Update app.py

app.py

@@ -20,6 +20,7 @@ from torch.utils.data import DataLoader, Dataset
 from sklearn.model_selection import train_test_split
 import pandas as pd
 import gradio as gr
+import os
 
 # Load the pre-trained model and tokenizer
 model = AutoModel.from_pretrained("Alibaba-NLP/gte-multilingual-base", trust_remote_code=True)
@@ -27,15 +28,20 @@ tokenizer = AutoTokenizer.from_pretrained("Alibaba-NLP/gte-multilingual-base", t
 
 # Function to load the dataset
 def load_dataset():
-    df = pd.read_excel("data.xlsx")  # Ensure the file name and path are correct
+    # Use the uploaded file path
+    file_path = "Valid-part-2.xlsx"
+    if not os.path.exists(file_path):
+        raise FileNotFoundError(f"Dataset not found. Please ensure that '{file_path}' exists.")
+    
+    df = pd.read_excel(file_path)  # Load the Excel file
     print("Columns in the dataset:", df.columns.tolist())
     return df
 
 # Function to search by name and return the PEC number
 def search_by_name(name, df):
-    name_matches = df[df['Name'].str.contains(name, case=False, na=False)]
+    name_matches = df[df['name'].str.contains(name, case=False, na=False)]
     if not name_matches.empty:
-        return f"Your PEC number: {name_matches['PEC No'].values[0]}"
+        return f"Your PEC number: {name_matches['PEC number'].values[0]}"
     else:
         return "No matches found for your name."
 
@@ -53,5 +59,9 @@ def build_interface():
 
 # Main function to run the Gradio app
 if __name__ == "__main__":
-    iface = build_interface()
-    iface.launch()
+    try:
+        iface = build_interface()
+        iface.launch()
+    except FileNotFoundError as e:
+        print(str(e))
+