openapi: 3.0.0
info:
  title: Flux Model API
  description: API for generating images using the Flux model
  version: 1.0.0
servers:
  - url: https://http.flux.proxy.prod.s9t.link
    description: Flux DEV Endpoint 
paths:
  /model/infer/flux:
    post:
      summary: Generate images using the Flux model
      description: |
        This endpoint generates images based on a prompt using the Flux model, with optional parameters for customization.
      operationId: generateImage
      parameters:
        - in: header
          name: Authorization
          description: Bearer token for authentication
          required: true
          schema:
            type: string
            example: "Bearer "
      requestBody:
        required: true
        content:
          application/json:
            schema:
              type: object
              properties:
                prompt:
                  type: string
                  description: |
                    The prompt parameter is a string that defines the content or concept the Flux model should generate. 
                    It specifies the desired characteristics, theme, or scene of the image, guiding the model to produce a 
                    relevant output based on the input description.
                  example: "Futuristic city skyline, magnificent crystal clear picture. realistic skyscrapers"
                height:
                  type: integer
                  description: "Height of the generated image in pixels."
                  example: 1024
                width:
                  type: integer
                  description: "Width of the generated image in pixels."
                  example: 1024
                seed:
                  type: integer
                  description: |
                    The seed parameter is a random number that ensures reproducibility, producing the same output for 
                    identical inputs across multiple runs.
                  example: 129232030
                num_inference_steps:
                  type: integer
                  description: |
                    The Num_Inference_Steps parameter determines the number of iterations the model performs during image 
                    generation, with more steps improving image quality at the cost of increased processing time. 
                    The recommended number is 28.
                  example: 28
                num_images_per_prompt:
                  type: integer
                  description: |
                    The Num_images_per_prompt specifies the number of images the API should generate for a given input prompt. 
                    Each prompt can be associated with one or more images, depending on the value set for this parameter.
                  example: 1
                guidance_scale:
                  type: number
                  format: float
                  description: |
                    The guidance_scale controls how closely the model follows the input prompt. Higher values make the image stick 
                    more closely to the prompt, while lower values allow for more creative freedom. 
                    The recommended number is 3.
                  example: 3
                negative_prompt:
                  type: string
                  description: "Optional negative prompt to influence the model's generation."
                  example: "dystopian"
                controlnet_type:
                  type: string
                  description: "ControlNet type for additional model control."
                  example: "depth"
                image:
                  type: string
                  description: "URL of an input image to use for additional processing."
                  example: "https://test-bucket-invideo.s3.ap-south-1."
                lora_weights:
                  type: string
                  description: |
                    The lora_weights parameter points to the file containing the learned LoRA weights. Add the PublicURL of the LoRA weights 
                    obtained from the Simplismart Training Suite.
                  example: "https://example.com/lora-weights"
                lora_scale:
                  type: number
                  format: float
                  description: |
                    The lora_scale is set to 1, meaning the LoRA weights will have a full impact on adjusting the model.
                  example: 1.0
      responses:
        '200':
          description: "Successfully generated images"
          content:
            application/json:
              schema:
                type: object
                properties:
                  status:
                    type: string
                    description: "Request status"
                    example: "success"
                  data:
                    type: array
                    items:
                      type: string
                      description: "URL of the generated image"
                      example: "https://example.com/generated_image.png"
        '400':
          description: "Bad request, invalid parameters"
        '401':
          description: "Unauthorized, invalid or missing authentication"
        '500':
          description: "Internal server error"