Changes to allocate the error

app.py

@@ -1,95 +1,94 @@
-import streamlit as st
-import arxiv
-
 import os
-import pdfminer
-from pdfminer.high_level import extract_text, extract_pages
-from pdfminer.layout import LTTextContainer
+import streamlit as st
+from pdfminer.high_level import extract_pages
 from search import search
 from get_paper import get_paper
 from get_pages import get_pages
 from tts import inference
-import IPython.display as ipd
 
 st.title("ArXiV Audio")
 
-with st.form(key = "search_form"):
-  col1, col2, col3 = st.columns(3)
-  with col1:
-    query = st.text_input("Search Paper")
-  with col2:
-    sort_by = st.selectbox(label = "Sort By", options=('Relevance', 'Last Updated Date','Submitted Date'))
-  with col3:
-    order_by = st.selectbox(label = "Order By", options=('Ascending', 'Descending'))
-  submit = st.form_submit_button(label = "Search")
-  
+with st.form(key="search_form"):
+    col1, col2, col3 = st.columns(3)
+    with col1:
+        query = st.text_input("Search Paper")
+    with col2:
+        sort_by = st.selectbox(label="Sort By", options=(
+            'Relevance', 'Last Updated Date', 'Submitted Date'))
+    with col3:
+        order_by = st.selectbox(
+            label="Order By", options=('Ascending', 'Descending'))
+    submit = st.form_submit_button(label="Search")
+
 lst = search(query=query, sort_by=sort_by, sort_order=order_by)
 if len(lst) != 0:
-  label = "Papers for " + query
-  with st.form(key = "paper_form"):
-    pname = st.selectbox(label = label, options=lst)
-    submit_paper = st.form_submit_button(label = "Fetch Paper")
+    label = "Papers for " + query
+    with st.form(key="paper_form"):
+        pname = st.selectbox(label=label, options=lst)
+        submit_paper = st.form_submit_button(label="Fetch Paper")
 else:
-  with st.form(key = "paper_form"):
-    pname = st.selectbox(label = "NO PAPERS", options=lst)
-    submit_paper = st.form_submit_button(label = "Fetch Paper")
-paper=""
-if submit_paper:    
-  paper = get_paper(pname)
-  
-  print("Submit_paper = ", submit_paper)
+    with st.form(key="paper_form"):
+        pname = st.selectbox(label="NO PAPERS", options=lst)
+        submit_paper = st.form_submit_button(label="Fetch Paper")
+
+paper = ""
+if submit_paper or os.path.exists('downloads/paper.pdf'):
+    paper = get_paper(pname)
+
+    print("Submit_paper = ", submit_paper)
 
-  name=""
-  tpages=0
-  lst_idx=1
-  if paper:
-    name = "./downloads/paper.pdf"
-    tpages = len(list(extract_pages(name)))
-    lst_idx = tpages-1
-    
-  pgs = [i+1 for i in range(tpages)]
-        
-  start_page = 1
-  end_page = pgs[-1]
+    name = ""
+    tpages = 0
+    lst_idx = 1
+    if paper:
+        name = "./downloads/paper.pdf"
+        tpages = len(list(extract_pages(name)))
+        lst_idx = tpages-1
+
+    pgs = [i+1 for i in range(tpages)]
+
+    start_page = 1
+    end_page = pgs[-1]
     #content = get_pages(name, start_page, end_page)
     #audio_path = inference(content, "english")
     #audio_file = open(audio_path, "rb")
     #audio_bytes = audio_file.read()
     #st.audio(audio_bytes, format='audio/wav')
-    
-  with st.form(key = "page_form"):
-    print("inside page form")   
-    col4, col5 = st.columns(2)
-    with col4:
-      print("column 1")
-      s_page = st.selectbox(label = "Start Page", options = pgs)
-      print(s_page)
-      start_page = s_page
-    with col5:
-      print("column 2")
-      e_page = st.selectbox(label = "End Page", options = pgs, index = lst_idx)
-      print(e_page)
-      end_page = e_page
-    submit_pages = st.form_submit_button(label = "Convert To Audio")
-    print("Submit_pages' = ", submit_pages)
-  print(start_page, end_page)  
-    
-  print("Submit_pages = ", submit_pages)        
-  if submit_pages:
-    content = get_pages(name, start_page, end_page)
-    audio_path = inference(content, "english")
-    audio_file = open(audio_path, "rb")
-    audio_bytes = audio_file.read()
-    st.audio(audio_bytes, format='audio/wav')
-  
-  print("Submit_paper at end state = ", submit_paper)
 
-            
+    with st.form(key="page_form"):
+        print("inside page form")
+        col4, col5 = st.columns(2)
+        with col4:
+            print("column 1")
+            s_page = st.selectbox(label="Start Page", options=pgs)
+            print(s_page)
+            start_page = s_page
+        with col5:
+            print("column 2")
+            e_page = st.selectbox(label="End Page", options=pgs, index=lst_idx)
+            print(e_page)
+            end_page = e_page
+        submit_pages = st.form_submit_button(label="Convert To Audio")
+        print("Submit_pages' = ", submit_pages)
+    print(start_page, end_page)
+
+    print("Submit_pages = ", submit_pages)
+    if submit_pages:
+        content = get_pages(name, start_page, end_page)
+        audio_path = inference(content, "english")
+        audio_file = open(audio_path, "rb")
+        audio_bytes = audio_file.read()
+        st.audio(audio_bytes, format='audio/wav')
+        os.remove('downloads/paper.pdf')
+
+    print("Submit_paper at end state = ", submit_paper)
+
+
 else:
-  with st.form(key = "page_form"):   
-    col1, col2 = st.columns(2)
-    with col1:
-      s_page = st.selectbox(label = "Start Page", options = [])
-    with col2:
-      e_page = st.selectbox(label = "End Page", options = [])
-    submit_pages2 = st.form_submit_button(label = "Convert To Audio")
+    with st.form(key="page_form"):
+        col1, col2 = st.columns(2)
+        with col1:
+            s_page = st.selectbox(label="Start Page", options=[])
+        with col2:
+            e_page = st.selectbox(label="End Page", options=[])
+        submit_pages2 = st.form_submit_button(label="Convert To Audio")

tts.py

@@ -1,11 +1,10 @@
-import time
 import torch
 import scipy.io.wavfile
 from espnet2.bin.tts_inference import Text2Speech
 from espnet2.utils.types import str_or_none
 
-tagen = 'kan-bayashi/ljspeech_vits' 
-vocoder_tagen = "none" 
+tagen = 'kan-bayashi/ljspeech_vits'
+vocoder_tagen = "none"
 
 text2speechen = Text2Speech.from_pretrained(
     model_tag=str_or_none(tagen),
@@ -27,10 +26,11 @@ text2speechen = Text2Speech.from_pretrained(
 )
 
 
-def inference(text,lang):
-  print("Converting to Audio")
-  with torch.no_grad():
-      if lang == "english":
-          wav = text2speechen(text)["wav"]
-          scipy.io.wavfile.write("./audio/out.wav",text2speechen.fs , wav.view(-1).cpu().numpy())
-  return  "./audio/out.wav"
+def inference(text, lang):
+    print("Converting to Audio")
+    with torch.no_grad():
+        if lang == "english":
+            wav = text2speechen(text)["wav"]
+            scipy.io.wavfile.write(
+                "./audio/out.wav", text2speechen.fs, wav.view(-1).cpu().numpy())
+    return "./audio/out.wav"