Create app.py

app.py

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+import gradio as gr
+from transformers import MarianMTModel, MarianTokenizer
+
+# Define a function that loads a model and tokenizer based on the chosen language
+def load_model(lang_pair):
+    if lang_pair == "English to French":
+        model_name = 'Helsinki-NLP/opus-mt-en-fr'
+    elif lang_pair == "Kinyarwanda to English":
+        model_name = 'Helsinki-NLP/opus-mt-rw-en'
+    else:
+        raise ValueError("Unsupported language pair")
+    
+    tokenizer = MarianTokenizer.from_pretrained(model_name)
+    model = MarianMTModel.from_pretrained(model_name)
+    return model, tokenizer
+
+# Function to translate text based on selected language
+def translate(lang_pair, text):
+    model, tokenizer = load_model(lang_pair)
+    
+    # Tokenize the text using the __call__ method
+    model_inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+    
+    # Perform the translation
+    gen = model.generate(**model_inputs)
+    
+    # Decode the generated tokens to string
+    translation = tokenizer.batch_decode(gen, skip_special_tokens=True)
+    return translation[0]
+
+# Create a Gradio interface with a dropdown menu for language selection
+iface = gr.Interface(
+    fn=translate,
+    inputs=[
+        gr.Dropdown(choices=["English to French", "Kinyarwanda to English"], label="Select Language"),
+        gr.Textbox(lines=2, placeholder="Enter Message...")
+    ],
+    outputs=gr.Textbox()
+)
+
+# Launch the interface
+iface.launch(debug=True,inline=False)