Initial commit with model and application files

.gitattributes

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+*.keras filter=lfs diff=lfs merge=lfs -text

app.py

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+import os
+import tensorflow as tf
+import pandas as pd
+import gradio as gr
+
+# Load the model
+# Load the model dynamically from the current directory
+model_path = "model.keras"
+
+try:
+    model = tf.keras.models.load_model(model_path)
+    print(f"Model loaded successfully from: {model_path}")
+except Exception as e:
+    raise RuntimeError(f"Failed to load the model from {model_path}: {e}")
+
+
+# Define the risk classes
+classes = ['No Immediate Risk', 'Medium Risk of Harm - Needs Monitoring', 'Immediate Concern - Needs Urgent Support']
+
+# Yes/No mapping for questions
+yes_no_mapping = {
+    'q1': {'yes': 0.1, 'no': 0}, 'q2': {'yes': 0.1, 'no': 0}, 'q3': {'yes': 0.1, 'no': 0},
+    'q4': {'yes': 0.1, 'no': 0}, 'q5': {'yes': 0.1, 'no': 0}, 'q6': {'yes': 0.1, 'no': 0},
+    'q7': {'yes': 0.1, 'no': 0}, 'q8': {'yes': 0.1, 'no': 0}, 'q9': {'yes': 0.1, 'no': 0},
+    'q10': {'yes': 0.1, 'no': 0}, 'q11': {'yes': 0.5, 'no': 0}, 'q12': {'yes': 0.7, 'no': 0},
+    'q13': {'yes': 0.5, 'no': 0}, 'q14': {'yes': 0.5, 'no': 0}, 'q15': {'yes': 0.5, 'no': 0},
+    'q16': {'yes': 0.5, 'no': 0}, 'q17': {'yes': 0.7, 'no': 0}, 'q18': {'yes': 0.7, 'no': 0},
+    'q19': {'yes': 0.7, 'no': 0}, 'q20': {'yes': 0.7, 'no': 0}, 'q21': {'yes': 0.7, 'no': 0},
+    'q22': {'yes': 0.7, 'no': 0}, 'q23': {'yes': 0.7, 'no': 0}, 'q24': {'yes': 0.7, 'no': 0},
+    'q25': {'yes': 0.7, 'no': 0}, 'q26': {'yes': 0.7, 'no': 0}, 'q27': {'yes': 0.9, 'no': 0},
+    'q28': {'yes': 0.9, 'no': 0}, 'q29': {'yes': 0.9, 'no': 0}, 'q30': {'yes': 0.9, 'no': 0},
+    'q31': {'yes': 1, 'no': 0}, 'q32': {'yes': 1, 'no': 0}, 'q33': {'yes': 1, 'no': 0}
+}
+
+# Store responses in a DataFrame
+responses_df = pd.DataFrame(columns=["Name", "ID", "Predicted Risk Level"])
+
+# Function to process form input
+def predict_from_form(name, id_number, *responses):
+    global responses_df
+    try:
+        # Map Yes/No to numeric
+        processed_data = [yes_no_mapping[f'q{i+1}'][response.lower()] for i, response in enumerate(responses)]
+        input_data = pd.DataFrame([processed_data], columns=[f'q{i+1}' for i in range(len(responses))])
+
+        # Predict using model
+        predictions = model.predict(input_data)
+        predicted_class = predictions.argmax(axis=1)[0]
+
+        # Store the result
+        new_entry = {"Name": name or "N/A", "ID": id_number or "N/A", "Predicted Risk Level": classes[predicted_class]}
+        responses_df = pd.concat([responses_df, pd.DataFrame([new_entry])], ignore_index=True)
+
+        return f"Prediction for {name or 'Anonymous'}: {classes[predicted_class]}"
+    except Exception as e:
+        return f"Error: {e}"
+
+# Function to process uploaded CSV file
+def predict_risk_from_csv(file):
+    try:
+        # Load the CSV file
+        form_data = pd.read_csv(file.name)
+
+        # Clean column names: Remove trailing spaces, parentheses, etc.
+        cleaned_columns = [col.split('(')[0].strip() for col in form_data.columns]
+        form_data.columns = cleaned_columns
+
+        # Standardize "Yes"/"No" answers: Strip spaces and standardize case
+        form_data_cleaned = form_data.apply(
+            lambda x: x.str.strip().str.lower() if x.dtype == "object" else x
+        )
+
+        # Remove unnecessary columns (optional, can be adjusted as per the CSV format)
+        form_data_cleaned.drop(columns=["Timestamp", "Full Name", "Preparing for"], inplace=True, errors='ignore')
+
+        # Rename questions to match model input: Mapping column names to q1, q2, ..., q33
+        simplified_columns = {
+            'Is your age is less than 18 years?': 'q1',
+            'Are you Male': 'q2',
+            'Have financial concerns been a source of stress for you or your family?': 'q3',
+            'Are you currently living alone, and unsatisfied with your living situation?': 'q4',
+            'Are you living in Hostel and unsatisfied with your living situation?': 'q5',
+            'Do you feel like you are studying here mainly because of your family’s expectations?': 'q6',
+            'Have you been feeling disappointed with your academic performance recently?': 'q7',
+            'Do you feel like your parents are unhappy with your academic performance and you are letting them down?': 'q8',
+            'Are there are several problems in your family or your family environment is very stressful?': 'q9',
+            'Your family does not support your decisions or your choices?': 'q10',
+            'Have you recently experienced a breakup': 'q11',
+            'Have you ever suffered from any mental illness in past or are currently suffering': 'q12',
+            'Is there any history of psychiatric illness in your family?': 'q13',
+            'Suicide committed by any close family member recently or in past': 'q14',
+            'Suicide committed by any close friend recently': 'q15',
+            'Suffering from any medical illness like Diabetes or Asthma or Hypertension or any other chronic illness': 'q16',
+            'Have you found yourself using alcohol, drugs, or online gaming to cope with stress or emotions recently?': 'q17',
+            'Have you ever experienced any form of abuse': 'q18',
+            'Have you been feeling emotionally numb or disconnected over the past few days?': 'q19',
+            'Are you feeling very sad or very anxious since last few days': 'q20',
+            'Have you been feeling hurt or embarrassed by things others have said or done recently?': 'q21',
+            'Have you been feeling trapped in your current situation, and do you need support to find a way out?': 'q22',
+            'Have you been feeling particularly lonely over the past few days?': 'q23',
+            'Have you been feeling uncertain or hopeless about your future?': 'q24',
+            'Have you lost interest in things you usually enjoy over the past few days?': 'q25',
+            'Have you been struggling with sleep recently, either finding it hard to fall asleep or stay asleep?': 'q26',
+            'Have thoughts about hurting yourself crossed your mind?': 'q27',
+            'Have you felt like life has been overwhelming recently?': 'q28',
+            'Have you been feeling a lack of motivation or desire to keep going in life ?': 'q29',
+            'Have you been feeling like hurting yourself recently?': 'q30',
+            'Have you been searching online for information related to suicide?': 'q31',
+            'Have you been feeling so overwhelmed or distressed that you’ve considered or planned how to end your life?': 'q32',
+            'Have you previously had moments where you tried to harm yourself or end your life?': 'q33'
+        }
+
+        form_data_cleaned.rename(columns=simplified_columns, inplace=True)
+
+        # Apply Yes/No mapping
+        for col, mapping in yes_no_mapping.items():
+            if col in form_data_cleaned.columns:
+                form_data_cleaned[col] = form_data_cleaned[col].map(mapping)
+
+        # Convert any non-numeric values to NaN
+        form_data_cleaned = form_data_cleaned.apply(pd.to_numeric, errors='coerce')
+
+        # Drop rows with missing data
+        form_data_cleaned.dropna(inplace=True)
+
+        # Ensure valid rows exist after cleaning
+        if not form_data_cleaned.empty:
+            predictions = model.predict(form_data_cleaned)
+            predicted_classes = predictions.argmax(axis=1)
+
+            # Add predicted risk category back to the original data
+            form_data['Predicted Risk Category'] = [classes[i] for i in predicted_classes]
+
+            # Return relevant columns: Full Name (if exists) and Predictions
+            if 'Full Name' in form_data.columns:
+                return form_data[['Full Name', 'Predicted Risk Category']]
+            else:
+                return form_data[['Predicted Risk Category']]
+        else:
+            return "No valid data to process after cleaning. Please check the file format."
+
+    except Exception as e:
+        return f"Error processing the file: {str(e)}"
+
+
+# Function to view all recorded responses
+def view_responses():
+    if responses_df.empty:
+        return "No responses recorded yet."
+    return responses_df
+
+# Define Gradio Inputs
+form_inputs = [
+    gr.Textbox(label="Name (Optional)"), gr.Textbox(label="ID (Optional)")
+]
+form_inputs.extend([
+    gr.Radio(["Yes", "No"], label="Is your age less than 18 years?"),  # q1
+    gr.Radio(["Yes", "No"], label="Are you Male?"),  # q2
+    gr.Radio(["Yes", "No"], label="Have financial concerns been a source of stress for you or your family?"),  # q3
+    gr.Radio(["Yes", "No"], label="Are you currently living alone, and unsatisfied with your living situation?"),  # q4
+    gr.Radio(["Yes", "No"], label="Are you living in Hostel and unsatisfied with your living situation?"),  # q5
+    gr.Radio(["Yes", "No"], label="Do you feel like you are studying here mainly because of your family’s expectations?"),  # q6
+    gr.Radio(["Yes", "No"], label="Have you been feeling disappointed with your academic performance recently?"),  # q7
+    gr.Radio(["Yes", "No"], label="Do you feel like your parents are unhappy with your academic performance and you are letting them down?"),  # q8
+    gr.Radio(["Yes", "No"], label="Are there are several problems in your family or your family environment is very stressful?"),  # q9
+    gr.Radio(["Yes", "No"], label="Your family does not support your decisions or your choices?"),  # q10
+    gr.Radio(["Yes", "No"], label="Have you recently experienced a breakup?"),  # q11
+    gr.Radio(["Yes", "No"], label="Have you ever suffered from any mental illness in past or are currently suffering?"),  # q12
+    gr.Radio(["Yes", "No"], label="Is there any history of psychiatric illness in your family?"),  # q13
+    gr.Radio(["Yes", "No"], label="Has any close family member recently or in the past committed suicide?"),  # q14
+    gr.Radio(["Yes", "No"], label="Has any close friend recently committed suicide?"),  # q15
+    gr.Radio(["Yes", "No"], label="Are you suffering from any medical illness like Diabetes, Asthma, Hypertension, or other chronic illness?"),  # q16
+    gr.Radio(["Yes", "No"], label="Have you found yourself using alcohol, drugs, or online gaming to cope with stress recently?"),  # q17
+    gr.Radio(["Yes", "No"], label="Have you ever experienced any form of abuse?"),  # q18
+    gr.Radio(["Yes", "No"], label="Have you been feeling emotionally numb or disconnected over the past few days?"),  # q19
+    gr.Radio(["Yes", "No"], label="Are you feeling very sad or anxious since the last few days?"),  # q20
+    gr.Radio(["Yes", "No"], label="Have you been feeling hurt or embarrassed by things others have said recently?"),  # q21
+    gr.Radio(["Yes", "No"], label="Have you been feeling trapped in your current situation and need support to find a way out?"),  # q22
+    gr.Radio(["Yes", "No"], label="Have you been feeling particularly lonely over the past few days?"),  # q23
+    gr.Radio(["Yes", "No"], label="Have you been feeling uncertain or hopeless about your future?"),  # q24
+    gr.Radio(["Yes", "No"], label="Have you lost interest in things you usually enjoy over the past few days?"),  # q25
+    gr.Radio(["Yes", "No"], label="Have you been struggling with sleep recently, either finding it hard to fall asleep or stay asleep?"),  # q26
+    gr.Radio(["Yes", "No"], label="Have thoughts about hurting yourself crossed your mind?"),  # q27
+    gr.Radio(["Yes", "No"], label="Have you felt like life has been overwhelming recently?"),  # q28
+    gr.Radio(["Yes", "No"], label="Have you been feeling a lack of motivation or desire to keep going in life?"),  # q29
+    gr.Radio(["Yes", "No"], label="Have you been feeling like hurting yourself recently?"),  # q30
+    gr.Radio(["Yes", "No"], label="Have you been searching online for information related to suicide?"),  # q31
+    gr.Radio(["Yes", "No"], label="Have you been feeling so distressed that you’ve considered or planned how to end your life?"),  # q32
+    gr.Radio(["Yes", "No"], label="Have you previously had moments where you tried to harm yourself or end your life?")  # q33
+])
+
+
+# Gradio Interface
+interface = gr.TabbedInterface(
+    [
+        gr.Interface(
+            fn=predict_from_form,
+            inputs=form_inputs,
+            outputs="text",
+            title="Manual Form Submission",
+            description="Submit your responses manually."
+        ),
+        gr.Interface(
+            fn=predict_risk_from_csv,
+            inputs=gr.File(label="Upload CSV File"),
+            outputs="dataframe",
+            title="Upload CSV File",
+            description="Upload a Google Form CSV file for bulk predictions."
+        ),
+        gr.Interface(
+            fn=view_responses,
+            inputs=None,
+            outputs="dataframe",
+            title="View All Responses",
+            description="View all the recorded responses so far."
+        )
+    ],
+    ["Manual Form Submission", "Upload CSV File", "View All Responses"]
+)
+
+# Launch the Gradio app
+if __name__ == "__main__":
+    interface.launch(share=False, inbrowser=True)

model.keras

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+version https://git-lfs.github.com/spec/v1
+oid sha256:23fcfce21eeb6f07d4a9e48417cec80da9b823a320a2fb06c713cd3e207fef18
+size 265377

requirements.txt

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+tensorflow==2.18.0
+pandas
+gradio
+numpy