Add AI text detector Gradio app

README.md

@@ -1,12 +1,16 @@
 ---
-title: Ai Detector
-emoji: 🐢
-colorFrom: indigo
-colorTo: blue
+title: AI Text Detector
+emoji: 🔍
+colorFrom: blue
+colorTo: indigo
 sdk: gradio
-sdk_version: 6.10.0
+sdk_version: 5.29.0
 app_file: app.py
 pinned: false
+license: apache-2.0
+models:
+- adaptive-classifier/ai-detector
+datasets:
+- pangram/editlens_iclr
+short_description: Detect AI-generated text using adaptive-classifier
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,48 @@
+"""HuggingFace Space for AI text detection using adaptive-classifier."""
+
+import gradio as gr
+from adaptive_classifier import AdaptiveClassifier
+
+# Load model once at startup
+print("Loading model...")
+classifier = AdaptiveClassifier.from_pretrained(
+    "adaptive-classifier/ai-detector", use_onnx=False
+)
+print("Model loaded!")
+
+
+def detect(text: str) -> dict:
+    """Classify text as human-written or AI-generated."""
+    if not text or len(text.strip()) < 20:
+        return {"error": "Please enter at least a few sentences of text."}
+
+    predictions = classifier.predict(text, k=2)
+    return {label: round(score, 4) for label, score in predictions}
+
+
+demo = gr.Interface(
+    fn=detect,
+    inputs=gr.Textbox(
+        lines=10,
+        placeholder="Paste text here to check if it's human-written or AI-generated...",
+        label="Input Text",
+    ),
+    outputs=gr.Label(num_top_classes=2, label="Prediction"),
+    title="AI Text Detector",
+    description=(
+        "Detects whether text is **human-written** or **AI-generated/edited**. "
+        "Built with [adaptive-classifier](https://github.com/codelion/adaptive-classifier) "
+        "using frozen [RADAR](https://huggingface.co/TrustSafeAI/RADAR-Vicuna-7B) embeddings, "
+        "trained on the [EditLens](https://huggingface.co/datasets/pangram/editlens_iclr) dataset. "
+        "Works best with 50+ words."
+    ),
+    examples=[
+        ["The quick brown fox jumps over the lazy dog. I went to the store yesterday and forgot my wallet, which was pretty embarrassing. Had to ask the cashier to hold my stuff while I ran back to the car."],
+        ["The implementation leverages a novel approach to address the fundamental challenges inherent in modern natural language processing systems. By utilizing advanced transformer architectures, we demonstrate significant improvements across multiple benchmark datasets."],
+    ],
+    cache_examples=False,
+    api_name="detect",
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,2 @@
+adaptive-classifier>=0.1.2
+gradio>=4.0.0