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

backend/backend_domains/llms/llm_chat_endpoint_v1.py

@@ -0,0 +1,44 @@
+# backend/domains/llm/agent_endpoints.py
+
+from fastapi import APIRouter, HTTPException
+from fastapi.responses import StreamingResponse
+from pydantic import BaseModel
+from fastapi.concurrency import run_in_threadpool
+
+from backend.backend_domains.llms.llm_chat_srvc import construir_agente_llm, responder, responder_stream
+from domains.Logger.logger_db import LoggerDB, logger
+from entrypoint.init_db import db_credencial
+
+LoggerDB(db_credencial, "logger_llm", created_by="sistema")
+
+router = APIRouter()
+agente = construir_agente_llm()  # inicializa el agente una vez
+
+# 📥 Schema para entrada de prompt
+class ChatInput(BaseModel):
+    prompt: str
+
+# ✅ Endpoint de respuesta simple
+@router.post("/chat", summary="Enviar prompt y obtener respuesta completa del agente")
+async def chat_endpoint(data: ChatInput):
+    try:
+        return await responder(data.prompt, agente)
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    except Exception as e:
+        logger.exception("[ERROR] Fallo durante respuesta del agente:")
+        raise HTTPException(status_code=500, detail="Error interno al procesar la solicitud.")
+
+# 🔁 Endpoint de streaming
+@router.post("/chat-stream", summary="Enviar prompt y recibir respuesta del agente en streaming")
+async def chat_stream_endpoint(data: ChatInput):
+    try:
+        return StreamingResponse(
+            responder_stream(data.prompt, agente),
+            media_type="text/plain"
+        )
+    except ValueError as e:
+        raise HTTPException(status_code=400, detail=str(e))
+    except Exception as e:
+        logger.exception("[ERROR] Fallo durante respuesta en streaming:")
+        raise HTTPException(status_code=500, detail="Error interno en el agente.")