Implement investor processing and querying functionality

- Added InvestorProcessor class for processing CSV data in batches and saving to SQL and vector databases.
- Introduced QueryProcessor class for querying investor information from SQL and vector databases.
- Integrated OpenAI's ChatGPT for structured output generation.
- Implemented data cleaning and control character removal in CSV processing.
- Added asynchronous processing capabilities for batch handling.
- Established connection to ChromaDB for vector storage of investor descriptions.
- Defined structured output schemas using Pydantic for investor data validation.
- Enhanced settings management for API key and database configurations.

app/db/tables.py

@@ -0,0 +1,23 @@
+import datetime
+
+from sqlalchemy import Column, DateTime, Integer, String
+
+from db.db import Base
+
+
+class InvestorTable(Base):
+    __tablename__ = "investors"
+
+    id = Column(Integer, primary_key=True, index=True)
+    name = Column(String, nullable=False)
+    aum = Column(Integer, nullable=False)
+    check_size = Column(String, nullable=False)
+    sector_focus = Column(String, nullable=False)
+    stage_focus = Column(String, nullable=False)
+    region = Column(String, nullable=False)
+    created_at = Column(DateTime, default=datetime.datetime.now(datetime.UTC))
+    updated_at = Column(
+        DateTime,
+        default=datetime.datetime.now(datetime.UTC),
+        onupdate=datetime.datetime.now(datetime.UTC),
+    )