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/pydantic_schemas.py

@@ -0,0 +1,38 @@
+from typing import List
+
+from pydantic import BaseModel
+
+
+class Investor(BaseModel):
+    name: str
+    aum: int
+    check_size: str
+    sector_focus: str
+    stage_focus: str
+    region: str
+    investment_thesis: str
+    investor_description: str
+
+
+class InvestorList(BaseModel):
+    investor_list: List[Investor]
+
+
+class QueryResponse(BaseModel):
+    name: str
+    aum: int
+    check_size: str
+    sector_focus: str
+    stage_focus: str
+    region: str
+    investment_thesis: str
+    investor_description: str
+    reason: str
+
+
+class QueryRequest(BaseModel):
+    question: str
+
+
+class QueryResponseList(BaseModel):
+    responses: List[QueryResponse]