feat: Implement LLM and scheduler modules

- Implement `llm.py` with OpenAI API integration for smart responses.
- Implement `scheduler.py` to send a daily summary to the bot owner using `python-telegram-bot`'s `JobQueue`.
- Integrate the scheduler into the main application.
- Add `pytz` as a new dependency.
- Update `tasks.md` to mark all tasks as complete.

app/llm.py

@@ -1,15 +1,23 @@
 # app/llm.py
-
+import openai
 from config import OPENAI_API_KEY
 
 def get_smart_response(prompt):
     """
-    Generates a smart response using an LLM.
+    Generates a smart response using the OpenAI API.
     """
-
     if not OPENAI_API_KEY:
-        return "OpenAI API key not configured."
+        return "Error: OpenAI API key is not configured."
 
-    print(f"Generating smart response for: {prompt}")
-    # TODO: Implement OpenAI API integration
-    return "This is a smart response."
+    try:
+        client = openai.OpenAI(api_key=OPENAI_API_KEY)
+        response = client.chat.completions.create(
+            model="gpt-3.5-turbo",
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": prompt},
+            ],
+        )
+        return response.choices[0].message.content.strip()
+    except Exception as e:
+        return f"An error occurred while communicating with OpenAI: {e}"

app/main.py

@@ -29,6 +29,7 @@ from modules.aprobaciones import view_pending, handle_approval_action
 from modules.servicios import get_service_info
 from modules.admin import get_system_status
 from modules.print import print_handler
+from app.scheduler import schedule_daily_summary
 
 # Enable logging
 logging.basicConfig(
@@ -89,6 +90,9 @@ def main() -> None:
 
     application = Application.builder().token(TELEGRAM_BOT_TOKEN).build()
 
+    # Schedule daily summary
+    schedule_daily_summary(application)
+
     # Conversation handler for proposing activities
     conv_handler = ConversationHandler(
         entry_points=[CallbackQueryHandler(propose_activity_start, pattern='^propose_activity$')],

app/scheduler.py

@@ -1,27 +1,54 @@
 # app/scheduler.py
+import logging
+from datetime import time
+from telegram.ext import ContextTypes
+import pytz
 
-import schedule
-import time
-from datetime import datetime
+from app.config import OWNER_CHAT_ID, TIMEZONE
+from app.modules.agenda import get_agenda
 
-from config import TIMEZONE
+# Enable logging
+logger = logging.getLogger(__name__)
 
-def send_daily_summary():
-    """
-    Sends the daily summary to the owner.
-    """
-    print(f"[{datetime.now()}] Sending daily summary...")
-    # TODO: Implement the logic to fetch and send the summary
+async def send_daily_summary(context: ContextTypes.DEFAULT_TYPE) -> None:
+    """Sends the daily summary to the owner."""
+    job = context.job
+    chat_id = job.chat_id
 
-def main():
-    """
-    Main function to run the scheduler.
-    """
-    schedule.every().day.at("07:00").do(send_daily_summary)
+    logger.info(f"Running daily summary job for chat_id: {chat_id}")
 
-    while True:
-        schedule.run_pending()
-        time.sleep(1)
+    try:
+        agenda_text = get_agenda()
+        summary_text = f"🔔 *Resumen Diario - Buen día, Marco!*\n\n{agenda_text}"
 
-if __name__ == "__main__":
-    main()
+        await context.bot.send_message(
+            chat_id=chat_id,
+            text=summary_text,
+            parse_mode='Markdown'
+        )
+        logger.info(f"Successfully sent daily summary to {chat_id}")
+    except Exception as e:
+        logger.error(f"Failed to send daily summary to {chat_id}: {e}")
+
+def schedule_daily_summary(application) -> None:
+    """Schedules the daily summary job."""
+    if not OWNER_CHAT_ID:
+        logger.warning("OWNER_CHAT_ID not set. Daily summary will not be scheduled.")
+        return
+
+    job_queue = application.job_queue
+
+    # Use the timezone from config
+    tz = pytz.timezone(TIMEZONE)
+
+    # Schedule the job to run every day at 7:00 AM
+    scheduled_time = time(hour=7, minute=0, tzinfo=tz)
+
+    job_queue.run_daily(
+        send_daily_summary,
+        time=scheduled_time,
+        chat_id=int(OWNER_CHAT_ID),
+        name="daily_summary"
+    )
+
+    logger.info(f"Scheduled daily summary for {OWNER_CHAT_ID} at {scheduled_time} {TIMEZONE}")

requirements.txt

@@ -5,3 +5,4 @@ google-api-python-client
 google-auth-httplib2
 google-auth-oauthlib
 openai
+pytz

tasks.md

@@ -31,8 +31,8 @@ This file tracks the development tasks for the Talía project.
 ## Phase 4: Integrations
 
 - [x] Implement `calendar.py` for Google Calendar integration.
-- [ ] Implement `llm.py` for AI-powered responses.
-- [ ] Implement `scheduler.py` for daily summaries.
+- [x] Implement `llm.py` for AI-powered responses.
+- [x] Implement `scheduler.py` for daily summaries.
 
 ## Log