Update app.py

app.py

@@ -6,7 +6,7 @@ import os
 from sklearn.ensemble import RandomForestRegressor
 
 # --------------------------------------------------
-# LOGO PATH (ABSOLUTE WINDOWS PATH)
+# CORRECT LOGO PATH (RAW STRING)
 # --------------------------------------------------
 LOGO_FILE = r"C:\Users\SASTRA\Desktop\sastra_logo.jpg"
 
@@ -41,7 +41,7 @@ model = RandomForestRegressor(n_estimators=150, random_state=42)
 model.fit(X_train,y_train)
 
 # --------------------------------------------------
-# IQ CALCULATION (OUTPUT)
+# IQ CALCULATION
 # --------------------------------------------------
 def calculate_iq(reasoning, aptitude, problem_solving,
                  verbal, communication, understanding):
@@ -58,7 +58,7 @@ def calculate_iq(reasoning, aptitude, problem_solving,
     return round(iq,2)
 
 # --------------------------------------------------
-# ANTIGRAVITY AI FUNCTION
+# MAIN AI FUNCTION
 # --------------------------------------------------
 def institutional_ai(
     name, regno, vision, mission, arrears,
@@ -82,7 +82,7 @@ def institutional_ai(
 
     performance = float(model.predict(features)[0])
 
-    # -------- Weak Areas --------
+    # Weak areas
     weak=[]
     if coding<5: weak.append("Coding")
     if aptitude<5: weak.append("Aptitude")
@@ -91,7 +91,7 @@ def institutional_ai(
 
     concentration=", ".join(weak) if weak else "Balanced Skill Profile"
 
-    # -------- Placement --------
+    # Placement prediction
     if performance>=80 and cgpa>=8:
         placement="High Probability → Product Companies"
     elif performance>=65:
@@ -141,9 +141,6 @@ Student: {name} ({regno})
 Predicted Performance : {round(performance,2)}
 Estimated IQ          : {iq}
 
-Academic Trend:
-{"Improving" if sg6>=sg1 else "Needs Improvement"}
-
 Focus Areas:
 {concentration}
 
@@ -151,21 +148,15 @@ Placement Outlook:
 {placement}
 """
 
-    # --------------------------------------------------
-    # SAVE CSV
-    # --------------------------------------------------
-    row={
-        "Name":name,"RegisterNo":regno,
-        "Arrears":arrears,
-        "SGPA1":sg1,"SGPA2":sg2,"SGPA3":sg3,
-        "SGPA4":sg4,"SGPA5":sg5,"SGPA6":sg6,
+    # Save CSV
+    df=pd.DataFrame([{
+        "Name":name,
+        "RegisterNo":regno,
         "CGPA":cgpa,
         "IQ":iq,
         "Performance":round(performance,2),
         "Placement":placement
-    }
-
-    df=pd.DataFrame([row])
+    }])
 
     if os.path.exists(CSV_FILE):
         df.to_csv(CSV_FILE,mode='a',header=False,index=False)
@@ -180,12 +171,10 @@ Placement Outlook:
 # --------------------------------------------------
 with gr.Blocks() as demo:
 
-    # Safe logo display
+    # Logo display (safe)
     if os.path.exists(LOGO_FILE):
-        gr.Image(value=LOGO_FILE,
-                 show_label=False,
-                 container=False,
-                 height=150)
+        gr.Image(LOGO_FILE, show_label=False,
+                 container=False, height=150)
 
     gr.HTML(INSTITUTION_HTML)