> ## Documentation Index > Fetch the complete documentation index at: https://docs.octen.ai/llms.txt > Use this file to discover all available pages before exploring further. # Embedding > Converts text into vector representations. Supports batch input, multiple models, and configurable output dimensions. ## OpenAPI ````yaml /api-reference/openapi.json post /embedding openapi: 3.1.0 info: title: Octen API description: >- Octen API provides Search, Extract, Embeddings, VL Embeddings, Web Chat, Broad Search, and Deep Research services. The Search API searches ranked web results with optional filters, highlights, and full content. The Extract API extracts clean markdown content from URLs, with optional query-focused highlights, page classification, and multimedia resources. The Embeddings API converts text into vector representations. The VL Embeddings API converts multimodal inputs (text, images, videos) into vector representations. The Web Chat API provides LLM chat completions with search augmentation. The Broad Search API automatically decomposes queries into multiple sub-queries for comprehensive search and synthesis. The Deep Research API runs a multi-round adaptive research pipeline that produces a structured research plan, executes iterative web searches, builds a report brief with evidence, and streams a final long-form report. version: 1.0.0 servers: - url: https://api.octen.ai security: - apiKeyAuth: [] paths: /embedding: post: summary: Embedding description: >- Converts text into vector representations. Supports batch input, multiple models, and configurable output dimensions. operationId: Embedding requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/EmbeddingRequest' examples: singleInput: summary: Single Input value: input: - What is vector search? model: octen-embedding-8b dimension: 4096 input_type: query batchInput: summary: Batch Input value: input: - Vector databases store embeddings. - Embeddings enable semantic search. model: octen-embedding-0.6b input_type: document responses: '200': description: Successful embedding response content: application/json: schema: $ref: '#/components/schemas/EmbeddingResponse' example: code: 0 msg: success request_id: req_abc123def456 data: results: - index: 0 embedding: - 0.0123 - -0.0456 - 0.0789 - index: 1 embedding: - -0.0011 - 0.0234 - 0.0567 model: octen-embedding-0.6b meta: usage: input_tokens: 128 warning: Input was truncated for one or more items. '400': description: >- Missing required parameter — Returned when a required parameter is missing. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: code: 400 msg: Missing required parameter '401': $ref: '#/components/responses/Unauthorized' '403': $ref: '#/components/responses/InsufficientBalance' '429': $ref: '#/components/responses/RateLimited' '500': $ref: '#/components/responses/InternalError' components: schemas: EmbeddingRequest: type: object required: - input properties: input: type: array items: type: string default: - What is vector search? maxItems: 1000 description: >- The text to be converted into embeddings. Maximum tokens per element: 32768. Maximum request body size: 2MB model: type: string enum: - octen-embedding-0.6b - octen-embedding-4b - octen-embedding-8b default: octen-embedding-4b description: >- The embedding model used for this request. `octen-embedding-0.6b` (max dim: 1024) for cost/throughput priority; `octen-embedding-4b` (max dim: 2560) for most applications; `octen-embedding-8b` (max dim: 4096) for accuracy-critical tasks. dimension: type: integer description: >- The dimensionality of the output embedding vectors. Defaults to the model's max dimension (0.6b: 1024, 4b: 2560, 8b: 4096). If set to a value smaller than the model default, the embedding will be truncated to the first N values. Any positive integer ≤ model default dimension is allowed. input_type: type: string enum: - query - document nullable: true default: null description: >- Specifies whether the input is a query or a document for retrieval. Different values apply different internal prompts: `query` → "Represent the query for retrieving supporting" (prepended and counted in input_tokens); `document` and `null` mean no special prompt is applied. EmbeddingResponse: type: object properties: code: type: integer description: Business status code. 0 indicates success. msg: type: string description: A human-readable message describing the result. request_id: type: string description: The unique identifier for this request. data: $ref: '#/components/schemas/EmbeddingData' meta: $ref: '#/components/schemas/EmbeddingMeta' ErrorResponse: type: object properties: code: type: integer description: Business status code. Non-zero values indicate an error. msg: type: string description: A human-readable message describing the error. required: - code - msg EmbeddingData: type: object description: The main embedding response payload. properties: results: type: array description: A list of embedding results. Each item corresponds to one input. items: $ref: '#/components/schemas/EmbeddingResult' model: type: string description: The embedding model used for this request. EmbeddingMeta: type: object description: Additional metadata for the embedding request. properties: usage: $ref: '#/components/schemas/EmbeddingUsage' warning: type: string nullable: true description: Optional warning message (e.g. truncation applied). EmbeddingResult: type: object description: A single embedding result. properties: index: type: integer description: >- The position of the embedding in the input array (useful when input is a list). embedding: type: array items: type: number description: The generated embedding vector. EmbeddingUsage: type: object description: Usage information for the embedding request. properties: input_tokens: type: integer description: The number of input tokens processed in this request. responses: Unauthorized: description: Invalid API Key — Returned when the API key is missing or invalid. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: code: 401 msg: Invalid API Key InsufficientBalance: description: >- Insufficient balance in account — Returned when the account balance is insufficient to complete the request. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: code: 403 msg: Insufficient balance in account RateLimited: description: >- Exceeding the rate limit — Returned when the request exceeds the configured rate limit. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: code: 429 msg: Exceeding the rate limit InternalError: description: Internal error — Returned when an unexpected server-side error occurs. content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' example: code: 500 msg: Internal error securitySchemes: apiKeyAuth: type: apiKey in: header name: x-api-key description: >- API key used for request authentication. Obtain an API key before using the API. Note: A payment method is required to use the API. ````