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23d6dd1 8c910e7 23d6dd1 c48ebf9 dade5ab 23a71da c48ebf9 23d6dd1 dade5ab 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 c48ebf9 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 c48ebf9 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 dade5ab 8c910e7 23d6dd1 c48ebf9 | 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 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 | import gradio as gr
import requests
import os
# Configure the endpoint and authentication
ENDPOINT_URL = os.environ.get("ENDPOINT_URL", "https://dz0eq6vxq3nm0uh7.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 "β οΈ Warning: HF_API_TOKEN is not configured. The app won't work until you add this secret in your Space settings."
return "β
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"β
{safety_result}"
# else:
# return f"β {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)}"
def check_safety(input_text, uploaded_image):
if not input_text.strip() and uploaded_image is None:
return "β οΈ Please enter text or upload an image to check."
payload = {}
if input_text.strip():
payload["inputs"] = input_text
if uploaded_image is not None:
# In Gradio, uploaded_image will be a local temp file path
# Your endpoint expects a URL or base64. Here, we send as base64.
import base64
with open(uploaded_image, "rb") as img_file:
img_bytes = img_file.read()
img_base64 = base64.b64encode(img_bytes).decode('utf-8')
payload["image"] = img_base64 # Assume your backend can accept image this way
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {HF_API_TOKEN}"
}
try:
response = requests.post(ENDPOINT_URL, json=payload, headers=headers, timeout=30)
if response.status_code == 200:
result = response.json()
is_safe = result.get("is_safe", False)
safety_result = result.get("safety_result", {})
safety = safety_result.get("Safety", "Unknown")
score = safety_result.get("Score", "")
categories = safety_result.get("Unsafe Categories", "")
if is_safe:
return f"β
Safe\n\nSafety: {safety}\nScore: {score}\nUnsafe Categories: {categories}"
else:
return f"β Unsafe\n\nSafety: {safety}\nScore: {score}\nUnsafe Categories: {categories}"
else:
return f"β Error: Request failed with status code {response.status_code}.\nDetails: {response.text}"
except requests.exceptions.Timeout:
return "β Error: Request timed out."
except requests.exceptions.ConnectionError:
return "β Error: Failed to connect to the endpoint."
except Exception as e:
return f"β Error: {str(e)}"
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")
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 and images 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
)
uploaded_image = gr.Image(
label="Upload Image to check",
type="filepath" # important: get local path
)
check_button = gr.Button("Check Safety", variant="primary")
with gr.Column():
output = gr.Textbox(
label="Safety Result",
lines=8
)
# Update event handlers
check_button.click(fn=check_safety, inputs=[input_text, uploaded_image], outputs=output)
input_text.submit(fn=check_safety, inputs=[input_text, uploaded_image], outputs=output)
gr.Examples(
[
["Hello, how are you today?", None],
["I want to learn how to make a bomb.", None],
["", "example_images/unsafe_meme.png"],
["", "example_images/normal_photo.jpg"],
],
inputs=[input_text, uploaded_image]
)
demo.launch()
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