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frontend/Home.py

@@ -7,6 +7,10 @@ import plotly.graph_objects as go
 import numpy as np
 
 API_URL = os.getenv("API_URL", "http://localhost:8000")
+if "hf.space" in os.getenv("SPACE_ID", ""):
+    # On HF Spaces, the backend might be on a subpath or the same port
+    # But for this setup, we assume it's running on localhost:8000 internally as per app.py
+    API_URL = "http://localhost:8000"
 
 st.set_page_config(page_title="TinyML Heart Health Monitoring", page_icon="🫀", layout="wide")
 

frontend/pages/2_Data_Analytics.py

@@ -10,6 +10,8 @@ st.set_page_config(page_title="Advanced Analytics", page_icon="📊", layout="wi
 st.title("📊 Population Analytics Deep Dive")
 
 API_URL = os.getenv("API_URL", "http://localhost:8000")
+if "hf.space" in os.getenv("SPACE_ID", ""):
+    API_URL = "http://localhost:8000"
 
 @st.cache_data(ttl=3600)
 def load_data():

seed_db.py

@@ -0,0 +1,66 @@
+import sqlite3
+import os
+import random
+from datetime import datetime, timedelta
+
+DB_NAME = 'patient_history.db'
+DB_PATH = os.path.join('backend', DB_NAME)
+
+def seed_data():
+    if not os.path.exists('backend'):
+        os.makedirs('backend')
+
+    conn = sqlite3.connect(DB_PATH)
+    cursor = conn.cursor()
+    
+    # Ensure table exists
+    cursor.execute('''
+        CREATE TABLE IF NOT EXISTS predictions (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            timestamp DATETIME,
+            heart_rate REAL,
+            spo2 REAL,
+            sys_bp REAL,
+            dia_bp REAL,
+            temp REAL,
+            fall_detection TEXT,
+            prediction_label TEXT,
+            confidence REAL
+        )
+    ''')
+
+    # Sample data generation
+    labels = ["Healthy", "At Risk"]
+    fall_options = ["No Fall", "Fall Detected"]
+    
+    now = datetime.now()
+    
+    print("Seeding 30 sample predictions...")
+    for i in range(30):
+        timestamp = (now - timedelta(minutes=i*15)).strftime("%Y-%m-%d %H:%M:%S")
+        hr = round(random.uniform(60, 110), 1)
+        spo2 = round(random.uniform(92, 99), 1)
+        sys = round(random.uniform(110, 150), 1)
+        dia = round(random.uniform(70, 95), 1)
+        temp = round(random.uniform(36.1, 37.8), 1)
+        fall = random.choice(fall_options) if hr > 100 else "No Fall"
+        
+        # Simple logic for label
+        if hr > 100 or spo2 < 94 or sys > 140:
+            label = "At Risk"
+            conf = random.uniform(0.7, 0.95)
+        else:
+            label = "Healthy"
+            conf = random.uniform(0.85, 0.99)
+
+        cursor.execute('''
+            INSERT INTO predictions (timestamp, heart_rate, spo2, sys_bp, dia_bp, temp, fall_detection, prediction_label, confidence)
+            VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
+        ''', (timestamp, hr, spo2, sys, dia, temp, fall, label, conf))
+
+    conn.commit()
+    conn.close()
+    print("Done seeding.")
+
+if __name__ == "__main__":
+    seed_data()