app.py

import json
import os
import gradio as gr

# Dictionary to store data for each difficulty
datasets = {}
difficulty_files = {
    "Easy": "data/scalar_easy.json",
    "Medium": "data/scalar_medium.json",
    "Hard": "data/scalar_hard.json"
}

# Load all json files
for difficulty, filepath in difficulty_files.items():
    with open(filepath) as f:
        datasets[difficulty] = json.load(f)

# Current state variables
current_index = 0
current_difficulty = "Easy"  # default difficulty
current_data = datasets[current_difficulty]

# Update display function with difficulty parameter
def update_display(index, difficulty=None):
    global current_index, current_difficulty, current_data
    
    # Update difficulty if provided
    if difficulty is not None and difficulty != current_difficulty:
        current_difficulty = difficulty
        current_data = datasets[difficulty]
        current_index = 0
        index = 0
    
    current_index = index
    item = current_data[current_index]
    
    # escape markdown but keep our color formatting
    question = item['question'].replace("<", "&lt;").replace(">", "&gt;")
    
    # Add styled background with rounded corners
    colored_question = question.replace(
        "[MASKED_CITATION]", 
        '<span style="background-color: #ffebeb; padding: 2px 6px; border-radius: 4px; color: blue;">[MASKED_CITATION]</span>'
    )
    
    # Format the citation dictionary with indentation
    formatted_citation = json.dumps(item["citation"], indent=4, ensure_ascii=False)
    return colored_question, formatted_citation, item["reference_id"], item['label_id'], index

def prev_item(difficulty):
    global current_index, current_data
    current_data = datasets[difficulty]
    current_index = (current_index - 1) % len(current_data)
    return update_display(current_index, difficulty)

def next_item(difficulty):
    global current_index, current_data
    current_data = datasets[difficulty]
    current_index = (current_index + 1) % len(current_data)
    return update_display(current_index, difficulty)

# Create Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("""
    ## Data viewer for [SCALAR](https://arxiv.org/abs/2502.13753/)
    * SCALAR (Scientific Citation-based Live Assessment of Long-context Academic Reasoning) is a novel benchmark that leverages academic papers and their citation networks, featuring automatic generation of high-quality ground truth labels without human annotation, controllable difficulty levels, and a dynamic updating mechanism that prevents data contamination.
    * The benchmark provides a reliable and sustainable way to track progress in long-context understanding as LLM capabilities evolve.
    """)
    with gr.Column():
        with gr.Row():
            
            # Display current index
            with gr.Column():

                # Add difficulty selector
                difficulty_dropdown = gr.Dropdown(
                    choices=list(difficulty_files.keys()),
                    value="Easy",
                    label="Difficulty Level"
                )

                index_slider = gr.Slider(minimum=0, maximum=len(datasets["Easy"]) - 1, step=1, label="Select Index", value=0)
                with gr.Row():
                    prev_btn = gr.Button("Previous")
                    next_btn = gr.Button("Next")
            
            # Display question and citation
            with gr.Column():
                citation_text = gr.TextArea(label="Citation", interactive=False)
                reference_id = gr.Textbox(label="Reference ID", interactive=False)
                label_id = gr.Textbox(label="Label ID", interactive=False)

        with gr.Row():
            question_md = gr.Markdown(label="Question")

    # Bind events
    difficulty_dropdown.change(
        fn=lambda d: gr.Slider(minimum=0, maximum=len(datasets[d]) - 1, step=1, value=0),
        inputs=[difficulty_dropdown],
        outputs=[index_slider]
    )
    
    index_slider.change(
        update_display,
        inputs=[index_slider, difficulty_dropdown],
        outputs=[question_md, citation_text, reference_id, label_id, index_slider]
    )
    
    prev_btn.click(
        prev_item,
        inputs=[difficulty_dropdown],
        outputs=[question_md, citation_text, reference_id, label_id, index_slider]
    )
    
    next_btn.click(
        next_item,
        inputs=[difficulty_dropdown],
        outputs=[question_md, citation_text, reference_id, label_id, index_slider]
    )

    # Initialize display
    demo.load(
        update_display,
        inputs=[index_slider, difficulty_dropdown],
        outputs=[question_md, citation_text, reference_id, label_id, index_slider]
    )

# Launch interface
demo.launch()