Added logging to main

app/main.py

@@ -1,9 +1,11 @@
 import io
+import logging
 
 import pandas as pd
 from db.db import Base, db_dependency, engine
 from dotenv import load_dotenv
-from fastapi import FastAPI, File, Form, UploadFile
+from fastapi import FastAPI, File, Form, HTTPException, UploadFile
+from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
 from routers import (
     companies,
@@ -26,10 +28,21 @@ def init_database():
     Base.metadata.create_all(bind=engine)
 
 
+logger = logging.getLogger(__name__)
+
 init_database()
 
 app = FastAPI()
 
+# Add CORS middleware to allow frontend requests
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # In production, replace with specific origins
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
 
 # Request models
 class QueryRequest(BaseModel):
@@ -109,42 +122,30 @@ async def parse_csv(
     "/query", response_model=PaginatedResponse[InvestmentResponse], tags=["Querying"]
 )
 async def query_investors(request: QueryRequest):
-    """
+    """Query investors/funds using natural language"""
-    Query investors using natural language.
+    try:
-
-    Returns fund-level matches (one row per fund) with investor details.
-    This ensures only relevant funds are included in the response.
-
-    Supports queries like:
-    - "Show me seed stage investors"
-    - "Find fintech investors in Silicon Valley"
-    - "Growth stage investors with $5M+ check sizes"
-    - "Healthcare investors in Europe"
-    """
         processor = QueryProcessor()
-    results = await processor.process_query(request.question)
+        result = await processor.process_query(request.question)
-    return results
+        logger.info(f"Query completed successfully with {result.total} results")
+        return result
+    except Exception as e:
+        logger.error(f"Error in query_investors: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
 
 
 @app.post(
     "/query-companies", response_model=PaginatedResponse[CompanyData], tags=["Querying"]
 )
 async def query_companies(request: CompanyQueryRequest):
-    """
+    """Query companies using natural language"""
-    Query companies using natural language.
+    try:
-
-    Returns company matches with their investor relationships, team members, and sectors.
-
-    Supports queries like:
-    - "Show me fintech companies founded in 2020"
-    - "Find healthcare companies in San Francisco"
-    - "Companies in the AI sector"
-    - "Companies that received funding from Sequoia"
-    - "European startups founded after 2019"
-    """
         processor = CompanyQueryProcessor()
-    results = await processor.process_query(request.question)
+        result = await processor.process_query(request.question)
-    return results
+        logger.info(f"Company query completed successfully with {result.total} results")
+        return result
+    except Exception as e:
+        logger.error(f"Error in query_companies: {e}", exc_info=True)
+        raise HTTPException(status_code=500, detail=str(e))
 
 
 app.include_router(investors.router)