{ "aboutHtml": "

Text Embedding Ada 002 Batch naudoja /v1/batches su tiksliu openai/text-embedding-ada-002:batch modelio ID. Laukui endpoint priskirkite reikšmę /v1/embeddings ir pateikite requests; kiekviename elemente turi būti custom_id ir body, kurio lauko input reikšmė yra teksto eilutė arba eilučių masyvas. Identifikatorius išlaikykite stabilius, kad jūsų programa galėtų susieti rezultatus su naujų ar pakeistų ištraukų rinkiniu.

Paketas vykdomas asinchroniškai. Išsaugokite pradinį grąžintą operacijos ID ir naudokite GET /v1/batches/{operation_id}, kad tas pats kvietėjas sektų tą pačią operaciją. Užbaigtame rezultatų rinkinyje kiekvienam custom_id gali būti atsakymas arba klaida, todėl tikrinkite ne tik bendrą būseną, bet ir atskirų elementų rezultatus.

Visus užbaigtus rezultatus išsaugokite JSONL formatu, išlaikydami kiekvieną custom_id ir visą jo atsakymą arba klaidą. Prieš atnaujindami indeksą sėkmingus vektorius susiekite su pateiktų dokumentų ID. Pradinės operacijos ir elementų įrašus laikykite kartu, kad neužbaigtą ar nepavykusį elementą būtų galima tirti neprarandant jau grąžintų rezultatų.

", "aboutText": "Text Embedding Ada 002 Batch naudoja /v1/batches su tiksliu openai/text-embedding-ada-002:batch modelio ID. Laukui endpoint priskirkite reikšmę /v1/embeddings ir pateikite requests; kiekviename elemente turi būti custom_id ir body, kurio lauko input reikšmė yra teksto eilutė arba eilučių masyvas. Identifikatorius išlaikykite stabilius, kad jūsų programa galėtų susieti rezultatus su naujų ar pakeistų ištraukų rinkiniu.\n\nPaketas vykdomas asinchroniškai. Išsaugokite pradinį grąžintą operacijos ID ir naudokite GET /v1/batches/{operation_id}, kad tas pats kvietėjas sektų tą pačią operaciją. Užbaigtame rezultatų rinkinyje kiekvienam custom_id gali būti atsakymas arba klaida, todėl tikrinkite ne tik bendrą būseną, bet ir atskirų elementų rezultatus.\n\nVisus užbaigtus rezultatus išsaugokite JSONL formatu, išlaikydami kiekvieną custom_id ir visą jo atsakymą arba klaidą. Prieš atnaujindami indeksą sėkmingus vektorius susiekite su pateiktų dokumentų ID. Pradinės operacijos ir elementų įrašus laikykite kartu, kad neužbaigtą ar nepavykusį elementą būtų galima tirti neprarandant jau grąžintų rezultatų.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "a4f223ca4c940fe61e841d60be78b782964ac427e2e8bc309169b6cff225797a", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "lt", "methods": [ { "html": "
•

OpenAI: Text Embedding Ada 002 (batch)

Kita /openai/text-embedding-ada-002:batch

Pradžia

Text Embedding Ada 002 Batch pateikia teksto vektorinių atvaizdų užklausų grupes kaip vieną Ailoot paketą. Kiekvieną elementą sekite pagal custom_id ir gaukite visus pradinės operacijos rezultatus.

Leidžiamos įvestys
Tekstas
Rezultatai
embedding
Apie modelį

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

Text Embedding Ada 002 Batch naudoja /v1/batches su tiksliu openai/text-embedding-ada-002:batch modelio ID. Laukui endpoint priskirkite reikšmę /v1/embeddings ir pateikite requests; kiekviename elemente turi būti custom_id ir body, kurio lauko input reikšmė yra teksto eilutė arba eilučių masyvas. Identifikatorius išlaikykite stabilius, kad jūsų programa galėtų susieti rezultatus su naujų ar pakeistų ištraukų rinkiniu.

Paketas vykdomas asinchroniškai. Išsaugokite pradinį grąžintą operacijos ID ir naudokite GET /v1/batches/{operation_id}, kad tas pats kvietėjas sektų tą pačią operaciją. Užbaigtame rezultatų rinkinyje kiekvienam custom_id gali būti atsakymas arba klaida, todėl tikrinkite ne tik bendrą būseną, bet ir atskirų elementų rezultatus.

Visus užbaigtus rezultatus išsaugokite JSONL formatu, išlaikydami kiekvieną custom_id ir visą jo atsakymą arba klaidą. Prieš atnaujindami indeksą sėkmingus vektorius susiekite su pateiktų dokumentų ID. Pradinės operacijos ir elementų įrašus laikykite kartu, kad neužbaigtą ar nepavykusį elementą būtų galima tirti neprarandant jau grąžintų rezultatų.

Prieinama Ailoot · įvestys ir metodai

Ailoot Ultra · Batch POST /v1/batches
Įvestis
text
Išvestis
embedding
LaukasTipasReikalavimasReikšmės ir ribosNumatyta
LaukasmodelTipasstringReikalavimasPrivalomaReikšmės ir ribos
openai/text-embedding-ada-002:batch
Sąlygos: Naudokite būtent šį Ailoot maršrutizavimo parinkiklį.
Numatyta—
LaukasendpointTipasstringReikalavimasPrivalomaReikšmės ir ribos
/v1/embeddings
Sąlygos:
Numatyta—
LaukasrequestsTipasarrayReikalavimasPrivalomaReikšmės ir ribos
Sąlygos:
Numatyta—
Metodo parametrai ir gyvavimo ciklas
ParametrasSpecifikacija
Parametrascontent_typeSpecifikacijaapplication/json
ParametrasrequiredSpecifikacijamodel, endpoint, requests
ParametrasoptionalSpecifikacija
Parametrasmaterial_typesSpecifikacijatext
ParametrasconditionsSpecifikacijaNaudokite būtent šį Ailoot maršrutizavimo parinkiklį.

Gyvavimo ciklas: asynchronous

GET /v1/batches/{operation_id} · Tikrasis pradinis response.id, tas pats užklausos siuntėjas, raktas ir grupė.

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)
Išreikštinio podėlio kainodara
Neįjungta Kai prašoma išreikštinio podėlio

Ailoot įkainiai

Kainos pagal konfigūraciją

Kiekvieną mokestį susiekite su nurodytomis sąlygomis. Kiekvienam alternatyvių konfigūracijų rinkiniui taikykite vieną įkainį.

KonfigūracijaĮkainių lentelėKonteksto tokenų daugiau neiKonteksto tokenų iki imtinaiMokestis
KonfigūracijaBaziniai žetonų įkainiaiĮkainių lentelėBazinis įkainisKonteksto tokenų daugiau nei—Konteksto tokenų iki imtinaiBe viršutinės ribosMokestis
Įvestis · Įvesties tokenai $0.0001 / 1K tokenų
Išvestis · Išvesties tokenai $0 / 1K tokenų
Įvestis · Talpyklos skaitymas — / 1K tokenų
Įvestis · Rašymas į talpyklą — / 1K tokenų
Įvestis · Rašymas į talpyklą, 1 val — / 1K tokenų
KonfigūracijaUžklausos ilgio pakopa 1Įkainių lentelė—Konteksto tokenų daugiau nei0Konteksto tokenų iki imtinaiBe viršutinės ribosMokestis
Įvestis · Įvesties tokenai $0.0001 / 1K tokenų
Išvestis · Išvesties tokenai $0 / 1K tokenų
Įvestis · Talpyklos skaitymas — / 1K tokenų
Įvestis · Rašymas į talpyklą — / 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 · Batch

set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"endpoint": "/v1/embeddings", "model": "openai/text-embedding-ada-002:batch", "requests": [{"custom_id": "embedding-1", "body": {"input": "The quick brown fox jumps over the lazy dog"}}]}')\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/batches \\\n  -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\n# Submit once. Retain the complete result, original identifiers and every response header.\n

Gauti ir išsaugoti rezultatus

Ailoot Ultra · Batch

Išsaugoti visus baigtus rezultatus

Išsaugokite kiekvieną visą grąžintą atsakymą, failą ir turinio dalį.

Išsaugokite pradinę būseną, kiekvieną custom_id ir visą atsakymą arba klaidą. Visus užbaigtus results[] išsaugokite JSONL formatu; joks įkėlimo ar atsisiuntimo per Files kelias nenumanomas.

Jei reikia patikrinti pradinį atsakymą

Išsaugokite pradinį operacijos ID ir skaitykite tik pradinį užklausų paketą. Pasibaigęs laukimo laikas, klaida ar nežinoma būsena nesuteikia leidimo siųsti dar vieną kūrimo užklausą.

Atsakymo laukai
LaukasTipas
Laukasresults[]Tipasarray
Laukasresults[].custom_idTipasstring
Laukasresults[].responseTipasobject
Laukasresults[].errorTipasobject
Klaidos ir tolesni veiksmai
AtsakymasSąlygaKitas žingsnis
Atsakymas400 · invalid_request_errorSąlygaPrivalomas laukas, modelio parinkiklis, tipas arba įvesties pateikimo forma yra netinkami.Kitas žingsnisPrieš rengdami atskirą užklausą, peržiūrėkite grąžintą išsamią patikros informaciją.
AtsakymasSąlygaPradinė užklausa arba rezultatas nežinomi arba juos reikia patikrinti.Kitas žingsnisIšsaugokite pradinius identifikatorius ir antraštes; skaitykite tik palaikomus būsenos ar bibliotekos įrašus. Nesiųskite kūrimo užklausos dar kartą.

Pseudonimai

Modelių pseudonimai

Ailoot Ultra openai/text-embedding-ada-002:batch

Metodų kelių pseudonimai

Naudokite aukščiau nurodytus metodų kelius.

Susiję ID iškvietimui

openai/text-embedding-ada-002:batch

", "method_identity": { "effective_request_model_id": "openai/text-embedding-ada-002:batch", "fmt": "batches", "http": "POST", "path": "/v1/batches", "request_model_id": "openai/text-embedding-ada-002:batch", "route_label": "Ultra" }, "method_key": "Ultra|batches|/v1/batches|openai%2Ftext-embedding-ada-002%3Abatch", "ordinal": 0, "rawMethod": { "available": null, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Retain the complete response and headers, original identifiers, every actual output and all usage/accounting fields. Save each unique owned asset and retain every role pointing to it.", "authentication": { "header": "Authorization", "scheme": "Bearer", "value": "$AILOOT_API_KEY" }, "errors": [ { "condition": "Privalomas laukas, modelio parinkiklis, tipas arba įvesties pateikimo forma yra netinkami.", "http_status": 400, "recovery": "Prieš rengdami atskirą užklausą, peržiūrėkite grąžintą išsamią patikros informaciją.", "type": "invalid_request_error" }, { "condition": "Pradinė užklausa arba rezultatas nežinomi arba juos reikia patikrinti.", "http_status": null, "recovery": "Išsaugokite pradinius identifikatorius ir antraštes; skaitykite tik palaikomus būsenos ar bibliotekos įrašus. Nesiųskite kūrimo užklausos dar kartą.", "type": null } ], "lifecycle": { "cancel_endpoint": null, "create": { "accepted_status": 202, "http": "POST", "path": "/v1/batches" }, "file_upload": null, "mode": "asynchronous", "status": [ { "http": "GET", "id_source": "actual original response.id, same caller/key/group", "path": "/v1/batches/{operation_id}" } ], "terminal": [ "completed", "failed", "expired", "cancelled" ], "unknown": "Išsaugokite pradinį operacijos ID ir skaitykite tik pradinį užklausų paketą. Pasibaigęs laukimo laikas, klaida ar nežinoma būsena nesuteikia leidimo siųsti dar vieną kūrimo užklausą.", "unknown_no_replay": true }, "outputs": { "all_results": "Išsaugokite pradinę būseną, kiekvieną custom_id ir visą atsakymą arba klaidą. Visus užbaigtus results[] išsaugokite JSONL formatu; joks įkėlimo ar atsisiuntimo per Files kelias nenumanomas.", "every_actual_output": true, "family": "batch", "fields": [ { "name": "results[]", "type": "array" }, { "name": "results[].custom_id", "type": "string" }, { "name": "results[].response", "type": "object" }, { "name": "results[].error", "type": "object" } ] }, "parameters": [ { "conditions": "Naudokite būtent šį Ailoot maršrutizavimo parinkiklį.", "default_known": false, "enum": [ "openai/text-embedding-ada-002:batch" ], "enum_known": true, "maximum_length": null, "name": "model", "required": true, "type": "string" }, { "conditions": "", "default_known": false, "enum": [ "/v1/embeddings" ], "enum_known": true, "maximum_length": null, "name": "endpoint", "required": true, "type": "string" }, { "conditions": "", "default_known": false, "enum_known": false, "items": { "properties": { "body": { "properties": { "input": { "oneOf": [ { "type": "string" }, { "items": { "type": "string" }, "type": "array" } ] } }, "required": [ "input" ], "type": "object" }, "custom_id": { "type": "string" } }, "required": [ "custom_id", "body" ], "type": "object" }, "maximum_length": null, "minItems": 1, "name": "requests", "required": true, "type": "array" } ], "request_schema": { "additionalProperties": true, "properties": { "endpoint": { "enum": [ "/v1/embeddings" ], "type": "string" }, "model": { "enum": [ "openai/text-embedding-ada-002:batch" ], "type": "string" }, "requests": { "items": { "properties": { "body": { "properties": { "input": { "oneOf": [ { "type": "string" }, { "items": { "type": "string" }, "type": "array" } ] } }, "required": [ "input" ], "type": "object" }, "custom_id": { "type": "string" } }, "required": [ "custom_id", "body" ], "type": "object" }, "minItems": 1, "type": "array" } }, "required": [ "model", "endpoint", "requests" ], "type": "object" }, "schema_template": { "actual_file_preparation_required": false, "body": { "endpoint": "/v1/embeddings", "model": "openai/text-embedding-ada-002:batch", "requests": [ { "body": { "input": "The quick brown fox jumps over the lazy dog" }, "custom_id": "embedding-1" } ] }, "content_type": "application/json", "example_is_offline_content": true }, "usage": { "meter": "Use the accepted method price and actual recorded usage; the request reserve is an estimate. A billing unit does not add an input capability.", "preserve": "Keep all returned usage, accounting and request identifiers with every actual output.", "settlement": "Retain the original operation; reconcile its result and accounting once." } }, "input": { "conditions": [ "Naudokite būtent šį Ailoot maršrutizavimo parinkiklį." ], "content_type": "application/json", "material_types": [ "text" ], "optional": [], "required": [ "model", "endpoint", "requests" ] }, "lifecycle": { "cancel_endpoint": null, "create": { "accepted_status": 202, "http": "POST", "path": "/v1/batches" }, "file_upload": null, "mode": "asynchronous", "status": [ { "http": "GET", "id_source": "Tikrasis pradinis response.id, tas pats užklausos siuntėjas, raktas ir grupė.", "path": "/v1/batches/{operation_id}" } ], "terminal": [ "completed", "failed", "expired", "cancelled" ], "unknown": "Preserve the original operation ID and read only that original batch. A timeout, error or unknown state does not authorize another creation.", "unknown_no_replay": true }, "method": { "http": "POST", "path": "/v1/batches" }, "method_aliases": [], "output": { "all_results": "Preserve original status, every custom_id and full response/error. Save all completed results[] as JSONL; no Files upload/download path is inferred.", "every_actual_output": true, "family": "batch", "fields": [ { "name": "results[]", "type": "array" }, { "name": "results[].custom_id", "type": "string" }, { "name": "results[].response", "type": "object" }, { "name": "results[].error", "type": "object" } ] } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"endpoint\": \"/v1/embeddings\", \"model\": \"openai/text-embedding-ada-002:batch\", \"requests\": [{\"custom_id\": \"embedding-1\", \"body\": {\"input\": \"The quick brown fox jumps over the lazy dog\"}}]}')\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/batches \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\n# Submit once. Retain the complete result, original identifiers and every response header.\n", "label": "curl · create once and retain the complete result", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\npython3 - <<'PY_BATCH'\nimport json,os,subprocess\nfrom pathlib import Path\nfrom urllib.parse import quote\nr=json.loads(Path(\"result.json\").read_text()); operation=r[\"id\"]\nsubprocess.run([\"curl\",\"--fail-with-body\",\"--silent\",\"--show-error\",\"https://api.ailoot.ai/v1/batches/\"+quote(operation,safe=\"\"),\"-H\",\"Authorization: Bearer \"+os.environ[\"AILOOT_API_KEY\"],\"-D\",\"status-headers.txt\",\"-o\",\"status.json\"],check=True)\ns=json.loads(Path(\"status.json\").read_text())\nif s.get(\"status\")==\"completed\": Path(\"results.jsonl\").write_text(\"\".join(json.dumps(x,ensure_ascii=False)+\"\\n\" for x in s.get(\"results\",[])))\n# Repeat only this same original GET while pending; never repeat creation.\nPY_BATCH\n", "label": "Read the original batch and preserve every result", "language": "bash" } ], "family": "batch", "fast_multiplier": null, "flex_multiplier": null, "fmt": "batches", "http": "POST", "in": 0.1, "input": [ "text" ], "label": "Batch", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": 0, "output": [ "embedding" ], "path": "/v1/batches", "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" }, { "label": "Explicit cache pricing", "value": "Not enabled", "when": "When explicit cache is requested" } ], "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": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "request_model_id": "openai/text-embedding-ada-002:batch", "route_label": "Ultra", "status_reads": [ "GET /v1/batches/{operation_id}" ], "tiers": [ { "cache_read": null, "cache_read_multiplier": null, "cache_write": null, "cache_write_1h": null, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 0.1, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 0, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } } ], "model_id": "openai/text-embedding-ada-002:batch", "nativeProvenance": { "input_facts_canonical_sha256": "9fb831542b8402d2da9cf784cdd9f87561dc22c75707c82bbd378d13e5271b11", "input_html_sha256": "1b9d6110a9a2326282867156cf97ef9eff60513a02444b858725c0d653b939d6", "private_audit_sha256": "3fef5b17a456282b28c9321f7d5fd62e70faae7e43a168cb7d13c8f98cc9aed6", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/lt/openai-text-embedding-ada-002-u003a-batch/", "description": "Text Embedding Ada 002 Batch pateikia teksto vektorinių atvaizdų užklausų grupes kaip vieną Ailoot paketą. Kiekvieną elementą sekite pagal custom_id ir gaukite visus pradinės operacijos rezultatus.", "locale": "lt", "md_url": "https://ailoot.ai/models/lt/openai-text-embedding-ada-002-u003a-batch/index.md", "title": "OpenAI: Text Embedding Ada 002 (batch) — Ailoot", "url": "https://ailoot.ai/models/lt/openai-text-embedding-ada-002-u003a-batch/" }, "rawModel": { "about": "Text Embedding Ada 002 Batch naudoja /v1/batches su tiksliu openai/text-embedding-ada-002:batch modelio ID. Laukui endpoint priskirkite reikšmę /v1/embeddings ir pateikite requests; kiekviename elemente turi būti custom_id ir body, kurio lauko input reikšmė yra teksto eilutė arba eilučių masyvas. Identifikatorius išlaikykite stabilius, kad jūsų programa galėtų susieti rezultatus su naujų ar pakeistų ištraukų rinkiniu.\n\nPaketas vykdomas asinchroniškai. Išsaugokite pradinį grąžintą operacijos ID ir naudokite GET /v1/batches/{operation_id}, kad tas pats kvietėjas sektų tą pačią operaciją. Užbaigtame rezultatų rinkinyje kiekvienam custom_id gali būti atsakymas arba klaida, todėl tikrinkite ne tik bendrą būseną, bet ir atskirų elementų rezultatus.\n\nVisus užbaigtus rezultatus išsaugokite JSONL formatu, išlaikydami kiekvieną custom_id ir visą jo atsakymą arba klaidą. Prieš atnaujindami indeksą sėkmingus vektorius susiekite su pateiktų dokumentų ID. Pradinės operacijos ir elementų įrašus laikykite kartu, kad neužbaigtą ar nepavykusį elementą būtų galima tirti neprarandant jau grąžintų rezultatų.", "alias_of": null, "aliases": [], "card_routes": [ { "label": "Ultra", "rates": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" } ], "summary": "Visa konfigūracijos kainodara pateikta išsamioje informacijoje." } ], "ctx": null, "formats": [ "batches" ], "id": "openai/text-embedding-ada-002:batch", "input": [ "text" ], "kind": "embedding", "max_out": null, "methods": [ { "available": null, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "all_results": "Retain the complete response and headers, original identifiers, every actual output and all usage/accounting fields. Save each unique owned asset and retain every role pointing to it.", "authentication": { "header": "Authorization", "scheme": "Bearer", "value": "$AILOOT_API_KEY" }, "errors": [ { "condition": "Privalomas laukas, modelio parinkiklis, tipas arba įvesties pateikimo forma yra netinkami.", "http_status": 400, "recovery": "Prieš rengdami atskirą užklausą, peržiūrėkite grąžintą išsamią patikros informaciją.", "type": "invalid_request_error" }, { "condition": "Pradinė užklausa arba rezultatas nežinomi arba juos reikia patikrinti.", "http_status": null, "recovery": "Išsaugokite pradinius identifikatorius ir antraštes; skaitykite tik palaikomus būsenos ar bibliotekos įrašus. Nesiųskite kūrimo užklausos dar kartą.", "type": null } ], "lifecycle": { "cancel_endpoint": null, "create": { "accepted_status": 202, "http": "POST", "path": "/v1/batches" }, "file_upload": null, "mode": "asynchronous", "status": [ { "http": "GET", "id_source": "actual original response.id, same caller/key/group", "path": "/v1/batches/{operation_id}" } ], "terminal": [ "completed", "failed", "expired", "cancelled" ], "unknown": "Išsaugokite pradinį operacijos ID ir skaitykite tik pradinį užklausų paketą. Pasibaigęs laukimo laikas, klaida ar nežinoma būsena nesuteikia leidimo siųsti dar vieną kūrimo užklausą.", "unknown_no_replay": true }, "outputs": { "all_results": "Išsaugokite pradinę būseną, kiekvieną custom_id ir visą atsakymą arba klaidą. Visus užbaigtus results[] išsaugokite JSONL formatu; joks įkėlimo ar atsisiuntimo per Files kelias nenumanomas.", "every_actual_output": true, "family": "batch", "fields": [ { "name": "results[]", "type": "array" }, { "name": "results[].custom_id", "type": "string" }, { "name": "results[].response", "type": "object" }, { "name": "results[].error", "type": "object" } ] }, "parameters": [ { "conditions": "Naudokite būtent šį Ailoot maršrutizavimo parinkiklį.", "default_known": false, "enum": [ "openai/text-embedding-ada-002:batch" ], "enum_known": true, "maximum_length": null, "name": "model", "required": true, "type": "string" }, { "conditions": "", "default_known": false, "enum": [ "/v1/embeddings" ], "enum_known": true, "maximum_length": null, "name": "endpoint", "required": true, "type": "string" }, { "conditions": "", "default_known": false, "enum_known": false, "items": { "properties": { "body": { "properties": { "input": { "oneOf": [ { "type": "string" }, { "items": { "type": "string" }, "type": "array" } ] } }, "required": [ "input" ], "type": "object" }, "custom_id": { "type": "string" } }, "required": [ "custom_id", "body" ], "type": "object" }, "maximum_length": null, "minItems": 1, "name": "requests", "required": true, "type": "array" } ], "request_schema": { "additionalProperties": true, "properties": { "endpoint": { "enum": [ "/v1/embeddings" ], "type": "string" }, "model": { "enum": [ "openai/text-embedding-ada-002:batch" ], "type": "string" }, "requests": { "items": { "properties": { "body": { "properties": { "input": { "oneOf": [ { "type": "string" }, { "items": { "type": "string" }, "type": "array" } ] } }, "required": [ "input" ], "type": "object" }, "custom_id": { "type": "string" } }, "required": [ "custom_id", "body" ], "type": "object" }, "minItems": 1, "type": "array" } }, "required": [ "model", "endpoint", "requests" ], "type": "object" }, "schema_template": { "actual_file_preparation_required": false, "body": { "endpoint": "/v1/embeddings", "model": "openai/text-embedding-ada-002:batch", "requests": [ { "body": { "input": "The quick brown fox jumps over the lazy dog" }, "custom_id": "embedding-1" } ] }, "content_type": "application/json", "example_is_offline_content": true }, "usage": { "meter": "Use the accepted method price and actual recorded usage; the request reserve is an estimate. A billing unit does not add an input capability.", "preserve": "Keep all returned usage, accounting and request identifiers with every actual output.", "settlement": "Retain the original operation; reconcile its result and accounting once." } }, "input": { "conditions": [ "Naudokite būtent šį Ailoot maršrutizavimo parinkiklį." ], "content_type": "application/json", "material_types": [ "text" ], "optional": [], "required": [ "model", "endpoint", "requests" ] }, "lifecycle": { "cancel_endpoint": null, "create": { "accepted_status": 202, "http": "POST", "path": "/v1/batches" }, "file_upload": null, "mode": "asynchronous", "status": [ { "http": "GET", "id_source": "Tikrasis pradinis response.id, tas pats užklausos siuntėjas, raktas ir grupė.", "path": "/v1/batches/{operation_id}" } ], "terminal": [ "completed", "failed", "expired", "cancelled" ], "unknown": "Preserve the original operation ID and read only that original batch. A timeout, error or unknown state does not authorize another creation.", "unknown_no_replay": true }, "method": { "http": "POST", "path": "/v1/batches" }, "method_aliases": [], "output": { "all_results": "Preserve original status, every custom_id and full response/error. Save all completed results[] as JSONL; no Files upload/download path is inferred.", "every_actual_output": true, "family": "batch", "fields": [ { "name": "results[]", "type": "array" }, { "name": "results[].custom_id", "type": "string" }, { "name": "results[].response", "type": "object" }, { "name": "results[].error", "type": "object" } ] } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "examples": [ { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"endpoint\": \"/v1/embeddings\", \"model\": \"openai/text-embedding-ada-002:batch\", \"requests\": [{\"custom_id\": \"embedding-1\", \"body\": {\"input\": \"The quick brown fox jumps over the lazy dog\"}}]}')\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/batches \\\n -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\n# Submit once. Retain the complete result, original identifiers and every response header.\n", "label": "curl · create once and retain the complete result", "language": "bash" }, { "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\nexport AILOOT_API_KEY\npython3 - <<'PY_BATCH'\nimport json,os,subprocess\nfrom pathlib import Path\nfrom urllib.parse import quote\nr=json.loads(Path(\"result.json\").read_text()); operation=r[\"id\"]\nsubprocess.run([\"curl\",\"--fail-with-body\",\"--silent\",\"--show-error\",\"https://api.ailoot.ai/v1/batches/\"+quote(operation,safe=\"\"),\"-H\",\"Authorization: Bearer \"+os.environ[\"AILOOT_API_KEY\"],\"-D\",\"status-headers.txt\",\"-o\",\"status.json\"],check=True)\ns=json.loads(Path(\"status.json\").read_text())\nif s.get(\"status\")==\"completed\": Path(\"results.jsonl\").write_text(\"\".join(json.dumps(x,ensure_ascii=False)+\"\\n\" for x in s.get(\"results\",[])))\n# Repeat only this same original GET while pending; never repeat creation.\nPY_BATCH\n", "label": "Read the original batch and preserve every result", "language": "bash" } ], "family": "batch", "fast_multiplier": null, "flex_multiplier": null, "fmt": "batches", "http": "POST", "in": 0.1, "input": [ "text" ], "label": "Batch", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": 0, "output": [ "embedding" ], "path": "/v1/batches", "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" }, { "label": "Explicit cache pricing", "value": "Not enabled", "when": "When explicit cache is requested" } ], "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": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] }, { "dimensions": { "max_context_tokens_inclusive": null, "min_context_tokens_exclusive": 0 }, "label": "Request-length tier 1", "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "request_model_id": "openai/text-embedding-ada-002:batch", "route_label": "Ultra", "status_reads": [ "GET /v1/batches/{operation_id}" ], "tiers": [ { "cache_read": null, "cache_read_multiplier": null, "cache_write": null, "cache_write_1h": null, "cache_write_multiplier": null, "created_at": "0001-01-01T00:00:00Z", "in": 0.1, "input_multiplier": null, "max": null, "max_tokens": null, "min": 0, "min_tokens": 0, "out": 0, "output_multiplier": null, "per_request_price": null, "sort_order": 0, "tier_label": "", "updated_at": "0001-01-01T00:00:00Z" } ], "units": [ { "amount": "0.0001000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.0000001", "native_quantity": 1, "native_unit": "input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "input_token" }, { "amount": "0", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "output_price", "label": "Output tokens", "native_amount_usd_per_unit": "0", "native_quantity": 1, "native_unit": "output_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "out", "unit": "output_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_read_price", "label": "Cache read", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "cached_input_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "cached_input_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_price", "label": "Cache write", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "generic_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "generic_cache_creation_token" }, { "amount": null, "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "cache_write_1h_price", "label": "Cache write, 1 hour", "native_amount_usd_per_unit": null, "native_quantity": 1, "native_unit": "one_hour_cache_creation_token", "public_unit_label": "/ 1K tokens", "quantity": 1000, "quantity_is_estimate": false, "rate_role": "typed_native_retail_rate", "side": "in", "unit": "one_hour_cache_creation_token" } ] } ], "model_aliases": [ { "canonical_model_id": "openai/text-embedding-ada-002:batch", "request_model_id": "openai/text-embedding-ada-002:batch", "route_label": "Ultra" } ], "name": "OpenAI: Text Embedding Ada 002 (batch)", "price": { "in": 0.1, "in_label": null, "out": 0, "out_label": null, "scope_label": "Token rates", "sort_in": 0.1, "sort_out": 0, "varies": true }, "short": "Text Embedding Ada 002 Batch pateikia teksto vektorinių atvaizdų užklausų grupes kaip vieną Ailoot paketą. Kiekvieną elementą sekite pagal custom_id ir gaukite visus pradinės operacijos rezultatus.", "title": "OpenAI: Text Embedding Ada 002 (batch)" }, "renderer_schema": { "method_order": "Original DTO methods order; every exact route/format/path/caller survives.", "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers." }, "representation": "exact-public-dto-and-native-renderer-html", "representationNotes": { "current_reference": { "about_json_pointer": "/aboutHtml", "methods": [ { "contract_json_pointer": "/methods/0/rawMethod/contract", "html_json_pointer": "/methods/0/html", "method_ordinal": 0 } ], "role": "current-semantic-reference" }, "raw_input": { "examples_role": "historical-input-not-current-ready-examples", "json_pointers": [ "/rawModel", "/methods/0/rawMethod" ], "role": "historical-owner-input" }, "schema": "ailoot-native-model-representations-v1" }, "schema": "ailoot-static-model-facts-v1", "schema_version": 1, "shortText": "Text Embedding Ada 002 Batch pateikia teksto vektorinių atvaizdų užklausų grupes kaip vieną Ailoot paketą. Kiekvieną elementą sekite pagal custom_id ir gaukite visus pradinės operacijos rezultatus.", "source": { "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1", "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036", "raw_model_json_sha256": "66d155072b852cb95cd2f056096d9d6fa5dfee99e7783f393f8feb3a7ead0967", "renderer_sha256": "57bd2f8a61f57d341aae369006eca818e3eea645ec43af488ec7b2289eeca772" }, "sourceRevision": "11aa8291b06ab774523c457380d89af8c58fb41f780c8e4c0521a3582faead6a" }