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llm / api /app /clients /tools /structured /StableDiffusion.js
Marco Beretta
LibreChat upload repo
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// Generates image using stable diffusion webui's api (automatic1111)
const fs = require('fs');
const { StructuredTool } = require('langchain/tools');
const { z } = require('zod');
const path = require('path');
const axios = require('axios');
const sharp = require('sharp');
class StableDiffusionAPI extends StructuredTool {
constructor(fields) {
super();
this.name = 'stable-diffusion';
this.url = fields.SD_WEBUI_URL || this.getServerURL();
this.description = `You can generate images with 'stable-diffusion'. This tool is exclusively for visual content.
Guidelines:
- Visually describe the moods, details, structures, styles, and/or proportions of the image. Remember, the focus is on visual attributes.
- Craft your input by "showing" and not "telling" the imagery. Think in terms of what you'd want to see in a photograph or a painting.
- Here's an example for generating a realistic portrait photo of a man:
"prompt":"photo of a man in black clothes, half body, high detailed skin, coastline, overcast weather, wind, waves, 8k uhd, dslr, soft lighting, high quality, film grain, Fujifilm XT3"
"negative_prompt":"semi-realistic, cgi, 3d, render, sketch, cartoon, drawing, anime, out of frame, low quality, ugly, mutation, deformed"
- Generate images only once per human query unless explicitly requested by the user`;
this.schema = z.object({
prompt: z
.string()
.describe(
'Detailed keywords to describe the subject, using at least 7 keywords to accurately describe the image, separated by comma',
),
negative_prompt: z
.string()
.describe(
'Keywords we want to exclude from the final image, using at least 7 keywords to accurately describe the image, separated by comma',
),
});
}
replaceNewLinesWithSpaces(inputString) {
return inputString.replace(/\r\n|\r|\n/g, ' ');
}
getMarkdownImageUrl(imageName) {
const imageUrl = path
.join(this.relativeImageUrl, imageName)
.replace(/\\/g, '/')
.replace('public/', '');
return `![generated image](/${imageUrl})`;
}
getServerURL() {
const url = process.env.SD_WEBUI_URL || '';
if (!url) {
throw new Error('Missing SD_WEBUI_URL environment variable.');
}
return url;
}
async _call(data) {
const url = this.url;
const { prompt, negative_prompt } = data;
const payload = {
prompt,
negative_prompt,
steps: 20,
};
const response = await axios.post(`${url}/sdapi/v1/txt2img`, payload);
const image = response.data.images[0];
const pngPayload = { image: `data:image/png;base64,${image}` };
const response2 = await axios.post(`${url}/sdapi/v1/png-info`, pngPayload);
const info = response2.data.info;
// Generate unique name
const imageName = `${Date.now()}.png`;
this.outputPath = path.resolve(
__dirname,
'..',
'..',
'..',
'..',
'..',
'client',
'public',
'images',
);
const appRoot = path.resolve(__dirname, '..', '..', '..', '..', '..', 'client');
this.relativeImageUrl = path.relative(appRoot, this.outputPath);
// Check if directory exists, if not create it
if (!fs.existsSync(this.outputPath)) {
fs.mkdirSync(this.outputPath, { recursive: true });
}
try {
const buffer = Buffer.from(image.split(',', 1)[0], 'base64');
await sharp(buffer)
.withMetadata({
iptcpng: {
parameters: info,
},
})
.toFile(this.outputPath + '/' + imageName);
this.result = this.getMarkdownImageUrl(imageName);
} catch (error) {
console.error('Error while saving the image:', error);
// this.result = theImageUrl;
}
return this.result;
}
}
module.exports = StableDiffusionAPI;