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OpenAPI Specification
openapi: 3.2.0
info:
title: Jina AI Embeddings API
description: Generate high-quality multimodal embeddings for text, image, and code inputs using Jina AI's state-of-the-art embedding models. Supports synchronous embedding requests and batch jobs for large workloads.
version: '1.0'
contact:
name: Jina AI
url: https://jina.ai
servers:
- url: https://api.jina.ai/v1
description: Jina AI production API
security:
- BearerAuth: []
tags:
- name: Embeddings
description: Synchronous embedding generation
paths:
/embeddings:
post:
tags:
- Embeddings
summary: Create embeddings
description: Generate vector embeddings for one or more text, image, or code inputs.
operationId: createEmbeddings
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/EmbeddingRequest'
responses:
'200':
description: Embeddings successfully generated
content:
application/json:
schema:
$ref: '#/components/schemas/EmbeddingResponse'
'401':
description: Unauthorized
'429':
description: Rate limit exceeded
components:
schemas:
EmbeddingObject:
type: object
properties:
object:
type: string
example: embedding
index:
type: integer
embedding:
type: array
items:
type: number
format: float
Usage:
type: object
properties:
total_tokens:
type: integer
prompt_tokens:
type: integer
EmbeddingRequest:
type: object
required:
- model
- input
properties:
model:
type: string
description: Embedding model identifier
example: jina-embeddings-v4
enum:
- jina-embeddings-v5-text-small
- jina-embeddings-v5-text-nano
- jina-embeddings-v4
- jina-embeddings-v3
- jina-clip-v2
input:
type: array
description: Inputs to embed (text strings or image references)
items:
type: string
task:
type: string
description: Downstream task to optimize the embedding for
enum:
- retrieval.query
- retrieval.passage
- text-matching
- classification
- clustering
dimensions:
type: integer
description: Optional truncation length for output vectors
normalized:
type: boolean
description: Whether to L2-normalize the output vectors
embedding_type:
type: string
enum:
- float
- base64
- binary
- ubinary
EmbeddingResponse:
type: object
properties:
model:
type: string
object:
type: string
example: list
usage:
$ref: '#/components/schemas/Usage'
data:
type: array
items:
$ref: '#/components/schemas/EmbeddingObject'
securitySchemes:
BearerAuth:
type: http
scheme: bearer
bearerFormat: API Key