app.py

"""
Myanmar LLM Gradio App - Lite Version
Model: amkyawdev/mm-llm-tiny
"""

import gradio as gr
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

MODEL_NAME = "amkyawdev/mm-llm-tiny"

print(f"Loading {MODEL_NAME}...")

# Load tokenizer only first (saves memory)
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
tokenizer.pad_token = tokenizer.eos_token

# Model loads on first request (lazy load)
model = None

def get_model():
    global model
    if model is None:
        print("Loading model...")
        model = AutoModelForCausalLM.from_pretrained(
            MODEL_NAME,
            torch_dtype=torch.float32,
            low_cpu_mem_usage=True
        )
        model.eval()
        print("Model loaded!")
    return model

def generate(prompt, max_tokens=128, temp=0.7):
    m = get_model()
    
    inputs = tokenizer(prompt, return_tensors="pt", truncation=True, max_length=256)
    
    with torch.no_grad():
        outputs = m.generate(
            **inputs,
            max_new_tokens=int(max_tokens),
            temperature=temp,
            do_sample=temp > 0,
        )
    
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return response[len(prompt):].strip()

# UI
with gr.Blocks(title="Myanmar LLM") as app:
    gr.Markdown("# 🇲🇲 Myanmar LLM")
    gr.Markdown("Model: **amkyawdev/mm-llm-tiny**")
    
    with gr.Row():
        msg = gr.Textbox(label="Message", placeholder="မေးခွန်းရေးသားပါ။...")
        output = gr.Textbox(label="Response")
    
    with gr.Row():
        max_tokens = gr.Slider(32, 256, value=128, step=16, label="Max Tokens")
        temp = gr.Slider(0.1, 1.0, value=0.7, label="Temperature")
    
    btn = gr.Button("Generate")
    
    btn.click(
        generate,
        inputs=[msg, max_tokens, temp],
        outputs=output
    )
    
    gr.Examples(
        examples=[
            ["Hello မြန်မာလို ပြန်ပါ။", 64, 0.7],
            ["Python နဲ့ list ရေးပါ။", 128, 0.7],
        ],
        inputs=[msg, max_tokens, temp]
    )

app.launch(share=True)