feat: Implement main application shell with navigation and color scheme toggle

- Added Appshell component with responsive navbar and main content area
- Integrated ColorSchemeToggle for light/dark mode switching
- Created Welcome component with styled title and introductory text
- Developed ChatPage for LLM interaction with WebSocket support
- Implemented Biblioteca for managing notes with rich text editor
- Added LoginPage for user authentication with error handling
- Introduced MessageList and MessageBubble components for chat messages
- Styled components with CSS modules for consistent design

domains/Llms/Modelos/Openai_model_mmr.py

@@ -0,0 +1,122 @@
+import os
+from dotenv import load_dotenv
+from sqlalchemy import Column, Integer, String, Float, Boolean
+
+from domains.ArquitectureLayer.Mapper import Mapper_base
+from domains.ArquitectureLayer.Model import Model_base
+from domains.ArquitectureLayer.Repo import Repo_base
+from typing import Optional
+
+
+from domains.ConexionSql.Base_conexion import ConexionBase
+from domains.base import Base
+from domains.Llms.Modelos.Openai_model import ModeloOpenAI  # Clase real de lógica
+
+# ----------------------
+# Cargar clave maestra
+# ----------------------
+from entrypoint import ENV_PATH
+load_dotenv(ENV_PATH)
+pssword = os.getenv('MASTER_PASSWORD')
+if pssword is None:
+    raise ValueError("MASTER_PASSWORD no está definida en el archivo .env")
+
+# ----------------------
+# MODELO (SQLAlchemy)
+# ----------------------
+
+class ModeloOpenAIConfigModel(Base, Model_base):
+    __tablename__ = 'modelo_openai_configs'
+
+    id = Column(String, primary_key=True)
+
+    model = Column(String, nullable=False)
+    temperature = Column(Float, default=0.7, nullable=False)
+    top_p = Column(Float, default=1.0, nullable=False)
+    top_k = Column(Integer, nullable=True)
+
+    frecuencia_penalizacion = Column(Float, default=0.0, nullable=False)
+    num_tokens_maximos = Column(Integer, default=512, nullable=False)
+
+    use_legacy = Column(Boolean, default=False, nullable=False)
+
+# ----------------------
+# MAPPER
+# ----------------------
+
+class ModeloOpenAIConfigMapper(Mapper_base[ModeloOpenAI, ModeloOpenAIConfigModel]):
+
+    @staticmethod
+    def to_model(obj: ModeloOpenAI) -> ModeloOpenAIConfigModel:
+        return ModeloOpenAIConfigModel(
+            id=obj.id,
+            model=obj.model,
+            temperature=obj.temperature,
+            top_p=obj.top_p,
+            top_k=obj.top_k,
+            frecuencia_penalizacion=obj.frecuencia_penalizacion,
+            num_tokens_maximos=obj.num_tokens_maximos,
+            use_legacy=obj.use_legacy
+        )
+
+    @staticmethod
+    def from_model(model: ModeloOpenAIConfigModel, cliente: Optional[object] = None) -> ModeloOpenAI:
+        return ModeloOpenAI(
+            id=model.id,
+            cliente=cliente,
+            model=model.model,
+            temperature=model.temperature,
+            top_p=model.top_p,
+            top_k=model.top_k,
+            frecuencia_penalizacion=model.frecuencia_penalizacion,
+            num_tokens_maximos=model.num_tokens_maximos,
+            use_legacy=model.use_legacy
+        )
+
+    @staticmethod
+    def to_dict(obj: ModeloOpenAI) -> dict:
+        return {
+            "id": obj.id,
+            "model": obj.model,
+            "temperature": obj.temperature,
+            "top_p": obj.top_p,
+            "top_k": obj.top_k,
+            "frecuencia_penalizacion": obj.frecuencia_penalizacion,
+            "num_tokens_maximos": obj.num_tokens_maximos,
+            "use_legacy": obj.use_legacy
+        }
+
+    @staticmethod
+    def from_dict(data: dict, cliente: Optional[object] = None) -> ModeloOpenAI:
+        return ModeloOpenAI(
+            id=data["id"],
+            cliente=cliente,
+            model=data["model"],
+            temperature=data["temperature"],
+            top_p=data["top_p"],
+            top_k=data["top_k"],
+            frecuencia_penalizacion=data["frecuencia_penalizacion"],
+            num_tokens_maximos=data["num_tokens_maximos"],
+            use_legacy=data["use_legacy"]
+        )
+
+# ----------------------
+# REPO
+# ----------------------
+
+class ModeloOpenAIConfigRepo(Repo_base[ModeloOpenAIConfigModel, ModeloOpenAI]):
+    def __init__(self, conexion: ConexionBase, cliente: object):
+        super().__init__(
+            session=conexion.get_session(),
+            modelo=ModeloOpenAIConfigModel,
+            mapper=ModeloOpenAIConfigMapper
+        )
+        self.cliente = cliente  # Necesario para construir el dominio con lógica
+
+    def get_by_id(self, id_: str) -> ModeloOpenAI | None:
+        model = self.session.get(self.Modelo, id_)
+        return self.Mapper.from_model(model, self.cliente) if model else None
+
+    def get_all(self) -> list[ModeloOpenAI]:
+        models = self.session.query(self.Modelo).all()
+        return [self.Mapper.from_model(m, self.cliente) for m in models]