Update app.py

app.py

@@ -1,22 +1,43 @@
 import gradio as gr
-from transformers import pipeline
 import os
+import sys
+import subprocess
 
-# 1. Load the classifier from your Hugging Face Repo
-# This replaces the /content/drive path
-model_repo = "MakD1227/afriberta-hsd-model"
-classifier = pipeline("text-classification", model=model_repo)
+# ---- SAFETY: ensure transformers is installed ----
+try:
+    from transformers import pipeline
+except ModuleNotFoundError:
+    subprocess.check_call(
+        [sys.executable, "-m", "pip", "install", "transformers", "torch", "sentencepiece"]
+    )
+    from transformers import pipeline
+
+# 1. Load the classifier from Hugging Face Hub
+MODEL_REPO = "MakD1227/afriberta-hsd-model"
+
+classifier = pipeline(
+    task="text-classification",
+    model=MODEL_REPO,
+    tokenizer=MODEL_REPO
+)
 
 # 2. Prediction function
-def predict_speech(text): 
+def predict_speech(text):
+    if not text or not text.strip():
+        return "Free (Neutral)", "0.00%"
+
     results = classifier(text)
-    # Mapping: LABEL_0 -> Free, LABEL_1 -> Offensive, LABEL_2 -> Hate
-    label_map = {"LABEL_0": "Free (Neutral)", "LABEL_1": "Offensive", "LABEL_2": "Hate"}
 
-    label = results[0]['label']
-    score = results[0]['score']
+    label_map = {
+        "LABEL_0": "Free (Neutral)",
+        "LABEL_1": "Offensive",
+        "LABEL_2": "Hate"
+    }
+
+    label = results[0]["label"]
+    score = results[0]["score"]
 
-    return label_map.get(label, label), f"{round(score * 100, 2)}%"
+    return label_map.get(label, label), f"{score * 100:.2f}%"
 
 # 3. Gradio Interface
 interface = gr.Interface(
@@ -32,13 +53,17 @@ interface = gr.Interface(
     ],
     title="Amharic & Afan Oromo Hate Speech Detector",
     description="Classify text into Free, Offensive, or Hate Speech",
-    article="<p style='text-align: center;'>@2025 Mequanent Degu Belete </p><p style='text-align: center;'>mekuanentde@gmail.com</p><p style='text-align: center;'>SNHCC, Academia Sinica, Taiwan</p>",
+    article="""
+    <p style='text-align:center;'>© 2025 Mequanent Degu Belete</p>
+    <p style='text-align:center;'>mekuanentde@gmail.com</p>
+    <p style='text-align:center;'>SNHCC, Academia Sinica, Taiwan</p>
+    """,
     examples=[
         ["ኢትዮጵያ ለዘላለም ትኑር"],
         ["haatee sali shamtuu situ nuu beekaa waa ee baalee"]
     ]
 )
 
-# Launch (No 'share=True' needed on Hugging Face Spaces)
+# 4. Launch
 if __name__ == "__main__":
-    interface.launch()
+    interface.launch()