{ "aboutHtml": "

Selecteer Baichuan-Text-Embedding in een verzoek aan /v1/embeddings. Het verplichte veld input accepteert een niet-lege string of een niet-lege array van strings, zodat een losse passage en een voorbereide verzameling hetzelfde endpoint kunnen gebruiken. Het JSON-resultaat bevat data[].embedding en data[].index, plus het geselecteerde model en usage.

Verdeel brondocumenten voor een kennisverzameling in passages die de definities en context bewaren die een latere lezer nodig heeft. Beheer document-ID’s in je toepassing en koppel elke vector aan zijn verstuurde positie. Een zoekworkflow kan de zoekvraag van de gebruiker met hetzelfde model coderen en de bronpassage bij elk opgehaald resultaat bewaren.

Sla het volledige synchrone antwoord op voordat je de vectoren definitief opslaat. Controleer de koppeling tussen invoer en indexen, bewaar alle teruggegeven vectoren en houd usage bij de bewerking. Door de exacte modelidentiteit voor opgeslagen embeddings te gebruiken, is duidelijk welke verzameling en zoekvraagrepresentatie bij elkaar horen.

", "aboutText": "Selecteer Baichuan-Text-Embedding in een verzoek aan /v1/embeddings. Het verplichte veld input accepteert een niet-lege string of een niet-lege array van strings, zodat een losse passage en een voorbereide verzameling hetzelfde endpoint kunnen gebruiken. Het JSON-resultaat bevat data[].embedding en data[].index, plus het geselecteerde model en usage.\n\nVerdeel brondocumenten voor een kennisverzameling in passages die de definities en context bewaren die een latere lezer nodig heeft. Beheer document-ID’s in je toepassing en koppel elke vector aan zijn verstuurde positie. Een zoekworkflow kan de zoekvraag van de gebruiker met hetzelfde model coderen en de bronpassage bij elk opgehaald resultaat bewaren.\n\nSla het volledige synchrone antwoord op voordat je de vectoren definitief opslaat. Controleer de koppeling tussen invoer en indexen, bewaar alle teruggegeven vectoren en houd usage bij de bewerking. Door de exacte modelidentiteit voor opgeslagen embeddings te gebruiken, is duidelijk welke verzameling en zoekvraagrepresentatie bij elkaar horen.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "fd16f7971c93d3e14bc272cdd05b7ec1e4f4cb6e8f98a8f823069280e564e8c4", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "nl-be", "methods": [ { "html": "
•

Baichuan-Text-Embedding

Overig /Baichuan-Text-Embedding

Aan de slag

Baichuan-Text-Embedding geeft via Ailoots embeddings-API numerieke vectoren terug voor aangeleverde tekst. Verstuur één passage of een lijst en bewaar de antwoordindexen wanneer je een doorzoekbare verzameling opbouwt.

Toegestane invoer
Tekst
Resultaten
embedding
Over het model

Deze beschrijving gaat over de mogelijkheden van het model. De via Ailoot beschikbare invoer, uitvoer en opties staan hieronder voor de geselecteerde methode.

Selecteer Baichuan-Text-Embedding in een verzoek aan /v1/embeddings. Het verplichte veld input accepteert een niet-lege string of een niet-lege array van strings, zodat een losse passage en een voorbereide verzameling hetzelfde endpoint kunnen gebruiken. Het JSON-resultaat bevat data[].embedding en data[].index, plus het geselecteerde model en usage.

Verdeel brondocumenten voor een kennisverzameling in passages die de definities en context bewaren die een latere lezer nodig heeft. Beheer document-ID’s in je toepassing en koppel elke vector aan zijn verstuurde positie. Een zoekworkflow kan de zoekvraag van de gebruiker met hetzelfde model coderen en de bronpassage bij elk opgehaald resultaat bewaren.

Sla het volledige synchrone antwoord op voordat je de vectoren definitief opslaat. Controleer de koppeling tussen invoer en indexen, bewaar alle teruggegeven vectoren en houd usage bij de bewerking. Door de exacte modelidentiteit voor opgeslagen embeddings te gebruiken, is duidelijk welke verzameling en zoekvraagrepresentatie bij elkaar horen.

Beschikbaar in Ailoot · invoer en methoden

Ailoot Ultra · Embeddings POST /v1/embeddings
Invoer
text
Uitvoer
embedding
VeldTypeVereisteWaarden en limietenStandaard
VeldmodelTypestringVereisteVereistWaarden en limieten
Baichuan-Text-Embedding
Voorwaarden: Gebruik precies deze Ailoot-routeringsselector.
Standaard—
VeldinputTypestring or array<string>VereisteVereistWaarden en limieten
Voorwaarden:
Standaard—
Methodeparameters en levenscyclus
ParameterContract
Parametercontent_typeContractapplication/json
ParameterrequiredContractmodel, input
ParameteroptionalContract
Parametermaterial_typesContracttext
ParameterconditionsContractGebruik precies deze Ailoot-routeringsselector.

Levenscyclus: synchronous_json

Tarieven

Tariefverwijzingen voegen geen verzoekopties toe. Ondersteunde parameters staan bij de geselecteerde methode.

Snelle modus
Niet opgegeven Wanneer de snelle modus geselecteerd is
Flex-modus
Niet opgegeven Wanneer de flex-modus geselecteerd is
Maximale redeneerinspanning
Niet opgegeven Wanneer voor maximale redeneerinspanning de default-aanpassing wordt gebruikt

Ailoot-tarieven

Prijzen per configuratie

ConfiguratieTariefstaffelKosten
ConfiguratieBasistarieven voor tokensTariefstaffelBasistariefKosten
Invoer · Invoertokens $0.00016 / 1K tokens
Uitvoer · Uitvoertokens $0 / 1K tokens
Invoer · Cache lezen — / 1K tokens
Invoer · Cache schrijven — / 1K tokens
Invoer · Cache schrijven, 1 uur — / 1K tokens

Ailoot reserveert vóór een verzoek een geschat bedrag. Na het resultaat worden de uiteindelijke kosten afgerekend op basis van het gemeten verbruik. Bij streaming gebeurt de afrekening op basis van de definitieve verbruiksregistratie. Zo werken reservering en afrekening →

Voorbeeldverzoeken

Ailoot Ultra · Embeddings

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('{"model": "Baichuan-Text-Embedding", "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/embeddings \\\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

Resultaten ophalen en opslaan

Aliasnamen

Modelaliasnamen

Ailoot Ultra Baichuan-Text-Embedding

Aliasnamen voor methodepaden

Gebruik de hierboven getoonde methodepaden.

Gerelateerde aanroeper-ID’s

Baichuan-Text-Embedding

", "method_identity": { "effective_request_model_id": "Baichuan-Text-Embedding", "fmt": "embeddings", "http": "POST", "path": "/v1/embeddings", "request_model_id": "Baichuan-Text-Embedding", "route_label": "Ultra" }, "method_key": "Ultra|embeddings|/v1/embeddings|Baichuan-Text-Embedding", "ordinal": 0, "rawMethod": { "available": null, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "accepted_material_guidance": { "conditions": [ "Send text with the selected model; retain every returned vector and its index." ], "content_type": "application/json", "material_types": [ "text" ], "optional": [], "required": [ "model", "input" ] }, "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": "Een verplicht veld, modelselector, type of invoerrepresentatie is ongeldig.", "http_status": 400, "recovery": "Bekijk de teruggegeven validatiedetails voor u een afzonderlijk verzoek voorbereidt.", "type": "invalid_request_error" }, { "condition": "Het oorspronkelijke verzoek of resultaat is onbekend of moet nagekeken worden.", "http_status": null, "recovery": "Bewaar de oorspronkelijke identificatoren en headers; raadpleeg enkel ondersteunde statusgegevens of bibliotheekrecords. Dien het aanmaakverzoek niet opnieuw in.", "type": null } ], "lifecycle": { "cancel_endpoint": null, "create": { "http": "POST", "path": "/v1/embeddings" }, "mode": "synchronous_json", "status": [], "unknown": "Bewaar de oorspronkelijke X-Client-Request-ID, het antwoord en de headers. Een onbekende uitkomst of result_pending_check geeft geen toestemming voor een tweede aanmaakverzoek.", "unknown_no_replay": true }, "outputs": { "all_results": "Bewaar het volledige antwoord en de headers, de oorspronkelijke identificatiecodes, alle werkelijke uitvoer en alle velden voor verbruik en boekhouding. Sla elke unieke asset die je toebehoort op en behoud elke rol die ernaar verwijst.", "every_actual_output": true, "family": "embedding", "fields": [ { "name": "data[].index", "type": "integer" }, { "name": "data[].embedding", "type": "array" }, { "name": "model", "type": "string" }, { "name": "usage", "type": "object" } ] }, "parameters": [ { "conditions": "Gebruik precies deze Ailoot-routeringsselector.", "default_known": false, "enum": [ "Baichuan-Text-Embedding" ], "enum_known": true, "maximum_length": null, "name": "model", "required": true, "type": "string" }, { "conditions": "", "default_known": false, "enum_known": false, "maximum_length": null, "name": "input", "oneOf": [ { "minLength": 1, "type": "string" }, { "items": { "minLength": 1, "type": "string" }, "minItems": 1, "type": "array" } ], "required": true, "type": "string or array" } ], "request_schema": { "additionalProperties": true, "properties": { "input": { "oneOf": [ { "minLength": 1, "type": "string" }, { "items": { "minLength": 1, "type": "string" }, "minItems": 1, "type": "array" } ] }, "model": { "enum": [ "Baichuan-Text-Embedding" ], "type": "string" } }, "required": [ "model", "input" ], "type": "object" }, "schema_template": { "actual_file_preparation_required": false, "body": { "input": "The quick brown fox jumps over the lazy dog", "model": "Baichuan-Text-Embedding" }, "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": [ "Gebruik precies deze Ailoot-routeringsselector." ], "content_type": "application/json", "material_types": [ "text" ], "optional": [], "required": [ "model", "input" ] }, "lifecycle": { "cancel_endpoint": null, "create": { "http": "POST", "path": "/v1/embeddings" }, "mode": "synchronous_json", "status": [], "unknown": "Keep the original X-Client-Request-ID, response and headers. An unknown or result_pending_check outcome does not authorize a second creation.", "unknown_no_replay": true }, "method": { "http": "POST", "path": "/v1/embeddings" }, "method_aliases": [], "output": { "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.", "every_actual_output": true, "family": "embedding", "fields": [ { "name": "data[].index", "type": "integer" }, { "name": "data[].embedding", "type": "array" }, { "name": "model", "type": "string" }, { "name": "usage", "type": "object" } ] } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.00016000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000016", "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('{\"model\": \"Baichuan-Text-Embedding\", \"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/embeddings \\\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" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "embeddings", "http": "POST", "in": 0.16, "input": [ "text" ], "label": "Embeddings", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": 0, "output": [ "embedding" ], "path": "/v1/embeddings", "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": "0.00016000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000016", "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": "Baichuan-Text-Embedding", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.00016000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000016", "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": "Baichuan-Text-Embedding", "nativeProvenance": { "input_facts_canonical_sha256": "6dd9a40e0547af87f0f6de682c2f9d9190f16829e55ca8d6bc230f0e4da22c91", "input_html_sha256": "88eee75823d8b9181bb0c863efe77aead0ea5128bebe6be54f36dcfb5dd55b8d", "private_audit_sha256": "6db5ff2f6d8da83fd413a5ebba99aad862ef2de71ede12fb3786c8280fd8f079", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/nl-be/baichuan-text-embedding/", "description": "Baichuan-Text-Embedding geeft via Ailoots embeddings-API numerieke vectoren terug voor aangeleverde tekst. Verstuur één passage of een lijst en bewaar de antwoordindexen wanneer je een doorzoekbare verzameling opbouwt.", "locale": "nl-be", "md_url": "https://ailoot.ai/models/nl-be/baichuan-text-embedding/index.md", "title": "Baichuan-Text-Embedding — Ailoot", "url": "https://ailoot.ai/models/nl-be/baichuan-text-embedding/" }, "rawModel": { "about": "Selecteer Baichuan-Text-Embedding in een verzoek aan /v1/embeddings. Het verplichte veld input accepteert een niet-lege string of een niet-lege array van strings, zodat een losse passage en een voorbereide verzameling hetzelfde endpoint kunnen gebruiken. Het JSON-resultaat bevat data[].embedding en data[].index, plus het geselecteerde model en usage.\n\nVerdeel brondocumenten voor een kennisverzameling in passages die de definities en context bewaren die een latere lezer nodig heeft. Beheer document-ID’s in je toepassing en koppel elke vector aan zijn verstuurde positie. Een zoekworkflow kan de zoekvraag van de gebruiker met hetzelfde model coderen en de bronpassage bij elk opgehaald resultaat bewaren.\n\nSla het volledige synchrone antwoord op voordat je de vectoren definitief opslaat. Controleer de koppeling tussen invoer en indexen, bewaar alle teruggegeven vectoren en houd usage bij de bewerking. Door de exacte modelidentiteit voor opgeslagen embeddings te gebruiken, is duidelijk welke verzameling en zoekvraagrepresentatie bij elkaar horen.", "alias_of": null, "aliases": [], "card_routes": [ { "label": "Ultra", "rates": [ { "amount": "0.00016000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000016", "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": "De volledige prijsinformatie voor de configuratie vindt u bij de details." } ], "ctx": null, "formats": [ "embeddings" ], "id": "Baichuan-Text-Embedding", "input": [ "text" ], "kind": "embedding", "max_out": null, "methods": [ { "available": null, "cache_read": null, "cache_write": null, "cache_write_1h": null, "contract": { "data": { "accepted_material_guidance": { "conditions": [ "Send text with the selected model; retain every returned vector and its index." ], "content_type": "application/json", "material_types": [ "text" ], "optional": [], "required": [ "model", "input" ] }, "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": "Een verplicht veld, modelselector, type of invoerrepresentatie is ongeldig.", "http_status": 400, "recovery": "Bekijk de teruggegeven validatiedetails voor u een afzonderlijk verzoek voorbereidt.", "type": "invalid_request_error" }, { "condition": "Het oorspronkelijke verzoek of resultaat is onbekend of moet nagekeken worden.", "http_status": null, "recovery": "Bewaar de oorspronkelijke identificatoren en headers; raadpleeg enkel ondersteunde statusgegevens of bibliotheekrecords. Dien het aanmaakverzoek niet opnieuw in.", "type": null } ], "lifecycle": { "cancel_endpoint": null, "create": { "http": "POST", "path": "/v1/embeddings" }, "mode": "synchronous_json", "status": [], "unknown": "Bewaar de oorspronkelijke X-Client-Request-ID, het antwoord en de headers. Een onbekende uitkomst of result_pending_check geeft geen toestemming voor een tweede aanmaakverzoek.", "unknown_no_replay": true }, "outputs": { "all_results": "Bewaar het volledige antwoord en de headers, de oorspronkelijke identificatiecodes, alle werkelijke uitvoer en alle velden voor verbruik en boekhouding. Sla elke unieke asset die je toebehoort op en behoud elke rol die ernaar verwijst.", "every_actual_output": true, "family": "embedding", "fields": [ { "name": "data[].index", "type": "integer" }, { "name": "data[].embedding", "type": "array" }, { "name": "model", "type": "string" }, { "name": "usage", "type": "object" } ] }, "parameters": [ { "conditions": "Gebruik precies deze Ailoot-routeringsselector.", "default_known": false, "enum": [ "Baichuan-Text-Embedding" ], "enum_known": true, "maximum_length": null, "name": "model", "required": true, "type": "string" }, { "conditions": "", "default_known": false, "enum_known": false, "maximum_length": null, "name": "input", "oneOf": [ { "minLength": 1, "type": "string" }, { "items": { "minLength": 1, "type": "string" }, "minItems": 1, "type": "array" } ], "required": true, "type": "string or array" } ], "request_schema": { "additionalProperties": true, "properties": { "input": { "oneOf": [ { "minLength": 1, "type": "string" }, { "items": { "minLength": 1, "type": "string" }, "minItems": 1, "type": "array" } ] }, "model": { "enum": [ "Baichuan-Text-Embedding" ], "type": "string" } }, "required": [ "model", "input" ], "type": "object" }, "schema_template": { "actual_file_preparation_required": false, "body": { "input": "The quick brown fox jumps over the lazy dog", "model": "Baichuan-Text-Embedding" }, "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": [ "Gebruik precies deze Ailoot-routeringsselector." ], "content_type": "application/json", "material_types": [ "text" ], "optional": [], "required": [ "model", "input" ] }, "lifecycle": { "cancel_endpoint": null, "create": { "http": "POST", "path": "/v1/embeddings" }, "mode": "synchronous_json", "status": [], "unknown": "Keep the original X-Client-Request-ID, response and headers. An unknown or result_pending_check outcome does not authorize a second creation.", "unknown_no_replay": true }, "method": { "http": "POST", "path": "/v1/embeddings" }, "method_aliases": [], "output": { "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.", "every_actual_output": true, "family": "embedding", "fields": [ { "name": "data[].index", "type": "integer" }, { "name": "data[].embedding", "type": "array" }, { "name": "model", "type": "string" }, { "name": "usage", "type": "object" } ] } }, "ctx": null, "declared_pricing_profiles": [ { "dimensions": { "regime": "base" }, "label": "Base token rates", "units": [ { "amount": "0.00016000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000016", "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('{\"model\": \"Baichuan-Text-Embedding\", \"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/embeddings \\\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" } ], "family": "openai", "fast_multiplier": null, "flex_multiplier": null, "fmt": "embeddings", "http": "POST", "in": 0.16, "input": [ "text" ], "label": "Embeddings", "max_out": null, "max_reasoning_effort_multiplier": null, "method_aliases": [], "out": 0, "output": [ "embedding" ], "path": "/v1/embeddings", "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": "0.00016000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000016", "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": "Baichuan-Text-Embedding", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.00016000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000016", "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": "Baichuan-Text-Embedding", "request_model_id": "Baichuan-Text-Embedding", "route_label": "Ultra" } ], "name": "Baichuan-Text-Embedding", "price": { "in": 0.16, "in_label": null, "out": 0, "out_label": null, "scope_label": "Token rates", "sort_in": 0.16, "sort_out": 0, "varies": false }, "short": "Baichuan-Text-Embedding geeft via Ailoots embeddings-API numerieke vectoren terug voor aangeleverde tekst. Verstuur één passage of een lijst en bewaar de antwoordindexen wanneer je een doorzoekbare verzameling opbouwt.", "title": "Baichuan-Text-Embedding" }, "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": "Baichuan-Text-Embedding geeft via Ailoots embeddings-API numerieke vectoren terug voor aangeleverde tekst. Verstuur één passage of een lijst en bewaar de antwoordindexen wanneer je een doorzoekbare verzameling opbouwt.", "source": { "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1", "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036", "raw_model_json_sha256": "351d65a70607e6984bc3f6ffa2312596f9df51fbec28af0627de02585d203473", "renderer_sha256": "a5aefc67f30427b283b8d8bf7955908a0216c6e5e4ca3cc1887842431e2b1ee6" }, "sourceRevision": "a45c4cccc97017a108c713f7ccdb8cd7226b68db710b2f83289614350fa9a9f8" }