DevBM commited on
Commit
ef13efd
·
verified ·
1 Parent(s): 225bf42

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +7 -6
app.py CHANGED
@@ -16,13 +16,11 @@ from nltk.tokenize import sent_tokenize
16
 
17
  # Load spaCy model
18
  nlp = spacy.load("en_core_web_sm")
19
- # wiki_wiki = wikipediaapi.Wikipedia('en')
20
 
21
  # Initialize Wikipedia API with a user agent
22
  user_agent = 'QGen/1.0 ([email protected])'
23
  wiki_wiki = wikipediaapi.Wikipedia(user_agent= user_agent,language='en')
24
 
25
-
26
  # Load T5 model and tokenizer
27
  model_name = "DevBM/t5-large-squad"
28
  model = T5ForConditionalGeneration.from_pretrained(model_name)
@@ -102,7 +100,7 @@ def export_to_pdf(data):
102
  pdf.output("questions.pdf")
103
 
104
  # Streamlit interface
105
- st.title("Question Generator from Text")
106
  text = st.text_area("Enter text here:", value="Joe Biden, the current US president is on a weak wicket going in for his reelection later this November against former President Donald Trump.")
107
 
108
  # Customization options
@@ -110,7 +108,8 @@ num_beams = st.slider("Select number of beams for question generation", min_valu
110
  context_window_size = st.slider("Select context window size (number of sentences before and after)", min_value=1, max_value=5, value=1)
111
  num_questions = st.slider("Select number of questions to generate", min_value=1, max_value=1000, value=5)
112
  question_complexity = st.selectbox("Select question complexity", ["Simple", "Intermediate", "Complex"])
113
-
 
114
  if st.button("Generate Questions"):
115
  if text:
116
  keywords = extract_keywords(text)
@@ -132,11 +131,13 @@ if st.button("Generate Questions"):
132
  data.append((context, keyword, question))
133
 
134
  # Export buttons
135
- if st.button("Export to CSV"):
 
136
  export_to_csv(data)
137
  st.success("Questions exported to questions.csv")
138
 
139
- if st.button("Export to PDF"):
 
140
  export_to_pdf(data)
141
  st.success("Questions exported to questions.pdf")
142
  else:
 
16
 
17
  # Load spaCy model
18
  nlp = spacy.load("en_core_web_sm")
 
19
 
20
  # Initialize Wikipedia API with a user agent
21
  user_agent = 'QGen/1.0 ([email protected])'
22
  wiki_wiki = wikipediaapi.Wikipedia(user_agent= user_agent,language='en')
23
 
 
24
  # Load T5 model and tokenizer
25
  model_name = "DevBM/t5-large-squad"
26
  model = T5ForConditionalGeneration.from_pretrained(model_name)
 
100
  pdf.output("questions.pdf")
101
 
102
  # Streamlit interface
103
+ st.title(":blue[Question Generator from Text]")
104
  text = st.text_area("Enter text here:", value="Joe Biden, the current US president is on a weak wicket going in for his reelection later this November against former President Donald Trump.")
105
 
106
  # Customization options
 
108
  context_window_size = st.slider("Select context window size (number of sentences before and after)", min_value=1, max_value=5, value=1)
109
  num_questions = st.slider("Select number of questions to generate", min_value=1, max_value=1000, value=5)
110
  question_complexity = st.selectbox("Select question complexity", ["Simple", "Intermediate", "Complex"])
111
+ downlaod_csv = st.toggle('Download CSV',value=False)
112
+ download_pdf = st.toggle('Download PDF',value=False)
113
  if st.button("Generate Questions"):
114
  if text:
115
  keywords = extract_keywords(text)
 
131
  data.append((context, keyword, question))
132
 
133
  # Export buttons
134
+ # if st.button("Export to CSV"):
135
+ if downlaod_csv:
136
  export_to_csv(data)
137
  st.success("Questions exported to questions.csv")
138
 
139
+ # if st.button("Export to PDF"):
140
+ if download_pdf:
141
  export_to_pdf(data)
142
  st.success("Questions exported to questions.pdf")
143
  else: