Update app.py

app.py

@@ -1,79 +1,77 @@
-import gradio as gr
-from Backend import process_and_generate_report  # Import backend functions
-
-with gr.Blocks() as iface:
-    gr.Markdown("## <div style='text-align: center;'>AI-DRIVEN DROPOUT PREDICTION AND PREVENTION TOOL</div>")
-
-    with gr.Row():
-        with gr.Column():
-            inputs = {}
-
-            gr.Markdown("### Basic Information")
-            with gr.Row():
-                inputs["roll_no"] = gr.Textbox(label="Roll No")
-                inputs["semester"] = gr.Dropdown(label="Semester", choices=["I", "II", "III", "IV", "V", "VI", "VII", "VIII"], interactive=True)
-
-            gr.Markdown("### Degree Information")
-            inputs["degree"] = gr.Dropdown(label="Degree", choices=[
-                "B.E. - ELECTRONICS AND INSTRUMENTATION ENGINEERING",
-                "B.E. - ELECTRONICS AND COMMUNICATION ENGINEERING",
-                "B.E. - ELECTRICAL AND ELECTRONICS ENGINEERING",
-                "B.E. - COMPUTER SCIENCE AND ENGINEERING",
-                "B.E. - MECHANICAL ENGINEERING",
-                "B.E. - MECHATRONICS ENGINEERING",
-                "B.Tech. - AGRICULTURAL ENGINEERING",
-                "B.Tech. - ARTIFICIAL INTELLIGENCE AND DATA SCIENCE",
-                "B.Tech. - ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING",
-                "B.Tech. - COMPUTER SCIENCE AND BUSINESS SYSTEMS",
-                "B.Tech. - INFORMATION TECHNOLOGY","B.Tech. - BIOTECHNOLOGY",
-            ], interactive=True)
-
-            inputs["special_lab"] = gr.Dropdown(label="Special Lab", choices=["Active", "Non-Active"], interactive=True)
-
-            gr.Markdown("### Academic Performance")
-            with gr.Row():
-                inputs["attendance_percentage"] = gr.Number(label="Attendance Percentage", minimum=0, maximum=100)
-                inputs["formative_assessment"] = gr.Number(label="Formative Assessment (Academic %)", minimum=0, maximum=100)
-
-            with gr.Row():
-                inputs["cgpa"] = gr.Number(label="CGPA", minimum=0, maximum=10)
-                inputs["current_sgpa"] = gr.Number(label="Current SGPA", minimum=0, maximum=10)
-                inputs["arrear_count"] = gr.Number(label="Arrear Count", minimum=0, maximum=48)
-
-            gr.Markdown("### Placement and Assessments")
-            with gr.Row():
-                inputs["placement_fa"] = gr.Number(label="Placement FA %", minimum=0, maximum=100)
-                inputs["placement_cumulative"] = gr.Number(label="Placement Cumulative", minimum=0, maximum=100)
-                inputs["placement_Attendence"] = gr.Number(label="Placement Attendance", minimum=0, maximum=100)
-                inputs["interim_assessment_status"] = gr.Number(label="Interim Assessment Status", minimum=0, maximum=100)
-                inputs["training_assessment_status"] = gr.Number(label="Training Assessment Status", minimum=0, maximum=100)
-                inputs["mock_assessment_status"] = gr.Number(label="Mock Assessment Status", minimum=0, maximum=100)
-
-                
-            gr.Markdown("### Skill Rankings")
-            with gr.Row():
-                inputs["full_stack_rank"] = gr.Number(label="Full Stack Rank", minimum=0, maximum=1700)
-                inputs["ps_rank"] = gr.Number(label="PS Level Completed", minimum=0, maximum=30)
-                inputs["Overall_Skills_Acquired"] = gr.Number(label="Total Skills Acquired")
-
-            gr.Markdown("### Extracurricular Activities")
-            with gr.Row():
-                for key in ["Technical_Competition", "Paper_Presentation", "Project_Competition", "Product_Development", "Patent", "Internship", "Online_Course"]:
-                    inputs[key] = gr.Number(label=key.replace("_", " ").title())
-
-            submit = gr.Button("Predict Dropout")
-
-        with gr.Column():
-            gr.Markdown("### Prediction Output")
-            output_plot = gr.Plot(label ="Dropout Risk Graph")
-            summary = gr.Textbox(label = "Final Summary")
-            download_btn = gr.File(label="Download Report",interactive=False)
-            
-
-    submit.click(
-        lambda *args: process_and_generate_report(**dict(zip(inputs.keys(), args))),
-        inputs=list(inputs.values()),
-        outputs=[output_plot, summary, download_btn]
-    )
-
-iface.launch()
+import gradio as gr
+from Backend import process_and_generate_report  # Import backend functions
+
+with gr.Blocks() as iface:
+    gr.Markdown("## <div style='text-align: center;'>AI-DRIVEN DROPOUT PREDICTION AND PREVENTION TOOL</div>")
+
+    with gr.Row():
+        with gr.Column():
+            inputs = {}
+
+            gr.Markdown("### Basic Information")
+            with gr.Row():
+                inputs["roll_no"] = gr.Textbox(label="Roll No", value="7376211CS203")
+                inputs["semester"] = gr.Dropdown(label="Semester", choices=["I", "II", "III", "IV", "V", "VI", "VII", "VIII"], value="VIII", interactive=True)
+
+            gr.Markdown("### Degree Information")
+            inputs["degree"] = gr.Dropdown(label="Degree", choices=[
+                "B.E. - ELECTRONICS AND INSTRUMENTATION ENGINEERING",
+                "B.E. - ELECTRONICS AND COMMUNICATION ENGINEERING",
+                "B.E. - ELECTRICAL AND ELECTRONICS ENGINEERING",
+                "B.E. - COMPUTER SCIENCE AND ENGINEERING",
+                "B.E. - MECHANICAL ENGINEERING",
+                "B.E. - MECHATRONICS ENGINEERING",
+                "B.Tech. - AGRICULTURAL ENGINEERING",
+                "B.Tech. - ARTIFICIAL INTELLIGENCE AND DATA SCIENCE",
+                "B.Tech. - ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING",
+                "B.Tech. - COMPUTER SCIENCE AND BUSINESS SYSTEMS",
+                "B.Tech. - INFORMATION TECHNOLOGY","B.Tech. - BIOTECHNOLOGY",
+            ], value="B.E. - COMPUTER SCIENCE AND ENGINEERING", interactive=True)
+
+            inputs["special_lab"] = gr.Dropdown(label="Special Lab", choices=["Active", "Non-Active"], value="Non-Active", interactive=True)
+
+            gr.Markdown("### Academic Performance")
+            with gr.Row():
+                inputs["attendance_percentage"] = gr.Number(label="Attendance Percentage", minimum=0, maximum=100, value=90)
+                inputs["formative_assessment"] = gr.Number(label="Formative Assessment (Academic %)", minimum=0, maximum=100, value=50)
+
+            with gr.Row():
+                inputs["cgpa"] = gr.Number(label="CGPA", minimum=0, maximum=10, value=8.0)
+                inputs["current_sgpa"] = gr.Number(label="Current SGPA", minimum=0, maximum=10, value=7.5)
+                inputs["arrear_count"] = gr.Number(label="Arrear Count", minimum=0, maximum=48, value=1)
+
+            gr.Markdown("### Placement and Assessments")
+            with gr.Row():
+                inputs["placement_fa"] = gr.Number(label="Placement FA %", minimum=0, maximum=100, value=50)
+                inputs["placement_cumulative"] = gr.Number(label="Placement Cumulative", minimum=0, maximum=100, value=60)
+                inputs["placement_Attendence"] = gr.Number(label="Placement Attendance", minimum=0, maximum=100, value=70)
+                inputs["interim_assessment_status"] = gr.Number(label="Interim Assessment Status", minimum=0, maximum=100, value=70)
+                inputs["training_assessment_status"] = gr.Number(label="Training Assessment Status", minimum=0, maximum=100, value=75)
+                inputs["mock_assessment_status"] = gr.Number(label="Mock Assessment Status", minimum=0, maximum=100, value=80)
+
+            gr.Markdown("### Skill Rankings")
+            with gr.Row():
+                inputs["full_stack_rank"] = gr.Number(label="Full Stack Rank", minimum=0, maximum=1700, value=850)
+                inputs["ps_rank"] = gr.Number(label="PS Level Completed", minimum=0, maximum=30, value=3)
+                inputs["Overall_Skills_Acquired"] = gr.Number(label="Total Skills Acquired", value=7)
+
+            gr.Markdown("### Extracurricular Activities")
+            with gr.Row():
+                for key in ["Technical_Competition", "Paper_Presentation", "Project_Competition", "Product_Development", "Patent", "Internship", "Online_Course"]:
+                    inputs[key] = gr.Number(label=key.replace("_", " ").title(), value=0)
+
+            submit = gr.Button("Predict Dropout")
+
+        with gr.Column():
+            gr.Markdown("### Prediction Output")
+            output_plot = gr.Plot(label="Dropout Risk Graph")
+            summary = gr.Textbox(label="Final Summary")
+            download_btn = gr.File(label="Download Report", interactive=False)
+
+    submit.click(
+        lambda *args: process_and_generate_report(**dict(zip(inputs.keys(), args))),
+        inputs=list(inputs.values()),
+        outputs=[output_plot, summary, download_btn]
+    )
+
+iface.launch()