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

pyproject.toml

@@ -0,0 +1,19 @@
+[project]
+name = "knowledge-inbox"
+version = "0.1.0"
+requires-python = ">=3.11"
+dependencies = [
+    "python-telegram-bot>=21.0",
+    "youtube-transcript-api>=0.6",
+    "httpx>=0.27",
+    "oracledb>=2.0",
+    "oci>=2.100",
+    "python-dotenv>=1.0",
+]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["bot", "core", "daemon"]