CO

app.py

@@ -4,6 +4,9 @@ from transformers import pipeline
 from gtts import gTTS
 import tempfile
 import os
+import qrcode
+from PIL import Image
+import io
 
 # Streamlit page setup
 st.set_page_config(page_title="Health Report Analyzer", page_icon="🩺")
@@ -25,21 +28,6 @@ def extract_text(file):
 def load_explainer():
     return pipeline("text2text-generation", model="google/flan-t5-large")
 
-# Doctor recommendation based on keywords
-def doctor_suggestion(term):
-    doctor_map = {
-        "creatinine": ("nephrologist", "This test usually relates to kidney function."),
-        "hemoglobin": ("hematologist", "This test is related to red blood cells and anemia."),
-        "platelets": ("hematologist", "Platelet levels affect blood clotting."),
-        "cholesterol": ("cardiologist", "High cholesterol can increase risk of heart disease."),
-        "ecg": ("cardiologist", "This test checks heart activity and rhythm."),
-        "ct scan": ("radiologist", "A CT scan helps visualize internal body structures.")
-    }
-    for key in doctor_map:
-        if key in term.lower():
-            return doctor_map[key]
-    return None, None
-
 # Main logic
 if uploaded_file:
     text_data = extract_text(uploaded_file)
@@ -75,12 +63,6 @@ if uploaded_file:
         st.success("Explanation:")
         st.write(response)
 
-        # Doctor suggestion
-        doctor, note = doctor_suggestion(user_question)
-        if doctor:
-            st.markdown(f"🩺 **You should consider seeing a {doctor}.**")
-            st.markdown(f"📌 _Note: {note}_")
-
         # Text-to-speech using gTTS
         tts = gTTS(text=response)
         temp_audio = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
@@ -90,5 +72,17 @@ if uploaded_file:
         audio_bytes = audio_file.read()
         st.audio(audio_bytes, format='audio/mp3')
 
+        # Generate QR Code for the explanation text
+        if st.button("📱 Generate QR Code to Share Explanation"):
+            qr = qrcode.QRCode(version=1, box_size=10, border=5)
+            qr.add_data(response[:300])  # Keep text short for QR
+            qr.make(fit=True)
+
+            img = qr.make_image(fill='black', back_color='white')
+
+            buf = io.BytesIO()
+            img.save(buf)
+            st.image(buf.getvalue(), caption="Scan to Read Explanation", use_column_width=False)
+
 else:
     st.info("Upload a PDF Health Report to begin.")