Update app.py

app.py

@@ -1,34 +1,25 @@
 import gradio as gr
-from transformers import MarianMTModel, MarianTokenizer
+from transformers import pipeline
 
-# 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)
+# Load pre-trained question-answering model
+qa_model = pipeline("question-answering", model="distilbert-base-cased-distilled-squad")
 
-# 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
+# Define the question-answering function
+def answer_question(context, question):
+    result = qa_model(context=context, question=question)
+    answer = result["answer"]
+    confidence = result["score"]
+    return f"Answer: {answer}\nConfidence: {confidence:.4f}"
 
 # Create Gradio interface
 iface = gr.Interface(
-    fn=translate_text,
-    inputs=gr.Textbox(),
+    fn=answer_question,
+    inputs=[gr.Textbox(label="Context"), gr.Textbox(label="Question")],
     outputs=gr.Textbox(),
     live=True,
-    title="Language Translation App",
-    description="Translate text from English to German using MarianMT.",
+    title="Question Answering System",
+    description="Enter a context and a question, and the model will provide an answer.",
 )
 
 # Launch the Gradio app
 iface.launch()
-