Create app.py

app.py

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+import torch
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+# تحميل النموذج العربي
+model_name = "CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+labels = ["negative", "neutral", "positive"]
+
+# دالة تحليل المشاعر
+def analyze_arabic_sentiment(text):
+    if not text.strip():
+        return "الرجاء إدخال نص"
+
+    inputs = tokenizer(text, return_tensors="pt", truncation=True)
+    outputs = model(**inputs)
+    probs = torch.nn.functional.softmax(outputs.logits, dim=1)
+    label_id = torch.argmax(probs).item()
+    confidence = float(probs[0][label_id])
+
+    return f"التصنيف: {labels[label_id]}\nدرجة الثقة: {round(confidence, 3)}"
+
+# واجهة Gradio
+with gr.Blocks() as demo:
+    gr.Markdown("## 🔍 Arabic Sentiment Analyzer")
+    gr.Markdown("اكتب نصًا عربيًا وسيتم تحديد نوع المشاعر.")
+
+    text_input = gr.Textbox(label="النص")
+    text_output = gr.Textbox(label="النتيجة")
+
+    analyze_btn = gr.Button("تحليل")
+
+    analyze_btn.click(fn=analyze_arabic_sentiment, inputs=text_input, outputs=text_output)
+
+demo.launch()