app.py

import gradio as gr

# Define the 44 BFI questions
questions = [
    "1. Talks a lot",
    "2. Notices other people’s weak points",
    "3. Does things carefully and completely",
    "4. Is sad, depressed",
    "5. Is original, comes up with new ideas",
    "6. Keeps their thoughts to themselves",
    "7. Is helpful and not selfish with others",
    "8. Can be kind of careless",
    "9. Is relaxed, handles stress well",
    "10. Is curious about lots of different things",
    "11. Has a lot of energy",
    "12. Starts arguments with others",
    "13. Is a good, hard worker",
    "14. Can be tense; not always easy going",
    "15. Clever; thinks a lot",
    "16. Makes things exciting",
    "17. Forgives others easily",
    "18. Isn’t very organized",
    "19. Worries a lot",
    "20. Has a good, active imagination",
    "21. Tends to be quiet",
    "22. Usually trusts people",
    "23. Tends to be lazy",
    "24. Doesn’t get upset easily; steady",
    "25. Is creative and inventive",
    "26. Has a good, strong personality",
    "27. Can be cold and distant with others",
    "28. Keeps working until things are done",
    "29. Can be moody",
    "30. Likes artistic and creative experiences",
    "31. Is kind of shy",
    "32. Kind and considerate to almost everyone",
    "33. Does things quickly and carefully",
    "34. Stays calm in difficult situations",
    "35. Likes work that is the same every time",
    "36. Is outgoing; likes to be with people",
    "37. Is sometimes rude to others",
    "38. Makes plans and sticks to them",
    "39. Get nervous easily",
    "40. Likes to think and play with ideas",
    "41. Doesn’t like artistic things (plays, music)",
    "42. Likes to cooperate; goes along with others",
    "43. Has trouble paying attention",
    "44. Knows a lot about art, music and books"
]

# Scoring function based on the provided SPSS syntax
def compute_bfi_scores(*args):
    responses = list(args)
    # Convert 'No response' to None, else to int
    processed = []
    for r in responses:
        if r == "No response":
            processed.append(None)
        else:
            processed.append(int(r))
    
    # Define traits with their respective items and scoring parameters
    traits = {
        'Extraversion': {
            'positive': [1, 11, 16, 26, 36],
            'reverse': [6, 21, 31],
            'threshold': 1,
            'formula_pos_mult': 5,
            'formula_reverse_mult': 3,
            'formula_reverse_const': 12
        },
        'Agreeableness': {
            'positive': [7, 17, 22, 32, 42],
            'reverse': [2, 12, 27, 37],
            'threshold': 1,
            'formula_pos_mult': 5,
            'formula_reverse_mult':4,
            'formula_reverse_const':16
        },
        'Conscientiousness': {
            'positive': [3, 13, 28, 33, 38],
            'reverse': [8, 18, 23, 43],
            'threshold': 1,
            'formula_pos_mult':5,
            'formula_reverse_mult':4,
            'formula_reverse_const':16
        },
        'Neuroticism':{
            'positive':[4, 14, 19, 29, 39],
            'reverse':[9, 24, 34],
            'threshold':1,
            'formula_pos_mult':5,
            'formula_reverse_mult':3,
            'formula_reverse_const':12
        },
        'Openness':{
            'positive':[5, 10, 15, 20, 25, 30, 40, 44],
            'reverse':[35, 41],
            'threshold':2,
            'formula_pos_mult':8,
            'formula_reverse_mult':2,
            'formula_reverse_const':8
        }
    }

    scores = {}

    for trait, info in traits.items():
        pos_items = [processed[i-1] for i in info['positive']]
        rev_items = [processed[i-1] for i in info['reverse']]

        missing_pos = pos_items.count(None)
        missing_rev = rev_items.count(None)
        total_missing = missing_pos + missing_rev

        if total_missing > info['threshold']:
            scores[trait] = "Incomplete"
        else:
            # Compute means, ignoring None
            pos_values = [x for x in pos_items if x is not None]
            rev_values = [x for x in rev_items if x is not None]

            mean_pos = sum(pos_values) / len(pos_values) if pos_values else 0
            mean_rev = sum(rev_values) / len(rev_values) if rev_values else 0

            # Apply the scoring formula
            score = (mean_pos * info['formula_pos_mult']) + (info['formula_reverse_const'] - (mean_rev * info['formula_reverse_mult']))
            score = round(score, 2)
            scores[trait] = score

    # Prepare the output in Markdown format
    output = "## Your Big Five Personality Traits Scores\n\n"
    for trait, score in scores.items():
        output += f"**{trait}**: {score}\n\n"

    return output

# Create the Gradio interface
def create_interface():
    with gr.Blocks() as demo:
        gr.Markdown("## Big Five Inventory (BFI) Quiz")
        gr.Markdown("Please rate the following statements on a scale from **1 (Disagree a lot)** to **5 (Agree a lot)**. If you prefer not to respond to a particular statement, select **'No response'**.")

        # Create a grid layout for better organization
        with gr.Column():
            dropdowns = []
            for q in questions:
                dropdown = gr.Dropdown(
                    choices=["No response", 1, 2, 3, 4, 5],
                    label=q,
                    value="No response"
                )
                dropdowns.append(dropdown)
        
        # Submit button
        submit_btn = gr.Button("Submit")
        
        # Results display
        result = gr.Markdown()
        
        # Link the button to the function
        submit_btn.click(fn=compute_bfi_scores, inputs=dropdowns, outputs=result)

    return demo

# Launch the interface
demo = create_interface()
demo.launch()