First Commit

app.py

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+import streamlit as st
+from streamlit_tags import st_tags, st_tags_sidebar
+from keytotext import pipeline
+from PIL import Image
+
+############
+## Main page
+############
+st.write("# Code for Keywords to Text")
+
+st.markdown("***Idea is to build a model which will take keywords as inputs and generate sentences as outputs.***")
+image = Image.open('1.png')
+st.image(image)
+        
+st.sidebar.write("# Parameter Selection")
+maxtags_sidebar = st.sidebar.slider('Number of tags allowed?', 1, 10, 3, key='ehikwegrjifbwreuk')
+keywords = st_tags(
+    label='# Enter Keywords:',
+    text='Press enter to add more',
+    value=['Summer', 'Shoes', 'Sports'],
+    suggestions=['five', 'six', 'seven', 'eight', 'nine', 'three', 'eleven', 'ten', 'four'],
+    maxtags=maxtags_sidebar,
+    key="aljnf")
+
+# Add selectbox in streamlit
+option = st.sidebar.selectbox(
+     'Which model would you like to be selected?',
+     ('k2t', 'k2t-base', 'mrm8488/t5-base-finetuned-common_gen'))
+
+#if st.sidebar.button('Load Model'):
+#    nlp=pipeline(option)
+#    st.sidebar.success("Load Successfully!")
+nlp=pipeline(option)
+st.sidebar.success("Load Successfully!")
+
+st.write("## Results:")
+if st.button('Generate Text'):
+    out=nlp(keywords)
+    st.success(out)