{ "aboutHtml": "

GPT-4o Transcribe — OpenAI kompaniyasining GPT-4o asosidagi nutqni matnga aylantirish modeli. Uning kirishi — ixtiyoriy matnli yo‘riq bilan audio, chiqishi esa tanilgan matndir. U GPT-4o Mini Transcribe nashridan va so‘zlovchilarni belgilashga ixtisoslashgan GPT-4o Transcribe Diarize modelidan alohida. Bu profildan nutqning aniq matnli yozuvini tayyorlash uchun foydalaning; manba audioni tekshirish va keyingi tahrir uchun saqlang.

Fayl kirishi va uzun materialni tayyorlash

OpenAI transkripsiya qo‘llanmasida 25 MB gacha yuklash hujjatlashtirilgan. Joriy endpoint ma’lumotnomasi FLAC, MP3, MP4, MPEG, MPGA, M4A, OGG, WAV va WebM ni qabul qiladi hamda formatni belgilaydigan fayl metama’lumotlarini, jumladan kengaytmali fayl nomi va mos kontent turini tavsiya qiladi. Kattaroq yozuv uchun siqish yoki 25 MB dan oshmaydigan tartiblangan qismlar ishlab chiqaruvchining uzun kirish bo‘yicha yo‘riqlariga mos keladi. Gap o‘rtasidan bo‘lmang va har bir qismning butun yozuvdagi o‘rnini saqlang.

Intervyuda har bir kirish faylini yozuv va u qamrab oladigan parcha bilan bog‘lang. Texnik taqdimotda tegishli mahsulot nomlari, qisqartmalar va soha lug‘atini kontekst sifatida tayyorlang, so‘ng ularning yozilishini so‘zlovchi aslida aytgan gap bilan tekshiring. Sonli qiymatlarga ega yozib olingan tushuntirishni yozma tartibga aylantirishdan oldin transkriptni manba bilan solishtiring. Kerakli birinchi artefakt — matn shaklida tanilgan nutq; qisqa hisobot yoki tarjima qilingan hujjatni shu matndan alohida bosqichda tayyorlash mumkin.

Yozuvga xos promptlar va til tanlovi

Ishlab chiqaruvchi qo‘llanmasi GPT-4o Transcribe ni promptlarni qo‘llaydigan modellar qatoriga aniq kiritadi. Prompt to‘g‘ri yozilishlar, oldingi segment konteksti va tinish belgilari, bosh harflar, to‘ldiruvchi so‘zlar yoki yozuv tizimi bo‘yicha istaklarni berishi mumkin. Ma’lumotnomaga ko‘ra, u yozuv tiliga mos kelishi kerak. Mavzu va lug‘atning qisqa, tegishli tavsifi aytilmagan terminlarni majburiy chiqish deb qabul qilmasdan, transkripsiyaga foydali kontekst beradi.

Bu profil ISO 639-1 shaklida hujjatlashtirilgan, bitta tilni bildiruvchi language ko‘rsatmasini qo‘llaydi. Haqiqiy kirish tilini berish tanishga yordam berishi mumkin. Yangi keywords va ko‘plikdagi languages maydonlari alohida nomlangan GPT Transcribe modeliga tegishli; ularni GPT-4o Transcribe uchun bor deb hisoblamang. Til sozlamasini transkripsiya qilinadigan nutqqa bog‘lang va keyingi tarjima yoki uslubiy qayta yozishdan oldin asl so‘zlarni saqlang.

Natija formati, ehtimollar va maxsus chiqishlar

Joriy endpoint ma’lumotnomasi JSON ni GPT-4o Transcribe qo‘llaydigan javob formati sifatida hujjatlashtiradi. Natijada tanilgan matn bo‘ladi va shu JSON formatida ixtiyoriy token logarifmik ehtimollarini so‘rash mumkin. Ehtimol ma’lumotlari modelning token tanlovini ifodalaydi. Ular qaysi parchalarni tekshirish kerakligini ko‘rsatishi mumkin, ammo transkript murakkab ism, son yoki iborani to‘g‘ri aks ettirganini audio bilan solishtirish belgilaydi.

Standart profilning JSON natijasi modelning o‘z subtitr formatlari, batafsil so‘z vaqt belgilari yoki so‘zlovchi tayinlovlarini bermaydi. Bunday chiqishlar kerak bo‘lsa, OpenAI boshqa model va format tanlovlarini hujjatlashtiradi; GPT-4o Transcribe Diarize — so‘zlovchilarni belgilash uchun alohida nashr. Subtitr vazifasida mos vaqt belgilash bosqichi uchun tekshirilgan transkriptni saqlang. Suhbat transkriptida bir paragraf mavzu yoki ovozni o‘zgartirgandek ko‘ringani uchungina so‘zlovchi ismlarini o‘ylab topmang.

Tugallangan fayldan oqimli natijalar

OpenAI ning nutqni matnga aylantirish qo‘llanmasi mavjud GPT-4o Transcribe integratsiyalari fayldan oqimli uzatishni qo‘llashini aytadi. Dastur avval yozuvni taqdim etadi, keyin u qayta ishlanayotganda transkript matnini oladi va tugallangan natijani saqlaydi. Bu mikrofon audiosini kelishi bilan qabul qilish emas, tugallangan yozuv transkriptini oqimli uzatishdir. Aynan shu model kartasida transkripsiya va Realtime endpoint oilalari ham sanab o‘tilgan; modelga xos sessiya xatti-harakati yangi, uzluksiz oqimli modeldan olinmasdan, shu profilga bog‘langan holda qolishi kerak.

Model chegaralari va yakuniy artefaktni tekshirish

Joriy GPT-4o Transcribe spetsifikatsiyasida 16,000 tokenli kontekst oynasi, ko‘pi bilan 2,000 chiqish tokeni va 2024-yil 1-iyundagi bilimlar chegarasi ko‘rsatilgan. Bu token limitlari belgilangan audio davomiyligi emas va fayldan transkripsiya tayyorlash qoidalarini almashtirmaydi. Uzun yozuvda manba tartibi va tegishli oldingi kontekstni saqlang, so‘ng tugallangan matn har bir kerakli segment oxirigacha yetganini tekshiring.

Foydali yakuniy transkript qidirish mumkin bo‘lgan intervyu materiali, texnik hujjatlar manbasi yoki keyingi subtitr jarayoni uchun matnga aylanishi mumkin. Noaniq lug‘at, miqdorlar, tinish belgilari, aksentlar va bir vaqtda gapirishni yozuv bilan tekshiring. Tanilgan matnni keyingi tuzatishlar yoki qisqacha bayonlardan ajrating va atrofdagi jarayon identifikatorlari orqali manba bilan bog‘lanishni saqlang. Model matnli yozuvni beradi; kirishni puxta tayyorlash va manbani tekshirish bu yozuv keyingi foydalanishga mos kelishini belgilaydi.

", "aboutText": "GPT-4o Transcribe — OpenAI kompaniyasining GPT-4o asosidagi nutqni matnga aylantirish modeli. Uning kirishi — ixtiyoriy matnli yo‘riq bilan audio, chiqishi esa tanilgan matndir. U GPT-4o Mini Transcribe nashridan va so‘zlovchilarni belgilashga ixtisoslashgan GPT-4o Transcribe Diarize modelidan alohida. Bu profildan nutqning aniq matnli yozuvini tayyorlash uchun foydalaning; manba audioni tekshirish va keyingi tahrir uchun saqlang.\n\n### Fayl kirishi va uzun materialni tayyorlash\n\nOpenAI transkripsiya qo‘llanmasida 25 MB gacha yuklash hujjatlashtirilgan. Joriy endpoint ma’lumotnomasi FLAC, MP3, MP4, MPEG, MPGA, M4A, OGG, WAV va WebM ni qabul qiladi hamda formatni belgilaydigan fayl metama’lumotlarini, jumladan kengaytmali fayl nomi va mos kontent turini tavsiya qiladi. Kattaroq yozuv uchun siqish yoki 25 MB dan oshmaydigan tartiblangan qismlar ishlab chiqaruvchining uzun kirish bo‘yicha yo‘riqlariga mos keladi. Gap o‘rtasidan bo‘lmang va har bir qismning butun yozuvdagi o‘rnini saqlang.\n\nIntervyuda har bir kirish faylini yozuv va u qamrab oladigan parcha bilan bog‘lang. Texnik taqdimotda tegishli mahsulot nomlari, qisqartmalar va soha lug‘atini kontekst sifatida tayyorlang, so‘ng ularning yozilishini so‘zlovchi aslida aytgan gap bilan tekshiring. Sonli qiymatlarga ega yozib olingan tushuntirishni yozma tartibga aylantirishdan oldin transkriptni manba bilan solishtiring. Kerakli birinchi artefakt — matn shaklida tanilgan nutq; qisqa hisobot yoki tarjima qilingan hujjatni shu matndan alohida bosqichda tayyorlash mumkin.\n\n### Yozuvga xos promptlar va til tanlovi\n\nIshlab chiqaruvchi qo‘llanmasi GPT-4o Transcribe ni promptlarni qo‘llaydigan modellar qatoriga aniq kiritadi. Prompt to‘g‘ri yozilishlar, oldingi segment konteksti va tinish belgilari, bosh harflar, to‘ldiruvchi so‘zlar yoki yozuv tizimi bo‘yicha istaklarni berishi mumkin. Ma’lumotnomaga ko‘ra, u yozuv tiliga mos kelishi kerak. Mavzu va lug‘atning qisqa, tegishli tavsifi aytilmagan terminlarni majburiy chiqish deb qabul qilmasdan, transkripsiyaga foydali kontekst beradi.\n\nBu profil ISO 639-1 shaklida hujjatlashtirilgan, bitta tilni bildiruvchi language ko‘rsatmasini qo‘llaydi. Haqiqiy kirish tilini berish tanishga yordam berishi mumkin. Yangi keywords va ko‘plikdagi languages maydonlari alohida nomlangan GPT Transcribe modeliga tegishli; ularni GPT-4o Transcribe uchun bor deb hisoblamang. Til sozlamasini transkripsiya qilinadigan nutqqa bog‘lang va keyingi tarjima yoki uslubiy qayta yozishdan oldin asl so‘zlarni saqlang.\n\n### Natija formati, ehtimollar va maxsus chiqishlar\n\nJoriy endpoint ma’lumotnomasi JSON ni GPT-4o Transcribe qo‘llaydigan javob formati sifatida hujjatlashtiradi. Natijada tanilgan matn bo‘ladi va shu JSON formatida ixtiyoriy token logarifmik ehtimollarini so‘rash mumkin. Ehtimol ma’lumotlari modelning token tanlovini ifodalaydi. Ular qaysi parchalarni tekshirish kerakligini ko‘rsatishi mumkin, ammo transkript murakkab ism, son yoki iborani to‘g‘ri aks ettirganini audio bilan solishtirish belgilaydi.\n\nStandart profilning JSON natijasi modelning o‘z subtitr formatlari, batafsil so‘z vaqt belgilari yoki so‘zlovchi tayinlovlarini bermaydi. Bunday chiqishlar kerak bo‘lsa, OpenAI boshqa model va format tanlovlarini hujjatlashtiradi; GPT-4o Transcribe Diarize — so‘zlovchilarni belgilash uchun alohida nashr. Subtitr vazifasida mos vaqt belgilash bosqichi uchun tekshirilgan transkriptni saqlang. Suhbat transkriptida bir paragraf mavzu yoki ovozni o‘zgartirgandek ko‘ringani uchungina so‘zlovchi ismlarini o‘ylab topmang.\n\n### Tugallangan fayldan oqimli natijalar\n\nOpenAI ning nutqni matnga aylantirish qo‘llanmasi mavjud GPT-4o Transcribe integratsiyalari fayldan oqimli uzatishni qo‘llashini aytadi. Dastur avval yozuvni taqdim etadi, keyin u qayta ishlanayotganda transkript matnini oladi va tugallangan natijani saqlaydi. Bu mikrofon audiosini kelishi bilan qabul qilish emas, tugallangan yozuv transkriptini oqimli uzatishdir. Aynan shu model kartasida transkripsiya va Realtime endpoint oilalari ham sanab o‘tilgan; modelga xos sessiya xatti-harakati yangi, uzluksiz oqimli modeldan olinmasdan, shu profilga bog‘langan holda qolishi kerak.\n\n### Model chegaralari va yakuniy artefaktni tekshirish\n\nJoriy GPT-4o Transcribe spetsifikatsiyasida 16,000 tokenli kontekst oynasi, ko‘pi bilan 2,000 chiqish tokeni va 2024-yil 1-iyundagi bilimlar chegarasi ko‘rsatilgan. Bu token limitlari belgilangan audio davomiyligi emas va fayldan transkripsiya tayyorlash qoidalarini almashtirmaydi. Uzun yozuvda manba tartibi va tegishli oldingi kontekstni saqlang, so‘ng tugallangan matn har bir kerakli segment oxirigacha yetganini tekshiring.\n\nFoydali yakuniy transkript qidirish mumkin bo‘lgan intervyu materiali, texnik hujjatlar manbasi yoki keyingi subtitr jarayoni uchun matnga aylanishi mumkin. Noaniq lug‘at, miqdorlar, tinish belgilari, aksentlar va bir vaqtda gapirishni yozuv bilan tekshiring. Tanilgan matnni keyingi tuzatishlar yoki qisqacha bayonlardan ajrating va atrofdagi jarayon identifikatorlari orqali manba bilan bog‘lanishni saqlang. Model matnli yozuvni beradi; kirishni puxta tayyorlash va manbani tekshirish bu yozuv keyingi foydalanishga mos kelishini belgilaydi.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "42fc1c11a10d6423075e29a72ef36bf8fc219e09f43937a6a2b8a88d292ed0cc", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "uz", "methods": [ { "html": "
O

OpenAI: GPT-4o Transcribe

OpenAI /openai/gpt-4o-transcribe

Boshlash

GPT-4o Transcribe OpenAI ning GPT-4o nutqni tanish imkoniyatlari yordamida audioni matnga aylantiradi. U kontekstli promptlar, kirish tilini ko‘rsatish, JSON transkriptlar, fayl natijasini oqimli uzatish va noaniq so‘zlarni tekshirish uchun ixtiyoriy token logarifmik ehtimollarini qo‘llaydi.

Qabul qilinadigan kirish ma’lumotlari
Audio
Natijalar
Matn
Model haqida

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

GPT-4o Transcribe — OpenAI kompaniyasining GPT-4o asosidagi nutqni matnga aylantirish modeli. Uning kirishi — ixtiyoriy matnli yo‘riq bilan audio, chiqishi esa tanilgan matndir. U GPT-4o Mini Transcribe nashridan va so‘zlovchilarni belgilashga ixtisoslashgan GPT-4o Transcribe Diarize modelidan alohida. Bu profildan nutqning aniq matnli yozuvini tayyorlash uchun foydalaning; manba audioni tekshirish va keyingi tahrir uchun saqlang.

Fayl kirishi va uzun materialni tayyorlash

OpenAI transkripsiya qo‘llanmasida 25 MB gacha yuklash hujjatlashtirilgan. Joriy endpoint ma’lumotnomasi FLAC, MP3, MP4, MPEG, MPGA, M4A, OGG, WAV va WebM ni qabul qiladi hamda formatni belgilaydigan fayl metama’lumotlarini, jumladan kengaytmali fayl nomi va mos kontent turini tavsiya qiladi. Kattaroq yozuv uchun siqish yoki 25 MB dan oshmaydigan tartiblangan qismlar ishlab chiqaruvchining uzun kirish bo‘yicha yo‘riqlariga mos keladi. Gap o‘rtasidan bo‘lmang va har bir qismning butun yozuvdagi o‘rnini saqlang.

Intervyuda har bir kirish faylini yozuv va u qamrab oladigan parcha bilan bog‘lang. Texnik taqdimotda tegishli mahsulot nomlari, qisqartmalar va soha lug‘atini kontekst sifatida tayyorlang, so‘ng ularning yozilishini so‘zlovchi aslida aytgan gap bilan tekshiring. Sonli qiymatlarga ega yozib olingan tushuntirishni yozma tartibga aylantirishdan oldin transkriptni manba bilan solishtiring. Kerakli birinchi artefakt — matn shaklida tanilgan nutq; qisqa hisobot yoki tarjima qilingan hujjatni shu matndan alohida bosqichda tayyorlash mumkin.

Yozuvga xos promptlar va til tanlovi

Ishlab chiqaruvchi qo‘llanmasi GPT-4o Transcribe ni promptlarni qo‘llaydigan modellar qatoriga aniq kiritadi. Prompt to‘g‘ri yozilishlar, oldingi segment konteksti va tinish belgilari, bosh harflar, to‘ldiruvchi so‘zlar yoki yozuv tizimi bo‘yicha istaklarni berishi mumkin. Ma’lumotnomaga ko‘ra, u yozuv tiliga mos kelishi kerak. Mavzu va lug‘atning qisqa, tegishli tavsifi aytilmagan terminlarni majburiy chiqish deb qabul qilmasdan, transkripsiyaga foydali kontekst beradi.

Bu profil ISO 639-1 shaklida hujjatlashtirilgan, bitta tilni bildiruvchi language ko‘rsatmasini qo‘llaydi. Haqiqiy kirish tilini berish tanishga yordam berishi mumkin. Yangi keywords va ko‘plikdagi languages maydonlari alohida nomlangan GPT Transcribe modeliga tegishli; ularni GPT-4o Transcribe uchun bor deb hisoblamang. Til sozlamasini transkripsiya qilinadigan nutqqa bog‘lang va keyingi tarjima yoki uslubiy qayta yozishdan oldin asl so‘zlarni saqlang.

Natija formati, ehtimollar va maxsus chiqishlar

Joriy endpoint ma’lumotnomasi JSON ni GPT-4o Transcribe qo‘llaydigan javob formati sifatida hujjatlashtiradi. Natijada tanilgan matn bo‘ladi va shu JSON formatida ixtiyoriy token logarifmik ehtimollarini so‘rash mumkin. Ehtimol ma’lumotlari modelning token tanlovini ifodalaydi. Ular qaysi parchalarni tekshirish kerakligini ko‘rsatishi mumkin, ammo transkript murakkab ism, son yoki iborani to‘g‘ri aks ettirganini audio bilan solishtirish belgilaydi.

Standart profilning JSON natijasi modelning o‘z subtitr formatlari, batafsil so‘z vaqt belgilari yoki so‘zlovchi tayinlovlarini bermaydi. Bunday chiqishlar kerak bo‘lsa, OpenAI boshqa model va format tanlovlarini hujjatlashtiradi; GPT-4o Transcribe Diarize — so‘zlovchilarni belgilash uchun alohida nashr. Subtitr vazifasida mos vaqt belgilash bosqichi uchun tekshirilgan transkriptni saqlang. Suhbat transkriptida bir paragraf mavzu yoki ovozni o‘zgartirgandek ko‘ringani uchungina so‘zlovchi ismlarini o‘ylab topmang.

Tugallangan fayldan oqimli natijalar

OpenAI ning nutqni matnga aylantirish qo‘llanmasi mavjud GPT-4o Transcribe integratsiyalari fayldan oqimli uzatishni qo‘llashini aytadi. Dastur avval yozuvni taqdim etadi, keyin u qayta ishlanayotganda transkript matnini oladi va tugallangan natijani saqlaydi. Bu mikrofon audiosini kelishi bilan qabul qilish emas, tugallangan yozuv transkriptini oqimli uzatishdir. Aynan shu model kartasida transkripsiya va Realtime endpoint oilalari ham sanab o‘tilgan; modelga xos sessiya xatti-harakati yangi, uzluksiz oqimli modeldan olinmasdan, shu profilga bog‘langan holda qolishi kerak.

Model chegaralari va yakuniy artefaktni tekshirish

Joriy GPT-4o Transcribe spetsifikatsiyasida 16,000 tokenli kontekst oynasi, ko‘pi bilan 2,000 chiqish tokeni va 2024-yil 1-iyundagi bilimlar chegarasi ko‘rsatilgan. Bu token limitlari belgilangan audio davomiyligi emas va fayldan transkripsiya tayyorlash qoidalarini almashtirmaydi. Uzun yozuvda manba tartibi va tegishli oldingi kontekstni saqlang, so‘ng tugallangan matn har bir kerakli segment oxirigacha yetganini tekshiring.

Foydali yakuniy transkript qidirish mumkin bo‘lgan intervyu materiali, texnik hujjatlar manbasi yoki keyingi subtitr jarayoni uchun matnga aylanishi mumkin. Noaniq lug‘at, miqdorlar, tinish belgilari, aksentlar va bir vaqtda gapirishni yozuv bilan tekshiring. Tanilgan matnni keyingi tuzatishlar yoki qisqacha bayonlardan ajrating va atrofdagi jarayon identifikatorlari orqali manba bilan bog‘lanishni saqlang. Model matnli yozuvni beradi; kirishni puxta tayyorlash va manbani tekshirish bu yozuv keyingi foydalanishga mos kelishini belgilaydi.

Ailoot da mavjud · kirish ma’lumotlari va usullar

Ailoot Ultra · Transkripsiya POST /v1/audio/transcriptions
Kirish
audio
Chiqish
text
MaydonTurTalabQiymatlar va cheklovlarStandart
MaydonmodelTurstringTalabMajburiyQiymatlar va cheklovlar
openai/gpt-4o-transcribe
Standart—
Maydoninput_audioTurobjectTalabMajburiyQiymatlar va cheklovlarStandart—
Usul parametrlari va hayot sikli
ParametrParametr talablari
Parametrcontent_typeParametr talablariapplication/json
ParametrrequiredParametr talablarimodel, input_audio
Parametrmaterial_typesParametr talablariaudio
Parametrmaterial_conditionsParametr talablariMisol haqiqiy, bo‘sh bo‘lmagan PCM WAV faylingizni o‘qiydi, faylning barcha baytlarini base64 ko‘rinishida kodlaydi va input_audio.format qiymatini wav qilib yuboradi.

Hayot sikli: synchronous_result_then_owned_library

GET /v1/media/tasks/{task_id} · mavjud, egalik qilinadigan media yozuvidan aniq task_id

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
Sozlamakirish tokeniTariflar jadvali—Hisob birligi/ 1K tokenTo‘lov
Kirish $0.005 / 1K token
Sozlamachiqish tokeniTariflar jadvali—Hisob birligi/ 1K tokenTo‘lov
Chiqish $0.02 / 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 · Transkripsiya

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_AUDIO_FILE:?Set the path to your actual PCM WAV recording}"\nexport AILOOT_AUDIO_FILE\npython3 - <<'PY_REQUEST'\nimport base64, io, json, os, wave\nfrom pathlib import Path\naudio = Path(os.environ['AILOOT_AUDIO_FILE']).read_bytes()\nif not (audio[:4] == b'RIFF' and audio[8:12] == b'WAVE'):\n    raise SystemExit('Supply your actual PCM WAV audio file')\nwith wave.open(io.BytesIO(audio), 'rb') as recording:\n    if recording.getcomptype() != 'NONE' or recording.getnframes() <= 0:\n        raise SystemExit('Supply a nonempty PCM WAV recording')\nrequest = {'model': 'openai/gpt-4o-transcribe', 'input_audio': {'data': base64.b64encode(audio).decode('ascii'), 'format': 'wav'}}\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/audio/transcriptions \\\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 original response, headers and actual X-Client-Request-ID.\n# Read existing owned records for recovery; do not resubmit an uncertain operation.\n

Natijalarni olish va saqlash

Ailoot Ultra · Transkripsiya

To‘liq dastlabki javob tanasi, holat va uzatilgan sarlavhalar. Bu ishlovchi universal JSON tuzilmasi, matn maydoni yoki vazifa o‘rovini qo‘shmaydi.

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
MaydonTur
Maydontext (when present)Tur
Maydonusage (when present)Tur
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 · server_errorShartDastlabki 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 openai/gpt-4o-transcribe

Usul yo‘llari taxalluslari

Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.

Chaqirish uchun tegishli ID lar

openai/gpt-4o-transcribe

", "method_identity": { "effective_request_model_id": "openai/gpt-4o-transcribe", "fmt": "transcriptions", "http": "POST", "path": "/v1/audio/transcriptions", "request_model_id": "openai/gpt-4o-transcribe", "route_label": "Ultra" }, "method_key": "Ultra|transcriptions|/v1/audio/transcriptions|openai%2Fgpt-4o-transcribe", "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, "operation_id_source": "actual X-Client-Request-ID", "recovery": "Haqiqiy so‘rov ID si va dastlabki javobni saqlang. Mavjud, egalik qilinadigan yozuvni o‘qing; yaratishni qayta yubormang.", "response_headers": { "x-should-retry": "false" }, "type": "server_error" } ], "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": [ { "http": "GET", "id_source": "exact task_id from an existing owned media record", "path": "/v1/media/tasks/{task_id}" } ], "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": "text", "fields": [ { "description": null, "name": "text (when present)", "type": null }, { "description": null, "name": "usage (when present)", "type": null } ], "result": "To‘liq dastlabki javob tanasi, holat va uzatilgan sarlavhalar. Bu ishlovchi universal JSON tuzilmasi, matn maydoni yoki vazifa o‘rovini qo‘shmaydi." }, "parameters": [ { "default_known": false, "enum": [ "openai/gpt-4o-transcribe" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "default_known": false, "enum_known": false, "name": "input_audio", "required": true, "type": "object" } ], "request_schema": { "properties": { "input_audio": { "properties": { "data": { "contentEncoding": "base64", "type": "string" }, "format": { "type": "string" } }, "required": [ "data", "format" ], "type": "object" }, "model": { "enum": [ "openai/gpt-4o-transcribe" ], "type": "string" } }, "required": [ "model", "input_audio" ], "type": "object" }, "schema_template": { "actual_file_preparation_required": true, "body": { "input_audio": { "data": "${BASE64_ACTUAL_WAV_BYTES}", "format": "wav" }, "model": "openai/gpt-4o-transcribe" }, "content_type": "application/json" } }, "input": { "content_type": "application/json", "material_conditions": [ "Misol haqiqiy, bo‘sh bo‘lmagan PCM WAV faylingizni o‘qiydi, faylning barcha baytlarini base64 ko‘rinishida kodlaydi va input_audio.format qiymatini wav qilib yuboradi." ], "material_types": [ "audio" ], "required": [ "model", "input_audio" ] }, "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": [ { "http": "GET", "id_source": "mavjud, egalik qilinadigan media yozuvidan aniq task_id", "path": "/v1/media/tasks/{task_id}" } ], "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/audio/transcriptions" }, "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": "text", "fields": [ { "description": null, "name": "text (when present)", "type": null }, { "description": null, "name": "usage (when present)", "type": null } ], "result": "Complete original response body, status and forwarded headers. No universal JSON shape, text field or task envelope is added by this handler." } }, "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": "input token", "units": [ { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_token", "label": "input token", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" } ] }, { "dimensions": { "quoted_unit": "/ 1K tokens" }, "label": "output token", "units": [ { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_token", "label": "output token", "native_amount_usd_per_unit": "0.00002", "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" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_AUDIO_FILE:?Set the path to your actual PCM WAV recording}\"\nexport AILOOT_AUDIO_FILE\npython3 - <<'PY_REQUEST'\nimport base64, io, json, os, wave\nfrom pathlib import Path\naudio = Path(os.environ['AILOOT_AUDIO_FILE']).read_bytes()\nif not (audio[:4] == b'RIFF' and audio[8:12] == b'WAVE'):\n raise SystemExit('Supply your actual PCM WAV audio file')\nwith wave.open(io.BytesIO(audio), 'rb') as recording:\n if recording.getcomptype() != 'NONE' or recording.getnframes() <= 0:\n raise SystemExit('Supply a nonempty PCM WAV recording')\nrequest = {'model': 'openai/gpt-4o-transcribe', 'input_audio': {'data': base64.b64encode(audio).decode('ascii'), 'format': 'wav'}}\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/audio/transcriptions \\\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 original response, headers and actual X-Client-Request-ID.\n# Read existing owned records for recovery; do not resubmit an uncertain operation.\n", "label": "curl · actual WAV file and complete original result", "language": "bash" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "transcriptions", "hints": [ "The example reads your actual nonempty PCM WAV file, encodes the complete file bytes as base64 and sends input_audio.format as wav.", "The format value in the example is the documented recipe; no model-specific format list, limit or default is asserted.", "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": [ "audio" ], "label": "Transkripsiya", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "native_endpoint": "audio_transcriptions", "out": null, "output": [ "text" ], "path": "/v1/audio/transcriptions", "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": { "input_token": 5e-06, "output_token": 2e-05 } }, "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": "input token", "units": [ { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_token", "label": "input token", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" } ] }, { "dimensions": { "quoted_unit": "/ 1K tokens" }, "label": "output token", "units": [ { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_token", "label": "output token", "native_amount_usd_per_unit": "0.00002", "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" } ] } ], "request_model_id": "openai/gpt-4o-transcribe", "route_label": "Ultra", "status_reads": [ "GET /v1/media/tasks/{task_id}" ], "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": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_token", "label": "input token", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_token", "label": "output token", "native_amount_usd_per_unit": "0.00002", "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" } ] } } ], "model_id": "openai/gpt-4o-transcribe", "nativeProvenance": { "input_facts_canonical_sha256": "006f66fb6a3d9b52c3aaa208f022dc7a06305497d75fcd3496f07269c6795af4", "input_html_sha256": "22bc69ae962e8f9e9dc0b9b54d3e1e5032b5f61263c19a775b6f87fb398fc83e", "private_audit_sha256": "32c17902de51e6c313917afac53ede01eaafc09381e545ac9eb431cb3279ba31", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/uz/openai-gpt-4o-transcribe/", "description": "GPT-4o Transcribe OpenAI ning GPT-4o nutqni tanish imkoniyatlari yordamida audioni matnga aylantiradi. U kontekstli promptlar, kirish tilini ko‘rsatish, JSON transkriptlar, fayl natijasini oqimli uzatish va noaniq so‘zlarni tekshirish uchun ixtiyoriy token logarifmik ehtimollarini qo‘llaydi.", "locale": "uz", "md_url": "https://ailoot.ai/models/uz/openai-gpt-4o-transcribe/index.md", "title": "OpenAI: GPT-4o Transcribe — Ailoot", "url": "https://ailoot.ai/models/uz/openai-gpt-4o-transcribe/" }, "rawModel": { "about": "GPT-4o Transcribe — OpenAI kompaniyasining GPT-4o asosidagi nutqni matnga aylantirish modeli. Uning kirishi — ixtiyoriy matnli yo‘riq bilan audio, chiqishi esa tanilgan matndir. U GPT-4o Mini Transcribe nashridan va so‘zlovchilarni belgilashga ixtisoslashgan GPT-4o Transcribe Diarize modelidan alohida. Bu profildan nutqning aniq matnli yozuvini tayyorlash uchun foydalaning; manba audioni tekshirish va keyingi tahrir uchun saqlang.\n\n### Fayl kirishi va uzun materialni tayyorlash\n\nOpenAI transkripsiya qo‘llanmasida 25 MB gacha yuklash hujjatlashtirilgan. Joriy endpoint ma’lumotnomasi FLAC, MP3, MP4, MPEG, MPGA, M4A, OGG, WAV va WebM ni qabul qiladi hamda formatni belgilaydigan fayl metama’lumotlarini, jumladan kengaytmali fayl nomi va mos kontent turini tavsiya qiladi. Kattaroq yozuv uchun siqish yoki 25 MB dan oshmaydigan tartiblangan qismlar ishlab chiqaruvchining uzun kirish bo‘yicha yo‘riqlariga mos keladi. Gap o‘rtasidan bo‘lmang va har bir qismning butun yozuvdagi o‘rnini saqlang.\n\nIntervyuda har bir kirish faylini yozuv va u qamrab oladigan parcha bilan bog‘lang. Texnik taqdimotda tegishli mahsulot nomlari, qisqartmalar va soha lug‘atini kontekst sifatida tayyorlang, so‘ng ularning yozilishini so‘zlovchi aslida aytgan gap bilan tekshiring. Sonli qiymatlarga ega yozib olingan tushuntirishni yozma tartibga aylantirishdan oldin transkriptni manba bilan solishtiring. Kerakli birinchi artefakt — matn shaklida tanilgan nutq; qisqa hisobot yoki tarjima qilingan hujjatni shu matndan alohida bosqichda tayyorlash mumkin.\n\n### Yozuvga xos promptlar va til tanlovi\n\nIshlab chiqaruvchi qo‘llanmasi GPT-4o Transcribe ni promptlarni qo‘llaydigan modellar qatoriga aniq kiritadi. Prompt to‘g‘ri yozilishlar, oldingi segment konteksti va tinish belgilari, bosh harflar, to‘ldiruvchi so‘zlar yoki yozuv tizimi bo‘yicha istaklarni berishi mumkin. Ma’lumotnomaga ko‘ra, u yozuv tiliga mos kelishi kerak. Mavzu va lug‘atning qisqa, tegishli tavsifi aytilmagan terminlarni majburiy chiqish deb qabul qilmasdan, transkripsiyaga foydali kontekst beradi.\n\nBu profil ISO 639-1 shaklida hujjatlashtirilgan, bitta tilni bildiruvchi language ko‘rsatmasini qo‘llaydi. Haqiqiy kirish tilini berish tanishga yordam berishi mumkin. Yangi keywords va ko‘plikdagi languages maydonlari alohida nomlangan GPT Transcribe modeliga tegishli; ularni GPT-4o Transcribe uchun bor deb hisoblamang. Til sozlamasini transkripsiya qilinadigan nutqqa bog‘lang va keyingi tarjima yoki uslubiy qayta yozishdan oldin asl so‘zlarni saqlang.\n\n### Natija formati, ehtimollar va maxsus chiqishlar\n\nJoriy endpoint ma’lumotnomasi JSON ni GPT-4o Transcribe qo‘llaydigan javob formati sifatida hujjatlashtiradi. Natijada tanilgan matn bo‘ladi va shu JSON formatida ixtiyoriy token logarifmik ehtimollarini so‘rash mumkin. Ehtimol ma’lumotlari modelning token tanlovini ifodalaydi. Ular qaysi parchalarni tekshirish kerakligini ko‘rsatishi mumkin, ammo transkript murakkab ism, son yoki iborani to‘g‘ri aks ettirganini audio bilan solishtirish belgilaydi.\n\nStandart profilning JSON natijasi modelning o‘z subtitr formatlari, batafsil so‘z vaqt belgilari yoki so‘zlovchi tayinlovlarini bermaydi. Bunday chiqishlar kerak bo‘lsa, OpenAI boshqa model va format tanlovlarini hujjatlashtiradi; GPT-4o Transcribe Diarize — so‘zlovchilarni belgilash uchun alohida nashr. Subtitr vazifasida mos vaqt belgilash bosqichi uchun tekshirilgan transkriptni saqlang. Suhbat transkriptida bir paragraf mavzu yoki ovozni o‘zgartirgandek ko‘ringani uchungina so‘zlovchi ismlarini o‘ylab topmang.\n\n### Tugallangan fayldan oqimli natijalar\n\nOpenAI ning nutqni matnga aylantirish qo‘llanmasi mavjud GPT-4o Transcribe integratsiyalari fayldan oqimli uzatishni qo‘llashini aytadi. Dastur avval yozuvni taqdim etadi, keyin u qayta ishlanayotganda transkript matnini oladi va tugallangan natijani saqlaydi. Bu mikrofon audiosini kelishi bilan qabul qilish emas, tugallangan yozuv transkriptini oqimli uzatishdir. Aynan shu model kartasida transkripsiya va Realtime endpoint oilalari ham sanab o‘tilgan; modelga xos sessiya xatti-harakati yangi, uzluksiz oqimli modeldan olinmasdan, shu profilga bog‘langan holda qolishi kerak.\n\n### Model chegaralari va yakuniy artefaktni tekshirish\n\nJoriy GPT-4o Transcribe spetsifikatsiyasida 16,000 tokenli kontekst oynasi, ko‘pi bilan 2,000 chiqish tokeni va 2024-yil 1-iyundagi bilimlar chegarasi ko‘rsatilgan. Bu token limitlari belgilangan audio davomiyligi emas va fayldan transkripsiya tayyorlash qoidalarini almashtirmaydi. Uzun yozuvda manba tartibi va tegishli oldingi kontekstni saqlang, so‘ng tugallangan matn har bir kerakli segment oxirigacha yetganini tekshiring.\n\nFoydali yakuniy transkript qidirish mumkin bo‘lgan intervyu materiali, texnik hujjatlar manbasi yoki keyingi subtitr jarayoni uchun matnga aylanishi mumkin. Noaniq lug‘at, miqdorlar, tinish belgilari, aksentlar va bir vaqtda gapirishni yozuv bilan tekshiring. Tanilgan matnni keyingi tuzatishlar yoki qisqacha bayonlardan ajrating va atrofdagi jarayon identifikatorlari orqali manba bilan bog‘lanishni saqlang. Model matnli yozuvni beradi; kirishni puxta tayyorlash va manbani tekshirish bu yozuv keyingi foydalanishga mos kelishini belgilaydi.", "alias_of": null, "aliases": [], "author": "OpenAI", "capabilities": { "context_length": 128000, "manufacturer_input": [ "audio" ], "manufacturer_output": [ "transcription" ] }, "card_routes": [ { "label": "Ultra", "rates": [ { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_token", "label": "input token", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_token", "label": "output token", "native_amount_usd_per_unit": "0.00002", "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, "formats": [ "transcriptions" ], "id": "openai/gpt-4o-transcribe", "input": [ "audio" ], "kind": "audio", "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, "operation_id_source": "actual X-Client-Request-ID", "recovery": "Haqiqiy so‘rov ID si va dastlabki javobni saqlang. Mavjud, egalik qilinadigan yozuvni o‘qing; yaratishni qayta yubormang.", "response_headers": { "x-should-retry": "false" }, "type": "server_error" } ], "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": [ { "http": "GET", "id_source": "exact task_id from an existing owned media record", "path": "/v1/media/tasks/{task_id}" } ], "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": "text", "fields": [ { "description": null, "name": "text (when present)", "type": null }, { "description": null, "name": "usage (when present)", "type": null } ], "result": "To‘liq dastlabki javob tanasi, holat va uzatilgan sarlavhalar. Bu ishlovchi universal JSON tuzilmasi, matn maydoni yoki vazifa o‘rovini qo‘shmaydi." }, "parameters": [ { "default_known": false, "enum": [ "openai/gpt-4o-transcribe" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "default_known": false, "enum_known": false, "name": "input_audio", "required": true, "type": "object" } ], "request_schema": { "properties": { "input_audio": { "properties": { "data": { "contentEncoding": "base64", "type": "string" }, "format": { "type": "string" } }, "required": [ "data", "format" ], "type": "object" }, "model": { "enum": [ "openai/gpt-4o-transcribe" ], "type": "string" } }, "required": [ "model", "input_audio" ], "type": "object" }, "schema_template": { "actual_file_preparation_required": true, "body": { "input_audio": { "data": "${BASE64_ACTUAL_WAV_BYTES}", "format": "wav" }, "model": "openai/gpt-4o-transcribe" }, "content_type": "application/json" } }, "input": { "content_type": "application/json", "material_conditions": [ "Misol haqiqiy, bo‘sh bo‘lmagan PCM WAV faylingizni o‘qiydi, faylning barcha baytlarini base64 ko‘rinishida kodlaydi va input_audio.format qiymatini wav qilib yuboradi." ], "material_types": [ "audio" ], "required": [ "model", "input_audio" ] }, "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": [ { "http": "GET", "id_source": "mavjud, egalik qilinadigan media yozuvidan aniq task_id", "path": "/v1/media/tasks/{task_id}" } ], "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/audio/transcriptions" }, "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": "text", "fields": [ { "description": null, "name": "text (when present)", "type": null }, { "description": null, "name": "usage (when present)", "type": null } ], "result": "Complete original response body, status and forwarded headers. No universal JSON shape, text field or task envelope is added by this handler." } }, "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": "input token", "units": [ { "amount": "0.005000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_token", "label": "input token", "native_amount_usd_per_unit": "0.000005", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" } ] }, { "dimensions": { "quoted_unit": "/ 1K tokens" }, "label": "output token", "units": [ { "amount": "0.02000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_token", "label": "output token", "native_amount_usd_per_unit": "0.00002", "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" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_AUDIO_FILE:?Set the path to your actual PCM WAV recording}\"\nexport AILOOT_AUDIO_FILE\npython3 - <<'PY_REQUEST'\nimport base64, io, json, os, wave\nfrom pathlib import Path\naudio = Path(os.environ['AILOOT_AUDIO_FILE']).read_bytes()\nif not (audio[:4] == b'RIFF' and audio[8:12] == b'WAVE'):\n raise SystemExit('Supply your actual PCM WAV audio file')\nwith wave.open(io.BytesIO(audio), 'rb') as recording:\n if recording.getcomptype() != 'NONE' or recording.getnframes() <= 0:\n raise SystemExit('Supply a nonempty PCM WAV recording')\nrequest = {'model': 'openai/gpt-4o-transcribe', 'input_audio': {'data': base64.b64encode(audio).decode('ascii'), 'format': 'wav'}}\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/audio/transcriptions \\\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 original response, headers and actual X-Client-Request-ID.\n# Read existing owned records for recovery; do not resubmit an uncertain operation.\n", "label": "curl · actual WAV file and complete original result", "language": "bash" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "transcriptions", "hints": [ "The example reads your actual nonempty PCM WAV file, encodes the complete file bytes as base64 and sends input_audio.format as wav.", "The format value in the example is the documented recipe; no model-specific format list, limit or default is asserted.", "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": [ "audio" ], "label": "Transkripsiya", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "native_endpoint": "audio_transcriptions", "out": null, "output": [ "text" ], "path": "/v1/audio/transcriptions", "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": { "input_token": 5e-06, "output_token": 2e-05 } }, "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": 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