Update app.py

app.py

@@ -2,17 +2,29 @@ import gradio as gr
 import nlpaug.augmenter.word as naw
 import nlpaug.augmenter.char as nac
 import nlpaug.augmenter.sentence as nas
-
+import os
 import nltk
+from nlpaug.util.file.download import DownloadUtil
+
+# Download necessary NLTK resources
 nltk.download('averaged_perceptron_tagger')
 nltk.download('wordnet')
 
+# Function to download Word2Vec model if not available
+def download_word2vec():
+    word2vec_path = "GoogleNews-vectors-negative300.bin"
+    if not os.path.exists(word2vec_path):
+        print("Downloading Word2Vec model...")
+        DownloadUtil.download_word2vec(dest_dir='.')
+    return word2vec_path
+
 # Function for NLP augmentation
 def augment_text(text, method):
     if method == "Synonym Replacement":
         aug = naw.SynonymAug(aug_src="wordnet", aug_max=3)
     elif method == "Word Embedding Substitution":
-        aug = naw.WordEmbsAug(model_type='word2vec', model_path="GoogleNews-vectors-negative300.bin", action="substitute")
+        word2vec_path = download_word2vec()  # Ensure the model is downloaded
+        aug = naw.WordEmbsAug(model_type='word2vec', model_path=word2vec_path, action="substitute")
     elif method == "Contextual Word Insertion":
         aug = naw.ContextualWordEmbsAug(model_path="bert-base-uncased", action="insert")
     elif method == "Back Translation":
@@ -36,4 +48,4 @@ iface = gr.Interface(
     title="NLP Text Augmentation with Gradio"
 )
 
-iface.launch()
+iface.launch(share=True)