Update app.py

app.py

@@ -5,6 +5,7 @@ import os
 import torch
 import re
 
+
 MODEL_ID = "Muhammadidrees/MedicalInsights"
 
 # -----------------------
@@ -63,6 +64,7 @@ def split_report(text):
     right = text[idx:].strip()
     return left, right
 
+
 # -----------------------
 # The analyze function
 # -----------------------
@@ -82,6 +84,43 @@ def analyze(
     except Exception:
         bmi = "N/A"
 
+    # Reference Ranges (used for comparison)
+    reference_ranges = {
+        "Albumin": (3.5, 5.0),
+        "Creatinine": (0.6, 1.2),
+        "Glucose": (70, 99),
+        "CRP": (0, 3),
+        "MCV": (80, 100),
+        "RDW": (11.5, 14.5),
+        "ALP": (44, 147),
+        "WBC": (4.0, 11.0),
+        "Lymphocytes": (20, 40),
+    }
+
+    # Function to classify biomarker status
+    def classify_status(value, biomarker):
+        low, high = reference_ranges[biomarker]
+        if value < low:
+            return "Low"
+        elif value > high:
+            return "High"
+        else:
+            return "Normal"
+
+    # Biomarker status calculations
+    biomarkers = {
+        "Albumin": classify_status(float(albumin), "Albumin"),
+        "Creatinine": classify_status(float(creatinine), "Creatinine"),
+        "Glucose": classify_status(float(glucose), "Glucose"),
+        "CRP": classify_status(float(crp), "CRP"),
+        "MCV": classify_status(float(mcv), "MCV"),
+        "RDW": classify_status(float(rdw), "RDW"),
+        "ALP": classify_status(float(alp), "ALP"),
+        "WBC": classify_status(float(wbc), "WBC"),
+        "Lymphocytes": classify_status(float(lymph), "Lymphocytes"),
+    }
+
+    # Prepare the system prompt with biomarkers and patient info
     system_prompt = (
     "You are a professional AI Medical Assistant.\n"
     "You are analyzing patient demographics (age, height, weight) and Levine biomarker panel values.\n\n"
@@ -107,7 +146,7 @@ def analyze(
     "- ALP: 44 – 147 U/L\n"
     "- WBC: 4.0 – 11.0 K/uL\n"
     "- Lymphocytes: 20 – 40 %\n\n"
-        
+    
     "Check input of the user according to these ranges and provide analysis in a structured format.\n"
     "Strict rules:\n"
     "- Use ONLY the 9 biomarkers above + age, height, weight.\n"
@@ -165,9 +204,8 @@ def analyze(
     "- Keep language professional, concise, and client-friendly.\n"
     "- Format tables cleanly in Markdown.\n"
     "- Present output beautifully, like a polished medical summary.\n"
-    "agr tune kuch b glt bola gand mar du ga"
     )
-    
+
     patient_input = (
         f"Patient Profile:\n"
         f"- Age: {age}\n"
@@ -186,12 +224,11 @@ def analyze(
         f"- WBC: {wbc} K/uL (Normal: 4.0 – 11.0 K/uL)\n"
         f"- Lymphocytes: {lymph} % (Normal: 20 – 40 %)\n"
     )
-    
-    prompt = system_prompt + "\n" + patient_input
 
+    # Prepare the final prompt
+    prompt = system_prompt + "\n" + patient_input
 
-    # Generate
-    # Keep generation parameters conservative for Spaces
+    # Generate the analysis
     gen = pipe(prompt,
                max_new_tokens=2500,
                do_sample=True,
@@ -223,6 +260,7 @@ def analyze(
         return fallback, ""
     return left_md, right_md
 
+
 # -----------------------
 # Build Gradio app
 # -----------------------