updated the correct path

app.py

@@ -3,6 +3,7 @@ import pandas as pd
 from tensorflow.keras.preprocessing.text import Tokenizer
 from tensorflow.keras.preprocessing.sequence import pad_sequences
 from tensorflow.keras.models import load_model
+from datasets import load_dataset
 from huggingface_hub import hf_hub_download
 import numpy as np
 import tensorflow as tf
@@ -16,7 +17,15 @@ rnn_filename = "model_rnn_1.keras"
 lstm_model_path = hf_hub_download(repo_id=repo_id, filename=lstm_filename)
 rnn_model_path = hf_hub_download(repo_id=repo_id, filename=rnn_filename)
 
-data_text_path = "/Users/himanishprakash/NLP-Application/code/data_preprocess/df_commentary.csv"
+# Specify the repository and the CSV file name
+# Specify the repository and the CSV file name
+repo_path = "himanishprak23/commentry_Data"
+file_name = "df_commentary_new.csv"
+
+# Load the dataset
+dataset = load_dataset(repo_path, data_files=file_name, split='train')
+data_text = dataset.to_pandas()
+
 
 # Load the LSTM model
 lstm_model = load_model(lstm_model_path)
@@ -24,8 +33,7 @@ lstm_model = load_model(lstm_model_path)
 # Load the RNN model
 rnn_model = load_model(rnn_model_path)
 
-# Load the data for tokenizer fitting
-data_text = pd.read_csv(data_text_path)
+
 
 # Check the embedding layer's input dimension for LSTM
 embedding_layer = lstm_model.layers[0]
@@ -162,7 +170,7 @@ def generate_with_all_models(commentary_text, num_words, max_length, temperature
     return lstm_output, rnn_output, gpt2_finetuned_output, gpt2_base_output
 
 # Create the Gradio interface
-commentrymodel = gr.Interface(
+iface = gr.Interface(
     fn=generate_with_all_models,
     inputs=[
         gr.Textbox(lines=2, placeholder="Enter commentary text here...", label="Prompt"),
@@ -182,4 +190,4 @@ commentrymodel = gr.Interface(
 
 # Launch the app
 if __name__ == "__main__":
-    commentrymodel.launch()
+    iface.launch()