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  "aboutHtml": "<p>Voyage Code 2 manba kodi va tegishli matn uchun sonli embeddinglar yaratadi. U semantik kod qidiruvi uchun ishlab chiqilgan: dasturchi xatti-harakatni tavsiflaydi yoki kod parchasini beradi, qidiruv tizimi esa tegishli dasturiy yechimlarni topadi. Ishlab chiqaruvchi misollarida qidiruv kirishi sifatida tabiiy tildagi savollar, kod parchalari va ikkalasining birikmalari bor.</p><p>Undan haqiqiy dasturlash savollariga yo‘naltirilgan repozitoriy qidiruvini yaratish uchun foydalaning. Dasturchi faqat birinchi va oxirgi mos kelgan belgilarni olib tashlaydigan protsedurani yoki loyihaning daraxtni aylanib chiqishning muayyan usulini qo‘llaydigan qismini izlashi mumkin. Xatti-harakatni aniq ifodalaydigan, kerakli yechimni yaqin, ammo noto‘g‘ri variantdan ajratadigan shartni ham o‘z ichiga olgan so‘rovlarni tayyorlang.</p><p>Har bir faylni ixtiyoriy belgilar sonida bo‘lish o‘rniga kodni foydali birliklarda indekslang. Funksiya signaturasi, tanasi va tegishli izohini birga saqlang. Yordamchi funksiya mahalliy turlar yoki doimiy qiymatlarga bog‘liq bo‘lsa, uning vazifasini tushunish uchun yetarli atrof matnini saqlang. Natija asl kodni bevosita ochishi uchun fayl yo‘llari, repozitoriy tahrirlari va manba joylashuvlarini embeddingdan tashqarida saqlang.</p><p>Bu nashr 16 000 tokenli kontekst oynasiga ega va 1 536 o‘lchamli embeddinglar yaratadi. Vektor indeksini shu ifodaga mos hajmlang va so‘rov hamda hujjat embeddinglarini ayni model bilan bog‘liq saqlang. Voyage Code 2 bilan allaqachon indekslangan to‘plam manba yozuvlari yangilanayotganda bir xil qidiruv ifodasini saqlashi mumkin. Boshqa embedding nashriga o‘tish ayni repozitoriyda aniq taqqoslanadigan indeks migratsiyasi sifatida ko‘rilishi kerak.</p><p>Tabiiy tildagi so‘rovda operatsiya, kirishlar va tegishli natijani tavsiflang. Kod so‘rovida mantiqi moslashtirilishi kerak bo‘lgan parchani kiriting va qidiruvga muhim har qanday shartni tushuntiring. Masalan, qayta urinishni qayta ishlaydigan kodni izlashda kod vaqt tugagach qayta urinadimi yoki to‘liq xato javobidan keyinmi, deb aniqlashtirish mumkin. Topilgan manbani tahrirda ishlatishdan oldin shu farq bo‘yicha tekshirish kerak.</p><p>Hujjatlar ham, manba kodi ham indekslansa, ikkalasini ham asl manbasiga kuzatish imkonini saqlang. Izohli parcha foydali kontekst bo‘lishi mumkin, dasturchi tekshirishi kerak bo‘lgan artefakt esa dasturiy yechimning o‘zi. Qidiruv sahifasi to‘g‘ri manzilni ko‘rsatishi va dasturlash yordamchisi tavsifni bajariladigan manba kodidan ajratishi uchun yozuv turlarini yorliqlang.</p><p>Topilgan parchalardan repozitoriyda yo‘l topish, dasturiy yechimni aniqlash yoki dasturlash yordamchisining keyingi bosqichi uchun kontekst sifatida foydalaning. Keyingi bosqichga berishda to‘liq tegishli parcha va uning joylashuvini saqlang. O‘xshashlik nomzod kodni topishga yordam beradi; haqiqiy kirishlar, yon ta’sirlar va shartlarni tekshirish esa nomzod joriy muammoni hal qiladimi, shuni aniqlaydi.</p><p>Qidiruvni manbadagi javoblari ma’lum haqiqiy savollar to‘plamida baholang. Nomi o‘zgargan funksiyalar, chalg‘ituvchi izohlar, chegaraviy holatlari turli o‘xshash yordamchi vositalar va kodda yo‘q so‘zlardan foydalanadigan so‘rovlarni kiriting. Kutilgan yechim foydali natijalar orasida chiqishini va ko‘rsatilgan parcha uni baholashga yetarli kontekst berishini tekshiring. Repozitoriy o‘sganda ham shu savollarni saqlang: ma’lumot ajratish, parcha chegaralari yoki indekslashdagi o‘zgarishlarni ayni vazifalarda solishtirish mumkin bo‘lsin.</p>",
  "aboutText": "Voyage Code 2 manba kodi va tegishli matn uchun sonli embeddinglar yaratadi. U semantik kod qidiruvi uchun ishlab chiqilgan: dasturchi xatti-harakatni tavsiflaydi yoki kod parchasini beradi, qidiruv tizimi esa tegishli dasturiy yechimlarni topadi. Ishlab chiqaruvchi misollarida qidiruv kirishi sifatida tabiiy tildagi savollar, kod parchalari va ikkalasining birikmalari bor.\n\nUndan haqiqiy dasturlash savollariga yo‘naltirilgan repozitoriy qidiruvini yaratish uchun foydalaning. Dasturchi faqat birinchi va oxirgi mos kelgan belgilarni olib tashlaydigan protsedurani yoki loyihaning daraxtni aylanib chiqishning muayyan usulini qo‘llaydigan qismini izlashi mumkin. Xatti-harakatni aniq ifodalaydigan, kerakli yechimni yaqin, ammo noto‘g‘ri variantdan ajratadigan shartni ham o‘z ichiga olgan so‘rovlarni tayyorlang.\n\nHar bir faylni ixtiyoriy belgilar sonida bo‘lish o‘rniga kodni foydali birliklarda indekslang. Funksiya signaturasi, tanasi va tegishli izohini birga saqlang. Yordamchi funksiya mahalliy turlar yoki doimiy qiymatlarga bog‘liq bo‘lsa, uning vazifasini tushunish uchun yetarli atrof matnini saqlang. Natija asl kodni bevosita ochishi uchun fayl yo‘llari, repozitoriy tahrirlari va manba joylashuvlarini embeddingdan tashqarida saqlang.\n\nBu nashr 16 000 tokenli kontekst oynasiga ega va 1 536 o‘lchamli embeddinglar yaratadi. Vektor indeksini shu ifodaga mos hajmlang va so‘rov hamda hujjat embeddinglarini ayni model bilan bog‘liq saqlang. Voyage Code 2 bilan allaqachon indekslangan to‘plam manba yozuvlari yangilanayotganda bir xil qidiruv ifodasini saqlashi mumkin. Boshqa embedding nashriga o‘tish ayni repozitoriyda aniq taqqoslanadigan indeks migratsiyasi sifatida ko‘rilishi kerak.\n\nTabiiy tildagi so‘rovda operatsiya, kirishlar va tegishli natijani tavsiflang. Kod so‘rovida mantiqi moslashtirilishi kerak bo‘lgan parchani kiriting va qidiruvga muhim har qanday shartni tushuntiring. Masalan, qayta urinishni qayta ishlaydigan kodni izlashda kod vaqt tugagach qayta urinadimi yoki to‘liq xato javobidan keyinmi, deb aniqlashtirish mumkin. Topilgan manbani tahrirda ishlatishdan oldin shu farq bo‘yicha tekshirish kerak.\n\nHujjatlar ham, manba kodi ham indekslansa, ikkalasini ham asl manbasiga kuzatish imkonini saqlang. Izohli parcha foydali kontekst bo‘lishi mumkin, dasturchi tekshirishi kerak bo‘lgan artefakt esa dasturiy yechimning o‘zi. Qidiruv sahifasi to‘g‘ri manzilni ko‘rsatishi va dasturlash yordamchisi tavsifni bajariladigan manba kodidan ajratishi uchun yozuv turlarini yorliqlang.\n\nTopilgan parchalardan repozitoriyda yo‘l topish, dasturiy yechimni aniqlash yoki dasturlash yordamchisining keyingi bosqichi uchun kontekst sifatida foydalaning. Keyingi bosqichga berishda to‘liq tegishli parcha va uning joylashuvini saqlang. O‘xshashlik nomzod kodni topishga yordam beradi; haqiqiy kirishlar, yon ta’sirlar va shartlarni tekshirish esa nomzod joriy muammoni hal qiladimi, shuni aniqlaydi.\n\nQidiruvni manbadagi javoblari ma’lum haqiqiy savollar to‘plamida baholang. Nomi o‘zgargan funksiyalar, chalg‘ituvchi izohlar, chegaraviy holatlari turli o‘xshash yordamchi vositalar va kodda yo‘q so‘zlardan foydalanadigan so‘rovlarni kiriting. Kutilgan yechim foydali natijalar orasida chiqishini va ko‘rsatilgan parcha uni baholashga yetarli kontekst berishini tekshiring. Repozitoriy o‘sganda ham shu savollarni saqlang: ma’lumot ajratish, parcha chegaralari yoki indekslashdagi o‘zgarishlarni ayni vazifalarda solishtirish mumkin bo‘lsin.",
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">•</span><h2 id=\"sheet-title\">Voyage AI: Voyage Code 2</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"Yopish\">×</button></div><div class=\"idline\"><span>Voyage AI /</span><code>voyage-code-2</code><button type=\"button\" id=\"copy-id\">ID ni nusxalash</button></div><nav class=\"card-jump-nav\" aria-label=\"Model kartochkasi bo‘limlari\"><button type=\"button\" data-card-jump=\"overview\">Boshlash</button><button type=\"button\" data-card-jump=\"methods\">Kirish ma’lumotlari va usullar</button><button type=\"button\" data-card-jump=\"pricing\">Tariflar</button><button type=\"button\" data-card-jump=\"examples\">Namunalar</button><button type=\"button\" data-card-jump=\"results\">Natijalar</button><button type=\"button\" data-card-jump=\"aliases\">Taxalluslar</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"API usullari\"><button type=\"button\" role=\"tab\" tabindex=\"0\" aria-controls=\"card-method-content\" aria-selected=\"true\" id=\"card-method-tab-0\" data-card-method=\"Ultra|embeddings|/v1/embeddings|voyage-code-2\">Embeddinglar</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\">Boshlash</h3><p class=\"mdesc-full\">Voyage Code 2 repozitoriyda semantik qidiruv uchun manba kodi va tegishli matndan embeddinglar yaratadi. Tabiiy tildagi savollar, kod parchalari yoki aralash so‘rovlar tegishli dasturiy yechimlarni topishi mumkin; bu nashr 16 000 tokenli kontekst oynasi va 1 536 o‘lchamli vektorlardan foydalanadi.</p><dl class=\"card-io\" data-card-io><div><dt>Qabul qilinadigan kirish ma’lumotlari</dt><dd>Matn</dd></div><div><dt>Natijalar</dt><dd>embedding</dd></div></dl><details class=\"card-about\"><summary>Model haqida</summary><p class=\"note-s\" data-model-method-boundary>Bu tavsif model imkoniyatlarini yoritadi. Ailoot da tanlangan usul uchun mavjud kirish, chiqish va parametrlar quyida keltirilgan.</p><div class=\"mabout\" id=\"m-about\"><p>Voyage Code 2 manba kodi va tegishli matn uchun sonli embeddinglar yaratadi. U semantik kod qidiruvi uchun ishlab chiqilgan: dasturchi xatti-harakatni tavsiflaydi yoki kod parchasini beradi, qidiruv tizimi esa tegishli dasturiy yechimlarni topadi. Ishlab chiqaruvchi misollarida qidiruv kirishi sifatida tabiiy tildagi savollar, kod parchalari va ikkalasining birikmalari bor.</p><p>Undan haqiqiy dasturlash savollariga yo‘naltirilgan repozitoriy qidiruvini yaratish uchun foydalaning. Dasturchi faqat birinchi va oxirgi mos kelgan belgilarni olib tashlaydigan protsedurani yoki loyihaning daraxtni aylanib chiqishning muayyan usulini qo‘llaydigan qismini izlashi mumkin. Xatti-harakatni aniq ifodalaydigan, kerakli yechimni yaqin, ammo noto‘g‘ri variantdan ajratadigan shartni ham o‘z ichiga olgan so‘rovlarni tayyorlang.</p><p>Har bir faylni ixtiyoriy belgilar sonida bo‘lish o‘rniga kodni foydali birliklarda indekslang. Funksiya signaturasi, tanasi va tegishli izohini birga saqlang. Yordamchi funksiya mahalliy turlar yoki doimiy qiymatlarga bog‘liq bo‘lsa, uning vazifasini tushunish uchun yetarli atrof matnini saqlang. Natija asl kodni bevosita ochishi uchun fayl yo‘llari, repozitoriy tahrirlari va manba joylashuvlarini embeddingdan tashqarida saqlang.</p><p>Bu nashr 16 000 tokenli kontekst oynasiga ega va 1 536 o‘lchamli embeddinglar yaratadi. Vektor indeksini shu ifodaga mos hajmlang va so‘rov hamda hujjat embeddinglarini ayni model bilan bog‘liq saqlang. Voyage Code 2 bilan allaqachon indekslangan to‘plam manba yozuvlari yangilanayotganda bir xil qidiruv ifodasini saqlashi mumkin. Boshqa embedding nashriga o‘tish ayni repozitoriyda aniq taqqoslanadigan indeks migratsiyasi sifatida ko‘rilishi kerak.</p><p>Tabiiy tildagi so‘rovda operatsiya, kirishlar va tegishli natijani tavsiflang. Kod so‘rovida mantiqi moslashtirilishi kerak bo‘lgan parchani kiriting va qidiruvga muhim har qanday shartni tushuntiring. Masalan, qayta urinishni qayta ishlaydigan kodni izlashda kod vaqt tugagach qayta urinadimi yoki to‘liq xato javobidan keyinmi, deb aniqlashtirish mumkin. Topilgan manbani tahrirda ishlatishdan oldin shu farq bo‘yicha tekshirish kerak.</p><p>Hujjatlar ham, manba kodi ham indekslansa, ikkalasini ham asl manbasiga kuzatish imkonini saqlang. Izohli parcha foydali kontekst bo‘lishi mumkin, dasturchi tekshirishi kerak bo‘lgan artefakt esa dasturiy yechimning o‘zi. Qidiruv sahifasi to‘g‘ri manzilni ko‘rsatishi va dasturlash yordamchisi tavsifni bajariladigan manba kodidan ajratishi uchun yozuv turlarini yorliqlang.</p><p>Topilgan parchalardan repozitoriyda yo‘l topish, dasturiy yechimni aniqlash yoki dasturlash yordamchisining keyingi bosqichi uchun kontekst sifatida foydalaning. Keyingi bosqichga berishda to‘liq tegishli parcha va uning joylashuvini saqlang. O‘xshashlik nomzod kodni topishga yordam beradi; haqiqiy kirishlar, yon ta’sirlar va shartlarni tekshirish esa nomzod joriy muammoni hal qiladimi, shuni aniqlaydi.</p><p>Qidiruvni manbadagi javoblari ma’lum haqiqiy savollar to‘plamida baholang. Nomi o‘zgargan funksiyalar, chalg‘ituvchi izohlar, chegaraviy holatlari turli o‘xshash yordamchi vositalar va kodda yo‘q so‘zlardan foydalanadigan so‘rovlarni kiriting. Kutilgan yechim foydali natijalar orasida chiqishini va ko‘rsatilgan parcha uni baholashga yetarli kontekst berishini tekshiring. Repozitoriy o‘sganda ham shu savollarni saqlang: ma’lumot ajratish, parcha chegaralari yoki indekslashdagi o‘zgarishlarni ayni vazifalarda solishtirish mumkin bo‘lsin.</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Ailoot da mavjud · kirish ma’lumotlari va usullar</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · Embeddinglar</b> <code>POST /v1/embeddings</code></summary><dl class=\"method-capabilities\"><div><dt>Kirish</dt><dd><code>text</code></dd></div><div><dt>Chiqish</dt><dd><code>embedding</code></dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>Maydon</th><th>Tur</th><th>Talab</th><th>Qiymatlar va cheklovlar</th><th>Standart</th></tr></thead><tbody><tr><th data-cell-label=\"Maydon\" scope=\"row\"><span class=\"card-cell-label\">Maydon</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Tur\" data-field-type><span class=\"card-cell-label\">Tur</span><code>string</code></td><td data-cell-label=\"Talab\"><span class=\"card-cell-label\">Talab</span>Majburiy</td><td data-cell-label=\"Qiymatlar va cheklovlar\"><span class=\"card-cell-label\">Qiymatlar va cheklovlar</span><div>voyage-code-2</div><div>Shartlar: Ailoot ning aniq model tanlagichidan foydalaning.</div></td><td data-cell-label=\"Standart\" data-default=\"unspecified\"><span class=\"card-cell-label\">Standart</span>—</td></tr><tr><th data-cell-label=\"Maydon\" scope=\"row\"><span class=\"card-cell-label\">Maydon</span><code class=\"card-field-name\">input</code></th><td data-cell-label=\"Tur\" data-field-type><span class=\"card-cell-label\">Tur</span><code>string or array&lt;string&gt;</code></td><td data-cell-label=\"Talab\"><span class=\"card-cell-label\">Talab</span>Majburiy</td><td data-cell-label=\"Qiymatlar va cheklovlar\"><span class=\"card-cell-label\">Qiymatlar va cheklovlar</span><div>Shartlar: Matn yoki matnlar ro‘yxati; qaytarilgan har bir data elementi va uning indeksiga bittadan vektor saqlang.</div></td><td data-cell-label=\"Standart\" data-default=\"unspecified\"><span class=\"card-cell-label\">Standart</span>—</td></tr></tbody></table></div><details class=\"note-s\" data-method-contract><summary>Usul parametrlari va hayot sikli</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>Parametr</th><th>Parametr talablari</th></tr></thead><tbody><tr><th data-cell-label=\"Parametr\" scope=\"row\"><span class=\"card-cell-label\">Parametr</span><code>content_type</code></th><td data-cell-label=\"Parametr talablari\"><span class=\"card-cell-label\">Parametr talablari</span>application/json</td></tr><tr><th data-cell-label=\"Parametr\" scope=\"row\"><span class=\"card-cell-label\">Parametr</span><code>required</code></th><td data-cell-label=\"Parametr talablari\"><span class=\"card-cell-label\">Parametr talablari</span>model, input</td></tr><tr><th data-cell-label=\"Parametr\" scope=\"row\"><span class=\"card-cell-label\">Parametr</span><code>optional</code></th><td data-cell-label=\"Parametr talablari\"><span class=\"card-cell-label\">Parametr talablari</span></td></tr><tr><th data-cell-label=\"Parametr\" scope=\"row\"><span class=\"card-cell-label\">Parametr</span><code>material_types</code></th><td data-cell-label=\"Parametr talablari\"><span class=\"card-cell-label\">Parametr talablari</span>text</td></tr><tr><th data-cell-label=\"Parametr\" scope=\"row\"><span class=\"card-cell-label\">Parametr</span><code>conditions</code></th><td data-cell-label=\"Parametr talablari\"><span class=\"card-cell-label\">Parametr talablari</span>Tanlangan model bilan matn yuboring; qaytarilgan har bir vektor va uning indeksini saqlang.</td></tr></tbody></table></div><p>Hayot sikli: <code>synchronous</code></p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">Tariflar</h3><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>Tarif ma’lumotlari so‘rov imkoniyatlarini qo‘shmaydi. Qo‘llab-quvvatlanadigan parametrlar tanlangan usulda ko‘rsatilgan.</p><dl data-price-conditions><dt>Tezkor rejim</dt><dd>Ko‘rsatilmagan <span class=\"note-s\">Tezkor rejim tanlanganda</span></dd><dt>Flex rejimi</dt><dd>Ko‘rsatilmagan <span class=\"note-s\">flex rejimi tanlanganda</span></dd><dt>Maksimal fikrlash darajasi</dt><dd>Ko‘rsatilmagan <span class=\"note-s\">Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda</span></dd></dl></div><div data-declared-tariff-pricing><h4>Ailoot tariflari</h4><h4>Sozlamalar bo‘yicha narxlar</h4><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Sozlama</th><th>Tariflar jadvali</th><th>To‘lov</th></tr></thead><tbody><tr><th data-cell-label=\"Sozlama\" scope=\"row\"><span class=\"card-cell-label\">Sozlama</span>Tokenlar uchun bazaviy tariflar</th><td data-cell-label=\"Tariflar jadvali\"><span class=\"card-cell-label\">Tariflar jadvali</span>Asosiy tarif</td><td data-cell-label=\"To‘lov\"><span class=\"card-cell-label\">To‘lov</span><div><span>Kirish · Kirish tokenlari</span> <b>$0.0004</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Chiqish · Chiqish tokenlari</span> <b>$0</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Kirish · Keshdan o‘qish</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Kirish · Keshga yozish</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div><div><span>Kirish · Keshga yozish, 1 soat</span> <b>—</b> <span class=\"price-unit\">/ 1K token</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot so‘rovdan oldin taxminiy summani band qiladi. Natijadan keyin o‘lchangan sarf asosidagi yakuniy to‘lovni yechadi. Oqimli javob bo‘yicha yakuniy hisob-kitob yakuniy sarf yozuviga asoslanadi. <a href=\"/docs/uz/billing/reserve/\">Summani band qilish va to‘lovni hisoblash tartibi →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">So‘rov namunalari</h3><h4>Ailoot Ultra · Embeddinglar</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Kod variantlari\"><button class=\"cg-tab\" id=\"model-code-2789-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-2789-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl · Barcha vektorlar va foydalanish ma’lumotlarini saqlang</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Kodni nusxalash\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-2789-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-2789-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\ncat &gt; request.json &lt;&lt;&#39;JSON&#39;\n{\n  &quot;model&quot;: &quot;voyage-code-2&quot;,\n  &quot;input&quot;: &quot;The quick brown fox jumps over the lazy dog&quot;\n}\nJSON\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/embeddings \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -H &#39;Content-Type: application/json&#39; \\\n  --data-binary @request.json -D response-headers.txt -o embeddings.json\n# Keep every data item and its index, the full usage object and response headers.\n</code></pre></div></div></div></section><section class=\"card-section\" data-card-section=\"results\"><h3 tabindex=\"-1\">Natijalarni olish va saqlash</h3></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">Taxalluslar</h3><h4>Model taxalluslari</h4><p class=\"note-s\"><span data-model-alias-route=\"Ultra\"><b>Ailoot Ultra</b> <a href=\"#m=voyage-code-2&amp;route=Ultra&amp;caller=voyage-code-2&amp;fmt=embeddings\"><code>voyage-code-2</code></a></span></p><h4>Usul yo‘llari taxalluslari</h4><p class=\"note-s\">Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.</p><h4>Chaqirish uchun tegishli ID lar</h4><p class=\"note-s\"><a href=\"#m=voyage-code-2&amp;route=Ultra&amp;caller=voyage-code-2&amp;fmt=embeddings\"><code>voyage-code-2</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "voyage-code-2",
        "fmt": "embeddings",
        "http": "POST",
        "path": "/v1/embeddings",
        "request_model_id": "voyage-code-2",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|embeddings|/v1/embeddings|voyage-code-2",
      "ordinal": 0,
      "rawMethod": {
        "cache_read": null,
        "cache_write": null,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Save the complete JSON response, every vector with its index, all usage fields and request headers.",
            "lifecycle": {
              "content": [],
              "create": {
                "http": "POST",
                "path": "/v1/embeddings"
              },
              "mode": "synchronous",
              "status": [],
              "unknown": "Solishtirib tekshirish uchun asl javobni va X-Client-Request-ID qiymatini saqlang. Noaniq javob ayni yaratish so‘rovini qayta yuborishga ruxsat bermaydi.",
              "unknown_no_replay": true
            },
            "outputs": {
              "all_results": "To‘liq JSON javobini, har bir vektorni o‘z indeksi bilan, foydalanishga oid barcha maydonlarni va so‘rov sarlavhalarini saqlang.",
              "every_actual_output": true,
              "family": "embedding",
              "fields": [
                {
                  "name": "object",
                  "type": "string"
                },
                {
                  "name": "model",
                  "type": "string"
                },
                {
                  "name": "data[].index",
                  "type": "integer"
                },
                {
                  "name": "data[].embedding",
                  "type": "array<number>"
                },
                {
                  "name": "usage",
                  "type": "object"
                },
                {
                  "name": "usage.prompt_tokens",
                  "type": "integer"
                },
                {
                  "name": "usage.total_tokens",
                  "type": "integer"
                }
              ]
            },
            "parameters": [
              {
                "conditions": "Ailoot ning aniq model tanlagichidan foydalaning.",
                "default_known": false,
                "enum": [
                  "voyage-code-2"
                ],
                "enum_known": true,
                "maximum_length": null,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "conditions": "Matn yoki matnlar ro‘yxati; qaytarilgan har bir data elementi va uning indeksiga bittadan vektor saqlang.",
                "default_known": false,
                "enum_known": false,
                "maximum_length": null,
                "name": "input",
                "oneOf": [
                  {
                    "minLength": 1,
                    "type": "string"
                  },
                  {
                    "items": {
                      "minLength": 1,
                      "type": "string"
                    },
                    "minItems": 1,
                    "type": "array"
                  }
                ],
                "required": true,
                "type": "string or array<string>"
              }
            ],
            "request_schema": {
              "additionalProperties": true,
              "properties": {
                "input": {
                  "oneOf": [
                    {
                      "minLength": 1,
                      "type": "string"
                    },
                    {
                      "items": {
                        "minLength": 1,
                        "type": "string"
                      },
                      "minItems": 1,
                      "type": "array"
                    }
                  ]
                },
                "model": {
                  "enum": [
                    "voyage-code-2"
                  ],
                  "type": "string"
                }
              },
              "required": [
                "model",
                "input"
              ],
              "type": "object"
            },
            "schema_template": {
              "actual_file_preparation_required": false,
              "body": {
                "input": "The quick brown fox jumps over the lazy dog",
                "model": "voyage-code-2"
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "conditions": [
              "Tanlangan model bilan matn yuboring; qaytarilgan har bir vektor va uning indeksini saqlang."
            ],
            "content_type": "application/json",
            "material_types": [
              "text"
            ],
            "optional": [],
            "required": [
              "model",
              "input"
            ]
          },
          "lifecycle": {
            "content": [],
            "create": {
              "http": "POST",
              "path": "/v1/embeddings"
            },
            "mode": "synchronous",
            "status": [],
            "unknown": "Keep the original response and X-Client-Request-ID for reconciliation. An ambiguous response is not permission to submit the same creation again.",
            "unknown_no_replay": true
          },
          "method": {
            "http": "POST",
            "path": "/v1/embeddings"
          },
          "output": {
            "all_results": "Save the complete JSON response, every vector with its index, all usage fields and request headers.",
            "every_actual_output": true,
            "family": "embedding",
            "fields": [
              {
                "name": "object",
                "type": "string"
              },
              {
                "name": "model",
                "type": "string"
              },
              {
                "name": "data[].index",
                "type": "integer"
              },
              {
                "name": "data[].embedding",
                "type": "array<number>"
              },
              {
                "name": "usage",
                "type": "object"
              },
              {
                "name": "usage.prompt_tokens",
                "type": "integer"
              },
              {
                "name": "usage.total_tokens",
                "type": "integer"
              }
            ]
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Tokenlar uchun bazaviy tariflar",
            "units": [
              {
                "amount": "0.0004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000004",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\ncat > request.json <<'JSON'\n{\n  \"model\": \"voyage-code-2\",\n  \"input\": \"The quick brown fox jumps over the lazy dog\"\n}\nJSON\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/embeddings \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o embeddings.json\n# Keep every data item and its index, the full usage object and response headers.\n",
            "label": "curl · save all vectors and usage",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "embeddings",
        "http": "POST",
        "in": 0.4,
        "input": [
          "text"
        ],
        "label": "Embeddinglar",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "out": 0,
        "output": [
          "embedding"
        ],
        "path": "/v1/embeddings",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "token",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0.0004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000004",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "request_model_id": "voyage-code-2",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": "0.0004000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.0000004",
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0",
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          }
        ]
      }
    }
  ],
  "model_id": "voyage-code-2",
  "nativeProvenance": {
    "input_facts_canonical_sha256": "40cce08262163661413d0012fcd21dd3af67d9b98182284697a9f9bdb964f1cf",
    "input_html_sha256": "9d0581daedc9d6547a5c3c21f21c7d7f89277c5604a71e713da16280d3c16a2d",
    "private_audit_sha256": "59d271832542dbd67ff7141a3c4d4175524a649480db5caf795c543d4c2a0cf9",
    "role": "historical-normalized-input-audit-hashes",
    "schema": "ailoot-native-model-provenance-v2"
  },
  "page": {
    "canonical": "https://ailoot.ai/models/uz/voyage-code-2/",
    "description": "Voyage Code 2 repozitoriyda semantik qidiruv uchun manba kodi va tegishli matndan embeddinglar yaratadi. Tabiiy tildagi savollar, kod parchalari yoki aralash so‘rovlar tegishli dasturiy yechimlarni topishi mumkin; bu nashr 16 000 tokenli kontekst oynasi va 1 536 o‘lchamli vektorlardan foydalanadi.",
    "locale": "uz",
    "md_url": "https://ailoot.ai/models/uz/voyage-code-2/index.md",
    "title": "Voyage AI: Voyage Code 2 — Ailoot",
    "url": "https://ailoot.ai/models/uz/voyage-code-2/"
  },
  "rawModel": {
    "about": "Voyage Code 2 manba kodi va tegishli matn uchun sonli embeddinglar yaratadi. U semantik kod qidiruvi uchun ishlab chiqilgan: dasturchi xatti-harakatni tavsiflaydi yoki kod parchasini beradi, qidiruv tizimi esa tegishli dasturiy yechimlarni topadi. Ishlab chiqaruvchi misollarida qidiruv kirishi sifatida tabiiy tildagi savollar, kod parchalari va ikkalasining birikmalari bor.\n\nUndan haqiqiy dasturlash savollariga yo‘naltirilgan repozitoriy qidiruvini yaratish uchun foydalaning. Dasturchi faqat birinchi va oxirgi mos kelgan belgilarni olib tashlaydigan protsedurani yoki loyihaning daraxtni aylanib chiqishning muayyan usulini qo‘llaydigan qismini izlashi mumkin. Xatti-harakatni aniq ifodalaydigan, kerakli yechimni yaqin, ammo noto‘g‘ri variantdan ajratadigan shartni ham o‘z ichiga olgan so‘rovlarni tayyorlang.\n\nHar bir faylni ixtiyoriy belgilar sonida bo‘lish o‘rniga kodni foydali birliklarda indekslang. Funksiya signaturasi, tanasi va tegishli izohini birga saqlang. Yordamchi funksiya mahalliy turlar yoki doimiy qiymatlarga bog‘liq bo‘lsa, uning vazifasini tushunish uchun yetarli atrof matnini saqlang. Natija asl kodni bevosita ochishi uchun fayl yo‘llari, repozitoriy tahrirlari va manba joylashuvlarini embeddingdan tashqarida saqlang.\n\nBu nashr 16 000 tokenli kontekst oynasiga ega va 1 536 o‘lchamli embeddinglar yaratadi. Vektor indeksini shu ifodaga mos hajmlang va so‘rov hamda hujjat embeddinglarini ayni model bilan bog‘liq saqlang. Voyage Code 2 bilan allaqachon indekslangan to‘plam manba yozuvlari yangilanayotganda bir xil qidiruv ifodasini saqlashi mumkin. Boshqa embedding nashriga o‘tish ayni repozitoriyda aniq taqqoslanadigan indeks migratsiyasi sifatida ko‘rilishi kerak.\n\nTabiiy tildagi so‘rovda operatsiya, kirishlar va tegishli natijani tavsiflang. Kod so‘rovida mantiqi moslashtirilishi kerak bo‘lgan parchani kiriting va qidiruvga muhim har qanday shartni tushuntiring. Masalan, qayta urinishni qayta ishlaydigan kodni izlashda kod vaqt tugagach qayta urinadimi yoki to‘liq xato javobidan keyinmi, deb aniqlashtirish mumkin. Topilgan manbani tahrirda ishlatishdan oldin shu farq bo‘yicha tekshirish kerak.\n\nHujjatlar ham, manba kodi ham indekslansa, ikkalasini ham asl manbasiga kuzatish imkonini saqlang. Izohli parcha foydali kontekst bo‘lishi mumkin, dasturchi tekshirishi kerak bo‘lgan artefakt esa dasturiy yechimning o‘zi. Qidiruv sahifasi to‘g‘ri manzilni ko‘rsatishi va dasturlash yordamchisi tavsifni bajariladigan manba kodidan ajratishi uchun yozuv turlarini yorliqlang.\n\nTopilgan parchalardan repozitoriyda yo‘l topish, dasturiy yechimni aniqlash yoki dasturlash yordamchisining keyingi bosqichi uchun kontekst sifatida foydalaning. Keyingi bosqichga berishda to‘liq tegishli parcha va uning joylashuvini saqlang. O‘xshashlik nomzod kodni topishga yordam beradi; haqiqiy kirishlar, yon ta’sirlar va shartlarni tekshirish esa nomzod joriy muammoni hal qiladimi, shuni aniqlaydi.\n\nQidiruvni manbadagi javoblari ma’lum haqiqiy savollar to‘plamida baholang. Nomi o‘zgargan funksiyalar, chalg‘ituvchi izohlar, chegaraviy holatlari turli o‘xshash yordamchi vositalar va kodda yo‘q so‘zlardan foydalanadigan so‘rovlarni kiriting. Kutilgan yechim foydali natijalar orasida chiqishini va ko‘rsatilgan parcha uni baholashga yetarli kontekst berishini tekshiring. Repozitoriy o‘sganda ham shu savollarni saqlang: ma’lumot ajratish, parcha chegaralari yoki indekslashdagi o‘zgarishlarni ayni vazifalarda solishtirish mumkin bo‘lsin.",
    "about_sha256": "02443af503f57362991a7f624a9b2b777836a591a3816de5330425a291427ffb",
    "alias_of": null,
    "aliases": [],
    "author": "Voyage AI",
    "capabilities": {
      "context_length": 16000,
      "manufacturer_input": [
        "text"
      ],
      "manufacturer_output": [
        "embeddings"
      ]
    },
    "card_routes": [
      {
        "label": "Ultra",
        "rates": [
          {
            "amount": "0.0004000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.0000004",
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0",
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          }
        ],
        "summary": "Konfiguratsiya narxlari tafsilotlarda to‘liq ko‘rsatilgan."
      }
    ],
    "ctx": null,
    "display_name": "Voyage AI: Voyage Code 2",
    "formats": [
      "embeddings"
    ],
    "id": "voyage-code-2",
    "input": [
      "text"
    ],
    "kind": "embedding",
    "locale": "en",
    "max_out": null,
    "methods": [
      {
        "cache_read": null,
        "cache_write": null,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Save the complete JSON response, every vector with its index, all usage fields and request headers.",
            "lifecycle": {
              "content": [],
              "create": {
                "http": "POST",
                "path": "/v1/embeddings"
              },
              "mode": "synchronous",
              "status": [],
              "unknown": "Solishtirib tekshirish uchun asl javobni va X-Client-Request-ID qiymatini saqlang. Noaniq javob ayni yaratish so‘rovini qayta yuborishga ruxsat bermaydi.",
              "unknown_no_replay": true
            },
            "outputs": {
              "all_results": "To‘liq JSON javobini, har bir vektorni o‘z indeksi bilan, foydalanishga oid barcha maydonlarni va so‘rov sarlavhalarini saqlang.",
              "every_actual_output": true,
              "family": "embedding",
              "fields": [
                {
                  "name": "object",
                  "type": "string"
                },
                {
                  "name": "model",
                  "type": "string"
                },
                {
                  "name": "data[].index",
                  "type": "integer"
                },
                {
                  "name": "data[].embedding",
                  "type": "array<number>"
                },
                {
                  "name": "usage",
                  "type": "object"
                },
                {
                  "name": "usage.prompt_tokens",
                  "type": "integer"
                },
                {
                  "name": "usage.total_tokens",
                  "type": "integer"
                }
              ]
            },
            "parameters": [
              {
                "conditions": "Ailoot ning aniq model tanlagichidan foydalaning.",
                "default_known": false,
                "enum": [
                  "voyage-code-2"
                ],
                "enum_known": true,
                "maximum_length": null,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "conditions": "Matn yoki matnlar ro‘yxati; qaytarilgan har bir data elementi va uning indeksiga bittadan vektor saqlang.",
                "default_known": false,
                "enum_known": false,
                "maximum_length": null,
                "name": "input",
                "oneOf": [
                  {
                    "minLength": 1,
                    "type": "string"
                  },
                  {
                    "items": {
                      "minLength": 1,
                      "type": "string"
                    },
                    "minItems": 1,
                    "type": "array"
                  }
                ],
                "required": true,
                "type": "string or array<string>"
              }
            ],
            "request_schema": {
              "additionalProperties": true,
              "properties": {
                "input": {
                  "oneOf": [
                    {
                      "minLength": 1,
                      "type": "string"
                    },
                    {
                      "items": {
                        "minLength": 1,
                        "type": "string"
                      },
                      "minItems": 1,
                      "type": "array"
                    }
                  ]
                },
                "model": {
                  "enum": [
                    "voyage-code-2"
                  ],
                  "type": "string"
                }
              },
              "required": [
                "model",
                "input"
              ],
              "type": "object"
            },
            "schema_template": {
              "actual_file_preparation_required": false,
              "body": {
                "input": "The quick brown fox jumps over the lazy dog",
                "model": "voyage-code-2"
              },
              "content_type": "application/json"
            }
          },
          "input": {
            "conditions": [
              "Tanlangan model bilan matn yuboring; qaytarilgan har bir vektor va uning indeksini saqlang."
            ],
            "content_type": "application/json",
            "material_types": [
              "text"
            ],
            "optional": [],
            "required": [
              "model",
              "input"
            ]
          },
          "lifecycle": {
            "content": [],
            "create": {
              "http": "POST",
              "path": "/v1/embeddings"
            },
            "mode": "synchronous",
            "status": [],
            "unknown": "Keep the original response and X-Client-Request-ID for reconciliation. An ambiguous response is not permission to submit the same creation again.",
            "unknown_no_replay": true
          },
          "method": {
            "http": "POST",
            "path": "/v1/embeddings"
          },
          "output": {
            "all_results": "Save the complete JSON response, every vector with its index, all usage fields and request headers.",
            "every_actual_output": true,
            "family": "embedding",
            "fields": [
              {
                "name": "object",
                "type": "string"
              },
              {
                "name": "model",
                "type": "string"
              },
              {
                "name": "data[].index",
                "type": "integer"
              },
              {
                "name": "data[].embedding",
                "type": "array<number>"
              },
              {
                "name": "usage",
                "type": "object"
              },
              {
                "name": "usage.prompt_tokens",
                "type": "integer"
              },
              {
                "name": "usage.total_tokens",
                "type": "integer"
              }
            ]
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Tokenlar uchun bazaviy tariflar",
            "units": [
              {
                "amount": "0.0004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000004",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\ncat > request.json <<'JSON'\n{\n  \"model\": \"voyage-code-2\",\n  \"input\": \"The quick brown fox jumps over the lazy dog\"\n}\nJSON\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/embeddings \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o embeddings.json\n# Keep every data item and its index, the full usage object and response headers.\n",
            "label": "curl · save all vectors and usage",
            "language": "bash"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "embeddings",
        "http": "POST",
        "in": 0.4,
        "input": [
          "text"
        ],
        "label": "Embeddinglar",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "out": 0,
        "output": [
          "embedding"
        ],
        "path": "/v1/embeddings",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "token",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0.0004000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.0000004",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "request_model_id": "voyage-code-2",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": "0.0004000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.0000004",
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0",
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          }
        ]
      }
    ],
    "model_aliases": [
      {
        "canonical_model_id": "voyage-code-2",
        "request_model_id": "voyage-code-2",
        "route_label": "Ultra"
      }
    ],
    "name": "Voyage AI: Voyage Code 2",
    "price": {
      "in": 0.4,
      "in_label": null,
      "out": 0,
      "out_label": null,
      "scope_label": "Token rates",
      "sort_in": 0.4,
      "sort_out": 0,
      "varies": false
    },
    "short": "Voyage Code 2 repozitoriyda semantik qidiruv uchun manba kodi va tegishli matndan embeddinglar yaratadi. Tabiiy tildagi savollar, kod parchalari yoki aralash so‘rovlar tegishli dasturiy yechimlarni topishi mumkin; bu nashr 16 000 tokenli kontekst oynasi va 1 536 o‘lchamli vektorlardan foydalanadi.",
    "short_sha256": "392f5ff2471da11418d1ad1c0971fff44fb348ff0d8d619073b3d78c51bb9acb"
  },
  "renderer_schema": {
    "method_order": "Original DTO methods order; every exact route/format/path/caller survives.",
    "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers."
  },
  "representation": "exact-public-dto-and-native-renderer-html",
  "representationNotes": {
    "current_reference": {
      "about_json_pointer": "/aboutHtml",
      "methods": [
        {
          "contract_json_pointer": "/methods/0/rawMethod/contract",
          "html_json_pointer": "/methods/0/html",
          "method_ordinal": 0
        }
      ],
      "role": "current-semantic-reference"
    },
    "raw_input": {
      "examples_role": "historical-input-not-current-ready-examples",
      "json_pointers": [
        "/rawModel",
        "/methods/0/rawMethod"
      ],
      "role": "historical-owner-input"
    },
    "schema": "ailoot-native-model-representations-v1"
  },
  "schema": "ailoot-static-model-facts-v1",
  "schema_version": 1,
  "shortText": "Voyage Code 2 repozitoriyda semantik qidiruv uchun manba kodi va tegishli matndan embeddinglar yaratadi. Tabiiy tildagi savollar, kod parchalari yoki aralash so‘rovlar tegishli dasturiy yechimlarni topishi mumkin; bu nashr 16 000 tokenli kontekst oynasi va 1 536 o‘lchamli vektorlardan foydalanadi.",
  "source": {
    "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1",
    "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036",
    "raw_model_json_sha256": "eadc8d46f56349d9af43515a2dca5ce5cdd12fab7f7960ddba4df2bb3db0eac5",
    "renderer_sha256": "aa8a0fca1bd770c042b64987512b6187fca2067aea3ddc877f68b163d80e7df6"
  },
  "sourceRevision": "f448f1173fea019f90b50248914f84fbda36821cf7fd2b01935c39e58bec69bc"
}