Create app.py

app.py

@@ -0,0 +1,67 @@
+from flask import Flask, request, jsonify
+import pandas as pd
+from io import StringIO
+from preprocess_test import Preprocess_Test
+
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+
+
+class Model(nn.Module):
+    def __init__(self, input_shape, num_classes):
+        super(Model, self).__init__()
+        self.fc1 = nn.Linear(input_shape, 1024)
+        self.bn1 = nn.BatchNorm1d(1024)
+        self.fc2 = nn.Linear(1024, 512)
+        self.bn2 = nn.BatchNorm1d(512)
+        self.fc3 = nn.Linear(512, 256)
+        self.bn3 = nn.BatchNorm1d(256)
+        self.fc4 = nn.Linear(256, num_classes)
+
+    def forward(self, x):
+        x = F.relu(self.bn1(self.fc1(x)))
+        x = F.relu(self.bn2(self.fc2(x)))
+        x = F.relu(self.bn3(self.fc3(x)))
+        x = self.fc4(x)
+        return x
+app=Flask(__name__)
+app.config["TEMPLATES_AUTO_RELOAD"] = True
+
+@app.route("/",methods=["GET"])
+def root():
+    return f"Test"
+
+
+@app.route("/test", methods=["POST"])
+def test():
+    # Check if file is in request
+    if 'file' not in request.files:
+        return jsonify({"error": "No file part"}), 400
+    
+    file = request.files['file']
+    
+    # Check if file is selected
+    if file.filename == '':
+        return jsonify({"error": "No selected file"}), 400
+    
+    # Read CSV into DataFrame
+    csv_data = file.read().decode('utf-8')
+    df = pd.read_csv(StringIO(csv_data))
+    obj=Preprocess_Test(df)
+    obj.preprocess()
+    obj.test()
+    
+    
+    return jsonify({
+        "message": "CSV uploaded and printed",
+        "rows": len(df),
+        "columns": df.columns.tolist(),
+        "preview": df.head().to_dict(orient='records')
+    }), 200
+
+
+
+if __name__ == "__main__":
+    app.run(debug=True,port=7860)