Add application file

app.py

@@ -129,22 +129,9 @@ def remove_non_ascii(text):
 
 
 
-article_text = """
-## Affect/Emotion
-This category is concerned with how people feel or respond to emotions. It includes bodily sensations. Inner Experience described as pleasant or unpleasant. Sentences with words relating to emotions, feelings, affect, or mood. Sentences about avoiding, suppressing, getting rid of, or controlling emotions. Phrases that indicate an intense emotional response belong here: e.g., I can't stand it, it is unbearable, it is intolerable.
-
-## Cognition
-Statements that center on beliefs, thoughts, or cognitive reactions to situations. Includes judgments, assessments, or reflections on events or circumstances. Includes inferences and rules that don’t directly have to do with the self. Silently saying things to yourself would fall here, whereas if it was saying something *out loud*, it would be overt behavior. Blame, if not said *out loud* to a person, would be cognition, as it involves attributing the issue to someone. "Shoulds" and "musts" go here, (but may include additional categories).
-
-## Attention
-Sentences that discuss what people are focusing on or paying attention to, including awareness of emotions, thoughts, or sensations. Ability or inability to shift attention, and preoccupations that include phrases like worry or ruminate, e.g., I was worrying about x all day; I kept ruminating about the past.
-
-## Motivation
-Statements focusing on what drives actions or behaviors. Includes stating what one values, expressing the desire to achieve particular goals, or giving reasons for acting, such as compliance or values. Also about wishing or hoping for something, which implies value. Phrases about "not caring for *something*" relates to motivation. Sentences about wanting to give up or escape may also imply motivation, e.g., escaping an aversive or an absence of motivation.
-"""
+article_text = "Just a placeholder text"
 
 # Apply the function to your Markdown strings
-article = remove_non_ascii(article_text)
 
 txtbx = gr.Textbox(value = 'I would like to feel better', label = 'Please enter your item:', container = 'True')
 txtbxopt = gr.Textbox(label = 'The item you provided was classified as:', container = 'True')