fal 0.3.6

A Rust crate for the fal.ai API, including generated, typed functions for all public models
Documentation 
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#[allow(unused_imports)]
use crate::prelude::*;
#[allow(unused_imports)]
use serde::{Deserialize, Serialize};
#[allow(unused_imports)]
use std::collections::HashMap;

#[derive(Debug, Serialize, Deserialize, Default)]
pub struct HTTPValidationError {
    #[serde(skip_serializing_if = "Option::is_none")]
    pub detail: Option<Vec<Option<ValidationError>>>,
}

#[derive(Debug, Serialize, Deserialize, Default)]
pub struct Image {
    /// The mime type of the file.
    /// "image/png"
    #[serde(skip_serializing_if = "Option::is_none")]
    pub content_type: Option<String>,
    /// File data
    #[serde(skip_serializing_if = "Option::is_none")]
    pub file_data: Option<String>,
    /// The name of the file. It will be auto-generated if not provided.
    /// "z9RV14K95DvU.png"
    #[serde(skip_serializing_if = "Option::is_none")]
    pub file_name: Option<String>,
    /// The size of the file in bytes.
    /// 4404019
    #[serde(skip_serializing_if = "Option::is_none")]
    pub file_size: Option<i64>,
    /// The height of the image in pixels.
    /// 1024
    #[serde(skip_serializing_if = "Option::is_none")]
    pub height: Option<i64>,
    /// The URL where the file can be downloaded from.
    pub url: String,
    /// The width of the image in pixels.
    /// 1024
    #[serde(skip_serializing_if = "Option::is_none")]
    pub width: Option<i64>,
}

#[derive(Debug, Serialize, Deserialize, Default)]
pub struct Input {
    /// Whether to perform prompt expansion (recommended)
    #[serde(skip_serializing_if = "Option::is_none")]
    pub expand_prompt: Option<bool>,
    /// Classifier free guidance scale
    #[serde(skip_serializing_if = "Option::is_none")]
    pub guidance_scale: Option<f64>,
    /// The number of images to generate
    #[serde(skip_serializing_if = "Option::is_none")]
    pub num_images: Option<i64>,
    /// The number of inference steps to take
    #[serde(skip_serializing_if = "Option::is_none")]
    pub num_inference_steps: Option<i64>,
    /// The prompt to generate images from
    /// "Close-up portrait of a majestic iguana with vibrant blue-green scales, piercing amber eyes, and orange spiky crest. Intricate textures and details visible on scaly skin. Wrapped in dark hood, giving regal appearance. Dramatic lighting against black background. Hyper-realistic, high-resolution image showcasing the reptile's expressive features and coloration."
    pub prompt: String,
    /// The seed to use for generating images
    #[serde(skip_serializing_if = "Option::is_none")]
    pub seed: Option<i64>,
}

#[derive(Debug, Serialize, Deserialize)]
pub struct Output {
    /// The generated images
    pub images: Vec<Image>,
    /// The expanded prompt
    pub prompt: String,
    /// The seed used to generate the images
    pub seed: i64,
}

#[derive(Debug, Serialize, Deserialize, Default)]
pub struct ValidationError {
    pub loc: Vec<serde_json::Value>,
    pub msg: String,
    #[serde(rename = "type")]
    pub ty: String,
}

/// AuraFlow
///
/// Category: text-to-image
/// Machine Type: A100
/// License Type: commercial
pub fn aura_flow(params: Input) -> FalRequest<Input, Output> {
    FalRequest::new("fal-ai/aura-flow", params)
}