Spaces:
Sleeping
Sleeping
File size: 2,367 Bytes
1277029 809b1fe ad77051 f76e239 809b1fe 1277029 c541f5d 1277029 ad77051 1277029 e0e8a14 ad77051 e0e8a14 ad77051 e0e8a14 ad77051 e0e8a14 f76e239 e0e8a14 ad77051 1277029 ad77051 1277029 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 |
import os
import requests
import gradio as gr
from gradio_client import Client
import matplotlib.pyplot as plt
import io
from PIL import Image
import base64
# Fetch the dynamic endpoint
dynamic_endpoint = "https://duchaba-friendly-text-moderation.hf.space/api/predict"
def moderate_text(text, safer_value):
"""
Moderates the given text using the Hugging Face API and returns the result and moderation pie chart.
Args:
text (str): The text to be moderated.
safer_value (float): The safer value for text moderation.
Returns:
result (dict): The moderation result.
img (PIL.Image): The moderation pie chart.
"""
try:
result = client.predict(
text,
safer_value,
api_name="/censor_me"
)
# Example structure of the result
base64_data = result.get('plot', '').split(',')[1]
# Decode base64 to bytes
img_data = base64.b64decode(base64_data)
# Convert bytes to PIL Image
img = Image.open(io.BytesIO(img_data))
return result, img
except Exception as e:
print(f"Error during moderation: {e}")
return {"error": "Failed to moderate text"}, None
# Define the Gradio interface
demo = gr.Interface(
fn=moderate_text,
inputs=[
gr.Textbox(label="Enter Text:", placeholder="Type your text here...", lines=5),
gr.Slider(minimum=0.005, maximum=0.1, value=0.005, label="Personalize Safer Value: (larger value is less safe)")
],
outputs=[
gr.Textbox(label="Moderated Text:", lines=5),
gr.Image(type="pil", label="Moderation Pie Chart")
],
title="Friendly Text Moderator",
description="Enter text to be moderated and adjust the safer value to see how it affects the moderation.",
theme="compact"
)
# Customize the CSS
custom_css = """
body {
background-color: #f5f5f5;
font-family: Arial, sans-serif;
}
.gradio-container {
max-width: 800px;
margin: auto;
padding: 20px;
background-color: white;
border: 1px solid #ddd;
border-radius: 8px;
box-shadow: 0 2px 10px rgba(0, 0, 0, 0.1);
}
.gr-button {
background-color: #4CAF50;
color: white;
}
.gr-button:hover {
background-color: #45a049;
}
"""
# Add the custom CSS to the Gradio app
demo.css = custom_css
# Launch the app
demo.launch() |