{ "aboutHtml": "

BAAI/bge-large-zh-v1.5 is de Chinese editie van BAAI General Embedding v1.5. Kies dit model voor een Chineestalige zoekindex, bijvoorbeeld om een klantvraag aan de juiste alinea uit het retourbeleid te koppelen. Het resultaat is een numerieke vector voor gelijkeniszoeken, geen gegenereerd antwoord. De officiële modelkaart vermeldt de Chinese taalfocus en beschrijft v1.5 als een verbetering van de gelijkenisverdeling.

Ailoot accepteert op /v1/embeddings één tekenreeks of een array van tekenreeksen. Gebruik deze exacte editie voor passages én zoekvragen en koppel elke data[].embedding aan data[].index. Voor korte vragen die passages moeten vinden raadt BAAI een zoekinstructie bij de vraag aan; passages krijgen geen voorvoegsel. Kalibreer gelijkenisdrempels op je eigen materiaal: een score is geen kans dat de passage de vraag beantwoordt. Zie de BAAI-modelkaart voor de vraagconventie.

", "aboutText": "BAAI/bge-large-zh-v1.5 is de Chinese editie van BAAI General Embedding v1.5. Kies dit model voor een Chineestalige zoekindex, bijvoorbeeld om een klantvraag aan de juiste alinea uit het retourbeleid te koppelen. Het resultaat is een numerieke vector voor gelijkeniszoeken, geen gegenereerd antwoord. De officiële modelkaart vermeldt de Chinese taalfocus en beschrijft v1.5 als een verbetering van de gelijkenisverdeling. Ailoot accepteert op /v1/embeddings één tekenreeks of een array van tekenreeksen. Gebruik deze exacte editie voor passages én zoekvragen en koppel elke data[].embedding aan data[].index. Voor korte vragen die passages moeten vinden raadt BAAI een zoekinstructie bij de vraag aan; passages krijgen geen voorvoegsel. Kalibreer gelijkenisdrempels op je eigen materiaal: een score is geen kans dat de passage de vraag beantwoordt. Zie de BAAI-modelkaart voor de vraagconventie.", "editorialOverlay": { "copy_fields": { "about_html": "

BAAI/bge-large-zh-v1.5 is de Chinese editie van BAAI General Embedding v1.5. Kies dit model voor een Chineestalige zoekindex, bijvoorbeeld om een klantvraag aan de juiste alinea uit het retourbeleid te koppelen. Het resultaat is een numerieke vector voor gelijkeniszoeken, geen gegenereerd antwoord. De officiële modelkaart vermeldt de Chinese taalfocus en beschrijft v1.5 als een verbetering van de gelijkenisverdeling.

Ailoot accepteert op /v1/embeddings één tekenreeks of een array van tekenreeksen. Gebruik deze exacte editie voor passages én zoekvragen en koppel elke data[].embedding aan data[].index. Voor korte vragen die passages moeten vinden raadt BAAI een zoekinstructie bij de vraag aan; passages krijgen geen voorvoegsel. Kalibreer gelijkenisdrempels op je eigen materiaal: een score is geen kans dat de passage de vraag beantwoordt. Zie de BAAI-modelkaart voor de vraagconventie.

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•

BAAI/bge-large-zh-v1.5

Overig /BAAI/bge-large-zh-v1.5

Aan de slag

Chinese embeddings van BAAI voor passagezoeken, via tekst-naar-vectorverzoeken in Ailoot.

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.

BAAI/bge-large-zh-v1.5 is de Chinese editie van BAAI General Embedding v1.5. Kies dit model voor een Chineestalige zoekindex, bijvoorbeeld om een klantvraag aan de juiste alinea uit het retourbeleid te koppelen. Het resultaat is een numerieke vector voor gelijkeniszoeken, geen gegenereerd antwoord. De officiële modelkaart vermeldt de Chinese taalfocus en beschrijft v1.5 als een verbetering van de gelijkenisverdeling.

Ailoot accepteert op /v1/embeddings één tekenreeks of een array van tekenreeksen. Gebruik deze exacte editie voor passages én zoekvragen en koppel elke data[].embedding aan data[].index. Voor korte vragen die passages moeten vinden raadt BAAI een zoekinstructie bij de vraag aan; passages krijgen geen voorvoegsel. Kalibreer gelijkenisdrempels op je eigen materiaal: een score is geen kans dat de passage de vraag beantwoordt. Zie de BAAI-modelkaart voor de vraagconventie.

Beschikbaar in Ailoot · invoer en methoden

Ailoot Ultra · Embeddings POST /v1/embeddings
Invoer
text
Uitvoer
embedding
VeldTypeVereisteWaarden en limietenStandaard
VeldmodelTypestringVereisteVereistWaarden en limieten
BAAI/bge-large-zh-v1.5
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 $0.00004 / 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": "BAAI/bge-large-zh-v1.5", "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 BAAI/bge-large-zh-v1.5

Aliasnamen voor methodepaden

Gebruik de hierboven getoonde methodepaden.

Gerelateerde aanroeper-ID’s

BAAI/bge-large-zh-v1.5

", "method_identity": { "effective_request_model_id": "BAAI/bge-large-zh-v1.5", "fmt": "embeddings", "http": "POST", "path": "/v1/embeddings", "request_model_id": "BAAI/bge-large-zh-v1.5", "route_label": "Ultra" }, "method_key": "Ultra|embeddings|/v1/embeddings|BAAI%2Fbge-large-zh-v1.5", "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": [ "BAAI/bge-large-zh-v1.5" ], "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": [ "BAAI/bge-large-zh-v1.5" ], "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": "BAAI/bge-large-zh-v1.5" }, "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": "0.00004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000004", "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\": \"BAAI/bge-large-zh-v1.5\", \"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": 0.04, "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": "0.00004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000004", "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": "BAAI/bge-large-zh-v1.5", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.00004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000004", "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": "BAAI/bge-large-zh-v1.5", "nativeProvenance": { "input_facts_canonical_sha256": "15e2d42e84e213d61a8373b540606f41b2f1ff291b60ef58fda3f0fc90ce429a", "input_html_sha256": "8e564a8d7f211c79e1bd4ab70f2fbc61b633fbd37eb77c6f7b303277baede7cc", "private_audit_sha256": "4f60d96acdb04b3c886df20baa06da71dccad95d9b4c52305d9f7fc79ce8f7e4", "role": "historical-normalized-input-audit-hashes", "schema": "ailoot-native-model-provenance-v2" }, "page": { "canonical": "https://ailoot.ai/models/nl-be/baai-bge-large-zh-v1-5/", "description": "Chinese embeddings van BAAI voor passagezoeken, via tekst-naar-vectorverzoeken in Ailoot.", "locale": "nl-be", "md_url": "https://ailoot.ai/models/nl-be/baai-bge-large-zh-v1-5/index.md", "title": "BAAI/bge-large-zh-v1.5 — Ailoot", "url": "https://ailoot.ai/models/nl-be/baai-bge-large-zh-v1-5/" }, "rawModel": { "about": "BAAI/bge-large-zh-v1.5 gebruikt /v1/embeddings met model en input. Geef de exacte model-ID mee en ofwel één niet-lege tekststring, ofwel een niet-lege array van tekststrings. Het JSON-antwoord bevat data-items met index en embedding, samen met informatie over model en usage.\n\nBereid voor een documentindex samenhangende passages voor en bewaar je eigen document- en segment-ID’s bij de verstuurde strings. Koppel elke teruggegeven vector aan zijn data[].index in plaats van de bewoording van een passage als identificatie te gebruiken. Codeer een zoekopdracht met hetzelfde geselecteerde model wanneer je toepassing die met geïndexeerd materiaal vergelijkt.\n\nHet endpoint geeft vectoren synchroon terug. Bewaar elk data-item en het volledige usage-record voordat je de index bijwerkt. Controleer of de teruggegeven indexen het verstuurde materiaal afdekken en sla de oorspronkelijke tekst en model-ID samen met de vectoren op, zodat latere zoekresultaten naar hun bronpassages kunnen worden herleid.", "alias_of": null, "aliases": [], "card_routes": [ { "label": "Ultra", "rates": [ { "amount": "0.00004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000004", "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": "BAAI/bge-large-zh-v1.5", "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": [ "BAAI/bge-large-zh-v1.5" ], "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": [ "BAAI/bge-large-zh-v1.5" ], "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": "BAAI/bge-large-zh-v1.5" }, "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": "0.00004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000004", "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\": \"BAAI/bge-large-zh-v1.5\", \"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": 0.04, "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": "0.00004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000004", "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": "BAAI/bge-large-zh-v1.5", "route_label": "Ultra", "status_reads": [], "tiers": [], "units": [ { "amount": "0.00004000", "amount_unit": "usd_per_thousand_tokens", "billing_input": true, "estimate_only": false, "key": "input_price", "label": "Input tokens", "native_amount_usd_per_unit": "0.00000004", "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": "BAAI/bge-large-zh-v1.5", "request_model_id": "BAAI/bge-large-zh-v1.5", "route_label": "Ultra" } ], "name": "BAAI/bge-large-zh-v1.5", "price": { "in": 0.04, "in_label": null, "out": 0, "out_label": null, "scope_label": "Token rates", "sort_in": 0.04, "sort_out": 0, "varies": false }, "short": "BAAI/bge-large-zh-v1.5 zet via Ailoot een tekststring of lijst met strings om in numerieke embeddings. Bewaar elke vector met zijn invoerindex voor workflows rond zoeken en documentindexering.", "title": "BAAI/bge-large-zh-v1.5" }, "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": "Chinese embeddings van BAAI voor passagezoeken, via tekst-naar-vectorverzoeken in Ailoot.", "source": { "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1", "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036", "raw_model_json_sha256": "2e1cc215794c7de498e6aabe08c73f16e2d368146afa6335cfed11c194e8eb68", "renderer_sha256": "a5aefc67f30427b283b8d8bf7955908a0216c6e5e4ca3cc1887842431e2b1ee6" }, "sourceRevision": "b26da30acbbe6706f11ccf57b7c27dfdd890ab77aebd5a4dbac9723ed87f1a2d" }