feat: initial knowledge-inbox pipeline implementation

- Oracle ADB queue table (sql/schema.sql)
- Queue CRUD: core/queue_db.py
- YouTube transcript: core/youtube.py
- Web page fetch: core/web.py
- LLM enrichment via OCI GenAI Gemini Flash: core/enricher.py
- Text chunker: core/chunker.py
- Obsidian note writer: core/obsidian.py
- Oracle vector store insertion: core/vector.py
- Polling daemon: daemon/worker.py
- Telegram bot: bot/telegram_bot.py
- Main runner: main.py

main.py

@@ -0,0 +1,23 @@
+"""Main entry point: starts daemon thread + Telegram bot."""
+
+import threading
+
+from dotenv import load_dotenv
+
+load_dotenv()
+
+from bot.telegram_bot import build_app
+from daemon.worker import run_loop
+
+
+def main() -> None:
+    """Start the daemon in a background thread, then run the bot (blocking)."""
+    t = threading.Thread(target=run_loop, args=(30,), daemon=True)
+    t.start()
+
+    app = build_app()
+    app.run_polling()
+
+
+if __name__ == "__main__":
+    main()