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import gradio as gr
import pandas as pd
# Read source sentences and translations from an Excel file
excel_file = "demo.xlsx" # Path to your Excel file
df = pd.read_excel(excel_file)
# Assuming the Excel file has columns: "Source", "Translation_1", "Translation_2", ..., "Translation_5"
source_col = "Source Sentence"
translation_cols = [f"Translation_{i}" for i in range(1, 6)]
# Store the result scores after evaluation
#result_columns = ['Source', 'Translation', 'Accuracy', 'Fluency', 'Overall']
result_columns = ['Source', 'Translation', 'Rating']
# Function to simulate the rating collection and return scores
def evaluate_translations(*ratings):
# Initialize lists to store results for all translations
sources = []
translations = []
#accuracy_ratings = []
#fluency_ratings = []
overall_ratings = []
name = ratings[0]
for item in ratings:
if type(item)==int:
overall_ratings.append(item)
for idx, row in df.iterrows():
source = row[source_col]
translations_list = [row[translation_col] for translation_col in translation_cols]
# Collect ratings for each translation
for i, translation in enumerate(translations_list):
sources.append(source)
translations.append(translation)
# Store the results in a DataFrame
results_df = pd.DataFrame({
'Source': sources,
'Translation': translations,
#'Accuracy': accuracy_ratings,
#'Fluency': fluency_ratings,
'Overall': overall_ratings
})
# Save the result to an Excel file
filename = name+"_evaluation_results.xlsx"
results_df.to_excel(filename, index=False)
return "Evaluation complete. Results have been saved to" + filename + "."
# Function to create the input sliders dynamically for each translation
def get_inputs():
inputs = []
inputs.append(gr.Textbox(label="User Name :", interactive=True))
for idx, row in df.iterrows():
source = row[source_col]
translations_list = [row[translation_col] for translation_col in translation_cols]
# Source sentence display (non-editable)
inputs.append(gr.Textbox(value=source, label=f"Source Sentence {idx+1}", interactive=False))
# Add 3 sliders for each translation (accuracy, fluency, overall)
for i, translation in enumerate(translations_list):
with gr.Row():
inputs.append(gr.Textbox(value=translation, label=f"Translation {i+1}"))
#inputs.append(gr.Slider(minimum=1, maximum=5, step=1, label=f"Accuracy (Translation {i+1})"))
#inputs.append(gr.Slider(minimum=1, maximum=5, step=1, label=f"Fluency (Translation {i+1})"))
inputs.append(gr.Slider(minimum=1, maximum=5, step=1, label=f"Rating (Translation {i+1})"))
return inputs
# Define the Gradio interface outputs
def get_outputs():
return gr.Textbox(label="Evaluation Status")
# Create the Gradio interface
with gr.Blocks() as demo:
# Inputs
inputs = get_inputs()
# Outputs
output = get_outputs()
# Add a Submit Button
submit_button = gr.Button("Submit Evaluation")
# Bind the button to the evaluation function
submit_button.click(evaluate_translations, inputs=inputs, outputs=output)
# Launch the interface
demo.launch()
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