Update server.js
Browse files
server.js
CHANGED
|
@@ -6,10 +6,12 @@ import { Readable } from 'stream';
|
|
| 6 |
const app = express();
|
| 7 |
const PORT = 7860;
|
| 8 |
|
|
|
|
|
|
|
| 9 |
app.set('trust proxy', 1);
|
| 10 |
app.use(cors());
|
| 11 |
|
| 12 |
-
//
|
| 13 |
app.use(express.json({ limit: '50mb' }));
|
| 14 |
app.use(express.urlencoded({ limit: '50mb', extended: true }));
|
| 15 |
|
|
@@ -29,12 +31,12 @@ const PROVIDERS = [
|
|
| 29 |
id: "pollinations",
|
| 30 |
url: "https://text.pollinations.ai/openai",
|
| 31 |
modelsUrl: "https://text.pollinations.ai/models",
|
| 32 |
-
imageUrl: "https://image.pollinations.ai/prompt"
|
| 33 |
},
|
| 34 |
{
|
| 35 |
id: "airforce",
|
| 36 |
url: "https://api.airforce/v1/chat/completions",
|
| 37 |
-
imageUrl: "https://api.airforce/v1/images/generations"
|
| 38 |
},
|
| 39 |
{
|
| 40 |
id: "ventarys-mirror",
|
|
@@ -48,9 +50,11 @@ const QUEUE_TIMEOUT = 25000;
|
|
| 48 |
|
| 49 |
let currentLoad = { "llm7": 0, "pollinations": 0, "airforce": 0, "ventarys-mirror": 0 };
|
| 50 |
|
|
|
|
| 51 |
const limiter = rateLimit({
|
| 52 |
windowMs: 60 * 1000,
|
| 53 |
max: 25,
|
|
|
|
| 54 |
message: { error: { message: "Límite alcanzado. Espera 1 minuto entre mensajes.", code: 429 } },
|
| 55 |
standardHeaders: true,
|
| 56 |
legacyHeaders: false,
|
|
@@ -60,17 +64,19 @@ const limiter = rateLimit({
|
|
| 60 |
const IMAGE_KEYWORDS = ["flux", "dall", "midjourney", "sdxl", "stable-diffusion", "image", "vision"];
|
| 61 |
const AUDIO_KEYWORDS = ["suno", "udio", "music", "audio", "song", "voice", "tts"];
|
| 62 |
|
| 63 |
-
function isImageModel(
|
| 64 |
-
if (!
|
| 65 |
-
|
| 66 |
-
|
|
|
|
|
|
|
|
|
|
| 67 |
}
|
| 68 |
|
| 69 |
-
function isAudioModel(
|
| 70 |
-
if (type === 'audio' || type === 'music') return true;
|
| 71 |
-
|
| 72 |
-
|
| 73 |
-
return AUDIO_KEYWORDS.some(kw => lowerId.includes(kw));
|
| 74 |
}
|
| 75 |
|
| 76 |
async function fetchAllModels() {
|
|
@@ -93,8 +99,9 @@ async function fetchAllModels() {
|
|
| 93 |
|
| 94 |
if (modelsArray.length > 0) {
|
| 95 |
return modelsArray
|
| 96 |
-
//
|
| 97 |
-
.filter(model => !isAudioModel(model
|
|
|
|
| 98 |
.map(model => ({
|
| 99 |
...model,
|
| 100 |
id: model.id || model.name,
|
|
@@ -129,11 +136,14 @@ app.get('/health', (req, res) => {
|
|
| 129 |
app.get('/v1/models', async (req, res) => {
|
| 130 |
try {
|
| 131 |
const allModels = await fetchAllModels();
|
| 132 |
-
|
| 133 |
-
const textModels = allModels
|
| 134 |
-
|
| 135 |
-
|
| 136 |
-
|
|
|
|
|
|
|
|
|
|
| 137 |
|
| 138 |
res.json({ object: "list", data: textModels });
|
| 139 |
} catch (error) {
|
|
@@ -146,13 +156,16 @@ app.get('/v1/models', async (req, res) => {
|
|
| 146 |
app.get('/v1/images/models', async (req, res) => {
|
| 147 |
try {
|
| 148 |
const allModels = await fetchAllModels();
|
| 149 |
-
|
| 150 |
-
let imageModels = allModels
|
| 151 |
-
|
| 152 |
-
|
| 153 |
-
|
|
|
|
|
|
|
|
|
|
| 154 |
|
| 155 |
-
// Garantizar que la App siempre reconozca los modelos base
|
| 156 |
const baseImages = [
|
| 157 |
{ id: "flux", object: "model", type: "image", owned_by: "system", tier: "standard" },
|
| 158 |
{ id: "dall-e-3", object: "model", type: "image", owned_by: "system", tier: "standard" }
|
|
@@ -220,14 +233,12 @@ app.post(['/v1/chat/completions', '/v1/images/generations'], limiter, async (req
|
|
| 220 |
const prompt = req.body.prompt || "A random image";
|
| 221 |
const seed = Math.floor(Math.random() * 10000000);
|
| 222 |
|
| 223 |
-
// Extraer resolución del body (por defecto cuadrado si no se provee)
|
| 224 |
let width = 1024, height = 1024;
|
| 225 |
if (req.body.size) {
|
| 226 |
const parts = req.body.size.split('x');
|
| 227 |
if (parts.length === 2) { width = parseInt(parts[0]); height = parseInt(parts[1]); }
|
| 228 |
}
|
| 229 |
|
| 230 |
-
// Ajustar el modelo si el usuario pidió uno en específico
|
| 231 |
const pollModel = req.body.model && req.body.model.includes('flux') ? 'flux' : 'dall-e-3';
|
| 232 |
|
| 233 |
targetUrl = `${targetUrl}/${encodeURIComponent(prompt)}?seed=${seed}&width=${width}&height=${height}&model=${pollModel}&nologo=true`;
|
|
@@ -253,9 +264,15 @@ app.post(['/v1/chat/completions', '/v1/images/generations'], limiter, async (req
|
|
| 253 |
if (contentType.includes("application/json")) {
|
| 254 |
const jsonResp = await response.json();
|
| 255 |
|
| 256 |
-
//
|
| 257 |
-
|
| 258 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 259 |
if (item.url && !item.b64_json) {
|
| 260 |
try {
|
| 261 |
const imgRes = await fetch(item.url);
|
|
@@ -267,7 +284,14 @@ app.post(['/v1/chat/completions', '/v1/images/generations'], limiter, async (req
|
|
| 267 |
}
|
| 268 |
}
|
| 269 |
}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 270 |
}
|
|
|
|
|
|
|
| 271 |
releaseSlot();
|
| 272 |
return res.status(response.status).json(jsonResp);
|
| 273 |
}
|
|
@@ -277,14 +301,13 @@ app.post(['/v1/chat/completions', '/v1/images/generations'], limiter, async (req
|
|
| 277 |
const b64 = Buffer.from(arrayBuffer).toString('base64');
|
| 278 |
releaseSlot();
|
| 279 |
|
| 280 |
-
//
|
| 281 |
return res.status(200).json({
|
| 282 |
created: Math.floor(Date.now() / 1000),
|
| 283 |
data: [{ b64_json: b64 }]
|
| 284 |
});
|
| 285 |
}
|
| 286 |
else {
|
| 287 |
-
// Caída libre para errores o comportamientos inesperados de los proveedores
|
| 288 |
const textResp = await response.text();
|
| 289 |
releaseSlot();
|
| 290 |
return res.status(response.status).type(contentType).send(textResp);
|
|
|
|
| 6 |
const app = express();
|
| 7 |
const PORT = 7860;
|
| 8 |
|
| 9 |
+
// Configuración CRÍTICA para que express-rate-limit lea la IP real del usuario
|
| 10 |
+
// cuando la app está detrás de proxies inversos (ej. Vercel, Render, HF Spaces, Nginx)
|
| 11 |
app.set('trust proxy', 1);
|
| 12 |
app.use(cors());
|
| 13 |
|
| 14 |
+
// Aumentar límite a 50mb para soportar imágenes en Base64 (Visión / Multimodal)
|
| 15 |
app.use(express.json({ limit: '50mb' }));
|
| 16 |
app.use(express.urlencoded({ limit: '50mb', extended: true }));
|
| 17 |
|
|
|
|
| 31 |
id: "pollinations",
|
| 32 |
url: "https://text.pollinations.ai/openai",
|
| 33 |
modelsUrl: "https://text.pollinations.ai/models",
|
| 34 |
+
imageUrl: "https://image.pollinations.ai/prompt"
|
| 35 |
},
|
| 36 |
{
|
| 37 |
id: "airforce",
|
| 38 |
url: "https://api.airforce/v1/chat/completions",
|
| 39 |
+
imageUrl: "https://api.airforce/v1/images/generations"
|
| 40 |
},
|
| 41 |
{
|
| 42 |
id: "ventarys-mirror",
|
|
|
|
| 50 |
|
| 51 |
let currentLoad = { "llm7": 0, "pollinations": 0, "airforce": 0, "ventarys-mirror": 0 };
|
| 52 |
|
| 53 |
+
// --- RATE LIMITING (Basado en la IP real del usuario) ---
|
| 54 |
const limiter = rateLimit({
|
| 55 |
windowMs: 60 * 1000,
|
| 56 |
max: 25,
|
| 57 |
+
keyGenerator: (req) => req.ip, // Extrae la IP real verificada por 'trust proxy'
|
| 58 |
message: { error: { message: "Límite alcanzado. Espera 1 minuto entre mensajes.", code: 429 } },
|
| 59 |
standardHeaders: true,
|
| 60 |
legacyHeaders: false,
|
|
|
|
| 64 |
const IMAGE_KEYWORDS = ["flux", "dall", "midjourney", "sdxl", "stable-diffusion", "image", "vision"];
|
| 65 |
const AUDIO_KEYWORDS = ["suno", "udio", "music", "audio", "song", "voice", "tts"];
|
| 66 |
|
| 67 |
+
function isImageModel(model) {
|
| 68 |
+
if (!model) return false;
|
| 69 |
+
// Soporte directo para el flag de api.airforce
|
| 70 |
+
if (model.type === 'image' || model.supports_images === true) return true;
|
| 71 |
+
|
| 72 |
+
const id = (model.id || model.name || "").toLowerCase();
|
| 73 |
+
return IMAGE_KEYWORDS.some(kw => id.includes(kw));
|
| 74 |
}
|
| 75 |
|
| 76 |
+
function isAudioModel(model) {
|
| 77 |
+
if (model.type === 'audio' || model.type === 'music') return true;
|
| 78 |
+
const id = (model.id || model.name || "").toLowerCase();
|
| 79 |
+
return AUDIO_KEYWORDS.some(kw => id.includes(kw));
|
|
|
|
| 80 |
}
|
| 81 |
|
| 82 |
async function fetchAllModels() {
|
|
|
|
| 99 |
|
| 100 |
if (modelsArray.length > 0) {
|
| 101 |
return modelsArray
|
| 102 |
+
// Filtrar modelos de audio/música
|
| 103 |
+
.filter(model => !isAudioModel(model))
|
| 104 |
+
// Procesar y formatear campos
|
| 105 |
.map(model => ({
|
| 106 |
...model,
|
| 107 |
id: model.id || model.name,
|
|
|
|
| 136 |
app.get('/v1/models', async (req, res) => {
|
| 137 |
try {
|
| 138 |
const allModels = await fetchAllModels();
|
| 139 |
+
|
| 140 |
+
const textModels = allModels
|
| 141 |
+
// Excluir imágenes y asegurar que soporte chat (filtro estricto para api.airforce)
|
| 142 |
+
.filter(m => !isImageModel(m) && m.supports_chat !== false)
|
| 143 |
+
.map(m => {
|
| 144 |
+
m.type = 'text'; // Forzar etiqueta
|
| 145 |
+
return m;
|
| 146 |
+
});
|
| 147 |
|
| 148 |
res.json({ object: "list", data: textModels });
|
| 149 |
} catch (error) {
|
|
|
|
| 156 |
app.get('/v1/images/models', async (req, res) => {
|
| 157 |
try {
|
| 158 |
const allModels = await fetchAllModels();
|
| 159 |
+
|
| 160 |
+
let imageModels = allModels
|
| 161 |
+
// Incluir explícitamente modelos de imagen (o que supports_images sea true en airforce)
|
| 162 |
+
.filter(m => isImageModel(m))
|
| 163 |
+
.map(m => {
|
| 164 |
+
m.type = 'image'; // Forzar etiqueta
|
| 165 |
+
return m;
|
| 166 |
+
});
|
| 167 |
|
| 168 |
+
// Garantizar que la App siempre reconozca los modelos base
|
| 169 |
const baseImages = [
|
| 170 |
{ id: "flux", object: "model", type: "image", owned_by: "system", tier: "standard" },
|
| 171 |
{ id: "dall-e-3", object: "model", type: "image", owned_by: "system", tier: "standard" }
|
|
|
|
| 233 |
const prompt = req.body.prompt || "A random image";
|
| 234 |
const seed = Math.floor(Math.random() * 10000000);
|
| 235 |
|
|
|
|
| 236 |
let width = 1024, height = 1024;
|
| 237 |
if (req.body.size) {
|
| 238 |
const parts = req.body.size.split('x');
|
| 239 |
if (parts.length === 2) { width = parseInt(parts[0]); height = parseInt(parts[1]); }
|
| 240 |
}
|
| 241 |
|
|
|
|
| 242 |
const pollModel = req.body.model && req.body.model.includes('flux') ? 'flux' : 'dall-e-3';
|
| 243 |
|
| 244 |
targetUrl = `${targetUrl}/${encodeURIComponent(prompt)}?seed=${seed}&width=${width}&height=${height}&model=${pollModel}&nologo=true`;
|
|
|
|
| 264 |
if (contentType.includes("application/json")) {
|
| 265 |
const jsonResp = await response.json();
|
| 266 |
|
| 267 |
+
// Extraer el array de datos o crearlo si la API (ej. airforce) responde con { url: "..." } directo
|
| 268 |
+
let dataArray = jsonResp.data;
|
| 269 |
+
if (!dataArray && jsonResp.url) {
|
| 270 |
+
dataArray = [{ url: jsonResp.url }];
|
| 271 |
+
}
|
| 272 |
+
|
| 273 |
+
// Convertir URLs de imágenes a base64_json (Formato esperado idéntico a Aqua AI)
|
| 274 |
+
if (dataArray && Array.isArray(dataArray)) {
|
| 275 |
+
for (let item of dataArray) {
|
| 276 |
if (item.url && !item.b64_json) {
|
| 277 |
try {
|
| 278 |
const imgRes = await fetch(item.url);
|
|
|
|
| 284 |
}
|
| 285 |
}
|
| 286 |
}
|
| 287 |
+
releaseSlot();
|
| 288 |
+
return res.status(response.status).json({
|
| 289 |
+
created: Math.floor(Date.now() / 1000),
|
| 290 |
+
data: dataArray
|
| 291 |
+
});
|
| 292 |
}
|
| 293 |
+
|
| 294 |
+
// Respaldo de seguridad si no encontró formato extraíble
|
| 295 |
releaseSlot();
|
| 296 |
return res.status(response.status).json(jsonResp);
|
| 297 |
}
|
|
|
|
| 301 |
const b64 = Buffer.from(arrayBuffer).toString('base64');
|
| 302 |
releaseSlot();
|
| 303 |
|
| 304 |
+
// Formato Aqua AI Strict:
|
| 305 |
return res.status(200).json({
|
| 306 |
created: Math.floor(Date.now() / 1000),
|
| 307 |
data: [{ b64_json: b64 }]
|
| 308 |
});
|
| 309 |
}
|
| 310 |
else {
|
|
|
|
| 311 |
const textResp = await response.text();
|
| 312 |
releaseSlot();
|
| 313 |
return res.status(response.status).type(contentType).send(textResp);
|