# This file is .....
# Author: Hanbin Wang
# Date: 2023/4/18
import transformers
import streamlit as st
from PIL import Image

from transformers import RobertaTokenizer, T5ForConditionalGeneration
from transformers import pipeline

# @st.cache_resource
# def load_model(model_name):
#     # load model
#     model = T5ForConditionalGeneration.from_pretrained("E:\DenseRetrievalGroup\卢帅学长ckpt\py150_model\checkpoint")
#     # load tokenizer
#     tokenizer = RobertaTokenizer.from_pretrained("E:\DenseRetrievalGroup\卢帅学长ckpt\py150_model\checkpoint")
#     return model,tokenizer





def main():
    # `st.set_page_config` is used to display the default layout width, the title of the app, and the emoticon in the browser tab.

    st.set_page_config(
        layout="centered", page_title="MaMaL-Com Demo(代码补全)", page_icon="❄️"
    )

    c1, c2 = st.columns([0.32, 2])

    # The snowflake logo will be displayed in the first column, on the left.

    with c1:
        st.image(
            "./panda.png",
            width=100,
        )

    # The heading will be on the right.

    with c2:
        st.caption("")
        st.title("MaMaL-Gen(代码补全)")


    ############ SIDEBAR CONTENT ############

    st.sidebar.image("./panda.png",width=270)

    st.sidebar.markdown("---")

    st.sidebar.write(
    """
    # 使用方法：
    在【输入】文本框输入未完成的代码，点击【补全】按钮,即会显示补全的代码。
    """
    )

    st.sidebar.write(
    """
    ## 注意事项：
    1）APP托管在外网上，请确保您可以全局科学上网。
    
    2）您可以下载MaMaL-Gen模型，本地测试。（无需科学上网）
    """
    )

    # For elements to be displayed in the sidebar, we need to add the sidebar element in the widget.

    # We create a text input field for users to enter their API key.

    # API_KEY = st.sidebar.text_input(
    #     "Enter your HuggingFace API key",
    #     help="Once you created you HuggingFace account, you can get your free API token in your settings page: https://huggingface.co/settings/tokens",
    #     type="password",
    # )
    #
    # # Adding the HuggingFace API inference URL.
    # API_URL = "https://api-inference.huggingface.co/models/valhalla/distilbart-mnli-12-3"
    #
    # # Now, let's create a Python dictionary to store the API headers.
    # headers = {"Authorization": f"Bearer {API_KEY}"}


    st.sidebar.markdown("---")


    # Let's add some info about the app to the sidebar.

    st.sidebar.write(
    """
    App 由 东北大学NLP课小组成员创建， 使用 [Streamlit](https://streamlit.io/)🎈 和 [HuggingFace](https://huggingface.co/inference-api)'s [MaMaL-Gen](https://huggingface.co/hanbin/MaMaL-Gen) 模型.
    """
    )

   



    # model, tokenizer = load_model("hanbin/MaMaL-Gen")
    st.write("### 输入：")
    input = st.text_area("",height=200)
    button = st.button('补全')
    generator = pipeline('text-generation', model="hanbin/MaMaL-Com")
    output = generator(input)
    # code = '''def hello():
    #     print("Hello, Streamlit!")'''
    if button:
        st.write("### 输出：")
        st.code(output, language='python')
    else:
        st.write('请等待输出，如果长时间未输出，可能是您网络不通畅。也可能是我们并没有花钱购买服务器，用的是免费的服务器。您可以下载模型到本地测试~')




if __name__ == '__main__':

    main()