Create app.py

app.py

@@ -0,0 +1,725 @@
+import os
+import sys
+import torch
+import pickle
+import time
+import gc
+from fastapi import FastAPI, Request
+from fastapi.responses import HTMLResponse, StreamingResponse
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel, Field
+from huggingface_hub import snapshot_download
+import uvicorn
+
+# ======================
+# CONFIGURACIÓN DE DISPOSITIVO
+# ======================
+if torch.cuda.is_available():
+    DEVICE = "cuda"
+    print("✅ GPU NVIDIA detectada. Usando CUDA.")
+else:
+    DEVICE = "cpu"
+    print("⚠️ GPU no detectada. Usando CPU (puede ser más lento).")
+
+# Optimización de hilos para CPU
+if DEVICE == "cpu":
+    torch.set_num_threads(max(1, os.cpu_count() // 2))
+
+torch.set_grad_enabled(False)
+
+MODEL_REPO = "TeszenAI/mtp-3.1"
+
+# ======================
+# DESCARGA Y CARGA DEL MODELO
+# ======================
+print(f"📦 Descargando modelo desde {MODEL_REPO}...")
+repo_path = snapshot_download(
+    repo_id=MODEL_REPO,
+    repo_type="model",
+    local_dir="mtptz_repo"
+)
+
+sys.path.insert(0, repo_path)
+
+# Importar modelo mejorado compatible
+from model import MTPMiniModel
+from tokenizer import MTPTokenizer
+
+print("🔧 Cargando tensores y configuración...")
+with open(os.path.join(repo_path, "mtp_mini.pkl"), "rb") as f:
+    model_data = pickle.load(f)
+
+tokenizer = MTPTokenizer(os.path.join(repo_path, "mtp_tokenizer.model"))
+VOCAB_SIZE = tokenizer.sp.get_piece_size()
+config = model_data["config"]
+
+# Detectar si el modelo usa SwiGLU
+use_swiglu = config["model"].get("use_swiglu", False)
+
+print(f"🧠 Inicializando modelo...")
+print(f"   → Vocabulario: {VOCAB_SIZE}")
+print(f"   → Dimensión: {config['model']['d_model']}")
+print(f"   → Capas: {config['model']['n_layers']}")
+print(f"   → SwiGLU: {'✓' if use_swiglu else '✗'}")
+
+model = MTPMiniModel(
+    vocab_size=VOCAB_SIZE,
+    d_model=config["model"]["d_model"],
+    n_layers=config["model"]["n_layers"],
+    n_heads=config["model"]["n_heads"],
+    d_ff=config["model"]["d_ff"],
+    max_seq_len=config["model"]["max_seq_len"],
+    dropout=0.0,
+    use_swiglu=use_swiglu  # NUEVO: soporte para SwiGLU
+)
+
+model.load_state_dict(model_data["model_state_dict"])
+model.eval()
+
+# Cuantización para CPU
+if DEVICE == "cpu":
+    print("⚡ Aplicando cuantización dinámica para CPU...")
+    model = torch.quantization.quantize_dynamic(
+        model, 
+        {torch.nn.Linear}, 
+        dtype=torch.qint8
+    )
+
+model.to(DEVICE)
+
+param_count = sum(p.numel() for p in model.parameters())
+print(f"✅ Modelo cargado: {param_count:,} parámetros ({param_count/1e6:.1f}M)")
+
+# ======================
+# API CONFIG
+# ======================
+app = FastAPI(
+    title="MTP-3 API",
+    description="API para modelo de lenguaje MTP-3 mejorado",
+    version="3.0"
+)
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+class PromptRequest(BaseModel):
+    text: str = Field(..., max_length=2000, description="Texto de entrada")
+    max_tokens: int = Field(default=150, ge=10, le=300, description="Tokens máximos a generar")
+    temperature: float = Field(default=0.7, ge=0.1, le=2.0, description="Temperatura de muestreo")
+    top_k: int = Field(default=50, ge=1, le=100, description="Top-k sampling")
+    top_p: float = Field(default=0.9, ge=0.1, le=1.0, description="Top-p (nucleus) sampling")
+    repetition_penalty: float = Field(default=1.1, ge=1.0, le=2.0, description="Penalización por repetición")
+
+def build_prompt(user_input: str) -> str:
+    """Construye el prompt en el formato del modelo"""
+    return f"### Instrucción:\n{user_input}\n\n### Respuesta:\n"
+
+# ======================
+# ⚡ GESTIÓN DE CARGA
+# ======================
+ACTIVE_REQUESTS = 0
+
+@app.post("/generate")
+async def generate(req: PromptRequest):
+    """Endpoint principal de generación de texto"""
+    global ACTIVE_REQUESTS
+    ACTIVE_REQUESTS += 1
+    
+    # Ajuste dinámico bajo carga
+    dyn_max_tokens = req.max_tokens
+    dyn_temperature = req.temperature
+    
+    if ACTIVE_REQUESTS > 2:
+        print(f"⚠️ Carga alta ({ACTIVE_REQUESTS} requests). Ajustando parámetros.")
+        dyn_max_tokens = min(dyn_max_tokens, 120)
+        dyn_temperature = max(0.5, dyn_temperature * 0.9)
+
+    user_input = req.text.strip()
+    if not user_input:
+        ACTIVE_REQUESTS -= 1
+        return {"reply": "", "tokens_generated": 0}
+
+    full_prompt = build_prompt(user_input)
+    tokens = [tokenizer.bos_id()] + tokenizer.encode(full_prompt)
+    input_ids = torch.tensor([tokens], device=DEVICE)
+
+    try:
+        with torch.no_grad():
+            output_ids = model.generate(
+                input_ids,
+                max_new_tokens=dyn_max_tokens,
+                temperature=dyn_temperature,
+                top_k=req.top_k,
+                top_p=req.top_p,
+                repetition_penalty=req.repetition_penalty
+            )
+
+        gen_tokens = output_ids[0, len(tokens):].tolist()
+        
+        # Filtro de seguridad
+        safe_tokens = [
+            t for t in gen_tokens 
+            if 0 <= t < VOCAB_SIZE and t != tokenizer.eos_id()
+        ]
+        
+        response = tokenizer.decode(safe_tokens).strip()
+        
+        # Limpiar marcadores de sección
+        if "###" in response:
+            response = response.split("###")[0].strip()
+
+        return {
+            "reply": response,
+            "tokens_generated": len(safe_tokens),
+            "model": "MTP-3"
+        }
+    
+    except Exception as e:
+        print(f"❌ Error durante generación: {e}")
+        return {
+            "reply": "Lo siento, ocurrió un error al procesar tu solicitud.",
+            "error": str(e)
+        }
+    
+    finally:
+        ACTIVE_REQUESTS -= 1
+        if DEVICE == "cuda":
+            torch.cuda.empty_cache()
+        gc.collect()
+
+# ======================
+# 📡 STREAMING SSE
+# ======================
+@app.get("/generate_sse")
+def generate_sse(
+    text: str,
+    max_tokens: int = 150,
+    temperature: float = 0.7
+):
+    """Endpoint de streaming con Server-Sent Events"""
+    global ACTIVE_REQUESTS
+    ACTIVE_REQUESTS += 1
+    
+    def event_stream():
+        try:
+            full_prompt = build_prompt(text)
+            tokens = [tokenizer.bos_id()] + tokenizer.encode(full_prompt)
+            input_ids = torch.tensor([tokens], device=DEVICE)
+
+            # Ajuste dinámico
+            limit = 100 if ACTIVE_REQUESTS > 2 else max_tokens
+            temp = max(0.5, temperature * 0.9) if ACTIVE_REQUESTS > 2 else temperature
+
+            for step in range(limit):
+                with torch.no_grad():
+                    logits, _ = model(input_ids)
+                    logits = logits[:, -1, :VOCAB_SIZE]
+                    
+                    # Sampling con temperatura
+                    probs = torch.softmax(logits / temp, dim=-1)
+                    next_id = torch.multinomial(probs, num_samples=1).item()
+
+                if next_id == tokenizer.eos_id():
+                    break
+
+                if 0 <= next_id < VOCAB_SIZE:
+                    token_text = tokenizer.decode([next_id])
+                    
+                    # Limpiar salida
+                    if "###" in token_text:
+                        break
+                    
+                    yield f"data:{token_text}\n\n"
+                    
+                    input_ids = torch.cat(
+                        [input_ids, torch.tensor([[next_id]], device=DEVICE)],
+                        dim=1
+                    )
+                    time.sleep(0.01)
+
+            yield "data:[DONE]\n\n"
+            
+        except Exception as e:
+            yield f"data:[ERROR: {str(e)}]\n\n"
+        
+        finally:
+            ACTIVE_REQUESTS -= 1
+            if DEVICE == "cuda":
+                torch.cuda.empty_cache()
+    
+    return StreamingResponse(event_stream(), media_type="text/event-stream")
+
+# ======================
+# 📊 ENDPOINTS DE INFORMACIÓN
+# ======================
+@app.get("/health")
+def health_check():
+    """Check del estado del servicio"""
+    return {
+        "status": "healthy",
+        "model": "MTP-3",
+        "device": DEVICE,
+        "active_requests": ACTIVE_REQUESTS,
+        "vocab_size": VOCAB_SIZE,
+        "parameters": sum(p.numel() for p in model.parameters())
+    }
+
+@app.get("/info")
+def model_info():
+    """Información detallada del modelo"""
+    return {
+        "model_name": "MTP-3",
+        "version": "3.0",
+        "architecture": {
+            "d_model": config["model"]["d_model"],
+            "n_layers": config["model"]["n_layers"],
+            "n_heads": config["model"]["n_heads"],
+            "d_ff": config["model"]["d_ff"],
+            "max_seq_len": config["model"]["max_seq_len"],
+            "vocab_size": VOCAB_SIZE,
+            "use_swiglu": config["model"].get("use_swiglu", False)
+        },
+        "parameters": sum(p.numel() for p in model.parameters()),
+        "device": DEVICE,
+        "improvements": [
+            "RoPE (Rotary Position Embedding)",
+            "RMSNorm",
+            "Label Smoothing",
+            "Repetition Penalty",
+            "SwiGLU (opcional)" if config["model"].get("use_swiglu") else None
+        ]
+    }
+
+# ======================
+# 🎨 INTERFAZ WEB
+# ======================
+@app.get("/", response_class=HTMLResponse)
+def chat_ui():
+    return """
+<!DOCTYPE html>
+<html lang="es">
+<head>
+<meta charset="UTF-8">
+<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no">
+<title>MTP 3</title>
+<link rel="preconnect" href="https://fonts.googleapis.com">
+<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
+<link href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600&display=swap" rel="stylesheet">
+<style>
+:root {
+    --bg-color: #131314;
+    --surface-color: #1E1F20;
+    --accent-color: #4a9eff;
+    --text-primary: #e3e3e3;
+    --text-secondary: #9aa0a6;
+    --user-bubble: #282a2c;
+    --bot-actions-color: #c4c7c5;
+    --logo-url: url('https://i.postimg.cc/yxS54PF3/IMG-3082.jpg');
+}
+* { box-sizing: border-box; outline: none; -webkit-tap-highlight-color: transparent; }
+body {
+    margin: 0;
+    background-color: var(--bg-color);
+    font-family: 'Inter', sans-serif;
+    color: var(--text-primary);
+    height: 100dvh;
+    display: flex;
+    flex-direction: column;
+    overflow: hidden;
+}
+header {
+    padding: 12px 20px;
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    background: rgba(19, 19, 20, 0.85);
+    backdrop-filter: blur(12px);
+    position: fixed;
+    top: 0;
+    width: 100%;
+    z-index: 50;
+    border-bottom: 1px solid rgba(255,255,255,0.05);
+}
+.brand-wrapper {
+    display: flex;
+    align-items: center;
+    gap: 12px;
+    cursor: pointer;
+}
+.brand-logo {
+    width: 32px;
+    height: 32px;
+    border-radius: 50%;
+    background-image: var(--logo-url);
+    background-size: cover;
+    background-position: center;
+    border: 1px solid rgba(255,255,255,0.1);
+}
+.brand-text {
+    font-weight: 500;
+    font-size: 1.05rem;
+    display: flex;
+    align-items: center;
+    gap: 8px;
+}
+.version-badge {
+    font-size: 0.75rem;
+    background: rgba(74, 158, 255, 0.15);
+    color: #8ab4f8;
+    padding: 2px 8px;
+    border-radius: 12px;
+    font-weight: 600;
+}
+.chat-scroll {
+    flex: 1;
+    overflow-y: auto;
+    padding: 80px 20px 40px 20px;
+    display: flex;
+    flex-direction: column;
+    gap: 30px;
+    max-width: 850px;
+    margin: 0 auto;
+    width: 100%;
+    scroll-behavior: smooth;
+}
+.msg-row {
+    display: flex;
+    gap: 16px;
+    width: 100%;
+    opacity: 0;
+    transform: translateY(10px);
+    animation: slideUpFade 0.4s cubic-bezier(0.2, 0.8, 0.2, 1) forwards;
+}
+.msg-row.user { justify-content: flex-end; }
+.msg-row.bot { justify-content: flex-start; align-items: flex-start; }
+.msg-content {
+    line-height: 1.6;
+    font-size: 1rem;
+    word-wrap: break-word;
+    max-width: 85%;
+}
+.user .msg-content {
+    background-color: var(--user-bubble);
+    padding: 10px 18px;
+    border-radius: 18px;
+    border-top-right-radius: 4px;
+    color: #fff;
+}
+.bot .msg-content-wrapper {
+    display: flex;
+    flex-direction: column;
+    gap: 8px;
+    width: 100%;
+}
+.bot .msg-text {
+    padding-top: 6px;
+    color: var(--text-primary);
+}
+.bot-avatar {
+    width: 34px;
+    height: 34px;
+    min-width: 34px;
+    border-radius: 50%;
+    background-image: var(--logo-url);
+    background-size: cover;
+    box-shadow: 0 2px 6px rgba(0,0,0,0.2);
+}
+.bot-actions {
+    display: flex;
+    gap: 10px;
+    opacity: 0;
+    transition: opacity 0.3s;
+    margin-top: 5px;
+}
+.action-btn {
+    background: transparent;
+    border: none;
+    color: var(--text-secondary);
+    cursor: pointer;
+    padding: 4px;
+    border-radius: 4px;
+    display: flex;
+    align-items: center;
+    transition: color 0.2s, background 0.2s;
+}
+.action-btn:hover {
+    color: var(--text-primary);
+    background: rgba(255,255,255,0.08);
+}
+.action-btn svg { width: 16px; height: 16px; fill: currentColor; }
+.typing-cursor::after {
+    content: '';
+    display: inline-block;
+    width: 10px;
+    height: 10px;
+    background: var(--accent-color);
+    border-radius: 50%;
+    margin-left: 5px;
+    vertical-align: middle;
+    animation: blink 1s infinite;
+}
+.footer-container {
+    padding: 0 20px 20px 20px;
+    background: linear-gradient(to top, var(--bg-color) 85%, transparent);
+    position: relative;
+    z-index: 60;
+}
+.input-box {
+    max-width: 850px;
+    margin: 0 auto;
+    background: var(--surface-color);
+    border-radius: 28px;
+    padding: 8px 10px 8px 20px;
+    display: flex;
+    align-items: center;
+    border: 1px solid rgba(255,255,255,0.1);
+    transition: border-color 0.2s, box-shadow 0.2s;
+}
+.input-box:focus-within {
+    border-color: rgba(74, 158, 255, 0.5);
+    box-shadow: 0 0 0 2px rgba(74, 158, 255, 0.1);
+}
+#userInput {
+    flex: 1;
+    background: transparent;
+    border: none;
+    color: white;
+    font-size: 1rem;
+    font-family: inherit;
+    padding: 10px 0;
+}
+#mainBtn {
+    background: white;
+    color: black;
+    border: none;
+    width: 36px;
+    height: 36px;
+    border-radius: 50%;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    cursor: pointer;
+    margin-left: 8px;
+    transition: transform 0.2s;
+}
+#mainBtn:hover { transform: scale(1.05); }
+.disclaimer {
+    text-align: center;
+    font-size: 0.75rem;
+    color: #666;
+    margin-top: 12px;
+}
+@keyframes slideUpFade {
+    from { opacity: 0; transform: translateY(15px); }
+    to { opacity: 1; transform: translateY(0); }
+}
+@keyframes blink { 0%, 100% { opacity: 1; } 50% { opacity: 0; } }
+@keyframes pulseAvatar {
+    0% { box-shadow: 0 0 0 0 rgba(74, 158, 255, 0.4); }
+    70% { box-shadow: 0 0 0 8px rgba(74, 158, 255, 0); }
+    100% { box-shadow: 0 0 0 0 rgba(74, 158, 255, 0); }
+}
+.pulsing { animation: pulseAvatar 1.5s infinite; }
+::-webkit-scrollbar { width: 8px; }
+::-webkit-scrollbar-track { background: transparent; }
+::-webkit-scrollbar-thumb { background: #333; border-radius: 4px; }
+</style>
+</head>
+<body>
+<header>
+    <div class="brand-wrapper" onclick="location.reload()">
+        <div class="brand-logo"></div>
+        <div class="brand-text">
+            MTP <span class="version-badge">3</span>
+        </div>
+    </div>
+</header>
+<div id="chatScroll" class="chat-scroll">
+    <div class="msg-row bot" style="animation-delay: 0.1s;">
+        <div class="bot-avatar"></div>
+        <div class="msg-content-wrapper">
+            <div class="msg-text">
+                ¡Hola! Soy MTP 3. ¿En qué puedo ayudarte hoy?
+            </div>
+        </div>
+    </div>
+</div>
+<div class="footer-container">
+    <div class="input-box">
+        <input type="text" id="userInput" placeholder="Escribe un mensaje..." autocomplete="off">
+        <button id="mainBtn" onclick="handleBtnClick()"></button>
+    </div>
+    <div class="disclaimer">
+        MTP puede cometer errores. Considera verificar la información importante.
+    </div>
+</div>
+<script>
+const chatScroll = document.getElementById('chatScroll');
+const userInput = document.getElementById('userInput');
+const mainBtn = document.getElementById('mainBtn');
+let isGenerating = false;
+let abortController = null;
+let typingTimeout = null;
+let lastUserPrompt = "";
+const ICON_SEND = `<svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"><path d="M22 2L11 13M22 2l-7 20-4-9-9-4 20-7z"></path></svg>`;
+const ICON_STOP = `<svg width="14" height="14" viewBox="0 0 24 24" fill="currentColor" stroke="currentColor" stroke-width="0"><rect x="2" y="2" width="20" height="20" rx="4" ry="4"></rect></svg>`;
+mainBtn.innerHTML = ICON_SEND;
+function scrollToBottom() {
+    chatScroll.scrollTop = chatScroll.scrollHeight;
+}
+function setBtnState(state) {
+    if (state === 'sending') {
+        mainBtn.innerHTML = ICON_STOP;
+        isGenerating = true;
+    } else {
+        mainBtn.innerHTML = ICON_SEND;
+        isGenerating = false;
+        abortController = null;
+    }
+}
+function handleBtnClick() {
+    if (isGenerating) {
+        stopGeneration();
+    } else {
+        sendMessage();
+    }
+}
+function stopGeneration() {
+    if (abortController) abortController.abort();
+    if (typingTimeout) clearTimeout(typingTimeout);
+    const activeCursor = document.querySelector('.typing-cursor');
+    if (activeCursor) activeCursor.classList.remove('typing-cursor');
+    const activeAvatar = document.querySelector('.pulsing');
+    if (activeAvatar) activeAvatar.classList.remove('pulsing');
+    setBtnState('idle');
+    userInput.focus();
+}
+async function sendMessage(textOverride = null) {
+    const text = textOverride || userInput.value.trim();
+    if (!text) return;
+    lastUserPrompt = text;
+    if (!textOverride) {
+        userInput.value = '';
+        addMessage(text, 'user');
+    }
+    setBtnState('sending');
+    abortController = new AbortController();
+    const botRow = document.createElement('div');
+    botRow.className = 'msg-row bot';
+    const avatar = document.createElement('div');
+    avatar.className = 'bot-avatar pulsing'; 
+    const wrapper = document.createElement('div');
+    wrapper.className = 'msg-content-wrapper';
+    const msgText = document.createElement('div');
+    msgText.className = 'msg-text'; 
+    wrapper.appendChild(msgText);
+    botRow.appendChild(avatar);
+    botRow.appendChild(wrapper);
+    chatScroll.appendChild(botRow);
+    scrollToBottom();
+    try {
+        const response = await fetch('/generate', {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify({ text: text }),
+            signal: abortController.signal
+        });
+        const data = await response.json();
+        if (!isGenerating) return; 
+        avatar.classList.remove('pulsing');
+        const reply = data.reply || "No entendí eso.";
+        await typeWriter(msgText, reply);
+        if (isGenerating) {
+            addActions(wrapper, reply);
+            setBtnState('idle');
+        }
+    } catch (error) {
+        if (error.name === 'AbortError') {
+            msgText.textContent += " [Detenido]";
+        } else {
+            avatar.classList.remove('pulsing');
+            msgText.textContent = "Error de conexión.";
+            msgText.style.color = "#ff8b8b";
+            setBtnState('idle');
+        }
+    }
+}
+function addMessage(text, sender) {
+    const row = document.createElement('div');
+    row.className = `msg-row ${sender}`;
+    const content = document.createElement('div');
+    content.className = 'msg-content';
+    content.textContent = text;
+    row.appendChild(content);
+    chatScroll.appendChild(row);
+    scrollToBottom();
+}
+function typeWriter(element, text, speed = 12) {
+    return new Promise(resolve => {
+        let i = 0;
+        element.classList.add('typing-cursor');
+        function type() {
+            if (!isGenerating) {
+                element.classList.remove('typing-cursor');
+                resolve();
+                return;
+            }
+            if (i < text.length) {
+                element.textContent += text.charAt(i);
+                i++;
+                scrollToBottom();
+                typingTimeout = setTimeout(type, speed + Math.random() * 5);
+            } else {
+                element.classList.remove('typing-cursor');
+                resolve();
+            }
+        }
+        type();
+    });
+}
+function addActions(wrapperElement, textToCopy) {
+    const actionsDiv = document.createElement('div');
+    actionsDiv.className = 'bot-actions';
+    const copyBtn = document.createElement('button');
+    copyBtn.className = 'action-btn';
+    copyBtn.innerHTML = `<svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><rect x="9" y="9" width="13" height="13" rx="2" ry="2"></rect><path d="M5 15H4a2 2 0 0 1-2-2V4a2 2 0 0 1 2-2h9a2 2 0 0 1 2 2v1"></path></svg>`;
+    copyBtn.onclick = () => {
+        navigator.clipboard.writeText(textToCopy);
+    };
+    const regenBtn = document.createElement('button');
+    regenBtn.className = 'action-btn';
+    regenBtn.innerHTML = `<svg viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"><path d="M23 4v6h-6"></path><path d="M1 20v-6h6"></path><path d="M3.51 9a9 9 0 0 1 14.85-3.36L23 10M1 14l4.64 4.36A9 9 0 0 0 20.49 15"></path></svg>`;
+    regenBtn.onclick = () => {
+        sendMessage(lastUserPrompt);
+    };
+    actionsDiv.appendChild(copyBtn);
+    actionsDiv.appendChild(regenBtn);
+    wrapperElement.appendChild(actionsDiv);
+    requestAnimationFrame(() => actionsDiv.style.opacity = "1");
+    scrollToBottom();
+}
+userInput.addEventListener('keydown', (e) => {
+    if (e.key === 'Enter') handleBtnClick();
+});
+window.onload = () => userInput.focus();
+</script>
+</body>
+</html>
+"""
+
+if __name__ == "__main__":
+    port = int(os.environ.get("PORT", 7860))
+    print(f"\n🚀 Iniciando servidor en puerto {port}...")
+    print(f"🌐 Interfaz web: http://0.0.0.0:{port}")
+    print(f"📡 API docs: http://0.0.0.0:{port}/docs")
+    
+    uvicorn.run(
+        app,
+        host="0.0.0.0",
+        port=port,
+        log_level="info"
+    )