{ "aboutHtml": "

Selecteer Baichuan-Text-Embedding in een /v1/embeddings-request. De vereiste input accepteert een niet-lege string of een niet-lege array met 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 behouden die een latere lezer nodig heeft. Beheer document-ID’s in uw applicatie en koppel elke vector aan zijn positie in de ingediende invoer. Een zoekworkflow kan de vraag van de gebruiker met hetzelfde model encoderen en de bronpassage bij elk opgehaald resultaat bewaren.

Sla de volledige synchrone response op voordat u de vectoren definitief opslaat. Controleer de koppeling tussen invoer en index, bewaar alle teruggegeven vectoren en houd usage bij de bewerking. Door de exacte modelidentiteit bij opgeslagen embeddings te gebruiken, blijft duidelijk welke verzameling en zoekvraagrepresentatie bij elkaar horen.

", "aboutText": "Selecteer Baichuan-Text-Embedding in een /v1/embeddings-request. De vereiste input accepteert een niet-lege string of een niet-lege array met 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 behouden die een latere lezer nodig heeft. Beheer document-ID’s in uw applicatie en koppel elke vector aan zijn positie in de ingediende invoer. Een zoekworkflow kan de vraag van de gebruiker met hetzelfde model encoderen en de bronpassage bij elk opgehaald resultaat bewaren.\n\nSla de volledige synchrone response op voordat u de vectoren definitief opslaat. Controleer de koppeling tussen invoer en index, bewaar alle teruggegeven vectoren en houd usage bij de bewerking. Door de exacte modelidentiteit bij opgeslagen embeddings te gebruiken, blijft duidelijk welke verzameling en zoekvraagrepresentatie bij elkaar horen.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "acbcb10ecb85612c5a7516ed9b3e8c5436cfb0053554d9f0eb3cee708b0634cb", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "nl", "methods": [ { "html": "
•

Baichuan-Text-Embedding

Overig /Baichuan-Text-Embedding

Aan de slag

Baichuan-Text-Embedding geeft via de embeddings-API van Ailoot numerieke vectoren terug voor aangeleverde tekst. Stuur één passage of een lijst en bewaar de response-indices bij het opbouwen van een doorzoekbare verzameling.

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 /v1/embeddings-request. De vereiste input accepteert een niet-lege string of een niet-lege array met 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 behouden die een latere lezer nodig heeft. Beheer document-ID’s in uw applicatie en koppel elke vector aan zijn positie in de ingediende invoer. Een zoekworkflow kan de vraag van de gebruiker met hetzelfde model encoderen en de bronpassage bij elk opgehaald resultaat bewaren.

Sla de volledige synchrone response op voordat u de vectoren definitief opslaat. Controleer de koppeling tussen invoer en index, bewaar alle teruggegeven vectoren en houd usage bij de bewerking. Door de exacte modelidentiteit bij opgeslagen embeddings te gebruiken, blijft duidelijk welke verzameling en zoekvraagrepresentatie bij elkaar horen.

Beschikbaar in Ailoot · invoer en methoden

Ailoot Ultra · Embeddings POST /v1/embeddings
Invoertypen
text
Uitvoertypen
embedding
VeldTypeVereisteWaarden en limietenStandaard
VeldmodelTypestringVereisteVereistWaarden en limieten
Baichuan-Text-Embedding
Voorwaarden: Gebruik exact 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 exact 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 is geselecteerd
Flexmodus
Niet opgegeven Wanneer de modus flex is geselecteerd
Maximale redeneerinspanning
Niet opgegeven Wanneer bij 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 geretourneerde validatiedetails voordat u een afzonderlijk verzoek voorbereidt.", "type": "invalid_request_error" }, { "condition": "Het oorspronkelijke verzoek of resultaat is onbekend of moet worden gecontroleerd.", "http_status": null, "recovery": "Bewaar de oorspronkelijke identificatoren en headers; lees alleen 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, respons en 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 identificaties, alle daadwerkelijke uitvoer en alle gebruiks-/afrekenvelden. Sla elke unieke asset op die u bezit 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 exact 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 exact 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": "786e0c3ed8daef747e28c8e0df9c9bc7bb79149fea035ce0b0f236908b7c13e3", "input_html_sha256": "766acec482dcf62825250bf58cfb151cdc6b57a08653132b3f50e844fbf3912c", "private_audit_sha256": "216fa40a574be60db9ca048e0f6e708bb96953cebfe60f2e5e59b4404a396966", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/nl/baichuan-text-embedding/", "description": "Baichuan-Text-Embedding geeft via de embeddings-API van Ailoot numerieke vectoren terug voor aangeleverde tekst. Stuur één passage of een lijst en bewaar de response-indices bij het opbouwen van een doorzoekbare verzameling.", "locale": "nl", "md_url": "https://ailoot.ai/models/nl/baichuan-text-embedding/index.md", "title": "Baichuan-Text-Embedding — Ailoot", "url": "https://ailoot.ai/models/nl/baichuan-text-embedding/" }, "rawModel": { "about": "Selecteer Baichuan-Text-Embedding in een /v1/embeddings-request. De vereiste input accepteert een niet-lege string of een niet-lege array met 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 behouden die een latere lezer nodig heeft. Beheer document-ID’s in uw applicatie en koppel elke vector aan zijn positie in de ingediende invoer. Een zoekworkflow kan de vraag van de gebruiker met hetzelfde model encoderen en de bronpassage bij elk opgehaald resultaat bewaren.\n\nSla de volledige synchrone response op voordat u de vectoren definitief opslaat. Controleer de koppeling tussen invoer en index, bewaar alle teruggegeven vectoren en houd usage bij de bewerking. Door de exacte modelidentiteit bij opgeslagen embeddings te gebruiken, blijft 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 geretourneerde validatiedetails voordat u een afzonderlijk verzoek voorbereidt.", "type": "invalid_request_error" }, { "condition": "Het oorspronkelijke verzoek of resultaat is onbekend of moet worden gecontroleerd.", "http_status": null, "recovery": "Bewaar de oorspronkelijke identificatoren en headers; lees alleen 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, respons en 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 identificaties, alle daadwerkelijke uitvoer en alle gebruiks-/afrekenvelden. Sla elke unieke asset op die u bezit 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 exact 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 exact 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 de embeddings-API van Ailoot numerieke vectoren terug voor aangeleverde tekst. Stuur één passage of een lijst en bewaar de response-indices bij het opbouwen van een doorzoekbare verzameling.", "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 de embeddings-API van Ailoot numerieke vectoren terug voor aangeleverde tekst. Stuur één passage of een lijst en bewaar de response-indices bij het opbouwen van een doorzoekbare verzameling.", "source": { "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1", "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036", "raw_model_json_sha256": "0a5c20f712e2db754b6e12889293d982c5f81567d9cbc1421db6c9a19e1a767b", "renderer_sha256": "be7649af06bb0ae446191041c6cfb8a9b83a53896c8c6e9173e76a39d513e829" }, "sourceRevision": "ebacde5427e8b50c71e8f386ac78d9aac948a41a89091bf8d6279b43fed26768" }