Update app.py

app.py

@@ -3,15 +3,10 @@ os.system('pip install transformers')
 # Import the necessary libraries
 import os
 os.system('pip install torch')
-
-from transformers import AutoModel, AutoTokenizer
-import torch
-
 from transformers import AutoModel, AutoTokenizer
 import torch
 from torch.utils.data import DataLoader, Dataset
 from sklearn.model_selection import train_test_split
-from google.colab import files
 import pandas as pd
 import gradio as gr
 
@@ -19,25 +14,12 @@ import gradio as gr
 model = AutoModel.from_pretrained("Alibaba-NLP/gte-multilingual-base", trust_remote_code=True)
 tokenizer = AutoTokenizer.from_pretrained("Alibaba-NLP/gte-multilingual-base", trust_remote_code=True)
 
-# Upload your dataset
-uploaded = files.upload()
-
-# Load the dataset
-filename = next(iter(uploaded))  # Automatically get the first uploaded file's name
-df = pd.read_excel(filename)  # Read the uploaded Excel file
-
-# Display the columns in the uploaded DataFrame to help identify correct names
-print("Columns in the dataset:", df.columns.tolist())
-
-# Function to search by name and return the PEC number
+# Example Gradio function
 def search_by_name(name):
-    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]}"
-    else:
-        return "No matches found for your name."
+    # Your logic to search by name and return a response
+    pass
 
-# Gradio interface with the updated syntax
+# Gradio interface
 iface = gr.Interface(
     fn=search_by_name,
     inputs=gr.Textbox(label="Please write your Name"),
@@ -46,7 +28,6 @@ iface = gr.Interface(
     description="Enter your name to find your PEC number."
 )
 
-# Launch the Gradio interface
+# Launch the interface
 iface.launch()
 
-