{ "aboutHtml": "

Step 3.7 Flash — real sharoitdagi agent topshiriqlari uchun StepFun’ning siyrak ekspertlar aralashmasiga asoslangan ko‘rish-til modeli. Taxminan 198 milliard parametrli tizim 196B parametrli til tarmog‘i va 1.8B parametrli ko‘rish kodlagichini birlashtiradi; har bir token uchun taxminan 11B parametr faollashadi. U matn va tasvirlarni qabul qilib, bog‘langan ilova uchun matn, kod yoki taklif etilgan vosita chaqiruvlarini yaratadi.

Ishlab chiqaruvchi 256K kontekst oynasi va low, medium hamda high mulohaza darajalarini ko‘rsatadi. Ular ishlab chiqaruvchi jarayonida topshiriqqa turli hajmda fikrlash ajratishga imkon beradi. Uzun kontekstli ish katta hisobotlar va bir nechta fayl bo‘yicha dasturiy tadqiqotlarni o‘z ichiga oladi; model shu kontekst doirasida aniq maqsadga ega bo‘lishi uchun tegishli materialni savol va kerakli natija bilan birga tayyorlang.

Modelning o‘zidagi vizual tushunish imkoniyati mahsulot interfeyslari, hujjatlar, diagrammalar va tabiiy sahnalarni qamrab oladi. Interfeys topshirig‘ida skrinshot yoki dizaynni bering va tekshiriladigan yoki amalga oshiriladigan funksiyani ko‘rsating. Diagramma uchun tushuntiriladigan taqqoslash yoki tendensiyani ayting. Ishlab chiqaruvchi vizual talqinni ma’lumot izlash va vositalardan foydalanish bilan birlashtiradi, shuning uchun tasvirning o‘zi savolni ochiq qoldirsa, bog‘langan jarayon qo‘shimcha dalil yig‘ishi mumkin.

Dasturlash topshiriqlari repozitoriyni kuzatib chiqish, xatoni topish va tuzatish taklif qilishni o‘z ichiga oladi. Kuzatilgan muammo, kutilgan xatti-harakat va joriy natijani tasdiqlaydigan fayllar yoki jurnallarni bering. O‘zgartirilgan materialni va uni baholaydigan tekshiruvlarni so‘rang. Ilova tekshiruvni ishga tushirganda, keyingi qadamdan oldin uning haqiqiy natijasini qaytaring; shunda model tuzatish ishladi deb taxmin qilmasdan, kuzatuvga javob beradi.

Ishlab chiqaruvchining kengroq jarayonlari qidiruv, terminallar, brauzerlar va ofis vositalarini qamrab oladi. Vosita ta’riflari va topshiriq chegaralarini bering, taklif etilgan chaqiruvni ilova qaytargan natijadan ajrating. Tadqiqot topshirig‘i manbalarni taqqoslashi va har bir xulosa dalilini saqlashi mumkin; hujjat topshirig‘i esa atrofdagi ilova yakuniy materialga aylantirishi uchun izoh yoki tuzilmali kontentni qaytarishi mumkin.

StepFun alohida aniqlik variantlari va joylashtirish retseptlarini e’lon qiladi. Uning mahalliy GGUF misollarida til modeli vizual proyektordan ajratiladi va vazn fayllaridan tashqari qo‘shimcha ishlash xotirasi hisobga olinadi. Kartochkada mahalliy xotiraning minimumi taxminan 120 GB deb berilgan va shu tuzilma uchun 128 GB birlashtirilgan xotira tavsiya etilgan. Bular muayyan model tanlovi ortidagi konfiguratsiya haqidagi da’vo emas, ishlab chiqaruvchining joylashtirish shartlaridir.

Step 3.7 Flash’ni oldingi Step 3.5 matn modelidan ajrating: ko‘rish kodlagichi va tasvirni tushunish muhim qo‘shimchalardir. Topshiriqning yakuniy natijasi ishlatilgan manba yoki vizual dalilni, taklif etilgan o‘zgarish yoki topilmani va hali kuzatuv talab etiladigan har qanday shartni ko‘rsatishi kerak. Tashqi qidiruvlar, buyruqlar va fayl o‘zgarishlari ilova bog‘lagan vositalarga bog‘liq.

", "aboutText": "Step 3.7 Flash — real sharoitdagi agent topshiriqlari uchun StepFun’ning siyrak ekspertlar aralashmasiga asoslangan ko‘rish-til modeli. Taxminan 198 milliard parametrli tizim 196B parametrli til tarmog‘i va 1.8B parametrli ko‘rish kodlagichini birlashtiradi; har bir token uchun taxminan 11B parametr faollashadi. U matn va tasvirlarni qabul qilib, bog‘langan ilova uchun matn, kod yoki taklif etilgan vosita chaqiruvlarini yaratadi.\n\nIshlab chiqaruvchi 256K kontekst oynasi va low, medium hamda high mulohaza darajalarini ko‘rsatadi. Ular ishlab chiqaruvchi jarayonida topshiriqqa turli hajmda fikrlash ajratishga imkon beradi. Uzun kontekstli ish katta hisobotlar va bir nechta fayl bo‘yicha dasturiy tadqiqotlarni o‘z ichiga oladi; model shu kontekst doirasida aniq maqsadga ega bo‘lishi uchun tegishli materialni savol va kerakli natija bilan birga tayyorlang.\n\nModelning o‘zidagi vizual tushunish imkoniyati mahsulot interfeyslari, hujjatlar, diagrammalar va tabiiy sahnalarni qamrab oladi. Interfeys topshirig‘ida skrinshot yoki dizaynni bering va tekshiriladigan yoki amalga oshiriladigan funksiyani ko‘rsating. Diagramma uchun tushuntiriladigan taqqoslash yoki tendensiyani ayting. Ishlab chiqaruvchi vizual talqinni ma’lumot izlash va vositalardan foydalanish bilan birlashtiradi, shuning uchun tasvirning o‘zi savolni ochiq qoldirsa, bog‘langan jarayon qo‘shimcha dalil yig‘ishi mumkin.\n\nDasturlash topshiriqlari repozitoriyni kuzatib chiqish, xatoni topish va tuzatish taklif qilishni o‘z ichiga oladi. Kuzatilgan muammo, kutilgan xatti-harakat va joriy natijani tasdiqlaydigan fayllar yoki jurnallarni bering. O‘zgartirilgan materialni va uni baholaydigan tekshiruvlarni so‘rang. Ilova tekshiruvni ishga tushirganda, keyingi qadamdan oldin uning haqiqiy natijasini qaytaring; shunda model tuzatish ishladi deb taxmin qilmasdan, kuzatuvga javob beradi.\n\nIshlab chiqaruvchining kengroq jarayonlari qidiruv, terminallar, brauzerlar va ofis vositalarini qamrab oladi. Vosita ta’riflari va topshiriq chegaralarini bering, taklif etilgan chaqiruvni ilova qaytargan natijadan ajrating. Tadqiqot topshirig‘i manbalarni taqqoslashi va har bir xulosa dalilini saqlashi mumkin; hujjat topshirig‘i esa atrofdagi ilova yakuniy materialga aylantirishi uchun izoh yoki tuzilmali kontentni qaytarishi mumkin.\n\nStepFun alohida aniqlik variantlari va joylashtirish retseptlarini e’lon qiladi. Uning mahalliy GGUF misollarida til modeli vizual proyektordan ajratiladi va vazn fayllaridan tashqari qo‘shimcha ishlash xotirasi hisobga olinadi. Kartochkada mahalliy xotiraning minimumi taxminan 120 GB deb berilgan va shu tuzilma uchun 128 GB birlashtirilgan xotira tavsiya etilgan. Bular muayyan model tanlovi ortidagi konfiguratsiya haqidagi da’vo emas, ishlab chiqaruvchining joylashtirish shartlaridir.\n\nStep 3.7 Flash’ni oldingi Step 3.5 matn modelidan ajrating: ko‘rish kodlagichi va tasvirni tushunish muhim qo‘shimchalardir. Topshiriqning yakuniy natijasi ishlatilgan manba yoki vizual dalilni, taklif etilgan o‘zgarish yoki topilmani va hali kuzatuv talab etiladigan har qanday shartni ko‘rsatishi kerak. Tashqi qidiruvlar, buyruqlar va fayl o‘zgarishlari ilova bog‘lagan vositalarga bog‘liq.", "editorialOverlay": { "copy_fields": { "practical_html": "

Amaliy vazifa

Ingliz tilidagi texnik misol

Trace a failed configuration lookup\n\nSource excerpt: settings = {"timeout_seconds": 30}; timeout = settings["timeout"]. Log: KeyError: timeout. Required public setting remains timeout_seconds. Identify the mismatch, propose the smallest source correction and give a test that reads the configured value plus a test for a missing required setting. Do not rename the public field.

Kutiladigan natija

A source-linked diagnosis, focused patch and two test cases.

Natijani tekshirish

Check that the patch reads timeout_seconds and that the missing-setting case is not hidden by an invented default.

" }, "copy_sha256": "618d8c982562e7be11f02aac8627f4b470f2d9fde902fc39370166f99c37f83e", "copy_source": { "locale": "uz", "pack_sha256": "0f56d90ba41881e1134accf82e57338f246f8753ca4c0cee929aaffada5d10e7", "record_model_id": "stepfun/step-3.7-flash", "source_facts_sha256": "52f1576661d9d2bafb5e8672e61fd87d0b3a661a8965c51409adc888e638e978", "validation_sha256": "a2ac2f28056280fc0b2ea34a501bf156d5ce155406e57e708edf30bfdf6bfdc6" }, "html_sha256": "3a36c564bfe4be06ed0f1751f9370cf2e2f31466470a1de18fc5d95c3edf7038", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "uz", "methods": [ { "html": "

•

StepFun: Step 3.7 Flash

StepFun /stepfun/step-3.7-flash

Boshlash

StepFun’ning Step 3.7 Flash modeli — dasturlash, vizual tushunish va vositalar bilan boshqariladigan jarayonlar uchun siyrak ko‘rish-til modeli. U 196B parametrli til tarmog‘ini 1.8B parametrli ko‘rish kodlagichi, 256K kontekst va ishlab chiqaruvchi hujjatlashtirgan uchta mulohaza darajasi bilan birlashtiradi.

Qabul qilinadigan kirish ma’lumotlari: Matn
Natijalar: Matn

Model haqida

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

Step 3.7 Flash — real sharoitdagi agent topshiriqlari uchun StepFun’ning siyrak ekspertlar aralashmasiga asoslangan ko‘rish-til modeli. Taxminan 198 milliard parametrli tizim 196B parametrli til tarmog‘i va 1.8B parametrli ko‘rish kodlagichini birlashtiradi; har bir token uchun taxminan 11B parametr faollashadi. U matn va tasvirlarni qabul qilib, bog‘langan ilova uchun matn, kod yoki taklif etilgan vosita chaqiruvlarini yaratadi.

Ishlab chiqaruvchi 256K kontekst oynasi va low, medium hamda high mulohaza darajalarini ko‘rsatadi. Ular ishlab chiqaruvchi jarayonida topshiriqqa turli hajmda fikrlash ajratishga imkon beradi. Uzun kontekstli ish katta hisobotlar va bir nechta fayl bo‘yicha dasturiy tadqiqotlarni o‘z ichiga oladi; model shu kontekst doirasida aniq maqsadga ega bo‘lishi uchun tegishli materialni savol va kerakli natija bilan birga tayyorlang.

Modelning o‘zidagi vizual tushunish imkoniyati mahsulot interfeyslari, hujjatlar, diagrammalar va tabiiy sahnalarni qamrab oladi. Interfeys topshirig‘ida skrinshot yoki dizaynni bering va tekshiriladigan yoki amalga oshiriladigan funksiyani ko‘rsating. Diagramma uchun tushuntiriladigan taqqoslash yoki tendensiyani ayting. Ishlab chiqaruvchi vizual talqinni ma’lumot izlash va vositalardan foydalanish bilan birlashtiradi, shuning uchun tasvirning o‘zi savolni ochiq qoldirsa, bog‘langan jarayon qo‘shimcha dalil yig‘ishi mumkin.

Dasturlash topshiriqlari repozitoriyni kuzatib chiqish, xatoni topish va tuzatish taklif qilishni o‘z ichiga oladi. Kuzatilgan muammo, kutilgan xatti-harakat va joriy natijani tasdiqlaydigan fayllar yoki jurnallarni bering. O‘zgartirilgan materialni va uni baholaydigan tekshiruvlarni so‘rang. Ilova tekshiruvni ishga tushirganda, keyingi qadamdan oldin uning haqiqiy natijasini qaytaring; shunda model tuzatish ishladi deb taxmin qilmasdan, kuzatuvga javob beradi.

Ishlab chiqaruvchining kengroq jarayonlari qidiruv, terminallar, brauzerlar va ofis vositalarini qamrab oladi. Vosita ta’riflari va topshiriq chegaralarini bering, taklif etilgan chaqiruvni ilova qaytargan natijadan ajrating. Tadqiqot topshirig‘i manbalarni taqqoslashi va har bir xulosa dalilini saqlashi mumkin; hujjat topshirig‘i esa atrofdagi ilova yakuniy materialga aylantirishi uchun izoh yoki tuzilmali kontentni qaytarishi mumkin.

StepFun alohida aniqlik variantlari va joylashtirish retseptlarini e’lon qiladi. Uning mahalliy GGUF misollarida til modeli vizual proyektordan ajratiladi va vazn fayllaridan tashqari qo‘shimcha ishlash xotirasi hisobga olinadi. Kartochkada mahalliy xotiraning minimumi taxminan 120 GB deb berilgan va shu tuzilma uchun 128 GB birlashtirilgan xotira tavsiya etilgan. Bular muayyan model tanlovi ortidagi konfiguratsiya haqidagi da’vo emas, ishlab chiqaruvchining joylashtirish shartlaridir.

Step 3.7 Flash’ni oldingi Step 3.5 matn modelidan ajrating: ko‘rish kodlagichi va tasvirni tushunish muhim qo‘shimchalardir. Topshiriqning yakuniy natijasi ishlatilgan manba yoki vizual dalilni, taklif etilgan o‘zgarish yoki topilmani va hali kuzatuv talab etiladigan har qanday shartni ko‘rsatishi kerak. Tashqi qidiruvlar, buyruqlar va fayl o‘zgarishlari ilova bog‘lagan vositalarga bog‘liq.

Ailoot da mavjud · kirish ma’lumotlari va usullar

Ailoot Ultra · OpenAI Chat POST /v1/chat/completions

Kirish: text
Chiqish: text
Chiqish formati: json yoki SSE

Maydon	Tur	Talab	Qiymatlar va cheklovlar	Standart
Maydon`model`	Tur`string`	TalabMajburiy	Qiymatlar va cheklovlar stepfun/step-3.7-flash	Standart—
Maydon`messages`	Tur`message[]`	TalabMajburiy	Qiymatlar va cheklovlar Elementlarning eng kam soni: 1	Standart—
Maydon`messages[].role`	Tur`string`	TalabMajburiy	Qiymatlar va cheklovlar Namunalar: system, user, assistant, tool, function Shartlar: Bu rollar manba kodining moslik turlarida ochiq ifodalangan; aniq rollar to‘plami har bir modelga xos bo‘lib qoladi. Modelga bogʻliq	Standart—
Maydon`messages[].content`	Tur`string\|content_part[]\|null`	TalabIxtiyoriy	Qiymatlar va cheklovlar	Standart—
Maydon`messages[].tool_calls`	Tur`tool_call[]`	TalabIxtiyoriy	Qiymatlar va cheklovlar	Standart—
Maydon`messages[].tool_call_id`	Tur`string`	TalabIxtiyoriy	Qiymatlar va cheklovlar Quyidagi holatda qo‘llanadi: role=tool; haqiqatan qaytarilgan IDdan foydalaning	Standart—
Maydon`messages[].name`	Tur`string`	TalabIxtiyoriy	Qiymatlar va cheklovlar	Standart—
Maydon`messages[].reasoning_content`	Tur`string`	TalabIxtiyoriy	Qiymatlar va cheklovlar Quyidagi holatda qo‘llanadi: Ushbu model foydalanganda, haqiqatan qaytarilgan fikrlash ma’lumotlarini keyingi so‘rovda qayta yuboring	Standart—
Maydon`messages[].reasoning_details`	Tur`object\|array`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`max_tokens`	Tur`integer`	TalabIxtiyoriy	Qiymatlar va cheklovlar Eng kam: 1 Modelga bogʻliq	Standart—
Maydon`max_completion_tokens`	Tur`integer`	TalabIxtiyoriy	Qiymatlar va cheklovlar Eng kam: 1 Modelga bogʻliq	Standart—
Maydon`stream`	Tur`boolean`	TalabIxtiyoriy	Qiymatlar va cheklovlar	Standartfalse
Maydon`stream_options.include_usage`	Tur`boolean`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`temperature`	Tur`number`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`top_p`	Tur`number`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`stop`	Tur`string\|string[]`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`tools`	Tur`function_tool[]`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`tools[].type`	Tur`string`	TalabIxtiyoriy	Qiymatlar va cheklovlar function Modelga bogʻliq	Standart—
Maydon`tools[].function.name`	Tur`string`	TalabMajburiy	Qiymatlar va cheklovlar Quyidagi holatda qo‘llanadi: Funksiya vositasi taqdim etilgan	Standart—
Maydon`tools[].function.description`	Tur`string`	TalabIxtiyoriy	Qiymatlar va cheklovlar	Standart—
Maydon`tools[].function.parameters`	Tur`JSON_schema`	TalabIxtiyoriy	Qiymatlar va cheklovlar	Standart—
Maydon`tool_choice`	Tur`string\|object`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`parallel_tool_calls`	Tur`boolean`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`response_format`	Tur`object`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`reasoning_effort`	Tur`string`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`reasoning`	Tur`object`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`service_tier`	Tur`string`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`instructions`	Tur`string`	TalabIxtiyoriy	Qiymatlar va cheklovlar Moslik maydoni	Standart—
Maydon`functions`	Tur`function[]`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`function_call`	Tur`string\|object`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`prompt_cache_options`	Tur`object`	TalabIxtiyoriy	Qiymatlar va cheklovlar Modelga bogʻliq	Standart—
Maydon`modalities`	Tur`string[]`	TalabIxtiyoriy	Qiymatlar va cheklovlar text	Standart—
Maydon`provider`	Tur`object`	TalabIxtiyoriy	Qiymatlar va cheklovlar Shartlar: Ushbu Ultra matn marshrutida provider.options rad etiladi	Standart—
Maydon`cache_control.ttl`	Tur`string`	TalabIxtiyoriy	Qiymatlar va cheklovlar Shartlar: Haqiqiy prompt-kesh joylarida 1h rad etiladi	Standart—

Kirish materiallari birikmalari

Matn · UTF8 matni

messages[].content

Usul parametrlari va hayot sikli

Parametr	Parametr talablari
Parametr`content_type`	Parametr talablariapplication/json
Parametr`required`	Parametr talablarimodel, messages
Parametr`material_types`	Parametr talablaritext
Parametr`messages`	Parametr talablarirole/content tuzilishidagi xabarlar massivi
Parametr`file_material`	Parametr talablariHaqiqiy UTF-8 hujjati aynan matn sifatida kiritiladi; fayl IDsi faraz qilinmaydi
Parametr`optional_controls`	Parametr talablaristream, temperature, top_p, stop, max_tokens, max_completion_tokens, reasoning, response_format, tools, tool_choice
Parametr`control_scope`	Parametr talablariModelga xos; foydalanuvchi funksiya vositalari hostingdagi vositalardan farq qiladi
Parametr`output_modalities`	Parametr talablaritext
Parametr`hosted_operations`	Parametr talablarifalse
Parametr`multimodal_input_binding`	Parametr talablarinull

Hayot sikli: synchronous_or_streamed

Aniq model IDsini messages bilan yuboring.

Kontekst uzunligi chiqishning yuqori chegarasi emas.

Matn fayli aynan matnni taqdim etishi mumkin; tasvir, audio va fayl obyekti kirishlari aniq bog‘lashni talab qiladi.

Tariflar

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

Tezkor rejim: Standart tarif Tezkor rejim tanlanganda
Flex rejimi: Standart tarif flex rejimi tanlanganda
Maksimal fikrlash darajasi: Standart tarif Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda
Fikrlash darajasi · yuqori: Standart tarif Fikrlash darajasi yuqori bo‘lganda
Fikrlash darajasi · past: Standart tarif Fikrlash darajasi past bo‘lganda
Fikrlash darajasi · o‘rtacha: Standart tarif Fikrlash darajasi o‘rtacha bo‘lganda

Ailoot tariflari

Sozlamalar bo‘yicha narxlar

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

Sozlama	Tariflar jadvali	Kontekst tokenlari soni bundan ko‘p	Kontekst tokenlari soni bundan oshmaydi, chegara kiradi	To‘lov
SozlamaTokenlar uchun bazaviy tariflar	Tariflar jadvaliAsosiy tarif	Kontekst tokenlari soni bundan ko‘p—	Kontekst tokenlari soni bundan oshmaydi, chegara kiradiYuqori chegara yo‘q	To‘lov Kirish · Kirish tokenlari $0.0004 / 1K token Chiqish · Chiqish tokenlari $0.0023 / 1K token Kirish · Keshdan o‘qish $0.00008 / 1K token Kirish · Keshga yozish — / 1K token Kirish · Keshga yozish, 1 soat — / 1K token
SozlamaSo‘rov uzunligi bo‘yicha 1-daraja	Tariflar jadvali—	Kontekst tokenlari soni bundan ko‘p0	Kontekst tokenlari soni bundan oshmaydi, chegara kiradiYuqori chegara yo‘q	To‘lov Kirish · Kirish tokenlari $0.0004 / 1K token Chiqish · Chiqish tokenlari $0.0023 / 1K token Kirish · Keshdan o‘qish $0.00008 / 1K token Kirish · Keshga yozish — / 1K token Kirish · Keshga yozish, 1 soat — / 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 · OpenAI Chat

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "stepfun/step-3.7-flash", "messages": [{"role": "user", "content": "Explain the difference between an observation and a hypothesis in three sentences."}]}')\n\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path("result.json").read_text())\nfor x in r.get("choices",[]):\n    if x.get("message",{}).get("content"): print(x["message"]["content"])\nPY_RESULT\n

from openai import OpenAI\nimport os\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nresult=client.chat.completions.create(model='stepfun/step-3.7-flash',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}])\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nsave_result(result.to_dict(mode="json"))\n

from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get("AILOOT_API_KEY", "").strip(): raise SystemExit("Set AILOOT_API_KEY before making a request")\nclient=OpenAI(base_url="https://api.ailoot.ai/v1",api_key=os.environ["AILOOT_API_KEY"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem="result"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + ".json").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b"-_", validate=True)\n        ext = "png" if raw.startswith(b"\\x89PNG\\r\\n\\x1a\\n") else "jpg" if raw.startswith(b"\\xff\\xd8") else "webp" if raw[:4] == b"RIFF" and raw[8:12] == b"WEBP" else suffix\n        file = Path(stem + "-" + label + "." + ext)\n        file.write_bytes(raw)\n        print("Saved", file)\n    for index, block in enumerate(data.get("content") or []):\n        print("Content", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get("choices") or []:\n        print("Choice", choice.get("index"), json.dumps(choice.get("message", choice.get("delta", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get("output") or []):\n        print("Output", index, json.dumps(item, ensure_ascii=False))\n        if item.get("type") == "image_generation_call" and item.get("result"):\n            save_blob(item["result"], item.get("output_format") or "bin", "output-" + str(index))\n    for ci, candidate in enumerate(data.get("candidates") or []):\n        for pi, part in enumerate((candidate.get("content") or {}).get("parts") or []):\n            print("Candidate/part", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get("inlineData") or part.get("inline_data")\n            if blob and blob.get("data"):\n                mime = blob.get("mimeType") or blob.get("mime_type")\n                suffix = {"image/png":"png", "image/jpeg":"jpg", "image/webp":"webp", "audio/wav":"wav", "audio/mpeg":"mp3", "video/mp4":"mp4"}.get(mime, "bin")\n                save_blob(blob["data"], suffix, "candidate-" + str(ci) + "-part-" + str(pi))\n\nwith client.chat.completions.stream(model='stepfun/step-3.7-flash',messages=[{"role":"user","content":"Explain observations and hypotheses in three sentences."}]) as stream:\n    with Path("stream-events.jsonl").open("w",encoding="utf-8") as log:\n        for event in stream:\n            payload=event.to_dict(mode="json")\n            log.write(json.dumps(payload,ensure_ascii=False)+"\\n"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_completion()\n    save_result(final.to_dict(mode="json"),"stream-result")\n

Natijalarni olish va saqlash

Ailoot Ultra · OpenAI Chat

json yoki SSE

Barcha tayyor natijalarni saqlash

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

Har bir javob variantini va uning kontenti, vosita chaqiruvlari hamda fikrlash ma’lumotlarini saqlang. SSEda o‘zgarish qismlarini variant va vosita indeksi bo‘yicha yig‘ing, yakuniy tugash sababi va sarf ma’lumotlarini saqlang.

Asl javobni tekshirish kerak bo‘lsa

So‘rov va javob IDlari hamda sarlavhalarini saqlang. Matn vazifasini olish uchun umumiy URL taqdim etilmagan.

Javob maydonlari

Maydon	Tur
Maydon`choices[].index`	Turinteger
Maydon`choices[].message.content`	Turstring\|null
Maydon`choices[].message.tool_calls`	Turtool_call[]
Maydon`choices[].message.reasoning_content`	Turstring
Maydon`choices[].message.reasoning_details`	Turobject\|array
Maydon`choices[].finish_reason`	Turstring\|null
Maydon`usage`	Turobject

Xatolar va keyingi qadamlar

Javob	Shart	Keyingi qadam
Javob400 · `invalid_request_error`	ShartMajburiy maydonlar, material ifodasi yoki parametr qiymati noto‘g‘ri	Keyingi qadamYangi yaratish so‘rovidan oldin ko‘rsatilgan maydonlarni tuzating.

Taxalluslar

Model taxalluslari

Ailoot Ultra stepfun/step-3.7-flash

Usul yo‘llari taxalluslari

Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.

Chaqirish uchun tegishli ID lar

stepfun/step-3.7-flash

", "method_identity": { "effective_request_model_id": "stepfun/step-3.7-flash", "fmt": "chat", "http": "POST", "path": "/v1/chat/completions", "request_model_id": "stepfun/step-3.7-flash", "route_label": "Ultra" }, "method_key": "Ultra|chat|/v1/chat/completions|stepfun%2Fstep-3.7-flash", "ordinal": 0, "rawMethod": { "available": null, "cache_read": 0.08, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "Majburiy maydonlar, material ifodasi yoki parametr qiymati noto‘g‘ri", "http_status": 400, "recovery": "Yangi yaratish so‘rovidan oldin ko‘rsatilgan maydonlarni tuzating.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID.", "Guarded canonical keys must occur once; duplicate or case-varied model/tools/cap fields are rejected." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "So‘rov va javob IDlari hamda sarlavhalarini saqlang. Matn vazifasini olish uchun umumiy URL taqdim etilmagan." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "UTF8 matni" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "Har bir javob variantini va uning kontenti, vosita chaqiruvlari hamda fikrlash ma’lumotlarini saqlang. SSEda o‘zgarish qismlarini variant va vosita indeksi bo‘yicha yig‘ing, yakuniy tugash sababi va sarf ma’lumotlarini saqlang.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json yoki SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "stepfun/step-3.7-flash" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "conditions": "Bu rollar manba kodining moslik turlarida ochiq ifodalangan; aniq rollar to‘plami har bir modelga xos bo‘lib qoladi.", "default": null, "default_known": false, "enum": [ "system", "user", "assistant", "tool", "function" ], "enum_exhaustive": false, "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string|content_part[]|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_calls", "required": false, "type": "tool_call[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_call_id", "required": false, "type": "string", "when": "role=tool; haqiqatan qaytarilgan IDdan foydalaning" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].name", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_content", "required": false, "type": "string", "when": "Ushbu model foydalanganda, haqiqatan qaytarilgan fikrlash ma’lumotlarini keyingi so‘rovda qayta yuboring" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_details", "required": false, "type": "object|array" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_completion_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stream_options.include_usage", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop", "required": false, "type": "string|string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "function_tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": [ "function" ], "enum_known": true, "name": "tools[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.name", "required": true, "type": "string", "when": "Funksiya vositasi taqdim etilgan" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.parameters", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "response_format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning_effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "source_compatibility", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "functions", "required": false, "type": "function[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "function_call", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "text" ], "enum_known": true, "name": "modalities", "required": false, "type": "string[]" }, { "availability": "source_interface", "conditions": "Ushbu Ultra matn marshrutida provider.options rad etiladi", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "provider", "required": false, "type": "object" }, { "availability": "source_interface", "conditions": "Haqiqiy prompt-kesh joylarida 1h rad etiladi", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control.ttl", "required": false, "type": "string" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [ "additional models/models list", "plugins", "route", "hosted tools; ordinary client function tools remain separate", "non-text output modalities", "provider.options overrides", "one-hour prompt-cache TTL" ] }, "hints": [ "Aniq model IDsini messages bilan yuboring.", "Kontekst uzunligi chiqishning yuqori chegarasi emas.", "Matn fayli aynan matnni taqdim etishi mumkin; tasvir, audio va fayl obyekti kirishlari aniq bog‘lashni talab qiladi." ], "input": { "content_type": "application/json", "control_scope": "Modelga xos; foydalanuvchi funksiya vositalari hostingdagi vositalardan farq qiladi", "file_material": "Haqiqiy UTF-8 hujjati aynan matn sifatida kiritiladi; fayl IDsi faraz qilinmaydi", "hosted_operations": false, "material_types": [ "text" ], "messages": "role/content tuzilishidagi xabarlar massivi", "multimodal_input_binding": null, "optional_controls": [ "stream", "temperature", "top_p", "stop", "max_tokens", "max_completion_tokens", "reasoning", "response_format", "tools", "tool_choice" ], "output_modalities": [ "text" ], "required": [ "model", "messages" ] }, "lifecycle": { "mode": "synchronous_or_streamed", "unknown": "preserve original request id; no generic chat job retrieval path" }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/chat/completions" }, "method_aliases": [], "operation_modes": [ "text_chat" ], "output": { "content": "choices[].message.content or stream delta", "family": "text", "format": "json or supported SSE", "tool_calls": "retain actual returned function calls" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Tokenlar uchun bazaviy tariflar", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "So‘rov uzunligi bo‘yicha 1-daraja", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"stepfun/step-3.7-flash\", \"messages\": [{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}]}')\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path(\"result.json\").read_text())\nfor x in r.get(\"choices\",[]):\n if x.get(\"message\",{}).get(\"content\"): print(x[\"message\"][\"content\"])\nPY_RESULT\n", "label": "curl · retained exact creation", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nresult=client.chat.completions.create(model='stepfun/step-3.7-flash',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}])\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(result.to_dict(mode=\"json\"))\n", "label": "Python SDK · all choices", "language": "python" }, { "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='stepfun/step-3.7-flash',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python SDK streaming · all events", "language": "python" } ], "family": "openai", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "chat", "hints": [ "Send exact model ID with messages.", "Context length is not an output cap.", "A text file may supply literal text; image/audio/file-object inputs need exact binding." ], "http": "POST", "in": 0.4, "input": [ "text" ], "label": "OpenAI Chat", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 2.3, "output": [ "text" ], "path": "/v1/chat/completions", "price_conditions": [ { "label": "Tezkor rejim", "value": "Standart tarif", "when": "Tezkor rejim tanlanganda" }, { "label": "Flex rejimi", "value": "Standart tarif", "when": "flex rejimi tanlanganda" }, { "label": "Maksimal fikrlash darajasi", "value": "Standart tarif", "when": "Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda" }, { "label": "Fikrlash darajasi · yuqori", "value": "Standart tarif", "when": "Fikrlash darajasi yuqori bo‘lganda" }, { "label": "Fikrlash darajasi · past", "value": "Standart tarif", "when": "Fikrlash darajasi past bo‘lganda" }, { "label": "Fikrlash darajasi · o‘rtacha", "value": "Standart tarif", "when": "Fikrlash darajasi o‘rtacha bo‘lganda" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "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" } ] } ], "reasoning_effort_multipliers": { "high": 1, "low": 1, "medium": 1 }, "request_model_id": "stepfun/step-3.7-flash", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.08, "cache_read_multiplier": null, "cache_write": null, "cache_write_1h": null, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 0.4, "input_multiplier": null, "interval_boundary": "min_exclusive_max_inclusive", "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "null_rate_policy": "unknown or inherited; never zero", "out": 2.3, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "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" } ] } }, { "html": "

•

StepFun: Step 3.7 Flash

StepFun /stepfun/step-3.7-flash

Boshlash

StepFun’ning Step 3.7 Flash modeli — dasturlash, vizual tushunish va vositalar bilan boshqariladigan jarayonlar uchun siyrak ko‘rish-til modeli. U 196B parametrli til tarmog‘ini 1.8B parametrli ko‘rish kodlagichi, 256K kontekst va ishlab chiqaruvchi hujjatlashtirgan uchta mulohaza darajasi bilan birlashtiradi.

Qabul qilinadigan kirish ma’lumotlari: Matn
Natijalar: json · sse

Model haqida

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

Step 3.7 Flash — real sharoitdagi agent topshiriqlari uchun StepFun’ning siyrak ekspertlar aralashmasiga asoslangan ko‘rish-til modeli. Taxminan 198 milliard parametrli tizim 196B parametrli til tarmog‘i va 1.8B parametrli ko‘rish kodlagichini birlashtiradi; har bir token uchun taxminan 11B parametr faollashadi. U matn va tasvirlarni qabul qilib, bog‘langan ilova uchun matn, kod yoki taklif etilgan vosita chaqiruvlarini yaratadi.

Ishlab chiqaruvchi 256K kontekst oynasi va low, medium hamda high mulohaza darajalarini ko‘rsatadi. Ular ishlab chiqaruvchi jarayonida topshiriqqa turli hajmda fikrlash ajratishga imkon beradi. Uzun kontekstli ish katta hisobotlar va bir nechta fayl bo‘yicha dasturiy tadqiqotlarni o‘z ichiga oladi; model shu kontekst doirasida aniq maqsadga ega bo‘lishi uchun tegishli materialni savol va kerakli natija bilan birga tayyorlang.

Modelning o‘zidagi vizual tushunish imkoniyati mahsulot interfeyslari, hujjatlar, diagrammalar va tabiiy sahnalarni qamrab oladi. Interfeys topshirig‘ida skrinshot yoki dizaynni bering va tekshiriladigan yoki amalga oshiriladigan funksiyani ko‘rsating. Diagramma uchun tushuntiriladigan taqqoslash yoki tendensiyani ayting. Ishlab chiqaruvchi vizual talqinni ma’lumot izlash va vositalardan foydalanish bilan birlashtiradi, shuning uchun tasvirning o‘zi savolni ochiq qoldirsa, bog‘langan jarayon qo‘shimcha dalil yig‘ishi mumkin.

Dasturlash topshiriqlari repozitoriyni kuzatib chiqish, xatoni topish va tuzatish taklif qilishni o‘z ichiga oladi. Kuzatilgan muammo, kutilgan xatti-harakat va joriy natijani tasdiqlaydigan fayllar yoki jurnallarni bering. O‘zgartirilgan materialni va uni baholaydigan tekshiruvlarni so‘rang. Ilova tekshiruvni ishga tushirganda, keyingi qadamdan oldin uning haqiqiy natijasini qaytaring; shunda model tuzatish ishladi deb taxmin qilmasdan, kuzatuvga javob beradi.

Ishlab chiqaruvchining kengroq jarayonlari qidiruv, terminallar, brauzerlar va ofis vositalarini qamrab oladi. Vosita ta’riflari va topshiriq chegaralarini bering, taklif etilgan chaqiruvni ilova qaytargan natijadan ajrating. Tadqiqot topshirig‘i manbalarni taqqoslashi va har bir xulosa dalilini saqlashi mumkin; hujjat topshirig‘i esa atrofdagi ilova yakuniy materialga aylantirishi uchun izoh yoki tuzilmali kontentni qaytarishi mumkin.

StepFun alohida aniqlik variantlari va joylashtirish retseptlarini e’lon qiladi. Uning mahalliy GGUF misollarida til modeli vizual proyektordan ajratiladi va vazn fayllaridan tashqari qo‘shimcha ishlash xotirasi hisobga olinadi. Kartochkada mahalliy xotiraning minimumi taxminan 120 GB deb berilgan va shu tuzilma uchun 128 GB birlashtirilgan xotira tavsiya etilgan. Bular muayyan model tanlovi ortidagi konfiguratsiya haqidagi da’vo emas, ishlab chiqaruvchining joylashtirish shartlaridir.

Step 3.7 Flash’ni oldingi Step 3.5 matn modelidan ajrating: ko‘rish kodlagichi va tasvirni tushunish muhim qo‘shimchalardir. Topshiriqning yakuniy natijasi ishlatilgan manba yoki vizual dalilni, taklif etilgan o‘zgarish yoki topilmani va hali kuzatuv talab etiladigan har qanday shartni ko‘rsatishi kerak. Tashqi qidiruvlar, buyruqlar va fayl o‘zgarishlari ilova bog‘lagan vositalarga bog‘liq.

Ailoot da mavjud · kirish ma’lumotlari va usullar

Ailoot Ultra · Anthropic Messages POST /v1/messages

Kirish: text
Chiqish: json, sse
Chiqish formati: JSON yoki SSE

Maydon	Tur	Talab	Qiymatlar va cheklovlar	Standart
Maydon`model`	Tur`string`	TalabMajburiy	Qiymatlar va cheklovlar stepfun/step-3.7-flash	Standart—
Maydon`messages`	Tur`message[]`	TalabMajburiy	Qiymatlar va cheklovlar	Standart—
Maydon`messages[].role`	Tur`string`	TalabMajburiy	Qiymatlar va cheklovlar user, assistant	Standart—
Maydon`messages[].content`	Tur`string`	TalabMajburiy	Qiymatlar va cheklovlar	Standart—
Maydon`max_tokens`	Tur`integer`	TalabMajburiy	Qiymatlar va cheklovlar	Standart—
Maydon`stream`	Tur`boolean`	TalabIxtiyoriy	Qiymatlar va cheklovlar	Standartfalse

Kirish materiallari birikmalari

Matn · UTF-8 matni

messages[].content satri

Usul parametrlari va hayot sikli

Parametr	Parametr talablari
Parametr`content_type`	Parametr talablariapplication/json
Parametr`required`	Parametr talablarimodel, messages, max_tokens
Parametr`optional_controls`	Parametr talablaristream
Parametr`material_types`	Parametr talablaritext
Parametr`text_file_material`	Parametr talablariHaqiqiy UTF-8 hujjatini o‘qing va uning matnini ko‘rsatilgan kirish yoki xabar kontenti satriga joylashtiring.

Hayot sikli: synchronous_or_streamed

Tariflar

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

Tezkor rejim: Standart tarif Tezkor rejim tanlanganda
Flex rejimi: Standart tarif flex rejimi tanlanganda
Maksimal fikrlash darajasi: Standart tarif Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda
Fikrlash darajasi · yuqori: Standart tarif Fikrlash darajasi yuqori bo‘lganda
Fikrlash darajasi · past: Standart tarif Fikrlash darajasi past bo‘lganda
Fikrlash darajasi · o‘rtacha: Standart tarif Fikrlash darajasi o‘rtacha bo‘lganda

Ailoot tariflari

Sozlamalar bo‘yicha narxlar

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

Sozlama	Tariflar jadvali	Kontekst tokenlari soni bundan ko‘p	Kontekst tokenlari soni bundan oshmaydi, chegara kiradi	To‘lov
SozlamaTokenlar uchun bazaviy tariflar	Tariflar jadvaliAsosiy tarif	Kontekst tokenlari soni bundan ko‘p—	Kontekst tokenlari soni bundan oshmaydi, chegara kiradiYuqori chegara yo‘q	To‘lov Kirish · Kirish tokenlari $0.0004 / 1K token Chiqish · Chiqish tokenlari $0.0023 / 1K token Kirish · Keshdan o‘qish $0.00008 / 1K token Kirish · Keshga yozish — / 1K token Kirish · Keshga yozish, 1 soat — / 1K token
SozlamaSo‘rov uzunligi bo‘yicha 1-daraja	Tariflar jadvali—	Kontekst tokenlari soni bundan ko‘p0	Kontekst tokenlari soni bundan oshmaydi, chegara kiradiYuqori chegara yo‘q	To‘lov Kirish · Kirish tokenlari $0.0004 / 1K token Chiqish · Chiqish tokenlari $0.0023 / 1K token Kirish · Keshdan o‘qish $0.00008 / 1K token Kirish · Keshga yozish — / 1K token Kirish · Keshga yozish, 1 soat — / 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 · Anthropic Messages

{\n  "model": "stepfun/step-3.7-flash",\n  "max_tokens": 128,\n  "messages": [\n    {\n      "role": "user",\n      "content": "Summarize the incident report."\n    }\n  ],\n  "stream": false\n}

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'stepfun/step-3.7-flash', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H "x-api-key: $AILOOT_API_KEY" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n

import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'stepfun/step-3.7-flash', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n    raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n    with urlopen(request, timeout=120) as response:\n        raw = response.read()\n        Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n    Path('result.json').write_bytes(error.read())\n    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n    raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n

Natijalarni olish va saqlash

Ailoot Ultra · Anthropic Messages

JSON yoki SSE

Barcha tayyor natijalarni saqlash

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

Barcha kontent bloklari, fikrlash imzolari va haqiqiy vosita ishlatish IDlarini saqlang. SSE bloklarining barcha o‘zgarish qismlarini yig‘ing; birinchi matn bloki to‘liq chiqish emas.

Asl javobni tekshirish kerak bo‘lsa

So‘rov va javob IDlari hamda sarlavhalarini saqlang. Matn vazifasini olish uchun umumiy URL taqdim etilmagan.

Javob maydonlari

Maydon	Tur
Maydon`id`	Turstring
Maydon`model`	Turstring
Maydon`content[]`	Turtext\|thinking\|tool_use\|other content block
Maydon`stop_reason`	Turstring\|null
Maydon`usage`	Turobject

Xatolar va keyingi qadamlar

Javob	Shart	Keyingi qadam
Javob400 · `invalid_request_error`	ShartMajburiy maydonlar, material ifodasi yoki parametr qiymati noto‘g‘ri	Keyingi qadamYangi yaratish so‘rovidan oldin ko‘rsatilgan maydonlarni tuzating.

Taxalluslar

Model taxalluslari

Ailoot Ultra stepfun/step-3.7-flash

Usul yo‘llari taxalluslari

Yuqorida ko‘rsatilgan usul yo‘llaridan foydalaning.

Chaqirish uchun tegishli ID lar

stepfun/step-3.7-flash

", "method_identity": { "effective_request_model_id": "stepfun/step-3.7-flash", "fmt": "messages", "http": "POST", "path": "/v1/messages", "request_model_id": "stepfun/step-3.7-flash", "route_label": "Ultra" }, "method_key": "Ultra|messages|/v1/messages|stepfun%2Fstep-3.7-flash", "ordinal": 1, "rawMethod": { "available": null, "cache_read": 0.08, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "Authorization: Bearer", "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "Majburiy maydonlar, material ifodasi yoki parametr qiymati noto‘g‘ri", "http_status": 400, "recovery": "Yangi yaratish so‘rovidan oldin ko‘rsatilgan maydonlarni tuzating.", "type": "invalid_request_error" } ], "example_body": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "stepfun/step-3.7-flash", "stream": false }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "So‘rov va javob IDlari hamda sarlavhalarini saqlang. Matn vazifasini olish uchun umumiy URL taqdim etilmagan." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content satri", "required_material": "UTF-8 matni" } ], "operation_modes": [ "synchronous_json", "streamed_SSE" ], "outputs": { "all_results": "Barcha kontent bloklari, fikrlash imzolari va haqiqiy vosita ishlatish IDlarini saqlang. SSE bloklarining barcha o‘zgarish qismlarini yig‘ing; birinchi matn bloki to‘liq chiqish emas.", "family": "protocol", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "JSON yoki SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "stepfun/step-3.7-flash" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" } ], "profile_binding": "Documented current stock Messages bridge; optional model capabilities are separate from this minimal text request.", "request_schema": { "additionalProperties": false, "properties": { "max_tokens": { "minimum": 1, "type": "integer" }, "messages": { "items": { "additionalProperties": false, "properties": { "content": { "oneOf": [ { "type": "string" }, { "items": { "oneOf": [ { "properties": { "text": { "type": "string" }, "type": { "const": "text" } }, "required": [ "type", "text" ], "type": "object" }, { "properties": { "source": { "oneOf": [ { "properties": { "type": { "const": "url" }, "url": { "type": "string" } }, "required": [ "type", "url" ], "type": "object" }, { "properties": { "data": { "type": "string" }, "media_type": { "type": "string" }, "type": { "const": "base64" } }, "required": [ "type", "media_type", "data" ], "type": "object" } ] }, "type": { "const": "image" } }, "required": [ "type", "source" ], "type": "object" } ] }, "type": "array" } ] }, "role": { "enum": [ "user", "assistant" ], "type": "string" } }, "required": [ "role", "content" ], "type": "object" }, "minItems": 1, "type": "array" }, "model": { "enum": [ "stepfun/step-3.7-flash" ], "type": "string" }, "stream": { "default": false, "type": "boolean" } }, "required": [ "model", "messages", "max_tokens" ], "type": "object" }, "schema_template": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "stepfun/step-3.7-flash", "stream": false }, "unsupported": [ "No query API key.", "Hosted/server-side tools and model-specific optional controls are not part of this minimal family example." ] }, "input": { "content_type": "application/json", "material_types": [ "text" ], "optional_controls": [ "stream" ], "required": [ "model", "messages", "max_tokens" ], "text_file_material": "Haqiqiy UTF-8 hujjatini o‘qing va uning matnini ko‘rsatilgan kirish yoki xabar kontenti satriga joylashtiring." }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "Keep request/response IDs and headers. No generic text job retrieval URL is supplied." }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/messages" }, "output": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "family": "protocol", "format": "JSON or SSE" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Tokenlar uchun bazaviy tariflar", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "So‘rov uzunligi bo‘yicha 1-daraja", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "{\n \"model\": \"stepfun/step-3.7-flash\",\n \"max_tokens\": 128,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Summarize the incident report.\"\n }\n ],\n \"stream\": false\n}", "label": "Complete minimal JSON body", "language": "json" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'stepfun/step-3.7-flash', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n", "label": "curl · use your UTF-8 document", "language": "bash" }, { "code": "import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'stepfun/step-3.7-flash', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n with urlopen(request, timeout=120) as response:\n raw = response.read()\n Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n Path('result.json').write_bytes(error.read())\n Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n", "label": "Python · save the complete result", "language": "python" } ], "family": "anthropic", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "messages", "http": "POST", "in": 0.4, "input": [ "text" ], "label": "Anthropic Messages", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 2.3, "output": [ "json", "sse" ], "path": "/v1/messages", "price_conditions": [ { "label": "Tezkor rejim", "value": "Standart tarif", "when": "Tezkor rejim tanlanganda" }, { "label": "Flex rejimi", "value": "Standart tarif", "when": "flex rejimi tanlanganda" }, { "label": "Maksimal fikrlash darajasi", "value": "Standart tarif", "when": "Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda" }, { "label": "Fikrlash darajasi · yuqori", "value": "Standart tarif", "when": "Fikrlash darajasi yuqori bo‘lganda" }, { "label": "Fikrlash darajasi · past", "value": "Standart tarif", "when": "Fikrlash darajasi past bo‘lganda" }, { "label": "Fikrlash darajasi · o‘rtacha", "value": "Standart tarif", "when": "Fikrlash darajasi o‘rtacha bo‘lganda" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "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" } ] } ], "reasoning_effort_multipliers": { "high": 1, "low": 1, "medium": 1 }, "request_model_id": "stepfun/step-3.7-flash", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.08, "cache_read_multiplier": null, "cache_write": null, "cache_write_1h": null, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 0.4, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 2.3, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } } ], "model_id": "stepfun/step-3.7-flash", "nativeProvenance": { "input_facts_canonical_sha256": "4c7d28e500964abb3a75b47b6381c4dc37c656dec97ddf4ef49de610c41fa551", "input_html_sha256": "e4adf048ae1198cb35c909dae7d9685559863a7e209085cb5eae7e224b683b7f", "private_audit_sha256": "f6143f06718eac17457c7193d1735ca69fd7e841b7aad9c29e3edfe46b8d1d60", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/uz/stepfun-step-3-7-flash/", "description": "StepFun’ning Step 3.7 Flash modeli — dasturlash, vizual tushunish va vositalar bilan boshqariladigan jarayonlar uchun siyrak ko‘rish-til modeli. U 196B parametrli til tarmog‘ini 1.8B parametrli ko‘rish kodlagichi, 256K kontekst va ishlab chiqaruvchi hujjatlashtirgan uchta mulohaza darajasi bilan birlashtiradi.", "locale": "uz", "md_url": "https://ailoot.ai/models/uz/stepfun-step-3-7-flash/index.md", "title": "StepFun: Step 3.7 Flash — Ailoot", "url": "https://ailoot.ai/models/uz/stepfun-step-3-7-flash/" }, "practicalHtml": "

Amaliy vazifa

Ingliz tilidagi texnik misol

Trace a failed configuration lookup\n\nSource excerpt: settings = {"timeout_seconds": 30}; timeout = settings["timeout"]. Log: KeyError: timeout. Required public setting remains timeout_seconds. Identify the mismatch, propose the smallest source correction and give a test that reads the configured value plus a test for a missing required setting. Do not rename the public field.

Kutiladigan natija

A source-linked diagnosis, focused patch and two test cases.

Natijani tekshirish

Check that the patch reads timeout_seconds and that the missing-setting case is not hidden by an invented default.

", "practicalText": "Amaliy vazifa Ingliz tilidagi texnik misol Trace a failed configuration lookup Source excerpt: settings = {\"timeout_seconds\": 30}; timeout = settings[\"timeout\"]. Log: KeyError: timeout. Required public setting remains timeout_seconds. Identify the mismatch, propose the smallest source correction and give a test that reads the configured value plus a test for a missing required setting. Do not rename the public field. Kutiladigan natija A source-linked diagnosis, focused patch and two test cases. Natijani tekshirish Check that the patch reads timeout_seconds and that the missing-setting case is not hidden by an invented default.", "rawModel": { "about": "Step 3.7 Flash — real sharoitdagi agent topshiriqlari uchun StepFun’ning siyrak ekspertlar aralashmasiga asoslangan ko‘rish-til modeli. Taxminan 198 milliard parametrli tizim 196B parametrli til tarmog‘i va 1.8B parametrli ko‘rish kodlagichini birlashtiradi; har bir token uchun taxminan 11B parametr faollashadi. U matn va tasvirlarni qabul qilib, bog‘langan ilova uchun matn, kod yoki taklif etilgan vosita chaqiruvlarini yaratadi.\n\nIshlab chiqaruvchi 256K kontekst oynasi va low, medium hamda high mulohaza darajalarini ko‘rsatadi. Ular ishlab chiqaruvchi jarayonida topshiriqqa turli hajmda fikrlash ajratishga imkon beradi. Uzun kontekstli ish katta hisobotlar va bir nechta fayl bo‘yicha dasturiy tadqiqotlarni o‘z ichiga oladi; model shu kontekst doirasida aniq maqsadga ega bo‘lishi uchun tegishli materialni savol va kerakli natija bilan birga tayyorlang.\n\nModelning o‘zidagi vizual tushunish imkoniyati mahsulot interfeyslari, hujjatlar, diagrammalar va tabiiy sahnalarni qamrab oladi. Interfeys topshirig‘ida skrinshot yoki dizaynni bering va tekshiriladigan yoki amalga oshiriladigan funksiyani ko‘rsating. Diagramma uchun tushuntiriladigan taqqoslash yoki tendensiyani ayting. Ishlab chiqaruvchi vizual talqinni ma’lumot izlash va vositalardan foydalanish bilan birlashtiradi, shuning uchun tasvirning o‘zi savolni ochiq qoldirsa, bog‘langan jarayon qo‘shimcha dalil yig‘ishi mumkin.\n\nDasturlash topshiriqlari repozitoriyni kuzatib chiqish, xatoni topish va tuzatish taklif qilishni o‘z ichiga oladi. Kuzatilgan muammo, kutilgan xatti-harakat va joriy natijani tasdiqlaydigan fayllar yoki jurnallarni bering. O‘zgartirilgan materialni va uni baholaydigan tekshiruvlarni so‘rang. Ilova tekshiruvni ishga tushirganda, keyingi qadamdan oldin uning haqiqiy natijasini qaytaring; shunda model tuzatish ishladi deb taxmin qilmasdan, kuzatuvga javob beradi.\n\nIshlab chiqaruvchining kengroq jarayonlari qidiruv, terminallar, brauzerlar va ofis vositalarini qamrab oladi. Vosita ta’riflari va topshiriq chegaralarini bering, taklif etilgan chaqiruvni ilova qaytargan natijadan ajrating. Tadqiqot topshirig‘i manbalarni taqqoslashi va har bir xulosa dalilini saqlashi mumkin; hujjat topshirig‘i esa atrofdagi ilova yakuniy materialga aylantirishi uchun izoh yoki tuzilmali kontentni qaytarishi mumkin.\n\nStepFun alohida aniqlik variantlari va joylashtirish retseptlarini e’lon qiladi. Uning mahalliy GGUF misollarida til modeli vizual proyektordan ajratiladi va vazn fayllaridan tashqari qo‘shimcha ishlash xotirasi hisobga olinadi. Kartochkada mahalliy xotiraning minimumi taxminan 120 GB deb berilgan va shu tuzilma uchun 128 GB birlashtirilgan xotira tavsiya etilgan. Bular muayyan model tanlovi ortidagi konfiguratsiya haqidagi da’vo emas, ishlab chiqaruvchining joylashtirish shartlaridir.\n\nStep 3.7 Flash’ni oldingi Step 3.5 matn modelidan ajrating: ko‘rish kodlagichi va tasvirni tushunish muhim qo‘shimchalardir. Topshiriqning yakuniy natijasi ishlatilgan manba yoki vizual dalilni, taklif etilgan o‘zgarish yoki topilmani va hali kuzatuv talab etiladigan har qanday shartni ko‘rsatishi kerak. Tashqi qidiruvlar, buyruqlar va fayl o‘zgarishlari ilova bog‘lagan vositalarga bog‘liq.", "alias_of": null, "aliases": [], "author": "StepFun", "available": null, "canonical_model": "stepfun/step-3.7-flash", "capabilities": { "context_length": 262144, "manufacturer_input": [ "text", "image", "video" ], "manufacturer_output": [ "text" ] }, "card_routes": [ { "label": "Ultra", "rates": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "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, "entity_type": "model", "formats": [ "chat", "messages" ], "id": "stepfun/step-3.7-flash", "input": [ "text" ], "kind": "text", "max_out": null, "methods": [ { "available": null, "cache_read": 0.08, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "Majburiy maydonlar, material ifodasi yoki parametr qiymati noto‘g‘ri", "http_status": 400, "recovery": "Yangi yaratish so‘rovidan oldin ko‘rsatilgan maydonlarni tuzating.", "type": "invalid_request_error" } ], "hints": [ "Model context is not an output cap.", "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.", "Tool calls propose actions; the client application returns actual observations with the returned call ID.", "Guarded canonical keys must occur once; duplicate or case-varied model/tools/cap fields are rejected." ], "ignored_fields": [], "lifecycle": { "create": { "http": "POST", "path": "/v1/chat/completions" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "So‘rov va javob IDlari hamda sarlavhalarini saqlang. Matn vazifasini olish uchun umumiy URL taqdim etilmagan." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "UTF8 matni" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "Har bir javob variantini va uning kontenti, vosita chaqiruvlari hamda fikrlash ma’lumotlarini saqlang. SSEda o‘zgarish qismlarini variant va vosita indeksi bo‘yicha yig‘ing, yakuniy tugash sababi va sarf ma’lumotlarini saqlang.", "family": "text", "fields": [ { "description": null, "name": "choices[].index", "type": "integer" }, { "description": null, "name": "choices[].message.content", "type": "string|null" }, { "description": null, "name": "choices[].message.tool_calls", "type": "tool_call[]" }, { "description": null, "name": "choices[].message.reasoning_content", "type": "string" }, { "description": null, "name": "choices[].message.reasoning_details", "type": "object|array" }, { "description": null, "name": "choices[].finish_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "json yoki SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "stepfun/step-3.7-flash" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "min_items": 1, "name": "messages", "required": true, "type": "message[]" }, { "availability": "model_dependent", "conditions": "Bu rollar manba kodining moslik turlarida ochiq ifodalangan; aniq rollar to‘plami har bir modelga xos bo‘lib qoladi.", "default": null, "default_known": false, "enum": [ "system", "user", "assistant", "tool", "function" ], "enum_exhaustive": false, "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": false, "type": "string|content_part[]|null" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_calls", "required": false, "type": "tool_call[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].tool_call_id", "required": false, "type": "string", "when": "role=tool; haqiqatan qaytarilgan IDdan foydalaning" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].name", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_content", "required": false, "type": "string", "when": "Ushbu model foydalanganda, haqiqatan qaytarilgan fikrlash ma’lumotlarini keyingi so‘rovda qayta yuboring" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].reasoning_details", "required": false, "type": "object|array" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_tokens", "required": false, "type": "integer" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "minimum": 1, "name": "max_completion_tokens", "required": false, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stream_options.include_usage", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "temperature", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "top_p", "required": false, "type": "number" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "stop", "required": false, "type": "string|string[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools", "required": false, "type": "function_tool[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": [ "function" ], "enum_known": true, "name": "tools[].type", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.name", "required": true, "type": "string", "when": "Funksiya vositasi taqdim etilgan" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.description", "required": false, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tools[].function.parameters", "required": false, "type": "JSON_schema" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "tool_choice", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "parallel_tool_calls", "required": false, "type": "boolean" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "response_format", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning_effort", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "reasoning", "required": false, "type": "object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "service_tier", "required": false, "type": "string" }, { "availability": "source_compatibility", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "instructions", "required": false, "type": "string" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "functions", "required": false, "type": "function[]" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "function_call", "required": false, "type": "string|object" }, { "availability": "model_dependent", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "prompt_cache_options", "required": false, "type": "object" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "text" ], "enum_known": true, "name": "modalities", "required": false, "type": "string[]" }, { "availability": "source_interface", "conditions": "Ushbu Ultra matn marshrutida provider.options rad etiladi", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "provider", "required": false, "type": "object" }, { "availability": "source_interface", "conditions": "Haqiqiy prompt-kesh joylarida 1h rad etiladi", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control.ttl", "required": false, "type": "string" } ], "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.", "unsupported": [ "additional models/models list", "plugins", "route", "hosted tools; ordinary client function tools remain separate", "non-text output modalities", "provider.options overrides", "one-hour prompt-cache TTL" ] }, "hints": [ "Aniq model IDsini messages bilan yuboring.", "Kontekst uzunligi chiqishning yuqori chegarasi emas.", "Matn fayli aynan matnni taqdim etishi mumkin; tasvir, audio va fayl obyekti kirishlari aniq bog‘lashni talab qiladi." ], "input": { "content_type": "application/json", "control_scope": "Modelga xos; foydalanuvchi funksiya vositalari hostingdagi vositalardan farq qiladi", "file_material": "Haqiqiy UTF-8 hujjati aynan matn sifatida kiritiladi; fayl IDsi faraz qilinmaydi", "hosted_operations": false, "material_types": [ "text" ], "messages": "role/content tuzilishidagi xabarlar massivi", "multimodal_input_binding": null, "optional_controls": [ "stream", "temperature", "top_p", "stop", "max_tokens", "max_completion_tokens", "reasoning", "response_format", "tools", "tool_choice" ], "output_modalities": [ "text" ], "required": [ "model", "messages" ] }, "lifecycle": { "mode": "synchronous_or_streamed", "unknown": "preserve original request id; no generic chat job retrieval path" }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/chat/completions" }, "method_aliases": [], "operation_modes": [ "text_chat" ], "output": { "content": "choices[].message.content or stream delta", "family": "text", "format": "json or supported SSE", "tool_calls": "retain actual returned function calls" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Tokenlar uchun bazaviy tariflar", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "So‘rov uzunligi bo‘yicha 1-daraja", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"stepfun/step-3.7-flash\", \"messages\": [{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}]}')\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path(\"result.json\").read_text())\nfor x in r.get(\"choices\",[]):\n if x.get(\"message\",{}).get(\"content\"): print(x[\"message\"][\"content\"])\nPY_RESULT\n", "label": "curl · retained exact creation", "language": "bash" }, { "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nresult=client.chat.completions.create(model='stepfun/step-3.7-flash',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}])\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(result.to_dict(mode=\"json\"))\n", "label": "Python SDK · all choices", "language": "python" }, { "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n # Keep every field, including usage, IDs, reasoning and tool requests.\n Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n print(json.dumps(data, ensure_ascii=False, indent=2))\n def save_blob(encoded, suffix, label):\n raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n file = Path(stem + \"-\" + label + \".\" + ext)\n file.write_bytes(raw)\n print(\"Saved\", file)\n for index, block in enumerate(data.get(\"content\") or []):\n print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n for choice in data.get(\"choices\") or []:\n print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n for index, item in enumerate(data.get(\"output\") or []):\n print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n for ci, candidate in enumerate(data.get(\"candidates\") or []):\n for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n if blob and blob.get(\"data\"):\n mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='stepfun/step-3.7-flash',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n for event in stream:\n payload=event.to_dict(mode=\"json\")\n log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n print(json.dumps(payload,ensure_ascii=False))\n final=stream.get_final_completion()\n save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n", "label": "Python SDK streaming · all events", "language": "python" } ], "family": "openai", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "chat", "hints": [ "Send exact model ID with messages.", "Context length is not an output cap.", "A text file may supply literal text; image/audio/file-object inputs need exact binding." ], "http": "POST", "in": 0.4, "input": [ "text" ], "label": "OpenAI Chat", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 2.3, "output": [ "text" ], "path": "/v1/chat/completions", "price_conditions": [ { "label": "Tezkor rejim", "value": "Standart tarif", "when": "Tezkor rejim tanlanganda" }, { "label": "Flex rejimi", "value": "Standart tarif", "when": "flex rejimi tanlanganda" }, { "label": "Maksimal fikrlash darajasi", "value": "Standart tarif", "when": "Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda" }, { "label": "Fikrlash darajasi · yuqori", "value": "Standart tarif", "when": "Fikrlash darajasi yuqori bo‘lganda" }, { "label": "Fikrlash darajasi · past", "value": "Standart tarif", "when": "Fikrlash darajasi past bo‘lganda" }, { "label": "Fikrlash darajasi · o‘rtacha", "value": "Standart tarif", "when": "Fikrlash darajasi o‘rtacha bo‘lganda" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "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" } ] } ], "reasoning_effort_multipliers": { "high": 1, "low": 1, "medium": 1 }, "request_model_id": "stepfun/step-3.7-flash", "route_label": "Ultra", "status_reads": [], "tiers": [ { "cache_read": 0.08, "cache_read_multiplier": null, "cache_write": null, "cache_write_1h": null, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 0.4, "input_multiplier": null, "interval_boundary": "min_exclusive_max_inclusive", "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "null_rate_policy": "unknown or inherited; never zero", "out": 2.3, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "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" } ] }, { "available": null, "cache_read": 0.08, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "authentication": { "api_key_source": "AILOOT_API_KEY", "headers": [ "Authorization: Bearer", "x-api-key", "anthropic-version" ], "version_example": "2023-06-01" }, "errors": [ { "code": null, "condition": "Majburiy maydonlar, material ifodasi yoki parametr qiymati noto‘g‘ri", "http_status": 400, "recovery": "Yangi yaratish so‘rovidan oldin ko‘rsatilgan maydonlarni tuzating.", "type": "invalid_request_error" } ], "example_body": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "stepfun/step-3.7-flash", "stream": false }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "So‘rov va javob IDlari hamda sarlavhalarini saqlang. Matn vazifasini olish uchun umumiy URL taqdim etilmagan." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content satri", "required_material": "UTF-8 matni" } ], "operation_modes": [ "synchronous_json", "streamed_SSE" ], "outputs": { "all_results": "Barcha kontent bloklari, fikrlash imzolari va haqiqiy vosita ishlatish IDlarini saqlang. SSE bloklarining barcha o‘zgarish qismlarini yig‘ing; birinchi matn bloki to‘liq chiqish emas.", "family": "protocol", "fields": [ { "description": null, "name": "id", "type": "string" }, { "description": null, "name": "model", "type": "string" }, { "description": null, "name": "content[]", "type": "text|thinking|tool_use|other content block" }, { "description": null, "name": "stop_reason", "type": "string|null" }, { "description": null, "name": "usage", "type": "object" } ], "format": "JSON yoki SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "stepfun/step-3.7-flash" ], "enum_known": true, "name": "model", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages", "required": true, "type": "message[]" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "user", "assistant" ], "enum_known": true, "name": "messages[].role", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "messages[].content", "required": true, "type": "string" }, { "availability": "source_interface", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "max_tokens", "required": true, "type": "integer" }, { "availability": "source_interface", "default": false, "default_known": true, "enum": null, "enum_known": false, "name": "stream", "required": false, "type": "boolean" } ], "profile_binding": "Documented current stock Messages bridge; optional model capabilities are separate from this minimal text request.", "request_schema": { "additionalProperties": false, "properties": { "max_tokens": { "minimum": 1, "type": "integer" }, "messages": { "items": { "additionalProperties": false, "properties": { "content": { "oneOf": [ { "type": "string" }, { "items": { "oneOf": [ { "properties": { "text": { "type": "string" }, "type": { "const": "text" } }, "required": [ "type", "text" ], "type": "object" }, { "properties": { "source": { "oneOf": [ { "properties": { "type": { "const": "url" }, "url": { "type": "string" } }, "required": [ "type", "url" ], "type": "object" }, { "properties": { "data": { "type": "string" }, "media_type": { "type": "string" }, "type": { "const": "base64" } }, "required": [ "type", "media_type", "data" ], "type": "object" } ] }, "type": { "const": "image" } }, "required": [ "type", "source" ], "type": "object" } ] }, "type": "array" } ] }, "role": { "enum": [ "user", "assistant" ], "type": "string" } }, "required": [ "role", "content" ], "type": "object" }, "minItems": 1, "type": "array" }, "model": { "enum": [ "stepfun/step-3.7-flash" ], "type": "string" }, "stream": { "default": false, "type": "boolean" } }, "required": [ "model", "messages", "max_tokens" ], "type": "object" }, "schema_template": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "stepfun/step-3.7-flash", "stream": false }, "unsupported": [ "No query API key.", "Hosted/server-side tools and model-specific optional controls are not part of this minimal family example." ] }, "input": { "content_type": "application/json", "material_types": [ "text" ], "optional_controls": [ "stream" ], "required": [ "model", "messages", "max_tokens" ], "text_file_material": "Haqiqiy UTF-8 hujjatini o‘qing va uning matnini ko‘rsatilgan kirish yoki xabar kontenti satriga joylashtiring." }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "Keep request/response IDs and headers. No generic text job retrieval URL is supplied." }, "manufacturer_capability": null, "method": { "http": "POST", "path": "/v1/messages" }, "output": { "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.", "family": "protocol", "format": "JSON or SSE" } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Tokenlar uchun bazaviy tariflar", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "So‘rov uzunligi bo‘yicha 1-daraja", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "{\n \"model\": \"stepfun/step-3.7-flash\",\n \"max_tokens\": 128,\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Summarize the incident report.\"\n }\n ],\n \"stream\": false\n}", "label": "Complete minimal JSON body", "language": "json" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'stepfun/step-3.7-flash', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n", "label": "curl · use your UTF-8 document", "language": "bash" }, { "code": "import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('Choose a document containing text')\npayload = {'model': 'stepfun/step-3.7-flash', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n with urlopen(request, timeout=120) as response:\n raw = response.read()\n Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n Path('result.json').write_bytes(error.read())\n Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n", "label": "Python · save the complete result", "language": "python" } ], "family": "anthropic", "fast_multiplier": 1, "flex_multiplier": 1, "fmt": "messages", "http": "POST", "in": 0.4, "input": [ "text" ], "label": "Anthropic Messages", "max_out": null, "max_reasoning_effort_multiplier": 1, "method_aliases": [], "out": 2.3, "output": [ "json", "sse" ], "path": "/v1/messages", "price_conditions": [ { "label": "Tezkor rejim", "value": "Standart tarif", "when": "Tezkor rejim tanlanganda" }, { "label": "Flex rejimi", "value": "Standart tarif", "when": "flex rejimi tanlanganda" }, { "label": "Maksimal fikrlash darajasi", "value": "Standart tarif", "when": "Maksimal fikrlash darajasi uchun standart (default) tuzatish qo‘llanganda" }, { "label": "Fikrlash darajasi · yuqori", "value": "Standart tarif", "when": "Fikrlash darajasi yuqori bo‘lganda" }, { "label": "Fikrlash darajasi · past", "value": "Standart tarif", "when": "Fikrlash darajasi past bo‘lganda" }, { "label": "Fikrlash darajasi · o‘rtacha", "value": "Standart tarif", "when": "Fikrlash darajasi o‘rtacha bo‘lganda" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.0004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000004", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0.0023000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.0000023", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": "0.00008000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": "0.00000008", "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, 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