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app.py

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+import gradio as gr
+from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
+
+# Load model & tokenizer from local directory
+model_path = "./khmer_lesson_model"
+
+model = AutoModelForCausalLM.from_pretrained(model_path, local_files_only=True)
+tokenizer = AutoTokenizer.from_pretrained(model_path, local_files_only=True)
+
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+def generate_lesson(grade, topic, level):
+    prompt = f"""Generate a Khmer math lesson plan.
+
+Grade: {grade}
+Topic: {topic}
+TaRL Level: {level}"""
+    output = pipe(prompt, max_new_tokens=200, do_sample=True, temperature=0.7)
+    return output[0]["generated_text"]
+
+iface = gr.Interface(
+    fn=generate_lesson,
+    inputs=[
+        gr.Dropdown(["1", "2", "3"], label="ថ្នាក់ (Grade)"),
+        gr.Dropdown(["Addition", "Subtraction", "Counting", "Number Recognition"], label="ប្រធានបទ (Topic)"),
+        gr.Dropdown(["Beginner", "Intermediate", "Advanced"], label="កម្រិត TaRL (TaRL Level)")
+    ],
+    outputs="text",
+    title="អ្នកជំនួយបង្កើតមេរៀនគណិតវិទ្យា (Khmer AI Math Assistant)",
+    description="ជ្រើសរើសថ្នាក់ ប្រធានបទ និងកម្រិតសិស្ស រួចចុចបង្កើតមេរៀន។"
+)
+
+iface.launch()

requirements.txt

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+transformers>=4.31
+gradio>=3.40
+torch