Update app.py

app.py

@@ -87,12 +87,12 @@ def bansum(text):
 def main():
     import streamlit as st
     import time
-    if "photo" not in st.session_state:
-        st.session_state["photo"]="not done"
-    def change_photo_state():
-        st.session_state["photo"]="done"
-    c1, c2, c3 = st.columns([2,2,1])
-    if st.checkbox("Summarize from text/images/pdfs"):
+    if st.checkbox("Summarize"):
+        if "photo" not in st.session_state:
+            st.session_state["photo"]="not done"
+        def change_photo_state():
+            st.session_state["photo"]="done"
+        c1, c2, c3 = st.columns([2,2,1])
         with st.container():
             message = c1.text_input("Type your text here!")
             uploaded_photo=None
@@ -102,8 +102,10 @@ def main():
                 if c2.button("Stop camera"):
                     CaptureImage =False
             if c3.button("Upload Images/PDFs"):
-                time.sleep(3)
                 uploaded_photo = c3.file_uploader("Upload your Images/PDF",type=['jpg','png','jpeg','pdf'], on_change=change_photo_state)
+                global Summarize
+                Summarize=True
+                time.sleep(3)
             if st.session_state["photo"]=="done" or message:
                 if uploaded_photo and uploaded_photo.type=='application/pdf':
                     tet = read_pdf(uploaded_photo)
@@ -132,12 +134,11 @@ def main():
                     img = img.save("img.png")
                     img = cv2.imread("img.png")
                     st.text("Select the summarization type:")
-                    c4, c5 = st.columns([1,1])
-                    if c4.button("BENGALI"):
+                    if st.button("BENGALI"):
                         text =  pytesseract.image_to_string(img, lang="ben")
                         st.subheader("সারাংশ/সারমর্ম")
                         bansum(text)
-                    if c5.button("ENGLISH"): 
+                    if st.button("ENGLISH"): 
                         text=pytesseract.image_to_string(img)
                         st.subheader("Summarized Text")
                         engsum(text)
@@ -149,24 +150,23 @@ def main():
                     img = cv2.imread("img.png")
                     #text = pytesseract.image_to_string(img) if st.checkbox("Bangla") else pytesseract.image_to_string(img, lang="ben")
                     st.text("Select the summarization type:")
-                    c6, c7 = st.columns([1,1])
-                    if c6.button("Bangla"):
+                    if st.button("Bangla"):
                         text =  pytesseract.image_to_string(img, lang="ben")
                         st.subheader("সারাংশ/সারমর্ম")
                         bansum(text)
-                    if c7.button("English"): 
+                    if st.button("English"): 
                         text=pytesseract.image_to_string(img)
                         st.subheader("Summarized Text")
                         engsum(text)
                 else:
                     text=None
                     text = message
-                    c8, c9 = st.columns([1,1])
-                    if c8.button("Bangla"):
+                    if st.button("Bangla"):
                         bansum(text)
-                    if c9.button("English"): 
+                    if st.button("English"): 
                         engsum(text) 
     if st.checkbox("Conversate"):         
+        Summarize=False
         with st.container():
             from streamlit_chat import message as st_message
             from transformers import BlenderbotTokenizer