> ## Documentation Index > Fetch the complete documentation index at: https://developers.meshapi.ai/llms.txt > Use this file to discover all available pages before exploring further. # Create Embeddings > Turn text into embedding vectors. OpenAI-compatible: point the OpenAI SDK's embeddings client at this gateway and it works unchanged. `input` takes a single string or a batch, and the response keeps the input order so you can zip results back to your records. `model` is required and must name a specific embedding model — `auto` is rejected, because a vector is only comparable to other vectors from the same model, so silently choosing one for you would corrupt an index. Provider failover and BYOK keys apply as they do to chat. ## OpenAPI ````yaml /api/openapi.json post /v1/embeddings openapi: 3.1.0 info: title: MeshAPI description: One key, all AI models. version: 0.1.0 servers: - url: https://api.meshapi.ai security: - BearerAuth: [] paths: /v1/embeddings: post: tags: - Embeddings summary: Create Embeddings description: >- Turn text into embedding vectors. OpenAI-compatible: point the OpenAI SDK's embeddings client at this gateway and it works unchanged. `input` takes a single string or a batch, and the response keeps the input order so you can zip results back to your records. `model` is required and must name a specific embedding model — `auto` is rejected, because a vector is only comparable to other vectors from the same model, so silently choosing one for you would corrupt an index. Provider failover and BYOK keys apply as they do to chat. operationId: create_embeddings parameters: - in: header name: X-Mesh-Version required: false schema: type: string enum: - 2026-08 default: 2026-08 example: 2026-08 description: >- Dated version of the API contract to pin this request to. Omit it and the request is served under `2026-08` — the oldest supported version, so an existing integration is never moved by a release. A malformed or unsupported value is rejected with `400 invalid_api_version` rather than falling back silently. The version actually served is echoed as `X-Mesh-Version` on every response, including errors. requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/EmbeddingsRequest' examples: default: summary: Example request value: model: openai/text-embedding-3-small input: The quick brown fox jumps over the lazy dog. responses: '200': description: Embedding response content: application/json: schema: {} examples: default: summary: Successful embedding response value: object: list data: - object: embedding index: 0 embedding: - -0.03264831379055977 - -0.03786936774849892 - 0.007462255656719208 model: amazon/titan-embed-text-v2 usage: prompt_tokens: 3 total_tokens: 3 '400': description: Model does not support embeddings API content: application/json: example: error: code: model_capability_not_supported message: Model 'gpt-4o' does not support the embeddings API. request_id: req_01ARZ3NDEKTSV4RRFFQ69G5FAV '401': description: Missing or invalid API key content: application/json: example: error: code: unauthorized message: Invalid or missing API key. request_id: req_01ARZ3NDEKTSV4RRFFQ69G5FAV '402': description: Insufficient balance or spend cap reached content: application/json: examples: spend_cap_reached: summary: Per-key spend cap reached value: error: code: spend_limit_exceeded message: >- Spend cap of $10.0000 reached. Current spend: $10.0023. Contact your administrator to increase the cap. request_id: req_01ARZ3NDEKTSV4RRFFQ69G5FAV no_balance: summary: Insufficient credit balance value: error: code: spend_limit_exceeded message: >- Insufficient balance. Top up your account to use paid models. request_id: req_01ARZ3NDEKTSV4RRFFQ69G5FAV '403': description: API key is suspended content: application/json: example: error: code: forbidden message: API key is suspended. request_id: req_01ARZ3NDEKTSV4RRFFQ69G5FAV '422': description: Request validation failed content: application/json: example: error: code: validation_error message: Request validation failed. details: - type: missing loc: - body - input msg: Field required request_id: req_01ARZ3NDEKTSV4RRFFQ69G5FAV '429': description: Rate limit exceeded (RPM or RPD) content: application/json: examples: rpm_exceeded: summary: Requests-per-minute limit hit value: error: code: rate_limit_exceeded message: RPM limit of 60 req/min exceeded. request_id: req_01ARZ3NDEKTSV4RRFFQ69G5FAV rpd_exceeded: summary: Requests-per-day limit hit value: error: code: rate_limit_exceeded message: RPD limit of 1000 req/day exceeded. request_id: req_01ARZ3NDEKTSV4RRFFQ69G5FAV '500': description: Upstream provider error or gateway timeout content: application/json: examples: upstream_error: summary: Upstream provider returned an error value: error: code: upstream_error message: Upstream provider returned an error. upstream_detail: >- {"error":{"message":"Input too large for model","code":413}} request_id: req_01ARZ3NDEKTSV4RRFFQ69G5FAV gateway_timeout: summary: Upstream timed out value: error: code: gateway_timeout message: Upstream provider did not respond in time. request_id: req_01ARZ3NDEKTSV4RRFFQ69G5FAV internal_error: summary: >- Internal platform error (DB failure — FastAPI default format) value: detail: Internal Server Error '503': description: Upstream provider temporarily unavailable content: application/json: example: error: code: provider_not_available message: >- The model provider is temporarily unavailable. Please try again shortly. request_id: req_01ARZ3NDEKTSV4RRFFQ69G5FAV security: - BearerAuth: [] components: schemas: EmbeddingsRequest: properties: model: anyOf: - type: string - type: 'null' title: Model description: Model ID to use for embedding, e.g. `perplexity/pplx-embed-v1-4b`. examples: - perplexity/pplx-embed-v1-4b - openai/text-embedding-3-small input: anyOf: - type: string - items: type: string type: array - items: type: integer type: array - items: items: type: integer type: array type: array - items: $ref: '#/components/schemas/MultimodalEmbeddingInput' type: array title: Input description: >- Text(s) to embed. Accepts a string, list of strings, list of token IDs, list of token ID lists, or a list of MultimodalEmbeddingInput objects (for BytePlus multimodal embedding models). dimensions: anyOf: - type: integer minimum: 1 - type: 'null' title: Dimensions description: >- Number of dimensions for the output embedding vector (model-dependent). encoding_format: anyOf: - type: string enum: - float - base64 - type: 'null' title: Encoding Format description: Format of the returned embedding. Defaults to `float`. input_type: anyOf: - type: string - type: 'null' title: Input Type description: >- Intended use of the embedding, e.g. `query` or `document`. Some models use this to apply asymmetric embedding. provider: anyOf: - type: string - $ref: '#/components/schemas/ProviderPreferences' - type: 'null' title: Provider description: >- Provider routing preferences. Pass a provider slug string (e.g. `'perplexity'`) or a `ProviderPreferences` object to control fallback and ordering behaviour. user: anyOf: - type: string maxLength: 256 - type: 'null' title: User description: End-user identifier for abuse monitoring. instructions: anyOf: - type: string - type: 'null' title: Instructions description: >- Inference prompt for BytePlus multimodal embeddings. A default is generated from the input modality if not set. sparse_embedding: anyOf: - additionalProperties: true type: object - type: 'null' title: Sparse Embedding description: >- Sparse vector switch for BytePlus text embeddings. Pass {"type": "enabled"} to return both dense and sparse vectors, or {"type": "disabled"} for dense only. type: object required: - input title: EmbeddingsRequest description: |- Request body for `POST /v1/embeddings`. Mirrors the OpenAI embeddings API. The `input` field accepts four shapes: - **string** — a single text to embed - **list[string]** — a batch of texts - **list[int]** — a single pre-tokenised input (token IDs) - **list[list[int]]** — a batch of pre-tokenised inputs example: input: Hello world model: amazon/titan-embed-text-v2 MultimodalEmbeddingInput: properties: type: type: string enum: - text - image_url - video_url title: Type text: anyOf: - type: string - type: 'null' title: Text image_url: anyOf: - $ref: '#/components/schemas/ImageEmbeddingUrl' - type: 'null' video_url: anyOf: - $ref: '#/components/schemas/VideoEmbeddingUrl' - type: 'null' type: object required: - type title: MultimodalEmbeddingInput description: >- A single item in a BytePlus multimodal embeddings input list. BytePlus /embeddings/multimodal accepts a list of typed content objects instead of plain strings. All items in one request are vectorized together as a single unit (e.g. one image + one text → one combined vector). ProviderPreferences: properties: order: anyOf: - items: type: string type: array - type: 'null' title: Order description: Preferred provider order, e.g. ['perplexity', 'openai']. allow_fallbacks: anyOf: - type: boolean - type: 'null' title: Allow Fallbacks description: Whether to fall back to other providers if the first is unavailable. require_parameters: anyOf: - type: boolean - type: 'null' title: Require Parameters description: Only use providers that support all requested parameters. data_collection: anyOf: - type: string enum: - allow - deny - type: 'null' title: Data Collection description: Control whether the provider may use the request for training. type: object title: ProviderPreferences description: Provider routing preferences. ImageEmbeddingUrl: properties: url: type: string title: Url type: object required: - url title: ImageEmbeddingUrl VideoEmbeddingUrl: properties: url: type: string title: Url type: object required: - url title: VideoEmbeddingUrl securitySchemes: BearerAuth: type: http scheme: bearer description: >- Enter your MeshAPI key (`rsk_...`) — sent as `Authorization: Bearer `. ````