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import gradio as gr | |
from Sample import * | |
display_dict, info_dict = sample_random_entry(n=1) | |
# Extract the question text | |
question_text = display_dict['qa'] | |
def markdown_to_html(markdown_text): | |
# You would use a Markdown library to convert markdown to HTML here | |
# Since this code runs in an environment without extra libraries, this is a placeholder | |
html = markdown_text.replace("\n", "<br>") # Simple replacement, not a real markdown conversion | |
return html | |
completion_text = '' | |
def evaluate_guess(reasoning, correctness, confidence): | |
# Placeholder for comparison logic | |
# You'll need to access the correct answer from `info_dict` or a similar structure | |
correct_answer = "Correctly" # Placeholder for the actual logic to determine this | |
evaluation_response = "Correct" if correctness == correct_answer else "Incorrect" | |
actual_model = info_dict['model'] | |
actual_completion = info_dict['completion'] | |
# Update the completion text | |
completion_text = f"Completion: {actual_completion}\n\nChoice: {chr(info_dict['verdict'] + 65)}" | |
model = actual_model | |
# Return the evaluation response and the completion text to update the interface | |
return evaluation_response, model, completion_text | |
print(display_dict['card']) | |
with gr.Blocks() as app: | |
with gr.Row(): | |
with gr.Column(scale=2): # This column is wider | |
# Use a Textbox to display the evaluation card content | |
evaluation_card = gr.Textbox(value=display_dict['card'], label="Evaluation Card", interactive=False) | |
model = gr.Textbox(value="", label="Model", placeholder='An anonymous Model', interactive=False) | |
completion = gr.Textbox(value="", label="Model's Completion", interactive=False) | |
with gr.Column(scale=1): | |
# Display the sampled question in a Textbox | |
question = gr.Textbox(value=question_text, label="Question", interactive=False) | |
reasoning = gr.Textbox(lines=5, placeholder="Your reasoning (optional)") | |
correctness = gr.Radio(choices=["Correct", "Incorrect"], label="I believe the model will answer this question") | |
confidence = gr.Slider(minimum=0, maximum=10, step=1, label="Confidence") | |
output_text = gr.Text(label="Evaluation Output") # Create an output text component | |
submit_button = gr.Button("Submit") | |
# This textbox will be used to display the model's completion | |
# When the button is clicked, it will update the content of the completion textbox | |
submit_button.click(fn=evaluate_guess, inputs=[reasoning, correctness, confidence], outputs=[output_text, model, completion]) | |
app.launch() |