Update app.py

app.py

@@ -1,49 +1,50 @@
-import streamlit as st
-from transformers import pipeline
-from PyPDF2 import PdfReader
-import PyPDF2
-import fitz
-import os
-import nltk
-
-
-def get_pdf_text(pdf_docs):
-    text = ""
-    for pdf in pdf_docs:
-        pdf_reader = PdfReader(pdf)
-        for page in pdf_reader.pages:
-            text += page.extract_text()
-    return text
-
-def main():
-    st.title('Question Generator from PDFs')
-    pipe = pipeline(
-        task = 'text2text-generation',
-        model = 'ramsrigouthamg/t5_squad_v1'
-    )
-    file = st.file_uploader(label='Upload',accept_multiple_files=True)
-    pr = st.button(label='Start')
-    if pr:
-        st.write('Hi')
-        raw_text = get_pdf_text(file)
-        sentences = nltk.sent_tokenize(text=raw_text)
-        # st.write(sts)
-        # for i in sentences:
-        #     st.write(i)
-        questions = []
-        st.subheader("Generated Questions are: ")
-        s = pipe(sentences)
-        for i in s:
-            questions.append(i['generated_text'][10:])
-            st.write(i['generated_text'][10:])
-        if st.toggle(label='Show Pipeline Output'):
-            st.write(s)
-        if st.toggle(label='Show Questions list'):
-            st.write(questions)
-        # for i in sts:
-        #     x = pipe(i)
-        #     questions.append(x)
-        #     st.write(x)
-
-if __name__ == '__main__':
+import streamlit as st
+from transformers import pipeline
+from PyPDF2 import PdfReader
+import PyPDF2
+import fitz
+import os
+import nltk
+
+nltk.download('punkt')
+
+def get_pdf_text(pdf_docs):
+    text = ""
+    for pdf in pdf_docs:
+        pdf_reader = PdfReader(pdf)
+        for page in pdf_reader.pages:
+            text += page.extract_text()
+    return text
+
+def main():
+    st.title('Question Generator from PDFs')
+    pipe = pipeline(
+        task = 'text2text-generation',
+        model = 'ramsrigouthamg/t5_squad_v1'
+    )
+    file = st.file_uploader(label='Upload',accept_multiple_files=True)
+    pr = st.button(label='Start')
+    if pr:
+        st.write('Hi')
+        raw_text = get_pdf_text(file)
+        sentences = nltk.sent_tokenize(text=raw_text)
+        # st.write(sts)
+        # for i in sentences:
+        #     st.write(i)
+        questions = []
+        st.subheader("Generated Questions are: ")
+        s = pipe(sentences)
+        for i in s:
+            questions.append(i['generated_text'][10:])
+            st.write(i['generated_text'][10:])
+        if st.toggle(label='Show Pipeline Output'):
+            st.write(s)
+        if st.toggle(label='Show Questions list'):
+            st.write(questions)
+        # for i in sts:
+        #     x = pipe(i)
+        #     questions.append(x)
+        #     st.write(x)
+
+if __name__ == '__main__':
     main()