app.py

import gradio as gr
import pandas as pd
import random

df = pd.read_csv('data.csv')


models = df.columns.tolist()
print(models)
models.remove('hash')
models.remove('message')
messages = sorted(df['message'].tolist(), key=len)
messages_select = [(m[:150],m) for m in messages]

def out(message, model1, model2):
    row = df[df['message'] == message]
    output1 = row[model1].values[0]
    output2 = row[model2].values[0]
    return message, output1, output2


with gr.Blocks() as iface:
    gr.Markdown("For information about the used dataset and generation see the [README.md](https://huggingface.co/spaces/floleuerer/german_llm_outputs/blob/main/README.md)")
    with gr.Row():
        drop_message = gr.Dropdown(messages_select, label='Prompt', value=random.choice(messages))
    with gr.Row():
        drop_model1 = gr.Dropdown(models, label='Model 1', value=random.choice(models))
        drop_model2 = gr.Dropdown(models, label='Model 2', value=random.choice(models))
    with gr.Row():
        btn = gr.Button("Show Outputs")
    with gr.Row():
        out_message = gr.TextArea(label='Prompt')
    with gr.Row():
        out_model1 = gr.TextArea(label='Output Model 1')
        out_model2 = gr.TextArea(label='Output Model 2')

    btn.click(out,
    inputs=[drop_message, drop_model1, drop_model2],
    outputs=[out_message, out_model1, out_model2])

iface.launch()