File size: 6,805 Bytes
b86a7bf 873f10f b86a7bf 873f10f b86a7bf 873f10f b86a7bf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 | import express from 'express';
import { getAvailableModels, generateImageForSD } from '../api/client.js';
import { generateRequestBody, prepareImageRequest } from '../utils/utils.js';
import tokenManager from '../auth/token_manager.js';
import logger from '../utils/logger.js';
const router = express.Router();
// 静态数据
const SD_MOCK_DATA = {
options: {
sd_model_checkpoint: 'gemini-3-pro-image',
sd_vae: 'auto',
CLIP_stop_at_last_layers: 1
},
samplers: [
{ name: 'Euler a', aliases: ['k_euler_a'] },
{ name: 'Euler', aliases: ['k_euler'] },
{ name: 'DPM++ 2M', aliases: ['k_dpmpp_2m'] },
{ name: 'DPM++ SDE', aliases: ['k_dpmpp_sde'] }
],
schedulers: [
{ name: 'Automatic', label: 'Automatic' },
{ name: 'Uniform', label: 'Uniform' },
{ name: 'Karras', label: 'Karras' },
{ name: 'Exponential', label: 'Exponential' }
],
upscalers: [
{ name: 'None', model_name: null, scale: 1 },
{ name: 'Lanczos', model_name: null, scale: 4 },
{ name: 'ESRGAN_4x', model_name: 'ESRGAN_4x', scale: 4 }
],
latentUpscaleModes: [
{ name: 'Latent' },
{ name: 'Latent (antialiased)' },
{ name: 'Latent (bicubic)' },
{ name: 'Latent (nearest)' }
],
vae: [
{ model_name: 'auto', filename: 'auto' },
{ model_name: 'None', filename: 'None' }
],
modules: [
{ name: 'none', path: null },
{ name: 'LoRA', path: 'lora' }
],
loras: [
{ name: 'example_lora_v1', alias: 'example_lora_v1', path: 'example_lora_v1.safetensors' },
{ name: 'style_lora', alias: 'style_lora', path: 'style_lora.safetensors' }
],
embeddings: [
{ name: 'EasyNegative', step: 1, sd_checkpoint: null, sd_checkpoint_name: null },
{ name: 'badhandv4', step: 1, sd_checkpoint: null, sd_checkpoint_name: null }
],
hypernetworks: [
{ name: 'example_hypernetwork', path: 'example_hypernetwork.pt' }
],
scripts: [
{ name: 'None', is_alwayson: false, is_img2img: false },
{ name: 'X/Y/Z plot', is_alwayson: false, is_img2img: false }
],
progress: {
progress: 0,
eta_relative: 0,
state: { skipped: false, interrupted: false, job: '', job_count: 0, job_timestamp: '0', job_no: 0 },
current_image: null,
textinfo: null
}
};
// 构建图片生成请求体
function buildImageRequestBody(prompt, token) {
const messages = [{ role: 'user', content: prompt }];
const requestBody = generateRequestBody(messages, 'gemini-3-pro-image', {}, null, token);
return prepareImageRequest(requestBody);
}
// GET 路由
router.get('/sd-models', async (req, res) => {
try {
const models = await getAvailableModels();
const imageModels = models.data
.filter(m => m.id.includes('-image'))
.map(m => ({
title: m.id,
model_name: m.id,
hash: null,
sha256: null,
filename: m.id,
config: null
}));
res.json(imageModels);
} catch (error) {
logger.error('获取SD模型列表失败:', error.message);
res.status(500).json({ error: error.message });
}
});
router.get('/options', (req, res) => res.json(SD_MOCK_DATA.options));
router.get('/samplers', (req, res) => res.json(SD_MOCK_DATA.samplers));
router.get('/schedulers', (req, res) => res.json(SD_MOCK_DATA.schedulers));
router.get('/upscalers', (req, res) => res.json(SD_MOCK_DATA.upscalers));
router.get('/latent-upscale-modes', (req, res) => res.json(SD_MOCK_DATA.latentUpscaleModes));
router.get('/sd-vae', (req, res) => res.json(SD_MOCK_DATA.vae));
router.get('/sd-modules', (req, res) => res.json(SD_MOCK_DATA.modules));
router.get('/loras', (req, res) => res.json(SD_MOCK_DATA.loras));
router.get('/embeddings', (req, res) => res.json({ loaded: SD_MOCK_DATA.embeddings, skipped: {} }));
router.get('/hypernetworks', (req, res) => res.json(SD_MOCK_DATA.hypernetworks));
router.get('/scripts', (req, res) => res.json({ txt2img: SD_MOCK_DATA.scripts, img2img: SD_MOCK_DATA.scripts }));
router.get('/script-info', (req, res) => res.json([]));
router.get('/progress', (req, res) => res.json(SD_MOCK_DATA.progress));
router.get('/cmd-flags', (req, res) => res.json({}));
router.get('/memory', (req, res) => res.json({ ram: { free: 8589934592, used: 8589934592, total: 17179869184 }, cuda: { system: { free: 0, used: 0, total: 0 } } }));
// POST 路由
router.post('/img2img', async (req, res) => {
const { prompt, init_images } = req.body;
try {
if (!prompt) {
return res.status(400).json({ error: 'prompt is required' });
}
const token = await tokenManager.getToken();
if (!token) {
throw new Error('没有可用的token');
}
// 构建包含图片的消息
const content = [{ type: 'text', text: prompt }];
if (init_images && init_images.length > 0) {
init_images.forEach(img => {
const format = img.startsWith('/9j/') ? 'jpeg' : 'png';
content.push({ type: 'image_url', image_url: { url: `data:image/${format};base64,${img}` } });
});
}
const messages = [{ role: 'user', content }];
const requestBody = prepareImageRequest(
generateRequestBody(messages, 'gemini-3-pro-image', {}, null, token)
);
const images = await generateImageForSD(requestBody, token);
if (images.length === 0) {
throw new Error('未生成图片');
}
res.json({
images,
parameters: req.body,
info: JSON.stringify({ prompt })
});
} catch (error) {
logger.error('SD图生图失败:', error.message);
res.status(500).json({ error: error.message });
}
});
router.post('/txt2img', async (req, res) => {
const { prompt, negative_prompt, steps, cfg_scale, width, height, seed, sampler_name } = req.body;
try {
if (!prompt) {
return res.status(400).json({ error: 'prompt is required' });
}
const token = await tokenManager.getToken();
if (!token) {
throw new Error('没有可用的token');
}
const requestBody = buildImageRequestBody(prompt, token);
const images = await generateImageForSD(requestBody, token);
if (images.length === 0) {
throw new Error('未生成图片');
}
res.json({
images,
parameters: { prompt, negative_prompt, steps, cfg_scale, width, height, seed, sampler_name },
info: JSON.stringify({ prompt, seed: seed || -1 })
});
} catch (error) {
logger.error('SD生图失败:', error.message);
res.status(500).json({ error: error.message });
}
});
router.post('/options', (req, res) => res.json({}));
router.post('/refresh-checkpoints', (req, res) => res.json(null));
router.post('/refresh-loras', (req, res) => res.json(null));
router.post('/interrupt', (req, res) => res.json(null));
router.post('/skip', (req, res) => res.json(null));
export default router;
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