{ "aboutHtml": "

Jina Reranker v2 Base Multilingual — ma’lumot olishning ikkinchi bosqichi uchun matn tartiblash modeli. Unga so‘rov va nomzod hujjatlar yoki parchalarni bering; u har bir so‘rov–hujjat juftligini baholab, tegishlilik ballini qaytaradi. Foydali natija — qidiruv yoki ma’lumot olish bilan boyitilgan jarayon uchun yaxshiroq tartiblangan nomzodlar to‘plami. U so‘rov javobini yozmaydi yoki hujjat embeddinglarini yaratmaydi.

So‘rov va nomzod parchalarni tayyorlang

So‘rovni axborot ehtiyojini aytadigan qilib yozing. So‘ng oldingi ma’lumot olish bosqichi topgan matnlarni bering. Tegishlilik ballini asl hujjat, bo‘lim yoki yozuvga bog‘lash uchun har nomzod yonida barqaror identifikator saqlang.

Yordam qidiruvida haqiqiy savol va tegishli jarayonni o‘z ichiga oladigan nomzod parchalarni ishlating. Muayyan qurilmani qayta tiklash haqidagi so‘rov qurilma nomi, versiyasi va qayta tiklash shartlari saqlangan parchalar bilan juftlanishi kerak. Qurilmani shunchaki eslatadigan parcha so‘ralgan operatsiyani tushuntiradiganidan kamroq foydali bo‘lishi mumkin. Faqat hujjat sarlavhasini emas, model solishtirishi kerak bo‘lgan mazmunni bering.

Yaxlit parchalar ishlating. Jadval sarlavhasi, ta’rif yoki istisno paragrafning so‘rovga aloqasini o‘zgartirishi mumkin; barcha nomzodlar bir xil qisqa bo‘lsin deb ularni olib tashlamang. Qayta tartiblovchi berilgan nomzodlarni baholaydi; oldingi ma’lumot olish bosqichi tashlab ketgan tegishli hujjatni tiklay olmaydi.

So‘rov–hujjat juftligini baholash

Bu cross-encoder: so‘rov va nomzod matn birgalikda qayta ishlanadi. Bevosita baholash interfeysi har mos juftlik uchun suzuvchi nuqtali tegishlilik ballini qaytaradi. Yuqoriroq ball shu taqqoslashda ko‘proq tegishlilikni bildiradi. Ball generatsiya qilingan izoh yoki hujjat rostligining isboti emas, tartiblash signalidir.

Ishlab chiqaruvchi ballari bilan tartiblangan hujjatlarni qaytaradigan qayta tartiblash yordamchisini ham beradi. Yuqori natijalar boshqaruvi nechta tartiblangan nomzod saqlanishini tanlaydi. Keyingi bosqichga o‘tkazishda identifikator va matnlarni saqlang. Savol-javob jarayonida keyingi modelga ham so‘rov va tanlangan dalil kerak; tartiblangan ro‘yxatning o‘zi savolga javob emas.

Ma’lumot olish o‘zgarishlarini solishtirganda so‘rov va baholash mezonlarini o‘zgartirmang. Yuqoriga chiqarilgan parchalar haqiqatan so‘ralgan axborotni o‘z ichiga olishini tekshiring. Tegishlilik ballini javob to‘g‘riligining universal o‘lchovi deb ko‘rmasdan, har qanday filtrlash chegarasini o‘z to‘plamingiz misollari asosida belgilang.

Model oynasi va uzunroq hujjatlar

Model 1 024 tokengacha kontekst uzunligini qo‘llab-quvvatlaydi. Hujjatlashtirilgan rerank() yordamchisi uzunroq hujjatlarda siljuvchi oyna yondashuvidan foydalanadi, qismlarni alohida baholaydi va hujjat darajasidagi natijalarga birlashtiradi. Bo‘laklash shu yordamchining xatti-harakatidir; uni cheksiz kontekst oynali bitta model kirishi bilan chalkashtirmang.

Yordamchi so‘rov uzunligi, bo‘lak uzunligi va ustma-ust tushish sozlamasini ochadi. Hujjatlashtirilgan standart ustma-ust tushish qiymati 80. E’lon qilingan foydalanish misoli maksimal so‘rov uzunligini 512, bo‘lak uzunligini 1 024 deb belgilaydi; bu yordamchi misoli sozlamalarini har bir chaqiruvchi yoki marshrut ulardan foydalanadi degan va’dadan ajrating.

Uzun qo‘llanmada ko‘rsatma va shartlari birga ko‘rinishi uchun atrofdagi yetarli matnni saqlang. Natijani baholashda yuqori o‘rindagi hujjatning har bo‘limi savolga teng darajada javob beradi deb taxmin qilmasdan, tegishli qismini tekshiring.

Ko‘p tilli va maxsus matndan ma’lumot olish

v2 modeli ko‘p tilli. Ishlab chiqaruvchi misollari inglizcha so‘rovlarni ingliz, nemis, ispan, xitoy va yaponcha parchalar bilan tartiblaydi. Bu tegishli material bir nechta tilda yozilgan to‘plamda avval har nomzodni so‘rov tiliga tarjima qilmasdan ishlashni qo‘llab-quvvatlaydi.

Hujjatlashtirilgan vazifalarga kodni topish va funksiya yoki SQL bilan bog‘liq matn ifodalarini tartiblash ham kiradi. Bular tegishlilikni tartiblash vazifalari bo‘lib qoladi: model berilgan matnni baholaydi. Nomzodlar to‘plamida shunday materiallar borligi uchungina funksiya bajarmaydi, SQL ishga tushirmaydi yoki vosita natijasi yaratmaydi.

Nashr va amaliy chegaralar

Ushbu v2 Base Multilingual variantini Jina’ning oldingi faqat inglizcha qayta tartiblovchisi, Jina Reranker v3 va multimodal qayta tartiblash variantlaridan ajrating. Ular vazifa va kirish xususiyatlari turlicha modellar. Bu variantning kirishi so‘rov–matn juftliklaridir; tasvir yoki video mazmuni o‘ziga mos ifoda yoki modelga muhtoj.

Ishlab chiqaruvchining namunaviy amalga oshirishi bevosita ballar va hujjat tartiblash yordamchisini, ixtiyoriy tezlashtirilgan diqqatni qo‘llab-quvvatlaydi. Bu tanlovlar kirishlarni tayyorlash va qayta ishlash usuliga ta’sir qiladi; har integratsiya bir xil boshqaruvlarni ochishini tasdiqlamaydi.

Tartiblangan chiqishdan ko‘p tilli qidiruv, yordam bilim bazalari, hujjat olish va generatsiyadan oldingi dalil tanlashda foydalaning. Yuqori parchalarni tekshiring, asl nomzod bog‘lanishini saqlang va tegishlilikni faktik yaroqlilikdan ajrating. Foydali qidiruv natijasi to‘g‘ri berilgan dalilni oldinga chiqarib, keyingi javob berish, qisqartirish yoki qaror qilish vazifasini tegishli jarayonga qoldiradi.

", "aboutText": "Jina Reranker v2 Base Multilingual — ma’lumot olishning ikkinchi bosqichi uchun matn tartiblash modeli. Unga so‘rov va nomzod hujjatlar yoki parchalarni bering; u har bir so‘rov–hujjat juftligini baholab, tegishlilik ballini qaytaradi. Foydali natija — qidiruv yoki ma’lumot olish bilan boyitilgan jarayon uchun yaxshiroq tartiblangan nomzodlar to‘plami. U so‘rov javobini yozmaydi yoki hujjat embeddinglarini yaratmaydi.\n\n### So‘rov va nomzod parchalarni tayyorlang\n\nSo‘rovni axborot ehtiyojini aytadigan qilib yozing. So‘ng oldingi ma’lumot olish bosqichi topgan matnlarni bering. Tegishlilik ballini asl hujjat, bo‘lim yoki yozuvga bog‘lash uchun har nomzod yonida barqaror identifikator saqlang.\n\nYordam qidiruvida haqiqiy savol va tegishli jarayonni o‘z ichiga oladigan nomzod parchalarni ishlating. Muayyan qurilmani qayta tiklash haqidagi so‘rov qurilma nomi, versiyasi va qayta tiklash shartlari saqlangan parchalar bilan juftlanishi kerak. Qurilmani shunchaki eslatadigan parcha so‘ralgan operatsiyani tushuntiradiganidan kamroq foydali bo‘lishi mumkin. Faqat hujjat sarlavhasini emas, model solishtirishi kerak bo‘lgan mazmunni bering.\n\nYaxlit parchalar ishlating. Jadval sarlavhasi, ta’rif yoki istisno paragrafning so‘rovga aloqasini o‘zgartirishi mumkin; barcha nomzodlar bir xil qisqa bo‘lsin deb ularni olib tashlamang. Qayta tartiblovchi berilgan nomzodlarni baholaydi; oldingi ma’lumot olish bosqichi tashlab ketgan tegishli hujjatni tiklay olmaydi.\n\n### So‘rov–hujjat juftligini baholash\n\nBu cross-encoder: so‘rov va nomzod matn birgalikda qayta ishlanadi. Bevosita baholash interfeysi har mos juftlik uchun suzuvchi nuqtali tegishlilik ballini qaytaradi. Yuqoriroq ball shu taqqoslashda ko‘proq tegishlilikni bildiradi. Ball generatsiya qilingan izoh yoki hujjat rostligining isboti emas, tartiblash signalidir.\n\nIshlab chiqaruvchi ballari bilan tartiblangan hujjatlarni qaytaradigan qayta tartiblash yordamchisini ham beradi. Yuqori natijalar boshqaruvi nechta tartiblangan nomzod saqlanishini tanlaydi. Keyingi bosqichga o‘tkazishda identifikator va matnlarni saqlang. Savol-javob jarayonida keyingi modelga ham so‘rov va tanlangan dalil kerak; tartiblangan ro‘yxatning o‘zi savolga javob emas.\n\nMa’lumot olish o‘zgarishlarini solishtirganda so‘rov va baholash mezonlarini o‘zgartirmang. Yuqoriga chiqarilgan parchalar haqiqatan so‘ralgan axborotni o‘z ichiga olishini tekshiring. Tegishlilik ballini javob to‘g‘riligining universal o‘lchovi deb ko‘rmasdan, har qanday filtrlash chegarasini o‘z to‘plamingiz misollari asosida belgilang.\n\n### Model oynasi va uzunroq hujjatlar\n\nModel 1 024 tokengacha kontekst uzunligini qo‘llab-quvvatlaydi. Hujjatlashtirilgan `rerank()` yordamchisi uzunroq hujjatlarda siljuvchi oyna yondashuvidan foydalanadi, qismlarni alohida baholaydi va hujjat darajasidagi natijalarga birlashtiradi. Bo‘laklash shu yordamchining xatti-harakatidir; uni cheksiz kontekst oynali bitta model kirishi bilan chalkashtirmang.\n\nYordamchi so‘rov uzunligi, bo‘lak uzunligi va ustma-ust tushish sozlamasini ochadi. Hujjatlashtirilgan standart ustma-ust tushish qiymati 80. E’lon qilingan foydalanish misoli maksimal so‘rov uzunligini 512, bo‘lak uzunligini 1 024 deb belgilaydi; bu yordamchi misoli sozlamalarini har bir chaqiruvchi yoki marshrut ulardan foydalanadi degan va’dadan ajrating.\n\nUzun qo‘llanmada ko‘rsatma va shartlari birga ko‘rinishi uchun atrofdagi yetarli matnni saqlang. Natijani baholashda yuqori o‘rindagi hujjatning har bo‘limi savolga teng darajada javob beradi deb taxmin qilmasdan, tegishli qismini tekshiring.\n\n### Ko‘p tilli va maxsus matndan ma’lumot olish\n\nv2 modeli ko‘p tilli. Ishlab chiqaruvchi misollari inglizcha so‘rovlarni ingliz, nemis, ispan, xitoy va yaponcha parchalar bilan tartiblaydi. Bu tegishli material bir nechta tilda yozilgan to‘plamda avval har nomzodni so‘rov tiliga tarjima qilmasdan ishlashni qo‘llab-quvvatlaydi.\n\nHujjatlashtirilgan vazifalarga kodni topish va funksiya yoki SQL bilan bog‘liq matn ifodalarini tartiblash ham kiradi. Bular tegishlilikni tartiblash vazifalari bo‘lib qoladi: model berilgan matnni baholaydi. Nomzodlar to‘plamida shunday materiallar borligi uchungina funksiya bajarmaydi, SQL ishga tushirmaydi yoki vosita natijasi yaratmaydi.\n\n### Nashr va amaliy chegaralar\n\nUshbu v2 Base Multilingual variantini Jina’ning oldingi faqat inglizcha qayta tartiblovchisi, Jina Reranker v3 va multimodal qayta tartiblash variantlaridan ajrating. Ular vazifa va kirish xususiyatlari turlicha modellar. Bu variantning kirishi so‘rov–matn juftliklaridir; tasvir yoki video mazmuni o‘ziga mos ifoda yoki modelga muhtoj.\n\nIshlab chiqaruvchining namunaviy amalga oshirishi bevosita ballar va hujjat tartiblash yordamchisini, ixtiyoriy tezlashtirilgan diqqatni qo‘llab-quvvatlaydi. Bu tanlovlar kirishlarni tayyorlash va qayta ishlash usuliga ta’sir qiladi; har integratsiya bir xil boshqaruvlarni ochishini tasdiqlamaydi.\n\nTartiblangan chiqishdan ko‘p tilli qidiruv, yordam bilim bazalari, hujjat olish va generatsiyadan oldingi dalil tanlashda foydalaning. Yuqori parchalarni tekshiring, asl nomzod bog‘lanishini saqlang va tegishlilikni faktik yaroqlilikdan ajrating. Foydali qidiruv natijasi to‘g‘ri berilgan dalilni oldinga chiqarib, keyingi javob berish, qisqartirish yoki qaror qilish vazifasini tegishli jarayonga qoldiradi.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "c32e2634342eed98bccef40861f191d5e59e5517d71b1f1fbba2b9af3d07bb5e", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "uz", "methods": [ { "html": "
•

jina-reranker-v2-base-multilingual

Jina AI /jina-reranker-v2-base-multilingual

Boshlash

Jina Reranker v2 Base Multilingual so‘rovni nomzod matnlarga solishtirib baholaydi va ularni tegishliligi bo‘yicha tartiblaydi. Uning cross-encoder tuzilishi ko‘p tilli ma’lumot olish bilan ishlaydi, ishlab chiqaruvchining qayta tartiblash yordamchisi esa uzunroq hujjatlarni 1 024 tokenli model oynasiga mos bo‘laklaydi.

Qabul qilinadigan kirish ma’lumotlari
Matn
Natijalar
Saralangan natijalar
Model haqida

Bu tavsif model imkoniyatlarini yoritadi. Ailoot da tanlangan usul uchun mavjud kirish, chiqish va parametrlar quyida keltirilgan.

Jina Reranker v2 Base Multilingual — ma’lumot olishning ikkinchi bosqichi uchun matn tartiblash modeli. Unga so‘rov va nomzod hujjatlar yoki parchalarni bering; u har bir so‘rov–hujjat juftligini baholab, tegishlilik ballini qaytaradi. Foydali natija — qidiruv yoki ma’lumot olish bilan boyitilgan jarayon uchun yaxshiroq tartiblangan nomzodlar to‘plami. U so‘rov javobini yozmaydi yoki hujjat embeddinglarini yaratmaydi.

So‘rov va nomzod parchalarni tayyorlang

So‘rovni axborot ehtiyojini aytadigan qilib yozing. So‘ng oldingi ma’lumot olish bosqichi topgan matnlarni bering. Tegishlilik ballini asl hujjat, bo‘lim yoki yozuvga bog‘lash uchun har nomzod yonida barqaror identifikator saqlang.

Yordam qidiruvida haqiqiy savol va tegishli jarayonni o‘z ichiga oladigan nomzod parchalarni ishlating. Muayyan qurilmani qayta tiklash haqidagi so‘rov qurilma nomi, versiyasi va qayta tiklash shartlari saqlangan parchalar bilan juftlanishi kerak. Qurilmani shunchaki eslatadigan parcha so‘ralgan operatsiyani tushuntiradiganidan kamroq foydali bo‘lishi mumkin. Faqat hujjat sarlavhasini emas, model solishtirishi kerak bo‘lgan mazmunni bering.

Yaxlit parchalar ishlating. Jadval sarlavhasi, ta’rif yoki istisno paragrafning so‘rovga aloqasini o‘zgartirishi mumkin; barcha nomzodlar bir xil qisqa bo‘lsin deb ularni olib tashlamang. Qayta tartiblovchi berilgan nomzodlarni baholaydi; oldingi ma’lumot olish bosqichi tashlab ketgan tegishli hujjatni tiklay olmaydi.

So‘rov–hujjat juftligini baholash

Bu cross-encoder: so‘rov va nomzod matn birgalikda qayta ishlanadi. Bevosita baholash interfeysi har mos juftlik uchun suzuvchi nuqtali tegishlilik ballini qaytaradi. Yuqoriroq ball shu taqqoslashda ko‘proq tegishlilikni bildiradi. Ball generatsiya qilingan izoh yoki hujjat rostligining isboti emas, tartiblash signalidir.

Ishlab chiqaruvchi ballari bilan tartiblangan hujjatlarni qaytaradigan qayta tartiblash yordamchisini ham beradi. Yuqori natijalar boshqaruvi nechta tartiblangan nomzod saqlanishini tanlaydi. Keyingi bosqichga o‘tkazishda identifikator va matnlarni saqlang. Savol-javob jarayonida keyingi modelga ham so‘rov va tanlangan dalil kerak; tartiblangan ro‘yxatning o‘zi savolga javob emas.

Ma’lumot olish o‘zgarishlarini solishtirganda so‘rov va baholash mezonlarini o‘zgartirmang. Yuqoriga chiqarilgan parchalar haqiqatan so‘ralgan axborotni o‘z ichiga olishini tekshiring. Tegishlilik ballini javob to‘g‘riligining universal o‘lchovi deb ko‘rmasdan, har qanday filtrlash chegarasini o‘z to‘plamingiz misollari asosida belgilang.

Model oynasi va uzunroq hujjatlar

Model 1 024 tokengacha kontekst uzunligini qo‘llab-quvvatlaydi. Hujjatlashtirilgan rerank() yordamchisi uzunroq hujjatlarda siljuvchi oyna yondashuvidan foydalanadi, qismlarni alohida baholaydi va hujjat darajasidagi natijalarga birlashtiradi. Bo‘laklash shu yordamchining xatti-harakatidir; uni cheksiz kontekst oynali bitta model kirishi bilan chalkashtirmang.

Yordamchi so‘rov uzunligi, bo‘lak uzunligi va ustma-ust tushish sozlamasini ochadi. Hujjatlashtirilgan standart ustma-ust tushish qiymati 80. E’lon qilingan foydalanish misoli maksimal so‘rov uzunligini 512, bo‘lak uzunligini 1 024 deb belgilaydi; bu yordamchi misoli sozlamalarini har bir chaqiruvchi yoki marshrut ulardan foydalanadi degan va’dadan ajrating.

Uzun qo‘llanmada ko‘rsatma va shartlari birga ko‘rinishi uchun atrofdagi yetarli matnni saqlang. Natijani baholashda yuqori o‘rindagi hujjatning har bo‘limi savolga teng darajada javob beradi deb taxmin qilmasdan, tegishli qismini tekshiring.

Ko‘p tilli va maxsus matndan ma’lumot olish

v2 modeli ko‘p tilli. Ishlab chiqaruvchi misollari inglizcha so‘rovlarni ingliz, nemis, ispan, xitoy va yaponcha parchalar bilan tartiblaydi. Bu tegishli material bir nechta tilda yozilgan to‘plamda avval har nomzodni so‘rov tiliga tarjima qilmasdan ishlashni qo‘llab-quvvatlaydi.

Hujjatlashtirilgan vazifalarga kodni topish va funksiya yoki SQL bilan bog‘liq matn ifodalarini tartiblash ham kiradi. Bular tegishlilikni tartiblash vazifalari bo‘lib qoladi: model berilgan matnni baholaydi. Nomzodlar to‘plamida shunday materiallar borligi uchungina funksiya bajarmaydi, SQL ishga tushirmaydi yoki vosita natijasi yaratmaydi.

Nashr va amaliy chegaralar

Ushbu v2 Base Multilingual variantini Jina’ning oldingi faqat inglizcha qayta tartiblovchisi, Jina Reranker v3 va multimodal qayta tartiblash variantlaridan ajrating. Ular vazifa va kirish xususiyatlari turlicha modellar. Bu variantning kirishi so‘rov–matn juftliklaridir; tasvir yoki video mazmuni o‘ziga mos ifoda yoki modelga muhtoj.

Ishlab chiqaruvchining namunaviy amalga oshirishi bevosita ballar va hujjat tartiblash yordamchisini, ixtiyoriy tezlashtirilgan diqqatni qo‘llab-quvvatlaydi. Bu tanlovlar kirishlarni tayyorlash va qayta ishlash usuliga ta’sir qiladi; har integratsiya bir xil boshqaruvlarni ochishini tasdiqlamaydi.

Tartiblangan chiqishdan ko‘p tilli qidiruv, yordam bilim bazalari, hujjat olish va generatsiyadan oldingi dalil tanlashda foydalaning. Yuqori parchalarni tekshiring, asl nomzod bog‘lanishini saqlang va tegishlilikni faktik yaroqlilikdan ajrating. Foydali qidiruv natijasi to‘g‘ri berilgan dalilni oldinga chiqarib, keyingi javob berish, qisqartirish yoki qaror qilish vazifasini tegishli jarayonga qoldiradi.

Ailoot da mavjud · kirish ma’lumotlari va usullar

Ailoot Ultra · Qayta saralash POST /v1/rerank
Kirish
text
Chiqish
rerank
MaydonTurTalabQiymatlar va cheklovlarStandart
MaydonmodelTurstringTalabMajburiyQiymatlar va cheklovlar
jina-reranker-v2-base-multilingual
Standart—
MaydonqueryTurstringTalabIxtiyoriyQiymatlar va cheklovlarStandart—
MaydondocumentsTurarrayTalabMajburiyQiymatlar va cheklovlarStandart—
Usul parametrlari va hayot sikli
ParametrParametr talablari
Parametrcontent_typeParametr talablariapplication/json
ParametrrequiredParametr talablarimodel, documents
Parametrmaterial_typesParametr talablaritext
Parametrmaterial_conditionsParametr talablariHaqiqiy qidiruv so‘rovingizni va dastlabki matn hujjatlarining bo‘sh bo‘lmagan massivini belgilang. Natija indekslari shu dastlabki massivga ishora qiladi.

Hayot sikli: synchronous_result_then_owned_library

GET /v1/media/assets/{asset_id}/content

GET /v1/media/assets

GET /v1/media/assets/{asset_id}

Tariflar

Tarif ma’lumotlari so‘rov imkoniyatlarini qo‘shmaydi. Qo‘llab-quvvatlanadigan parametrlar tanlangan usulda ko‘rsatilgan.

Tezkor rejim
Ko‘rsatilmagan Tezkor rejim tanlanganda
Flex rejimi
Ko‘rsatilmagan flex rejimi tanlanganda
Maksimal fikrlash darajasi
Ko‘rsatilmagan Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda

Ailoot tariflari

Sozlamalar bo‘yicha narxlar

Har bir to‘lovni ko‘rsatilgan shartlarga moslang. Har bir muqobil sozlamalar to‘plami uchun bitta tarifdan foydalaning.

SozlamaTariflar jadvaliHisob birligiTo‘lov
SozlamaTokenlar uchun bazaviy tariflarTariflar jadvaliAsosiy tarifHisob birligi—To‘lov
Kirish · Kirish tokenlari — / 1K token
Chiqish · Chiqish tokenlari — / 1K token
Kirish · Keshdan o‘qish — / 1K token
Kirish · Keshga yozish — / 1K token
Kirish · Keshga yozish, 1 soat — / 1K token
SozlamaJami tokenTariflar jadvali—Hisob birligi/ 1K tokenTo‘lov
Kirish · Jami token $0.0001 / 1K token

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. Summani band qilish va to‘lovni hisoblash tartibi →

So‘rov namunalari

Ailoot Ultra · Qayta saralash

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_QUERY:?Set the actual documented input value}"\nexport AILOOT_QUERY\n: "${AILOOT_DOCUMENTS_JSON:?Set the actual documented input value}"\nexport AILOOT_DOCUMENTS_JSON\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\nrequest={'model': 'jina-reranker-v2-base-multilingual', 'query': '${ACTUAL_QUERY}', 'documents': '${ACTUAL_DOCUMENTS}'}\nrequest['query']=os.environ['AILOOT_QUERY']\nrequest['documents']=json.loads(os.environ['AILOOT_DOCUMENTS_JSON'])\nPath('request.json').write_text(json.dumps(request,ensure_ascii=False),encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/rerank \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o response.bin\n# Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.\n

Natijalarni olish va saqlash

Ailoot Ultra · Qayta saralash

Sozlangan javob modeli, dastlabki hujjat indekslari, moslik baholari, hujjat satrlari va asl token sarfi mavjud to‘liq dastlabki asl JSON natijasi. Har bir haqiqiy natija va foydalanish maydonini saqlang.

Barcha tayyor natijalarni saqlash

Qaytarilgan har bir to‘liq javob, fayl va kontent qismini saqlang.

To‘liq javob va sarlavhalarni, amalda qaytarilgan barcha natijalarni, dastlab qaytarilgan identifikatorlarni hamda barcha usage maydonlarini saqlang. Yaratish so‘rovini qayta yubormasdan dastlabki operatsiyani tiklang.

Asl javobni tekshirish kerak bo‘lsa

Haqiqiy X-Client-Request-ID va to‘liq javobni saqlang. Egalik qilinadigan dastlabki aktivlar va ularning aniq imzolangan mazmun URL larini o‘qing; natijasi noaniq yaratishni hech qachon qayta yubormang.

Javob maydonlari
MaydonTurMa’nosi
MaydonmodelTurstringMa’nosiManbada sozlangan javobni qayta ishlovchi talab qiladigan aniq javob modeli.
Maydonresults[].indexTurintegerMa’nosiDastlabki kirish hujjatining noyob indeksi.
Maydonresults[].relevance_scoreTurnumberMa’nosiChekli moslik bahosi.
Maydonresults[].documentTurstringMa’nosiUshbu sozlangan javob iste’molchisi talab qiladigan dastlabki matn hujjati.
Maydonusage.total_tokensTurintegerMa’nosiHozirgi qabul qilingan tarif talab qiladigan chekli, manfiy bo‘lmagan asl tokenlar soni.
Xatolar va keyingi qadamlar
JavobShartKeyingi qadam
Javob400 · invalid_request_errorShartJSON tanasi yoki ochiq ko‘rsatilgan kanonik model ID si yaroqsiz.Keyingi qadamJavobni saqlang va ko‘rsatilgan so‘rov maydonini tuzating.
Javob401 · authentication_errorShartAiloot API kaliti yaroqsiz.Keyingi qadamRuxsat berilgan Ailoot API kalitingizdan foydalaning.
Javob403 · permission_errorShartKalit guruhi bu usulga ruxsat bermaydi.Keyingi qadamQaytarilgan xato tafsilotlarini saqlang.
Javob404 · not_found_errorShartTanlangan usul uchun ruxsat etilgan yo‘nalish yo‘q.Keyingi qadamQaytarilgan xato tafsilotlarini saqlang.
Javob422 · price_unavailableShartQabul qilingan tarif zarur kirish miqdorini yoki chegarasini aniqlay olmaydi.Keyingi qadamJavobni saqlang; qabul qilingan tarif talab qiladigan kirish ko‘rinishidan foydalaning.
Javob503 · ShartZarur saqlov, yo‘nalish, usul narxi yoki mablag‘ni band qilish imkoniyati mavjud emas.Keyingi qadamTo‘liq dastlabki javobni saqlang. Noaniq mablag‘ band qilish qayta yuborishga ruxsat bermaydi.
Javob502 · billing_requires_checkShartDastlabki natija, foydalanish ma’lumoti yoki hisob-kitobni tekshirish talab qilinadi.Keyingi qadamHaqiqiy so‘rov ID si va dastlabki javobni saqlang. Mavjud, egalik qilinadigan yozuvni o‘qing; yaratishni qayta yubormang.

Taxalluslar

Model taxalluslari

Ailoot Ultra jina-reranker-v2-base-multilingual

Usul yo‘llari taxalluslari

Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.

Chaqirish uchun tegishli ID lar

jina-reranker-v2-base-multilingual

", "method_identity": { "effective_request_model_id": "jina-reranker-v2-base-multilingual", "fmt": "rerank", "http": "POST", "path": "/v1/rerank", "request_model_id": "jina-reranker-v2-base-multilingual", "route_label": "Ultra" }, "method_key": "Ultra|rerank|/v1/rerank|jina-reranker-v2-base-multilingual", "ordinal": 0, "rawMethod": { "available": null, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.", "errors": [ { "code": null, "condition": "JSON tanasi yoki ochiq ko‘rsatilgan kanonik model ID si yaroqsiz.", "http_status": 400, "recovery": "Javobni saqlang va ko‘rsatilgan so‘rov maydonini tuzating.", "type": "invalid_request_error" }, { "code": null, "condition": "Ailoot API kaliti yaroqsiz.", "http_status": 401, "recovery": "Ruxsat berilgan Ailoot API kalitingizdan foydalaning.", "type": "authentication_error" }, { "code": null, "condition": "Kalit guruhi bu usulga ruxsat bermaydi.", "http_status": 403, "recovery": "Qaytarilgan xato tafsilotlarini saqlang.", "type": "permission_error" }, { "code": null, "condition": "Tanlangan usul uchun ruxsat etilgan yo‘nalish yo‘q.", "http_status": 404, "recovery": "Qaytarilgan xato tafsilotlarini saqlang.", "type": "not_found_error" }, { "code": null, "condition": "Qabul qilingan tarif zarur kirish miqdorini yoki chegarasini aniqlay olmaydi.", "http_status": 422, "recovery": "Javobni saqlang; qabul qilingan tarif talab qiladigan kirish ko‘rinishidan foydalaning.", "type": "price_unavailable" }, { "code": null, "condition": "Zarur saqlov, yo‘nalish, usul narxi yoki mablag‘ni band qilish imkoniyati mavjud emas.", "http_status": 503, "recovery": "To‘liq dastlabki javobni saqlang. Noaniq mablag‘ band qilish qayta yuborishga ruxsat bermaydi.", "type": null }, { "code": null, "condition": "Dastlabki natija, foydalanish ma’lumoti yoki hisob-kitobni tekshirish talab qilinadi.", "http_status": 502, "recovery": "Haqiqiy so‘rov ID si va dastlabki javobni saqlang. Mavjud, egalik qilinadigan yozuvni o‘qing; yaratishni qayta yubormang.", "type": "billing_requires_check" } ], "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed content URL" } ], "dedicated_method_polling_or_cancel": false, "mode": "synchronous_result_then_owned_library", "original_POST_adds_task_envelope": false, "status": [], "unknown": "Haqiqiy X-Client-Request-ID va to‘liq javobni saqlang. Egalik qilinadigan dastlabki aktivlar va ularning aniq imzolangan mazmun URL larini o‘qing; natijasi noaniq yaratishni hech qachon qayta yubormang." }, "outputs": { "all_results": "To‘liq javob va sarlavhalarni, amalda qaytarilgan barcha natijalarni, dastlab qaytarilgan identifikatorlarni hamda barcha usage maydonlarini saqlang. Yaratish so‘rovini qayta yubormasdan dastlabki operatsiyani tiklang.", "family": "rerank", "fields": [ { "description": "Manbada sozlangan javobni qayta ishlovchi talab qiladigan aniq javob modeli.", "name": "model", "type": "string" }, { "description": "Dastlabki kirish hujjatining noyob indeksi.", "name": "results[].index", "type": "integer" }, { "description": "Chekli moslik bahosi.", "name": "results[].relevance_score", "type": "number" }, { "description": "Ushbu sozlangan javob iste’molchisi talab qiladigan dastlabki matn hujjati.", "name": "results[].document", "type": "string" }, { "description": "Hozirgi qabul qilingan tarif talab qiladigan chekli, manfiy bo‘lmagan asl tokenlar soni.", "name": "usage.total_tokens", "type": "integer" } ], "result": "Sozlangan javob modeli, dastlabki hujjat indekslari, moslik baholari, hujjat satrlari va asl token sarfi mavjud to‘liq dastlabki asl JSON natijasi. Har bir haqiqiy natija va foydalanish maydonini saqlang." }, "parameters": [ { "default_known": false, "enum": [ "jina-reranker-v2-base-multilingual" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "default_known": false, "enum_known": false, "name": "query", "required": false, "type": "string" }, { "default_known": false, "enum_known": false, "name": "documents", "required": true, "type": "array" } ], "request_schema": { "properties": { "documents": { "items": { "type": "string" }, "minItems": 1, "type": "array" }, "model": { "enum": [ "jina-reranker-v2-base-multilingual" ], "type": "string" }, "query": { "type": "string" } }, "required": [ "model", "documents" ], "type": "object" }, "schema_template": { "actual_file_preparation_required": false, "body": { "documents": "${ACTUAL_DOCUMENTS}", "model": "jina-reranker-v2-base-multilingual", "query": "${ACTUAL_QUERY}" }, "content_type": "application/json" } }, "input": { "content_type": "application/json", "material_conditions": [ "Haqiqiy qidiruv so‘rovingizni va dastlabki matn hujjatlarining bo‘sh bo‘lmagan massivini belgilang. Natija indekslari shu dastlabki massivga ishora qiladi." ], "material_types": [ "text" ], "required": [ "model", "documents" ] }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed content URL" } ], "dedicated_method_polling_or_cancel": false, "mode": "synchronous_result_then_owned_library", "original_POST_adds_task_envelope": false, "status": [], "unknown": "Retain the actual X-Client-Request-ID and complete response. Read the original owned assets and their exact signed content URLs; never resubmit an uncertain creation." }, "method": { "http": "POST", "path": "/v1/rerank" }, "output": { "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.", "family": "rerank", "fields": [ { "description": "Exact response model required by the configured Source consumer.", "name": "model", "type": "string" }, { "description": "Unique original input document index.", "name": "results[].index", "type": "integer" }, { "description": "Finite relevance score.", "name": "results[].relevance_score", "type": "number" }, { "description": "Original text document required by this configured response consumer.", "name": "results[].document", "type": "string" }, { "description": "Finite nonnegative native token count required by the current accepted tariff.", "name": "usage.total_tokens", "type": "integer" } ], "result": "Complete original native JSON result with the configured response model, original document indices, relevance scores, document strings and native token usage. Retain every actual result and usage field." } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "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": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "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" } ] }, { "dimensions": { "quoted_unit": "/ 1K tokens" }, "label": "total token", "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "total_token", "label": "total token", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "total_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "total_token" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_QUERY:?Set the actual documented input value}\"\nexport AILOOT_QUERY\n: \"${AILOOT_DOCUMENTS_JSON:?Set the actual documented input value}\"\nexport AILOOT_DOCUMENTS_JSON\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\nrequest={'model': 'jina-reranker-v2-base-multilingual', 'query': '${ACTUAL_QUERY}', 'documents': '${ACTUAL_DOCUMENTS}'}\nrequest['query']=os.environ['AILOOT_QUERY']\nrequest['documents']=json.loads(os.environ['AILOOT_DOCUMENTS_JSON'])\nPath('request.json').write_text(json.dumps(request,ensure_ascii=False),encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/rerank \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o response.bin\n# Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.\n", "label": "Use actual input and retain the complete result", "language": "bash" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "rerank", "hints": [ "Set your actual query and nonempty array of original text documents. Result indices refer to that original array.", "The minimum example omits top_n, return_documents, instruct and other optional controls.", "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again." ], "http": "POST", "in": null, "input": [ "text" ], "label": "Qayta saralash", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "native_endpoint": "rerank", "out": null, "output": [ "rerank" ], "path": "/v1/rerank", "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": "per_request", "image_input_price": null, "image_output_price": null, "per_request_price": null, "unit_prices": { "total_token": 1e-07 } }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "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": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "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" } ] }, { "dimensions": { "quoted_unit": "/ 1K tokens" }, "label": "total token", "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "total_token", "label": "total token", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "total_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "total_token" } ] } ], "request_model_id": "jina-reranker-v2-base-multilingual", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "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": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "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" }, { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "total_token", "label": "total token", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "total_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "total_token" } ] } } ], "model_id": "jina-reranker-v2-base-multilingual", "nativeProvenance": { "input_facts_canonical_sha256": "19778f6c02a8f78b4b8df6a58af4e991a767d6669f8a8933ce487820dfdad38c", "input_html_sha256": "197de92fe2802db84f643f53d0e327b3056b13af57f8da2abba89033916c9546", "private_audit_sha256": "52f2eda02d16c7abefd2a499fea5487fe0a95a00b2871d005703f7caeb9c5a9a", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/uz/jina-reranker-v2-base-multilingual/", "description": "Jina Reranker v2 Base Multilingual so‘rovni nomzod matnlarga solishtirib baholaydi va ularni tegishliligi bo‘yicha tartiblaydi. Uning cross-encoder tuzilishi ko‘p tilli ma’lumot olish bilan ishlaydi, ishlab chiqaruvchining qayta tartiblash yordamchisi esa uzunroq hujjatlarni 1 024 tokenli model oynasiga mos bo‘laklaydi.", "locale": "uz", "md_url": "https://ailoot.ai/models/uz/jina-reranker-v2-base-multilingual/index.md", "title": "jina-reranker-v2-base-multilingual — Ailoot", "url": "https://ailoot.ai/models/uz/jina-reranker-v2-base-multilingual/" }, "rawModel": { "about": "Jina Reranker v2 Base Multilingual — ma’lumot olishning ikkinchi bosqichi uchun matn tartiblash modeli. Unga so‘rov va nomzod hujjatlar yoki parchalarni bering; u har bir so‘rov–hujjat juftligini baholab, tegishlilik ballini qaytaradi. Foydali natija — qidiruv yoki ma’lumot olish bilan boyitilgan jarayon uchun yaxshiroq tartiblangan nomzodlar to‘plami. U so‘rov javobini yozmaydi yoki hujjat embeddinglarini yaratmaydi.\n\n### So‘rov va nomzod parchalarni tayyorlang\n\nSo‘rovni axborot ehtiyojini aytadigan qilib yozing. So‘ng oldingi ma’lumot olish bosqichi topgan matnlarni bering. Tegishlilik ballini asl hujjat, bo‘lim yoki yozuvga bog‘lash uchun har nomzod yonida barqaror identifikator saqlang.\n\nYordam qidiruvida haqiqiy savol va tegishli jarayonni o‘z ichiga oladigan nomzod parchalarni ishlating. Muayyan qurilmani qayta tiklash haqidagi so‘rov qurilma nomi, versiyasi va qayta tiklash shartlari saqlangan parchalar bilan juftlanishi kerak. Qurilmani shunchaki eslatadigan parcha so‘ralgan operatsiyani tushuntiradiganidan kamroq foydali bo‘lishi mumkin. Faqat hujjat sarlavhasini emas, model solishtirishi kerak bo‘lgan mazmunni bering.\n\nYaxlit parchalar ishlating. Jadval sarlavhasi, ta’rif yoki istisno paragrafning so‘rovga aloqasini o‘zgartirishi mumkin; barcha nomzodlar bir xil qisqa bo‘lsin deb ularni olib tashlamang. Qayta tartiblovchi berilgan nomzodlarni baholaydi; oldingi ma’lumot olish bosqichi tashlab ketgan tegishli hujjatni tiklay olmaydi.\n\n### So‘rov–hujjat juftligini baholash\n\nBu cross-encoder: so‘rov va nomzod matn birgalikda qayta ishlanadi. Bevosita baholash interfeysi har mos juftlik uchun suzuvchi nuqtali tegishlilik ballini qaytaradi. Yuqoriroq ball shu taqqoslashda ko‘proq tegishlilikni bildiradi. Ball generatsiya qilingan izoh yoki hujjat rostligining isboti emas, tartiblash signalidir.\n\nIshlab chiqaruvchi ballari bilan tartiblangan hujjatlarni qaytaradigan qayta tartiblash yordamchisini ham beradi. Yuqori natijalar boshqaruvi nechta tartiblangan nomzod saqlanishini tanlaydi. Keyingi bosqichga o‘tkazishda identifikator va matnlarni saqlang. Savol-javob jarayonida keyingi modelga ham so‘rov va tanlangan dalil kerak; tartiblangan ro‘yxatning o‘zi savolga javob emas.\n\nMa’lumot olish o‘zgarishlarini solishtirganda so‘rov va baholash mezonlarini o‘zgartirmang. Yuqoriga chiqarilgan parchalar haqiqatan so‘ralgan axborotni o‘z ichiga olishini tekshiring. Tegishlilik ballini javob to‘g‘riligining universal o‘lchovi deb ko‘rmasdan, har qanday filtrlash chegarasini o‘z to‘plamingiz misollari asosida belgilang.\n\n### Model oynasi va uzunroq hujjatlar\n\nModel 1 024 tokengacha kontekst uzunligini qo‘llab-quvvatlaydi. Hujjatlashtirilgan `rerank()` yordamchisi uzunroq hujjatlarda siljuvchi oyna yondashuvidan foydalanadi, qismlarni alohida baholaydi va hujjat darajasidagi natijalarga birlashtiradi. Bo‘laklash shu yordamchining xatti-harakatidir; uni cheksiz kontekst oynali bitta model kirishi bilan chalkashtirmang.\n\nYordamchi so‘rov uzunligi, bo‘lak uzunligi va ustma-ust tushish sozlamasini ochadi. Hujjatlashtirilgan standart ustma-ust tushish qiymati 80. E’lon qilingan foydalanish misoli maksimal so‘rov uzunligini 512, bo‘lak uzunligini 1 024 deb belgilaydi; bu yordamchi misoli sozlamalarini har bir chaqiruvchi yoki marshrut ulardan foydalanadi degan va’dadan ajrating.\n\nUzun qo‘llanmada ko‘rsatma va shartlari birga ko‘rinishi uchun atrofdagi yetarli matnni saqlang. Natijani baholashda yuqori o‘rindagi hujjatning har bo‘limi savolga teng darajada javob beradi deb taxmin qilmasdan, tegishli qismini tekshiring.\n\n### Ko‘p tilli va maxsus matndan ma’lumot olish\n\nv2 modeli ko‘p tilli. Ishlab chiqaruvchi misollari inglizcha so‘rovlarni ingliz, nemis, ispan, xitoy va yaponcha parchalar bilan tartiblaydi. Bu tegishli material bir nechta tilda yozilgan to‘plamda avval har nomzodni so‘rov tiliga tarjima qilmasdan ishlashni qo‘llab-quvvatlaydi.\n\nHujjatlashtirilgan vazifalarga kodni topish va funksiya yoki SQL bilan bog‘liq matn ifodalarini tartiblash ham kiradi. Bular tegishlilikni tartiblash vazifalari bo‘lib qoladi: model berilgan matnni baholaydi. Nomzodlar to‘plamida shunday materiallar borligi uchungina funksiya bajarmaydi, SQL ishga tushirmaydi yoki vosita natijasi yaratmaydi.\n\n### Nashr va amaliy chegaralar\n\nUshbu v2 Base Multilingual variantini Jina’ning oldingi faqat inglizcha qayta tartiblovchisi, Jina Reranker v3 va multimodal qayta tartiblash variantlaridan ajrating. Ular vazifa va kirish xususiyatlari turlicha modellar. Bu variantning kirishi so‘rov–matn juftliklaridir; tasvir yoki video mazmuni o‘ziga mos ifoda yoki modelga muhtoj.\n\nIshlab chiqaruvchining namunaviy amalga oshirishi bevosita ballar va hujjat tartiblash yordamchisini, ixtiyoriy tezlashtirilgan diqqatni qo‘llab-quvvatlaydi. Bu tanlovlar kirishlarni tayyorlash va qayta ishlash usuliga ta’sir qiladi; har integratsiya bir xil boshqaruvlarni ochishini tasdiqlamaydi.\n\nTartiblangan chiqishdan ko‘p tilli qidiruv, yordam bilim bazalari, hujjat olish va generatsiyadan oldingi dalil tanlashda foydalaning. Yuqori parchalarni tekshiring, asl nomzod bog‘lanishini saqlang va tegishlilikni faktik yaroqlilikdan ajrating. Foydali qidiruv natijasi to‘g‘ri berilgan dalilni oldinga chiqarib, keyingi javob berish, qisqartirish yoki qaror qilish vazifasini tegishli jarayonga qoldiradi.", "alias_of": null, "aliases": [], "author": "Jina AI", "capabilities": { "context_length": 0, "manufacturer_input": [], "manufacturer_output": [] }, "card_routes": [ { "label": "Ultra", "rates": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "total_token", "label": "total token", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "total_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "total_token" } ], "summary": "Konfiguratsiya narxlari tafsilotlarda to‘liq ko‘rsatilgan." } ], "ctx": null, "formats": [ "rerank" ], "id": "jina-reranker-v2-base-multilingual", "input": [ "text" ], "kind": "text", "max_out": null, "methods": [ { "available": null, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.", "errors": [ { "code": null, "condition": "JSON tanasi yoki ochiq ko‘rsatilgan kanonik model ID si yaroqsiz.", "http_status": 400, "recovery": "Javobni saqlang va ko‘rsatilgan so‘rov maydonini tuzating.", "type": "invalid_request_error" }, { "code": null, "condition": "Ailoot API kaliti yaroqsiz.", "http_status": 401, "recovery": "Ruxsat berilgan Ailoot API kalitingizdan foydalaning.", "type": "authentication_error" }, { "code": null, "condition": "Kalit guruhi bu usulga ruxsat bermaydi.", "http_status": 403, "recovery": "Qaytarilgan xato tafsilotlarini saqlang.", "type": "permission_error" }, { "code": null, "condition": "Tanlangan usul uchun ruxsat etilgan yo‘nalish yo‘q.", "http_status": 404, "recovery": "Qaytarilgan xato tafsilotlarini saqlang.", "type": "not_found_error" }, { "code": null, "condition": "Qabul qilingan tarif zarur kirish miqdorini yoki chegarasini aniqlay olmaydi.", "http_status": 422, "recovery": "Javobni saqlang; qabul qilingan tarif talab qiladigan kirish ko‘rinishidan foydalaning.", "type": "price_unavailable" }, { "code": null, "condition": "Zarur saqlov, yo‘nalish, usul narxi yoki mablag‘ni band qilish imkoniyati mavjud emas.", "http_status": 503, "recovery": "To‘liq dastlabki javobni saqlang. Noaniq mablag‘ band qilish qayta yuborishga ruxsat bermaydi.", "type": null }, { "code": null, "condition": "Dastlabki natija, foydalanish ma’lumoti yoki hisob-kitobni tekshirish talab qilinadi.", "http_status": 502, "recovery": "Haqiqiy so‘rov ID si va dastlabki javobni saqlang. Mavjud, egalik qilinadigan yozuvni o‘qing; yaratishni qayta yubormang.", "type": "billing_requires_check" } ], "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed content URL" } ], "dedicated_method_polling_or_cancel": false, "mode": "synchronous_result_then_owned_library", "original_POST_adds_task_envelope": false, "status": [], "unknown": "Haqiqiy X-Client-Request-ID va to‘liq javobni saqlang. Egalik qilinadigan dastlabki aktivlar va ularning aniq imzolangan mazmun URL larini o‘qing; natijasi noaniq yaratishni hech qachon qayta yubormang." }, "outputs": { "all_results": "To‘liq javob va sarlavhalarni, amalda qaytarilgan barcha natijalarni, dastlab qaytarilgan identifikatorlarni hamda barcha usage maydonlarini saqlang. Yaratish so‘rovini qayta yubormasdan dastlabki operatsiyani tiklang.", "family": "rerank", "fields": [ { "description": "Manbada sozlangan javobni qayta ishlovchi talab qiladigan aniq javob modeli.", "name": "model", "type": "string" }, { "description": "Dastlabki kirish hujjatining noyob indeksi.", "name": "results[].index", "type": "integer" }, { "description": "Chekli moslik bahosi.", "name": "results[].relevance_score", "type": "number" }, { "description": "Ushbu sozlangan javob iste’molchisi talab qiladigan dastlabki matn hujjati.", "name": "results[].document", "type": "string" }, { "description": "Hozirgi qabul qilingan tarif talab qiladigan chekli, manfiy bo‘lmagan asl tokenlar soni.", "name": "usage.total_tokens", "type": "integer" } ], "result": "Sozlangan javob modeli, dastlabki hujjat indekslari, moslik baholari, hujjat satrlari va asl token sarfi mavjud to‘liq dastlabki asl JSON natijasi. Har bir haqiqiy natija va foydalanish maydonini saqlang." }, "parameters": [ { "default_known": false, "enum": [ "jina-reranker-v2-base-multilingual" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "default_known": false, "enum_known": false, "name": "query", "required": false, "type": "string" }, { "default_known": false, "enum_known": false, "name": "documents", "required": true, "type": "array" } ], "request_schema": { "properties": { "documents": { "items": { "type": "string" }, "minItems": 1, "type": "array" }, "model": { "enum": [ "jina-reranker-v2-base-multilingual" ], "type": "string" }, "query": { "type": "string" } }, "required": [ "model", "documents" ], "type": "object" }, "schema_template": { "actual_file_preparation_required": false, "body": { "documents": "${ACTUAL_DOCUMENTS}", "model": "jina-reranker-v2-base-multilingual", "query": "${ACTUAL_QUERY}" }, "content_type": "application/json" } }, "input": { "content_type": "application/json", "material_conditions": [ "Haqiqiy qidiruv so‘rovingizni va dastlabki matn hujjatlarining bo‘sh bo‘lmagan massivini belgilang. Natija indekslari shu dastlabki massivga ishora qiladi." ], "material_types": [ "text" ], "required": [ "model", "documents" ] }, "lifecycle": { "assets": [ { "http": "GET", "path": "/v1/media/assets" }, { "http": "GET", "path": "/v1/media/assets/{asset_id}" } ], "content": [ { "http": "GET", "path": "/v1/media/assets/{asset_id}/content", "url_source": "exact returned signed content URL" } ], "dedicated_method_polling_or_cancel": false, "mode": "synchronous_result_then_owned_library", "original_POST_adds_task_envelope": false, "status": [], "unknown": "Retain the actual X-Client-Request-ID and complete response. Read the original owned assets and their exact signed content URLs; never resubmit an uncertain creation." }, "method": { "http": "POST", "path": "/v1/rerank" }, "output": { "all_results": "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.", "family": "rerank", "fields": [ { "description": "Exact response model required by the configured Source consumer.", "name": "model", "type": "string" }, { "description": "Unique original input document index.", "name": "results[].index", "type": "integer" }, { "description": "Finite relevance score.", "name": "results[].relevance_score", "type": "number" }, { "description": "Original text document required by this configured response consumer.", "name": "results[].document", "type": "string" }, { "description": "Finite nonnegative native token count required by the current accepted tariff.", "name": "usage.total_tokens", "type": "integer" } ], "result": "Complete original native JSON result with the configured response model, original document indices, relevance scores, document strings and native token usage. Retain every actual result and usage field." } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "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": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "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" } ] }, { "dimensions": { "quoted_unit": "/ 1K tokens" }, "label": "total token", "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "total_token", "label": "total token", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "total_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "total_token" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_QUERY:?Set the actual documented input value}\"\nexport AILOOT_QUERY\n: \"${AILOOT_DOCUMENTS_JSON:?Set the actual documented input value}\"\nexport AILOOT_DOCUMENTS_JSON\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\nrequest={'model': 'jina-reranker-v2-base-multilingual', 'query': '${ACTUAL_QUERY}', 'documents': '${ACTUAL_DOCUMENTS}'}\nrequest['query']=os.environ['AILOOT_QUERY']\nrequest['documents']=json.loads(os.environ['AILOOT_DOCUMENTS_JSON'])\nPath('request.json').write_text(json.dumps(request,ensure_ascii=False),encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/rerank \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o response.bin\n# Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again.\n", "label": "Use actual input and retain the complete result", "language": "bash" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "rerank", "hints": [ "Set your actual query and nonempty array of original text documents. Result indices refer to that original array.", "The minimum example omits top_n, return_documents, instruct and other optional controls.", "Retain the complete response and headers, every actual output, original returned identifiers and all usage fields. Recover the original operation without submitting creation again." ], "http": "POST", "in": null, "input": [ "text" ], "label": "Qayta saralash", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "native_endpoint": "rerank", "out": null, "output": [ "rerank" ], "path": "/v1/rerank", "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": "per_request", "image_input_price": null, "image_output_price": null, "per_request_price": null, "unit_prices": { "total_token": 1e-07 } }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "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": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "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" } ] }, { "dimensions": { "quoted_unit": "/ 1K tokens" }, "label": "total token", "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "total_token", "label": "total token", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "total_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "total_token" } ] } ], "request_model_id": "jina-reranker-v2-base-multilingual", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": null, "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": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": null, "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" }, { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "total_token", "label": "total token", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "total_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "total_token" } ] } ], "model_aliases": [ { "canonical_model_id": "jina-reranker-v2-base-multilingual", "request_model_id": "jina-reranker-v2-base-multilingual", "route_label": "Ultra" } ], "name": "jina-reranker-v2-base-multilingual", "price": { "in": null, "in_label": null, "out": null, "out_label": null, "sort_in": null, "sort_out": null, "varies": true }, "short": "Jina Reranker v2 Base Multilingual so‘rovni nomzod matnlarga solishtirib baholaydi va ularni tegishliligi bo‘yicha tartiblaydi. Uning cross-encoder tuzilishi ko‘p tilli ma’lumot olish bilan ishlaydi, ishlab chiqaruvchining qayta tartiblash yordamchisi esa uzunroq hujjatlarni 1 024 tokenli model oynasiga mos bo‘laklaydi." }, "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": "Jina Reranker v2 Base Multilingual so‘rovni nomzod matnlarga solishtirib baholaydi va ularni tegishliligi bo‘yicha tartiblaydi. Uning cross-encoder tuzilishi ko‘p tilli ma’lumot olish bilan ishlaydi, ishlab chiqaruvchining qayta tartiblash yordamchisi esa uzunroq hujjatlarni 1 024 tokenli model oynasiga mos bo‘laklaydi.", "source": { "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1", "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036", "raw_model_json_sha256": "cd971bc6059766595325bdd9bb4f0a259c9797d4415879c03f051715e76e00df", "renderer_sha256": "aa8a0fca1bd770c042b64987512b6187fca2067aea3ddc877f68b163d80e7df6" }, "sourceRevision": "490648b452d9cf3fc65dd7fd37e64b11f7bc0b9add51f311a4f0b23adced6516" }