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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
# Load Hugging Face token from environment variable
HF_TOKEN = os.getenv("HF_TOKEN", "your_default_hf_token")
def get_dynamic_endpoint():
"""
Fetch the dynamic endpoint using the Hugging Face API.
Returns:
str: The current dynamic endpoint.
"""
api_url = "https://api.huggingface.co/space/duchaba/friendly-text-moderation"
headers = {"Authorization": f"Bearer {HF_TOKEN}"}
response = requests.get(api_url, headers=headers)
response.raise_for_status() # Raise an error for bad status codes
# Extract the endpoint from the response
data = response.json()
endpoint = data.get("url")
return endpoint
# Fetch the dynamic endpoint
dynamic_endpoint = get_dynamic_endpoint()
# Initialize the client with the dynamic endpoint
client = Client(dynamic_endpoint, hf_token=HF_TOKEN)
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.
"""
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
# 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()
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