Prodia

This page adapts the original AI SDK documentation: Prodia.

Prodia is a fast inference platform for generative AI, offering high-speed image generation with FLUX and Stable Diffusion models.

Setup

The Prodia provider is available in the ProdiaProvider module. Add it to your Swift package:

// Package.swift (excerpt)
dependencies: [
  .package(url: "https://github.com/teunlao/swift-ai-sdk", from: "0.14.1")
],
targets: [
  .target(
    name: "YourTarget",
    dependencies: [
      .product(name: "SwiftAISDK", package: "swift-ai-sdk"),
      .product(name: "ProdiaProvider", package: "swift-ai-sdk")
    ]
  )
]

Provider Instance

You can import the default provider instance prodia:

import SwiftAISDK
import ProdiaProvider

let model = prodia.image("inference.flux-fast.schnell.txt2img.v2")

If you need a customized setup, use createProdia and create a provider instance with your settings:

import ProdiaProvider

let prodia = createProdia(settings: ProdiaProviderSettings(
  apiKey: ProcessInfo.processInfo.environment["PRODIA_TOKEN"],
  baseURL: "https://inference.prodia.com/v2",
  headers: ["X-Custom-Header": "value"]
))

You can use the following optional settings to customize the Prodia provider instance:

• baseURL String

  Use a different URL prefix for API calls. The default prefix is https://inference.prodia.com/v2.

• apiKey String

  API key that is being sent using the Authorization header as a Bearer token. It defaults to the PRODIA_TOKEN environment variable.

• headers [String: String]

  Custom headers to include in the requests.

• fetch FetchFunction

  Custom fetch implementation (middleware) for testing or request interception.

Image Models

You can create Prodia image models using the .image() factory method. For more on image generation with the Swift AI SDK see Image Generation.

Basic Usage

import SwiftAISDK
import ProdiaProvider

let result = try await generateImage(
  model: prodia.image("inference.flux-fast.schnell.txt2img.v2"),
  prompt: "A cat wearing an intricate robe"
)

try result.image.data.write(to: URL(fileURLWithPath: "image.png"))

Model Capabilities

Prodia offers fast inference for various image generation models. Here are the supported model types:

Model	Description
inference.flux-fast.schnell.txt2img.v2	Fast FLUX Schnell model for text-to-image generation
inference.flux.schnell.txt2img.v2	FLUX Schnell model for text-to-image generation

Note: Prodia supports additional model IDs. Check the Prodia documentation for the full list of available models.

Image Size

You can specify the image size using the size parameter in WIDTHxHEIGHT format:

let result = try await generateImage(
  model: prodia.image("inference.flux-fast.schnell.txt2img.v2"),
  prompt: "A serene mountain landscape at sunset",
  size: "1024x768"
)

Provider Options

Prodia image models support additional options through the providerOptions.prodia object:

let result = try await generateImage(
  model: prodia.image("inference.flux-fast.schnell.txt2img.v2"),
  prompt: "A cat wearing an intricate robe",
  providerOptions: [
    "prodia": [
      "width": 1024,
      "height": 768,
      "steps": 4,
      "stylePreset": "cinematic"
    ]
  ]
)

The following provider options are supported:

• width number - Output width in pixels (256–1920). When set, this overrides any width derived from size.
• height number - Output height in pixels (256–1920). When set, this overrides any height derived from size.
• steps number - Number of computational iterations (1–4). More steps typically produce higher quality results.
• stylePreset string - Apply a visual theme to the output image. Supported presets: 3d-model, analog-film, anime, cinematic, comic-book, digital-art, enhance, fantasy-art, isometric, line-art, low-poly, neon-punk, origami, photographic, pixel-art, texture, craft-clay.
• loras string[] - Augment the output with up to 3 LoRA models.
• progressive boolean - When using JPEG output, return a progressive JPEG.

Seed

You can use the seed parameter to get reproducible results:

let result = try await generateImage(
  model: prodia.image("inference.flux-fast.schnell.txt2img.v2"),
  prompt: "A serene mountain landscape at sunset",
  seed: 12345
)

Provider Metadata

The generateImage response includes provider-specific metadata in providerMetadata["prodia"]?.images[]. Each image object may contain the following properties:

• jobId string - The unique identifier for the generation job.
• seed number - The seed used for generation. Useful for reproducing results.
• elapsed number - Generation time in seconds.
• iterationsPerSecond number - Processing speed metric.
• createdAt string - Timestamp when the job was created.
• updatedAt string - Timestamp when the job was last updated.

import SwiftAISDK
import ProdiaProvider

let result = try await generateImage(
  model: prodia.image("inference.flux-fast.schnell.txt2img.v2"),
  prompt: "A serene mountain landscape at sunset"
)

if let first = result.providerMetadata["prodia"]?.images.first,
   case let .object(fields) = first,
   case let .string(jobId)? = fields["jobId"] {
  print("Job ID:", jobId)
}