| # 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() |