Create app.py

app.py

@@ -0,0 +1,29 @@
+from transformers import pipeline
+import gradio as gr
+
+# Load the model once (global)
+pipe = pipeline("text-classification", model="Titeiiko/OTIS-Official-Spam-Model")
+
+def is_spam(input_text: str) -> dict:
+    """
+    Returns {"spam": bool, "label": str, "score": float}
+    """
+    result = pipe(input_text)[0]
+    is_spam_flag = result["label"] != "LABEL_0"
+    return {
+        "spam": is_spam_flag,
+        "label": result["label"],
+        "score": float(result["score"])
+    }
+
+# Gradio interface (for both API & UI)
+demo = gr.Interface(
+    fn=is_spam,
+    inputs=gr.Textbox(label="Enter text"),
+    outputs=gr.JSON(label="Result"),
+    title="Spam Detector API",
+    description="Detect spam using Hugging Face Transformers."
+)
+
+if __name__ == "__main__":
+    demo.launch()