# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Hugging Face Inference Providers Embeddings API
  version: 1.0.0
extends: openapi/hugging-face-embeddings-api-openapi.yml
actions:
- target: $.info
  update:
    x-apievangelist-phrasing:
      method: generated
      generated: '2026-10-01'
      generator: build-phrasing.py
      label: Generated by API Evangelist
      operations: 1
- target: $.paths['/v1/embeddings'].post
  update:
    x-apievangelist-phrasing:
      intent: Create text embedding vectors
      effect: write
      questions:
      - Can I turn sentences into dense vectors for semantic search with a Hugging Face embedding model?
      - Is it possible to embed several texts in a single request?
      - What encoding formats can the embedding vectors be returned in?
      instructions:
      - text: Embed {input} with model {model}.
        slots:
          input: requestBody.input
          model: requestBody.model
      - text: Create embeddings for {input} using {model} and return them as {encoding_format}.
        slots:
          input: requestBody.input
          model: requestBody.model
          encoding_format: requestBody.encoding_format
      method: generated
      generated: '2026-10-01'