feat: Add insight generation functionality with compatibility scoring and web search integration

app/routers/insight_route.py

@@ -0,0 +1,80 @@
+from typing import Optional
+
+from db.db import get_db
+from db.models import InvestorTable, ProjectTable
+from fastapi import APIRouter, Depends, HTTPException
+from schemas.insight_schema import InsightResponse
+from services.compatibility_score import (
+    calculate_project_investor_compatibility,
+    generate_compatibility_explanation,
+)
+from services.insight import QueryProcessor
+from sqlalchemy.orm import Session
+
+router = APIRouter()
+
+
+@router.get(
+    "/insights/{investor_id}", response_model=InsightResponse, tags=["Insights"]
+)
+async def get_insights(
+    investor_id: int, project_id: Optional[int] = None, db: Session = Depends(get_db)
+):
+    """
+    Get investor insights including investment pattern analysis, market position,
+    and optionally compatibility score with a project.
+
+    Args:
+        investor_id: The ID of the investor to analyze
+        project_id: Optional project ID to calculate compatibility score
+
+    Returns:
+        InsightResponse with investment_pattern_analysis, market_position,
+        and compatibility_score (if project_id provided)
+    """
+    # Get investor from database
+    investor = db.query(InvestorTable).filter(InvestorTable.id == investor_id).first()
+    if not investor:
+        raise HTTPException(
+            status_code=404, detail=f"Investor with id {investor_id} not found"
+        )
+
+    # Initialize the query processor for insights
+    query_processor = QueryProcessor()
+
+    # Get investment pattern analysis and market position using web search
+    insights = await query_processor.get_investor_insights(
+        investor_name=investor.name,
+        investor_website=investor.website,
+        investor_description=investor.description,
+        investor_headquarters=investor.headquarters,
+        investment_thesis=investor.investment_thesis,
+        portfolio_highlights=investor.portfolio_highlights,
+    )
+
+    # Calculate compatibility score if project_id is provided
+    compatibility_score = None
+    if project_id:
+        project = db.query(ProjectTable).filter(ProjectTable.id == project_id).first()
+        if not project:
+            raise HTTPException(
+                status_code=404, detail=f"Project with id {project_id} not found"
+            )
+
+        # Calculate the compatibility score
+        score = calculate_project_investor_compatibility(
+            project, investor, use_funds=True
+        )
+
+        # Generate detailed explanation
+        compatibility_score = generate_compatibility_explanation(
+            project, investor, score, use_funds=True
+        )
+    else:
+        compatibility_score = "Select a project to see compatibility analysis"
+
+    return InsightResponse(
+        investment_pattern_analysis=insights["investment_pattern_analysis"],
+        market_position=insights["market_position"],
+        compatibility_score=compatibility_score,
+    )