Delate app.py

app.py

@@ -1,559 +0,0 @@
-import os
-import io
-import base64
-import json
-import requests
-import tempfile
-from PIL import Image
-import gradio as gr
-from huggingface_hub import InferenceClient
-from openai import OpenAI
-
-# ============================================================
-#   CONFIGURACIÓN
-# ============================================================
-
-# SambaNova
-SAMBA_API_KEY = os.getenv("REVE_API_KEY")
-SAMBA_BASE_URL = "https://api.sambanova.ai/v1"
-
-# OpenRouter
-OPENROUTER_API_KEY = os.getenv("OPENROUTER_API_KEY")
-if not OPENROUTER_API_KEY:
-    raise ValueError("Falta la variable OPENROUTER_API_KEY.")
-
-openrouter_client = OpenAI(
-    base_url="https://openrouter.ai/api/v1",
-    api_key=OPENROUTER_API_KEY
-)
-
-# Hugging Face (para generación de imágenes)
-HF_TOKEN = os.getenv("HF_TOKEN")
-
-DEBUG = False  # Ponlo en True si quieres ver el payload enviado a SambaNova
-
-# ============================================================
-#   TODOS LOS MODELOS (SAMBA + OPENROUTER) CON ROLES
-# ============================================================
-
-MODELS = {
-    # ===================== SAMBANOVA =====================
-    "general_fast": {
-        "provider": "sambanova",
-        "name": "Meta-Llama-3.1-8B-Instruct",
-        "role": "🔄 Respuestas rápidas y generales. Conversación ligera y eficiente.",
-        "supports_images": False
-    },
-    "general_smart": {
-        "provider": "sambanova",
-        "name": "Meta-Llama-3.3-70B-Instruct",
-        "role": "🧠 Razonamiento profundo. Análisis detallado y avanzado.",
-        "supports_images": False
-    },
-    "coding_expert": {
-        "provider": "sambanova",
-        "name": "DeepSeek-V3.1",
-        "role": "💻 Programación y debugging. Ideal para desarrollo.",
-        "supports_images": False
-    },
-    "coding_alt": {
-        "provider": "sambanova",
-        "name": "DeepSeek-V3-0324",
-        "role": "⚡ Código rápido. Alternativa veloz.",
-        "supports_images": False
-    },
-    "massive_brain": {
-        "provider": "sambanova",
-        "name": "gpt-oss-120b",
-        "role": "🏛️ Sabiduría masiva. Problemas pesados y complejos.",
-        "supports_images": False
-    },
-    "specialized_1": {
-        "provider": "sambanova",
-        "name": "DeepSeek-V3.1-Terminus",
-        "role": "🎯 Especialista técnico. Tareas científicas y avanzadas.",
-        "supports_images": False
-    },
-    "specialized_2": {
-        "provider": "sambanova",
-        "name": "Llama-3.3-Swallow-70B-Instruct-v0.4",
-        "role": "🔥 Sin censura. Modelo sin restricciones.",
-        "supports_images": False
-    },
-    "multilingual": {
-        "provider": "sambanova",
-        "name": "Qwen3-32B",
-        "role": "🌍 Multilingüe. Manejo de múltiples idiomas.",
-        "supports_images": False
-    },
-    "vision_expert": {
-        "provider": "sambanova",
-        "name": "Llama-4-Maverick-17B-128E-Instruct",
-        "role": "👁️ Visión avanzada. Análisis de imágenes.",
-        "supports_images": True
-    },
-    "boudoir_specialist": {
-        "provider": "sambanova",
-        "name": "ALLaM-7B-Instruct-preview",
-        "role": "🎭 Especialista en Fotografía Íntima Profesional. Experto en prompts para fotografía boudoir.",
-        "supports_images": False,
-        "specialties": [
-            "Fotografía Boudoir",
-            "Desnudo Artístico",
-            "Moda Sensual",
-            "Lencería y moda íntima"
-        ],
-        "technical_expertise": [
-            "Iluminación suave",
-            "Composición elegante",
-            "Dirección de poses",
-            "Edición fina",
-            "Escenografía íntima"
-        ],
-        "ethical_principles": [
-            "Consentimiento explícito",
-            "Positividad corporal"
-        ]
-    },
-
-    # ===================== OPENROUTER =====================
-    # META LLAMA
-    "llama_3.1_70b": {
-        "provider": "openrouter",
-        "name": "meta-llama/llama-3.1-70b-instruct",
-        "role": "Respondes con precisión técnica y claridad.",
-        "supports_images": False
-    },
-    "llama_3.1_405b": {
-        "provider": "openrouter",
-        "name": "meta-llama/llama-3.1-405b-instruct",
-        "role": "Eres experto en programación, ciencia y análisis avanzado.",
-        "supports_images": False
-    },
-
-    # LLAMA 3.2 VISION
-    "llama_3.2_11b_vision": {
-        "provider": "openrouter",
-        "name": "meta-llama/llama-3.2-11b-vision-instruct",
-        "role": "Eres un modelo experto en análisis visual detallado.",
-        "supports_images": True
-    },
-    "llama_3.2_90b_vision": {
-        "provider": "openrouter",
-        "name": "meta-llama/llama-3.2-90b-vision-instruct",
-        "role": "Eres un analista visual avanzado altamente preciso.",
-        "supports_images": True
-    },
-
-    # QWEN
-    "qwen_72b": {
-        "provider": "openrouter",
-        "name": "qwen/qwen2.5-72b-instruct",
-        "role": "Respondes de forma profesional, directa y clara.",
-        "supports_images": False
-    },
-    "qwen_110b": {
-        "provider": "openrouter",
-        "name": "qwen/qwen2.5-110b-instruct",
-        "role": "Asistente experto en razonamiento estructurado.",
-        "supports_images": False
-    },
-
-    # GPT / OPENAI
-    "gpt_4.1": {
-        "provider": "openrouter",
-        "name": "openai/gpt-4.1",
-        "role": "Asistente avanzado para cualquier tarea general.",
-        "supports_images": False
-    },
-    "gpt_4.1_mini": {
-        "provider": "openrouter",
-        "name": "openai/gpt-4.1-mini",
-        "role": "Modelo rápido y eficiente, ideal para respuestas concisas.",
-        "supports_images": False
-    },
-    "gpt_4o_mini": {
-        "provider": "openrouter",
-        "name": "openai/gpt-4o-mini",
-        "role": "Asistente veloz con buena comprensión general.",
-        "supports_images": False
-    },
-
-    # CLAUDE
-    "claude_3.5_sonnet": {
-        "provider": "openrouter",
-        "name": "anthropic/claude-3.5-sonnet",
-        "role": "Especialista en redacción, precisión y análisis profundo.",
-        "supports_images": False
-    },
-    "claude_3.5_haiku": {
-        "provider": "openrouter",
-        "name": "anthropic/claude-3.5-haiku",
-        "role": "Modelo rápido con buena comprensión general.",
-        "supports_images": False
-    },
-    "claude_3_opus": {
-        "provider": "openrouter",
-        "name": "anthropic/claude-3-opus",
-        "role": "Máxima capacidad de análisis y lenguaje.",
-        "supports_images": False
-    },
-
-    # GOOGLE GEMINI
-    "gemini_flash": {
-        "provider": "openrouter",
-        "name": "google/gemini-flash-1.5",
-        "role": "Especialista en escenarios visuales y respuestas rápidas.",
-        "supports_images": True
-    },
-    "gemini_pro": {
-        "provider": "openrouter",
-        "name": "google/gemini-pro-1.5",
-        "role": "Razonador general robusto y flexible.",
-        "supports_images": True
-    },
-    "gemini_thinking": {
-        "provider": "openrouter",
-        "name": "google/gemini-1.5-thinking",
-        "role": "Modelo de razonamiento profundo y detallado.",
-        "supports_images": True
-    },
-
-    # DEEPSEEK
-    "deepseek_r1": {
-        "provider": "openrouter",
-        "name": "deepseek/deepseek-r1",
-        "role": "Razonamiento profundo y cadena de pensamiento estructurada.",
-        "supports_images": False
-    },
-
-    # MISTRAL
-    "mistral_large": {
-        "provider": "openrouter",
-        "name": "mistral/mistral-large-latest",
-        "role": "Asistente técnico avanzado y preciso.",
-        "supports_images": False
-    },
-    "mixtral_8x7b": {
-        "provider": "openrouter",
-        "name": "mistral/mixtral-8x7b-instruct",
-        "role": "Modelo eficiente para tareas complejas sin alto costo.",
-        "supports_images": False
-    },
-
-    # REKA
-    "reka_core": {
-        "provider": "openrouter",
-        "name": "reka/core",
-        "role": "Asistente racional y estructurado.",
-        "supports_images": False
-    },
-
-    # SAMBANOVA EN OPENROUTER
-    "samba_allam_7b": {
-        "provider": "openrouter",
-        "name": "sambanova/ALLAM-1-7B",
-        "role": "Asistente optimizado para rendimiento y claridad.",
-        "supports_images": False
-    },
-
-    # FLUX
-    "flux_pro": {
-        "provider": "openrouter",
-        "name": "black-forest-labs/flux-1.1-pro",
-        "role": "Experto en generación y análisis de imágenes.",
-        "supports_images": True
-    }
-}
-
-# ============================================================
-#   HELPERS
-# ============================================================
-
-def encode_image_to_base64(image):
-    if image is None:
-        return None
-    buf = io.BytesIO()
-    # Usar JPEG para mejor compatibilidad
-    if image.mode in ('RGBA', 'LA', 'P'):
-        # Convertir imágenes con alpha channel a RGB
-        background = Image.new('RGB', image.size, (255, 255, 255))
-        if image.mode == 'P':
-            image = image.convert('RGBA')
-        background.paste(image, mask=image.split()[-1] if image.mode == 'RGBA' else None)
-        image = background
-    image.save(buf, format="JPEG", quality=95)
-    return base64.b64encode(buf.getvalue()).decode("utf-8")
-
-def build_messages(system_prompt, user_input, history, image_b64, supports_images):
-    messages = []
-
-    if system_prompt:
-        messages.append({"role": "system", "content": system_prompt})
-
-    # Procesar historial de Gradio
-    for entry in history:
-        if isinstance(entry, (list, tuple)) and len(entry) == 2:
-            user_msg, assistant_msg = entry
-            
-            # Solo agregar mensajes no vacíos
-            if user_msg and str(user_msg).strip():
-                messages.append({"role": "user", "content": str(user_msg).strip()})
-            
-            if assistant_msg and str(assistant_msg).strip():
-                messages.append({"role": "assistant", "content": str(assistant_msg).strip()})
-
-    # Manejar mensaje actual con imagen
-    current_content = []
-    
-    # Agregar texto si existe
-    if user_input and str(user_input).strip():
-        current_content.append({"type": "text", "text": str(user_input).strip()})
-    
-    # Agregar imagen si existe y es compatible
-    if image_b64 and supports_images:
-        current_content.append({
-            "type": "image_url", 
-            "image_url": {"url": f"data:image/jpeg;base64,{image_b64}"}
-        })
-    
-    # Solo agregar el mensaje si hay contenido
-    if current_content:
-        # Si solo hay texto, usar formato simple
-        if len(current_content) == 1 and current_content[0]["type"] == "text":
-            messages.append({"role": "user", "content": current_content[0]["text"]})
-        else:
-            messages.append({"role": "user", "content": current_content})
-    elif not user_input and not image_b64:
-        # Si no hay contenido, agregar mensaje vacío para mantener la conversación
-        messages.append({"role": "user", "content": ""})
-
-    return messages
-
-# ============================================================
-#   LLAMADAS A LOS MODELOS
-# ============================================================
-
-def call_sambanova(model_name, messages):
-    payload = {
-        "model": model_name,
-        "messages": messages,
-        "stream": False
-    }
-
-    if DEBUG:
-        print("=== DEBUG SAMBANOVA PAYLOAD ===")
-        print(json.dumps(payload, indent=2, ensure_ascii=False))
-        print("=== END DEBUG ===")
-
-    headers = {
-        "Authorization": f"Bearer {SAMBA_API_KEY}",
-        "Content-Type": "application/json"
-    }
-
-    try:
-        r = requests.post(
-            f"{SAMBA_BASE_URL}/chat/completions",
-            json=payload,
-            headers=headers,
-            timeout=60
-        )
-        r.raise_for_status()
-        
-        data = r.json()
-        return data["choices"][0]["message"]["content"]
-    except requests.exceptions.RequestException as e:
-        return f"Error en la conexión con SambaNova: {str(e)}"
-    except Exception as e:
-        return f"Error procesando respuesta de SambaNova: {str(e)}"
-
-def call_openrouter(model_name, messages):
-    try:
-        response = openrouter_client.chat.completions.create(
-            model=model_name,
-            messages=messages,
-            temperature=0.7
-        )
-        return response.choices[0].message.content
-    except Exception as e:
-        return f"Error en OpenRouter: {str(e)}"
-
-# ============================================================
-#   LÓGICA DEL CHAT
-# ============================================================
-
-def chat_logic(user_text, user_image, model_key, history):
-    if history is None:
-        history = []
-
-    if model_key not in MODELS:
-        reply = "Error: modelo no encontrado."
-        history.append((user_text or "", reply))
-        return history, history
-
-    try:
-        model_cfg = MODELS[model_key]
-        image_b64 = encode_image_to_base64(user_image) if user_image else None
-
-        messages = build_messages(
-            system_prompt=model_cfg["role"],
-            user_input=user_text,
-            history=history,
-            image_b64=image_b64,
-            supports_images=model_cfg.get("supports_images", False)
-        )
-
-        if DEBUG:
-            print("=== FINAL MESSAGES ===")
-            for i, msg in enumerate(messages):
-                print(f"{i}: {msg['role']} - {type(msg['content'])}")
-                if isinstance(msg['content'], list):
-                    for item in msg['content']:
-                        print(f"   - {item['type']}")
-            print("=== END MESSAGES ===")
-
-        if model_cfg["provider"] == "sambanova":
-            reply = call_sambanova(model_cfg["name"], messages)
-        else:
-            reply = call_openrouter(model_cfg["name"], messages)
-
-        # Usar texto vacío si no hay entrada del usuario
-        display_text = user_text or ("[Imagen]" if user_image else "")
-        history.append((display_text, reply))
-        
-    except Exception as e:
-        error_msg = f"Error: {str(e)}"
-        history.append((user_text or "", error_msg))
-
-    return history, history
-
-# ============================================================
-#   GENERACIÓN DE IMÁGENES (HUGGING FACE, OPCIONAL)
-# ============================================================
-
-def generate_image_hf(prompt):
-    if not HF_TOKEN:
-        return None, "❌ Falta HF_TOKEN", gr.update(visible=False)
-
-    try:
-        client = InferenceClient(token=HF_TOKEN)
-        img = client.text_to_image(
-            prompt,
-            model="stabilityai/stable-diffusion-xl-base-1.0"
-        )
-
-        with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
-            img.save(tmp, format="PNG")
-            return img, "✅ Imagen generada", gr.update(value=tmp.name, visible=True)
-
-    except Exception as e:
-        return None, f"❌ Error: {e}", gr.update(visible=False)
-
-# ============================================================
-#   UI GRADIO UNIFICADA
-# ============================================================
-
-def create_ui():
-    with gr.Blocks(theme="soft") as demo:
-        gr.Markdown("## 🤖 Chat Multimodelo (SambaNova + OpenRouter)")
-        
-        with gr.Row():
-            with gr.Column(scale=1):
-                model_sel = gr.Dropdown(
-                    choices=list(MODELS.keys()),
-                    value="general_fast",
-                    label="Seleccionar Modelo",
-                    info="Elige el modelo que quieres usar"
-                )
-                gr.Markdown("### 📝 Instrucciones")
-                gr.Markdown("""
-                - **Texto**: Escribe tu mensaje normalmente
-                - **Imágenes**: Algunos modelos soportan análisis de imágenes
-                - **Historial**: La conversación se mantiene durante la sesión
-                """)
-                
-            with gr.Column(scale=2):
-                with gr.Tab("💬 Chat"):
-                    chat = gr.Chatbot(
-                        height=500, 
-                        label="Conversación",
-                        show_copy_button=True
-                    )
-                    with gr.Row():
-                        img = gr.Image(
-                            type="pil", 
-                            label="Imagen opcional (solo para modelos de visión)",
-                            height=150
-                        )
-                    with gr.Row():
-                        txt = gr.Textbox(
-                            label="Tu mensaje", 
-                            placeholder="Escribe tu mensaje aquí...", 
-                            lines=3,
-                            scale=4
-                        )
-                        send = gr.Button("🚀 Enviar", scale=1)
-                    
-                    # Botón para limpiar chat
-                    clear_btn = gr.Button("🧹 Limpiar Chat")
-
-        with gr.Tab("🎨 Generar Imágenes (HF)"):
-            gr.Markdown("### Generación de imágenes con Stable Diffusion XL")
-            gr.Markdown("Usa Hugging Face para generar imágenes a partir de texto.")
-            with gr.Row():
-                with gr.Column():
-                    p = gr.Textbox(
-                        label="Prompt para la imagen",
-                        placeholder="Describe la imagen que quieres generar...",
-                        lines=3
-                    )
-                    generate_btn = gr.Button("🖼️ Generar Imagen")
-                with gr.Column():
-                    out = gr.Image(label="Imagen generada", height=400)
-                    status = gr.Textbox(label="Estado", interactive=False)
-                    d = gr.DownloadButton("📥 Descargar", visible=False)
-        
-        # Conectar eventos
-        send.click(
-            chat_logic,
-            inputs=[txt, img, model_sel, chat],
-            outputs=[chat, chat]
-        ).then(
-            lambda: ("", None),  # Limpiar inputs después de enviar
-            outputs=[txt, img]
-        )
-        
-        txt.submit(
-            chat_logic,
-            inputs=[txt, img, model_sel, chat],
-            outputs=[chat, chat]
-        ).then(
-            lambda: ("", None),
-            outputs=[txt, img]
-        )
-        
-        clear_btn.click(
-            lambda: ([], []),
-            outputs=[chat, chat]
-        )
-        
-        generate_btn.click(
-            generate_image_hf,
-            inputs=[p],
-            outputs=[out, status, d]
-        )
-
-    return demo
-
-# ============================================================
-#   EJECUCIÓN
-# ============================================================
-
-demo = create_ui()
-
-if __name__ == "__main__":
-    demo.launch(
-        share=False,
-        show_error=True,
-        debug=False
-    )