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main.py β FastAPI Backend (Strict Grid Snapping - MySQL Removed)
=====================================================================
"""
import asyncio
import json
import math
import os
import random
import sys
import time
import uuid
from contextlib import asynccontextmanager
from typing import Dict, List, Optional
from fastapi import FastAPI, HTTPException, WebSocket, WebSocketDisconnect
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel, Field
from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse
BACKEND_DIR = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, os.path.join(BACKEND_DIR, "..", "openenv_env"))
sys.path.insert(0, os.path.join(BACKEND_DIR, "..", "rl"))
from healthcare_env import HealthcareRoutingEnv, haversine_distance, compute_eta
# ββ RL GLOBAL BOUNDS ββ
LAT_MIN, LAT_MAX = 17.60, 17.75
LON_MIN, LON_MAX = 75.85, 76.00
# ββ GRID SNAPPING LOGIC (Forces ambulances onto roads) ββ
def snap_val(val, min_v, max_v, steps=20):
step = (max_v - min_v) / steps
idx = round((val - min_v) / step)
return min_v + idx * step
def snap_lat(lat): return snap_val(lat, LAT_MIN, LAT_MAX, 20)
def snap_lon(lon): return snap_val(lon, LON_MIN, LON_MAX, 20)
# ββ IN-MEMORY DATABASE (Snapped to Intersections) ββ
HOSPITALS: List[Dict] = [
{"id": "h0", "name": "Ashwini Hospital", "lat": snap_lat(17.7300), "lon": snap_lon(75.9700), "total_beds": 100, "beds_available": 72, "icu_beds": 20, "icu_available": 14, "wait_time": 10, "address": "North-East Sector"},
{"id": "h1", "name": "Markandey Hospital", "lat": snap_lat(17.7200), "lon": snap_lon(75.8800), "total_beds": 80, "beds_available": 55, "icu_beds": 15, "icu_available": 9, "wait_time": 15, "address": "North-West Sector"},
{"id": "h2", "name": "Yashodhara Hospital", "lat": snap_lat(17.6800), "lon": snap_lon(75.9300), "total_beds": 60, "beds_available": 48, "icu_beds": 10, "icu_available": 7, "wait_time": 5, "address": "Central Sector"},
{"id": "h3", "name": "Monark Hospital", "lat": snap_lat(17.6200), "lon": snap_lon(75.8700), "total_beds": 120, "beds_available": 91, "icu_beds": 30, "icu_available": 22, "wait_time": 20, "address": "South-West Sector"},
{"id": "h4", "name": "Civil Hospital", "lat": snap_lat(17.6300), "lon": snap_lon(75.9800), "total_beds": 90, "beds_available": 63, "icu_beds": 25, "icu_available": 18, "wait_time": 8, "address": "South-East Sector"},
]
AMBULANCES: List[Dict] = [
{"id": "a0", "name": "AMB-001", "lat": snap_lat(17.7000), "lon": snap_lon(75.9000), "status": "available", "assigned_patient": None, "target_hosp_id": None, "speed_kmh": 60},
{"id": "a1", "name": "AMB-002", "lat": snap_lat(17.6500), "lon": snap_lon(75.9500), "status": "available", "assigned_patient": None, "target_hosp_id": None, "speed_kmh": 65},
{"id": "a2", "name": "AMB-003", "lat": snap_lat(17.7200), "lon": snap_lon(75.9600), "status": "available", "assigned_patient": None, "target_hosp_id": None, "speed_kmh": 55},
{"id": "a3", "name": "AMB-004", "lat": snap_lat(17.6400), "lon": snap_lon(75.8900), "status": "available", "assigned_patient": None, "target_hosp_id": None, "speed_kmh": 70},
]
PATIENTS: Dict[str, Dict] = {}
ASSIGNMENTS: List[Dict] = []
# ββ RL MODEL LOADER ββ
rl_env: Optional[HealthcareRoutingEnv] = None
try:
import torch
from dqn_agent import DQNAgent
_model_path = os.path.abspath(os.path.join(BACKEND_DIR, "..", "..", "rl", "models", "dqn_healthcare.pth"))
dqn_agent: Optional[DQNAgent] = None
if os.path.exists(_model_path):
_tmp_env = HealthcareRoutingEnv()
_tmp_obs, _ = _tmp_env.reset()
dqn_agent = DQNAgent(obs_size=_tmp_env.observation_space.shape[0], action_size=_tmp_env.action_space.n)
dqn_agent.load(_model_path)
print("[Backend] DQN model loaded β")
else:
print(f"[Backend] Model not found at {_model_path} β using greedy fallback")
except Exception as e:
dqn_agent = None
print(f"[Backend] DQN unavailable ({e}) β using greedy fallback")
# ββ FASTAPI SETUP ββ
simulation_running = False
simulation_task = None
ws_connections: List[WebSocket] = []
class PatientIn(BaseModel):
name: str = Field(default="Unknown Patient")
severity: float = Field(..., ge=1, le=10)
lat: float = Field(...)
lon: float = Field(...)
emergency_type: str = Field(default="General")
notes: Optional[str] = None
@asynccontextmanager
async def lifespan(app: FastAPI):
print("[Backend] Healthcare Routing API started")
yield
print("[Backend] Shutting down")
app = FastAPI(title="SmartER API", lifespan=lifespan)
app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"])
def rl_assign(patient: Dict) -> Dict:
env = HealthcareRoutingEnv(hospitals=HOSPITALS, ambulances=AMBULANCES)
env.LAT_MIN, env.LAT_MAX = LAT_MIN, LAT_MAX
env.LON_MIN, env.LON_MAX = LON_MIN, LON_MAX
env.hospitals = [{**h, "current_wait": h["wait_time"]} for h in HOSPITALS]
env.ambulances = [{**a} for a in AMBULANCES]
env.patient = {"severity": patient["severity"], "lat": patient["lat"], "lon": patient["lon"], "traffic": random.uniform(0.9, 1.8)}
if dqn_agent:
obs = env._get_observation()
action = dqn_agent.greedy_action(obs)
hosp_idx, amb_idx = env.decode_action(action)
else:
amb_idx = 0
min_d = float('inf')
for i, a in enumerate(AMBULANCES):
if a["status"] == "available":
d = haversine_distance(patient["lat"], patient["lon"], a["lat"], a["lon"])
if d < min_d: min_d = d; amb_idx = i
hosp_idx = 0
max_score = -float('inf')
for i, h in enumerate(HOSPITALS):
score = h["beds_available"] * 10 - haversine_distance(patient["lat"], patient["lon"], h["lat"], h["lon"])
if score > max_score: max_score = score; hosp_idx = i
hospital = HOSPITALS[min(hosp_idx, len(HOSPITALS) - 1)]
ambulance = AMBULANCES[min(amb_idx, len(AMBULANCES) - 1)]
dist_amb_pt = haversine_distance(ambulance["lat"], ambulance["lon"], patient["lat"], patient["lon"])
dist_pt_hosp = haversine_distance(patient["lat"], patient["lon"], hospital["lat"], hospital["lon"])
total_eta = round(compute_eta(dist_amb_pt + dist_pt_hosp, 1.2, 60), 1)
return {
"hospital": hospital, "ambulance": ambulance, "eta_minutes": total_eta,
"dist_to_hospital": round(dist_pt_hosp, 2),
"reasoning": [f"β
{hospital['beds_available']} beds free", f"π Ambulance {ambulance['name']} dispatched"],
"model_used": "DQN" if dqn_agent else "Greedy",
}
@app.post("/add_patient")
def add_patient(patient_in: PatientIn):
patient_id = f"PT-{str(uuid.uuid4())[:6].upper()}"
# Snap incoming coordinates to the grid so ambulances never leave the road!
patient_in.lat = snap_lat(patient_in.lat)
patient_in.lon = snap_lon(patient_in.lon)
patient = {
**patient_in.dict(), "id": patient_id, "status": "pending", "timestamp": time.time(),
"severity_label": "critical" if patient_in.severity >= 8 else "moderate" if patient_in.severity >= 5 else "mild"
}
PATIENTS[patient_id] = patient
assignment = rl_assign(patient)
for h in HOSPITALS:
if h["id"] == assignment["hospital"]["id"]:
h["beds_available"] = max(0, h["beds_available"] - 1)
break
for a in AMBULANCES:
if a["id"] == assignment["ambulance"]["id"]:
a["status"] = "en_route_to_patient"
a["assigned_patient"] = patient_id
a["target_hosp_id"] = assignment["hospital"]["id"]
break
patient["status"] = "assigned"
ASSIGNMENTS.append({"patient_id": patient_id, "hospital_id": h["id"], "ambulance_id": a["id"]})
return {"patient": patient, "assignment": assignment}
@app.get("/get_live_tracking")
def get_live_tracking(): return {"hospitals": HOSPITALS, "ambulances": AMBULANCES, "patients": list(PATIENTS.values())}
@app.get("/stats")
def get_stats():
used_beds = sum(h["total_beds"] - h["beds_available"] for h in HOSPITALS)
total_beds = sum(h["total_beds"] for h in HOSPITALS)
return {
"total_patients": len(PATIENTS),
"bed_occupancy_pct": round(used_beds / total_beds * 100, 1) if total_beds else 0,
"available_ambs": sum(1 for a in AMBULANCES if a["status"] == "available"),
"total_assignments": len(ASSIGNMENTS),
"hospitals": [{"name": h["name"], "occupancy_pct": round((h["total_beds"] - h["beds_available"]) / h["total_beds"] * 100, 1), "icu_occupancy": max(0, int(((h["total_beds"] - h["beds_available"]) / h["total_beds"]) * h["icu_beds"]))} for h in HOSPITALS]
}
async def simulation_loop():
global simulation_running
while simulation_running:
for a in AMBULANCES:
if a["status"] in ["en_route_to_patient", "en_route_to_hospital"]:
pid = a["assigned_patient"]
target = PATIENTS.get(pid) if a["status"] == "en_route_to_patient" else next((h for h in HOSPITALS if h["id"] == a["target_hosp_id"]), None)
if not target: continue
dlat = target["lat"] - a["lat"]
dlon = target["lon"] - a["lon"]
# STRICT GRID ALIGNMENT: Prevents diagonal cutting through buildings
step = 0.002
if abs(dlon) > step:
a["lon"] += math.copysign(step, dlon)
elif abs(dlat) > step:
a["lon"] = target["lon"] # Snap perfectly to the vertical road
a["lat"] += math.copysign(step, dlat)
else:
a["lat"] = target["lat"]
a["lon"] = target["lon"]
if a["status"] == "en_route_to_patient":
a["status"] = "en_route_to_hospital"
PATIENTS[pid]["status"] = "picked_up"
else:
a["status"] = "available"
a["assigned_patient"] = None
PATIENTS[pid]["status"] = "admitted"
free_ambs = [a for a in AMBULANCES if a["status"] == "available"]
if free_ambs and random.random() < 0.075:
# Snap generated patients perfectly to the grid roads!
fake = PatientIn(name=f"Sim-{random.randint(100,999)}", severity=random.uniform(1,10), lat=snap_lat(random.uniform(LAT_MIN, LAT_MAX)), lon=snap_lon(random.uniform(LON_MIN, LON_MAX)))
try: add_patient(fake)
except: pass
for h in HOSPITALS:
if random.random() < 0.005 and h["beds_available"] < h["total_beds"]: h["beds_available"] += 1
payload = json.dumps({"ambulances": AMBULANCES, "hospitals": HOSPITALS, "patients": list(PATIENTS.values())})
dead_sockets = []
for ws in ws_connections:
try: await ws.send_text(payload)
except: dead_sockets.append(ws)
for dead in dead_sockets: ws_connections.remove(dead)
await asyncio.sleep(0.1)
@app.get("/simulation/start")
async def start_sim():
global simulation_running, simulation_task
if not simulation_running:
simulation_running = True
simulation_task = asyncio.create_task(simulation_loop())
return {"message": "Simulation started"}
@app.get("/simulation/stop")
async def stop_sim():
global simulation_running
simulation_running = False
return {"message": "Simulation stopped"}
@app.websocket("/ws/live")
async def websocket_endpoint(websocket: WebSocket):
await websocket.accept()
ws_connections.append(websocket)
try:
while True: await websocket.receive_text()
except WebSocketDisconnect:
if websocket in ws_connections: ws_connections.remove(websocket)
except Exception:
if websocket in ws_connections: ws_connections.remove(websocket)
@app.post("/reset")
def env_reset():
global PATIENTS, ASSIGNMENTS
PATIENTS.clear(); ASSIGNMENTS.clear()
for h in HOSPITALS: h["beds_available"] = h["total_beds"] // 2
for a in AMBULANCES: a["status"] = "available"
return {"message": "Environment reset", "status": "success"}
@app.post("/step")
def env_step(action: dict): return {"observation": get_live_tracking(), "reward": 0.0, "done": False}
@app.get("/state")
def env_state(): return get_live_tracking()
static_path = os.path.join(os.getcwd(), "static")
if os.path.exists(static_path):
app.mount("/assets", StaticFiles(directory=os.path.join(static_path, "assets")), name="assets")
@app.get("/{full_path:path}")
async def serve_frontend(full_path: str):
local_file = os.path.join(static_path, full_path)
if full_path != "" and os.path.exists(local_file): return FileResponse(local_file)
return FileResponse(os.path.join(static_path, "index.html")) |