumenkan, dengan output ditafsirkan menurut tugas yang dinilainya.",
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">O</span><h2 id=\"sheet-title\">OpenAI: GPT-6 Luna Decisions</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"Tutup\">×</button></div><div class=\"idline\"><span>OpenAI /</span><code>openai/gpt-6-luna-decisions</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|systemone|/v1/systemone|openai%2Fgpt-6-luna-decisions\">System One</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\">GPT-6 Luna dalam mod Decisions OpenAI menilai teks dan imej serta memulangkan jawapan kebarangkalian dengan jenis yang ditetapkan: kebarangkalian sesuatu keadaan, pilihan tetap atau skor rubrik. Model ini menyokong pengelasan, penghalaan dan penetapan keutamaan tanpa menggunakan penjelasan bertulis sebagai hasil keputusan.</p><dl class=\"card-io\" data-card-io><div><dt>Input yang diterima</dt><dd>Teks · Imej</dd></div><div><dt>Hasil</dt><dd>decisions</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>GPT-6 Luna dalam mod Decisions OpenAI menilai bukti yang diberikan dan mengembalikan jawapan berjenis tentangnya. Pengeluar mendokumenkan GPT-6 Luna sebagai model untuk antara muka keputusan khusus ini. Ia boleh menganggarkan sama ada syarat berlaku, memilih daripada pilihan tetap atau meletakkan input pada rubrik bertertib. Gunakan mod GPT-6 Luna ini apabila tugas memerlukan hasil keputusan yang ditakrifkan, bukannya respons bertulis.</p><h4>Input bersama, soalan dan jawapan bernama</h4><p>Permintaan pengeluar mengandungi model, input bersama dan tatasusunan questions. Input boleh berupa rentetan teks atau mesej pengguna dengan teks dan imej. Setiap soalan mempunyai nama unik, jenis, arahan dan sebarang pilihan atau tahap yang diperlukan. Tatasusunan jawapan mengulangi nama soalan, membolehkan hasil dikaitkan dengan syarat, kategori atau penarafan yang benar-benar diminta.</p><p>Untuk mesej sokongan, berikan mesej dan konteks yang berkaitan dengan keputusan seterusnya, kemudian namakan soalan berdasarkan medan yang diperlukan aliran kerja. Untuk petikan dokumen, sertakan teks yang menetapkan kriteria, bukannya rujukan tanpa sokongan kepada fail lebih besar. Takrifkan soalan berdasarkan fakta yang boleh diperhatikan dan pisahkan perkara bebas. Hasil berguna boleh menggabungkan kategori masalah dengan penarafan keparahan sambil mengekalkan takrif dan makna setiap jawapan.</p><h4>Predicate: menganggarkan sama ada syarat berlaku</h4><p>Soalan predicate mengembalikan kebarangkalian dari 0 hingga 1 bahawa syarat yang ditakrifkan adalah benar. Ia boleh menyemak kerelevanan petikan atau keadaan yang kelihatan dalam imej. Untuk foto produk, terangkan kecacatan kelihatan yang perlu diperiksa, seperti retak atau koyak, dan berikan imej bersama kriteria itu. Nilai tersebut ialah anggaran model; aplikasi memilih ambang yang digunakan untuk penandaan atau semakan.</p><p>Panduan Decisions OpenAI memerlukan data imej terenkod yang disertakan terus untuk endpoint ini. Alamat imej yang dihoskan dan pengecam fail bukan input imej yang disokong dalam kontrak yang didokumenkan itu. Kandungan teks dan imej boleh digabungkan dalam mesej pengguna supaya bukti visual dinilai bersama konteks bertulis yang berkaitan. Pastikan imej jelas dan syarat khusus; kebarangkalian untuk satu kecacatan yang dinyatakan bukan laporan pemeriksaan umum yang meliputi setiap masalah berkemungkinan.</p><h4>Choice: memilih satu nilai yang diberikan</h4><p>Soalan choice memilih daripada pilihan dengan nilai berbeza dan penerangan yang menjelaskan bila ia terpakai. Pilihan yang dikembalikan ialah salah satu nilai itu, bersama kebarangkalian setiap pilihan dan medan confidence berasingan. Untuk penghalaan, takrifkan kategori berdasarkan pasukan sebenar atau hasil yang tersedia dan sertakan pilihan other apabila set tidak meliputi setiap input. Pastikan kategori ini tanpa tertib: kedudukannya bukan skala keparahan.</p><p>Taklimat pengelasan praktikal boleh membezakan kecacatan produk, masalah akses dan permintaan umum. Terangkan sempadan kategori itu, bukannya hanya bergantung pada nama pendek. Gunakan pilihan yang dikembalikan sebagai label cadangan dan periksa taburan apabila beberapa makna masih munasabah. Hasil membekalkan pemilihan; aplikasi menentukan sama ada pemilihan itu patut mencetuskan penghalaan automatik atau semakan.</p><h4>Score: kedudukan rubrik berwajaran kebarangkalian</h4><p>Soalan score menggunakan tahap bertertib yang disusun daripada paling rendah hingga paling tinggi. Indeks tahap bermula pada 0 dan skor ialah purata indeks tersebut berwajaran kebarangkalian. Ia boleh berada di antara tahap. Untuk keparahan masalah, satu tahap boleh bermakna kesan kosmetik, satu lagi penyelesaian sementara yang boleh digunakan dan satu lagi sekatan sepenuhnya; takrifkan kriteria yang memisahkannya. Jawapan merangkumi kebarangkalian setiap tahap dan confidence bersama skor.</p><p>Skor jangkaan merumuskan taburan, bukannya memilih satu kategori. Kekalkan perbezaan itu apabila menggunakan hasil untuk penentuan keutamaan atau trend agregat. Paparan kategori tetap boleh menggunakan soalan choice. Confidence ialah medan berasingan yang dilaporkan bagi jawapan choice dan score; panduan tidak mentakrifkannya sebagai sama dengan kebarangkalian pilihan terpilih.</p><h4>Beberapa soalan dan keputusan yang bergantung</h4><p>Soalan bebas boleh berkongsi input dalam satu permintaan pengeluar, termasuk jenis soalan berbeza. Foto boleh menyokong predicate kecacatan dan pilihan kategori, atau mesej boleh menyokong penilaian kategori dan keparahan. Berikan arahan dan makna sendiri bagi setiap perkara. Apabila keputusan kemudian bergantung pada hasil terdahulu, pengeluar mengesyorkan permintaan berasingan supaya soalan kedua boleh menggunakan hasil itu secara jelas. Jangan menganggap susunan soalan dalam satu tatasusunan menjadikannya perbualan berurutan.</p><h4>Memilih output yang betul dan mentafsir had</h4><p>Decisions membekalkan hasil predicate, choice atau score yang ditakrifkan. Sebaliknya, jawapan boleh mempunyai jenis refusal; periksa jenisnya sebelum membaca kebarangkalian, pilihan atau skor. OpenAI membezakannya daripada penjanaan objek berasaskan skema sembarang atau penjelasan bertulis melalui Structured Outputs, dan daripada permintaan tindakan alat melalui function calling. Jawapan keputusan tidak patut dibentangkan sebagai alasan terjana atau bukti bahawa tindakan luaran berlaku. Output, penaakulan dan tetapan alat model sembang umum tidak secara automatik menjadi sebahagian daripada mod khusus ini.</p><p>Gunakan input berlabel yang mewakili tugas untuk menilai ambang penghalaan, penapisan dan semakan, dengan mengambil kira akibat positif palsu dan negatif palsu. Simpan perkaitan antara bukti, takrif soalan dan output berangka mentah supaya hasil kabur dapat diperiksa. Pastikan bukti bersama berkaitan dengan soalan bernama dan takrifkan setiap pilihan atau tahap rubrik dengan jelas sebelum menghantar tugas keputusan. Sediakan bukti dan jenis jawapan berdasarkan aliran kerja keputusan yang didokumenkan, dengan output ditafsirkan menurut tugas yang dinilainya.</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 · System One</b> <code>POST /v1/systemone</code></summary><dl class=\"method-capabilities\"><div><dt>Input</dt><dd><code>text</code>, <code>image</code></dd></div><div><dt>Output</dt><dd><code>decisions</code></dd></div><div><dt>Format output</dt><dd>json</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>openai/gpt-6-luna-decisions</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>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=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">questions</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>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\">session_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></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\">state</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>schema</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\">trace</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>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=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">user</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\">questions.&lt;id&gt;.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>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>noul, choice, score</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\">questions.&lt;id&gt;.instructions</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string|object|array</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\">questions.&lt;id&gt;.criteria</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>Syarat: choice/score: wajib; noul: pilihan. Kriteria choice ialah objek; score ialah tatasusunan dengan minItems1.</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\">questions.&lt;id&gt;.criteria.true</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string|object|array</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: Objek kriteria noul 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\">questions.&lt;id&gt;.criteria.false</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string|object|array</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: Objek kriteria noul dibekalkan</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>noul</b> · Diperlukan: state, questions.&lt;id&gt;.type=noul, questions.&lt;id&gt;.instructions</p><p class=\"note-s\"><b>choice</b> · Diperlukan: state, questions.&lt;id&gt;.type=choice, questions.&lt;id&gt;.instructions, criteria object</p><p class=\"note-s\"><b>score</b> · Diperlukan: state, questions.&lt;id&gt;.type=score, questions.&lt;id&gt;.instructions, criteria array with minItems1</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, state, questions</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, image</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>provider, session_id, trace, user</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>Gunakan hanya bentuk perwakilan keadaan/dokumen tepat yang diisytiharkan. Keupayaan imej pengeluar sahaja tidak membuktikan bentuk input imej yang diterima bagi model tertentu.</td></tr></tbody></table></div><p>Kitar hayat: <code>synchronous</code></p><p class=\"note-s\">Hantar ID model yang tepat dan simpan respons natif yang lengkap.</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><p class=\"note-s\">Padankan setiap caj dengan syarat yang dipaparkan. Gunakan satu kadar bagi setiap set konfigurasi alternatif.</p><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Konfigurasi</th><th>Jadual kadar</th><th>Token konteks, melebihi</th><th>Token konteks, sehingga dan termasuk</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=\"Token konteks, melebihi\"><span class=\"card-cell-label\">Token konteks, melebihi</span>—</td><td data-cell-label=\"Token konteks, sehingga dan termasuk\"><span class=\"card-cell-label\">Token konteks, sehingga dan termasuk</span>Tiada had atas</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</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><tr><th data-cell-label=\"Konfigurasi\" scope=\"row\"><span class=\"card-cell-label\">Konfigurasi</span>Tahap panjang permintaan 1</th><td data-cell-label=\"Jadual kadar\"><span class=\"card-cell-label\">Jadual kadar</span>—</td><td data-cell-label=\"Token konteks, melebihi\"><span class=\"card-cell-label\">Token konteks, melebihi</span>0</td><td data-cell-label=\"Token konteks, sehingga dan termasuk\"><span class=\"card-cell-label\">Token konteks, sehingga dan termasuk</span>Tiada had atas</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</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><h4>Ailoot Ultra · System One</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Pilihan kod\"><button class=\"cg-tab\" id=\"model-code-2117-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2117-panel-0\" aria-selected=\"true\" tabindex=\"0\">Struktur permintaan rasmi yang dikekalkan; contoh dokumentasi</button><button class=\"cg-tab\" id=\"model-code-2117-tab-1\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2117-panel-1\" aria-selected=\"false\" tabindex=\"-1\">Gunakan bahan permintaan sebenar anda dan simpan hasil lengkap</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Salin kod\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-2117-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-2117-tab-0\"><pre data-lang=\"json\"><code>{\n  &quot;model&quot;: &quot;openai/gpt-6-luna-decisions&quot;,\n  &quot;questions&quot;: {\n    &quot;is_bug&quot;: {\n      &quot;criteria&quot;: {\n        &quot;false&quot;: &quot;The customer is asking a question or requesting a feature.&quot;,\n        &quot;true&quot;: &quot;The customer describes broken or unexpected product behavior.&quot;\n      },\n      &quot;instructions&quot;: &quot;Is the customer reporting a software defect?&quot;,\n      &quot;type&quot;: &quot;noul&quot;\n    },\n    &quot;team&quot;: {\n      &quot;criteria&quot;: {\n        &quot;account&quot;: &quot;Login, permissions, or profile issues.&quot;,\n        &quot;frontend&quot;: &quot;Rendering, layout, or browser compatibility issues.&quot;,\n        &quot;payments&quot;: &quot;Checkout, billing, or payment processing issues.&quot;\n      },\n      &quot;instructions&quot;: &quot;Which team should own this ticket?&quot;,\n      &quot;type&quot;: &quot;choice&quot;\n    },\n    &quot;urgency&quot;: {\n      &quot;criteria&quot;: [\n        &quot;Can wait for the next release&quot;,\n        &quot;Should be fixed this week&quot;,\n        &quot;Blocking revenue right now&quot;\n      ],\n      &quot;instructions&quot;: &quot;How urgent is this ticket?&quot;,\n      &quot;type&quot;: &quot;score&quot;\n    }\n  },\n  &quot;state&quot;: {\n    &quot;customer_tier&quot;: &quot;enterprise&quot;,\n    &quot;ticket&quot;: &quot;My checkout page shows a blank screen after I click Pay. I have tried two browsers.&quot;\n  }\n}</code></pre></div><div class=\"cg-pane\" id=\"model-code-2117-panel-1\" role=\"tabpanel\" aria-labelledby=\"model-code-2117-tab-1\" hidden><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\n: &quot;${AILOOT_REQUEST_FILE:?Set your actual JSON request file}&quot;\nexport AILOOT_REQUEST_FILE\npython3 - &lt;&lt;&#39;PY_REQUEST&#39;\nimport json,os\nfrom pathlib import Path\np=json.loads(Path(os.environ[&#39;AILOOT_REQUEST_FILE&#39;]).read_text(encoding=&#39;utf-8&#39;))\nif not isinstance(p,dict): raise SystemExit(&#39;Request must be a JSON object&#39;)\np[&#39;model&#39;]=&#39;openai/gpt-6-luna-decisions&#39;\nPath(&#39;request.json&#39;).write_text(json.dumps(p,ensure_ascii=False),encoding=&#39;utf-8&#39;)\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/systemone \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -H &#39;Content-Type: application/json&#39; \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - &lt;&lt;&#39;PY_RESULT&#39;\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path(&#39;result.json&#39;).read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n</code></pre></div></div></div></section><section class=\"card-section\" data-card-section=\"results\"><h3 tabindex=\"-1\">Terima dan simpan hasil</h3><h4>Ailoot Ultra · System One</h4><p class=\"note-s\">json</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\">Setiap jawapan bagi ID soalan yang diberikan dikekalkan berserta jenis tepatnya, nilai noul/choice/score, keyakinan, kebarangkalian dan petunjuk. Keseluruhan JSON asal disimpan dan hanya dikembalikan selepas penyelesaian caj.</p></div><div class=\"card-result-process\" data-unknown-recovery><h5>Jika respons asal perlu disemak</h5><p class=\"note-s\">Simpan operasi asal dan balasan penuh/separa; jangan ulang POST.</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\">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\">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\">provider</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\">answers.&lt;id&gt;.type</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\">answers.&lt;id&gt;.noul</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>number</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">answers.&lt;id&gt;.choice</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\">answers.&lt;id&gt;.score</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>number</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">answers.&lt;id&gt;.confidence</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>number</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">answers.&lt;id&gt;.probabilities</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>object</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">answers.&lt;id&gt;.legend</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>object</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">usage.input_tokens</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\">usage.output_tokens</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\">usage.cost</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>number</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, bentuk perwakilan atau nilai tidak sah</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Betulkan medan permintaan yang dinyatakan.</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=openai%2Fgpt-6-luna-decisions&amp;route=Ultra&amp;caller=openai%2Fgpt-6-luna-decisions&amp;fmt=systemone\"><code>openai/gpt-6-luna-decisions</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=openai%2Fgpt-6-luna-decisions&amp;route=Ultra&amp;caller=openai%2Fgpt-6-luna-decisions&amp;fmt=systemone\"><code>openai/gpt-6-luna-decisions</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "openai/gpt-6-luna-decisions",
        "fmt": "systemone",
        "http": "POST",
        "path": "/v1/systemone",
        "request_model_id": "openai/gpt-6-luna-decisions",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|systemone|/v1/systemone|openai%2Fgpt-6-luna-decisions",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "cache_read": 0,
        "cache_write": 0,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Every supplied question-ID answer with its exact type, noul/choice/score value, confidence, probabilities and legend is retained. Entire original JSON is stored and returned only after settlement.",
            "errors": [
              {
                "code": null,
                "condition": "Medan wajib, bentuk perwakilan atau nilai tidak sah",
                "http_status": 400,
                "recovery": "Betulkan medan permintaan yang dinyatakan.",
                "type": "invalid_request_error"
              }
            ],
            "hints": [],
            "ignored_fields": [],
            "lifecycle": {
              "cancel": null,
              "idempotency_header": null,
              "job_retrieve": null,
              "mode": "synchronous",
              "streaming": false,
              "unknown": "Simpan operasi asal dan balasan penuh/separa; jangan ulang POST."
            },
            "material_combinations": [
              {
                "mode": "noul",
                "optional": [
                  "criteria true/false descriptions"
                ],
                "required": [
                  "state",
                  "questions.<id>.type=noul",
                  "questions.<id>.instructions"
                ]
              },
              {
                "mode": "choice",
                "required": [
                  "state",
                  "questions.<id>.type=choice",
                  "questions.<id>.instructions",
                  "criteria object"
                ]
              },
              {
                "mode": "score",
                "required": [
                  "state",
                  "questions.<id>.type=score",
                  "questions.<id>.instructions",
                  "criteria array with minItems1"
                ]
              }
            ],
            "operation_modes": [
              "noul",
              "choice",
              "score"
            ],
            "outputs": {
              "all_results": "Setiap jawapan bagi ID soalan yang diberikan dikekalkan berserta jenis tepatnya, nilai noul/choice/score, keyakinan, kebarangkalian dan petunjuk. Keseluruhan JSON asal disimpan dan hanya dikembalikan selepas penyelesaian caj.",
              "family": "decisions",
              "fields": [
                {
                  "description": null,
                  "name": "model",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "id",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "provider",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "answers.<id>.type",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "answers.<id>.noul",
                  "type": "number"
                },
                {
                  "description": null,
                  "name": "answers.<id>.choice",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "answers.<id>.score",
                  "type": "number"
                },
                {
                  "description": null,
                  "name": "answers.<id>.confidence",
                  "type": "number"
                },
                {
                  "description": null,
                  "name": "answers.<id>.probabilities",
                  "type": "object"
                },
                {
                  "description": null,
                  "name": "answers.<id>.legend",
                  "type": "object"
                },
                {
                  "description": null,
                  "name": "usage.input_tokens",
                  "type": "integer"
                },
                {
                  "description": null,
                  "name": "usage.output_tokens",
                  "type": "integer"
                },
                {
                  "description": null,
                  "name": "usage.cost",
                  "type": "number"
                }
              ],
              "format": "json",
              "schema": {
                "properties": {
                  "answers": {
                    "additionalProperties": {
                      "description": "A Decisions answer using a boolean, choice, or score evaluation.",
                      "discriminator": {
                        "mapping": {
                          "choice": "#/components/schemas/DecisionsChoiceAnswer",
                          "noul": "#/components/schemas/DecisionsNoulAnswer",
                          "score": "#/components/schemas/DecisionsScoreAnswer"
                        },
                        "propertyName": "type"
                      },
                      "oneOf": [
                        {
                          "$ref": "#/components/schemas/DecisionsNoulAnswer"
                        },
                        {
                          "$ref": "#/components/schemas/DecisionsChoiceAnswer"
                        },
                        {
                          "$ref": "#/components/schemas/DecisionsScoreAnswer"
                        }
                      ]
                    },
                    "type": "object"
                  },
                  "id": {
                    "type": "string"
                  },
                  "model": {
                    "type": "string"
                  },
                  "provider": {
                    "type": "string"
                  },
                  "usage": {
                    "properties": {
                      "cost": {
                        "format": "double",
                        "type": "number"
                      },
                      "input_tokens": {
                        "type": "integer"
                      },
                      "output_tokens": {
                        "type": "integer"
                      }
                    },
                    "required": [
                      "input_tokens",
                      "output_tokens"
                    ],
                    "type": "object"
                  }
                },
                "required": [
                  "model",
                  "answers",
                  "usage"
                ],
                "type": "object"
              }
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "openai/gpt-6-luna-decisions"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "provider",
                "required": false,
                "type": "schema"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "questions",
                "required": true,
                "type": "object"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "description": "A unique identifier for grouping related requests (e.g., a conversation or agent workflow). Used for observability grouping in Broadcast and private logging; never sent to the provider. If provided in both the request body and the x-session-id header, the body value takes precedence. Maximum of 256 characters.",
                "enum": null,
                "enum_known": false,
                "maxLength": 256,
                "name": "session_id",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "description": "The content to evaluate: a plain string, or a JSON object or array of related context.",
                "enum": null,
                "enum_known": false,
                "name": "state",
                "required": true,
                "type": "schema"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "trace",
                "required": false,
                "type": "schema"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "maxLength": 256,
                "name": "user",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "noul",
                  "choice",
                  "score"
                ],
                "enum_known": true,
                "name": "questions.<id>.type",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "questions.<id>.instructions",
                "required": true,
                "type": "string|object|array"
              },
              {
                "availability": "source_interface",
                "conditions": "choice/score: wajib; noul: pilihan. Kriteria choice ialah objek; score ialah tatasusunan dengan minItems1.",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "questions.<id>.criteria",
                "required": false,
                "type": "object|array"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "questions.<id>.criteria.true",
                "required": true,
                "type": "string|object|array",
                "when": "Objek kriteria noul dibekalkan"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "questions.<id>.criteria.false",
                "required": true,
                "type": "string|object|array",
                "when": "Objek kriteria noul dibekalkan"
              }
            ],
            "unsupported": [
              "stream=true"
            ]
          },
          "hints": [
            "Hantar ID model yang tepat dan simpan respons natif yang lengkap."
          ],
          "input": {
            "content_type": "application/json",
            "material_types": [
              "text",
              "image"
            ],
            "multimodal_input_binding": "Gunakan hanya bentuk perwakilan keadaan/dokumen tepat yang diisytiharkan. Keupayaan imej pengeluar sahaja tidak membuktikan bentuk input imej yang diterima bagi model tertentu.",
            "optional_controls": [
              "provider",
              "session_id",
              "trace",
              "user"
            ],
            "required": [
              "model",
              "state",
              "questions"
            ]
          },
          "lifecycle": {
            "cancel": null,
            "idempotency_header": null,
            "job_retrieve": null,
            "mode": "synchronous",
            "streaming": false,
            "unknown": "Preserve original operation and full/partial reply; do not replay POST."
          },
          "manufacturer_capability": {
            "context_length": 1050000,
            "manufacturer_input": [
              "text",
              "image"
            ],
            "manufacturer_output": [
              "decisions"
            ]
          },
          "method": {
            "http": "POST",
            "path": "/v1/systemone"
          },
          "method_aliases": [],
          "operation_modes": [
            "noul",
            "choice",
            "score"
          ],
          "output": {
            "all_results": "Every supplied question-ID answer with its exact type, noul/choice/score value, confidence, probabilities and legend is retained. Entire original JSON is stored and returned only after settlement.",
            "family": "decisions",
            "fields": [
              {
                "description": null,
                "name": "model",
                "type": "string"
              },
              {
                "description": null,
                "name": "id",
                "type": "string"
              },
              {
                "description": null,
                "name": "provider",
                "type": "string"
              },
              {
                "description": null,
                "name": "answers.<id>.type",
                "type": "string"
              },
              {
                "description": null,
                "name": "answers.<id>.noul",
                "type": "number"
              },
              {
                "description": null,
                "name": "answers.<id>.choice",
                "type": "string"
              },
              {
                "description": null,
                "name": "answers.<id>.score",
                "type": "number"
              },
              {
                "description": null,
                "name": "answers.<id>.confidence",
                "type": "number"
              },
              {
                "description": null,
                "name": "answers.<id>.probabilities",
                "type": "object"
              },
              {
                "description": null,
                "name": "answers.<id>.legend",
                "type": "object"
              },
              {
                "description": null,
                "name": "usage.input_tokens",
                "type": "integer"
              },
              {
                "description": null,
                "name": "usage.output_tokens",
                "type": "integer"
              },
              {
                "description": null,
                "name": "usage.cost",
                "type": "number"
              }
            ],
            "format": "json",
            "schema": {
              "properties": {
                "answers": {
                  "additionalProperties": {
                    "description": "A Decisions answer using a boolean, choice, or score evaluation.",
                    "discriminator": {
                      "mapping": {
                        "choice": "#/components/schemas/DecisionsChoiceAnswer",
                        "noul": "#/components/schemas/DecisionsNoulAnswer",
                        "score": "#/components/schemas/DecisionsScoreAnswer"
                      },
                      "propertyName": "type"
                    },
                    "oneOf": [
                      {
                        "$ref": "#/components/schemas/DecisionsNoulAnswer"
                      },
                      {
                        "$ref": "#/components/schemas/DecisionsChoiceAnswer"
                      },
                      {
                        "$ref": "#/components/schemas/DecisionsScoreAnswer"
                      }
                    ]
                  },
                  "type": "object"
                },
                "id": {
                  "type": "string"
                },
                "model": {
                  "type": "string"
                },
                "provider": {
                  "type": "string"
                },
                "usage": {
                  "properties": {
                    "cost": {
                      "format": "double",
                      "type": "number"
                    },
                    "input_tokens": {
                      "type": "integer"
                    },
                    "output_tokens": {
                      "type": "integer"
                    }
                  },
                  "required": [
                    "input_tokens",
                    "output_tokens"
                  ],
                  "type": "object"
                }
              },
              "required": [
                "model",
                "answers",
                "usage"
              ],
              "type": "object"
            }
          },
          "schema": {
            "request": {
              "properties": {
                "model": {
                  "enum": [
                    "openai/gpt-6-luna-decisions"
                  ],
                  "type": "string"
                },
                "provider": {
                  "allOf": [
                    {
                      "$ref": "#/components/schemas/ProviderPreferences"
                    },
                    {
                      "description": "Provider routing preferences for the request."
                    }
                  ]
                },
                "questions": {
                  "additionalProperties": {
                    "description": "A Decisions question using a boolean, choice, or ordered score evaluation.",
                    "discriminator": {
                      "mapping": {
                        "choice": "#/components/schemas/DecisionsChoiceQuestion",
                        "noul": "#/components/schemas/DecisionsNoulQuestion",
                        "score": "#/components/schemas/DecisionsScoreQuestion"
                      },
                      "propertyName": "type"
                    },
                    "oneOf": [
                      {
                        "$ref": "#/components/schemas/DecisionsNoulQuestion"
                      },
                      {
                        "$ref": "#/components/schemas/DecisionsChoiceQuestion"
                      },
                      {
                        "$ref": "#/components/schemas/DecisionsScoreQuestion"
                      }
                    ]
                  },
                  "type": "object"
                },
                "session_id": {
                  "description": "A unique identifier for grouping related requests (e.g., a conversation or agent workflow). Used for observability grouping in Broadcast and private logging; never sent to the provider. If provided in both the request body and the x-session-id header, the body value takes precedence. Maximum of 256 characters.",
                  "example": "session-1234",
                  "maxLength": 256,
                  "type": "string"
                },
                "state": {
                  "anyOf": [
                    {
                      "type": "string"
                    },
                    {
                      "additionalProperties": {},
                      "type": "object"
                    },
                    {
                      "items": {},
                      "type": "array"
                    }
                  ],
                  "description": "The content to evaluate: a plain string, or a JSON object or array of related context."
                },
                "trace": {
                  "$ref": "#/components/schemas/TraceConfig"
                },
                "user": {
                  "maxLength": 256,
                  "type": "string"
                }
              },
              "required": [
                "model",
                "state",
                "questions"
              ],
              "type": "object"
            },
            "response": {
              "properties": {
                "answers": {
                  "additionalProperties": {
                    "description": "A Decisions answer using a boolean, choice, or score evaluation.",
                    "discriminator": {
                      "mapping": {
                        "choice": "#/components/schemas/DecisionsChoiceAnswer",
                        "noul": "#/components/schemas/DecisionsNoulAnswer",
                        "score": "#/components/schemas/DecisionsScoreAnswer"
                      },
                      "propertyName": "type"
                    },
                    "oneOf": [
                      {
                        "$ref": "#/components/schemas/DecisionsNoulAnswer"
                      },
                      {
                        "$ref": "#/components/schemas/DecisionsChoiceAnswer"
                      },
                      {
                        "$ref": "#/components/schemas/DecisionsScoreAnswer"
                      }
                    ]
                  },
                  "type": "object"
                },
                "id": {
                  "type": "string"
                },
                "model": {
                  "type": "string"
                },
                "provider": {
                  "type": "string"
                },
                "usage": {
                  "properties": {
                    "cost": {
                      "format": "double",
                      "type": "number"
                    },
                    "input_tokens": {
                      "type": "integer"
                    },
                    "output_tokens": {
                      "type": "integer"
                    }
                  },
                  "required": [
                    "input_tokens",
                    "output_tokens"
                  ],
                  "type": "object"
                }
              },
              "required": [
                "model",
                "answers",
                "usage"
              ],
              "type": "object"
            }
          }
        },
        "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",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "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,
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                "key": "cache_read_price",
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                "native_amount_usd_per_unit": "0",
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                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
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                "label": "Cache write",
                "native_amount_usd_per_unit": "0",
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            "label": "Tahap panjang permintaan 1",
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                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000002",
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                "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,
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                "rate_role": "typed_native_retail_rate",
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            ]
          }
        ],
        "examples": [
          {
            "code": "{\n  \"model\": \"openai/gpt-6-luna-decisions\",\n  \"questions\": {\n    \"is_bug\": {\n      \"criteria\": {\n        \"false\": \"The customer is asking a question or requesting a feature.\",\n        \"true\": \"The customer describes broken or unexpected product behavior.\"\n      },\n      \"instructions\": \"Is the customer reporting a software defect?\",\n      \"type\": \"noul\"\n    },\n    \"team\": {\n      \"criteria\": {\n        \"account\": \"Login, permissions, or profile issues.\",\n        \"frontend\": \"Rendering, layout, or browser compatibility issues.\",\n        \"payments\": \"Checkout, billing, or payment processing issues.\"\n      },\n      \"instructions\": \"Which team should own this ticket?\",\n      \"type\": \"choice\"\n    },\n    \"urgency\": {\n      \"criteria\": [\n        \"Can wait for the next release\",\n        \"Should be fixed this week\",\n        \"Blocking revenue right now\"\n      ],\n      \"instructions\": \"How urgent is this ticket?\",\n      \"type\": \"score\"\n    }\n  },\n  \"state\": {\n    \"customer_tier\": \"enterprise\",\n    \"ticket\": \"My checkout page shows a blank screen after I click Pay. I have tried two browsers.\"\n  }\n}",
            "label": "Retained official request structure; documentary example",
            "language": "json"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_REQUEST_FILE:?Set your actual JSON request file}\"\nexport AILOOT_REQUEST_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads(Path(os.environ['AILOOT_REQUEST_FILE']).read_text(encoding='utf-8'))\nif not isinstance(p,dict): raise SystemExit('Request must be a JSON object')\np['model']='openai/gpt-6-luna-decisions'\nPath('request.json').write_text(json.dumps(p,ensure_ascii=False),encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/systemone \\\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\nprint(json.dumps(json.loads(Path('result.json').read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n",
            "label": "Use your actual request material and retain the complete result",
            "language": "bash",
            "material_policy": "Use real owner-supplied state/questions or query/documents. No invented file ID, document, image URL, job ID or returned result."
          }
        ],
        "family": "systemone",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "systemone",
        "http": "POST",
        "in": 0.2,
        "input": [
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          "image"
        ],
        "label": "System One",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "native_endpoint": "systemone",
        "out": 0,
        "output": [
          "decisions"
        ],
        "path": "/v1/systemone",
        "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": [
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            "dimensions": {
              "regime": "base"
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            "label": "Base token rates",
            "units": [
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                "label": "Input tokens",
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                "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",
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                "native_quantity": 1,
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                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
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              }
            ]
          },
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              "min_context_tokens_exclusive": 0
            },
            "label": "Request-length tier 1",
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                "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",
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                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
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                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
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          }
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        "request_model_id": "openai/gpt-6-luna-decisions",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [
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            "cache_read_multiplier": null,
            "cache_write": 0,
            "cache_write_1h": null,
            "cache_write_multiplier": null,
            "created_at": "0001-01-01T00:00:00Z",
            "in": 0.2,
            "input_multiplier": null,
            "interval_boundary": "min_exclusive_max_inclusive",
            "max": null,
            "max_tokens": null,
            "min": 0,
            "min_tokens": 0,
            "null_rate_policy": "unknown or inherited; never zero",
            "out": 0,
            "output_multiplier": null,
            "per_request_price": null,
            "sort_order": 0,
            "tier_label": "",
            "updated_at": "0001-01-01T00:00:00Z"
          }
        ],
        "units": [
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            "billing_input": true,
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            "billing_input": true,
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            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
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            "native_unit": "one_hour_cache_creation_token",
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  ],
  "model_id": "openai/gpt-6-luna-decisions",
  "nativeProvenance": {
    "input_facts_canonical_sha256": "517837fc09109c085587cc56affa89d6f576bf23fc16cb748a3f318d1184a199",
    "input_html_sha256": "49c23f4eae126e3aac54ac3854d8b1fe494c59230a0bcef245b7a4b7fe66ca9f",
    "private_audit_sha256": "3664792fd6cce27deff032c21c0dd30801517ca197f714f8d196b0cb18abc385",
    "role": "historical-normalized-input-audit-hashes",
    "schema": "ailoot-native-model-provenance-v2"
  },
  "page": {
    "canonical": "https://ailoot.ai/models/ms/openai-gpt-6-luna-decisions/",
    "description": "GPT-6 Luna dalam mod Decisions OpenAI menilai teks dan imej serta memulangkan jawapan kebarangkalian dengan jenis yang ditetapkan: kebarangkalian sesuatu keadaan, pilihan tetap atau skor rubrik. Model ini menyokong pengelasan, penghalaan dan penetapan keutamaan tanpa menggunakan penjelasan bertulis sebagai hasil keputusan.",
    "locale": "ms",
    "md_url": "https://ailoot.ai/models/ms/openai-gpt-6-luna-decisions/index.md",
    "title": "OpenAI: GPT-6 Luna Decisions — Ailoot",
    "url": "https://ailoot.ai/models/ms/openai-gpt-6-luna-decisions/"
  },
  "rawModel": {
    "about": "GPT-6 Luna dalam mod Decisions OpenAI menilai bukti yang diberikan dan mengembalikan jawapan berjenis tentangnya. Pengeluar mendokumenkan GPT-6 Luna sebagai model untuk antara muka keputusan khusus ini. Ia boleh menganggarkan sama ada syarat berlaku, memilih daripada pilihan tetap atau meletakkan input pada rubrik bertertib. Gunakan mod GPT-6 Luna ini apabila tugas memerlukan hasil keputusan yang ditakrifkan, bukannya respons bertulis.\n\n### Input bersama, soalan dan jawapan bernama\n\nPermintaan pengeluar mengandungi model, input bersama dan tatasusunan questions. Input boleh berupa rentetan teks atau mesej pengguna dengan teks dan imej. Setiap soalan mempunyai nama unik, jenis, arahan dan sebarang pilihan atau tahap yang diperlukan. Tatasusunan jawapan mengulangi nama soalan, membolehkan hasil dikaitkan dengan syarat, kategori atau penarafan yang benar-benar diminta.\n\nUntuk mesej sokongan, berikan mesej dan konteks yang berkaitan dengan keputusan seterusnya, kemudian namakan soalan berdasarkan medan yang diperlukan aliran kerja. Untuk petikan dokumen, sertakan teks yang menetapkan kriteria, bukannya rujukan tanpa sokongan kepada fail lebih besar. Takrifkan soalan berdasarkan fakta yang boleh diperhatikan dan pisahkan perkara bebas. Hasil berguna boleh menggabungkan kategori masalah dengan penarafan keparahan sambil mengekalkan takrif dan makna setiap jawapan.\n\n### Predicate: menganggarkan sama ada syarat berlaku\n\nSoalan predicate mengembalikan kebarangkalian dari 0 hingga 1 bahawa syarat yang ditakrifkan adalah benar. Ia boleh menyemak kerelevanan petikan atau keadaan yang kelihatan dalam imej. Untuk foto produk, terangkan kecacatan kelihatan yang perlu diperiksa, seperti retak atau koyak, dan berikan imej bersama kriteria itu. Nilai tersebut ialah anggaran model; aplikasi memilih ambang yang digunakan untuk penandaan atau semakan.\n\nPanduan Decisions OpenAI memerlukan data imej terenkod yang disertakan terus untuk endpoint ini. Alamat imej yang dihoskan dan pengecam fail bukan input imej yang disokong dalam kontrak yang didokumenkan itu. Kandungan teks dan imej boleh digabungkan dalam mesej pengguna supaya bukti visual dinilai bersama konteks bertulis yang berkaitan. Pastikan imej jelas dan syarat khusus; kebarangkalian untuk satu kecacatan yang dinyatakan bukan laporan pemeriksaan umum yang meliputi setiap masalah berkemungkinan.\n\n### Choice: memilih satu nilai yang diberikan\n\nSoalan choice memilih daripada pilihan dengan nilai berbeza dan penerangan yang menjelaskan bila ia terpakai. Pilihan yang dikembalikan ialah salah satu nilai itu, bersama kebarangkalian setiap pilihan dan medan confidence berasingan. Untuk penghalaan, takrifkan kategori berdasarkan pasukan sebenar atau hasil yang tersedia dan sertakan pilihan other apabila set tidak meliputi setiap input. Pastikan kategori ini tanpa tertib: kedudukannya bukan skala keparahan.\n\nTaklimat pengelasan praktikal boleh membezakan kecacatan produk, masalah akses dan permintaan umum. Terangkan sempadan kategori itu, bukannya hanya bergantung pada nama pendek. Gunakan pilihan yang dikembalikan sebagai label cadangan dan periksa taburan apabila beberapa makna masih munasabah. Hasil membekalkan pemilihan; aplikasi menentukan sama ada pemilihan itu patut mencetuskan penghalaan automatik atau semakan.\n\n### Score: kedudukan rubrik berwajaran kebarangkalian\n\nSoalan score menggunakan tahap bertertib yang disusun daripada paling rendah hingga paling tinggi. Indeks tahap bermula pada 0 dan skor ialah purata indeks tersebut berwajaran kebarangkalian. Ia boleh berada di antara tahap. Untuk keparahan masalah, satu tahap boleh bermakna kesan kosmetik, satu lagi penyelesaian sementara yang boleh digunakan dan satu lagi sekatan sepenuhnya; takrifkan kriteria yang memisahkannya. Jawapan merangkumi kebarangkalian setiap tahap dan confidence bersama skor.\n\nSkor jangkaan merumuskan taburan, bukannya memilih satu kategori. Kekalkan perbezaan itu apabila menggunakan hasil untuk penentuan keutamaan atau trend agregat. Paparan kategori tetap boleh menggunakan soalan choice. Confidence ialah medan berasingan yang dilaporkan bagi jawapan choice dan score; panduan tidak mentakrifkannya sebagai sama dengan kebarangkalian pilihan terpilih.\n\n### Beberapa soalan dan keputusan yang bergantung\n\nSoalan bebas boleh berkongsi input dalam satu permintaan pengeluar, termasuk jenis soalan berbeza. Foto boleh menyokong predicate kecacatan dan pilihan kategori, atau mesej boleh menyokong penilaian kategori dan keparahan. Berikan arahan dan makna sendiri bagi setiap perkara. Apabila keputusan kemudian bergantung pada hasil terdahulu, pengeluar mengesyorkan permintaan berasingan supaya soalan kedua boleh menggunakan hasil itu secara jelas. Jangan menganggap susunan soalan dalam satu tatasusunan menjadikannya perbualan berurutan.\n\n### Memilih output yang betul dan mentafsir had\n\nDecisions membekalkan hasil predicate, choice atau score yang ditakrifkan. Sebaliknya, jawapan boleh mempunyai jenis refusal; periksa jenisnya sebelum membaca kebarangkalian, pilihan atau skor. OpenAI membezakannya daripada penjanaan objek berasaskan skema sembarang atau penjelasan bertulis melalui Structured Outputs, dan daripada permintaan tindakan alat melalui function calling. Jawapan keputusan tidak patut dibentangkan sebagai alasan terjana atau bukti bahawa tindakan luaran berlaku. 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                    "cost": {
                      "format": "double",
                      "type": "number"
                    },
                    "input_tokens": {
                      "type": "integer"
                    },
                    "output_tokens": {
                      "type": "integer"
                    }
                  },
                  "required": [
                    "input_tokens",
                    "output_tokens"
                  ],
                  "type": "object"
                }
              },
              "required": [
                "model",
                "answers",
                "usage"
              ],
              "type": "object"
            }
          }
        },
        "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",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "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"
              }
            ]
          },
          {
            "dimensions": {
              "max_context_tokens_inclusive": null,
              "min_context_tokens_exclusive": 0
            },
            "label": "Tahap panjang permintaan 1",
            "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",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "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\": \"openai/gpt-6-luna-decisions\",\n  \"questions\": {\n    \"is_bug\": {\n      \"criteria\": {\n        \"false\": \"The customer is asking a question or requesting a feature.\",\n        \"true\": \"The customer describes broken or unexpected product behavior.\"\n      },\n      \"instructions\": \"Is the customer reporting a software defect?\",\n      \"type\": \"noul\"\n    },\n    \"team\": {\n      \"criteria\": {\n        \"account\": \"Login, permissions, or profile issues.\",\n        \"frontend\": \"Rendering, layout, or browser compatibility issues.\",\n        \"payments\": \"Checkout, billing, or payment processing issues.\"\n      },\n      \"instructions\": \"Which team should own this ticket?\",\n      \"type\": \"choice\"\n    },\n    \"urgency\": {\n      \"criteria\": [\n        \"Can wait for the next release\",\n        \"Should be fixed this week\",\n        \"Blocking revenue right now\"\n      ],\n      \"instructions\": \"How urgent is this ticket?\",\n      \"type\": \"score\"\n    }\n  },\n  \"state\": {\n    \"customer_tier\": \"enterprise\",\n    \"ticket\": \"My checkout page shows a blank screen after I click Pay. I have tried two browsers.\"\n  }\n}",
            "label": "Retained official request structure; documentary example",
            "language": "json"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_REQUEST_FILE:?Set your actual JSON request file}\"\nexport AILOOT_REQUEST_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads(Path(os.environ['AILOOT_REQUEST_FILE']).read_text(encoding='utf-8'))\nif not isinstance(p,dict): raise SystemExit('Request must be a JSON object')\np['model']='openai/gpt-6-luna-decisions'\nPath('request.json').write_text(json.dumps(p,ensure_ascii=False),encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/systemone \\\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\nprint(json.dumps(json.loads(Path('result.json').read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\n",
            "label": "Use your actual request material and retain the complete result",
            "language": "bash",
            "material_policy": "Use real owner-supplied state/questions or query/documents. No invented file ID, document, image URL, job ID or returned result."
          }
        ],
        "family": "systemone",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "systemone",
        "http": "POST",
        "in": 0.2,
        "input": [
          "text",
          "image"
        ],
        "label": "System One",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "native_endpoint": "systemone",
        "out": 0,
        "output": [
          "decisions"
        ],
        "path": "/v1/systemone",
        "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",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "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"
              }
            ]
          },
          {
            "dimensions": {
              "max_context_tokens_inclusive": null,
              "min_context_tokens_exclusive": 0
            },
            "label": "Request-length tier 1",
            "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",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "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": "openai/gpt-6-luna-decisions",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [
          {
            "cache_read": 0,
            "cache_read_multiplier": null,
            "cache_write": 0,
            "cache_write_1h": null,
            "cache_write_multiplier": null,
            "created_at": "0001-01-01T00:00:00Z",
            "in": 0.2,
            "input_multiplier": null,
            "interval_boundary": "min_exclusive_max_inclusive",
            "max": null,
            "max_tokens": null,
            "min": 0,
            "min_tokens": 0,
            "null_rate_policy": "unknown or inherited; never zero",
            "out": 0,
            "output_multiplier": null,
            "per_request_price": null,
            "sort_order": 0,
            "tier_label": "",
            "updated_at": "0001-01-01T00:00:00Z"
          }
        ],
        "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",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0",
            "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": "openai/gpt-6-luna-decisions",
        "request_model_id": "openai/gpt-6-luna-decisions",
        "route_label": "Ultra"
      }
    ],
    "name": "OpenAI: GPT-6 Luna Decisions",
    "price": {
      "in": 0.2,
      "in_label": null,
      "out": 0,
      "out_label": null,
      "scope_label": "Token rates",
      "sort_in": 0.2,
      "sort_out": 0,
      "varies": true
    },
    "pricing_profiles": [
      {
        "dimensions": {
          "regime": "base"
        },
        "label": "System One · 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",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0",
            "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,
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