Update app.py

app.py

@@ -1,25 +1,34 @@
 import gradio as gr
-from transformers import pipeline
+from transformers import MarianMTModel, MarianTokenizer
 
-# Load pre-trained sentiment analysis model
-classifier = pipeline('sentiment-analysis')
+# Load pre-trained MarianMT model and tokenizer for translation
+model_name = "Helsinki-NLP/opus-mt-en-de"
+model = MarianMTModel.from_pretrained(model_name)
+tokenizer = MarianTokenizer.from_pretrained(model_name)
 
-# Define the sentiment analysis function
-def analyze_sentiment(text):
-    result = classifier(text)
-    sentiment = result[0]['label']
-    confidence = result[0]['score']
-    return f"Sentiment: {sentiment}, Confidence: {confidence:.4f}"
+# Define the translation function
+def translate_text(text):
+    # Tokenize the input text
+    inputs = tokenizer(text, return_tensors="pt")
+
+    # Perform translation
+    translation = model.generate(**inputs)
+
+    # Decode the translated text
+    translated_text = tokenizer.decode(translation[0], skip_special_tokens=True)
+
+    return translated_text
 
 # Create Gradio interface
 iface = gr.Interface(
-    fn=analyze_sentiment,
+    fn=translate_text,
     inputs=gr.Textbox(),
     outputs=gr.Textbox(),
     live=True,
-    title="Sentiment Analysis App",
-    description="Enter a sentence, and the model will predict its sentiment.",
+    title="Language Translation App",
+    description="Translate text from English to German using MarianMT.",
 )
 
 # Launch the Gradio app
 iface.launch()
+