Create app.py

app.py

@@ -0,0 +1,264 @@
+import os
+import gradio as gr
+import base64
+import io
+import json
+import re
+from PIL import Image
+from sambanova import SambaNova
+from contextlib import redirect_stdout
+
+# =========================
+# CONFIGURACIÓN
+# =========================
+API_KEY = os.getenv("SAMBANOVA_API_KEY")
+
+if not API_KEY:
+    raise ValueError("❌ Error: Configura la variable SAMBANOVA_API_KEY")
+
+client = SambaNova(
+    api_key=API_KEY,
+    base_url="https://api.sambanova.ai/v1",
+)
+
+# =========================
+# MODELOS
+# =========================
+MODELS = {
+    "vision": "Llama-4-Maverick-17B-128E-Instruct",
+    "code": "DeepSeek-R1-Distill-Llama-70B",
+    "general_precise": "gpt-oss-120b",
+    "general_creative": "Qwen3-32B",
+}
+
+# =========================
+# CLASIFICACIÓN LOCAL
+# =========================
+def classify_task_local(message, has_image):
+    if has_image:
+        return "vision"
+
+    msg = message.lower().strip()
+    if re.search(r'\b(imagen|foto|describe|ver|colores|visual|ocr|objeto)\b', msg):
+        return "vision"
+    if re.search(r'\b(código|python|js|java|debug|función|error|clase|algoritmo)\b', msg):
+        return "code"
+    if re.search(r'\b(historia|cuento|poema|escribe|creativo|inventa|relato|personaje)\b', msg):
+        return "general_creative"
+    return "general_precise"
+
+# =========================
+# HERRAMIENTAS
+# =========================
+TOOLS = [
+    {
+        "type": "function",
+        "function": {
+            "name": "execute_python",
+            "description": "Ejecuta código Python en sandbox seguro.",
+            "parameters": {
+                "type": "object",
+                "properties": {"code": {"type": "string"}},
+                "required": ["code"]
+            }
+        }
+    }
+]
+
+def execute_tool(tool_call):
+    name = tool_call.function.name
+    try:
+        args = json.loads(tool_call.function.arguments)
+    except json.JSONDecodeError:
+        return "❌ Argumentos inválidos."
+
+    if name == "execute_python":
+        code = args.get("code", "")
+        if not code.strip():
+            return "❌ Código vacío."
+        output = io.StringIO()
+        try:
+            with redirect_stdout(output):
+                exec(code, {"__builtins__": {}}, {})
+            result = output.getvalue().strip()
+            return f"✅ {result}" if result else "✅ Ejecutado sin salida."
+        except Exception as e:
+            return f"❌ Error: {str(e)}"
+    return f"❌ Tool no implementada: {name}"
+
+# =========================
+# ESTILO VISUAL DEL MODELO
+# =========================
+def model_badge(model_name):
+    colors = {
+        "gpt": "background-color:#3182ce;color:white;",
+        "Qwen3": "background-color:#38a169;color:white;",
+        "DeepSeek": "background-color:#e53e3e;color:white;",
+        "Llama": "background-color:#805ad5;color:white;",
+    }
+    for key, style in colors.items():
+        if key.lower() in model_name.lower():
+            return f'<span style="{style}padding:2px 6px;border-radius:6px;font-size:0.8em;">{model_name}</span>'
+    return f'<span style="background-color:#718096;color:white;padding:2px 6px;border-radius:6px;font-size:0.8em;">{model_name}</span>'
+
+# =========================
+# CHAT PRINCIPAL - CORREGIDO
+# =========================
+def chat_with_batuto(system_prompt, message, image, history):
+    if not message.strip():
+        return history, "", None
+
+    has_image = image is not None
+    task_type = classify_task_local(message, has_image)
+    selected_model = MODELS[task_type]
+    model_name = selected_model.split('-')[0]
+
+    # Construir mensajes para la API
+    messages = [{"role": "system", "content": system_prompt or "Eres BATUTO/ANDROIDE_90. Responde natural en español."}]
+    
+    # Convertir historial de Gradio a formato de API
+    for entry in history:
+        if isinstance(entry, list) and len(entry) == 2:
+            user_msg, bot_msg = entry
+            messages.append({"role": "user", "content": str(user_msg)})
+            messages.append({"role": "assistant", "content": str(bot_msg)})
+
+    # Agregar mensaje actual
+    if selected_model == "Llama-4-Maverick-17B-128E-Instruct" and has_image:
+        buffered = io.BytesIO()
+        image.save(buffered, format="PNG", optimize=True)
+        b64_img = base64.b64encode(buffered.getvalue()).decode()
+        content = [
+            {"type": "text", "text": message},
+            {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{b64_img}"}}
+        ]
+        messages.append({"role": "user", "content": content})
+    else:
+        messages.append({"role": "user", "content": message})
+
+    try:
+        tools_param = TOOLS if task_type != "vision" else None
+        api_call = client.chat.completions.create(
+            model=selected_model,
+            messages=messages,
+            tools=tools_param,
+            tool_choice="auto" if tools_param else None,
+            temperature=0.15,
+            top_p=0.1,
+            max_tokens=1024,
+        )
+
+        msg_out = api_call.choices[0].message
+        badge = model_badge(selected_model)
+        
+        # Procesar respuesta
+        if msg_out.content:
+            reply = f"{badge} {msg_out.content}"
+        elif hasattr(msg_out, 'tool_calls') and msg_out.tool_calls:
+            tool_results = []
+            for tool_call in msg_out.tool_calls:
+                result = execute_tool(tool_call)
+                tool_results.append(f"🔧 {tool_call.function.name}: {result}")
+            reply = f"{badge} " + "\n".join(tool_results)
+        else:
+            reply = f"{badge} Respuesta vacía."
+
+        # Actualizar historial en formato Gradio (tuplas)
+        history.append((message, reply))
+        return history, "", None
+
+    except Exception as e:
+        import traceback
+        error = f"❌ [{model_name}] {str(e)}"
+        print(f"Error completo: {traceback.format_exc()}")
+        history.append((message, error))
+        return history, "", None
+
+# =========================
+# INTERFAZ DE GRADIO - CORREGIDA
+# =========================
+def clear_inputs():
+    return [], "", None
+
+with gr.Blocks(
+    title="🤖 BATUTO/ANDROIDE_90 Pro",
+    theme=gr.themes.Soft(primary_hue="blue"),
+    css="""
+    .gradio-container {max-width: 1000px !important; margin: auto;}
+    .header {text-align: center; padding: 15px; background: linear-gradient(135deg,#667eea 0%,#764ba2 100%); color: white; border-radius: 8px;}
+    .chatbot {min-height: 480px;}
+    """,
+) as demo:
+
+    with gr.Column(elem_classes="header"):
+        gr.Markdown("""
+        # 🤖 BATUTO/ANDROIDE_90 Pro  
+        **Modelos SambaNova optimizados con selección automática y visualización**
+        """)
+
+    with gr.Tabs():
+        with gr.TabItem("💬 Chat"):
+            system_prompt = gr.Textbox(
+                lines=3, 
+                value="Eres BATUTO/ANDROIDE_90. Responde de manera natural y precisa en español.",
+                label="Prompt del sistema"
+            )
+            # Cambiar a type por defecto (sin "messages")
+            chatbot = gr.Chatbot(
+                height=480, 
+                show_copy_button=True,
+                elem_classes="chatbot"
+            )
+            msg = gr.Textbox(placeholder="Escribe tu mensaje...", label="Mensaje")
+            img = gr.Image(type="pil", label="Imagen opcional")
+
+            send = gr.Button("🚀 Enviar", variant="primary")
+            clear = gr.Button("🧹 Limpiar")
+
+            send.click(
+                chat_with_batuto, 
+                [system_prompt, msg, img, chatbot], 
+                [chatbot, msg, img]
+            )
+            msg.submit(
+                chat_with_batuto, 
+                [system_prompt, msg, img, chatbot], 
+                [chatbot, msg, img]
+            )
+            clear.click(clear_inputs, None, [chatbot, msg, img])
+
+        with gr.TabItem("⚙️ Ejecutor de Código"):
+            gr.Markdown("### Ejecutor Independiente de Python")
+            code_input = gr.Code(
+                language="python", 
+                lines=8, 
+                value='print("¡Hola desde BATUTO!")\nresultado = 2 + 2\nprint(f"2 + 2 = {resultado}")',
+                label="Código Python"
+            )
+            exec_output = gr.Textbox(
+                lines=8, 
+                label="Resultado de la ejecución",
+                interactive=False
+            )
+
+            def execute_independent(code):
+                if not code.strip():
+                    return "❌ Código vacío."
+                
+                output = io.StringIO()
+                try:
+                    with redirect_stdout(output):
+                        exec(code, {"__builtins__": {}}, {})
+                    result = output.getvalue().strip()
+                    return f"✅ Ejecutado correctamente:\n{result}" if result else "✅ Código ejecutado sin salida."
+                except Exception as e:
+                    return f"❌ Error:\n{str(e)}"
+
+            exec_button = gr.Button("▶️ Ejecutar Código", variant="primary")
+            exec_button.click(execute_independent, code_input, exec_output)
+
+    gr.Markdown("**Estado:** ✅ Modelos SambaNova activos | Visualización multimodal habilitada")
+
+# Lanzar la app
+if __name__ == "__main__":
+    demo.launch(share=True, show_error=True)