Create app.py

app.py

@@ -0,0 +1,128 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import torch
+
+# ==========================
+# 1. Load model from Hugging Face
+# ==========================
+
+MODEL_NAME = "angkor96/khmer-news-summarization"  # e.g., "Sedtha-019/khmer-summarization"
+
+print("Loading model and tokenizer...")
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
+
+# Move to GPU if available
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model = model.to(device)
+
+print(f"✅ Model loaded successfully on {device}!")
+
+# ==========================
+# 2. Summarization function
+# ==========================
+def summarize_khmer_text(text, max_length=150, min_length=40):
+    """
+    Summarize Khmer text
+    """
+    if not text or text.strip() == "":
+        return "⚠️ សូមបញ្ចូលអត្ថបទ / Please enter text"
+    
+    if len(text.strip()) < 20:
+        return "⚠️ អត្ថបទខ្លីពេក / Text is too short to summarize"
+    
+    try:
+        # Tokenize input
+        inputs = tokenizer(
+            text,
+            max_length=1024,
+            truncation=True,
+            padding="max_length",
+            return_tensors="pt"
+        ).to(device)
+        
+        # Generate summary
+        with torch.no_grad():
+            summary_ids = model.generate(
+                inputs["input_ids"],
+                max_length=max_length,
+                min_length=min_length,
+                length_penalty=2.0,
+                num_beams=4,
+                early_stopping=True,
+                no_repeat_ngram_size=3
+            )
+        
+        # Decode output
+        summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+        
+        return summary
+        
+    except Exception as e:
+        return f"❌ Error: {str(e)}"
+
+# ==========================
+# 3. Gradio UI
+# ==========================
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown(
+        """
+        # 🇰🇭 Khmer Text Summarization
+        ### បញ្ចូលអត្ថបទខ្មែរ ហើយទទួលបានការសង្ខេបដោយស្វ័យប្រវត្តិ
+        Enter Khmer text and get an automatic summary
+        """
+    )
+    
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.Textbox(
+                lines=10,
+                placeholder="បញ្ចូលអត្ថបទខ្មែរនៅទីនេះ...\nEnter Khmer text here...",
+                label="📝 អត្ថបទដើម / Original Text"
+            )
+            
+            with gr.Row():
+                max_len = gr.Slider(
+                    minimum=50,
+                    maximum=300,
+                    value=150,
+                    step=10,
+                    label="Maximum Summary Length"
+                )
+                min_len = gr.Slider(
+                    minimum=20,
+                    maximum=100,
+                    value=40,
+                    step=10,
+                    label="Minimum Summary Length"
+                )
+            
+            submit_btn = gr.Button("🔄 Summarize / សង្ខេប", variant="primary")
+        
+        with gr.Column():
+            output_text = gr.Textbox(
+                lines=10,
+                label="📋 សង្ខេប / Summary"
+            )
+    
+    # Examples
+    gr.Examples(
+        examples=[
+            ["ប្រទេសកម្ពុជាមានប្រវត្តិសាស្រ្តយូរលង់និងសម្បូរបែបដោយវប្បធម៌។ អាណាចក្រខ្មែរបានរីកចម្រើនក្នុងសតវត្សទី៩ដល់ទី១៥។ អង្គរវត្តជាស្នាដៃស្ថាបត្យកម្មដ៏អស្ចារ្យមួយរបស់ពិភពលោក។", 100, 30],
+            ["ការអប់រំជាមូលដ្ឋានគ្រឹះសំខាន់សម្រាប់ការអភិវឌ្ឍន៍ជាតិ។ សិស្សានុសិស្សគប្បីរៀនសូត្រយ៉ាងស្អិតរុំ។ គ្រូបង្រៀនមានតួនាទីសំខាន់ក្នុងការបង្កើតអនាគតកុមារ។", 80, 25],
+        ],
+        inputs=[input_text, max_len, min_len],
+    )
+    
+    # Connect button
+    submit_btn.click(
+        fn=summarize_khmer_text,
+        inputs=[input_text, max_len, min_len],
+        outputs=output_text
+    )
+
+# ==========================
+# 4. Launch
+# ==========================
+if __name__ == "__main__":
+    demo.launch(share=True)