Create app.py

app.py

@@ -0,0 +1,52 @@
+import gradio as gr
+from transformers import MarianMTModel, MarianTokenizer
+
+# Load English to Arabic translation model and tokenizer
+en_ar_model_name = "Helsinki-NLP/opus-mt-en-ar"
+en_ar_model = MarianMTModel.from_pretrained(en_ar_model_name)
+en_ar_tokenizer = MarianTokenizer.from_pretrained(en_ar_model_name)
+
+# Load Arabic to English translation model and tokenizer
+ar_en_model_name = "Helsinki-NLP/opus-mt-ar-en"
+ar_en_model = MarianMTModel.from_pretrained(ar_en_model_name)
+ar_en_tokenizer = MarianTokenizer.from_pretrained(ar_en_model_name)
+
+def translate_en_to_ar(text):
+    inputs = en_ar_tokenizer.encode(text, return_tensors="pt")
+    translation = en_ar_model.generate(inputs, max_length=128)
+    translated_text = en_ar_tokenizer.decode(translation[0], skip_special_tokens=True)
+    return translated_text
+
+def translate_ar_to_en(text):
+    inputs = ar_en_tokenizer.encode(text, return_tensors="pt")
+    translation = ar_en_model.generate(inputs, max_length=128)
+    translated_text = ar_en_tokenizer.decode(translation[0], skip_special_tokens=True)
+    return translated_text
+
+# Create Gradio interfaces for both translation directions
+en_ar_interface = gr.Interface(
+    fn=translate_en_to_ar,
+    inputs="text",
+    outputs="text",
+    title="English to Arabic Translation",
+    description="Translate English text to Arabic."
+)
+
+ar_en_interface = gr.Interface(
+    fn=translate_ar_to_en,
+    inputs="text",
+    outputs="text",
+    title="Arabic to English Translation",
+    description="Translate Arabic text to English."
+)
+
+# Combine the interfaces in a single app
+app = gr.Interface(
+    [en_ar_interface, ar_en_interface],
+    layout="horizontal",
+    title="Translation App",
+    description="Translate text between English and Arabic."
+)
+
+if __name__ == "__main__":
+    app.launch()