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  "aboutHtml": "<p>GPT-5.5 ialah model penaakulan perdana OpenAI untuk kerja profesional yang kompleks dan pengaturcaraan. Model ini menerima teks dan imej serta mengembalikan teks, dengan menggabungkan analisis dan penggunaan alat apabila tugas memerlukan maklumat atau tindakan di luar arahan yang dibekalkan. Panduan OpenAI menekankan kerja berdasarkan hasil yang jelas: terangkan hasil yang diperlukan, kekangan yang mesti dipatuhi, bukti yang perlu digunakan dan syarat yang menamatkan tugas.</p><p>Untuk perubahan perisian yang besar, sediakan bahan repositori yang berkaitan, tingkah laku semasa, tingkah laku yang dikehendaki dan kriteria penerimaan. Kenal pasti perkara yang boleh diubah dan perkara yang mesti kekal serasi. Hasil yang berguna untuk diminta ialah cadangan perubahan, penjelasan tentang tingkah laku yang terjejas dan bukti daripada pemeriksaan yang benar-benar dijalankan. Untuk tugas yang banyak melibatkan dokumen, labelkan dokumen sumber dan minta jawapan yang disusun berdasarkan keputusan yang perlu dibuat, dengan setiap kesimpulan dikaitkan dengan bukti yang dibekalkan serta soalan yang belum selesai dipisahkan daripada fakta yang telah ditetapkan.</p><p>GPT-5.5 menyokong usaha penaakulan none, low, medium, high dan xhigh, dengan medium sebagai lalai. OpenAI mengesyorkan agar low dipertimbangkan sebelum none apabila aliran kerja yang responsif masih memerlukan perancangan, carian atau beberapa panggilan alat. none sesuai untuk tugas langsung yang tidak memerlukan proses penaakulan itu. Usaha lebih tinggi tidak semestinya lebih baik: keperluan yang bercanggah, akses alat tanpa had yang jelas atau peraturan berhenti yang kabur boleh menyebabkan carian dan pemikiran berlebihan yang tidak perlu. Pilih usaha mengikut tugas sebenar dan nyatakan hasil akhir serta kriteria penyiapan yang dijangkakan dengan jelas.</p><p>Pengeluar menyenaraikan tetingkap konteks 1050000 token dan output maksimum 128000 token, dengan tarikh akhir pengetahuan pada 1 Disember 2025. Konteks menampung perbualan, bahan yang dibekalkan dan kandungan yang dijana; konteks bukan kuota berasingan untuk ditambahkan kepada output maksimum. Penaakulan dalaman turut menggunakan token dan kapasiti output. Oleh itu, kumpulan sumber yang besar perlu disusun berdasarkan soalan, dengan pengecam penting, unit dan sempadan dokumen dikekalkan serta ruang yang mencukupi diperuntukkan untuk penaakulan dan jawapan akhir.</p><p>Pengendalian imej berbeza daripada lalai terdahulu. Dalam panduan GPT-5.5 daripada OpenAI, tetapan butiran imej yang tidak dinyatakan atau auto menggunakan tingkah laku original, yang mengekalkan imej tanpa mengubah saiz apabila imej itu berada dalam kedua-dua had yang dinyatakan: bajet 10240000 piksel dan dimensi maksimum 6000 piksel. Tetapan high yang dipilih secara eksplisit mengekalkan butiran dalam kedua-dua had yang dinyatakan: bajet 2500000 piksel dan dimensi maksimum 2048 piksel; low mengubah saiz imej dengan dimensi melebihi 512 piksel secara lebih agresif. Ini ialah tetapan pemprosesan imej, bukannya jaminan bahawa setiap muat naik diterima. Untuk tangkapan skrin, rajah atau halaman, kenal pasti kawasan dan soalan, bekalkan imej yang jelas dan minta pemerhatian atau tafsiran yang diperlukan dan bukannya penerangan tanpa had.</p><p>OpenAI mendokumenkan antara muka Responses, Chat Completions dan Batch, dengan penstriman, Structured Outputs, panggilan fungsi, muat naik fail, input imej, carian fail dan web serta cache prompt. Set alat yang didokumenkan turut merangkumi carian alat, penjanaan imej, pentafsiran kod, shell yang dihoskan, operasi tampalan, kemahiran, penggunaan komputer dan MCP. Terangkan tujuan, argumen, kesan sampingan dan maklumat yang dikembalikan oleh setiap alat aplikasi. Permintaan untuk memanggil fungsi aplikasi memerlukan aplikasi melaksanakan operasi itu dan mengembalikan hasil sebenarnya; cadangan tindakan yang dijana bukan bukti bahawa tindakan itu telah berlaku. Modaliti output model itu sendiri kekal berupa teks, manakala alat penjanaan imej boleh menghasilkan bahan yang berasingan.</p><p>Untuk interaksi yang lebih panjang, kekalkan maklumat yang diperlukan untuk membezakan kerja sementara daripada jawapan yang telah selesai. Panduan OpenAI menerangkan nilai phase pada item assistant untuk jawapan commentary dan final: aplikasi yang memainkan semula item assistant secara manual mesti mengekalkan nilai phase asalnya, manakala rantaian melalui mekanisme respons terdahulu pengeluar mengekalkan keadaan itu secara automatik. Untuk jawapan yang kelihatan, tetapkan panjang, nada dan struktur yang dikehendaki dengan jelas. GPT-5.5 menggunakan gaya ringkas dan langsung secara lalai, dan tahap perincian teks (verbosity) ditetapkan kepada medium secara lalai; hasil padat boleh meminta tahap perincian yang lebih rendah tanpa membuang bukti atau penjelasan bersyarat yang diwajibkan.</p><p>Hasil akhir yang berguna boleh berupa fail yang disemak bersama penjelasan perubahan yang tertumpu, memo keputusan berasaskan dokumen bernama atau pengekstrakan berstruktur dengan nilai yang tiada ditandakan dengan jelas. Bekalkan fakta yang mesti terkini dan bukannya bergantung pada tarikh akhir pengetahuan model, serta bandingkan dakwaan penting dengan bahan asal. Peraturan bukti yang jelas, alat yang terhad dan syarat berhenti yang nyata membantu GPT-5.5 menyelesaikan tugas yang besar sambil mengekalkan hasil yang mudah difahami dan disemak.</p>",
  "aboutText": "GPT-5.5 ialah model penaakulan perdana OpenAI untuk kerja profesional yang kompleks dan pengaturcaraan. Model ini menerima teks dan imej serta mengembalikan teks, dengan menggabungkan analisis dan penggunaan alat apabila tugas memerlukan maklumat atau tindakan di luar arahan yang dibekalkan. Panduan OpenAI menekankan kerja berdasarkan hasil yang jelas: terangkan hasil yang diperlukan, kekangan yang mesti dipatuhi, bukti yang perlu digunakan dan syarat yang menamatkan tugas.\n\nUntuk perubahan perisian yang besar, sediakan bahan repositori yang berkaitan, tingkah laku semasa, tingkah laku yang dikehendaki dan kriteria penerimaan. Kenal pasti perkara yang boleh diubah dan perkara yang mesti kekal serasi. Hasil yang berguna untuk diminta ialah cadangan perubahan, penjelasan tentang tingkah laku yang terjejas dan bukti daripada pemeriksaan yang benar-benar dijalankan. Untuk tugas yang banyak melibatkan dokumen, labelkan dokumen sumber dan minta jawapan yang disusun berdasarkan keputusan yang perlu dibuat, dengan setiap kesimpulan dikaitkan dengan bukti yang dibekalkan serta soalan yang belum selesai dipisahkan daripada fakta yang telah ditetapkan.\n\nGPT-5.5 menyokong usaha penaakulan none, low, medium, high dan xhigh, dengan medium sebagai lalai. OpenAI mengesyorkan agar low dipertimbangkan sebelum none apabila aliran kerja yang responsif masih memerlukan perancangan, carian atau beberapa panggilan alat. none sesuai untuk tugas langsung yang tidak memerlukan proses penaakulan itu. Usaha lebih tinggi tidak semestinya lebih baik: keperluan yang bercanggah, akses alat tanpa had yang jelas atau peraturan berhenti yang kabur boleh menyebabkan carian dan pemikiran berlebihan yang tidak perlu. Pilih usaha mengikut tugas sebenar dan nyatakan hasil akhir serta kriteria penyiapan yang dijangkakan dengan jelas.\n\nPengeluar menyenaraikan tetingkap konteks 1050000 token dan output maksimum 128000 token, dengan tarikh akhir pengetahuan pada 1 Disember 2025. Konteks menampung perbualan, bahan yang dibekalkan dan kandungan yang dijana; konteks bukan kuota berasingan untuk ditambahkan kepada output maksimum. Penaakulan dalaman turut menggunakan token dan kapasiti output. Oleh itu, kumpulan sumber yang besar perlu disusun berdasarkan soalan, dengan pengecam penting, unit dan sempadan dokumen dikekalkan serta ruang yang mencukupi diperuntukkan untuk penaakulan dan jawapan akhir.\n\nPengendalian imej berbeza daripada lalai terdahulu. Dalam panduan GPT-5.5 daripada OpenAI, tetapan butiran imej yang tidak dinyatakan atau auto menggunakan tingkah laku original, yang mengekalkan imej tanpa mengubah saiz apabila imej itu berada dalam kedua-dua had yang dinyatakan: bajet 10240000 piksel dan dimensi maksimum 6000 piksel. Tetapan high yang dipilih secara eksplisit mengekalkan butiran dalam kedua-dua had yang dinyatakan: bajet 2500000 piksel dan dimensi maksimum 2048 piksel; low mengubah saiz imej dengan dimensi melebihi 512 piksel secara lebih agresif. Ini ialah tetapan pemprosesan imej, bukannya jaminan bahawa setiap muat naik diterima. Untuk tangkapan skrin, rajah atau halaman, kenal pasti kawasan dan soalan, bekalkan imej yang jelas dan minta pemerhatian atau tafsiran yang diperlukan dan bukannya penerangan tanpa had.\n\nOpenAI mendokumenkan antara muka Responses, Chat Completions dan Batch, dengan penstriman, Structured Outputs, panggilan fungsi, muat naik fail, input imej, carian fail dan web serta cache prompt. Set alat yang didokumenkan turut merangkumi carian alat, penjanaan imej, pentafsiran kod, shell yang dihoskan, operasi tampalan, kemahiran, penggunaan komputer dan MCP. Terangkan tujuan, argumen, kesan sampingan dan maklumat yang dikembalikan oleh setiap alat aplikasi. Permintaan untuk memanggil fungsi aplikasi memerlukan aplikasi melaksanakan operasi itu dan mengembalikan hasil sebenarnya; cadangan tindakan yang dijana bukan bukti bahawa tindakan itu telah berlaku. Modaliti output model itu sendiri kekal berupa teks, manakala alat penjanaan imej boleh menghasilkan bahan yang berasingan.\n\nUntuk interaksi yang lebih panjang, kekalkan maklumat yang diperlukan untuk membezakan kerja sementara daripada jawapan yang telah selesai. Panduan OpenAI menerangkan nilai phase pada item assistant untuk jawapan commentary dan final: aplikasi yang memainkan semula item assistant secara manual mesti mengekalkan nilai phase asalnya, manakala rantaian melalui mekanisme respons terdahulu pengeluar mengekalkan keadaan itu secara automatik. Untuk jawapan yang kelihatan, tetapkan panjang, nada dan struktur yang dikehendaki dengan jelas. GPT-5.5 menggunakan gaya ringkas dan langsung secara lalai, dan tahap perincian teks (verbosity) ditetapkan kepada medium secara lalai; hasil padat boleh meminta tahap perincian yang lebih rendah tanpa membuang bukti atau penjelasan bersyarat yang diwajibkan.\n\nHasil akhir yang berguna boleh berupa fail yang disemak bersama penjelasan perubahan yang tertumpu, memo keputusan berasaskan dokumen bernama atau pengekstrakan berstruktur dengan nilai yang tiada ditandakan dengan jelas. Bekalkan fakta yang mesti terkini dan bukannya bergantung pada tarikh akhir pengetahuan model, serta bandingkan dakwaan penting dengan bahan asal. Peraturan bukti yang jelas, alat yang terhad dan syarat berhenti yang nyata membantu GPT-5.5 menyelesaikan tugas yang besar sambil mengekalkan hasil yang mudah difahami dan disemak.",
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">O</span><h2 id=\"sheet-title\">OpenAI: GPT-5.5 (batch)</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"Tutup\">×</button></div><div class=\"idline\"><span>OpenAI /</span><code>openai/gpt-5.5:batch</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|batches|/v1/batches|openai%2Fgpt-5.5%3Abatch\">Kelompok</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-5.5 daripada OpenAI mengendalikan kerja profesional yang kompleks dan pengaturcaraan dengan input teks dan imej, penaakulan boleh konfigurasi serta set alat yang luas. Konteksnya yang besar menyokong kerja merentas bahan sumber yang banyak dan pengembalian hasil teks yang jelas serta khusus untuk tugas.</p><dl class=\"card-io\" data-card-io><div><dt>Input yang diterima</dt><dd>Teks</dd></div><div><dt>Hasil</dt><dd>Teks</dd></div></dl><details class=\"card-about\"><summary>Tentang model</summary><p class=\"note-s\" data-model-method-boundary>Huraian ini merangkumi keupayaan model. Input, output dan pilihan yang tersedia di Ailoot disenaraikan di bawah untuk kaedah yang dipilih.</p><div class=\"mabout\" id=\"m-about\"><p>GPT-5.5 ialah model penaakulan perdana OpenAI untuk kerja profesional yang kompleks dan pengaturcaraan. Model ini menerima teks dan imej serta mengembalikan teks, dengan menggabungkan analisis dan penggunaan alat apabila tugas memerlukan maklumat atau tindakan di luar arahan yang dibekalkan. Panduan OpenAI menekankan kerja berdasarkan hasil yang jelas: terangkan hasil yang diperlukan, kekangan yang mesti dipatuhi, bukti yang perlu digunakan dan syarat yang menamatkan tugas.</p><p>Untuk perubahan perisian yang besar, sediakan bahan repositori yang berkaitan, tingkah laku semasa, tingkah laku yang dikehendaki dan kriteria penerimaan. Kenal pasti perkara yang boleh diubah dan perkara yang mesti kekal serasi. Hasil yang berguna untuk diminta ialah cadangan perubahan, penjelasan tentang tingkah laku yang terjejas dan bukti daripada pemeriksaan yang benar-benar dijalankan. Untuk tugas yang banyak melibatkan dokumen, labelkan dokumen sumber dan minta jawapan yang disusun berdasarkan keputusan yang perlu dibuat, dengan setiap kesimpulan dikaitkan dengan bukti yang dibekalkan serta soalan yang belum selesai dipisahkan daripada fakta yang telah ditetapkan.</p><p>GPT-5.5 menyokong usaha penaakulan none, low, medium, high dan xhigh, dengan medium sebagai lalai. OpenAI mengesyorkan agar low dipertimbangkan sebelum none apabila aliran kerja yang responsif masih memerlukan perancangan, carian atau beberapa panggilan alat. none sesuai untuk tugas langsung yang tidak memerlukan proses penaakulan itu. Usaha lebih tinggi tidak semestinya lebih baik: keperluan yang bercanggah, akses alat tanpa had yang jelas atau peraturan berhenti yang kabur boleh menyebabkan carian dan pemikiran berlebihan yang tidak perlu. Pilih usaha mengikut tugas sebenar dan nyatakan hasil akhir serta kriteria penyiapan yang dijangkakan dengan jelas.</p><p>Pengeluar menyenaraikan tetingkap konteks 1050000 token dan output maksimum 128000 token, dengan tarikh akhir pengetahuan pada 1 Disember 2025. Konteks menampung perbualan, bahan yang dibekalkan dan kandungan yang dijana; konteks bukan kuota berasingan untuk ditambahkan kepada output maksimum. Penaakulan dalaman turut menggunakan token dan kapasiti output. Oleh itu, kumpulan sumber yang besar perlu disusun berdasarkan soalan, dengan pengecam penting, unit dan sempadan dokumen dikekalkan serta ruang yang mencukupi diperuntukkan untuk penaakulan dan jawapan akhir.</p><p>Pengendalian imej berbeza daripada lalai terdahulu. Dalam panduan GPT-5.5 daripada OpenAI, tetapan butiran imej yang tidak dinyatakan atau auto menggunakan tingkah laku original, yang mengekalkan imej tanpa mengubah saiz apabila imej itu berada dalam kedua-dua had yang dinyatakan: bajet 10240000 piksel dan dimensi maksimum 6000 piksel. Tetapan high yang dipilih secara eksplisit mengekalkan butiran dalam kedua-dua had yang dinyatakan: bajet 2500000 piksel dan dimensi maksimum 2048 piksel; low mengubah saiz imej dengan dimensi melebihi 512 piksel secara lebih agresif. Ini ialah tetapan pemprosesan imej, bukannya jaminan bahawa setiap muat naik diterima. Untuk tangkapan skrin, rajah atau halaman, kenal pasti kawasan dan soalan, bekalkan imej yang jelas dan minta pemerhatian atau tafsiran yang diperlukan dan bukannya penerangan tanpa had.</p><p>OpenAI mendokumenkan antara muka Responses, Chat Completions dan Batch, dengan penstriman, Structured Outputs, panggilan fungsi, muat naik fail, input imej, carian fail dan web serta cache prompt. Set alat yang didokumenkan turut merangkumi carian alat, penjanaan imej, pentafsiran kod, shell yang dihoskan, operasi tampalan, kemahiran, penggunaan komputer dan MCP. Terangkan tujuan, argumen, kesan sampingan dan maklumat yang dikembalikan oleh setiap alat aplikasi. Permintaan untuk memanggil fungsi aplikasi memerlukan aplikasi melaksanakan operasi itu dan mengembalikan hasil sebenarnya; cadangan tindakan yang dijana bukan bukti bahawa tindakan itu telah berlaku. Modaliti output model itu sendiri kekal berupa teks, manakala alat penjanaan imej boleh menghasilkan bahan yang berasingan.</p><p>Untuk interaksi yang lebih panjang, kekalkan maklumat yang diperlukan untuk membezakan kerja sementara daripada jawapan yang telah selesai. Panduan OpenAI menerangkan nilai phase pada item assistant untuk jawapan commentary dan final: aplikasi yang memainkan semula item assistant secara manual mesti mengekalkan nilai phase asalnya, manakala rantaian melalui mekanisme respons terdahulu pengeluar mengekalkan keadaan itu secara automatik. Untuk jawapan yang kelihatan, tetapkan panjang, nada dan struktur yang dikehendaki dengan jelas. GPT-5.5 menggunakan gaya ringkas dan langsung secara lalai, dan tahap perincian teks (verbosity) ditetapkan kepada medium secara lalai; hasil padat boleh meminta tahap perincian yang lebih rendah tanpa membuang bukti atau penjelasan bersyarat yang diwajibkan.</p><p>Hasil akhir yang berguna boleh berupa fail yang disemak bersama penjelasan perubahan yang tertumpu, memo keputusan berasaskan dokumen bernama atau pengekstrakan berstruktur dengan nilai yang tiada ditandakan dengan jelas. Bekalkan fakta yang mesti terkini dan bukannya bergantung pada tarikh akhir pengetahuan model, serta bandingkan dakwaan penting dengan bahan asal. Peraturan bukti yang jelas, alat yang terhad dan syarat berhenti yang nyata membantu GPT-5.5 menyelesaikan tugas yang besar sambil mengekalkan hasil yang mudah difahami dan disemak.</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 · Kelompok</b> <code>POST /v1/batches</code></summary><dl class=\"method-capabilities\"><div><dt>Input</dt><dd><code>text</code></dd></div><div><dt>Output</dt><dd><code>text</code></dd></div><div><dt>Format output</dt><dd>JSON results[].response.body sebaris</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\">endpoint</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>/v1/chat/completions</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\">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-5.5:batch</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\">requests</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>batch_item[]</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>Item minimum: 1</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">requests[].custom_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>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\">requests[].body.messages</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>message[]</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Diperlukan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">completion_window</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>24h</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">provider</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>object|null</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">requests[].body.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>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>openai/gpt-5.5:batch, openai/gpt-5.5</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.only</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>string[]</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>openai</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.allow_fallbacks</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span><code>boolean|null</code></td><td data-cell-label=\"Keperluan\"><span class=\"card-cell-label\">Keperluan</span>Pilihan</td><td data-cell-label=\"Nilai &amp; had\"><span class=\"card-cell-label\">Nilai &amp; had</span><div>false, null</div></td><td data-cell-label=\"Lalai\" data-default=\"unspecified\"><span class=\"card-cell-label\">Lalai</span>—</td></tr></tbody></table></div><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>endpoint, model, requests</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>material_types</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>text</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>representation</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>requests[] sebaris; setiap item mempunyai custom_id dan body</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>request_endpoint_profile</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>/v1/chat/completions</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>file_material</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>Pemanggil boleh membaca JSONL UTF-8 sebenar secara setempat ke dalam requests[]. Tiada tujuan muat naik, input_file_id atau rujukan fail digunakan. Bahan pelanggan yang tiada atau kosong menghentikan persediaan sebelum POST.</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>serialization_order</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>endpoint, model, provider (jika dibekalkan), completion_window (jika dibekalkan), requests di akhir</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.only, provider.allow_fallbacks, completion_window</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>schema_scope</code></th><td data-cell-label=\"Kontrak\"><span class=\"card-cell-label\">Kontrak</span>Badan permintaan Chat Completions teks dalam pembungkus Batch sebaris yang didokumenkan.</td></tr></tbody></table></div><p>Kitar hayat: <code>asynchronous</code></p><p class=\"note-s\"><code>GET /v1/batches/{operation_id}</code> · response.id sebenar daripada respons penciptaan asal; pengguna/kunci/kumpulan yang sama</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><dt>Harga cache eksplisit</dt><dd>Tidak diaktifkan <span class=\"note-s\">Apabila cache eksplisit diminta</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>$0.005</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Output · Token output</span> <b>$0.03</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Bacaan cache</span> <b>$0.0005</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Penulisan cache</span> <b>—</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>272,000</td><td data-cell-label=\"Caj\"><span class=\"card-cell-label\">Caj</span><div><span>Input · Token input</span> <b>$0.005</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Output · Token output</span> <b>$0.03</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Bacaan cache</span> <b>$0.0005</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Penulisan cache</span> <b>—</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 2</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>272,000</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>$0.01</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Output · Token output</span> <b>$0.045</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Bacaan cache</span> <b>$0.001</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Input · Penulisan cache</span> <b>—</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 · Kelompok</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-2094-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2094-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl · data ujian yang disimpan</button><button class=\"cg-tab\" id=\"model-code-2094-tab-1\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2094-panel-1\" aria-selected=\"false\" tabindex=\"-1\">Python HTTP · JSONL sebenar pelanggan</button><button class=\"cg-tab\" id=\"model-code-2094-tab-2\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2094-panel-2\" aria-selected=\"false\" tabindex=\"-1\">Python · simpan setiap hasil yang telah siap</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-2094-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-2094-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\npython3 - &lt;&lt;&#39;PY_REQUEST&#39;\nimport json\nfrom pathlib import Path\nbody=json.loads(&#39;{&quot;endpoint&quot;:&quot;/v1/chat/completions&quot;,&quot;model&quot;:&quot;openai/gpt-5.5:batch&quot;,&quot;requests&quot;:[{&quot;custom_id&quot;:&quot;req-0001&quot;,&quot;body&quot;:{&quot;messages&quot;:[{&quot;role&quot;:&quot;user&quot;,&quot;content&quot;:&quot;Hello!&quot;}],&quot;max_tokens&quot;:16}}]}&#39;)\nPath(&quot;batch-request.json&quot;).write_text(json.dumps(body,ensure_ascii=False),encoding=&quot;utf-8&quot;)\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/batches \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -H &#39;Content-Type: application/json&#39; \\\n  --data-binary @batch-request.json -D batch-response-headers.txt -o batch-create-response.json\n</code></pre></div><div class=\"cg-pane\" id=\"model-code-2094-panel-1\" role=\"tabpanel\" aria-labelledby=\"model-code-2094-tab-1\" hidden><pre data-lang=\"python\"><code>import json, os\nfrom pathlib import Path\nfrom urllib.request import Request, urlopen\n\ndef prepare_requests(customer_path):\n    path = Path(customer_path)\n    if not path.is_file(): raise ValueError(&quot;Customer JSONL file is missing&quot;)\n    items = [json.loads(line) for line in path.read_text(encoding=&quot;utf-8&quot;).splitlines() if line.strip()]\n    if not items: raise ValueError(&quot;Customer JSONL contains no requests&quot;)\n    ids = set()\n    for item in items:\n        if set(item) != {&quot;custom_id&quot;, &quot;body&quot;}: raise ValueError(&quot;Each item needs custom_id and body&quot;)\n        cid = item[&quot;custom_id&quot;]\n        if not isinstance(cid, str) or not cid.strip() or cid in ids: raise ValueError(&quot;custom_id must be nonempty and unique&quot;)\n        ids.add(cid)\n        if not isinstance(item[&quot;body&quot;], dict) or not item[&quot;body&quot;].get(&quot;messages&quot;): raise ValueError(&quot;Supply actual text messages&quot;)\n        supplied_model = item[&quot;body&quot;].get(&quot;model&quot;)\n        if supplied_model is not None and supplied_model not in [&#39;openai/gpt-5.5:batch&#39;, &#39;openai/gpt-5.5&#39;]: raise ValueError(&quot;body.model must be an exact documented caller or wire ID&quot;)\n    return {&quot;endpoint&quot;:&quot;/v1/chat/completions&quot;, &quot;model&quot;:&quot;openai/gpt-5.5:batch&quot;, &quot;requests&quot;:items}\n\nif __name__ == &quot;__main__&quot;:\n    material = os.environ.get(&quot;AILOOT_BATCH_REQUESTS_JSONL&quot;, &quot;&quot;)\n    if not material: raise SystemExit(&quot;Set AILOOT_BATCH_REQUESTS_JSONL to your actual customer file&quot;)\n    body = prepare_requests(material)\n    key = os.environ.get(&quot;AILOOT_API_KEY&quot;, &quot;&quot;)\n    if not key: raise SystemExit(&quot;Set AILOOT_API_KEY&quot;)\n    request = Request(&quot;https://api.ailoot.ai/v1/batches&quot;, data=json.dumps(body, ensure_ascii=False).encode(&quot;utf-8&quot;), headers={&quot;Authorization&quot;:&quot;Bearer &quot; + key, &quot;Content-Type&quot;:&quot;application/json&quot;}, method=&quot;POST&quot;)\n    with urlopen(request) as response:\n        raw = response.read()\n        Path(&quot;batch-create-response.json&quot;).write_bytes(raw)\n        print(raw.decode(&quot;utf-8&quot;))\n</code></pre></div><div class=\"cg-pane\" id=\"model-code-2094-panel-2\" role=\"tabpanel\" aria-labelledby=\"model-code-2094-tab-2\" hidden><pre data-lang=\"python\"><code>import json\nfrom pathlib import Path\nraw = Path(&quot;batch-status-response.json&quot;).read_bytes()\nresponse = json.loads(raw)\nif response.get(&quot;status&quot;) != &quot;completed&quot;:\n    raise SystemExit(&quot;Keep the original operation; read its status without resubmitting&quot;)\nresults = response.get(&quot;results&quot;)\nif not isinstance(results, list) or not results:\n    raise SystemExit(&quot;Preserve the original response; completed results are missing&quot;)\nPath(&quot;batch-results.jsonl&quot;).write_text(&quot;&quot;.join(json.dumps(item, ensure_ascii=False) + &quot;\\n&quot; for item in results), encoding=&quot;utf-8&quot;)\n# Preserve batch-status-response.json with aggregate usage and every result/error.\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 · Kelompok</h4><p class=\"note-s\">JSON results[].response.body sebaris</p><ul class=\"card-result-paths\"><li><code>GET /v1/batches/{operation_id}</code></li></ul><h5>Semak status tugas</h5><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-2095-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2095-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl · status operasi asal</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-2095-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-2095-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\nBATCH_OPERATION_ID=&quot;$(python3 - &lt;&lt;&#39;PY_ID&#39;\nimport json\nfrom pathlib import Path\nfrom urllib.parse import quote\nresponse = json.loads(Path(&quot;batch-create-response.json&quot;).read_text(encoding=&quot;utf-8&quot;))\noperation = response.get(&quot;id&quot;)\nif not isinstance(operation, str) or not operation: raise SystemExit(&quot;No actual original operation ID; preserve the response and do not resubmit&quot;)\nprint(quote(operation, safe=&quot;&quot;))\nPY_ID\n)&quot;\ncurl --fail-with-body --silent --show-error &quot;https://api.ailoot.ai/v1/batches/$BATCH_OPERATION_ID&quot; \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -o batch-status-response.json\n</code></pre></div></div></div><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\">Simpan keseluruhan JSON status asal, setiap hasil/custom_id serta badan respons atau ralat yang lengkap. Simpan results[] yang telah selesai sebagai JSONL tanpa penapisan.</p></div><div class=\"card-result-process\" data-unknown-recovery><h5>Jika respons asal perlu disemak</h5><p class=\"note-s\">Simpan ID operasi asal. 503 result_pending_check mempunyai X-Should-Retry:false; jangan sekali-kali hantar semula kelompok asal yang hasilnya tidak diketahui.</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\">results[].custom_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\">results[].response.body.choices[].message.content</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>string|null</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">results[].error</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>object|null</td></tr><tr><th data-cell-label=\"Medan\" scope=\"row\"><span class=\"card-cell-label\">Medan</span><code class=\"card-field-name\">usage</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>object|null</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\">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\">endpoint</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\">status</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\">request_counts</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\">results[].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\">results[].response.status_code</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\">results[].response.request_id</code></th><td data-cell-label=\"Jenis\" data-field-type><span class=\"card-cell-label\">Jenis</span>string</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>Pembungkus sebaris yang didokumenkan tidak sah, kunci berulang, identiti item atau keupayaan model yang dikonfigurasikan bercanggah.</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Betulkan medan yang dinyatakan sebelum sebarang penghantaran baharu.</td></tr><tr><th data-cell-label=\"Respons\" scope=\"row\"><span class=\"card-cell-label\">Respons</span>401 · <code>authentication_error</code></th><td data-cell-label=\"Syarat\"><span class=\"card-cell-label\">Syarat</span>Kunci API tidak sah.</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Gunakan kunci Ailoot yang dibenarkan.</td></tr><tr><th data-cell-label=\"Respons\" scope=\"row\"><span class=\"card-cell-label\">Respons</span>403 · <code>permission_error</code></th><td data-cell-label=\"Syarat\"><span class=\"card-cell-label\">Syarat</span>Kumpulan kelompok tidak tersedia.</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Semak hak akses kunci/kumpulan.</td></tr><tr><th data-cell-label=\"Respons\" scope=\"row\"><span class=\"card-cell-label\">Respons</span>422 · <code>invalid_request_error</code></th><td data-cell-label=\"Syarat\"><span class=\"card-cell-label\">Syarat</span>Kelompok menggunakan pengebilan baki; penciptaan melalui langganan ditolak.</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Gunakan kumpulan yang dibenarkan untuk pengebilan melalui baki.</td></tr><tr><th data-cell-label=\"Respons\" scope=\"row\"><span class=\"card-cell-label\">Respons</span>422 · <code>price_unavailable</code></th><td data-cell-label=\"Syarat\"><span class=\"card-cell-label\">Syarat</span>Sebut harga tidak dapat diberikan untuk input kelompok.</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Simpan respons; gunakan input keluarga API yang didokumenkan.</td></tr><tr><th data-cell-label=\"Respons\" scope=\"row\"><span class=\"card-cell-label\">Respons</span>402 · <code>billing_error</code></th><td data-cell-label=\"Syarat\"><span class=\"card-cell-label\">Syarat</span>Rizab kelompok tidak tersedia.</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Selesaikan isu penerimaan permintaan sebelum menghantar permintaan baharu.</td></tr><tr><th data-cell-label=\"Respons\" scope=\"row\"><span class=\"card-cell-label\">Respons</span>503 · <code>price_unavailable</code></th><td data-cell-label=\"Syarat\"><span class=\"card-cell-label\">Syarat</span>Harga kaedah kelompok/kadar natif tidak tersedia.</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Simpan respons; jangan gantikan harga.</td></tr><tr><th data-cell-label=\"Respons\" scope=\"row\"><span class=\"card-cell-label\">Respons</span>503 · <code>api_error</code></th><td data-cell-label=\"Syarat\"><span class=\"card-cell-label\">Syarat</span>Laluan pembekal yang tepat tidak tersedia.</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Simpan respons untuk pembaikan laluan.</td></tr><tr><th data-cell-label=\"Respons\" scope=\"row\"><span class=\"card-cell-label\">Respons</span>503 · <code>result_pending_check</code></th><td data-cell-label=\"Syarat\"><span class=\"card-cell-label\">Syarat</span>Hasil asal memerlukan semakan; X-Should-Retry:false.</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Simpan operation_id/id asal dan baca statusnya; jangan sekali-kali ulang POST asal.</td></tr><tr><th data-cell-label=\"Respons\" scope=\"row\"><span class=\"card-cell-label\">Respons</span>404 · <code>not_found</code></th><td data-cell-label=\"Syarat\"><span class=\"card-cell-label\">Syarat</span>Operasi status kelompok tiada atau dimiliki oleh identiti lain.</td><td data-cell-label=\"Langkah seterusnya\"><span class=\"card-cell-label\">Langkah seterusnya</span>Gunakan id asal yang tepat serta pengguna/kunci/kumpulan yang sama.</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-5.5%3Abatch&amp;route=Ultra&amp;caller=openai%2Fgpt-5.5%3Abatch&amp;fmt=batches\"><code>openai/gpt-5.5:batch</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-5.5%3Abatch&amp;route=Ultra&amp;caller=openai%2Fgpt-5.5%3Abatch&amp;fmt=batches\"><code>openai/gpt-5.5:batch</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "openai/gpt-5.5:batch",
        "fmt": "batches",
        "http": "POST",
        "path": "/v1/batches",
        "request_model_id": "openai/gpt-5.5:batch",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|batches|/v1/batches|openai%2Fgpt-5.5%3Abatch",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "cache_read": 0.5,
        "cache_write": null,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Preserve full JSON and every result; provider real IDs are only read from actual returned responses.",
            "authentication": {
              "api_key_source": "AILOOT_API_KEY",
              "header": "Authorization: Bearer"
            },
            "errors": [
              {
                "code": null,
                "condition": "Pembungkus sebaris yang didokumenkan tidak sah, kunci berulang, identiti item atau keupayaan model yang dikonfigurasikan bercanggah.",
                "http_status": 400,
                "recovery": "Betulkan medan yang dinyatakan sebelum sebarang penghantaran baharu.",
                "type": "invalid_request_error"
              },
              {
                "code": null,
                "condition": "Kunci API tidak sah.",
                "http_status": 401,
                "recovery": "Gunakan kunci Ailoot yang dibenarkan.",
                "type": "authentication_error"
              },
              {
                "code": null,
                "condition": "Kumpulan kelompok tidak tersedia.",
                "http_status": 403,
                "recovery": "Semak hak akses kunci/kumpulan.",
                "type": "permission_error"
              },
              {
                "code": null,
                "condition": "Kelompok menggunakan pengebilan baki; penciptaan melalui langganan ditolak.",
                "http_status": 422,
                "recovery": "Gunakan kumpulan yang dibenarkan untuk pengebilan melalui baki.",
                "type": "invalid_request_error"
              },
              {
                "code": null,
                "condition": "Sebut harga tidak dapat diberikan untuk input kelompok.",
                "http_status": 422,
                "recovery": "Simpan respons; gunakan input keluarga API yang didokumenkan.",
                "type": "price_unavailable"
              },
              {
                "code": null,
                "condition": "Rizab kelompok tidak tersedia.",
                "http_status": 402,
                "recovery": "Selesaikan isu penerimaan permintaan sebelum menghantar permintaan baharu.",
                "type": "billing_error"
              },
              {
                "code": null,
                "condition": "Harga kaedah kelompok/kadar natif tidak tersedia.",
                "http_status": 503,
                "recovery": "Simpan respons; jangan gantikan harga.",
                "type": "price_unavailable"
              },
              {
                "code": null,
                "condition": "Laluan pembekal yang tepat tidak tersedia.",
                "http_status": 503,
                "recovery": "Simpan respons untuk pembaikan laluan.",
                "type": "api_error"
              },
              {
                "code": "result_pending_check",
                "condition": "Hasil asal memerlukan semakan; X-Should-Retry:false.",
                "http_status": 503,
                "recovery": "Simpan operation_id/id asal dan baca statusnya; jangan sekali-kali ulang POST asal.",
                "type": null
              },
              {
                "code": "not_found",
                "condition": "Operasi status kelompok tiada atau dimiliki oleh identiti lain.",
                "http_status": 404,
                "recovery": "Gunakan id asal yang tepat serta pengguna/kunci/kumpulan yang sama.",
                "type": null
              }
            ],
            "example_body": {
              "endpoint": "/v1/chat/completions",
              "model": "openai/gpt-5.5:batch",
              "requests": [
                {
                  "body": {
                    "max_tokens": 16,
                    "messages": [
                      {
                        "content": "Hello!",
                        "role": "user"
                      }
                    ]
                  },
                  "custom_id": "req-0001"
                }
              ]
            },
            "input_constraints": [
              "Use the exact shown :batch model ID.",
              "Each custom_id must be nonempty and unique within the batch.",
              "Keep requests last in the serialized body; duplicate JSON keys are rejected.",
              "Each body.model is omitted or equals the exact batch caller or its documented base ID.",
              "Per-item provider, service_tier and input_type are outside this batch profile.",
              "stream is omitted or false.",
              "Supply text messages for this Chat batch profile; image/audio/file/video objects, hosted tools and cache-control fields are outside this profile.",
              "If body.model is present, use only the exact caller or wire ID listed here; no suffix conversion is needed.",
              "For google/ wire IDs, all items use an identical response_format."
            ],
            "outputs": {
              "all_results": "Simpan keseluruhan JSON status asal, setiap hasil/custom_id serta badan respons atau ralat yang lengkap. Simpan results[] yang telah selesai sebagai JSONL tanpa penapisan.",
              "enclosing_family": "batch",
              "family": "text",
              "fields": [
                {
                  "name": "results[].custom_id",
                  "type": "string"
                },
                {
                  "name": "results[].response.body.choices[].message.content",
                  "type": "string|null"
                },
                {
                  "name": "results[].error",
                  "type": "object|null"
                },
                {
                  "name": "usage",
                  "type": "object|null"
                },
                {
                  "description": null,
                  "name": "id",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "model",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "endpoint",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "status",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "request_counts",
                  "type": "object"
                },
                {
                  "description": null,
                  "name": "results[].id",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "results[].response.status_code",
                  "type": "integer"
                },
                {
                  "description": null,
                  "name": "results[].response.request_id",
                  "type": "string"
                }
              ],
              "format": "JSON results[].response.body sebaris"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "/v1/chat/completions"
                ],
                "enum_known": true,
                "name": "endpoint",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "openai/gpt-5.5:batch"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "min_items": 1,
                "name": "requests",
                "required": true,
                "type": "batch_item[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "requests[].custom_id",
                "required": true,
                "type": "string",
                "unique_within_batch": true
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "requests[].body.messages",
                "required": true,
                "type": "message[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "24h"
                ],
                "enum_known": true,
                "name": "completion_window",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "provider",
                "required": false,
                "type": "object|null"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "openai/gpt-5.5:batch",
                  "openai/gpt-5.5"
                ],
                "enum_known": true,
                "name": "requests[].body.model",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  [
                    "openai"
                  ]
                ],
                "enum_known": true,
                "name": "provider.only",
                "required": false,
                "type": "string[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  false,
                  null
                ],
                "enum_known": true,
                "name": "provider.allow_fallbacks",
                "required": false,
                "type": "boolean|null"
              }
            ],
            "provider_policy": {
              "allow_fallbacks": false,
              "configured_only": [
                "openai"
              ],
              "per_item_override": false,
              "when_omitted": "Current Source injects the exact persisted declaration before fresh submission."
            },
            "request_schema": {
              "additionalProperties": false,
              "properties": {
                "completion_window": {
                  "enum": [
                    "24h"
                  ],
                  "type": "string"
                },
                "endpoint": {
                  "enum": [
                    "/v1/chat/completions"
                  ],
                  "type": "string"
                },
                "model": {
                  "enum": [
                    "openai/gpt-5.5:batch"
                  ],
                  "type": "string"
                },
                "provider": {
                  "additionalProperties": false,
                  "properties": {
                    "allow_fallbacks": {
                      "enum": [
                        false,
                        null
                      ],
                      "type": [
                        "boolean",
                        "null"
                      ]
                    },
                    "only": {
                      "enum": [
                        [
                          "openai"
                        ]
                      ],
                      "items": {
                        "enum": [
                          "openai"
                        ],
                        "type": "string"
                      },
                      "maxItems": 1,
                      "minItems": 1,
                      "type": "array"
                    }
                  },
                  "type": [
                    "object",
                    "null"
                  ]
                },
                "requests": {
                  "items": {
                    "additionalProperties": false,
                    "properties": {
                      "body": {
                        "additionalProperties": true,
                        "properties": {
                          "max_tokens": {
                            "minimum": 1,
                            "type": "integer"
                          },
                          "messages": {
                            "items": {
                              "properties": {
                                "content": {
                                  "type": "string"
                                },
                                "role": {
                                  "type": "string"
                                }
                              },
                              "required": [
                                "role",
                                "content"
                              ],
                              "type": "object"
                            },
                            "minItems": 1,
                            "type": "array"
                          },
                          "model": {
                            "enum": [
                              "openai/gpt-5.5:batch",
                              "openai/gpt-5.5"
                            ],
                            "type": "string"
                          }
                        },
                        "required": [
                          "messages"
                        ],
                        "type": "object"
                      },
                      "custom_id": {
                        "minLength": 1,
                        "type": "string"
                      }
                    },
                    "required": [
                      "custom_id",
                      "body"
                    ],
                    "type": "object"
                  },
                  "minItems": 1,
                  "type": "array"
                }
              },
              "required": [
                "endpoint",
                "model",
                "requests"
              ],
              "type": "object"
            },
            "schema_template": {
              "endpoint": "/v1/chat/completions",
              "model": "openai/gpt-5.5:batch",
              "requests": [
                {
                  "body": {
                    "max_tokens": 16,
                    "messages": [
                      {
                        "content": "Hello!",
                        "role": "user"
                      }
                    ]
                  },
                  "custom_id": "req-0001"
                }
              ]
            },
            "unsupported": [
              "Files/input_file_id batch upload workflow",
              "active cancel route",
              "public batch list/delete/result-download route",
              "model-name-derived capability or weights equivalence"
            ]
          },
          "input": {
            "content_type": "application/json",
            "file_material": "Pemanggil boleh membaca JSONL UTF-8 sebenar secara setempat ke dalam requests[]. Tiada tujuan muat naik, input_file_id atau rujukan fail digunakan. Bahan pelanggan yang tiada atau kosong menghentikan persediaan sebelum POST.",
            "material_types": [
              "text"
            ],
            "optional_controls": [
              "provider.only",
              "provider.allow_fallbacks",
              "completion_window"
            ],
            "representation": "requests[] sebaris; setiap item mempunyai custom_id dan body",
            "request_endpoint_profile": "/v1/chat/completions",
            "required": [
              "endpoint",
              "model",
              "requests"
            ],
            "schema_scope": "Badan permintaan Chat Completions teks dalam pembungkus Batch sebaris yang didokumenkan.",
            "serialization_order": [
              "endpoint",
              "model",
              "provider (jika dibekalkan)",
              "completion_window (jika dibekalkan)",
              "requests di akhir"
            ]
          },
          "lifecycle": {
            "cancel": null,
            "create": {
              "accepted_status": 202,
              "http": "POST",
              "path": "/v1/batches"
            },
            "delete": null,
            "file_upload": null,
            "mode": "asynchronous",
            "observed_status_values": [
              "validating",
              "in_progress",
              "finalizing",
              "completed",
              "failed",
              "expired",
              "cancelling",
              "cancelled"
            ],
            "owned_results": {
              "behavior": "Completed results are saved as owned JSONL, read back byte-for-byte and registered in the existing media library before publication after settlement. Status returns inline results; no separate Batch download route is added.",
              "format": "application/x-ndjson",
              "public_url_field_in_status": null
            },
            "status": {
              "http": "GET",
              "id_source": "response.id sebenar daripada respons penciptaan asal; pengguna/kunci/kumpulan yang sama",
              "path": "/v1/batches/{operation_id}"
            },
            "terminal": [
              "completed",
              "failed",
              "expired",
              "cancelled"
            ],
            "unknown": "Simpan ID operasi asal. 503 result_pending_check mempunyai X-Should-Retry:false; jangan sekali-kali hantar semula kelompok asal yang hasilnya tidak diketahui."
          },
          "manufacturer_capability": null,
          "method": {
            "http": "POST",
            "path": "/v1/batches"
          },
          "output": {
            "all_results": "Preserve the full original status JSON, every result/custom_id and complete response or error body. Save completed results[] as JSONL without filtering.",
            "family": "batch",
            "format": "JSON; completed results[] are returned inline and can be saved as JSONL."
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Kadar asas token",
            "units": [
              {
                "amount": "0.005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000005",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.03000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00003",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0.0005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000005",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "max_context_tokens_inclusive": 272000,
              "min_context_tokens_exclusive": 0
            },
            "label": "Tahap panjang permintaan 1",
            "units": [
              {
                "amount": "0.005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000005",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.03000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00003",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0.0005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000005",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "max_context_tokens_inclusive": null,
              "min_context_tokens_exclusive": 272000
            },
            "label": "Tahap panjang permintaan 2",
            "units": [
              {
                "amount": "0.01000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.00001",
                "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": "0.045000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.000045",
                "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": "0.001000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.000001",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json\nfrom pathlib import Path\nbody=json.loads('{\"endpoint\":\"/v1/chat/completions\",\"model\":\"openai/gpt-5.5:batch\",\"requests\":[{\"custom_id\":\"req-0001\",\"body\":{\"messages\":[{\"role\":\"user\",\"content\":\"Hello!\"}],\"max_tokens\":16}}]}')\nPath(\"batch-request.json\").write_text(json.dumps(body,ensure_ascii=False),encoding=\"utf-8\")\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/batches \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @batch-request.json -D batch-response-headers.txt -o batch-create-response.json\n",
            "label": "curl · retained fixture",
            "language": "bash"
          },
          {
            "code": "import json, os\nfrom pathlib import Path\nfrom urllib.request import Request, urlopen\n\ndef prepare_requests(customer_path):\n    path = Path(customer_path)\n    if not path.is_file(): raise ValueError(\"Customer JSONL file is missing\")\n    items = [json.loads(line) for line in path.read_text(encoding=\"utf-8\").splitlines() if line.strip()]\n    if not items: raise ValueError(\"Customer JSONL contains no requests\")\n    ids = set()\n    for item in items:\n        if set(item) != {\"custom_id\", \"body\"}: raise ValueError(\"Each item needs custom_id and body\")\n        cid = item[\"custom_id\"]\n        if not isinstance(cid, str) or not cid.strip() or cid in ids: raise ValueError(\"custom_id must be nonempty and unique\")\n        ids.add(cid)\n        if not isinstance(item[\"body\"], dict) or not item[\"body\"].get(\"messages\"): raise ValueError(\"Supply actual text messages\")\n        supplied_model = item[\"body\"].get(\"model\")\n        if supplied_model is not None and supplied_model not in ['openai/gpt-5.5:batch', 'openai/gpt-5.5']: raise ValueError(\"body.model must be an exact documented caller or wire ID\")\n    return {\"endpoint\":\"/v1/chat/completions\", \"model\":\"openai/gpt-5.5:batch\", \"requests\":items}\n\nif __name__ == \"__main__\":\n    material = os.environ.get(\"AILOOT_BATCH_REQUESTS_JSONL\", \"\")\n    if not material: raise SystemExit(\"Set AILOOT_BATCH_REQUESTS_JSONL to your actual customer file\")\n    body = prepare_requests(material)\n    key = os.environ.get(\"AILOOT_API_KEY\", \"\")\n    if not key: raise SystemExit(\"Set AILOOT_API_KEY\")\n    request = Request(\"https://api.ailoot.ai/v1/batches\", data=json.dumps(body, ensure_ascii=False).encode(\"utf-8\"), headers={\"Authorization\":\"Bearer \" + key, \"Content-Type\":\"application/json\"}, method=\"POST\")\n    with urlopen(request) as response:\n        raw = response.read()\n        Path(\"batch-create-response.json\").write_bytes(raw)\n        print(raw.decode(\"utf-8\"))\n",
            "label": "Python HTTP · actual customer JSONL",
            "language": "python"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nBATCH_OPERATION_ID=\"$(python3 - <<'PY_ID'\nimport json\nfrom pathlib import Path\nfrom urllib.parse import quote\nresponse = json.loads(Path(\"batch-create-response.json\").read_text(encoding=\"utf-8\"))\noperation = response.get(\"id\")\nif not isinstance(operation, str) or not operation: raise SystemExit(\"No actual original operation ID; preserve the response and do not resubmit\")\nprint(quote(operation, safe=\"\"))\nPY_ID\n)\"\ncurl --fail-with-body --silent --show-error \"https://api.ailoot.ai/v1/batches/$BATCH_OPERATION_ID\" \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -o batch-status-response.json\n",
            "label": "curl · original operation status",
            "language": "bash"
          },
          {
            "code": "import json\nfrom pathlib import Path\nraw = Path(\"batch-status-response.json\").read_bytes()\nresponse = json.loads(raw)\nif response.get(\"status\") != \"completed\":\n    raise SystemExit(\"Keep the original operation; read its status without resubmitting\")\nresults = response.get(\"results\")\nif not isinstance(results, list) or not results:\n    raise SystemExit(\"Preserve the original response; completed results are missing\")\nPath(\"batch-results.jsonl\").write_text(\"\".join(json.dumps(item, ensure_ascii=False) + \"\\n\" for item in results), encoding=\"utf-8\")\n# Preserve batch-status-response.json with aggregate usage and every result/error.\n",
            "label": "Python · save every completed result",
            "language": "python"
          }
        ],
        "family": "batch",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "batches",
        "hints": [
          "Read your actual request items before submission; inline requests are required.",
          "Keep the returned operation ID and every result. Never replay an unknown submission."
        ],
        "http": "POST",
        "in": 5,
        "input": [
          "text"
        ],
        "label": "Kelompok",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "out": 30,
        "output": [
          "text"
        ],
        "path": "/v1/batches",
        "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"
          },
          {
            "label": "Explicit cache pricing",
            "value": "Not enabled",
            "when": "When explicit cache is requested"
          }
        ],
        "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": "0.005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000005",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.03000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00003",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0.0005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000005",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "max_context_tokens_inclusive": 272000,
              "min_context_tokens_exclusive": 0
            },
            "label": "Request-length tier 1",
            "units": [
              {
                "amount": "0.005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000005",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.03000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00003",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0.0005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000005",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
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    "about": "GPT-5.5 ialah model penaakulan perdana OpenAI untuk kerja profesional yang kompleks dan pengaturcaraan. Model ini menerima teks dan imej serta mengembalikan teks, dengan menggabungkan analisis dan penggunaan alat apabila tugas memerlukan maklumat atau tindakan di luar arahan yang dibekalkan. Panduan OpenAI menekankan kerja berdasarkan hasil yang jelas: terangkan hasil yang diperlukan, kekangan yang mesti dipatuhi, bukti yang perlu digunakan dan syarat yang menamatkan tugas.\n\nUntuk perubahan perisian yang besar, sediakan bahan repositori yang berkaitan, tingkah laku semasa, tingkah laku yang dikehendaki dan kriteria penerimaan. Kenal pasti perkara yang boleh diubah dan perkara yang mesti kekal serasi. Hasil yang berguna untuk diminta ialah cadangan perubahan, penjelasan tentang tingkah laku yang terjejas dan bukti daripada pemeriksaan yang benar-benar dijalankan. Untuk tugas yang banyak melibatkan dokumen, labelkan dokumen sumber dan minta jawapan yang disusun berdasarkan keputusan yang perlu dibuat, dengan setiap kesimpulan dikaitkan dengan bukti yang dibekalkan serta soalan yang belum selesai dipisahkan daripada fakta yang telah ditetapkan.\n\nGPT-5.5 menyokong usaha penaakulan none, low, medium, high dan xhigh, dengan medium sebagai lalai. OpenAI mengesyorkan agar low dipertimbangkan sebelum none apabila aliran kerja yang responsif masih memerlukan perancangan, carian atau beberapa panggilan alat. none sesuai untuk tugas langsung yang tidak memerlukan proses penaakulan itu. Usaha lebih tinggi tidak semestinya lebih baik: keperluan yang bercanggah, akses alat tanpa had yang jelas atau peraturan berhenti yang kabur boleh menyebabkan carian dan pemikiran berlebihan yang tidak perlu. Pilih usaha mengikut tugas sebenar dan nyatakan hasil akhir serta kriteria penyiapan yang dijangkakan dengan jelas.\n\nPengeluar menyenaraikan tetingkap konteks 1050000 token dan output maksimum 128000 token, dengan tarikh akhir pengetahuan pada 1 Disember 2025. Konteks menampung perbualan, bahan yang dibekalkan dan kandungan yang dijana; konteks bukan kuota berasingan untuk ditambahkan kepada output maksimum. Penaakulan dalaman turut menggunakan token dan kapasiti output. Oleh itu, kumpulan sumber yang besar perlu disusun berdasarkan soalan, dengan pengecam penting, unit dan sempadan dokumen dikekalkan serta ruang yang mencukupi diperuntukkan untuk penaakulan dan jawapan akhir.\n\nPengendalian imej berbeza daripada lalai terdahulu. Dalam panduan GPT-5.5 daripada OpenAI, tetapan butiran imej yang tidak dinyatakan atau auto menggunakan tingkah laku original, yang mengekalkan imej tanpa mengubah saiz apabila imej itu berada dalam kedua-dua had yang dinyatakan: bajet 10240000 piksel dan dimensi maksimum 6000 piksel. Tetapan high yang dipilih secara eksplisit mengekalkan butiran dalam kedua-dua had yang dinyatakan: bajet 2500000 piksel dan dimensi maksimum 2048 piksel; low mengubah saiz imej dengan dimensi melebihi 512 piksel secara lebih agresif. Ini ialah tetapan pemprosesan imej, bukannya jaminan bahawa setiap muat naik diterima. Untuk tangkapan skrin, rajah atau halaman, kenal pasti kawasan dan soalan, bekalkan imej yang jelas dan minta pemerhatian atau tafsiran yang diperlukan dan bukannya penerangan tanpa had.\n\nOpenAI mendokumenkan antara muka Responses, Chat Completions dan Batch, dengan penstriman, Structured Outputs, panggilan fungsi, muat naik fail, input imej, carian fail dan web serta cache prompt. Set alat yang didokumenkan turut merangkumi carian alat, penjanaan imej, pentafsiran kod, shell yang dihoskan, operasi tampalan, kemahiran, penggunaan komputer dan MCP. Terangkan tujuan, argumen, kesan sampingan dan maklumat yang dikembalikan oleh setiap alat aplikasi. Permintaan untuk memanggil fungsi aplikasi memerlukan aplikasi melaksanakan operasi itu dan mengembalikan hasil sebenarnya; cadangan tindakan yang dijana bukan bukti bahawa tindakan itu telah berlaku. Modaliti output model itu sendiri kekal berupa teks, manakala alat penjanaan imej boleh menghasilkan bahan yang berasingan.\n\nUntuk interaksi yang lebih panjang, kekalkan maklumat yang diperlukan untuk membezakan kerja sementara daripada jawapan yang telah selesai. Panduan OpenAI menerangkan nilai phase pada item assistant untuk jawapan commentary dan final: aplikasi yang memainkan semula item assistant secara manual mesti mengekalkan nilai phase asalnya, manakala rantaian melalui mekanisme respons terdahulu pengeluar mengekalkan keadaan itu secara automatik. Untuk jawapan yang kelihatan, tetapkan panjang, nada dan struktur yang dikehendaki dengan jelas. GPT-5.5 menggunakan gaya ringkas dan langsung secara lalai, dan tahap perincian teks (verbosity) ditetapkan kepada medium secara lalai; hasil padat boleh meminta tahap perincian yang lebih rendah tanpa membuang bukti atau penjelasan bersyarat yang diwajibkan.\n\nHasil akhir yang berguna boleh berupa fail yang disemak bersama penjelasan perubahan yang tertumpu, memo keputusan berasaskan dokumen bernama atau pengekstrakan berstruktur dengan nilai yang tiada ditandakan dengan jelas. Bekalkan fakta yang mesti terkini dan bukannya bergantung pada tarikh akhir pengetahuan model, serta bandingkan dakwaan penting dengan bahan asal. Peraturan bukti yang jelas, alat yang terhad dan syarat berhenti yang nyata membantu GPT-5.5 menyelesaikan tugas yang besar sambil mengekalkan hasil yang mudah difahami dan disemak.",
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            "example_body": {
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              "Per-item provider, service_tier and input_type are outside this batch profile.",
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              "If body.model is present, use only the exact caller or wire ID listed here; no suffix conversion is needed.",
              "For google/ wire IDs, all items use an identical response_format."
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                {
                  "description": null,
                  "name": "results[].response.request_id",
                  "type": "string"
                }
              ],
              "format": "JSON results[].response.body sebaris"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "/v1/chat/completions"
                ],
                "enum_known": true,
                "name": "endpoint",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "openai/gpt-5.5:batch"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "min_items": 1,
                "name": "requests",
                "required": true,
                "type": "batch_item[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "requests[].custom_id",
                "required": true,
                "type": "string",
                "unique_within_batch": true
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "requests[].body.messages",
                "required": true,
                "type": "message[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "24h"
                ],
                "enum_known": true,
                "name": "completion_window",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "provider",
                "required": false,
                "type": "object|null"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "openai/gpt-5.5:batch",
                  "openai/gpt-5.5"
                ],
                "enum_known": true,
                "name": "requests[].body.model",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  [
                    "openai"
                  ]
                ],
                "enum_known": true,
                "name": "provider.only",
                "required": false,
                "type": "string[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  false,
                  null
                ],
                "enum_known": true,
                "name": "provider.allow_fallbacks",
                "required": false,
                "type": "boolean|null"
              }
            ],
            "provider_policy": {
              "allow_fallbacks": false,
              "configured_only": [
                "openai"
              ],
              "per_item_override": false,
              "when_omitted": "Current Source injects the exact persisted declaration before fresh submission."
            },
            "request_schema": {
              "additionalProperties": false,
              "properties": {
                "completion_window": {
                  "enum": [
                    "24h"
                  ],
                  "type": "string"
                },
                "endpoint": {
                  "enum": [
                    "/v1/chat/completions"
                  ],
                  "type": "string"
                },
                "model": {
                  "enum": [
                    "openai/gpt-5.5:batch"
                  ],
                  "type": "string"
                },
                "provider": {
                  "additionalProperties": false,
                  "properties": {
                    "allow_fallbacks": {
                      "enum": [
                        false,
                        null
                      ],
                      "type": [
                        "boolean",
                        "null"
                      ]
                    },
                    "only": {
                      "enum": [
                        [
                          "openai"
                        ]
                      ],
                      "items": {
                        "enum": [
                          "openai"
                        ],
                        "type": "string"
                      },
                      "maxItems": 1,
                      "minItems": 1,
                      "type": "array"
                    }
                  },
                  "type": [
                    "object",
                    "null"
                  ]
                },
                "requests": {
                  "items": {
                    "additionalProperties": false,
                    "properties": {
                      "body": {
                        "additionalProperties": true,
                        "properties": {
                          "max_tokens": {
                            "minimum": 1,
                            "type": "integer"
                          },
                          "messages": {
                            "items": {
                              "properties": {
                                "content": {
                                  "type": "string"
                                },
                                "role": {
                                  "type": "string"
                                }
                              },
                              "required": [
                                "role",
                                "content"
                              ],
                              "type": "object"
                            },
                            "minItems": 1,
                            "type": "array"
                          },
                          "model": {
                            "enum": [
                              "openai/gpt-5.5:batch",
                              "openai/gpt-5.5"
                            ],
                            "type": "string"
                          }
                        },
                        "required": [
                          "messages"
                        ],
                        "type": "object"
                      },
                      "custom_id": {
                        "minLength": 1,
                        "type": "string"
                      }
                    },
                    "required": [
                      "custom_id",
                      "body"
                    ],
                    "type": "object"
                  },
                  "minItems": 1,
                  "type": "array"
                }
              },
              "required": [
                "endpoint",
                "model",
                "requests"
              ],
              "type": "object"
            },
            "schema_template": {
              "endpoint": "/v1/chat/completions",
              "model": "openai/gpt-5.5:batch",
              "requests": [
                {
                  "body": {
                    "max_tokens": 16,
                    "messages": [
                      {
                        "content": "Hello!",
                        "role": "user"
                      }
                    ]
                  },
                  "custom_id": "req-0001"
                }
              ]
            },
            "unsupported": [
              "Files/input_file_id batch upload workflow",
              "active cancel route",
              "public batch list/delete/result-download route",
              "model-name-derived capability or weights equivalence"
            ]
          },
          "input": {
            "content_type": "application/json",
            "file_material": "Pemanggil boleh membaca JSONL UTF-8 sebenar secara setempat ke dalam requests[]. Tiada tujuan muat naik, input_file_id atau rujukan fail digunakan. Bahan pelanggan yang tiada atau kosong menghentikan persediaan sebelum POST.",
            "material_types": [
              "text"
            ],
            "optional_controls": [
              "provider.only",
              "provider.allow_fallbacks",
              "completion_window"
            ],
            "representation": "requests[] sebaris; setiap item mempunyai custom_id dan body",
            "request_endpoint_profile": "/v1/chat/completions",
            "required": [
              "endpoint",
              "model",
              "requests"
            ],
            "schema_scope": "Badan permintaan Chat Completions teks dalam pembungkus Batch sebaris yang didokumenkan.",
            "serialization_order": [
              "endpoint",
              "model",
              "provider (jika dibekalkan)",
              "completion_window (jika dibekalkan)",
              "requests di akhir"
            ]
          },
          "lifecycle": {
            "cancel": null,
            "create": {
              "accepted_status": 202,
              "http": "POST",
              "path": "/v1/batches"
            },
            "delete": null,
            "file_upload": null,
            "mode": "asynchronous",
            "observed_status_values": [
              "validating",
              "in_progress",
              "finalizing",
              "completed",
              "failed",
              "expired",
              "cancelling",
              "cancelled"
            ],
            "owned_results": {
              "behavior": "Completed results are saved as owned JSONL, read back byte-for-byte and registered in the existing media library before publication after settlement. Status returns inline results; no separate Batch download route is added.",
              "format": "application/x-ndjson",
              "public_url_field_in_status": null
            },
            "status": {
              "http": "GET",
              "id_source": "response.id sebenar daripada respons penciptaan asal; pengguna/kunci/kumpulan yang sama",
              "path": "/v1/batches/{operation_id}"
            },
            "terminal": [
              "completed",
              "failed",
              "expired",
              "cancelled"
            ],
            "unknown": "Simpan ID operasi asal. 503 result_pending_check mempunyai X-Should-Retry:false; jangan sekali-kali hantar semula kelompok asal yang hasilnya tidak diketahui."
          },
          "manufacturer_capability": null,
          "method": {
            "http": "POST",
            "path": "/v1/batches"
          },
          "output": {
            "all_results": "Preserve the full original status JSON, every result/custom_id and complete response or error body. Save completed results[] as JSONL without filtering.",
            "family": "batch",
            "format": "JSON; completed results[] are returned inline and can be saved as JSONL."
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Kadar asas token",
            "units": [
              {
                "amount": "0.005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000005",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.03000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00003",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0.0005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000005",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "max_context_tokens_inclusive": 272000,
              "min_context_tokens_exclusive": 0
            },
            "label": "Tahap panjang permintaan 1",
            "units": [
              {
                "amount": "0.005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000005",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.03000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00003",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0.0005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000005",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          },
          {
            "dimensions": {
              "max_context_tokens_inclusive": null,
              "min_context_tokens_exclusive": 272000
            },
            "label": "Tahap panjang permintaan 2",
            "units": [
              {
                "amount": "0.01000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.00001",
                "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": "0.045000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.000045",
                "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": "0.001000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.000001",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json\nfrom pathlib import Path\nbody=json.loads('{\"endpoint\":\"/v1/chat/completions\",\"model\":\"openai/gpt-5.5:batch\",\"requests\":[{\"custom_id\":\"req-0001\",\"body\":{\"messages\":[{\"role\":\"user\",\"content\":\"Hello!\"}],\"max_tokens\":16}}]}')\nPath(\"batch-request.json\").write_text(json.dumps(body,ensure_ascii=False),encoding=\"utf-8\")\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/batches \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @batch-request.json -D batch-response-headers.txt -o batch-create-response.json\n",
            "label": "curl · retained fixture",
            "language": "bash"
          },
          {
            "code": "import json, os\nfrom pathlib import Path\nfrom urllib.request import Request, urlopen\n\ndef prepare_requests(customer_path):\n    path = Path(customer_path)\n    if not path.is_file(): raise ValueError(\"Customer JSONL file is missing\")\n    items = [json.loads(line) for line in path.read_text(encoding=\"utf-8\").splitlines() if line.strip()]\n    if not items: raise ValueError(\"Customer JSONL contains no requests\")\n    ids = set()\n    for item in items:\n        if set(item) != {\"custom_id\", \"body\"}: raise ValueError(\"Each item needs custom_id and body\")\n        cid = item[\"custom_id\"]\n        if not isinstance(cid, str) or not cid.strip() or cid in ids: raise ValueError(\"custom_id must be nonempty and unique\")\n        ids.add(cid)\n        if not isinstance(item[\"body\"], dict) or not item[\"body\"].get(\"messages\"): raise ValueError(\"Supply actual text messages\")\n        supplied_model = item[\"body\"].get(\"model\")\n        if supplied_model is not None and supplied_model not in ['openai/gpt-5.5:batch', 'openai/gpt-5.5']: raise ValueError(\"body.model must be an exact documented caller or wire ID\")\n    return {\"endpoint\":\"/v1/chat/completions\", \"model\":\"openai/gpt-5.5:batch\", \"requests\":items}\n\nif __name__ == \"__main__\":\n    material = os.environ.get(\"AILOOT_BATCH_REQUESTS_JSONL\", \"\")\n    if not material: raise SystemExit(\"Set AILOOT_BATCH_REQUESTS_JSONL to your actual customer file\")\n    body = prepare_requests(material)\n    key = os.environ.get(\"AILOOT_API_KEY\", \"\")\n    if not key: raise SystemExit(\"Set AILOOT_API_KEY\")\n    request = Request(\"https://api.ailoot.ai/v1/batches\", data=json.dumps(body, ensure_ascii=False).encode(\"utf-8\"), headers={\"Authorization\":\"Bearer \" + key, \"Content-Type\":\"application/json\"}, method=\"POST\")\n    with urlopen(request) as response:\n        raw = response.read()\n        Path(\"batch-create-response.json\").write_bytes(raw)\n        print(raw.decode(\"utf-8\"))\n",
            "label": "Python HTTP · actual customer JSONL",
            "language": "python"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nBATCH_OPERATION_ID=\"$(python3 - <<'PY_ID'\nimport json\nfrom pathlib import Path\nfrom urllib.parse import quote\nresponse = json.loads(Path(\"batch-create-response.json\").read_text(encoding=\"utf-8\"))\noperation = response.get(\"id\")\nif not isinstance(operation, str) or not operation: raise SystemExit(\"No actual original operation ID; preserve the response and do not resubmit\")\nprint(quote(operation, safe=\"\"))\nPY_ID\n)\"\ncurl --fail-with-body --silent --show-error \"https://api.ailoot.ai/v1/batches/$BATCH_OPERATION_ID\" \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -o batch-status-response.json\n",
            "label": "curl · original operation status",
            "language": "bash"
          },
          {
            "code": "import json\nfrom pathlib import Path\nraw = Path(\"batch-status-response.json\").read_bytes()\nresponse = json.loads(raw)\nif response.get(\"status\") != \"completed\":\n    raise SystemExit(\"Keep the original operation; read its status without resubmitting\")\nresults = response.get(\"results\")\nif not isinstance(results, list) or not results:\n    raise SystemExit(\"Preserve the original response; completed results are missing\")\nPath(\"batch-results.jsonl\").write_text(\"\".join(json.dumps(item, ensure_ascii=False) + \"\\n\" for item in results), encoding=\"utf-8\")\n# Preserve batch-status-response.json with aggregate usage and every result/error.\n",
            "label": "Python · save every completed result",
            "language": "python"
          }
        ],
        "family": "batch",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "batches",
        "hints": [
          "Read your actual request items before submission; inline requests are required.",
          "Keep the returned operation ID and every result. Never replay an unknown submission."
        ],
        "http": "POST",
        "in": 5,
        "input": [
          "text"
        ],
        "label": "Kelompok",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "out": 30,
        "output": [
          "text"
        ],
        "path": "/v1/batches",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
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            "label": "Explicit cache pricing",
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