app.py

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 "⚠️ 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"


def check_safety(input_text, uploaded_image):
    if not input_text.strip() and uploaded_image is None:
        return "⚠️ 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"✅ Safe\n\nSafety: {safety}\nScore: {score}\nUnsafe Categories: {categories}"
            else:
                return f"❌ Unsafe\n\nSafety: {safety}\nScore: {score}\nUnsafe Categories: {categories}"
        
        else:
            return f"❗ Error: Request failed with status code {response.status_code}.\nDetails: {response.text}"
    
    except requests.exceptions.Timeout:
        return "❗ Error: Request timed out."
    
    except requests.exceptions.ConnectionError:
        return "❗ Error: Failed to connect to the endpoint."
    
    except Exception as e:
        return f"❗ 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()