AIMLAPI Embeddings API
The Embeddings API from AIMLAPI — 1 operation(s) for embeddings.
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OpenAPI Specification
openapi: 3.2.0
info:
title: AIML Embeddings API
version: 1.0.0
servers:
- url: https://api.aimlapi.com
tags:
- name: Embeddings
paths:
/v1/embeddings:
post:
operationId: _v1_embeddings
requestBody:
required: true
content:
application/json:
schema:
anyOf:
- type: object
properties:
model:
type: string
enum:
- text-embedding-3-small
- openai/text-embedding-3-small
- text-embedding-3-large
- openai/text-embedding-3-large
input:
anyOf:
- type: string
minLength: 1
- type: array
items:
type: string
minItems: 1
description: Input text to embed, encoded as a string or array of tokens.
encoding_format:
type: string
enum:
- float
- base64
default: float
description: The format in which to return the embeddings.
dimensions:
type:
- number
- 'null'
minimum: 1
maximum: 3072
description: The number of dimensions for the embedding. Default is 1024.
required:
- model
- input
title: text-embedding-3-small, openai/text-embedding-3-small, text-embedding-3-large, openai/text-embedding-3-large
- type: object
properties:
model:
type: string
enum:
- text-embedding-ada-002
- openai/text-embedding-ada-002
input:
anyOf:
- type: string
minLength: 1
- type: array
items:
type: string
minItems: 1
description: Input text to embed, encoded as a string or array of tokens.
encoding_format:
type: string
enum:
- float
- base64
default: float
description: The format in which to return the embeddings.
required:
- model
- input
title: text-embedding-ada-002, openai/text-embedding-ada-002
- type: object
properties:
model:
type: string
enum:
- voyage-large-2-instruct
- anthropic/voyage-large-2-instruct
- voyage-finance-2
- anthropic/voyage-finance-2
- voyage-multilingual-2
- anthropic/voyage-multilingual-2
- voyage-law-2
- anthropic/voyage-law-2
- voyage-code-2
- anthropic/voyage-code-2
- voyage-large-2
- anthropic/voyage-large-2
- voyage-2
- anthropic/voyage-2
input:
anyOf:
- type: string
minLength: 1
maxLength: 8000
- type: array
items:
type: string
maxLength: 800
description: Input text to embed, encoded as a string or array of tokens.
input_type:
type: string
enum:
- document
default: document
description: The type of input data for the model.
required:
- model
- input
title: voyage-large-2-instruct, anthropic/voyage-large-2-instruct, voyage-finance-2, anthropic/voyage-finance-2, voyage-multilingual-2, anthropic/voyage-multilingual-2, voyage-law-2, anthropic/voyage-law-2, voyage-code-2, anthropic/voyage-code-2, voyage-large-2, anthropic/voyage-large-2, voyage-2, anthropic/voyage-2
- type: object
properties:
model:
type: string
enum:
- text-multilingual-embedding-002
- google/text-multilingual-embedding-002
input:
anyOf:
- type: string
minLength: 1
- type: array
items:
type: string
minItems: 1
description: Input text to embed, encoded as a string or array of tokens.
dimensions:
type:
- number
- 'null'
minimum: 1
maximum: 768
description: The number of dimensions for the embedding. Default is 1024.
auto_truncate:
type: boolean
default: true
description: If enabled, this parameter automatically truncates the input text to fit within the model’s maximum token limit. It helps ensure that longer texts are processed without errors.
task_type:
type: string
enum:
- RETRIEVAL_QUERY
- RETRIEVAL_DOCUMENT
- SEMANTIC_SIMILARITY
- CLASSIFICATION
- CLUSTERING
- QUESTION_ANSWERING
- FACT_VERIFICATION
description: Optional task type for which the embeddings will be used.
title:
type: string
description: "An optional title for the text. Only applicable when task_type is RETRIEVAL_DOCUMENT.\n \n Note: Specifying a title for RETRIEVAL_DOCUMENT provides better quality embeddings for retrieval."
required:
- model
- input
title: text-multilingual-embedding-002, google/text-multilingual-embedding-002
- type: object
properties:
model:
type: string
enum:
- text-embedding-v4
- alibaba/text-embedding-v4
- text-embedding-v3
- alibaba/text-embedding-v3
- alibaba/qwen-text-embedding-v4
- alibaba/qwen-text-embedding-v3
input:
anyOf:
- type: string
minLength: 1
- type: array
items:
type: string
minItems: 1
description: Input text to embed, encoded as a string or array of tokens.
dimensions:
type: integer
minimum: 64
maximum: 2048
default: 1024
description: The number of dimensions for the embedding. Default is 1024.
required:
- model
- input
title: text-embedding-v4, alibaba/text-embedding-v4, text-embedding-v3, alibaba/text-embedding-v3, alibaba/qwen-text-embedding-v4, alibaba/qwen-text-embedding-v3
- type: object
properties:
model:
type: string
enum:
- test/dummy-embeddings
input:
anyOf:
- type: string
minLength: 1
- type: array
items:
type: string
minItems: 1
encoding_format:
type: string
enum:
- float
- base64
dimensions:
type: number
minimum: 1
maximum: 3072
test:
type: object
properties:
credits:
type: number
delay:
type: number
errorStatus:
type: number
required:
- model
- input
title: test/dummy-embeddings
responses:
'200':
content:
application/json:
schema:
type: object
properties:
object:
type: string
enum:
- object
data:
type: array
items:
type: object
properties:
object:
type: string
enum:
- embedding
index:
type: number
embedding:
type: array
items:
type: number
required:
- object
- index
- embedding
model:
type: string
usage:
type: object
properties:
total_tokens:
type:
- number
- 'null'
meta:
type:
- object
- 'null'
properties:
usage:
type:
- object
- 'null'
properties:
credits_used:
type: number
description: The number of tokens consumed during generation.
example: 120000
usd_spent:
type: number
description: The total amount of money spent by the user in USD.
example: 0.06
required:
- credits_used
- usd_spent
required:
- object
- data
- model
- usage
tags:
- Embeddings
summary: V1 embeddings
x-summary-source: derived