api/router_intel.py

from fastapi import APIRouter, Depends, HTTPException
from typing import List, Dict, Any
from core.security import verify_api_key
from ml_services.nlp_graph_ai import nlp_graph_service
from models.schemas import GraphEdge
from core.db import db_handler

router = APIRouter(prefix="/api/v1/intel", tags=["Intelligence & Analysis"])

@router.post("/fraud-rings")
async def detect_fraud_rings(
    edges: List[GraphEdge],
    api_key: str = Depends(verify_api_key)
):
    try:
        result = nlp_graph_service.detect_fraud_rings(edges)
        
        # Save analysis to DB
        if db_handler.db is not None:
            await db_handler.db["fraud_rings"].insert_one({
                "communities": result["communities"],
                "mule_hubs": result["top_mule_hubs"],
                "edge_count": len(edges)
            })

        return {
            "fraud_rings": result["communities"], 
            "count": len(result["communities"]),
            "mule_hubs": result["top_mule_hubs"]
        }
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@router.get("/geo/hotspots")
async def get_hotspots(
    eps: float = 0.01,
    min_samples: int = 3,
    api_key: str = Depends(verify_api_key)
):
    try:
        # Fetch coordinates from MongoDB
        coordinates = []
        if db_handler.db is not None:
            # We look for incidents with valid Point locations
            cursor = db_handler.db["incidents"].find({"location": {"$ne": None}})
            async for document in cursor:
                loc = document.get("location")
                if loc and loc.get("type") == "Point" and len(loc.get("coordinates", [])) == 2:
                    # coordinates: [longitude, latitude] - map to [lat, lng] for DBSCAN
                    lng, lat = loc["coordinates"]
                    coordinates.append([lat, lng])
        
        clusters = nlp_graph_service.cluster_hotspots(coordinates, eps=eps, min_samples=min_samples)
        
        # Convert clusters to GeoJSON points for frontend rendering
        geojson_features = []
        for i, cluster in enumerate(clusters):
            for lat, lng in cluster:
                geojson_features.append({
                    "type": "Feature",
                    "geometry": {
                        "type": "Point",
                        "coordinates": [lng, lat]
                    },
                    "properties": {
                        "cluster_id": i
                    }
                })

        return {"type": "FeatureCollection", "features": geojson_features}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))