feat: Integrate Folk CRM API for investor synchronization and compatibility scoring

app/services/querying.py

@@ -1,8 +1,8 @@
 import os
-from typing import List
+from typing import List, Optional
 
 from db.db import DATABASE_URL, get_db
-from db.models import FundTable, InvestorTable
+from db.models import FundTable, InvestorTable, ProjectTable
 from langchain import hub
 from langchain_community.agent_toolkits import SQLDatabaseToolkit
 from langchain_community.utilities import SQLDatabase
@@ -16,6 +16,8 @@ from schemas.router_schemas import (
 )
 from sqlalchemy.orm import selectinload
 
+from services.compatibility_score import calculate_project_investor_compatibility
+
 # Connect to SQLite
 prompt_template = hub.pull("langchain-ai/sql-agent-system-prompt")
 db = SQLDatabase.from_uri(DATABASE_URL)
@@ -44,8 +46,15 @@ class QueryProcessor:
             prompt=system_message_updated,
         )
 
-    def process_query(self, question: str) -> PaginatedResponse[InvestmentResponse]:
-        """Process a query using the LLM and return investment response data."""
+    def process_query(
+        self, question: str, project_id: Optional[int] = None
+    ) -> PaginatedResponse[InvestmentResponse]:
+        """Process a query using the LLM and return investment response data.
+
+        Args:
+            question: The natural language query to process
+            project_id: Optional project ID for compatibility scoring
+        """
         # Let the LLM handle all database interactions and filtering to get fund IDs
         response = self.agent.invoke(
             {"messages": [("user", question)]},
@@ -60,7 +69,7 @@ class QueryProcessor:
         fund_ids = self._extract_fund_ids_from_response(ai_response)
 
         # Fetch full fund data with investor relationships using the IDs
-        return self._fetch_funds_by_ids(fund_ids)
+        return self._fetch_funds_by_ids(fund_ids, project_id)
 
     def _extract_fund_ids_from_response(self, ai_response: str) -> List[int]:
         """Extract fund IDs from AI response."""
@@ -85,10 +94,15 @@ class QueryProcessor:
         return fund_ids
 
     def _fetch_funds_by_ids(
-        self, fund_ids: List[int]
+        self, fund_ids: List[int], project_id: Optional[int] = None
     ) -> PaginatedResponse[InvestmentResponse]:
         """Fetch funds with all their relationships from the database using fund IDs.
-        Constructs response similar to read_investors but starting from funds."""
+        Constructs response similar to read_investors but starting from funds.
+
+        Args:
+            fund_ids: List of fund IDs to fetch
+            project_id: Optional project ID for compatibility scoring
+        """
         if not fund_ids:
             return PaginatedResponse(
                 items=[],
@@ -102,6 +116,16 @@ class QueryProcessor:
         db_session = next(get_db())
 
         try:
+            # Load project if project_id provided
+            project = None
+            if project_id is not None:
+                project = (
+                    db_session.query(ProjectTable)
+                    .options(selectinload(ProjectTable.sector))
+                    .filter(ProjectTable.id == project_id)
+                    .first()
+                )
+
             # Query funds with all necessary relationships loaded
             funds = (
                 db_session.query(FundTable)
@@ -127,6 +151,13 @@ class QueryProcessor:
             for fund in funds:
                 investor = fund.investor
 
+                # Calculate compatibility score if project provided
+                compatibility_score = 1.0
+                if project is not None:
+                    compatibility_score = calculate_project_investor_compatibility(
+                        project=project, investor=investor, use_funds=True
+                    )
+
                 # Get top 3 portfolio companies (id and name only)
                 portfolio_companies = [
                     CompanyMinimal(id=company.id, name=company.name)
@@ -158,7 +189,7 @@ class QueryProcessor:
                     stage_focus=stage_focus,
                     portfolio_companies=portfolio_companies,
                     sectors=fund_sectors,
-                    compatibility_score=1.0,
+                    compatibility_score=compatibility_score,
                 )
                 investment_responses.append(investment_response)