{ "aboutHtml": "

SenseNova V6 Pro – tai bendras „SenseTime“ multimodalus profilis pokalbiams, jungiantiems rašytinius klausimus ir vaizdus. Gamintojo profilių lentelė aprašo vaizdų ir teksto įvestį su tekstine išvestimi. V6 šeima pabrėžia mišrios vaizdinės bei kalbinės informacijos supratimą, samprotavimą ir analizę. Pro lieka atskiras nuo lengvesnio Turbo profilio ir atskirai pavadinto Reasoner, kurio išvestis apima samprotavimo medžiagą kartu su galutiniu atsakymu.

Pateikite klausimą su aiškiais vaizdiniais įrodymais

Pasirinkite klausimą pagrindžiantį vaizdą ar pradinį tekstą ir pasirūpinkite svarbių detalių įskaitomumu. Dokumento užduotyje galima pateikti puslapį su diagrama ar lentele ir klausti, kurią sąlygą pagrindžia matomos reikšmės. Ekrano nuotraukos klausime galima įvardyti aptariamą valdiklį ar žinutę. Papildomą foną atskirkite nuo to, ką rodo pats paveikslėlis.

Paprašykite užduočiai tinkamo rezultato: paaiškinimo, palyginimo, išgauto matomų reikšmių rinkinio ar pateikta medžiaga pagrįsto juodraščio. Naudingas dokumentų palyginimas gali išsaugoti puslapio identifikatorių ir įrodymus prie kiekvieno pastebėjimo. Grąžintame tekste tikrinkite žymas, vienetus ir ryšius su šaltiniais, užuot rėmęsi įtikinama viso paveikslėlio interpretacija.

Samprotaukite pagal tekstą ir vaizdus

Gamintojo V6 pristatymas aprašo sulietą modelių seriją, o ne atskiras kalbos ir regos šakas. Jos paskirtis apima matematikos, programavimo ir dokumentų analizės užduotis, kurioms reikia suprasti susijusią informaciją. Nurodykite sąlygas, kurias atsakymas turi atitikti, ir atskirkite žinomas reikšmes nuo prielaidų. Pagrįstas atsakymas turi leisti jo išvadą įvertinti pagal tikrą pradinę medžiagą.

Kelių dokumentų klausime nurodykite, kuris šaltinis turi lemti nesutarimo sprendimą, ir išsaugokite svarbias ištraukas ar matomas sritis. Jei medžiaga nepilna, trūkstamą sąlygą laikykite atskirai nuo užpildyto lauko. Užtikrintas paaiškinimas savaime neįrodo, kad šaltinyje yra jam priskirta reikšmė.

Profilis ir platesnės šeimos darbo eigos

Pro lentelė nurodo tekstinį atsakymą pokalbiui pagal vaizdą ir tekstą. V6 šeimos pristatyme taip pat aptariama išplėstų vaizdo įrašų analizė ir atskiras Omni tikralaikės sąveikos profilis. Šios šeimos demonstracijos turi likti susietos su gamintojo darbo eigomis, o ne būti laikomos visa Pro užklausos laukų specifikacija. Vėlesni V6.5 ir V6.7 modeliai turi savo galimybes ir valdiklius.

Pro vaizdų bei teksto užduočiai išsaugokite pateiktą klausimą, vaizdus ir užbaigtą tekstinį atsakymą. Svarbius skaičius, vaizdinius ryšius, siūlomą kodą ar samprotavimą tikrinkite pagal juos pagrindžiančius įrodymus. Naudingas perdavimo rezultatas gali būti paaiškinimas ar struktūruotas palyginimas, kurio pastebėjimus galima atsekti iki pradinio puslapio, leidžiant konkrečiai tęsti darbą dėl vienos neišspręstos detalės.

", "aboutText": "SenseNova V6 Pro – tai bendras „SenseTime“ multimodalus profilis pokalbiams, jungiantiems rašytinius klausimus ir vaizdus. Gamintojo profilių lentelė aprašo vaizdų ir teksto įvestį su tekstine išvestimi. V6 šeima pabrėžia mišrios vaizdinės bei kalbinės informacijos supratimą, samprotavimą ir analizę. Pro lieka atskiras nuo lengvesnio Turbo profilio ir atskirai pavadinto Reasoner, kurio išvestis apima samprotavimo medžiagą kartu su galutiniu atsakymu.\n\n### Pateikite klausimą su aiškiais vaizdiniais įrodymais\n\nPasirinkite klausimą pagrindžiantį vaizdą ar pradinį tekstą ir pasirūpinkite svarbių detalių įskaitomumu. Dokumento užduotyje galima pateikti puslapį su diagrama ar lentele ir klausti, kurią sąlygą pagrindžia matomos reikšmės. Ekrano nuotraukos klausime galima įvardyti aptariamą valdiklį ar žinutę. Papildomą foną atskirkite nuo to, ką rodo pats paveikslėlis.\n\nPaprašykite užduočiai tinkamo rezultato: paaiškinimo, palyginimo, išgauto matomų reikšmių rinkinio ar pateikta medžiaga pagrįsto juodraščio. Naudingas dokumentų palyginimas gali išsaugoti puslapio identifikatorių ir įrodymus prie kiekvieno pastebėjimo. Grąžintame tekste tikrinkite žymas, vienetus ir ryšius su šaltiniais, užuot rėmęsi įtikinama viso paveikslėlio interpretacija.\n\n### Samprotaukite pagal tekstą ir vaizdus\n\nGamintojo V6 pristatymas aprašo sulietą modelių seriją, o ne atskiras kalbos ir regos šakas. Jos paskirtis apima matematikos, programavimo ir dokumentų analizės užduotis, kurioms reikia suprasti susijusią informaciją. Nurodykite sąlygas, kurias atsakymas turi atitikti, ir atskirkite žinomas reikšmes nuo prielaidų. Pagrįstas atsakymas turi leisti jo išvadą įvertinti pagal tikrą pradinę medžiagą.\n\nKelių dokumentų klausime nurodykite, kuris šaltinis turi lemti nesutarimo sprendimą, ir išsaugokite svarbias ištraukas ar matomas sritis. Jei medžiaga nepilna, trūkstamą sąlygą laikykite atskirai nuo užpildyto lauko. Užtikrintas paaiškinimas savaime neįrodo, kad šaltinyje yra jam priskirta reikšmė.\n\n### Profilis ir platesnės šeimos darbo eigos\n\nPro lentelė nurodo tekstinį atsakymą pokalbiui pagal vaizdą ir tekstą. V6 šeimos pristatyme taip pat aptariama išplėstų vaizdo įrašų analizė ir atskiras Omni tikralaikės sąveikos profilis. Šios šeimos demonstracijos turi likti susietos su gamintojo darbo eigomis, o ne būti laikomos visa Pro užklausos laukų specifikacija. Vėlesni V6.5 ir V6.7 modeliai turi savo galimybes ir valdiklius.\n\nPro vaizdų bei teksto užduočiai išsaugokite pateiktą klausimą, vaizdus ir užbaigtą tekstinį atsakymą. Svarbius skaičius, vaizdinius ryšius, siūlomą kodą ar samprotavimą tikrinkite pagal juos pagrindžiančius įrodymus. Naudingas perdavimo rezultatas gali būti paaiškinimas ar struktūruotas palyginimas, kurio pastebėjimus galima atsekti iki pradinio puslapio, leidžiant konkrečiai tęsti darbą dėl vienos neišspręstos detalės.", "editorialOverlay": { "copy_fields": { "practical_html": "

Praktinė užduotis

Techninis pavyzdys anglų kalba

Explain a supplied chart transcription\n\nUse this text transcription of report page P7: 'Target line: 50 units. North: 48. South: 53. East: 50.' State which regions meet a target defined as at least 50 units. Return each region's value, its relation to the target and the page label. Distinguish meeting the target from strictly exceeding it.

Laukiamas rezultatas

A region-by-region source-linked comparison with the inclusive target condition applied.

Rezultato patikra

East must be treated as meeting, but not exceeding, the 50-unit target.

" }, "copy_sha256": "7ed7828767271f19c3af8d901dd2dd5085ccfecd22a1bf12f7c255a436f0b797", "copy_source": { "locale": "lt", "pack_sha256": "0f56d90ba41881e1134accf82e57338f246f8753ca4c0cee929aaffada5d10e7", "record_model_id": "sensetime/sensenova-v6-pro", "source_facts_sha256": "31418181bc7f53ebdc08ca80bb7f1413bdb50cbd422a3c7c26d5c2c122d753b0", "validation_sha256": "a2ac2f28056280fc0b2ea34a501bf156d5ce155406e57e708edf30bfdf6bfdc6" }, "html_sha256": "a52cd8891b7ca87707826816d1384d9876e157935e3412a9d6ef40409f3c82c2", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "lt", "methods": [ { "html": "

•

SenseNova-V6-Pro

Kita /SenseNova-V6-Pro

Modelio ID

Pradžia

SenseNova V6 Pro – tai bendros paskirties „SenseTime“ vaizdų ir teksto pokalbio profilis, grąžinantis tekstą. Pateikite dokumentus, paveikslėlius ir klausimus paaiškinimui ar palyginimui, išlaikydami atsakymo ryšį su vaizdiniais ir rašytiniais įrodymais.

Leidžiamos įvestys: Tekstas
Rezultatai: Tekstas

Apie modelį

Šis aprašas apima modelio galimybes. Pasirinktam metodui Ailoot prieinamos įvestys, išvestys ir parinktys nurodytos toliau.

SenseNova V6 Pro – tai bendras „SenseTime“ multimodalus profilis pokalbiams, jungiantiems rašytinius klausimus ir vaizdus. Gamintojo profilių lentelė aprašo vaizdų ir teksto įvestį su tekstine išvestimi. V6 šeima pabrėžia mišrios vaizdinės bei kalbinės informacijos supratimą, samprotavimą ir analizę. Pro lieka atskiras nuo lengvesnio Turbo profilio ir atskirai pavadinto Reasoner, kurio išvestis apima samprotavimo medžiagą kartu su galutiniu atsakymu.

Pateikite klausimą su aiškiais vaizdiniais įrodymais

Pasirinkite klausimą pagrindžiantį vaizdą ar pradinį tekstą ir pasirūpinkite svarbių detalių įskaitomumu. Dokumento užduotyje galima pateikti puslapį su diagrama ar lentele ir klausti, kurią sąlygą pagrindžia matomos reikšmės. Ekrano nuotraukos klausime galima įvardyti aptariamą valdiklį ar žinutę. Papildomą foną atskirkite nuo to, ką rodo pats paveikslėlis.

Paprašykite užduočiai tinkamo rezultato: paaiškinimo, palyginimo, išgauto matomų reikšmių rinkinio ar pateikta medžiaga pagrįsto juodraščio. Naudingas dokumentų palyginimas gali išsaugoti puslapio identifikatorių ir įrodymus prie kiekvieno pastebėjimo. Grąžintame tekste tikrinkite žymas, vienetus ir ryšius su šaltiniais, užuot rėmęsi įtikinama viso paveikslėlio interpretacija.

Samprotaukite pagal tekstą ir vaizdus

Gamintojo V6 pristatymas aprašo sulietą modelių seriją, o ne atskiras kalbos ir regos šakas. Jos paskirtis apima matematikos, programavimo ir dokumentų analizės užduotis, kurioms reikia suprasti susijusią informaciją. Nurodykite sąlygas, kurias atsakymas turi atitikti, ir atskirkite žinomas reikšmes nuo prielaidų. Pagrįstas atsakymas turi leisti jo išvadą įvertinti pagal tikrą pradinę medžiagą.

Kelių dokumentų klausime nurodykite, kuris šaltinis turi lemti nesutarimo sprendimą, ir išsaugokite svarbias ištraukas ar matomas sritis. Jei medžiaga nepilna, trūkstamą sąlygą laikykite atskirai nuo užpildyto lauko. Užtikrintas paaiškinimas savaime neįrodo, kad šaltinyje yra jam priskirta reikšmė.

Profilis ir platesnės šeimos darbo eigos

Pro lentelė nurodo tekstinį atsakymą pokalbiui pagal vaizdą ir tekstą. V6 šeimos pristatyme taip pat aptariama išplėstų vaizdo įrašų analizė ir atskiras Omni tikralaikės sąveikos profilis. Šios šeimos demonstracijos turi likti susietos su gamintojo darbo eigomis, o ne būti laikomos visa Pro užklausos laukų specifikacija. Vėlesni V6.5 ir V6.7 modeliai turi savo galimybes ir valdiklius.

Pro vaizdų bei teksto užduočiai išsaugokite pateiktą klausimą, vaizdus ir užbaigtą tekstinį atsakymą. Svarbius skaičius, vaizdinius ryšius, siūlomą kodą ar samprotavimą tikrinkite pagal juos pagrindžiančius įrodymus. Naudingas perdavimo rezultatas gali būti paaiškinimas ar struktūruotas palyginimas, kurio pastebėjimus galima atsekti iki pradinio puslapio, leidžiant konkrečiai tęsti darbą dėl vienos neišspręstos detalės.

Prieinama Ailoot · įvestys ir metodai

Ailoot Ultra · OpenAI Chat · SenseNova-V6-Pro POST /v1/chat/completions

Įvestis: text
Išvestis: text
Išvesties formatas: json arba SSE

Laukas	Tipas	Reikalavimas	Reikšmės ir ribos	Numatyta
Laukas`model`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos SenseNova-V6-Pro	Numatyta—
Laukas`messages`	Tipas`message[]`	ReikalavimasPrivaloma	Reikšmės ir ribos Mažiausias elementų skaičius: 1	Numatyta—
Laukas`messages[].role`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos Pavyzdžiai: system, user, assistant, tool, function Sąlygos: Palaikomų vaidmenų rinkinys priklauso nuo pasirinkto modelio. Priklauso nuo modelio	Numatyta—
Laukas`messages[].content`	Tipas`string\|content_part[]\|null`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatyta—
Laukas`messages[].tool_calls`	Tipas`tool_call[]`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatyta—
Laukas`messages[].tool_call_id`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Taikoma, kai: role=tool; naudokite tikrąjį grąžintą ID	Numatyta—
Laukas`messages[].name`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatyta—
Laukas`messages[].reasoning_content`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Taikoma, kai: Grąžinkite tikrąjį gautą samprotavimą ten, kur šis modelis jį naudoja	Numatyta—
Laukas`messages[].reasoning_details`	Tipas`object\|array`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`max_tokens`	Tipas`integer`	ReikalavimasNeprivaloma	Reikšmės ir ribos Mažiausia reikšmė: 1 Priklauso nuo modelio	Numatyta—
Laukas`max_completion_tokens`	Tipas`integer`	ReikalavimasNeprivaloma	Reikšmės ir ribos Mažiausia reikšmė: 1 Priklauso nuo modelio	Numatyta—
Laukas`stream`	Tipas`boolean`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatytafalse
Laukas`stream_options.include_usage`	Tipas`boolean`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`temperature`	Tipas`number`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`top_p`	Tipas`number`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`stop`	Tipas`string\|string[]`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`tools`	Tipas`function_tool[]`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`tools[].type`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos function Priklauso nuo modelio	Numatyta—
Laukas`tools[].function.name`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos Taikoma, kai: pateiktas funkcijos tipo įrankis	Numatyta—
Laukas`tools[].function.description`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatyta—
Laukas`tools[].function.parameters`	Tipas`JSON_schema`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatyta—
Laukas`tool_choice`	Tipas`string\|object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`parallel_tool_calls`	Tipas`boolean`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`response_format`	Tipas`object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`reasoning_effort`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`reasoning`	Tipas`object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`service_tier`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`instructions`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Suderinamumo laukas	Numatyta—
Laukas`functions`	Tipas`function[]`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`function_call`	Tipas`string\|object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`prompt_cache_options`	Tipas`object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`modalities`	Tipas`string[]`	ReikalavimasNeprivaloma	Reikšmės ir ribos text	Numatyta—
Laukas`provider`	Tipas`object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Sąlygos: provider.options šiame Ultra teksto maršrute atmetamas	Numatyta—
Laukas`cache_control.ttl`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Sąlygos: 1h atmetamas tikrosiose užklausų podėlio vietose	Numatyta—

Įvesties medžiagos deriniai

Tekstas · UTF8 tekstas

messages[].content

Metodo parametrai ir gyvavimo ciklas

Parametras	Specifikacija
Parametras`content_type`	Specifikacijaapplication/json
Parametras`required`	Specifikacijamodel, messages
Parametras`material_types`	Specifikacijatext
Parametras`messages`	Specifikacijapranešimų masyvas su role/content struktūra
Parametras`file_material`	SpecifikacijaNuskaitykite savo tikrą UTF-8 dokumentą ir įterpkite jo tekstą į messages[].content.
Parametras`optional_controls`	Specifikacijastream, temperature, top_p, stop, max_tokens, max_completion_tokens, reasoning, response_format, tools, tool_choice
Parametras`control_scope`	Specifikacijapriklauso nuo modelio; naudotojo funkcijų įrankiai skiriasi nuo priglobtų įrankių
Parametras`output_modalities`	Specifikacijatext
Parametras`hosted_operations`	Specifikacijafalse
Parametras`multimodal_input_binding`	Specifikacijanull

Gyvavimo ciklas: synchronous_or_streamed

Siųskite tikslų modelio ID kartu su messages.

Konteksto ilgis nėra išvesties limitas.

Teksto failas gali pateikti pažodinį tekstą; vaizdų / garso / failų objektų įvestims reikia tikslaus susiejimo.

Planai

Tarifų informacija neprideda užklausos parinkčių. Palaikomi parametrai nurodyti prie pasirinkto metodo.

Spartusis režimas: Nenurodyta Pasirinkus spartųjį režimą
Flex režimas: Nenurodyta Pasirinkus flex režimą
Didžiausios samprotavimo pastangos: Nenurodyta Kai didžiausioms samprotavimo pastangoms taikomas numatytasis koregavimas (default)

Ailoot įkainiai

Kainos pagal konfigūraciją

Konfigūracija	Įkainių lentelė	Mokestis
KonfigūracijaBaziniai žetonų įkainiai	Įkainių lentelėBazinis įkainis	Mokestis Įvestis · Įvesties tokenai $0.0011 / 1K tokenų Išvestis · Išvesties tokenai $0.00286 / 1K tokenų Įvestis · Talpyklos skaitymas $0 / 1K tokenų Įvestis · Rašymas į talpyklą $0 / 1K tokenų Įvestis · Rašymas į talpyklą, 1 val — / 1K tokenų

Ailoot prieš užklausą rezervuoja numatomą sumą. Gavus rezultatą, galutinis mokestis nuskaitomas pagal išmatuotą naudojimą. Srautinio atsakymo atsiskaitymui naudojamas galutinis naudojimo įrašas. Kaip veikia rezervavimas ir atsiskaitymas →

Užklausų pavyzdžiai

Ailoot Ultra · OpenAI Chat · SenseNova-V6-Pro

{\n  "model": "SenseNova-V6-Pro",\n  "messages": [\n    {\n      "role": "user",\n      "content": "Hello!"\n    }\n  ]\n}

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_TEXT_FILE:?Set your actual UTF-8 source document}"\nexport AILOOT_TEXT_FILE AILOOT_STREAM\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nmaterial_path = Path(os.environ['AILOOT_TEXT_FILE'])\nif not material_path.is_file():\n    raise SystemExit('Choose your actual UTF-8 document')\ntext = material_path.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('The document must contain text')\nstream = os.environ.get('AILOOT_STREAM', '0') == '1'\npayload = {'model': 'SenseNova-V6-Pro', 'messages': [{'role': 'user', 'content': 'Hello!'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting passages.\\n\\n' + text\npayload['stream'] = stream\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/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-body.bin\npython3 - <<'PY_RESULT'\nimport json, os\nfrom pathlib import Path\n\nraw = Path('result-body.bin').read_bytes()\nif os.environ.get('AILOOT_STREAM', '0') == '1':\n    Path('result.sse').write_bytes(raw)\n    print(raw.decode('utf-8'))\nelse:\n    Path('result.json').write_bytes(raw)\n    result = json.loads(raw)\n    print(json.dumps(result, ensure_ascii=False, indent=2))\n    for choice in result.get('choices', []):\n        print('Choice', choice.get('index'), json.dumps(choice, ensure_ascii=False))\nPY_RESULT\n

import json, os\nfrom pathlib import Path\n\nmaterial_path = Path(os.environ['AILOOT_TEXT_FILE'])\nif not material_path.is_file():\n    raise SystemExit('Choose your actual UTF-8 document')\ntext = material_path.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('The document must contain text')\nstream = os.environ.get('AILOOT_STREAM', '0') == '1'\npayload = {'model': 'SenseNova-V6-Pro', 'messages': [{'role': 'user', 'content': 'Hello!'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting passages.\\n\\n' + text\npayload['stream'] = stream\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')\nrequest = Request('https://api.ailoot.ai/v1/chat/completions', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers={'Authorization': 'Bearer ' + api_key, 'Content-Type': 'application/json'}, 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-body.bin').write_bytes(error.read())\n    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n    raise\nPath('result-body.bin').write_bytes(raw)\nimport json, os\nfrom pathlib import Path\n\nraw = Path('result-body.bin').read_bytes()\nif os.environ.get('AILOOT_STREAM', '0') == '1':\n    Path('result.sse').write_bytes(raw)\n    print(raw.decode('utf-8'))\nelse:\n    Path('result.json').write_bytes(raw)\n    result = json.loads(raw)\n    print(json.dumps(result, ensure_ascii=False, indent=2))\n    for choice in result.get('choices', []):\n        print('Choice', choice.get('index'), json.dumps(choice, ensure_ascii=False))\n

import { readFileSync, writeFileSync } from 'node:fs';\n\nconst apiKey = process.env.AILOOT_API_KEY;\nif (!apiKey?.trim()) throw new Error('Set AILOOT_API_KEY');\nif (!process.env.AILOOT_TEXT_FILE) throw new Error('Choose your actual UTF-8 document');\nconst text = readFileSync(process.env.AILOOT_TEXT_FILE, 'utf8');\nif (!text.trim()) throw new Error('The document must contain text');\nconst stream = process.env.AILOOT_STREAM === '1';\nconst payload = {"model": "SenseNova-V6-Pro", "messages": [{"role": "user", "content": "Hello!"}]};\npayload.messages[0].content = 'Summarize this material and quote supporting passages.\\n\\n' + text;\npayload.stream = stream;\nconst response = await fetch('https://api.ailoot.ai/v1/chat/completions', { method: 'POST', headers: { 'Authorization': 'Bearer ' + apiKey, 'Content-Type': 'application/json' }, body: JSON.stringify(payload) });\nconst raw = Buffer.from(await response.arrayBuffer());\nwriteFileSync('result-body.bin', raw);\nwriteFileSync('response-headers.txt', [...response.headers].map(([key, value]) => key + ': ' + value).join('\\n'));\nif (!response.ok) throw new Error('HTTP ' + response.status + '; original response saved in result-body.bin');\nif (stream) {\n  writeFileSync('result.sse', raw);\n  process.stdout.write(raw);\n} else {\n  writeFileSync('result.json', raw);\n  const result = JSON.parse(raw.toString('utf8'));\n  console.log(JSON.stringify(result, null, 2));\n  for (const choice of result.choices ?? []) console.log('Choice', choice.index, JSON.stringify(choice));\n}\n

Gauti ir išsaugoti rezultatus

Ailoot Ultra · OpenAI Chat · SenseNova-V6-Pro

json arba SSE

Išsaugoti visus baigtus rezultatus

Išsaugokite kiekvieną visą grąžintą atsakymą, failą ir turinio dalį.

Išsaugokite kiekvieną variantą ir jo turinį / įrankių iškvietimus / samprotavimą. SSE prieaugius surinkite pagal varianto / įrankio indeksą; išsaugokite galutinę užbaigimo priežastį ir naudojimo duomenis.

Jei reikia patikrinti pradinį atsakymą

Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas.

Atsakymo laukai

Laukas	Tipas
Laukas`choices[].index`	Tipasinteger
Laukas`choices[].message.content`	Tipasstring\|null
Laukas`choices[].message.tool_calls`	Tipastool_call[]
Laukas`choices[].message.reasoning_content`	Tipasstring
Laukas`choices[].message.reasoning_details`	Tipasobject\|array
Laukas`choices[].finish_reason`	Tipasstring\|null
Laukas`usage`	Tipasobject

Klaidos ir tolesni veiksmai

Atsakymas	Sąlyga	Kitas žingsnis
Atsakymas400 · `invalid_request_error`	SąlygaNetinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė	Kitas žingsnisPrieš naują kūrimo užklausą pataisykite nurodytus laukus.

Pseudonimai

Modelių pseudonimai

Ailoot Ultra SenseNova-V6-Pro, sensetime/sensenova-v6-pro

Metodų kelių pseudonimai

Naudokite aukščiau nurodytus metodų kelius.

Susiję ID iškvietimui

sensetime/sensenova-v6-pro, SenseNova-V6-Pro

", "method_identity": { "effective_request_model_id": "SenseNova-V6-Pro", "fmt": "chat", "http": "POST", "path": "/v1/chat/completions", "request_model_id": "SenseNova-V6-Pro", "route_label": "Ultra" }, "method_key": "Ultra|chat|/v1/chat/completions|SenseNova-V6-Pro", "ordinal": 0, "rawMethod": { "available": null, "cache_read": 0, "cache_write": 0, "cache_write_1h": null, "contract": { "data": { "all_results": "Save every choices[] entry, content, reasoning, tool call and usage field. For streaming, save every SSE event and delta through [DONE].", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "Netinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė", "http_status": 400, "recovery": "Prieš naują kūrimo užklausą pataisykite nurodytus laukus.", "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": "Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "UTF8 tekstas" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "Išsaugokite kiekvieną variantą ir jo turinį / įrankių iškvietimus / samprotavimą. SSE prieaugius surinkite pagal varianto / įrankio indeksą; išsaugokite galutinę užbaigimo priežastį ir naudojimo duomenis.", "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 arba SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "SenseNova-V6-Pro" ], "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": "Palaikomų vaidmenų rinkinys priklauso nuo pasirinkto modelio.", "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; naudokite tikrąjį grąžintą ID" }, { "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": "Grąžinkite tikrąjį gautą samprotavimą ten, kur šis modelis jį naudoja" }, { "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": "pateiktas funkcijos tipo įrankis" }, { "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": "provider.options šiame Ultra teksto maršrute atmetamas", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "provider", "required": false, "type": "object" }, { "availability": "source_interface", "conditions": "1h atmetamas tikrosiose užklausų podėlio vietose", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control.ttl", "required": false, "type": "string" } ], "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": [ "Siųskite tikslų modelio ID kartu su messages.", "Konteksto ilgis nėra išvesties limitas.", "Teksto failas gali pateikti pažodinį tekstą; vaizdų / garso / failų objektų įvestims reikia tikslaus susiejimo." ], "input": { "content_type": "application/json", "control_scope": "priklauso nuo modelio; naudotojo funkcijų įrankiai skiriasi nuo priglobtų įrankių", "file_material": "Nuskaitykite savo tikrą UTF-8 dokumentą ir įterpkite jo tekstą į messages[].content.", "hosted_operations": false, "material_types": [ "text" ], "messages": "pranešimų masyvas su role/content struktūra", "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": [], "official_sources": [ { "title": "Chat Completions API", "url": "https://302ai-en.apifox.cn/207705102e0" } ], "operation_modes": [ "text_chat" ], "output": { "all_results": "Save every choices[] entry, content, reasoning, tool call and usage field. For streaming, save every SSE event and delta through [DONE].", "content": "choices[].message.content or stream delta", "family": "text", "format": "json or supported SSE", "tool_calls": "retain actual returned function calls" }, "schema": { "request": { "properties": { "frequency_penalty": { "description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)", "type": "number" }, "logit_bias": { "description": "Modify the likelihood of specific tokens appearing in the completion. This can be done by providing a JSON object that maps tokens (identified by their token IDs in the tokenizer) to a bias value ranging from -100 to 100. Mathematically, this bias is added to the logits generated by the model before sampling. The exact effect varies depending on the model, but values between -1 and 1 will slightly decrease or increase the likelihood of selection, while values like -100 or 100 will either ban or exclusively select the relevant token.", "type": "null" }, "max_tokens": { "description": "The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length.", "type": "integer" }, "messages": { "description": "Generate messages in [chat format](https://platform.openai.com/docs/guides/chat/introduction) for chat completions.", "items": { "properties": { "content": { "type": "string" }, "role": { "type": "string" } }, "type": "object", "x-apifox-orders": [ "role", "content" ] }, "type": "array" }, "model": { "description": "The ID of the model to be used. For detailed information on which models are applicable to the chat API, please view [Model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility)", "enum": [ "SenseNova-V6-Pro" ], "type": "string" }, "n": { "description": "How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.", "type": "integer" }, "presence_penalty": { "description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)", "type": "number" }, "stop": { "description": "Up to 4 sequences where the API will stop generating further tokens.", "type": "string" }, "stream": { "description": "If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by `data: [DONE]` message. For [Example Code.](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb)，Please view OpenAI Cookbook.", "type": "boolean" }, "temperature": { "description": "What sampling temperature to use, ranging from 0 to 2. Higher values, such as 0.8, will make the output more random, while lower values, like 0.2, will make it more focused and deterministic. We generally recommend adjusting either this or `top_p`, but not both simultaneously.", "type": "integer" }, "top_p": { "description": "An alternative to temperature sampling is nucleus sampling, where the model considers tokens within the top_p probability mass. For instance, top_p = 0.1 means only tokens within the top 10% probability mass are considered. We recommend adjusting either this or `temperature`, but not both simultaneously.", "type": "integer" }, "user": { "description": "A unique identifier representing your end users, which helps OpenAI monitor and detect abuse. [View more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids)", "type": "string" } }, "required": [ "model", "messages" ], "type": "object", "x-apifox-orders": [ "model", "messages", "temperature", "top_p", "n", "stream", "stop", "max_tokens", "presence_penalty", "frequency_penalty", "logit_bias", "user" ] } } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Baziniai žetonų įkainiai", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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\": \"SenseNova-V6-Pro\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Hello!\"\n }\n ]\n}", "label": "Complete minimal Chat body", "language": "json" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source document}\"\nexport AILOOT_TEXT_FILE AILOOT_STREAM\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nmaterial_path = Path(os.environ['AILOOT_TEXT_FILE'])\nif not material_path.is_file():\n raise SystemExit('Choose your actual UTF-8 document')\ntext = material_path.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('The document must contain text')\nstream = os.environ.get('AILOOT_STREAM', '0') == '1'\npayload = {'model': 'SenseNova-V6-Pro', 'messages': [{'role': 'user', 'content': 'Hello!'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting passages.\\n\\n' + text\npayload['stream'] = stream\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/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-body.bin\npython3 - <<'PY_RESULT'\nimport json, os\nfrom pathlib import Path\n\nraw = Path('result-body.bin').read_bytes()\nif os.environ.get('AILOOT_STREAM', '0') == '1':\n Path('result.sse').write_bytes(raw)\n print(raw.decode('utf-8'))\nelse:\n Path('result.json').write_bytes(raw)\n result = json.loads(raw)\n print(json.dumps(result, ensure_ascii=False, indent=2))\n for choice in result.get('choices', []):\n print('Choice', choice.get('index'), json.dumps(choice, ensure_ascii=False))\nPY_RESULT\n", "label": "curl · your UTF-8 document; AILOOT_STREAM=1 saves all SSE", "language": "bash" }, { "code": "import json, os\nfrom pathlib import Path\n\nmaterial_path = Path(os.environ['AILOOT_TEXT_FILE'])\nif not material_path.is_file():\n raise SystemExit('Choose your actual UTF-8 document')\ntext = material_path.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('The document must contain text')\nstream = os.environ.get('AILOOT_STREAM', '0') == '1'\npayload = {'model': 'SenseNova-V6-Pro', 'messages': [{'role': 'user', 'content': 'Hello!'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting passages.\\n\\n' + text\npayload['stream'] = stream\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')\nrequest = Request('https://api.ailoot.ai/v1/chat/completions', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers={'Authorization': 'Bearer ' + api_key, 'Content-Type': 'application/json'}, 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-body.bin').write_bytes(error.read())\n Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n raise\nPath('result-body.bin').write_bytes(raw)\nimport json, os\nfrom pathlib import Path\n\nraw = Path('result-body.bin').read_bytes()\nif os.environ.get('AILOOT_STREAM', '0') == '1':\n Path('result.sse').write_bytes(raw)\n print(raw.decode('utf-8'))\nelse:\n Path('result.json').write_bytes(raw)\n result = json.loads(raw)\n print(json.dumps(result, ensure_ascii=False, indent=2))\n for choice in result.get('choices', []):\n print('Choice', choice.get('index'), json.dumps(choice, ensure_ascii=False))\n", "label": "Python · complete JSON or all SSE events", "language": "python" }, { "code": "import { readFileSync, writeFileSync } from 'node:fs';\n\nconst apiKey = process.env.AILOOT_API_KEY;\nif (!apiKey?.trim()) throw new Error('Set AILOOT_API_KEY');\nif (!process.env.AILOOT_TEXT_FILE) throw new Error('Choose your actual UTF-8 document');\nconst text = readFileSync(process.env.AILOOT_TEXT_FILE, 'utf8');\nif (!text.trim()) throw new Error('The document must contain text');\nconst stream = process.env.AILOOT_STREAM === '1';\nconst payload = {\"model\": \"SenseNova-V6-Pro\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]};\npayload.messages[0].content = 'Summarize this material and quote supporting passages.\\n\\n' + text;\npayload.stream = stream;\nconst response = await fetch('https://api.ailoot.ai/v1/chat/completions', { method: 'POST', headers: { 'Authorization': 'Bearer ' + apiKey, 'Content-Type': 'application/json' }, body: JSON.stringify(payload) });\nconst raw = Buffer.from(await response.arrayBuffer());\nwriteFileSync('result-body.bin', raw);\nwriteFileSync('response-headers.txt', [...response.headers].map(([key, value]) => key + ': ' + value).join('\\n'));\nif (!response.ok) throw new Error('HTTP ' + response.status + '; original response saved in result-body.bin');\nif (stream) {\n writeFileSync('result.sse', raw);\n process.stdout.write(raw);\n} else {\n writeFileSync('result.json', raw);\n const result = JSON.parse(raw.toString('utf8'));\n console.log(JSON.stringify(result, null, 2));\n for (const choice of result.choices ?? []) console.log('Choice', choice.index, JSON.stringify(choice));\n}\n", "label": "Node.js · complete JSON or all SSE events", "language": "javascript" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "chat", "hints": [ "Send your actual text with this exact model ID.", "Set AILOOT_STREAM=1 in an example to save the complete SSE result." ], "http": "POST", "in": 1.1, "input": [ "text" ], "label": "OpenAI Chat · SenseNova-V6-Pro", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "official_sources": [ { "title": "Chat Completions API", "url": "https://302ai-en.apifox.cn/207705102e0" } ], "out": 2.86, "output": [ "text" ], "path": "/v1/chat/completions", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "request_model_id": "SenseNova-V6-Pro", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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": "

•

SenseNova-V6-Pro

Kita /SenseNova-V6-Pro

Modelio ID

Pradžia

SenseNova V6 Pro – tai bendros paskirties „SenseTime“ vaizdų ir teksto pokalbio profilis, grąžinantis tekstą. Pateikite dokumentus, paveikslėlius ir klausimus paaiškinimui ar palyginimui, išlaikydami atsakymo ryšį su vaizdiniais ir rašytiniais įrodymais.

Leidžiamos įvestys: Tekstas
Rezultatai: json · sse

Apie modelį

Šis aprašas apima modelio galimybes. Pasirinktam metodui Ailoot prieinamos įvestys, išvestys ir parinktys nurodytos toliau.

SenseNova V6 Pro – tai bendras „SenseTime“ multimodalus profilis pokalbiams, jungiantiems rašytinius klausimus ir vaizdus. Gamintojo profilių lentelė aprašo vaizdų ir teksto įvestį su tekstine išvestimi. V6 šeima pabrėžia mišrios vaizdinės bei kalbinės informacijos supratimą, samprotavimą ir analizę. Pro lieka atskiras nuo lengvesnio Turbo profilio ir atskirai pavadinto Reasoner, kurio išvestis apima samprotavimo medžiagą kartu su galutiniu atsakymu.

Pateikite klausimą su aiškiais vaizdiniais įrodymais

Pasirinkite klausimą pagrindžiantį vaizdą ar pradinį tekstą ir pasirūpinkite svarbių detalių įskaitomumu. Dokumento užduotyje galima pateikti puslapį su diagrama ar lentele ir klausti, kurią sąlygą pagrindžia matomos reikšmės. Ekrano nuotraukos klausime galima įvardyti aptariamą valdiklį ar žinutę. Papildomą foną atskirkite nuo to, ką rodo pats paveikslėlis.

Paprašykite užduočiai tinkamo rezultato: paaiškinimo, palyginimo, išgauto matomų reikšmių rinkinio ar pateikta medžiaga pagrįsto juodraščio. Naudingas dokumentų palyginimas gali išsaugoti puslapio identifikatorių ir įrodymus prie kiekvieno pastebėjimo. Grąžintame tekste tikrinkite žymas, vienetus ir ryšius su šaltiniais, užuot rėmęsi įtikinama viso paveikslėlio interpretacija.

Samprotaukite pagal tekstą ir vaizdus

Gamintojo V6 pristatymas aprašo sulietą modelių seriją, o ne atskiras kalbos ir regos šakas. Jos paskirtis apima matematikos, programavimo ir dokumentų analizės užduotis, kurioms reikia suprasti susijusią informaciją. Nurodykite sąlygas, kurias atsakymas turi atitikti, ir atskirkite žinomas reikšmes nuo prielaidų. Pagrįstas atsakymas turi leisti jo išvadą įvertinti pagal tikrą pradinę medžiagą.

Kelių dokumentų klausime nurodykite, kuris šaltinis turi lemti nesutarimo sprendimą, ir išsaugokite svarbias ištraukas ar matomas sritis. Jei medžiaga nepilna, trūkstamą sąlygą laikykite atskirai nuo užpildyto lauko. Užtikrintas paaiškinimas savaime neįrodo, kad šaltinyje yra jam priskirta reikšmė.

Profilis ir platesnės šeimos darbo eigos

Pro lentelė nurodo tekstinį atsakymą pokalbiui pagal vaizdą ir tekstą. V6 šeimos pristatyme taip pat aptariama išplėstų vaizdo įrašų analizė ir atskiras Omni tikralaikės sąveikos profilis. Šios šeimos demonstracijos turi likti susietos su gamintojo darbo eigomis, o ne būti laikomos visa Pro užklausos laukų specifikacija. Vėlesni V6.5 ir V6.7 modeliai turi savo galimybes ir valdiklius.

Pro vaizdų bei teksto užduočiai išsaugokite pateiktą klausimą, vaizdus ir užbaigtą tekstinį atsakymą. Svarbius skaičius, vaizdinius ryšius, siūlomą kodą ar samprotavimą tikrinkite pagal juos pagrindžiančius įrodymus. Naudingas perdavimo rezultatas gali būti paaiškinimas ar struktūruotas palyginimas, kurio pastebėjimus galima atsekti iki pradinio puslapio, leidžiant konkrečiai tęsti darbą dėl vienos neišspręstos detalės.

Prieinama Ailoot · įvestys ir metodai

Ailoot Ultra · Anthropic pranešimai POST /v1/messages

Įvestis: text
Išvestis: json, sse
Išvesties formatas: JSON arba SSE

Laukas	Tipas	Reikalavimas	Reikšmės ir ribos	Numatyta
Laukas`model`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos SenseNova-V6-Pro	Numatyta—
Laukas`messages`	Tipas`message[]`	ReikalavimasPrivaloma	Reikšmės ir ribos	Numatyta—
Laukas`messages[].role`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos user, assistant	Numatyta—
Laukas`messages[].content`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos	Numatyta—
Laukas`max_tokens`	Tipas`integer`	ReikalavimasPrivaloma	Reikšmės ir ribos	Numatyta—
Laukas`stream`	Tipas`boolean`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatytafalse

Įvesties medžiagos deriniai

Tekstas · UTF-8 tekstas

messages[].content eilutė

Metodo parametrai ir gyvavimo ciklas

Parametras	Specifikacija
Parametras`content_type`	Specifikacijaapplication/json
Parametras`required`	Specifikacijamodel, messages, max_tokens
Parametras`optional_controls`	Specifikacijastream
Parametras`material_types`	Specifikacijatext
Parametras`text_file_material`	SpecifikacijaPerskaitykite tikrąjį UTF-8 dokumentą ir įterpkite jo tekstą į nurodytą input lauką arba pranešimo turinio eilutę.

Gyvavimo ciklas: synchronous_or_streamed

Planai

Tarifų informacija neprideda užklausos parinkčių. Palaikomi parametrai nurodyti prie pasirinkto metodo.

Spartusis režimas: Nenurodyta Pasirinkus spartųjį režimą
Flex režimas: Nenurodyta Pasirinkus flex režimą
Didžiausios samprotavimo pastangos: Nenurodyta Kai didžiausioms samprotavimo pastangoms taikomas numatytasis koregavimas (default)

Ailoot įkainiai

Kainos pagal konfigūraciją

Konfigūracija	Įkainių lentelė	Mokestis
KonfigūracijaBaziniai žetonų įkainiai	Įkainių lentelėBazinis įkainis	Mokestis Įvestis · Įvesties tokenai $0.0011 / 1K tokenų Išvestis · Išvesties tokenai $0.00286 / 1K tokenų Įvestis · Talpyklos skaitymas $0 / 1K tokenų Įvestis · Rašymas į talpyklą $0 / 1K tokenų Įvestis · Rašymas į talpyklą, 1 val — / 1K tokenų

Ailoot prieš užklausą rezervuoja numatomą sumą. Gavus rezultatą, galutinis mokestis nuskaitomas pagal išmatuotą naudojimą. Srautinio atsakymo atsiskaitymui naudojamas galutinis naudojimo įrašas. Kaip veikia rezervavimas ir atsiskaitymas →

Užklausų pavyzdžiai

Ailoot Ultra · Anthropic pranešimai

{\n  "model": "SenseNova-V6-Pro",\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': 'SenseNova-V6-Pro', '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': 'SenseNova-V6-Pro', '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

Gauti ir išsaugoti rezultatus

Ailoot Ultra · Anthropic pranešimai

JSON arba SSE

Išsaugoti visus baigtus rezultatus

Išsaugokite kiekvieną visą grąžintą atsakymą, failą ir turinio dalį.

Išsaugokite visus turinio blokus, mąstymo parašus ir tikruosius įrankių naudojimo ID. Surinkite visus SSE blokų prieaugius; pirmasis teksto blokas nėra visa išvestis.

Jei reikia patikrinti pradinį atsakymą

Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas.

Atsakymo laukai

Laukas	Tipas
Laukas`id`	Tipasstring
Laukas`model`	Tipasstring
Laukas`content[]`	Tipastext\|thinking\|tool_use\|other content block
Laukas`stop_reason`	Tipasstring\|null
Laukas`usage`	Tipasobject

Klaidos ir tolesni veiksmai

Atsakymas	Sąlyga	Kitas žingsnis
Atsakymas400 · `invalid_request_error`	SąlygaNetinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė	Kitas žingsnisPrieš naują kūrimo užklausą pataisykite nurodytus laukus.

Pseudonimai

Modelių pseudonimai

Ailoot Ultra SenseNova-V6-Pro, sensetime/sensenova-v6-pro

Metodų kelių pseudonimai

Naudokite aukščiau nurodytus metodų kelius.

Susiję ID iškvietimui

sensetime/sensenova-v6-pro, SenseNova-V6-Pro

", "method_identity": { "effective_request_model_id": "SenseNova-V6-Pro", "fmt": "messages", "http": "POST", "path": "/v1/messages", "request_model_id": "SenseNova-V6-Pro", "route_label": "Ultra" }, "method_key": "Ultra|messages|/v1/messages|SenseNova-V6-Pro", "ordinal": 1, "rawMethod": { "available": null, "cache_read": 0, "cache_write": 0, "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": "Netinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė", "http_status": 400, "recovery": "Prieš naują kūrimo užklausą pataisykite nurodytus laukus.", "type": "invalid_request_error" } ], "example_body": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "SenseNova-V6-Pro", "stream": false }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content eilutė", "required_material": "UTF-8 tekstas" } ], "operation_modes": [ "synchronous_json", "streamed_SSE" ], "outputs": { "all_results": "Išsaugokite visus turinio blokus, mąstymo parašus ir tikruosius įrankių naudojimo ID. Surinkite visus SSE blokų prieaugius; pirmasis teksto blokas nėra visa išvestis.", "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 arba SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "SenseNova-V6-Pro" ], "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": [ "SenseNova-V6-Pro" ], "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": "SenseNova-V6-Pro", "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": "Perskaitykite tikrąjį UTF-8 dokumentą ir įterpkite jo tekstą į nurodytą input lauką arba pranešimo turinio eilutę." }, "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": "Baziniai žetonų įkainiai", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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\": \"SenseNova-V6-Pro\",\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': 'SenseNova-V6-Pro', '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': 'SenseNova-V6-Pro', '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": null, "flex_multiplier": null, "fmt": "messages", "http": "POST", "in": 1.1, "input": [ "text" ], "label": "Anthropic pranešimai", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": 2.86, "output": [ "json", "sse" ], "path": "/v1/messages", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "request_model_id": "SenseNova-V6-Pro", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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": "

•

SenseNova-V6-Pro

Kita /sensetime/sensenova-v6-pro

Modelio ID

Pradžia

SenseNova V6 Pro – tai bendros paskirties „SenseTime“ vaizdų ir teksto pokalbio profilis, grąžinantis tekstą. Pateikite dokumentus, paveikslėlius ir klausimus paaiškinimui ar palyginimui, išlaikydami atsakymo ryšį su vaizdiniais ir rašytiniais įrodymais.

Leidžiamos įvestys: Tekstas
Rezultatai: Tekstas

Apie modelį

Šis aprašas apima modelio galimybes. Pasirinktam metodui Ailoot prieinamos įvestys, išvestys ir parinktys nurodytos toliau.

SenseNova V6 Pro – tai bendras „SenseTime“ multimodalus profilis pokalbiams, jungiantiems rašytinius klausimus ir vaizdus. Gamintojo profilių lentelė aprašo vaizdų ir teksto įvestį su tekstine išvestimi. V6 šeima pabrėžia mišrios vaizdinės bei kalbinės informacijos supratimą, samprotavimą ir analizę. Pro lieka atskiras nuo lengvesnio Turbo profilio ir atskirai pavadinto Reasoner, kurio išvestis apima samprotavimo medžiagą kartu su galutiniu atsakymu.

Pateikite klausimą su aiškiais vaizdiniais įrodymais

Pasirinkite klausimą pagrindžiantį vaizdą ar pradinį tekstą ir pasirūpinkite svarbių detalių įskaitomumu. Dokumento užduotyje galima pateikti puslapį su diagrama ar lentele ir klausti, kurią sąlygą pagrindžia matomos reikšmės. Ekrano nuotraukos klausime galima įvardyti aptariamą valdiklį ar žinutę. Papildomą foną atskirkite nuo to, ką rodo pats paveikslėlis.

Paprašykite užduočiai tinkamo rezultato: paaiškinimo, palyginimo, išgauto matomų reikšmių rinkinio ar pateikta medžiaga pagrįsto juodraščio. Naudingas dokumentų palyginimas gali išsaugoti puslapio identifikatorių ir įrodymus prie kiekvieno pastebėjimo. Grąžintame tekste tikrinkite žymas, vienetus ir ryšius su šaltiniais, užuot rėmęsi įtikinama viso paveikslėlio interpretacija.

Samprotaukite pagal tekstą ir vaizdus

Gamintojo V6 pristatymas aprašo sulietą modelių seriją, o ne atskiras kalbos ir regos šakas. Jos paskirtis apima matematikos, programavimo ir dokumentų analizės užduotis, kurioms reikia suprasti susijusią informaciją. Nurodykite sąlygas, kurias atsakymas turi atitikti, ir atskirkite žinomas reikšmes nuo prielaidų. Pagrįstas atsakymas turi leisti jo išvadą įvertinti pagal tikrą pradinę medžiagą.

Kelių dokumentų klausime nurodykite, kuris šaltinis turi lemti nesutarimo sprendimą, ir išsaugokite svarbias ištraukas ar matomas sritis. Jei medžiaga nepilna, trūkstamą sąlygą laikykite atskirai nuo užpildyto lauko. Užtikrintas paaiškinimas savaime neįrodo, kad šaltinyje yra jam priskirta reikšmė.

Profilis ir platesnės šeimos darbo eigos

Pro lentelė nurodo tekstinį atsakymą pokalbiui pagal vaizdą ir tekstą. V6 šeimos pristatyme taip pat aptariama išplėstų vaizdo įrašų analizė ir atskiras Omni tikralaikės sąveikos profilis. Šios šeimos demonstracijos turi likti susietos su gamintojo darbo eigomis, o ne būti laikomos visa Pro užklausos laukų specifikacija. Vėlesni V6.5 ir V6.7 modeliai turi savo galimybes ir valdiklius.

Pro vaizdų bei teksto užduočiai išsaugokite pateiktą klausimą, vaizdus ir užbaigtą tekstinį atsakymą. Svarbius skaičius, vaizdinius ryšius, siūlomą kodą ar samprotavimą tikrinkite pagal juos pagrindžiančius įrodymus. Naudingas perdavimo rezultatas gali būti paaiškinimas ar struktūruotas palyginimas, kurio pastebėjimus galima atsekti iki pradinio puslapio, leidžiant konkrečiai tęsti darbą dėl vienos neišspręstos detalės.

Prieinama Ailoot · įvestys ir metodai

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

Įvestis: text
Išvestis: text
Išvesties formatas: json arba SSE

Laukas	Tipas	Reikalavimas	Reikšmės ir ribos	Numatyta
Laukas`model`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos sensetime/sensenova-v6-pro	Numatyta—
Laukas`messages`	Tipas`message[]`	ReikalavimasPrivaloma	Reikšmės ir ribos Mažiausias elementų skaičius: 1	Numatyta—
Laukas`messages[].role`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos Pavyzdžiai: system, user, assistant, tool, function Sąlygos: Šie vaidmenys aiškiai išreikšti šaltinio kodo suderinamumo tipuose; tikslus vaidmenų rinkinys priklauso nuo konkretaus modelio. Priklauso nuo modelio	Numatyta—
Laukas`messages[].content`	Tipas`string\|content_part[]\|null`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatyta—
Laukas`messages[].tool_calls`	Tipas`tool_call[]`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatyta—
Laukas`messages[].tool_call_id`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Taikoma, kai: role=tool; naudokite tikrąjį grąžintą ID	Numatyta—
Laukas`messages[].name`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatyta—
Laukas`messages[].reasoning_content`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Taikoma, kai: Grąžinkite tikrąjį gautą samprotavimą ten, kur šis modelis jį naudoja	Numatyta—
Laukas`messages[].reasoning_details`	Tipas`object\|array`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`max_tokens`	Tipas`integer`	ReikalavimasNeprivaloma	Reikšmės ir ribos Mažiausia reikšmė: 1 Priklauso nuo modelio	Numatyta—
Laukas`max_completion_tokens`	Tipas`integer`	ReikalavimasNeprivaloma	Reikšmės ir ribos Mažiausia reikšmė: 1 Priklauso nuo modelio	Numatyta—
Laukas`stream`	Tipas`boolean`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatytafalse
Laukas`stream_options.include_usage`	Tipas`boolean`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`temperature`	Tipas`number`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`top_p`	Tipas`number`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`stop`	Tipas`string\|string[]`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`tools`	Tipas`function_tool[]`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`tools[].type`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos function Priklauso nuo modelio	Numatyta—
Laukas`tools[].function.name`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos Taikoma, kai: pateiktas funkcijos tipo įrankis	Numatyta—
Laukas`tools[].function.description`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatyta—
Laukas`tools[].function.parameters`	Tipas`JSON_schema`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatyta—
Laukas`tool_choice`	Tipas`string\|object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`parallel_tool_calls`	Tipas`boolean`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`response_format`	Tipas`object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`reasoning_effort`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`reasoning`	Tipas`object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`service_tier`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`instructions`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Suderinamumo laukas	Numatyta—
Laukas`functions`	Tipas`function[]`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`function_call`	Tipas`string\|object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`prompt_cache_options`	Tipas`object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Priklauso nuo modelio	Numatyta—
Laukas`modalities`	Tipas`string[]`	ReikalavimasNeprivaloma	Reikšmės ir ribos text	Numatyta—
Laukas`provider`	Tipas`object`	ReikalavimasNeprivaloma	Reikšmės ir ribos Sąlygos: provider.options šiame Ultra teksto maršrute atmetamas	Numatyta—
Laukas`cache_control.ttl`	Tipas`string`	ReikalavimasNeprivaloma	Reikšmės ir ribos Sąlygos: 1h atmetamas tikrosiose užklausų podėlio vietose	Numatyta—

Įvesties medžiagos deriniai

Tekstas · UTF8 tekstas

messages[].content

Metodo parametrai ir gyvavimo ciklas

Parametras	Specifikacija
Parametras`content_type`	Specifikacijaapplication/json
Parametras`required`	Specifikacijamodel, messages
Parametras`material_types`	Specifikacijatext
Parametras`messages`	Specifikacijapranešimų masyvas su role/content struktūra
Parametras`file_material`	Specifikacijatikrasis UTF-8 dokumentas įterptas kaip pažodinis tekstas; failo ID nenumanomas
Parametras`optional_controls`	Specifikacijastream, temperature, top_p, stop, max_tokens, max_completion_tokens, reasoning, response_format, tools, tool_choice
Parametras`control_scope`	Specifikacijapriklauso nuo modelio; naudotojo funkcijų įrankiai skiriasi nuo priglobtų įrankių
Parametras`output_modalities`	Specifikacijatext
Parametras`hosted_operations`	Specifikacijafalse
Parametras`multimodal_input_binding`	Specifikacijanull

Gyvavimo ciklas: synchronous_or_streamed

Siųskite tikslų modelio ID kartu su messages.

Konteksto ilgis nėra išvesties limitas.

Teksto failas gali pateikti pažodinį tekstą; vaizdų / garso / failų objektų įvestims reikia tikslaus susiejimo.

Planai

Tarifų informacija neprideda užklausos parinkčių. Palaikomi parametrai nurodyti prie pasirinkto metodo.

Spartusis režimas: Nenurodyta Pasirinkus spartųjį režimą
Flex režimas: Nenurodyta Pasirinkus flex režimą
Didžiausios samprotavimo pastangos: Nenurodyta Kai didžiausioms samprotavimo pastangoms taikomas numatytasis koregavimas (default)

Ailoot įkainiai

Kainos pagal konfigūraciją

Konfigūracija	Įkainių lentelė	Mokestis
KonfigūracijaBaziniai žetonų įkainiai	Įkainių lentelėBazinis įkainis	Mokestis Įvestis · Įvesties tokenai $0.0011 / 1K tokenų Išvestis · Išvesties tokenai $0.00286 / 1K tokenų Įvestis · Talpyklos skaitymas $0 / 1K tokenų Įvestis · Rašymas į talpyklą $0 / 1K tokenų Įvestis · Rašymas į talpyklą, 1 val — / 1K tokenų

Ailoot prieš užklausą rezervuoja numatomą sumą. Gavus rezultatą, galutinis mokestis nuskaitomas pagal išmatuotą naudojimą. Srautinio atsakymo atsiskaitymui naudojamas galutinis naudojimo įrašas. Kaip veikia rezervavimas ir atsiskaitymas →

Užklausų pavyzdžiai

Ailoot Ultra · OpenAI pokalbis

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": "sensetime/sensenova-v6-pro", "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='sensetime/sensenova-v6-pro',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='sensetime/sensenova-v6-pro',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

Gauti ir išsaugoti rezultatus

Ailoot Ultra · OpenAI pokalbis

json arba SSE

Išsaugoti visus baigtus rezultatus

Išsaugokite kiekvieną visą grąžintą atsakymą, failą ir turinio dalį.

Išsaugokite kiekvieną variantą ir jo turinį / įrankių iškvietimus / samprotavimą. SSE prieaugius surinkite pagal varianto / įrankio indeksą; išsaugokite galutinę užbaigimo priežastį ir naudojimo duomenis.

Jei reikia patikrinti pradinį atsakymą

Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas.

Atsakymo laukai

Laukas	Tipas
Laukas`choices[].index`	Tipasinteger
Laukas`choices[].message.content`	Tipasstring\|null
Laukas`choices[].message.tool_calls`	Tipastool_call[]
Laukas`choices[].message.reasoning_content`	Tipasstring
Laukas`choices[].message.reasoning_details`	Tipasobject\|array
Laukas`choices[].finish_reason`	Tipasstring\|null
Laukas`usage`	Tipasobject

Klaidos ir tolesni veiksmai

Atsakymas	Sąlyga	Kitas žingsnis
Atsakymas400 · `invalid_request_error`	SąlygaNetinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė	Kitas žingsnisPrieš naują kūrimo užklausą pataisykite nurodytus laukus.

Pseudonimai

Modelių pseudonimai

Ailoot Ultra SenseNova-V6-Pro, sensetime/sensenova-v6-pro

Metodų kelių pseudonimai

Naudokite aukščiau nurodytus metodų kelius.

Susiję ID iškvietimui

sensetime/sensenova-v6-pro, SenseNova-V6-Pro

", "method_identity": { "effective_request_model_id": "sensetime/sensenova-v6-pro", "fmt": "chat", "http": "POST", "path": "/v1/chat/completions", "request_model_id": "sensetime/sensenova-v6-pro", "route_label": "Ultra" }, "method_key": "Ultra|chat|/v1/chat/completions|sensetime%2Fsensenova-v6-pro", "ordinal": 2, "rawMethod": { "available": null, "cache_read": 0, "cache_write": 0, "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": "Netinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė", "http_status": 400, "recovery": "Prieš naują kūrimo užklausą pataisykite nurodytus laukus.", "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": "Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "UTF8 tekstas" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "Išsaugokite kiekvieną variantą ir jo turinį / įrankių iškvietimus / samprotavimą. SSE prieaugius surinkite pagal varianto / įrankio indeksą; išsaugokite galutinę užbaigimo priežastį ir naudojimo duomenis.", "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 arba SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "sensetime/sensenova-v6-pro" ], "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": "Šie vaidmenys aiškiai išreikšti šaltinio kodo suderinamumo tipuose; tikslus vaidmenų rinkinys priklauso nuo konkretaus modelio.", "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; naudokite tikrąjį grąžintą ID" }, { "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": "Grąžinkite tikrąjį gautą samprotavimą ten, kur šis modelis jį naudoja" }, { "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": "pateiktas funkcijos tipo įrankis" }, { "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": "provider.options šiame Ultra teksto maršrute atmetamas", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "provider", "required": false, "type": "object" }, { "availability": "source_interface", "conditions": "1h atmetamas tikrosiose užklausų podėlio vietose", "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": [ "Siųskite tikslų modelio ID kartu su messages.", "Konteksto ilgis nėra išvesties limitas.", "Teksto failas gali pateikti pažodinį tekstą; vaizdų / garso / failų objektų įvestims reikia tikslaus susiejimo." ], "input": { "content_type": "application/json", "control_scope": "priklauso nuo modelio; naudotojo funkcijų įrankiai skiriasi nuo priglobtų įrankių", "file_material": "tikrasis UTF-8 dokumentas įterptas kaip pažodinis tekstas; failo ID nenumanomas", "hosted_operations": false, "material_types": [ "text" ], "messages": "pranešimų masyvas su role/content struktūra", "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": "Baziniai žetonų įkainiai", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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\": \"sensetime/sensenova-v6-pro\", \"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='sensetime/sensenova-v6-pro',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='sensetime/sensenova-v6-pro',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": null, "flex_multiplier": null, "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": 1.1, "input": [ "text" ], "label": "OpenAI pokalbis", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": 2.86, "output": [ "text" ], "path": "/v1/chat/completions", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "request_model_id": "sensetime/sensenova-v6-pro", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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": "

•

SenseNova-V6-Pro

Kita /sensetime/sensenova-v6-pro

Modelio ID

Pradžia

SenseNova V6 Pro – tai bendros paskirties „SenseTime“ vaizdų ir teksto pokalbio profilis, grąžinantis tekstą. Pateikite dokumentus, paveikslėlius ir klausimus paaiškinimui ar palyginimui, išlaikydami atsakymo ryšį su vaizdiniais ir rašytiniais įrodymais.

Leidžiamos įvestys: Tekstas
Rezultatai: json · sse

Apie modelį

Šis aprašas apima modelio galimybes. Pasirinktam metodui Ailoot prieinamos įvestys, išvestys ir parinktys nurodytos toliau.

SenseNova V6 Pro – tai bendras „SenseTime“ multimodalus profilis pokalbiams, jungiantiems rašytinius klausimus ir vaizdus. Gamintojo profilių lentelė aprašo vaizdų ir teksto įvestį su tekstine išvestimi. V6 šeima pabrėžia mišrios vaizdinės bei kalbinės informacijos supratimą, samprotavimą ir analizę. Pro lieka atskiras nuo lengvesnio Turbo profilio ir atskirai pavadinto Reasoner, kurio išvestis apima samprotavimo medžiagą kartu su galutiniu atsakymu.

Pateikite klausimą su aiškiais vaizdiniais įrodymais

Pasirinkite klausimą pagrindžiantį vaizdą ar pradinį tekstą ir pasirūpinkite svarbių detalių įskaitomumu. Dokumento užduotyje galima pateikti puslapį su diagrama ar lentele ir klausti, kurią sąlygą pagrindžia matomos reikšmės. Ekrano nuotraukos klausime galima įvardyti aptariamą valdiklį ar žinutę. Papildomą foną atskirkite nuo to, ką rodo pats paveikslėlis.

Paprašykite užduočiai tinkamo rezultato: paaiškinimo, palyginimo, išgauto matomų reikšmių rinkinio ar pateikta medžiaga pagrįsto juodraščio. Naudingas dokumentų palyginimas gali išsaugoti puslapio identifikatorių ir įrodymus prie kiekvieno pastebėjimo. Grąžintame tekste tikrinkite žymas, vienetus ir ryšius su šaltiniais, užuot rėmęsi įtikinama viso paveikslėlio interpretacija.

Samprotaukite pagal tekstą ir vaizdus

Gamintojo V6 pristatymas aprašo sulietą modelių seriją, o ne atskiras kalbos ir regos šakas. Jos paskirtis apima matematikos, programavimo ir dokumentų analizės užduotis, kurioms reikia suprasti susijusią informaciją. Nurodykite sąlygas, kurias atsakymas turi atitikti, ir atskirkite žinomas reikšmes nuo prielaidų. Pagrįstas atsakymas turi leisti jo išvadą įvertinti pagal tikrą pradinę medžiagą.

Kelių dokumentų klausime nurodykite, kuris šaltinis turi lemti nesutarimo sprendimą, ir išsaugokite svarbias ištraukas ar matomas sritis. Jei medžiaga nepilna, trūkstamą sąlygą laikykite atskirai nuo užpildyto lauko. Užtikrintas paaiškinimas savaime neįrodo, kad šaltinyje yra jam priskirta reikšmė.

Profilis ir platesnės šeimos darbo eigos

Pro lentelė nurodo tekstinį atsakymą pokalbiui pagal vaizdą ir tekstą. V6 šeimos pristatyme taip pat aptariama išplėstų vaizdo įrašų analizė ir atskiras Omni tikralaikės sąveikos profilis. Šios šeimos demonstracijos turi likti susietos su gamintojo darbo eigomis, o ne būti laikomos visa Pro užklausos laukų specifikacija. Vėlesni V6.5 ir V6.7 modeliai turi savo galimybes ir valdiklius.

Pro vaizdų bei teksto užduočiai išsaugokite pateiktą klausimą, vaizdus ir užbaigtą tekstinį atsakymą. Svarbius skaičius, vaizdinius ryšius, siūlomą kodą ar samprotavimą tikrinkite pagal juos pagrindžiančius įrodymus. Naudingas perdavimo rezultatas gali būti paaiškinimas ar struktūruotas palyginimas, kurio pastebėjimus galima atsekti iki pradinio puslapio, leidžiant konkrečiai tęsti darbą dėl vienos neišspręstos detalės.

Prieinama Ailoot · įvestys ir metodai

Ailoot Ultra · Anthropic pranešimai POST /v1/messages

Įvestis: text
Išvestis: json, sse
Išvesties formatas: JSON arba SSE

Laukas	Tipas	Reikalavimas	Reikšmės ir ribos	Numatyta
Laukas`model`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos sensetime/sensenova-v6-pro	Numatyta—
Laukas`messages`	Tipas`message[]`	ReikalavimasPrivaloma	Reikšmės ir ribos	Numatyta—
Laukas`messages[].role`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos user, assistant	Numatyta—
Laukas`messages[].content`	Tipas`string`	ReikalavimasPrivaloma	Reikšmės ir ribos	Numatyta—
Laukas`max_tokens`	Tipas`integer`	ReikalavimasPrivaloma	Reikšmės ir ribos	Numatyta—
Laukas`stream`	Tipas`boolean`	ReikalavimasNeprivaloma	Reikšmės ir ribos	Numatytafalse

Įvesties medžiagos deriniai

Tekstas · UTF-8 tekstas

messages[].content eilutė

Metodo parametrai ir gyvavimo ciklas

Parametras	Specifikacija
Parametras`content_type`	Specifikacijaapplication/json
Parametras`required`	Specifikacijamodel, messages, max_tokens
Parametras`optional_controls`	Specifikacijastream
Parametras`material_types`	Specifikacijatext
Parametras`text_file_material`	SpecifikacijaPerskaitykite tikrąjį UTF-8 dokumentą ir įterpkite jo tekstą į nurodytą input lauką arba pranešimo turinio eilutę.

Gyvavimo ciklas: synchronous_or_streamed

Planai

Tarifų informacija neprideda užklausos parinkčių. Palaikomi parametrai nurodyti prie pasirinkto metodo.

Spartusis režimas: Nenurodyta Pasirinkus spartųjį režimą
Flex režimas: Nenurodyta Pasirinkus flex režimą
Didžiausios samprotavimo pastangos: Nenurodyta Kai didžiausioms samprotavimo pastangoms taikomas numatytasis koregavimas (default)

Ailoot įkainiai

Kainos pagal konfigūraciją

Konfigūracija	Įkainių lentelė	Mokestis
KonfigūracijaBaziniai žetonų įkainiai	Įkainių lentelėBazinis įkainis	Mokestis Įvestis · Įvesties tokenai $0.0011 / 1K tokenų Išvestis · Išvesties tokenai $0.00286 / 1K tokenų Įvestis · Talpyklos skaitymas $0 / 1K tokenų Įvestis · Rašymas į talpyklą $0 / 1K tokenų Įvestis · Rašymas į talpyklą, 1 val — / 1K tokenų

Ailoot prieš užklausą rezervuoja numatomą sumą. Gavus rezultatą, galutinis mokestis nuskaitomas pagal išmatuotą naudojimą. Srautinio atsakymo atsiskaitymui naudojamas galutinis naudojimo įrašas. Kaip veikia rezervavimas ir atsiskaitymas →

Užklausų pavyzdžiai

Ailoot Ultra · Anthropic pranešimai

{\n  "model": "sensetime/sensenova-v6-pro",\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': 'sensetime/sensenova-v6-pro', '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': 'sensetime/sensenova-v6-pro', '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

Gauti ir išsaugoti rezultatus

Ailoot Ultra · Anthropic pranešimai

JSON arba SSE

Išsaugoti visus baigtus rezultatus

Išsaugokite kiekvieną visą grąžintą atsakymą, failą ir turinio dalį.

Išsaugokite visus turinio blokus, mąstymo parašus ir tikruosius įrankių naudojimo ID. Surinkite visus SSE blokų prieaugius; pirmasis teksto blokas nėra visa išvestis.

Jei reikia patikrinti pradinį atsakymą

Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas.

Atsakymo laukai

Laukas	Tipas
Laukas`id`	Tipasstring
Laukas`model`	Tipasstring
Laukas`content[]`	Tipastext\|thinking\|tool_use\|other content block
Laukas`stop_reason`	Tipasstring\|null
Laukas`usage`	Tipasobject

Klaidos ir tolesni veiksmai

Atsakymas	Sąlyga	Kitas žingsnis
Atsakymas400 · `invalid_request_error`	SąlygaNetinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė	Kitas žingsnisPrieš naują kūrimo užklausą pataisykite nurodytus laukus.

Pseudonimai

Modelių pseudonimai

Ailoot Ultra SenseNova-V6-Pro, sensetime/sensenova-v6-pro

Metodų kelių pseudonimai

Naudokite aukščiau nurodytus metodų kelius.

Susiję ID iškvietimui

sensetime/sensenova-v6-pro, SenseNova-V6-Pro

", "method_identity": { "effective_request_model_id": "sensetime/sensenova-v6-pro", "fmt": "messages", "http": "POST", "path": "/v1/messages", "request_model_id": "sensetime/sensenova-v6-pro", "route_label": "Ultra" }, "method_key": "Ultra|messages|/v1/messages|sensetime%2Fsensenova-v6-pro", "ordinal": 3, "rawMethod": { "available": null, "cache_read": 0, "cache_write": 0, "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": "Netinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė", "http_status": 400, "recovery": "Prieš naują kūrimo užklausą pataisykite nurodytus laukus.", "type": "invalid_request_error" } ], "example_body": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "sensetime/sensenova-v6-pro", "stream": false }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content eilutė", "required_material": "UTF-8 tekstas" } ], "operation_modes": [ "synchronous_json", "streamed_SSE" ], "outputs": { "all_results": "Išsaugokite visus turinio blokus, mąstymo parašus ir tikruosius įrankių naudojimo ID. Surinkite visus SSE blokų prieaugius; pirmasis teksto blokas nėra visa išvestis.", "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 arba SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "sensetime/sensenova-v6-pro" ], "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": [ "sensetime/sensenova-v6-pro" ], "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": "sensetime/sensenova-v6-pro", "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": "Perskaitykite tikrąjį UTF-8 dokumentą ir įterpkite jo tekstą į nurodytą input lauką arba pranešimo turinio eilutę." }, "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": "Baziniai žetonų įkainiai", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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\": \"sensetime/sensenova-v6-pro\",\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': 'sensetime/sensenova-v6-pro', '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': 'sensetime/sensenova-v6-pro', '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": null, "flex_multiplier": null, "fmt": "messages", "http": "POST", "in": 1.1, "input": [ "text" ], "label": "Anthropic pranešimai", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": 2.86, "output": [ "json", "sse" ], "path": "/v1/messages", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "request_model_id": "sensetime/sensenova-v6-pro", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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": "sensetime/sensenova-v6-pro", "nativeProvenance": { "input_facts_canonical_sha256": "9631e45644c0621d8a1c9639166a9d37a585ed0af68b2774fa870715933245e3", "input_html_sha256": "c4932be55ea2b26c63496f6f8eed7b7e3af5624c7722b69aa5b459eac710b293", "private_audit_sha256": "2d603b4c1d3b208f75e05f73995e60fe36365ccc743d4ce26f0fcf7c43bf2dc5", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/lt/sensetime-sensenova-v6-pro/", "description": "SenseNova V6 Pro – tai bendros paskirties „SenseTime“ vaizdų ir teksto pokalbio profilis, grąžinantis tekstą. Pateikite dokumentus, paveikslėlius ir klausimus paaiškinimui ar palyginimui, išlaikydami atsakymo ryšį su vaizdiniais ir rašytiniais įrodymais.", "locale": "lt", "md_url": "https://ailoot.ai/models/lt/sensetime-sensenova-v6-pro/index.md", "title": "SenseNova-V6-Pro — Ailoot", "url": "https://ailoot.ai/models/lt/sensetime-sensenova-v6-pro/" }, "practicalHtml": "

Praktinė užduotis

Techninis pavyzdys anglų kalba

Explain a supplied chart transcription\n\nUse this text transcription of report page P7: 'Target line: 50 units. North: 48. South: 53. East: 50.' State which regions meet a target defined as at least 50 units. Return each region's value, its relation to the target and the page label. Distinguish meeting the target from strictly exceeding it.

Laukiamas rezultatas

A region-by-region source-linked comparison with the inclusive target condition applied.

Rezultato patikra

East must be treated as meeting, but not exceeding, the 50-unit target.

", "practicalText": "Praktinė užduotis Techninis pavyzdys anglų kalba Explain a supplied chart transcription Use this text transcription of report page P7: 'Target line: 50 units. North: 48. South: 53. East: 50.' State which regions meet a target defined as at least 50 units. Return each region's value, its relation to the target and the page label. Distinguish meeting the target from strictly exceeding it. Laukiamas rezultatas A region-by-region source-linked comparison with the inclusive target condition applied. Rezultato patikra East must be treated as meeting, but not exceeding, the 50-unit target.", "rawModel": { "about": "SenseNova V6 Pro – tai bendras „SenseTime“ multimodalus profilis pokalbiams, jungiantiems rašytinius klausimus ir vaizdus. Gamintojo profilių lentelė aprašo vaizdų ir teksto įvestį su tekstine išvestimi. V6 šeima pabrėžia mišrios vaizdinės bei kalbinės informacijos supratimą, samprotavimą ir analizę. Pro lieka atskiras nuo lengvesnio Turbo profilio ir atskirai pavadinto Reasoner, kurio išvestis apima samprotavimo medžiagą kartu su galutiniu atsakymu.\n\n### Pateikite klausimą su aiškiais vaizdiniais įrodymais\n\nPasirinkite klausimą pagrindžiantį vaizdą ar pradinį tekstą ir pasirūpinkite svarbių detalių įskaitomumu. Dokumento užduotyje galima pateikti puslapį su diagrama ar lentele ir klausti, kurią sąlygą pagrindžia matomos reikšmės. Ekrano nuotraukos klausime galima įvardyti aptariamą valdiklį ar žinutę. Papildomą foną atskirkite nuo to, ką rodo pats paveikslėlis.\n\nPaprašykite užduočiai tinkamo rezultato: paaiškinimo, palyginimo, išgauto matomų reikšmių rinkinio ar pateikta medžiaga pagrįsto juodraščio. Naudingas dokumentų palyginimas gali išsaugoti puslapio identifikatorių ir įrodymus prie kiekvieno pastebėjimo. Grąžintame tekste tikrinkite žymas, vienetus ir ryšius su šaltiniais, užuot rėmęsi įtikinama viso paveikslėlio interpretacija.\n\n### Samprotaukite pagal tekstą ir vaizdus\n\nGamintojo V6 pristatymas aprašo sulietą modelių seriją, o ne atskiras kalbos ir regos šakas. Jos paskirtis apima matematikos, programavimo ir dokumentų analizės užduotis, kurioms reikia suprasti susijusią informaciją. Nurodykite sąlygas, kurias atsakymas turi atitikti, ir atskirkite žinomas reikšmes nuo prielaidų. Pagrįstas atsakymas turi leisti jo išvadą įvertinti pagal tikrą pradinę medžiagą.\n\nKelių dokumentų klausime nurodykite, kuris šaltinis turi lemti nesutarimo sprendimą, ir išsaugokite svarbias ištraukas ar matomas sritis. Jei medžiaga nepilna, trūkstamą sąlygą laikykite atskirai nuo užpildyto lauko. Užtikrintas paaiškinimas savaime neįrodo, kad šaltinyje yra jam priskirta reikšmė.\n\n### Profilis ir platesnės šeimos darbo eigos\n\nPro lentelė nurodo tekstinį atsakymą pokalbiui pagal vaizdą ir tekstą. V6 šeimos pristatyme taip pat aptariama išplėstų vaizdo įrašų analizė ir atskiras Omni tikralaikės sąveikos profilis. Šios šeimos demonstracijos turi likti susietos su gamintojo darbo eigomis, o ne būti laikomos visa Pro užklausos laukų specifikacija. Vėlesni V6.5 ir V6.7 modeliai turi savo galimybes ir valdiklius.\n\nPro vaizdų bei teksto užduočiai išsaugokite pateiktą klausimą, vaizdus ir užbaigtą tekstinį atsakymą. Svarbius skaičius, vaizdinius ryšius, siūlomą kodą ar samprotavimą tikrinkite pagal juos pagrindžiančius įrodymus. Naudingas perdavimo rezultatas gali būti paaiškinimas ar struktūruotas palyginimas, kurio pastebėjimus galima atsekti iki pradinio puslapio, leidžiant konkrečiai tęsti darbą dėl vienos neišspręstos detalės.", "alias_of": null, "aliases": [ "SenseNova-V6-Pro" ], "author": "Other", "available": null, "canonical_model": "sensetime/sensenova-v6-pro", "capabilities": { "context_length": 32000, "manufacturer_input": [], "manufacturer_output": [] }, "card_routes": [ { "label": "Ultra", "rates": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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": "Visa konfigūracijos kainodara pateikta išsamioje informacijoje." }, { "label": "Ultra", "rates": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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": "Visa konfigūracijos kainodara pateikta išsamioje informacijoje." } ], "ctx": null, "entity_type": "model", "formats": [ "chat", "messages" ], "id": "sensetime/sensenova-v6-pro", "input": [ "text" ], "kind": "text", "max_out": null, "methods": [ { "available": null, "cache_read": 0, "cache_write": 0, "cache_write_1h": null, "contract": { "data": { "all_results": "Save every choices[] entry, content, reasoning, tool call and usage field. For streaming, save every SSE event and delta through [DONE].", "authentication": { "api_key_source": "AILOOT_API_KEY", "header": "Authorization: Bearer" }, "errors": [ { "code": null, "condition": "Netinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė", "http_status": 400, "recovery": "Prieš naują kūrimo užklausą pataisykite nurodytus laukus.", "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": "Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "UTF8 tekstas" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "Išsaugokite kiekvieną variantą ir jo turinį / įrankių iškvietimus / samprotavimą. SSE prieaugius surinkite pagal varianto / įrankio indeksą; išsaugokite galutinę užbaigimo priežastį ir naudojimo duomenis.", "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 arba SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "SenseNova-V6-Pro" ], "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": "Palaikomų vaidmenų rinkinys priklauso nuo pasirinkto modelio.", "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; naudokite tikrąjį grąžintą ID" }, { "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": "Grąžinkite tikrąjį gautą samprotavimą ten, kur šis modelis jį naudoja" }, { "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": "pateiktas funkcijos tipo įrankis" }, { "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": "provider.options šiame Ultra teksto maršrute atmetamas", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "provider", "required": false, "type": "object" }, { "availability": "source_interface", "conditions": "1h atmetamas tikrosiose užklausų podėlio vietose", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "cache_control.ttl", "required": false, "type": "string" } ], "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": [ "Siųskite tikslų modelio ID kartu su messages.", "Konteksto ilgis nėra išvesties limitas.", "Teksto failas gali pateikti pažodinį tekstą; vaizdų / garso / failų objektų įvestims reikia tikslaus susiejimo." ], "input": { "content_type": "application/json", "control_scope": "priklauso nuo modelio; naudotojo funkcijų įrankiai skiriasi nuo priglobtų įrankių", "file_material": "Nuskaitykite savo tikrą UTF-8 dokumentą ir įterpkite jo tekstą į messages[].content.", "hosted_operations": false, "material_types": [ "text" ], "messages": "pranešimų masyvas su role/content struktūra", "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": [], "official_sources": [ { "title": "Chat Completions API", "url": "https://302ai-en.apifox.cn/207705102e0" } ], "operation_modes": [ "text_chat" ], "output": { "all_results": "Save every choices[] entry, content, reasoning, tool call and usage field. For streaming, save every SSE event and delta through [DONE].", "content": "choices[].message.content or stream delta", "family": "text", "format": "json or supported SSE", "tool_calls": "retain actual returned function calls" }, "schema": { "request": { "properties": { "frequency_penalty": { "description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)", "type": "number" }, "logit_bias": { "description": "Modify the likelihood of specific tokens appearing in the completion. This can be done by providing a JSON object that maps tokens (identified by their token IDs in the tokenizer) to a bias value ranging from -100 to 100. Mathematically, this bias is added to the logits generated by the model before sampling. The exact effect varies depending on the model, but values between -1 and 1 will slightly decrease or increase the likelihood of selection, while values like -100 or 100 will either ban or exclusively select the relevant token.", "type": "null" }, "max_tokens": { "description": "The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length.", "type": "integer" }, "messages": { "description": "Generate messages in [chat format](https://platform.openai.com/docs/guides/chat/introduction) for chat completions.", "items": { "properties": { "content": { "type": "string" }, "role": { "type": "string" } }, "type": "object", "x-apifox-orders": [ "role", "content" ] }, "type": "array" }, "model": { "description": "The ID of the model to be used. For detailed information on which models are applicable to the chat API, please view [Model endpoint compatibility](https://platform.openai.com/docs/models/model-endpoint-compatibility)", "enum": [ "SenseNova-V6-Pro" ], "type": "string" }, "n": { "description": "How many chat completion choices to generate for each input message. Note that you will be charged based on the number of generated tokens across all of the choices. Keep n as 1 to minimize costs.", "type": "integer" }, "presence_penalty": { "description": "Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics. [See more information about frequency and presence penalties.](https://platform.openai.com/docs/api-reference/parameter-details)", "type": "number" }, "stop": { "description": "Up to 4 sequences where the API will stop generating further tokens.", "type": "string" }, "stream": { "description": "If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format) as they become available, with the stream terminated by `data: [DONE]` message. For [Example Code.](https://github.com/openai/openai-cookbook/blob/main/examples/How_to_stream_completions.ipynb)，Please view OpenAI Cookbook.", "type": "boolean" }, "temperature": { "description": "What sampling temperature to use, ranging from 0 to 2. Higher values, such as 0.8, will make the output more random, while lower values, like 0.2, will make it more focused and deterministic. We generally recommend adjusting either this or `top_p`, but not both simultaneously.", "type": "integer" }, "top_p": { "description": "An alternative to temperature sampling is nucleus sampling, where the model considers tokens within the top_p probability mass. For instance, top_p = 0.1 means only tokens within the top 10% probability mass are considered. We recommend adjusting either this or `temperature`, but not both simultaneously.", "type": "integer" }, "user": { "description": "A unique identifier representing your end users, which helps OpenAI monitor and detect abuse. [View more](https://platform.openai.com/docs/guides/safety-best-practices/end-user-ids)", "type": "string" } }, "required": [ "model", "messages" ], "type": "object", "x-apifox-orders": [ "model", "messages", "temperature", "top_p", "n", "stream", "stop", "max_tokens", "presence_penalty", "frequency_penalty", "logit_bias", "user" ] } } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Baziniai žetonų įkainiai", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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\": \"SenseNova-V6-Pro\",\n \"messages\": [\n {\n \"role\": \"user\",\n \"content\": \"Hello!\"\n }\n ]\n}", "label": "Complete minimal Chat body", "language": "json" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 source document}\"\nexport AILOOT_TEXT_FILE AILOOT_STREAM\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nmaterial_path = Path(os.environ['AILOOT_TEXT_FILE'])\nif not material_path.is_file():\n raise SystemExit('Choose your actual UTF-8 document')\ntext = material_path.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('The document must contain text')\nstream = os.environ.get('AILOOT_STREAM', '0') == '1'\npayload = {'model': 'SenseNova-V6-Pro', 'messages': [{'role': 'user', 'content': 'Hello!'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting passages.\\n\\n' + text\npayload['stream'] = stream\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/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-body.bin\npython3 - <<'PY_RESULT'\nimport json, os\nfrom pathlib import Path\n\nraw = Path('result-body.bin').read_bytes()\nif os.environ.get('AILOOT_STREAM', '0') == '1':\n Path('result.sse').write_bytes(raw)\n print(raw.decode('utf-8'))\nelse:\n Path('result.json').write_bytes(raw)\n result = json.loads(raw)\n print(json.dumps(result, ensure_ascii=False, indent=2))\n for choice in result.get('choices', []):\n print('Choice', choice.get('index'), json.dumps(choice, ensure_ascii=False))\nPY_RESULT\n", "label": "curl · your UTF-8 document; AILOOT_STREAM=1 saves all SSE", "language": "bash" }, { "code": "import json, os\nfrom pathlib import Path\n\nmaterial_path = Path(os.environ['AILOOT_TEXT_FILE'])\nif not material_path.is_file():\n raise SystemExit('Choose your actual UTF-8 document')\ntext = material_path.read_text(encoding='utf-8')\nif not text.strip():\n raise SystemExit('The document must contain text')\nstream = os.environ.get('AILOOT_STREAM', '0') == '1'\npayload = {'model': 'SenseNova-V6-Pro', 'messages': [{'role': 'user', 'content': 'Hello!'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting passages.\\n\\n' + text\npayload['stream'] = stream\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')\nrequest = Request('https://api.ailoot.ai/v1/chat/completions', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers={'Authorization': 'Bearer ' + api_key, 'Content-Type': 'application/json'}, 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-body.bin').write_bytes(error.read())\n Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n raise\nPath('result-body.bin').write_bytes(raw)\nimport json, os\nfrom pathlib import Path\n\nraw = Path('result-body.bin').read_bytes()\nif os.environ.get('AILOOT_STREAM', '0') == '1':\n Path('result.sse').write_bytes(raw)\n print(raw.decode('utf-8'))\nelse:\n Path('result.json').write_bytes(raw)\n result = json.loads(raw)\n print(json.dumps(result, ensure_ascii=False, indent=2))\n for choice in result.get('choices', []):\n print('Choice', choice.get('index'), json.dumps(choice, ensure_ascii=False))\n", "label": "Python · complete JSON or all SSE events", "language": "python" }, { "code": "import { readFileSync, writeFileSync } from 'node:fs';\n\nconst apiKey = process.env.AILOOT_API_KEY;\nif (!apiKey?.trim()) throw new Error('Set AILOOT_API_KEY');\nif (!process.env.AILOOT_TEXT_FILE) throw new Error('Choose your actual UTF-8 document');\nconst text = readFileSync(process.env.AILOOT_TEXT_FILE, 'utf8');\nif (!text.trim()) throw new Error('The document must contain text');\nconst stream = process.env.AILOOT_STREAM === '1';\nconst payload = {\"model\": \"SenseNova-V6-Pro\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]};\npayload.messages[0].content = 'Summarize this material and quote supporting passages.\\n\\n' + text;\npayload.stream = stream;\nconst response = await fetch('https://api.ailoot.ai/v1/chat/completions', { method: 'POST', headers: { 'Authorization': 'Bearer ' + apiKey, 'Content-Type': 'application/json' }, body: JSON.stringify(payload) });\nconst raw = Buffer.from(await response.arrayBuffer());\nwriteFileSync('result-body.bin', raw);\nwriteFileSync('response-headers.txt', [...response.headers].map(([key, value]) => key + ': ' + value).join('\\n'));\nif (!response.ok) throw new Error('HTTP ' + response.status + '; original response saved in result-body.bin');\nif (stream) {\n writeFileSync('result.sse', raw);\n process.stdout.write(raw);\n} else {\n writeFileSync('result.json', raw);\n const result = JSON.parse(raw.toString('utf8'));\n console.log(JSON.stringify(result, null, 2));\n for (const choice of result.choices ?? []) console.log('Choice', choice.index, JSON.stringify(choice));\n}\n", "label": "Node.js · complete JSON or all SSE events", "language": "javascript" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "chat", "hints": [ "Send your actual text with this exact model ID.", "Set AILOOT_STREAM=1 in an example to save the complete SSE result." ], "http": "POST", "in": 1.1, "input": [ "text" ], "label": "OpenAI Chat · SenseNova-V6-Pro", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "official_sources": [ { "title": "Chat Completions API", "url": "https://302ai-en.apifox.cn/207705102e0" } ], "out": 2.86, "output": [ "text" ], "path": "/v1/chat/completions", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "request_model_id": "SenseNova-V6-Pro", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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, "cache_write": 0, "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": "Netinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė", "http_status": 400, "recovery": "Prieš naują kūrimo užklausą pataisykite nurodytus laukus.", "type": "invalid_request_error" } ], "example_body": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "SenseNova-V6-Pro", "stream": false }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content eilutė", "required_material": "UTF-8 tekstas" } ], "operation_modes": [ "synchronous_json", "streamed_SSE" ], "outputs": { "all_results": "Išsaugokite visus turinio blokus, mąstymo parašus ir tikruosius įrankių naudojimo ID. Surinkite visus SSE blokų prieaugius; pirmasis teksto blokas nėra visa išvestis.", "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 arba SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "SenseNova-V6-Pro" ], "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": [ "SenseNova-V6-Pro" ], "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": "SenseNova-V6-Pro", "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": "Perskaitykite tikrąjį UTF-8 dokumentą ir įterpkite jo tekstą į nurodytą input lauką arba pranešimo turinio eilutę." }, "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": "Baziniai žetonų įkainiai", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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\": \"SenseNova-V6-Pro\",\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': 'SenseNova-V6-Pro', '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': 'SenseNova-V6-Pro', '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": null, "flex_multiplier": null, "fmt": "messages", "http": "POST", "in": 1.1, "input": [ "text" ], "label": "Anthropic pranešimai", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": 2.86, "output": [ "json", "sse" ], "path": "/v1/messages", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "request_model_id": "SenseNova-V6-Pro", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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, "cache_write": 0, "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": "Netinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė", "http_status": 400, "recovery": "Prieš naują kūrimo užklausą pataisykite nurodytus laukus.", "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": "Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content", "required_material": "UTF8 tekstas" } ], "operation_modes": [ "conversation", "function_tool_continuation", "streaming" ], "outputs": { "all_results": "Išsaugokite kiekvieną variantą ir jo turinį / įrankių iškvietimus / samprotavimą. SSE prieaugius surinkite pagal varianto / įrankio indeksą; išsaugokite galutinę užbaigimo priežastį ir naudojimo duomenis.", "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 arba SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "sensetime/sensenova-v6-pro" ], "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": "Šie vaidmenys aiškiai išreikšti šaltinio kodo suderinamumo tipuose; tikslus vaidmenų rinkinys priklauso nuo konkretaus modelio.", "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; naudokite tikrąjį grąžintą ID" }, { "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": "Grąžinkite tikrąjį gautą samprotavimą ten, kur šis modelis jį naudoja" }, { "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": "pateiktas funkcijos tipo įrankis" }, { "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": "provider.options šiame Ultra teksto maršrute atmetamas", "default": null, "default_known": false, "enum": null, "enum_known": false, "name": "provider", "required": false, "type": "object" }, { "availability": "source_interface", "conditions": "1h atmetamas tikrosiose užklausų podėlio vietose", "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": [ "Siųskite tikslų modelio ID kartu su messages.", "Konteksto ilgis nėra išvesties limitas.", "Teksto failas gali pateikti pažodinį tekstą; vaizdų / garso / failų objektų įvestims reikia tikslaus susiejimo." ], "input": { "content_type": "application/json", "control_scope": "priklauso nuo modelio; naudotojo funkcijų įrankiai skiriasi nuo priglobtų įrankių", "file_material": "tikrasis UTF-8 dokumentas įterptas kaip pažodinis tekstas; failo ID nenumanomas", "hosted_operations": false, "material_types": [ "text" ], "messages": "pranešimų masyvas su role/content struktūra", "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": "Baziniai žetonų įkainiai", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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\": \"sensetime/sensenova-v6-pro\", \"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='sensetime/sensenova-v6-pro',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='sensetime/sensenova-v6-pro',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": null, "flex_multiplier": null, "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": 1.1, "input": [ "text" ], "label": "OpenAI pokalbis", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": 2.86, "output": [ "text" ], "path": "/v1/chat/completions", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "request_model_id": "sensetime/sensenova-v6-pro", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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, "cache_write": 0, "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": "Netinkami privalomi laukai, medžiagos pateikimo forma arba parametro reikšmė", "http_status": 400, "recovery": "Prieš naują kūrimo užklausą pataisykite nurodytus laukus.", "type": "invalid_request_error" } ], "example_body": { "max_tokens": 128, "messages": [ { "content": "Summarize the incident report.", "role": "user" } ], "model": "sensetime/sensenova-v6-pro", "stream": false }, "lifecycle": { "create": { "http": "POST", "path": "/v1/messages" }, "job_read": null, "mode": "synchronous_or_streamed", "unknown": "Išsaugokite užklausų / atsakymų ID ir antraštes. Bendras teksto užduoties gavimo URL nepateikiamas." }, "material_combinations": [ { "mode": "text", "representation": "messages[].content eilutė", "required_material": "UTF-8 tekstas" } ], "operation_modes": [ "synchronous_json", "streamed_SSE" ], "outputs": { "all_results": "Išsaugokite visus turinio blokus, mąstymo parašus ir tikruosius įrankių naudojimo ID. Surinkite visus SSE blokų prieaugius; pirmasis teksto blokas nėra visa išvestis.", "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 arba SSE" }, "parameters": [ { "availability": "source_interface", "default": null, "default_known": false, "enum": [ "sensetime/sensenova-v6-pro" ], "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": [ "sensetime/sensenova-v6-pro" ], "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": "sensetime/sensenova-v6-pro", "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": "Perskaitykite tikrąjį UTF-8 dokumentą ir įterpkite jo tekstą į nurodytą input lauką arba pranešimo turinio eilutę." }, "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": "Baziniai žetonų įkainiai", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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\": \"sensetime/sensenova-v6-pro\",\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': 'sensetime/sensenova-v6-pro', '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': 'sensetime/sensenova-v6-pro', '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": null, "flex_multiplier": null, "fmt": "messages", "http": "POST", "in": 1.1, "input": [ "text" ], "label": "Anthropic pranešimai", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": 2.86, "output": [ "json", "sse" ], "path": "/v1/messages", "price_conditions": [ { "label": "Fast mode", "value": "Not specified", "when": "When fast mode is selected" }, { "label": "Flex mode", "value": "Not specified", "when": "When flex mode is selected" }, { "label": "Maximum reasoning effort", "value": "Not specified", "when": "When maximum reasoning effort uses the default adjustment" } ], "pricing": { "billing_mode": "token", "image_input_price": null, "image_output_price": null, "per_request_price": null }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "request_model_id": "sensetime/sensenova-v6-pro", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "model_aliases": [ { "canonical_model_id": "sensetime/sensenova-v6-pro", "request_model_id": "SenseNova-V6-Pro", "route_label": "Ultra" }, { "canonical_model_id": "sensetime/sensenova-v6-pro", "request_model_id": "sensetime/sensenova-v6-pro", "route_label": "Ultra" } ], "name": "SenseNova-V6-Pro", "price": { "in": 1.1, "in_label": null, "out": 2.86, "out_label": null, "scope_label": "Token rates", "sort_in": 1.1, "sort_out": 2.86, "varies": false }, "pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "OpenAI Chat · Base token rates", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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": { "regime": "base" }, "label": "Anthropic Messages · Base token rates", "units": [ { "amount": "0.0011000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000011", "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": "0.00286000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0.00000286", "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", "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", "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": "0", "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" } ] } ], "public_id": "sensetime/sensenova-v6-pro", "short": "SenseNova V6 Pro – tai bendros paskirties „SenseTime“ vaizdų ir teksto pokalbio profilis, grąžinantis tekstą. Pateikite dokumentus, paveikslėlius ir klausimus paaiškinimui ar palyginimui, išlaikydami atsakymo ryšį su vaizdiniais ir rašytiniais įrodymais." }, "renderer_schema": { "method_order": "Original DTO methods order; every exact route/format/path/caller survives.", "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers." }, "representation": "exact-public-dto-and-native-renderer-html", "representationNotes": { "current_reference": { "about_json_pointer": "/aboutHtml", "methods": [ { "contract_json_pointer": "/methods/0/rawMethod/contract", "html_json_pointer": "/methods/0/html", "method_ordinal": 0 }, { "contract_json_pointer": "/methods/1/rawMethod/contract", "html_json_pointer": "/methods/1/html", "method_ordinal": 1 }, { "contract_json_pointer": "/methods/2/rawMethod/contract", "html_json_pointer": "/methods/2/html", "method_ordinal": 2 }, { "contract_json_pointer": "/methods/3/rawMethod/contract", "html_json_pointer": "/methods/3/html", "method_ordinal": 3 } ], "role": "current-semantic-reference" }, "raw_input": { "examples_role": "historical-input-not-current-ready-examples", "json_pointers": [ "/rawModel", "/methods/0/rawMethod", "/methods/1/rawMethod", "/methods/2/rawMethod", "/methods/3/rawMethod" ], "role": "historical-owner-input" }, "schema": "ailoot-native-model-representations-v1" }, "schema": "ailoot-static-model-facts-v1", "schema_version": 1, "shortText": "SenseNova V6 Pro – tai bendros paskirties „SenseTime“ vaizdų ir teksto pokalbio profilis, grąžinantis tekstą. Pateikite dokumentus, paveikslėlius ir klausimus paaiškinimui ar palyginimui, išlaikydami atsakymo ryšį su vaizdiniais ir rašytiniais įrodymais.", "source": { "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1", "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036", "raw_model_json_sha256": "41dc5d31ed15d9697bc2eeaa15436f8680612241ba69f46deb8b11f74d0e6761", "renderer_sha256": "57bd2f8a61f57d341aae369006eca818e3eea645ec43af488ec7b2289eeca772" }, "sourceRevision": "982caa3e4e97119e3fb78df7abd40c8c789ac459b0450df6723fc448302c1821" }