import pandas as pd
import joblib
import gradio as gr
import json
import requests
MODEL_PATH = "risk_model.joblib"
ZAPIER_WEBHOOK_URL = "https://hooks.zapier.com/hooks/catch/27083565/uvtxiub/"
DISCLAIMER = (
"Educational demo only. This tool does not provide diagnosis, "
"prescriptions, or treatment plans. If symptoms are severe or urgent, seek emergency care."
)
RED_FLAGS = [
"chest pain",
"chest tightness",
"severe shortness of breath",
"fainting",
"loss of consciousness",
"stroke"
]
risk_model = joblib.load(MODEL_PATH)
def send_urgent_alert(symptom_text, risk_score):
try:
requests.post(ZAPIER_WEBHOOK_URL, json={
"triage_level": "urgent",
"symptom": symptom_text,
"risk_score": risk_score,
"message": "URGENT triage case detected by HealthBridge AI"
}, timeout=5)
except Exception:
pass
def assess(sexvar, educa, genhlth, menthlth, stress, sleep_hours, sleep_quality, duration_days, adherence_prob, symptom_text):
text_lower = str(symptom_text).lower()
red_flag_hit = any(flag in text_lower for flag in RED_FLAGS)
input_df = pd.DataFrame([{
"user_id": 0,
"SEXVAR": sexvar,
"EDUCA": educa,
"GENHLTH": genhlth,
"MENTHLTH": menthlth,
"stress_score_0_10": stress,
"sleep_hours": sleep_hours,
"sleep_quality_0_10": sleep_quality,
"symptom_duration_days": duration_days,
"adherence_prob": adherence_prob,
"symptom_text": symptom_text,
"triage_label": "medium"
}])
risk_score = float(risk_model.predict_proba(input_df)[0][1])
if red_flag_hit:
triage_level = "urgent"
elif risk_score >= 0.7:
triage_level = "high"
elif risk_score >= 0.4:
triage_level = "medium"
else:
triage_level = "low"
if triage_level == "urgent":
send_urgent_alert(symptom_text, round(risk_score, 3))
if triage_level == "urgent":
next_steps = [
"🚨 Seek emergency care immediately or call emergency services.",
"Do not drive yourself — ask someone nearby to help.",
"Do not wait to see if symptoms improve."
]
elif triage_level == "high":
next_steps = [
"Contact a healthcare provider as soon as possible.",
"Monitor symptoms closely and note any changes.",
"Seek emergency care if symptoms worsen rapidly."
]
elif triage_level == "medium":
next_steps = [
"Schedule an appointment with your doctor within the next few days.",
"Rest and monitor your symptoms.",
"Seek urgent care if symptoms escalate."
]
else:
next_steps = [
"Monitor symptoms and maintain healthy routines.",
"Seek professional care if symptoms persist beyond a week.",
"Stay hydrated and rest as needed."
]
LEVEL_COLORS = {
"urgent": "#FF2D2D",
"high": "#FF8C00",
"medium": "#F5C518",
"low": "#2ECC71"
}
LEVEL_BG = {
"urgent": "#FFF0F0",
"high": "#FFF5E6",
"medium": "#FFFBEA",
"low": "#F0FFF6"
}
LEVEL_ICONS = {
"urgent": "🚨",
"high": "⚠️",
"medium": "🔶",
"low": "✅"
}
color = LEVEL_COLORS[triage_level]
bg = LEVEL_BG[triage_level]
icon = LEVEL_ICONS[triage_level]
risk_pct = int(risk_score * 100)
bar_color = color
steps_html = "".join(f"{s}" for s in next_steps)
alert_banner = ""
if triage_level == "urgent":
alert_banner = f"""
🚨 URGENT — An automated alert email has been sent.
"""
html = f"""
{alert_banner}
{icon}
Triage Level
{triage_level.upper()}
{"🚩" if red_flag_hit else "✔️"}
Red Flag: {"DETECTED" if red_flag_hit else "None detected"}
⚠️ {DISCLAIMER}