app.py

import gradio as gr
from typing import List

def prepare_input(question: str):
    inputs = f"{prompt} {question}"
    input_ids = tokenizer(inputs, max_length=700, return_tensors="pt").input_ids
    return input_ids

def inference(question: str) -> str:
    input_data = prepare_input(question=question)
    input_data = input_data.to(model.device)
    outputs = model.generate(inputs=input_data, num_beams=10, top_k=10, max_length=1024)

    result = tokenizer.decode(token_ids=outputs[0], skip_special_tokens=True)

    # print("question:", question, "answer:", result)
    return result

# test_id = 1160
# # 거실조명1 꺼주세요	"Home:거실,NickName:조명1,ActionID:1061,Value:없음"
# print("model result:", inference(dataset_finetuning["train"][test_id]["Q"]))
# print("real result:", dataset_finetuning["train"][test_id]["C"])
print(inference("거실 조명1 꺼주세요"))

gr.load("models/yeye776/t5-OndeviceAI-HomeIoT").launch()
# iface = gradio.Interface(fn=pipe_home, inputs="text", outputs="text")
# iface.launch()