python --version

   node -v
   npm -v

   git --version

git clone https://github.com/hrlpavan/aarogyasetu.git
cd aarogyasetu

.\scripts\setup.bat

.\scripts\start.bat

[0:00 - 0:30] HOOK & PROBLEM STATEMENT
"Judges, 700 million rural citizens in India live 40+ kilometers away from the nearest hospital. 
When they try to use modern video-telemedicine apps on rural cell towers, the call crashes because 
they are on 2G EDGE connections with speeds below 60 kbps.

We built AAROGYASETU (आरोग्यसेतु) — 'Healthcare Beyond Boundaries' — an ultra-lightweight telemedicine 
platform engineered from the ground up to operate reliably on 2G networks, feature phones, and rural clinics."

[0:30 - 1:00] PATIENT ONBOARDING & LOW-BANDWIDTH BOOKING
"Let's click '1-Tap Login as Ramesh Patel' from Holehonnur Village.
Notice the top network indicator: we've built a real-time network simulator. We can switch from 4G to 
2G Low-Bandwidth Mode or even Simulated Offline Mode.

Ramesh needs to see a doctor. He goes to 'Find Doctors', selects Dr. Ananya Sharma, selects tomorrow at 10:30 AM, 
and clicks 'Confirm Request'.

Notice what just happened: an automated cellular SMS alert was triggered to Ramesh's phone, confirming his booking. 
Even if his internet disconnects right now, he stays informed via standard SMS."

[1:00 - 1:40] DOCTOR TRIAGE & CLINICAL GOVERNANCE
"Now, let's open a second tab and log in as Dr. Ananya Sharma on the Doctor Console.
Dr. Sharma sees Ramesh in her triage queue. With one click, she confirms the slot, which immediately 
dispatches an automated confirmation SMS to Ramesh.

Next, Dr. Sharma opens the Consultation Workspace. Ramesh uploads a photo of his blood test. 
Normally, a phone camera produces a 6MB image that would timeout on 2G. 
Our client-side HTML5 canvas pipeline compresses it down to 84KB (>96% reduction) before upload!

Our Smart Report Reader OCR extracts his Hemoglobin (11.2 g/dL) and Glucose (118 mg/dL). 
Notice the clinical safety label: '⚠️ Machine-read. Doctor review required.' 
Dr. Sharma verifies the report, enters a clinical consultation note into his EMR, and prescribes 
Paracetamol 650mg TDS."

[1:40 - 2:20] PATIENT ADHERENCE & PRIVACY-PRESERVING QR
"Back on Ramesh's dashboard:
1. His 'Rx Reminders' is immediately populated with Dr. Sharma's approved prescription. He taps 'Taken'. 
   AI cannot prescribe; only doctors can.
2. Ramesh is visiting a local village health camp tomorrow. He goes to 'QR Health Token', selects which 
   fields to share (Name, Blood Group, Allergies), and generates a 15-minute revocable QR token. 
   Notice: ZERO medical data is stored in the QR code—only an encrypted temporary token. If he loses his phone, 
   he can revoke it in one tap."

[2:20 - 3:00] AI SAFETY GUARDRAIL, EMERGENCY SOS & CLOSING
"What about AI? If Ramesh asks our AI Assistant about nutrition or blood sugar ranges, it educates him in simple terms.
BUT watch what happens if he types: 'I have severe chest pain and cannot breathe'.
The AI does NOT hallucinate a diagnosis. Our clinical guardrail intercepts acute symptoms immediately and displays 
a red emergency alert directing him to our 1-Tap Emergency SOS speed-dial for 108 Ambulance and 112 services.

Judges, AAROGYASETU delivers dignity, accessibility, and clinical safety to rural communities without requiring 
expensive broadband or paid API keys. Everything you see is running live locally on SQLite and FastAPI. Thank you!"

// Scales high-res camera photos (4000x3000px, 6MB) down to max 1280px at 0.72 quality
export async function compressImage(file: File, maxWidth = 1280, quality = 0.72): Promise<CompressionResult> {
  const img = new Image();
  img.src = URL.createObjectURL(file);
  await img.decode();

  const canvas = document.createElement('canvas');
  // Dynamic aspect-ratio bounding box
  canvas.width = targetWidth;
  canvas.height = targetHeight;
  const ctx = canvas.getContext('2d');
  ctx.drawImage(img, 0, 0, targetWidth, targetHeight);

  // Converts to WebP/JPEG blob under 100KB (96-98% bandwidth reduction)
  const blob = await new Promise<Blob>((resolve) => canvas.toBlob(resolve, 'image/jpeg', quality));
  return { file: new File([blob], 'lab_report.jpg'), compressedSizeKb: Math.round(blob.size / 1024) };
}

# Dispatches via Twilio if env credentials exist, else records in SQLite demo log
if TWILIO_ACCOUNT_SID and TWILIO_AUTH_TOKEN:
    # Send via Twilio REST API
    provider = "twilio"
    dispatch_status = "SENT"
else:
    # Local fallback: viewable in-app under Doctor Notification Audit
    provider = "demo_logger"
    dispatch_status = "DEMO_LOGGED"

# Strict medical privacy: Never include symptoms or diagnoses in plain SMS!
message_body = f"AAROGYASETU: Your appointment with Dr. {doctor_name} is CONFIRMED for {appointment_date} at {appointment_time}."

CRITICAL_EMERGENCY_KEYWORDS = [
    "chest pain", "shortness of breath", "cannot breathe", "unconscious",
    "stroke", "heavy bleeding", "poison", "snake bite"
]

def query_health_assistant(user_prompt: str):
    for kw in CRITICAL_EMERGENCY_KEYWORDS:
        if kw in user_prompt.lower():
            return {
                "response": "🚨 URGENT MEDICAL ADVISORY: These symptoms indicate a potential life-threatening emergency. Call 108 or 112 immediately.",
                "is_emergency": True,
                "provider": "SafetyGuardrail_EmergencyTriage"
            }