import { z } from "zod";
import type { DrawThingsClient } from "../client/drawthings.js";
export const transformImageSchema = z.object({
prompt: z
.string()
.describe("Text description of the desired transformation"),
image_path: z
.string()
.optional()
.describe("Path to the source image file to transform"),
image_base64: z
.string()
.optional()
.describe("Base64-encoded source image (alternative to image_path)"),
negative_prompt: z
.string()
.optional()
.describe("Elements to exclude from the transformed image"),
denoising_strength: z
.number()
.min(0)
.max(1)
.optional()
.describe(
"Strength of the transformation (0.0-1.0, default: 0.75). Lower values keep more of the original image."
),
steps: z
.number()
.int()
.min(1)
.max(150)
.optional()
.describe("Number of inference steps (default: 20)"),
cfg_scale: z
.number()
.min(1)
.max(30)
.optional()
.describe("Classifier-free guidance scale (default: 7.5)"),
seed: z
.number()
.int()
.optional()
.describe("Random seed for reproducibility (-1 for random)"),
output_path: z
.string()
.optional()
.describe("Custom file path to save the transformed image"),
});
export const transformImageDescription =
"Transform an existing image using a text prompt (img2img). Either image_path or image_base64 must be provided.";
export async function transformImage(
client: DrawThingsClient,
params: z.infer<typeof transformImageSchema>
): Promise<{ type: "text"; text: string }[]> {
try {
// Validate input
if (!params.image_path && !params.image_base64) {
return [
{
type: "text",
text: "Error: Either image_path or image_base64 must be provided",
},
];
}
// Check if server is running first
const status = await client.checkStatus();
if (!status.running) {
return [
{
type: "text",
text: `Error: ${status.message}`,
},
];
}
// Get base64 image data
let imageBase64 = params.image_base64;
if (params.image_path && !imageBase64) {
try {
imageBase64 = await client.readImageAsBase64(params.image_path);
} catch (error) {
const message = error instanceof Error ? error.message : String(error);
return [
{
type: "text",
text: `Error reading image file: ${message}`,
},
];
}
}
// Transform the image
const response = await client.img2img({
prompt: params.prompt,
init_images: [imageBase64!],
negative_prompt: params.negative_prompt,
denoising_strength: params.denoising_strength,
steps: params.steps,
cfg_scale: params.cfg_scale,
seed: params.seed,
});
if (!response.images || response.images.length === 0) {
return [
{
type: "text",
text: "Error: No images were generated",
},
];
}
// Save the image(s)
const savedPaths: string[] = [];
for (let i = 0; i < response.images.length; i++) {
const outputPath =
params.output_path && response.images.length === 1
? params.output_path
: undefined;
const path = await client.saveImage(response.images[i], outputPath);
savedPaths.push(path);
}
return [
{
type: "text",
text: JSON.stringify(
{
success: true,
message: `Transformed image, generated ${savedPaths.length} result(s)`,
files: savedPaths,
prompt: params.prompt,
source: params.image_path || "(base64 input)",
parameters: {
denoising_strength: params.denoising_strength ?? 0.75,
steps: params.steps || 20,
cfg_scale: params.cfg_scale || 7.5,
seed: params.seed ?? -1,
},
},
null,
2
),
},
];
} catch (error) {
const message = error instanceof Error ? error.message : String(error);
return [
{
type: "text",
text: `Error transforming image: ${message}`,
},
];
}
}
