feat: Implement database ingestion for investors and companies

- Added main ingestion logic in main.py to process CSV files for investors and companies.
- Implemented data cleaning functions for names, strings, integers, and websites.
- Established relationships between investors, companies, and sectors using SQLAlchemy ORM.
- Created models for investors, companies, sectors, and their relationships in models.py.
- Set up logging for error tracking during data processing.
- Initialized database and created necessary tables.

app/db/db.py

@@ -12,9 +12,9 @@ Base = declarative_base()
 # Database configuration
 # Use the preprocessor's database for consistency
 # Get absolute path to the preprocessor database
-APP_DIR = Path(__file__).parent.parent
-PREPROCESSOR_DB = APP_DIR.parent / "preprocessor" / "version_two.db"
-DATABASE_URL = os.getenv("DATABASE_URL", f"sqlite:///{PREPROCESSOR_DB}")
+# APP_DIR = Path(__file__).parent.parent
+# PREPROCESSOR_DB = APP_DIR.parent / "preprocessor" / "version_two.db"
+DATABASE_URL = os.getenv("DATABASE_URL", "sqlite:///./version_two.db")
 
 # Create engine
 engine = create_engine(DATABASE_URL, echo=False)