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import gradio as gr
import requests
import os
# Configure the endpoint and authentication
ENDPOINT_URL = os.environ.get("ENDPOINT_URL", "https://ggxihghat6yj6oti.us-east-1.aws.endpoints.huggingface.cloud")
# HF_API_TOKEN = os.environ.get("HF_API_TOKEN") # Get API token from environment variable
HF_API_TOKEN = os.environ.get("HF_API_TOKEN", "").strip() # Use strip() to remove extra whitespaces and newlines
# Check if the API token is configured
def is_token_configured():
if not HF_API_TOKEN:
return "⚠️ Warning: HF_API_TOKEN is not configured. The app won't work until you add this secret in your Space settings."
return "✅ API token is configured"
# Define the function to call your endpoint
def check_safety(input_text):
if not input_text.strip():
return "Please enter some text to check"
# Prepare the payload for your endpoint
payload = {
"inputs": input_text
}
# Set headers with authentication token
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {HF_API_TOKEN}"
}
try:
# Make the request to your endpoint
response = requests.post(ENDPOINT_URL, json=payload, headers=headers, timeout=30)
# Check if the request was successful
if response.status_code == 200:
result = response.json()
# Format the result based on your endpoint's response format
is_safe = result.get("is_safe", False)
safety_result = result.get("safety_result", "No result received")
if is_safe:
return f"✅ {safety_result}"
else:
return f"❌ {safety_result}"
else:
return f"Error: Request failed with status code {response.status_code}. Details: {response.text}"
except requests.exceptions.Timeout:
return "Error: Request timed out. The endpoint may be overloaded or unavailable."
except requests.exceptions.ConnectionError:
return "Error: Failed to connect to the endpoint. Please check the endpoint URL."
except Exception as e:
return f"Error: {str(e)}"
# Define the Gradio interface
with gr.Blocks(title="Safety Content Classifier", css="footer {display: none !important}") as demo:
gr.Markdown(f"# Safety Content Classifier")
gr.Markdown(f"## Connected to external safety model endpoint")
# Add token status indicator
token_status = gr.Markdown(is_token_configured())
with gr.Accordion("About this demo", open=False):
gr.Markdown("""
This demo uses an external API endpoint to classify text based on safety policies.
It checks content against the following categories:
- Harassment
- Dangerous Content
- Hate Speech
- Sexually Explicit Information
The model will respond with 'Safe' or 'Unsafe' followed by any violated categories.
""")
with gr.Row():
with gr.Column():
input_text = gr.Textbox(
label="Enter text to check",
placeholder="Type here...",
lines=5
)
check_button = gr.Button("Check Safety", variant="primary")
with gr.Column():
output = gr.Textbox(
label="Safety Result",
lines=5
)
# Set up event handlers
check_button.click(fn=check_safety, inputs=input_text, outputs=output)
input_text.submit(fn=check_safety, inputs=input_text, outputs=output)
# Example inputs
gr.Examples(
[
["Hello, how are you today?"],
["I love your work, it's amazing!"],
["I want to learn how to make a bomb."],
["I hate people from that country."],
["Let's meet for coffee and discuss the project."],
],
input_text
)
# Launch the app
demo.launch()
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