Update app.py

app.py

@@ -2,13 +2,54 @@ import streamlit as st
 import time
 import pandas as pd
 import io
-import zipfile
-from gliner import GLiNER
+from transformers import pipeline
 from streamlit_extras.stylable_container import stylable_container
 import plotly.express as px
+import zipfile
+from gliner import GLiNER
+
 import os
 from comet_ml import Experiment
 
+
+
+st.subheader("8-Named Entity Recognition Web App", divider = "red")
+st.link_button("DEMO APP by nlpblogs", "https://nlpblogs.com", type = "tertiary")
+
+expander = st.expander("**Important notes on the 8-Named Entity Recognition Web App**")
+expander.write('''
+    
+    **Named Entities:**
+    This 8-Named Entity Recognition Web App predicts eight (8) labels (“person”, “country”, “city”, “organization”, “date”, “money”, “percent value”, “position”). Results are presented in an easy-to-read table, visualized in an interactive tree map, pie chart, and bar chart, and are available for download along with a Glossary of tags.
+    
+    **How to Use:**
+    Type or paste your text and press Ctrl + Enter. Then, click the 'Results' button to extract and tag entities in your text data.
+    
+    **Usage Limits:**
+    Unlimited number of Result requests.
+ 
+    **Customization:**
+    To change the app's background color to white or black, click the three-dot menu on the right-hand side of your app, go to Settings and then Choose app theme, colors and fonts.
+    
+    **Technical issues:**
+    If your connection times out, please refresh the page or reopen the app's URL.
+    For any errors or inquiries, please contact us at [email protected]
+    
+''')
+
+
+with st.sidebar:
+    container = st.container(border=True)
+    container.write("**Named Entity Recognition (NER)** is the task of extracting and tagging entities in text data. Entities can be persons, organizations, locations, countries, products, events etc.")
+    
+   
+    
+    
+    
+st.subheader("Related NLP Web Apps", divider = "red")
+st.link_button("14-Named Entity Recognition Web App", "https://nlpblogs.com/shop/named-entity-recognition-ner/14-entity-ner-demo-app/", type = "primary")
+
+
 COMET_API_KEY = os.environ.get("COMET_API_KEY")
 COMET_WORKSPACE = os.environ.get("COMET_WORKSPACE")
 COMET_PROJECT_NAME = os.environ.get("COMET_PROJECT_NAME")
@@ -19,7 +60,17 @@ else:
     comet_initialized = False
     st.warning("Comet ML not initialized. Check environment variables.")
 
+    
+
 text = st.text_area("Type or paste your text below, and then press Ctrl + Enter", key='my_text_area')
+st.write("**Input text**: ", text)
+
+def clear_text():
+    st.session_state['my_text_area'] = ""
+
+st.button("Clear text", on_click=clear_text)
+
+st.divider()
 
 if st.button("Results"):
     with st.spinner("Wait for it...", show_time=True):