diff --git a/test_apps/test_app4.py b/test_apps/test_app4.py
new file mode 100644
index 0000000..61de004
--- /dev/null
+++ b/test_apps/test_app4.py
@@ -0,0 +1,92 @@
+import pandas as pd
+from flask import Flask, request, render_template_string
+import io
+
+app = Flask(__name__)
+
+@app.route('/')
+def index():
+    return '''
+        <h2>Upload File</h2>
+        <form action="/upload" method="post" enctype="multipart/form-data">
+            <input type="file" name="file">
+            <br><br>
+            <input type="text" name="tracking_no" placeholder="Enter Tracking No">
+            <br><br>
+            <input type="submit" value="Upload">
+        </form>
+    '''
+
+@app.route('/upload', methods=['POST'])
+def upload_file():
+    if 'file' not in request.files or 'tracking_no' not in request.form:
+        return "No file or tracking number provided.", 400
+
+    file = request.files['file']
+    tracking_no = request.form['tracking_no']
+    filename = file.filename
+
+    try:
+        # Determine file type and read accordingly
+        if filename.endswith('.csv'):
+            df = pd.read_csv(file, header=None, dtype=str)
+        elif filename.endswith(('.xls', '.xlsx')):
+            df = pd.read_excel(file, header=None, dtype=str)
+        else:
+            return "Unsupported file type. Please upload a CSV or Excel file.", 400
+
+        # Find the "Mail Bag No:" label and retrieve its value from column C (index 2)
+        mail_bag_no = None
+        for i, row in df.iterrows():
+            if row[0] == "Mail Bag No:":
+                mail_bag_no = row[2]
+                break
+
+        if mail_bag_no is None:
+            mail_bag_no = "N/A"
+
+        # Locate header row by looking for "Tracking No" in any row
+        header_row_index = None
+        for i, row in df.iterrows():
+            if row.str.contains("Tracking No", case=False, na=False).any():
+                header_row_index = i
+                break
+
+        if header_row_index is None:
+            return "'Tracking No' column not found in the file."
+
+        # Reload the file with the identified header row
+        file.seek(0)  # Reset file pointer to start of file for re-read
+        if filename.endswith('.csv'):
+            df = pd.read_csv(file, skiprows=header_row_index)
+        else:
+            df = pd.read_excel(file, skiprows=header_row_index)
+
+    except Exception as e:
+        return f"Error processing file: {e}", 500
+
+    # Confirm the 'Tracking No' column exists in this adjusted DataFrame
+    if 'Tracking No' not in df.columns:
+        return f"'Tracking No' column not found. Available columns after adjustment: {', '.join(df.columns)}"
+
+    # Filter the data based on the tracking number
+    filtered_data = df[df['Tracking No'] == tracking_no]
+
+    if filtered_data.empty:
+        return f"No data found for Tracking No: {tracking_no}"
+
+    # Collect data for each matching entry
+    result_html = "<h2>Tracking Information</h2>"
+    for _, row in filtered_data.iterrows():
+        hash_column = row.get('#', "N/A")
+        result_html += f"""
+            <p><strong>Tracking No:</strong> {row['Tracking No']}</p>
+            <p><strong>Mail Bag No:</strong> {mail_bag_no}</p>
+            <p><strong>#:</strong> {hash_column}</p>
+            <hr>
+        """
+    
+    return render_template_string(result_html)
+
+if __name__ == '__main__':
+    app.run(debug=True, port=5000, host='0.0.0.0')