Update app.py

app.py

@@ -8,7 +8,6 @@ import pdfplumber
 from PIL import Image
 import timm
 import torch
-from hashlib import sha256
 
 # Load pre-trained zero-shot model for text classification
 classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
@@ -20,9 +19,6 @@ image_model.eval()
 # Load saved TensorFlow eye disease detection model
 eye_model = tf.keras.models.load_model('model.h5')
 
-# Password Protection
-DOCTOR_PASSWORD_HASH = sha256("doctor123".encode()).hexdigest()
-
 # Patient database
 patients_db = []
 
@@ -70,22 +66,18 @@ disease_details = {
     }
 }
 
-# Helper Functions
-def hash_password(password):
-    return sha256(password.encode()).hexdigest()
-
 # Functions
-def register_patient(name, age, gender, password):
+def register_patient(name, age, gender):
     patient_id = len(patients_db) + 1
     patients_db.append({
         "ID": patient_id,
         "Name": name,
         "Age": age,
         "Gender": gender,
-        "Password": hash_password(password),
         "Diagnosis": "",
         "Medications": "",
-        "Precautions": ""
+        "Precautions": "",
+        "Doctor": ""
     })
     return f"✅ Patient {name} registered successfully. Patient ID: {patient_id}"
 
@@ -97,10 +89,10 @@ def analyze_report(patient_id, report_text):
     # Update patient's record
     medication = disease_details[diagnosis]['medication']
     precaution = disease_details[diagnosis]['precaution']
+    doctor = disease_details[diagnosis]['doctor']
     for patient in patients_db:
         if patient['ID'] == patient_id:
-            patient.update(Diagnosis=diagnosis, Medications=medication, Precautions=precaution)
-            break
+            patient.update(Diagnosis=diagnosis, Medications=medication, Precautions=precaution, Doctor=doctor)
     return f"🔍 Diagnosis: {diagnosis}"
 
 def extract_pdf_report(pdf):
@@ -120,47 +112,45 @@ def predict_eye_disease(input_image):
         return f"Congrats! No disease detected. Confidence: {confidence_scores['Normal']}%"
     return "\n".join([f"{label}: {confidence}%" for label, confidence in confidence_scores.items()])
 
-def view_patient_details(patient_id, password):
-    hashed_password = hash_password(password)
+def doctor_dashboard(password):
+    doctor_password = "doctor123"
+    if password != doctor_password:
+        return "❌ Access Denied: Incorrect Password"
+    if not patients_db:
+        return "No patient records available."
+    details = []
     for patient in patients_db:
-        if patient['ID'] == patient_id and patient['Password'] == hashed_password:
-            return pd.DataFrame([patient])
-    return "❌ Invalid ID or password. Access denied."
-
-def view_all_patients(password):
-    if hash_password(password) == DOCTOR_PASSWORD_HASH:
-        return pd.DataFrame(patients_db)
-    return "❌ Invalid doctor password."
+        details.append(f"🩺 Patient Name: {patient['Name']}\n"
+                       f"📋 Diagnosis: {patient['Diagnosis']}\n"
+                       f"💊 Medications: {patient['Medications']}\n"
+                       f"⚠️ Precautions: {patient['Precautions']}\n"
+                       f"👩‍⚕️ Recommended Doctor: {patient['Doctor']}")
+    return "\n\n".join(details)
+
+def pharmacist_space(password):
+    pharmacist_password = "pharmacist123"
+    if password != pharmacist_password:
+        return "❌ Access Denied: Incorrect Password"
+    if not patients_db:
+        return "No patient records available."
+    details = []
+    for patient in patients_db:
+        details.append(f"💊 Patient Name: {patient['Name']}\n"
+                       f"📋 Prescribed Medications: {patient['Medications']}")
+    return "\n\n".join(details)
 
 # Gradio Interfaces
-registration_interface = gr.Interface(fn=register_patient, inputs=[
-    gr.Textbox(label="Name"),
-    gr.Number(label="Age"),
-    gr.Radio(label="Gender", choices=["Male", "Female", "Other"]),
-    gr.Textbox(label="Password", type="password")
-], outputs="text")
-
-report_analysis_interface = gr.Interface(fn=analyze_report, inputs=[
-    gr.Number(label="Patient ID"),
-    gr.Textbox(label="Report Text")
-], outputs="text")
-
+registration_interface = gr.Interface(fn=register_patient, inputs=[gr.Textbox(label="Patient Name"), gr.Number(label="Age"), gr.Radio(label="Gender", choices=["Male", "Female", "Other"])], outputs="text")
+report_analysis_interface = gr.Interface(fn=analyze_report, inputs=[gr.Number(label="Patient ID"), gr.Textbox(label="Report Text")], outputs="text")
 pdf_report_extraction_interface = gr.Interface(fn=extract_pdf_report, inputs=gr.File(label="Upload PDF Report"), outputs="text")
-
 eye_disease_interface = gr.Interface(fn=predict_eye_disease, inputs=gr.Image(label="Upload an Eye Image", type="numpy"), outputs="text")
-
-patient_dashboard_interface = gr.Interface(fn=view_patient_details, inputs=[
-    gr.Number(label="Patient ID"),
-    gr.Textbox(label="Password", type="password")
-], outputs="dataframe")
-
-doctor_dashboard_interface = gr.Interface(fn=view_all_patients, inputs=[
-    gr.Textbox(label="Doctor Password", type="password")
-], outputs="dataframe")
+patient_dashboard_interface = gr.Interface(fn=lambda: pd.DataFrame(patients_db), inputs=None, outputs="dataframe")
+doctor_dashboard_interface = gr.Interface(fn=doctor_dashboard, inputs=gr.Textbox(label="Doctor Password", type="password"), outputs="text")
+pharmacist_interface = gr.Interface(fn=pharmacist_space, inputs=gr.Textbox(label="Pharmacist Password", type="password"), outputs="text")
 
 # Gradio App Layout
 with gr.Blocks() as app:
-    gr.Markdown("# Medical Analyzer and Patient Management System")
+    gr.Markdown("# Medical Analyzer and Eye Disease Detection")
     with gr.Tab("Patient Registration"):
         registration_interface.render()
     with gr.Tab("Analyze Medical Report"):
@@ -169,9 +159,11 @@ with gr.Blocks() as app:
         pdf_report_extraction_interface.render()
     with gr.Tab("Detect Eye Disease"):
         eye_disease_interface.render()
-    with gr.Tab("Patient Dashboard"):
-        patient_dashboard_interface.render()
     with gr.Tab("Doctor Dashboard"):
         doctor_dashboard_interface.render()
+    with gr.Tab("Pharmacist Space"):
+        pharmacist_interface.render()
+    with gr.Tab("Patient Dashboard"):
+        patient_dashboard_interface.render()
 
 app.launch(share=True)