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  "aboutHtml": "<p>GPT-5.6 Sol adalah model unggulan OpenAI dalam keluarga GPT-5.6 untuk pekerjaan profesional kompleks. Model ini sepadan dengan tingkat model utama yang digunakan dalam keluarga GPT-5 terdahulu, sekaligus tetap menjadi edisi tersendiri. Model ini menerima teks dan gambar serta menghasilkan teks, termasuk analisis, kode, dokumen, dan temuan berstruktur. Profil standarnya berbeda dari eksekusi penalaran Pro Sol.</p><h4>Menyiapkan pekerjaan yang berat</h4><p>Tentukan hasil, sumber yang relevan, dan kondisi yang harus dipenuhi hasil. Untuk pekerjaan perangkat lunak, berikan berkas atau kutipan yang relevan, perilaku yang diamati, perilaku yang diharapkan, dan batasan. Untuk analisis profesional, tentukan keputusan, kriteria perbandingan, dan bukti. Contoh instruksinya: “Bandingkan pendekatan ini dengan spesifikasi, identifikasi dependensi, dan hasilkan rekomendasi dengan kondisi dari sumber yang mendukung setiap temuan.”</p><p>Jika gambar memuat bukti, beri label dan tentukan bagan, diagram, atau elemen antarmuka yang harus dianalisis. Minta jawaban memisahkan detail yang diamati dari tafsiran. Untuk penulisan atau penyuntingan, berikan pembaca yang dituju dan fakta yang harus dipertahankan, lalu sebutkan artefak akhir serta struktur yang diwajibkan.</p><h4>Upaya, eksekusi, dan konteks yang berlanjut</h4><p>Produsen mendukung upaya none, low, medium, high, xhigh, dan max, dengan medium sebagai nilai bawaan. Mode penalaran standar adalah mode bawaan; Pro menambahkan pekerjaan model untuk tugas sulit. Keduanya merupakan kontrol yang independen, sehingga upaya tidak dengan sendirinya mengubah model yang disebutkan atau menjadikan Pro edisi dasar baru.</p><p>Secara bawaan, profil penalaran GPT-5.6 memasukkan penalaran yang tersedia dari giliran sebelumnya ke langkah berikutnya, dengan pengaturan konteks untuk alur yang didukung. Pertahankan kejelasan persyaratan yang diterima dan pengamatan sepanjang percakapan, serta bedakan gagasan antara dari temuan akhir. Bahan yang dipertahankan tetap menggunakan konteks.</p><h4>Batas dan persiapan sumber</h4><p>Kartu Sol mencantumkan konteks 1050000 token, masukan hingga 922000 token, dan keluaran hingga 128000 token, dengan batas pengetahuan 16 Februari 2026. Penalaran menggunakan ruang respons meskipun tidak ditampilkan sebagai jawaban akhir. Sisakan ruang untuk hasil alat serta artefak yang selesai dan periksa respons yang mencapai anggarannya sebelum menggunakannya.</p><p>Susun dokumen panjang dan kode berdasarkan pertanyaan yang sebenarnya. Simpan label sumber serta batas yang relevan agar kesimpulan dapat mengidentifikasi bahan yang menjadi dasarnya. Untuk fakta terkini, berikan bagian sumber yang otoritatif atau alat pencarian yang sesuai, alih-alih mengandalkan pengetahuan pelatihan dari masa batas pengetahuan.</p><h4>Alat dan keluaran</h4><p>OpenAI mencantumkan Structured Outputs, pengaliran, dan panggilan fungsi. Alat yang didokumentasikan meliputi pencarian web dan berkas, pembuatan gambar, interpreter kode, operasi shell dan patch, keterampilan, penggunaan komputer, koneksi MCP, serta pencarian alat. Aplikasi menyediakan dan mengeksekusi operasinya, mengembalikan pengamatan untuk langkah model berikutnya. Keluaran model sendiri tetap berupa teks, sedangkan media atau tindakan yang dihasilkan alat memiliki hasil tersendiri.</p><p>Berikan tujuan serta skema yang spesifik kepada fungsi. Untuk rekaman data, tentukan makna kolom dan konvensi nilai yang tidak tersedia. Periksa nilai terhadap sumber dan kode terhadap perilaku yang diminta. Serah terima yang berguna menyajikan hasil, bukti, dan kondisi yang belum terselesaikan dengan jelas; usulan operasi atau perintah validasi berbeda dari pekerjaan yang benar-benar dijalankan.</p><p>GPT-5.6 Sol berbeda dari Terra, Luna, dan model GPT-6 sesudahnya; alias gpt-5.6 OpenAI mengarah ke Sol. Pertahankan profil itu ketika tugas bergantung pada batas pengetahuan, kontrol penalaran, atau batas konteksnya.</p>",
  "aboutText": "GPT-5.6 Sol adalah model unggulan OpenAI dalam keluarga GPT-5.6 untuk pekerjaan profesional kompleks. Model ini sepadan dengan tingkat model utama yang digunakan dalam keluarga GPT-5 terdahulu, sekaligus tetap menjadi edisi tersendiri. Model ini menerima teks dan gambar serta menghasilkan teks, termasuk analisis, kode, dokumen, dan temuan berstruktur. Profil standarnya berbeda dari eksekusi penalaran Pro Sol.\n\n### Menyiapkan pekerjaan yang berat\n\nTentukan hasil, sumber yang relevan, dan kondisi yang harus dipenuhi hasil. Untuk pekerjaan perangkat lunak, berikan berkas atau kutipan yang relevan, perilaku yang diamati, perilaku yang diharapkan, dan batasan. Untuk analisis profesional, tentukan keputusan, kriteria perbandingan, dan bukti. Contoh instruksinya: “Bandingkan pendekatan ini dengan spesifikasi, identifikasi dependensi, dan hasilkan rekomendasi dengan kondisi dari sumber yang mendukung setiap temuan.”\n\nJika gambar memuat bukti, beri label dan tentukan bagan, diagram, atau elemen antarmuka yang harus dianalisis. Minta jawaban memisahkan detail yang diamati dari tafsiran. Untuk penulisan atau penyuntingan, berikan pembaca yang dituju dan fakta yang harus dipertahankan, lalu sebutkan artefak akhir serta struktur yang diwajibkan.\n\n### Upaya, eksekusi, dan konteks yang berlanjut\n\nProdusen mendukung upaya none, low, medium, high, xhigh, dan max, dengan medium sebagai nilai bawaan. Mode penalaran standar adalah mode bawaan; Pro menambahkan pekerjaan model untuk tugas sulit. Keduanya merupakan kontrol yang independen, sehingga upaya tidak dengan sendirinya mengubah model yang disebutkan atau menjadikan Pro edisi dasar baru.\n\nSecara bawaan, profil penalaran GPT-5.6 memasukkan penalaran yang tersedia dari giliran sebelumnya ke langkah berikutnya, dengan pengaturan konteks untuk alur yang didukung. Pertahankan kejelasan persyaratan yang diterima dan pengamatan sepanjang percakapan, serta bedakan gagasan antara dari temuan akhir. Bahan yang dipertahankan tetap menggunakan konteks.\n\n### Batas dan persiapan sumber\n\nKartu Sol mencantumkan konteks 1050000 token, masukan hingga 922000 token, dan keluaran hingga 128000 token, dengan batas pengetahuan 16 Februari 2026. Penalaran menggunakan ruang respons meskipun tidak ditampilkan sebagai jawaban akhir. Sisakan ruang untuk hasil alat serta artefak yang selesai dan periksa respons yang mencapai anggarannya sebelum menggunakannya.\n\nSusun dokumen panjang dan kode berdasarkan pertanyaan yang sebenarnya. Simpan label sumber serta batas yang relevan agar kesimpulan dapat mengidentifikasi bahan yang menjadi dasarnya. Untuk fakta terkini, berikan bagian sumber yang otoritatif atau alat pencarian yang sesuai, alih-alih mengandalkan pengetahuan pelatihan dari masa batas pengetahuan.\n\n### Alat dan keluaran\n\nOpenAI mencantumkan Structured Outputs, pengaliran, dan panggilan fungsi. Alat yang didokumentasikan meliputi pencarian web dan berkas, pembuatan gambar, interpreter kode, operasi shell dan patch, keterampilan, penggunaan komputer, koneksi MCP, serta pencarian alat. Aplikasi menyediakan dan mengeksekusi operasinya, mengembalikan pengamatan untuk langkah model berikutnya. Keluaran model sendiri tetap berupa teks, sedangkan media atau tindakan yang dihasilkan alat memiliki hasil tersendiri.\n\nBerikan tujuan serta skema yang spesifik kepada fungsi. Untuk rekaman data, tentukan makna kolom dan konvensi nilai yang tidak tersedia. Periksa nilai terhadap sumber dan kode terhadap perilaku yang diminta. Serah terima yang berguna menyajikan hasil, bukti, dan kondisi yang belum terselesaikan dengan jelas; usulan operasi atau perintah validasi berbeda dari pekerjaan yang benar-benar dijalankan.\n\nGPT-5.6 Sol berbeda dari Terra, Luna, dan model GPT-6 sesudahnya; alias gpt-5.6 OpenAI mengarah ke Sol. Pertahankan profil itu ketika tugas bergantung pada batas pengetahuan, kontrol penalaran, atau batas konteksnya.",
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">O</span><h2 id=\"sheet-title\">OpenAI: GPT-5.6 Sol (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-5.6-sol:batch</code><button type=\"button\" id=\"copy-id\">Salin ID</button></div><nav class=\"card-jump-nav\" aria-label=\"Bagian kartu model\"><button type=\"button\" data-card-jump=\"overview\">Mulai</button><button type=\"button\" data-card-jump=\"methods\">Masukan &amp; metode</button><button type=\"button\" data-card-jump=\"pricing\">Paket</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=\"Metode 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-5.6-sol%3Abatch\">Batch</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\">Mulai</h3><p class=\"mdesc-full\">GPT-5.6 Sol adalah model GPT-5.6 unggulan OpenAI untuk pekerjaan profesional kompleks. Model ini memadukan pemahaman teks serta gambar, penalaran yang dapat dikonfigurasi, dan alat dengan konteks 1050000 token untuk menghasilkan kode, analisis, dan dokumen yang didukung sumber.</p><dl class=\"card-io\" data-card-io><div><dt>Masukan 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>Deskripsi ini mencakup kemampuan model. Masukan, keluaran, dan opsi yang tersedia di Ailoot tercantum di bawah untuk metode yang dipilih.</p><div class=\"mabout\" id=\"m-about\"><p>GPT-5.6 Sol adalah model unggulan OpenAI dalam keluarga GPT-5.6 untuk pekerjaan profesional kompleks. Model ini sepadan dengan tingkat model utama yang digunakan dalam keluarga GPT-5 terdahulu, sekaligus tetap menjadi edisi tersendiri. Model ini menerima teks dan gambar serta menghasilkan teks, termasuk analisis, kode, dokumen, dan temuan berstruktur. Profil standarnya berbeda dari eksekusi penalaran Pro Sol.</p><h4>Menyiapkan pekerjaan yang berat</h4><p>Tentukan hasil, sumber yang relevan, dan kondisi yang harus dipenuhi hasil. Untuk pekerjaan perangkat lunak, berikan berkas atau kutipan yang relevan, perilaku yang diamati, perilaku yang diharapkan, dan batasan. Untuk analisis profesional, tentukan keputusan, kriteria perbandingan, dan bukti. Contoh instruksinya: “Bandingkan pendekatan ini dengan spesifikasi, identifikasi dependensi, dan hasilkan rekomendasi dengan kondisi dari sumber yang mendukung setiap temuan.”</p><p>Jika gambar memuat bukti, beri label dan tentukan bagan, diagram, atau elemen antarmuka yang harus dianalisis. Minta jawaban memisahkan detail yang diamati dari tafsiran. Untuk penulisan atau penyuntingan, berikan pembaca yang dituju dan fakta yang harus dipertahankan, lalu sebutkan artefak akhir serta struktur yang diwajibkan.</p><h4>Upaya, eksekusi, dan konteks yang berlanjut</h4><p>Produsen mendukung upaya none, low, medium, high, xhigh, dan max, dengan medium sebagai nilai bawaan. Mode penalaran standar adalah mode bawaan; Pro menambahkan pekerjaan model untuk tugas sulit. Keduanya merupakan kontrol yang independen, sehingga upaya tidak dengan sendirinya mengubah model yang disebutkan atau menjadikan Pro edisi dasar baru.</p><p>Secara bawaan, profil penalaran GPT-5.6 memasukkan penalaran yang tersedia dari giliran sebelumnya ke langkah berikutnya, dengan pengaturan konteks untuk alur yang didukung. Pertahankan kejelasan persyaratan yang diterima dan pengamatan sepanjang percakapan, serta bedakan gagasan antara dari temuan akhir. Bahan yang dipertahankan tetap menggunakan konteks.</p><h4>Batas dan persiapan sumber</h4><p>Kartu Sol mencantumkan konteks 1050000 token, masukan hingga 922000 token, dan keluaran hingga 128000 token, dengan batas pengetahuan 16 Februari 2026. Penalaran menggunakan ruang respons meskipun tidak ditampilkan sebagai jawaban akhir. Sisakan ruang untuk hasil alat serta artefak yang selesai dan periksa respons yang mencapai anggarannya sebelum menggunakannya.</p><p>Susun dokumen panjang dan kode berdasarkan pertanyaan yang sebenarnya. Simpan label sumber serta batas yang relevan agar kesimpulan dapat mengidentifikasi bahan yang menjadi dasarnya. Untuk fakta terkini, berikan bagian sumber yang otoritatif atau alat pencarian yang sesuai, alih-alih mengandalkan pengetahuan pelatihan dari masa batas pengetahuan.</p><h4>Alat dan keluaran</h4><p>OpenAI mencantumkan Structured Outputs, pengaliran, dan panggilan fungsi. Alat yang didokumentasikan meliputi pencarian web dan berkas, pembuatan gambar, interpreter kode, operasi shell dan patch, keterampilan, penggunaan komputer, koneksi MCP, serta pencarian alat. Aplikasi menyediakan dan mengeksekusi operasinya, mengembalikan pengamatan untuk langkah model berikutnya. Keluaran model sendiri tetap berupa teks, sedangkan media atau tindakan yang dihasilkan alat memiliki hasil tersendiri.</p><p>Berikan tujuan serta skema yang spesifik kepada fungsi. Untuk rekaman data, tentukan makna kolom dan konvensi nilai yang tidak tersedia. Periksa nilai terhadap sumber dan kode terhadap perilaku yang diminta. Serah terima yang berguna menyajikan hasil, bukti, dan kondisi yang belum terselesaikan dengan jelas; usulan operasi atau perintah validasi berbeda dari pekerjaan yang benar-benar dijalankan.</p><p>GPT-5.6 Sol berbeda dari Terra, Luna, dan model GPT-6 sesudahnya; alias gpt-5.6 OpenAI mengarah ke Sol. Pertahankan profil itu ketika tugas bergantung pada batas pengetahuan, kontrol penalaran, atau batas konteksnya.</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Tersedia di Ailoot · masukan &amp; metode</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · Batch</b> <code>POST /v1/batches</code></summary><dl class=\"method-capabilities\"><div><dt>Masukan</dt><dd><code>text</code></dd></div><div><dt>Keluaran</dt><dd><code>text</code></dd></div><div><dt>Format keluaran</dt><dd>JSON inline pada results[].response.body</dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>Kolom</th><th>Jenis</th><th>Persyaratan</th><th>Nilai &amp; batasan</th><th>Bawaan</th></tr></thead><tbody><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Wajib</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>/v1/chat/completions</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Wajib</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>openai/gpt-5.6-sol:batch</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Wajib</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>Item minimum: 1</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Wajib</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Wajib</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>24h</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>openai/gpt-5.6-sol:batch, openai/gpt-5.6-sol</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>openai</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Persyaratan\"><span class=\"card-cell-label\">Persyaratan</span>Opsional</td><td data-cell-label=\"Nilai &amp; batasan\"><span class=\"card-cell-label\">Nilai &amp; batasan</span><div>false, null</div></td><td data-cell-label=\"Bawaan\" data-default=\"unspecified\"><span class=\"card-cell-label\">Bawaan</span>—</td></tr></tbody></table></div><details class=\"note-s\" data-method-contract><summary>Parameter metode dan siklus hidup</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[] inline; setiap item memiliki 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 dapat membaca JSONL UTF-8 aktual secara lokal ke dalam requests[]. Tidak menggunakan purpose unggahan, input_file_id, atau referensi file. Materi pelanggan yang tidak ada atau kosong menghentikan persiapan 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 disertakan), completion_window (jika disertakan), requests paling 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>body teks Chat Completions dalam envelope Batch inline yang didokumentasikan.</td></tr></tbody></table></div><p>Siklus hidup: <code>asynchronous</code></p><p class=\"note-s\"><code>GET /v1/batches/{operation_id}</code> · response.id aktual dari operasi create awal; user/key/group yang sama</p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">Paket</h3><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>Referensi tarif tidak menambah opsi permintaan. Parameter yang didukung tercantum pada metode yang dipilih.</p><dl data-price-conditions><dt>Mode Fast</dt><dd>Tidak ditentukan <span class=\"note-s\">Saat mode fast dipilih</span></dd><dt>Mode Flex</dt><dd>Tidak ditentukan <span class=\"note-s\">Saat mode flex dipilih</span></dd><dt>Upaya penalaran maksimum</dt><dd>Tidak ditentukan <span class=\"note-s\">Saat upaya penalaran maksimum menggunakan penyesuaian default</span></dd><dt>Harga cache eksplisit</dt><dd>Tidak diaktifkan <span class=\"note-s\">Saat cache eksplisit diminta</span></dd></dl></div><div data-declared-tariff-pricing><h4>Tarif Ailoot</h4><h4>Harga menurut konfigurasi</h4><p class=\"note-s\">Cocokkan setiap biaya dengan kondisi yang ditampilkan. Gunakan satu tarif untuk setiap kelompok konfigurasi alternatif.</p><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Konfigurasi</th><th>Jadwal tarif</th><th>Token konteks, lebih dari</th><th>Token konteks, hingga dan termasuk</th><th>Biaya</th></tr></thead><tbody><tr><th data-cell-label=\"Konfigurasi\" scope=\"row\"><span class=\"card-cell-label\">Konfigurasi</span>Tarif dasar token</th><td data-cell-label=\"Jadwal tarif\"><span class=\"card-cell-label\">Jadwal tarif</span>Tarif dasar</td><td data-cell-label=\"Token konteks, lebih dari\"><span class=\"card-cell-label\">Token konteks, lebih dari</span>—</td><td data-cell-label=\"Token konteks, hingga dan termasuk\"><span class=\"card-cell-label\">Token konteks, hingga dan termasuk</span>Tanpa batas atas</td><td data-cell-label=\"Biaya\"><span class=\"card-cell-label\">Biaya</span><div><span>Masukan · Token masukan</span> <b>$0.002</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Keluaran · Token keluaran</span> <b>$0.01</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Pembacaan cache</span> <b>$0.0002</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Penulisan cache</span> <b>$0.0025</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · 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>Panjang permintaan · tingkat 1</th><td data-cell-label=\"Jadwal tarif\"><span class=\"card-cell-label\">Jadwal tarif</span>—</td><td data-cell-label=\"Token konteks, lebih dari\"><span class=\"card-cell-label\">Token konteks, lebih dari</span>0</td><td data-cell-label=\"Token konteks, hingga dan termasuk\"><span class=\"card-cell-label\">Token konteks, hingga dan termasuk</span>272.000</td><td data-cell-label=\"Biaya\"><span class=\"card-cell-label\">Biaya</span><div><span>Masukan · Token masukan</span> <b>$0.002</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Keluaran · Token keluaran</span> <b>$0.01</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Pembacaan cache</span> <b>$0.0002</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Penulisan cache</span> <b>$0.0025</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · 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>Panjang permintaan · tingkat 2</th><td data-cell-label=\"Jadwal tarif\"><span class=\"card-cell-label\">Jadwal tarif</span>—</td><td data-cell-label=\"Token konteks, lebih dari\"><span class=\"card-cell-label\">Token konteks, lebih dari</span>272.000</td><td data-cell-label=\"Token konteks, hingga dan termasuk\"><span class=\"card-cell-label\">Token konteks, hingga dan termasuk</span>Tanpa batas atas</td><td data-cell-label=\"Biaya\"><span class=\"card-cell-label\">Biaya</span><div><span>Masukan · Token masukan</span> <b>$0.004</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Keluaran · Token keluaran</span> <b>$0.015</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Pembacaan cache</span> <b>$0.0004</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · Penulisan cache</span> <b>$0.005</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Masukan · 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 mencadangkan perkiraan dana sebelum permintaan. Setelah hasil diterima, tagihan akhir diselesaikan berdasarkan penggunaan yang terukur. Penyelesaian tagihan streaming menggunakan catatan penggunaan akhir. <a href=\"/docs/id/billing/reserve/\">Cara kerja cadangan dan penyelesaian tagihan →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">Contoh permintaan</h3><h4>Ailoot Ultra · Batch</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Pilihan kode\"><button class=\"cg-tab\" id=\"model-code-2102-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2102-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl · fixture yang disimpan</button><button class=\"cg-tab\" id=\"model-code-2102-tab-1\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2102-panel-1\" aria-selected=\"false\" tabindex=\"-1\">Python HTTP · JSONL pelanggan yang sebenarnya</button><button class=\"cg-tab\" id=\"model-code-2102-tab-2\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2102-panel-2\" aria-selected=\"false\" tabindex=\"-1\">Python · simpan setiap hasil yang telah selesai</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Salin kode\"><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-2102-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-2102-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-5.6-sol: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-2102-panel-1\" role=\"tabpanel\" aria-labelledby=\"model-code-2102-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-5.6-sol:batch&#39;, &#39;openai/gpt-5.6-sol&#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-5.6-sol: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-2102-panel-2\" role=\"tabpanel\" aria-labelledby=\"model-code-2102-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 · Batch</h4><p class=\"note-s\">JSON inline pada results[].response.body</p><ul class=\"card-result-paths\"><li><code>GET /v1/batches/{operation_id}</code></li></ul><h5>Periksa status tugas</h5><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Pilihan kode\"><button class=\"cg-tab\" id=\"model-code-2103-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2103-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl · status operasi asli</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Salin kode\"><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-2103-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-2103-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, berkas, dan bagian konten yang dikembalikan.</p><p class=\"note-s\">Pertahankan JSON status asli secara lengkap, setiap result/custom_id, serta body response atau error yang lengkap. Simpan results[] yang telah selesai sebagai JSONL tanpa penyaringan.</p></div><div class=\"card-result-process\" data-unknown-recovery><h5>Jika respons asli perlu diperiksa</h5><p class=\"note-s\">Pertahankan ID operasi asli. 503 result_pending_check memiliki X-Should-Retry:false; jangan pernah kirim ulang batch asli yang statusnya tidak diketahui.</p></div><details class=\"card-about\" data-output-fields><summary>Kolom respons</summary><div class=\"tw\" data-card-table=\"output\"><table><thead><tr><th>Kolom</th><th>Jenis</th></tr></thead><tbody><tr><th data-cell-label=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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=\"Kolom\" scope=\"row\"><span class=\"card-cell-label\">Kolom</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>Kesalahan dan langkah berikutnya</summary><div class=\"tw\" data-card-table=\"errors\"><table><thead><tr><th>Respons</th><th>Kondisi</th><th>Langkah berikutnya</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=\"Kondisi\"><span class=\"card-cell-label\">Kondisi</span>Envelope inline yang didokumentasikan tidak valid, ada kunci duplikat, atau terdapat konflik pada identitas item atau kemampuan model yang dikonfigurasi.</td><td data-cell-label=\"Langkah berikutnya\"><span class=\"card-cell-label\">Langkah berikutnya</span>Perbaiki kolom yang ditunjukkan sebelum pengiriman baru apa pun.</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=\"Kondisi\"><span class=\"card-cell-label\">Kondisi</span>Kunci API tidak valid.</td><td data-cell-label=\"Langkah berikutnya\"><span class=\"card-cell-label\">Langkah berikutnya</span>Gunakan kunci Ailoot yang berizin.</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=\"Kondisi\"><span class=\"card-cell-label\">Kondisi</span>Grup Batch tidak tersedia.</td><td data-cell-label=\"Langkah berikutnya\"><span class=\"card-cell-label\">Langkah berikutnya</span>Periksa hak akses key/group.</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=\"Kondisi\"><span class=\"card-cell-label\">Kondisi</span>Batch menggunakan penagihan dari saldo; pembuatan dengan langganan ditolak.</td><td data-cell-label=\"Langkah berikutnya\"><span class=\"card-cell-label\">Langkah berikutnya</span>Gunakan grup berizin yang ditagih dari saldo.</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=\"Kondisi\"><span class=\"card-cell-label\">Kondisi</span>Penawaran harga untuk input Batch tidak dapat dibuat.</td><td data-cell-label=\"Langkah berikutnya\"><span class=\"card-cell-label\">Langkah berikutnya</span>Simpan respons; gunakan input keluarga API yang didokumentasikan.</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=\"Kondisi\"><span class=\"card-cell-label\">Kondisi</span>Cadangan Batch tidak tersedia.</td><td data-cell-label=\"Langkah berikutnya\"><span class=\"card-cell-label\">Langkah berikutnya</span>Selesaikan kendala penerimaan sebelum mengirim permintaan baru.</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=\"Kondisi\"><span class=\"card-cell-label\">Kondisi</span>Harga metode Batch/tarif native tidak tersedia.</td><td data-cell-label=\"Langkah berikutnya\"><span class=\"card-cell-label\">Langkah berikutnya</span>Simpan respons; jangan mengganti 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=\"Kondisi\"><span class=\"card-cell-label\">Kondisi</span>Rute pemasok yang tepat tidak tersedia.</td><td data-cell-label=\"Langkah berikutnya\"><span class=\"card-cell-label\">Langkah berikutnya</span>Simpan respons untuk perbaikan rute.</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=\"Kondisi\"><span class=\"card-cell-label\">Kondisi</span>Hasil asli perlu diperiksa; X-Should-Retry:false.</td><td data-cell-label=\"Langkah berikutnya\"><span class=\"card-cell-label\">Langkah berikutnya</span>Simpan operation_id/id asli dan baca statusnya; jangan pernah mengulangi POST asli.</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=\"Kondisi\"><span class=\"card-cell-label\">Kondisi</span>Operasi status Batch tidak ada atau dimiliki oleh identitas lain.</td><td data-cell-label=\"Langkah berikutnya\"><span class=\"card-cell-label\">Langkah berikutnya</span>Gunakan id asli yang persis sama dan user/key/group 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-5.6-sol%3Abatch&amp;route=Ultra&amp;caller=openai%2Fgpt-5.6-sol%3Abatch&amp;fmt=batches\"><code>openai/gpt-5.6-sol:batch</code></a></span></p><h4>Alias jalur metode</h4><p class=\"note-s\">Gunakan jalur metode yang ditampilkan di atas.</p><h4>ID pemanggil terkait</h4><p class=\"note-s\"><a href=\"#m=openai%2Fgpt-5.6-sol%3Abatch&amp;route=Ultra&amp;caller=openai%2Fgpt-5.6-sol%3Abatch&amp;fmt=batches\"><code>openai/gpt-5.6-sol:batch</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "openai/gpt-5.6-sol:batch",
        "fmt": "batches",
        "http": "POST",
        "path": "/v1/batches",
        "request_model_id": "openai/gpt-5.6-sol:batch",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|batches|/v1/batches|openai%2Fgpt-5.6-sol%3Abatch",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "cache_read": 0.2,
        "cache_write": 2.5,
        "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": "Envelope inline yang didokumentasikan tidak valid, ada kunci duplikat, atau terdapat konflik pada identitas item atau kemampuan model yang dikonfigurasi.",
                "http_status": 400,
                "recovery": "Perbaiki kolom yang ditunjukkan sebelum pengiriman baru apa pun.",
                "type": "invalid_request_error"
              },
              {
                "code": null,
                "condition": "Kunci API tidak valid.",
                "http_status": 401,
                "recovery": "Gunakan kunci Ailoot yang berizin.",
                "type": "authentication_error"
              },
              {
                "code": null,
                "condition": "Grup Batch tidak tersedia.",
                "http_status": 403,
                "recovery": "Periksa hak akses key/group.",
                "type": "permission_error"
              },
              {
                "code": null,
                "condition": "Batch menggunakan penagihan dari saldo; pembuatan dengan langganan ditolak.",
                "http_status": 422,
                "recovery": "Gunakan grup berizin yang ditagih dari saldo.",
                "type": "invalid_request_error"
              },
              {
                "code": null,
                "condition": "Penawaran harga untuk input Batch tidak dapat dibuat.",
                "http_status": 422,
                "recovery": "Simpan respons; gunakan input keluarga API yang didokumentasikan.",
                "type": "price_unavailable"
              },
              {
                "code": null,
                "condition": "Cadangan Batch tidak tersedia.",
                "http_status": 402,
                "recovery": "Selesaikan kendala penerimaan sebelum mengirim permintaan baru.",
                "type": "billing_error"
              },
              {
                "code": null,
                "condition": "Harga metode Batch/tarif native tidak tersedia.",
                "http_status": 503,
                "recovery": "Simpan respons; jangan mengganti harga.",
                "type": "price_unavailable"
              },
              {
                "code": null,
                "condition": "Rute pemasok yang tepat tidak tersedia.",
                "http_status": 503,
                "recovery": "Simpan respons untuk perbaikan rute.",
                "type": "api_error"
              },
              {
                "code": "result_pending_check",
                "condition": "Hasil asli perlu diperiksa; X-Should-Retry:false.",
                "http_status": 503,
                "recovery": "Simpan operation_id/id asli dan baca statusnya; jangan pernah mengulangi POST asli.",
                "type": null
              },
              {
                "code": "not_found",
                "condition": "Operasi status Batch tidak ada atau dimiliki oleh identitas lain.",
                "http_status": 404,
                "recovery": "Gunakan id asli yang persis sama dan user/key/group yang sama.",
                "type": null
              }
            ],
            "example_body": {
              "endpoint": "/v1/chat/completions",
              "model": "openai/gpt-5.6-sol: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": "Pertahankan JSON status asli secara lengkap, setiap result/custom_id, serta body response atau error yang lengkap. Simpan results[] yang telah selesai sebagai JSONL tanpa penyaringan.",
              "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 inline pada results[].response.body"
            },
            "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-5.6-sol: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-5.6-sol:batch",
                  "openai/gpt-5.6-sol"
                ],
                "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-5.6-sol: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-5.6-sol:batch",
                              "openai/gpt-5.6-sol"
                            ],
                            "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-5.6-sol: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 dapat membaca JSONL UTF-8 aktual secara lokal ke dalam requests[]. Tidak menggunakan purpose unggahan, input_file_id, atau referensi file. Materi pelanggan yang tidak ada atau kosong menghentikan persiapan sebelum POST.",
            "material_types": [
              "text"
            ],
            "optional_controls": [
              "provider.only",
              "provider.allow_fallbacks",
              "completion_window"
            ],
            "representation": "requests[] inline; setiap item memiliki custom_id dan body",
            "request_endpoint_profile": "/v1/chat/completions",
            "required": [
              "endpoint",
              "model",
              "requests"
            ],
            "schema_scope": "body teks Chat Completions dalam envelope Batch inline yang didokumentasikan.",
            "serialization_order": [
              "endpoint",
              "model",
              "provider (jika disertakan)",
              "completion_window (jika disertakan)",
              "requests paling 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 aktual dari operasi create awal; user/key/group yang sama",
              "path": "/v1/batches/{operation_id}"
            },
            "terminal": [
              "completed",
              "failed",
              "expired",
              "cancelled"
            ],
            "unknown": "Pertahankan ID operasi asli. 503 result_pending_check memiliki X-Should-Retry:false; jangan pernah kirim ulang batch asli yang statusnya 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": "Tarif dasar token",
            "units": [
              {
                "amount": "0.002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000002",
                "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": "0.01000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00001",
                "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000002",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0.0025000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.0000025",
                "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": "Panjang permintaan · tingkat 1",
            "units": [
              {
                "amount": "0.002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000002",
                "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": "0.01000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00001",
                "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000002",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0.0025000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.0000025",
                "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": "Panjang permintaan · tingkat 2",
            "units": [
              {
                "amount": "0.004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000004",
                "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": "0.015000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.000015",
                "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": "0.0004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000004",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0.005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.000005",
                "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-5.6-sol: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-5.6-sol:batch', 'openai/gpt-5.6-sol']: raise ValueError(\"body.model must be an exact documented caller or wire ID\")\n    return {\"endpoint\":\"/v1/chat/completions\", \"model\":\"openai/gpt-5.6-sol: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": 2,
        "input": [
          "text"
        ],
        "label": "Batch",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "out": 10,
        "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": "0.002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000002",
                "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": "0.01000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00001",
                "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000002",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0.0025000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.0000025",
                "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": "0.002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000002",
                "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": "0.01000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00001",
                "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000002",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0.0025000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.0000025",
                "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": "Request-length tier 2",
            "units": [
              {
                "amount": "0.004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000004",
                "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": "0.015000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.000015",
                "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": "0.0004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000004",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0.005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.000005",
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "request_model_id": "openai/gpt-5.6-sol:batch",
        "route_label": "Ultra",
        "status_reads": [
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    "description": "GPT-5.6 Sol adalah model GPT-5.6 unggulan OpenAI untuk pekerjaan profesional kompleks. Model ini memadukan pemahaman teks serta gambar, penalaran yang dapat dikonfigurasi, dan alat dengan konteks 1050000 token untuk menghasilkan kode, analisis, dan dokumen yang didukung sumber.",
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    "about": "GPT-5.6 Sol adalah model unggulan OpenAI dalam keluarga GPT-5.6 untuk pekerjaan profesional kompleks. Model ini sepadan dengan tingkat model utama yang digunakan dalam keluarga GPT-5 terdahulu, sekaligus tetap menjadi edisi tersendiri. Model ini menerima teks dan gambar serta menghasilkan teks, termasuk analisis, kode, dokumen, dan temuan berstruktur. Profil standarnya berbeda dari eksekusi penalaran Pro Sol.\n\n### Menyiapkan pekerjaan yang berat\n\nTentukan hasil, sumber yang relevan, dan kondisi yang harus dipenuhi hasil. Untuk pekerjaan perangkat lunak, berikan berkas atau kutipan yang relevan, perilaku yang diamati, perilaku yang diharapkan, dan batasan. Untuk analisis profesional, tentukan keputusan, kriteria perbandingan, dan bukti. Contoh instruksinya: “Bandingkan pendekatan ini dengan spesifikasi, identifikasi dependensi, dan hasilkan rekomendasi dengan kondisi dari sumber yang mendukung setiap temuan.”\n\nJika gambar memuat bukti, beri label dan tentukan bagan, diagram, atau elemen antarmuka yang harus dianalisis. Minta jawaban memisahkan detail yang diamati dari tafsiran. Untuk penulisan atau penyuntingan, berikan pembaca yang dituju dan fakta yang harus dipertahankan, lalu sebutkan artefak akhir serta struktur yang diwajibkan.\n\n### Upaya, eksekusi, dan konteks yang berlanjut\n\nProdusen mendukung upaya none, low, medium, high, xhigh, dan max, dengan medium sebagai nilai bawaan. Mode penalaran standar adalah mode bawaan; Pro menambahkan pekerjaan model untuk tugas sulit. Keduanya merupakan kontrol yang independen, sehingga upaya tidak dengan sendirinya mengubah model yang disebutkan atau menjadikan Pro edisi dasar baru.\n\nSecara bawaan, profil penalaran GPT-5.6 memasukkan penalaran yang tersedia dari giliran sebelumnya ke langkah berikutnya, dengan pengaturan konteks untuk alur yang didukung. Pertahankan kejelasan persyaratan yang diterima dan pengamatan sepanjang percakapan, serta bedakan gagasan antara dari temuan akhir. Bahan yang dipertahankan tetap menggunakan konteks.\n\n### Batas dan persiapan sumber\n\nKartu Sol mencantumkan konteks 1050000 token, masukan hingga 922000 token, dan keluaran hingga 128000 token, dengan batas pengetahuan 16 Februari 2026. Penalaran menggunakan ruang respons meskipun tidak ditampilkan sebagai jawaban akhir. Sisakan ruang untuk hasil alat serta artefak yang selesai dan periksa respons yang mencapai anggarannya sebelum menggunakannya.\n\nSusun dokumen panjang dan kode berdasarkan pertanyaan yang sebenarnya. Simpan label sumber serta batas yang relevan agar kesimpulan dapat mengidentifikasi bahan yang menjadi dasarnya. Untuk fakta terkini, berikan bagian sumber yang otoritatif atau alat pencarian yang sesuai, alih-alih mengandalkan pengetahuan pelatihan dari masa batas pengetahuan.\n\n### Alat dan keluaran\n\nOpenAI mencantumkan Structured Outputs, pengaliran, dan panggilan fungsi. Alat yang didokumentasikan meliputi pencarian web dan berkas, pembuatan gambar, interpreter kode, operasi shell dan patch, keterampilan, penggunaan komputer, koneksi MCP, serta pencarian alat. Aplikasi menyediakan dan mengeksekusi operasinya, mengembalikan pengamatan untuk langkah model berikutnya. Keluaran model sendiri tetap berupa teks, sedangkan media atau tindakan yang dihasilkan alat memiliki hasil tersendiri.\n\nBerikan tujuan serta skema yang spesifik kepada fungsi. Untuk rekaman data, tentukan makna kolom dan konvensi nilai yang tidak tersedia. Periksa nilai terhadap sumber dan kode terhadap perilaku yang diminta. Serah terima yang berguna menyajikan hasil, bukti, dan kondisi yang belum terselesaikan dengan jelas; usulan operasi atau perintah validasi berbeda dari pekerjaan yang benar-benar dijalankan.\n\nGPT-5.6 Sol berbeda dari Terra, Luna, dan model GPT-6 sesudahnya; alias gpt-5.6 OpenAI mengarah ke Sol. Pertahankan profil itu ketika tugas bergantung pada batas pengetahuan, kontrol penalaran, atau batas konteksnya.",
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              },
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                "http_status": 404,
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            "example_body": {
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              "Per-item provider, service_tier and input_type are outside this batch profile.",
              "stream is omitted or false.",
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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."
            ],
            "outputs": {
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              "enclosing_family": "batch",
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            "provider_policy": {
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              "configured_only": [
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              "when_omitted": "Current Source injects the exact persisted declaration before fresh submission."
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              ]
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            "unsupported": [
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              "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 dapat membaca JSONL UTF-8 aktual secara lokal ke dalam requests[]. Tidak menggunakan purpose unggahan, input_file_id, atau referensi file. Materi pelanggan yang tidak ada atau kosong menghentikan persiapan sebelum POST.",
            "material_types": [
              "text"
            ],
            "optional_controls": [
              "provider.only",
              "provider.allow_fallbacks",
              "completion_window"
            ],
            "representation": "requests[] inline; setiap item memiliki custom_id dan body",
            "request_endpoint_profile": "/v1/chat/completions",
            "required": [
              "endpoint",
              "model",
              "requests"
            ],
            "schema_scope": "body teks Chat Completions dalam envelope Batch inline yang didokumentasikan.",
            "serialization_order": [
              "endpoint",
              "model",
              "provider (jika disertakan)",
              "completion_window (jika disertakan)",
              "requests paling 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 aktual dari operasi create awal; user/key/group yang sama",
              "path": "/v1/batches/{operation_id}"
            },
            "terminal": [
              "completed",
              "failed",
              "expired",
              "cancelled"
            ],
            "unknown": "Pertahankan ID operasi asli. 503 result_pending_check memiliki X-Should-Retry:false; jangan pernah kirim ulang batch asli yang statusnya 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": "Tarif dasar token",
            "units": [
              {
                "amount": "0.002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000002",
                "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": "0.01000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00001",
                "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000002",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0.0025000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.0000025",
                "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": "Panjang permintaan · tingkat 1",
            "units": [
              {
                "amount": "0.002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000002",
                "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": "0.01000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00001",
                "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000002",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0.0025000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.0000025",
                "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": "Panjang permintaan · tingkat 2",
            "units": [
              {
                "amount": "0.004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000004",
                "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": "0.015000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.000015",
                "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": "0.0004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000004",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0.005000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.000005",
                "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-5.6-sol: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-5.6-sol:batch', 'openai/gpt-5.6-sol']: raise ValueError(\"body.model must be an exact documented caller or wire ID\")\n    return {\"endpoint\":\"/v1/chat/completions\", \"model\":\"openai/gpt-5.6-sol: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": 2,
        "input": [
          "text"
        ],
        "label": "Batch",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "out": 10,
        "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": "0.002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000002",
                "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": "0.01000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00001",
                "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000002",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0.0025000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.0000025",
                "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": "0.002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.000002",
                "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": "0.01000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.00001",
                "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": "0.0002000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0.0000002",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0.0025000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0.0000025",
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
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