Make sure that you copy paste below code in a file with extension as .yaml.
#google #gemini #openapi
openapi: 3.0.3
info:
title: Gemini AI API
description: |
The Gemini API allows developers to build generative AI applications using Gemini models.
Gemini is multimodal and can understand text, images, audio, video, and code.
version: v1beta
contact:
name: Google AI
url: https://ai.google.dev
license:
name: Apache 2.0
url: https://www.apache.org/licenses/LICENSE-2.0
servers:
- url: https://generativelanguage.googleapis.com/v1beta
description: Gemini API Production Server
security:
- ApiKeyQuery: []
- ApiKeyHeader: []
tags:
- name: Models
description: Operations for listing and retrieving model information
- name: Content Generation
description: Generate content using Gemini models
- name: Embeddings
description: Generate text embeddings
- name: Token Counting
description: Count tokens in prompts
paths:
/models:
get:
tags: [Models]
operationId: listModels
summary: List available models
description: Lists the Gemini models available through the API
parameters:
- $ref: '#/components/parameters/PageSize'
- $ref: '#/components/parameters/PageToken'
responses:
'200':
description: Successful response
content:
application/json:
schema:
$ref: '#/components/schemas/ListModelsResponse'
/models/{model}:
get:
tags: [Models]
operationId: getModel
summary: Get model information
description: Gets information about a specific model
parameters:
- name: model
in: path
required: true
schema:
type: string
example: gemini-1.5-pro
responses:
'200':
description: Successful response
content:
application/json:
schema:
$ref: '#/components/schemas/Model'
/models/{model}:generateContent:
post:
tags: [Content Generation]
operationId: generateContent
summary: Generate content
description: Generates a model response given an input GenerateContentRequest
parameters:
- name: model
in: path
required: true
schema:
type: string
description: 'Model name (e.g., models/gemini-1.5-pro)'
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/GenerateContentRequest'
examples:
simpleText:
summary: Simple text generation
value:
contents:
- role: user
parts:
- text: "Explain quantum computing in simple terms"
responses:
'200':
description: Successful response
content:
application/json:
schema:
$ref: '#/components/schemas/GenerateContentResponse'
/models/{model}:streamGenerateContent:
post:
tags: [Content Generation]
operationId: streamGenerateContent
summary: Stream generate content
description: Generates a streamed response from the model
parameters:
- name: model
in: path
required: true
schema:
type: string
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/GenerateContentRequest'
responses:
'200':
description: Successful response (server-sent events)
content:
application/json:
schema:
$ref: '#/components/schemas/GenerateContentResponse'
/models/{model}:countTokens:
post:
tags: [Token Counting]
operationId: countTokens
summary: Count tokens
description: Counts the number of tokens in a prompt
parameters:
- name: model
in: path
required: true
schema:
type: string
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/CountTokensRequest'
responses:
'200':
description: Successful response
content:
application/json:
schema:
$ref: '#/components/schemas/CountTokensResponse'
/models/{model}:embedContent:
post:
tags: [Embeddings]
operationId: embedContent
summary: Generate embedding
description: Generates a text embedding vector from the input content
parameters:
- name: model
in: path
required: true
schema:
type: string
description: 'Model name (e.g., models/text-embedding-004)'
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/EmbedContentRequest'
responses:
'200':
description: Successful response
content:
application/json:
schema:
$ref: '#/components/schemas/EmbedContentResponse'
/models/{model}:batchEmbedContents:
post:
tags: [Embeddings]
operationId: batchEmbedContents
summary: Batch generate embeddings
description: Generates multiple embedding vectors from a batch of inputs
parameters:
- name: model
in: path
required: true
schema:
type: string
requestBody:
required: true
content:
application/json:
schema:
$ref: '#/components/schemas/BatchEmbedContentsRequest'
responses:
'200':
description: Successful response
content:
application/json:
schema:
$ref: '#/components/schemas/BatchEmbedContentsResponse'
components:
securitySchemes:
ApiKeyQuery:
type: apiKey
in: query
name: key
description: API key for authentication
ApiKeyHeader:
type: apiKey
in: header
name: x-goog-api-key
description: API key for authentication (preferred)
parameters:
PageSize:
name: pageSize
in: query
schema:
type: integer
maximum: 1000
description: Maximum number of results to return
PageToken:
name: pageToken
in: query
schema:
type: string
description: Token for pagination
schemas:
Model:
type: object
properties:
name:
type: string
description: 'Model resource name (e.g., models/gemini-1.5-pro)'
displayName:
type: string
description:
type: string
inputTokenLimit:
type: integer
format: int32
outputTokenLimit:
type: integer
format: int32
supportedGenerationMethods:
type: array
items:
type: string
example: ["generateContent", "countTokens"]
ListModelsResponse:
type: object
properties:
models:
type: array
items:
$ref: '#/components/schemas/Model'
nextPageToken:
type: string
GenerateContentRequest:
type: object
required:
- contents
properties:
contents:
type: array
items:
$ref: '#/components/schemas/Content'
description: The content of the conversation with the model
systemInstruction:
$ref: '#/components/schemas/Content'
description: Developer set system instructions
generationConfig:
$ref: '#/components/schemas/GenerationConfig'
safetySettings:
type: array
items:
$ref: '#/components/schemas/SafetySetting'
GenerateContentResponse:
type: object
properties:
candidates:
type: array
items:
$ref: '#/components/schemas/Candidate'
usageMetadata:
$ref: '#/components/schemas/UsageMetadata'
Content:
type: object
properties:
role:
type: string
enum: [user, model]
description: The producer of the content
parts:
type: array
items:
$ref: '#/components/schemas/Part'
Part:
type: object
description: A part of multi-part content
properties:
text:
type: string
description: Inline text content
inlineData:
$ref: '#/components/schemas/Blob'
fileData:
$ref: '#/components/schemas/FileData'
Blob:
type: object
required:
- mimeType
- data
properties:
mimeType:
type: string
example: "image/jpeg"
data:
type: string
format: byte
description: Base64 encoded data
FileData:
type: object
required:
- fileUri
properties:
mimeType:
type: string
fileUri:
type: string
description: URI of the file
Candidate:
type: object
properties:
content:
$ref: '#/components/schemas/Content'
finishReason:
type: string
enum: [STOP, MAX_TOKENS, SAFETY, RECITATION, OTHER]
safetyRatings:
type: array
items:
$ref: '#/components/schemas/SafetyRating'
GenerationConfig:
type: object
properties:
temperature:
type: number
format: float
minimum: 0
maximum: 2
description: Controls randomness
topP:
type: number
format: float
topK:
type: integer
format: int32
maxOutputTokens:
type: integer
format: int32
stopSequences:
type: array
items:
type: string
SafetySetting:
type: object
required:
- category
- threshold
properties:
category:
type: string
enum:
- HARM_CATEGORY_HARASSMENT
- HARM_CATEGORY_HATE_SPEECH
- HARM_CATEGORY_SEXUALLY_EXPLICIT
- HARM_CATEGORY_DANGEROUS_CONTENT
threshold:
type: string
enum:
- BLOCK_NONE
- BLOCK_ONLY_HIGH
- BLOCK_MEDIUM_AND_ABOVE
- BLOCK_LOW_AND_ABOVE
SafetyRating:
type: object
properties:
category:
type: string
probability:
type: string
enum: [NEGLIGIBLE, LOW, MEDIUM, HIGH]
UsageMetadata:
type: object
properties:
promptTokenCount:
type: integer
candidatesTokenCount:
type: integer
totalTokenCount:
type: integer
CountTokensRequest:
type: object
properties:
contents:
type: array
items:
$ref: '#/components/schemas/Content'
CountTokensResponse:
type: object
properties:
totalTokens:
type: integer
EmbedContentRequest:
type: object
required:
- content
properties:
content:
$ref: '#/components/schemas/Content'
taskType:
type: string
enum:
- RETRIEVAL_QUERY
- RETRIEVAL_DOCUMENT
- SEMANTIC_SIMILARITY
- CLASSIFICATION
- CLUSTERING
EmbedContentResponse:
type: object
properties:
embedding:
$ref: '#/components/schemas/ContentEmbedding'
ContentEmbedding:
type: object
properties:
values:
type: array
items:
type: number
format: float
BatchEmbedContentsRequest:
type: object
required:
- requests
properties:
requests:
type: array
items:
$ref: '#/components/schemas/EmbedContentRequest'
BatchEmbedContentsResponse:
type: object
properties:
embeddings:
type: array
items:
$ref: '#/components/schemas/ContentEmbedding'
