Create app.py

app.py

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+import streamlit as st
+import requests
+from io import BytesIO
+
+# Hugging Face Inference API URL and Token
+API_URL = "https://api-inference.huggingface.co/models/Organika/sdxl-detector"
+API_TOKEN = st.secrets["HF_API_TOKEN"]  # You'll store this in the Hugging Face secret
+
+headers = {"Authorization": f"Bearer {API_TOKEN}"}
+
+def query(image_bytes):
+    response = requests.post(API_URL, headers=headers, files={"inputs": image_bytes})
+    return response.json()
+
+# Streamlit UI
+st.title("AI Image Detector")
+
+st.write("Upload an image, and we will check if it is AI-generated using the Hugging Face SDXL detector.")
+
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Display the uploaded image
+    image = uploaded_file.read()
+    st.image(image, caption="Uploaded Image", use_column_width=True)
+    
+    st.write("Classifying...")
+    
+    # Send the image to the model
+    result = query(image)
+    
+    # Display the result
+    if "error" in result:
+        st.error(f"Error: {result['error']}")
+    else:
+        label = result[0]["label"]
+        if label == "AI-generated":
+            st.success("This image is AI-generated.")
+        else:
+            st.success("This image is not AI-generated.")