Update app.py

app.py

@@ -25,7 +25,7 @@ def strip_diacritics(s: str):
     return DIACRITICS.sub("", s)
 
 def normalize_arabic(s: str):
-    return re.sub("[\u0622\u0623\u0625]", "ا", strip_diacritics(s)).replace("ى","ي").replace("ة","ه")
+    return re.sub("[\u0622\u0623\u0625]", "ا", strip_diacritics(s)).replace("ى", "ي").replace("ة", "ه")
 
 def split_sentences(text: str):
     return [p.strip() for p in SENT_SEP.split(text) if p.strip()]
@@ -40,7 +40,7 @@ def compute_metrics(ar_text: str) -> Dict[str, float]:
     text_norm = normalize_arabic(ar_text)
     sents = split_sentences(text_norm)
     words = tokenize_words(text_norm)
-    n_sents, n_words = max(len(sents),1), max(len(words),1)
+    n_sents, n_words = max(len(sents), 1), max(len(words), 1)
     diff_count = sum(1 for w in words if difficult_word(w))
     try:
         osman = float(textstat.osman(ar_text))
@@ -52,10 +52,10 @@ def compute_metrics(ar_text: str) -> Dict[str, float]:
         "Word count": n_words,
         "Sentence count": n_sents,
         "Character count": n_chars,
-        "OSMAN_Score": round(osman,3),
+        "OSMAN_Score": round(osman, 3),
         "ARI_ArScore": ari_ar_score,
         "Difficult_Words_Count": diff_count,
-        "Average_Sentence_Length_in_Words": round(n_words/n_sents,3)
+        "Average_Sentence_Length_in_Words": round(n_words / n_sents, 3),
     }
 
 # =======================
@@ -63,4 +63,27 @@ def compute_metrics(ar_text: str) -> Dict[str, float]:
 # =======================
 def analyze_text(text):
     inputs = tokenizer(text, return_tensors="pt", truncation=True, padding=True, max_length=128)
-    w
+    with torch.no_grad():
+        outputs = model(**inputs)
+        probs = torch.nn.functional.softmax(outputs.logits, dim=-1)
+        label_id = torch.argmax(probs, dim=1).item()
+    label_map = {0: "سهل", 1: "متوسط", 2: "صعب"}
+    label = label_map[label_id]
+    stats = compute_metrics(text)
+    return {"Predicted_Label": label, **stats}
+
+# =======================
+# واجهة Gradio
+# =======================
+demo = gr.Interface(
+    fn=analyze_text,
+    inputs=gr.Textbox(label="أدخل النص العربي هنا", lines=6, placeholder="اكتب النص هنا..."),
+    outputs=gr.JSON(label="نتائج التحليل"),
+    title="Arabic Readability Analyzer",
+    description="أداة ذكية لتقييم مقروئية النصوص العربية باستخدام نموذج AraBERT.",
+)
+
+# =======================
+# تشغيل التطبيق (بدون share=True)
+# =======================
+demo.launch()