Update app.py

app.py

@@ -16,7 +16,7 @@ example_contexts=page_py.text.split(f"\n")
 for i in range(len(example_contexts)):
     example_contexts[i]=re.sub(f'\n'," ", example_contexts[i])
 # Recommended words for users to choose from
-recommended_words = [
+recommended_words = word_list = [
     "did",
     "what",
     "how",
@@ -75,10 +75,8 @@ def generate_qa(context, recommended_word, temperature, top_p,num_seq, num_sampl
     #
     generated_text = tokenizer.batch_decode(output, skip_special_tokens=True)
 
-    formatted_output = "\n\n".join([f"Original Context: {context}", "Generated Sentences:"] + generated_text)
+    formatted_output = "\n\n".join(set(generated_text))
     return formatted_output
-
-# Create the Gradio interface with sliders for temperature and top-p
 iface = gr.Interface(
     fn=generate_qa,
     inputs=[
@@ -86,13 +84,11 @@ iface = gr.Interface(
         gr.inputs.Radio(recommended_words, label="Choose a Recommended Word"),
         gr.inputs.Slider(minimum=0.0, maximum=5, default=2.1, step=0.01, label="Temperature"),
         gr.inputs.Slider(minimum=0.0, maximum=1, default=0.5, step=0.01, label="Top-p"),     
-        gr.inputs.Slider(minimum=1, maximum=20, default=3, step=1, label="num of sequance")
-
+        gr.inputs.Slider(minimum=1, maximum=20, default=3, step=1, label="num of sequance"
     ],
     outputs=gr.outputs.Textbox(label="Generated Output"),
     title="Question Generation and Answering",
     description="Select an example context, choose a recommended word, adjust temperature and top-p. The model will generate questions and answers.",
 )
-
 # Launch the interface
 iface.launch()