Update app.py

app.py

@@ -3,40 +3,89 @@ import gradio as gr
 # Hardcoded NEET cutoff data for top 10 medical colleges in India (example data) by reservation category
 colleges_data = {
     "All India Institute of Medical Sciences (AIIMS) Delhi": {
-        "2023": {"GEN": 705, "OBC": 685, "SC": 675, "ST": 670},
-        "2022": {"GEN": 700, "OBC": 680, "SC": 670, "ST": 665},
-        "2021": {"GEN": 705, "OBC": 685, "SC": 675, "ST": 670},
+        "GEN": [705, 700, 705],
+        "OBC": [685, 680, 685],
+        "SC": [675, 670, 675],
+        "ST": [670, 665, 670],
     },
     "Maulana Azad Medical College (MAMC) Delhi": {
-        "2023": {"GEN": 690, "OBC": 675, "SC": 665, "ST": 660},
-        "2022": {"GEN": 685, "OBC": 670, "SC": 660, "ST": 655},
-        "2021": {"GEN": 690, "OBC": 675, "SC": 665, "ST": 660},
+        "GEN": [690, 685, 690],
+        "OBC": [675, 670, 675],
+        "SC": [665, 660, 665],
+        "ST": [660, 655, 660],
     },
-    # Add more colleges as needed
+    "Christian Medical College (CMC) Vellore": {
+        "GEN": [675, 670, 675],
+        "OBC": [660, 655, 660],
+        "SC": [650, 645, 650],
+        "ST": [645, 640, 645],
+    },
+    "King George's Medical University (KGMU) Lucknow": {
+        "GEN": [665, 660, 665],
+        "OBC": [650, 645, 650],
+        "SC": [640, 635, 640],
+        "ST": [635, 630, 635],
+    },
+    "Jawaharlal Institute of Postgraduate Medical Education & Research (JIPMER) Puducherry": {
+        "GEN": [670, 665, 670],
+        "OBC": [655, 650, 655],
+        "SC": [645, 640, 645],
+        "ST": [640, 635, 640],
+    },
+    "Grant Medical College Mumbai": {
+        "GEN": [655, 650, 655],
+        "OBC": [640, 635, 640],
+        "SC": [630, 625, 630],
+        "ST": [625, 620, 625],
+    },
+    "Seth GS Medical College Mumbai": {
+        "GEN": [660, 655, 660],
+        "OBC": [645, 640, 645],
+        "SC": [635, 630, 635],
+        "ST": [630, 625, 630],
+    },
+    "Banaras Hindu University (BHU) Varanasi": {
+        "GEN": [675, 670, 675],
+        "OBC": [660, 655, 660],
+        "SC": [650, 645, 650],
+        "ST": [645, 640, 645],
+    },
+    "Lady Hardinge Medical College (LHMC) Delhi": {
+        "GEN": [680, 675, 680],
+        "OBC": [665, 660, 665],
+        "SC": [655, 650, 655],
+        "ST": [650, 645, 650],
+    },
+    "University College of Medical Sciences (UCMS) Delhi": {
+        "GEN": [685, 680, 685],
+        "OBC": [670, 665, 670],
+        "SC": [660, 655, 660],
+        "ST": [655, 650, 655],
+    }
 }
 
-# Function to calculate eligible colleges based on NEET score, year, and reservation category
-def neet_cutoff_calculator(score, year, category):
+# Function to calculate eligible colleges based on NEET score and reservation category
+def neet_cutoff_calculator(score, category):
     eligible_colleges = []
     for college, cutoffs in colleges_data.items():
-        if year in cutoffs and category in cutoffs[year] and score >= cutoffs[year][category]:
-            eligible_colleges.append(college)
+        average_cutoff = sum(cutoffs[category]) / len(cutoffs[category])
+        if score >= average_cutoff:
+            eligible_colleges.append(f"{college} (Avg Cutoff: {average_cutoff:.2f})")
     return eligible_colleges
 
 # Function for Gradio interface
-def calculate_colleges(score, year, category):
-    eligible_colleges = neet_cutoff_calculator(score, year, category)
+def calculate_colleges(score, category):
+    eligible_colleges = neet_cutoff_calculator(score, category)
     if eligible_colleges:
         return f"With a score of {score}, you are eligible for admission to the following colleges: {', '.join(eligible_colleges)}"
     else:
-        return "Unfortunately, no colleges match your score for the selected year and category."
+        return "Unfortunately, no colleges match your score for the selected category."
 
 # Create the Gradio interface using the updated syntax
 iface = gr.Interface(
     fn=calculate_colleges,
     inputs=[
         gr.Slider(0, 720, label="NEET Score"),
-        gr.Dropdown(["2023", "2022", "2021"], label="Year"),
         gr.Dropdown(["GEN", "OBC", "SC", "ST"], label="Category")
     ],
     outputs="text",