feat: Implement LLM and scheduler functionalities

This commit finalizes Phase 4 of the project by implementing the
LLM and scheduler integrations.

- Implements `get_smart_response` in `app/llm.py` to generate
  AI-powered responses using the OpenAI API.
- Implements a daily summary scheduler in `app/scheduler.py` using
  the `JobQueue` from `python-telegram-bot` for better integration
  with the application's event loop.
- Adds `get_events_for_day` to `app/calendar.py` to fetch daily
  events for the summary.
- Integrates the scheduler into the main application loop in
  `app/main.py`.
- Improves the date formatting in the daily summary for better
  readability.
- Updates `tasks.md` to reflect the completion of Phase 4.

app/main.py

@@ -28,6 +28,7 @@ from modules.equipo import (
 from modules.aprobaciones import view_pending, handle_approval_action
 from modules.servicios import get_service_info
 from modules.admin import get_system_status
+from app.scheduler import setup_scheduler
 
 # Enable logging
 logging.basicConfig(
@@ -103,6 +104,9 @@ def main() -> None:
     application.add_handler(CommandHandler("start", start))
     application.add_handler(CallbackQueryHandler(button_dispatcher))
 
+    # Set up the scheduler
+    setup_scheduler(application)
+
     logger.info("Starting Talía Bot...")
     application.run_polling()