diff --git a/Linguify-main.py b/Linguify-main.py
deleted file mode 100644
index aca4b12..0000000
--- a/Linguify-main.py
+++ /dev/null
@@ -1,59 +0,0 @@
-import gradio as gr
-from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
-import torch
-from pyngrok import ngrok
-import os
-
-# Load the model and tokenizer
-model_name = "facebook/nllb-200-distilled-600M"
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-
-# Get all available language codes
-available_languages = list(tokenizer.lang_code_to_id.keys())
-
-def translate_text(text, src_lang, tgt_lang):
-    try:
-        # Tokenize the text with source language
-        inputs = tokenizer(text, return_tensors="pt", src_lang=src_lang)
-        
-        # Generate translation
-        translated = model.generate(
-            **inputs, 
-            forced_bos_token_id=tokenizer.lang_code_to_id[tgt_lang],
-            max_length=128
-        )
-        
-        # Decode the translation
-        translated_text = tokenizer.batch_decode(translated, skip_special_tokens=True)[0]
-        return translated_text
-    except Exception as e:
-        return f"Translation error: {str(e)}"
-
-# Create a Gradio interface
-with gr.Blocks() as app:
-    gr.Markdown("# AI Translator using META NLLB Model")
-    
-    with gr.Row():
-        src_lang = gr.Dropdown(choices=available_languages, label="Source Language")
-        tgt_lang = gr.Dropdown(choices=available_languages, label="Target Language")
-    
-    with gr.Row():
-        input_text = gr.Textbox(lines=5, label="Enter text to translate")
-        output_text = gr.Textbox(lines=5, label="Translated text")
-    
-    translate_btn = gr.Button("Translate")
-    translate_btn.click(fn=translate_text, inputs=[input_text, src_lang, tgt_lang], outputs=output_text)
-
-# Launch the Gradio app
-app.launch(share=True)
-
-# Set up ngrok tunneling (optional)
-if os.environ.get('USE_NGROK'):
-    ngrok_token = os.environ.get('NGROK_TOKEN')
-    if ngrok_token:
-        ngrok.set_auth_token(ngrok_token)
-        public_url = ngrok.connect(port=7860)
-        print(f"Public URL: {public_url}")
-    else:
-        print("NGROK_TOKEN not set. Skipping ngrok tunnel.")