Google Gemini

opencollection: 1.0.0
info:
  name: Google Gemini API
  version: v1beta
request:
  auth:
    type: apikey
    key: key
    value: '{{key}}'
    placement: query
items:
- info:
    name: Content Generation
    type: folder
  items:
  - info:
      name: Google Gemini Generates a model response given an input GenerateContentRequest. Refer to the text generation guide
        for detailed usage information. Input capabilities differ between models, including tuned models.
      type: http
    http:
      method: POST
      url: https://generativelanguage.googleapis.com/v1beta/models/:model:generateContent
      params:
      - name: model
        value: ''
        type: path
        description: 'The name of the Model to use for generating the completion. Format: models/{model}. Example: models/gemini-2.0-flash.'
      - name: key
        value: ''
        type: query
        description: API key for authentication.
      body:
        type: json
        data: '{}'
    docs: Generates a response from the model given an input. The input can include text, images, audio, video, and other
      multimodal content. The model processes the input according to its capabilities and returns generated content along
      with safety ratings and usage metadata.
  - info:
      name: Google Gemini Generates a streamed response from the model given an input GenerateContentRequest. Returns a stream
        of GenerateContentResponse chunks using server-sent events.
      type: http
    http:
      method: POST
      url: https://generativelanguage.googleapis.com/v1beta/models/:model:streamGenerateContent
      params:
      - name: model
        value: ''
        type: path
        description: 'The name of the Model to use for generating the completion. Format: models/{model}. Example: models/gemini-2.0-flash.'
      - name: key
        value: ''
        type: query
        description: API key for authentication.
      - name: alt
        value: ''
        type: query
        description: Set to 'sse' for server-sent events streaming.
      body:
        type: json
        data: '{}'
    docs: Generates a streamed response from the model. This endpoint behaves identically to generateContent but returns partial
      responses incrementally as server-sent events. Each event contains a GenerateContentResponse with one or more candidate
      content parts. Use the alt=sse query parameter to enable streaming.
- info:
    name: Embeddings
    type: folder
  items:
  - info:
      name: Google Gemini Generates a text embedding vector from the input Content using the specified Gemini Embedding model.
      type: http
    http:
      method: POST
      url: https://generativelanguage.googleapis.com/v1beta/models/:model:embedContent
      params:
      - name: model
        value: ''
        type: path
        description: 'The model name to use for embedding. Format: models/{model}. Example: models/gemini-embedding-001.'
      - name: key
        value: ''
        type: query
        description: API key for authentication.
      body:
        type: json
        data: '{}'
    docs: Generates an embedding from the model given input content. The embedding is a vector representation of the input
      text that captures semantic meaning. Embeddings can be used for semantic search, text classification, clustering, and
      retrieval tasks. Only the text parts of the input content are used for embedding generation.
bundled: true