added cache button

app.py

@@ -1,5 +1,4 @@
-import subprocess
-subprocess.check_call(["python", '-m', 'pip', 'install',"--upgrade", 'streamlit']) # upgrade pkg
+
 
 import streamlit as st
 import pandas as pd
@@ -35,7 +34,7 @@ model_classes ={
     13: "WiFi",
 }
 
-@st.cache
+@st.cache(suppress_st_warning=True)
 def load_t5():
     model = AutoModelForSeq2SeqLM.from_pretrained("t5-base")
 
@@ -43,23 +42,23 @@ def load_t5():
     return model, tokenizer
 
 
-@st.cache
+@st.cache(suppress_st_warning=True)
 def custom_model():
     return pipeline("summarization", model="my_awesome_sum/")
 
 
-@st.cache
+@st.cache(suppress_st_warning=True)
 def convert_df(df):
     # IMPORTANT: Cache the conversion to prevent computation on every rerun
     return df.to_csv(index=False).encode("utf-8")
 
 
-@st.cache
+@st.cache(suppress_st_warning=True)
 def load_one_line_summarizer(model):
     return model.load_model("t5", "snrspeaks/t5-one-line-summary")
 
 
-@st.cache
+@st.cache(suppress_st_warning=True)
 def classify_category():
     tokenizer = BertTokenizer.from_pretrained("bert-base-uncased")
     new_model = load_model("model")
@@ -75,16 +74,15 @@ summarizer_option = st.selectbox(
     ("Custom trained on the dataset", "t5-base", "t5-one-line-summary"),
 )
 classification = st.checkbox("Classify Category", value=True)
-hide_streamlit_style = """
-            <style>
-            #MainMenu {visibility: hidden;}
-            footer {visibility: hidden;}
-            </style>
-            """
-# st.markdown(hide_streamlit_style, unsafe_allow_html=True)
-st.write(st.__version__)
-st.write(pip.__version__)
+
 ps = st.empty()
+cache_button=st.empty()
+msg=st.empty()
+if cache_button.button("Clear"):
+    caching.clear_cache()
+    st.balloons()
+    msg.error("Cache is cleared, please reload to scrape new values")
+    
 if st.button("Process",type="primary"):
     cancel_button=st.empty()
     cancel_button2=st.empty()