Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -7,8 +7,7 @@ from rake_nltk import Rake
|
|
7 |
import pandas as pd
|
8 |
from fpdf import FPDF
|
9 |
import wikipediaapi
|
10 |
-
|
11 |
-
|
12 |
nltk.download('punkt')
|
13 |
nltk.download('stopwords')
|
14 |
nltk.download('brown')
|
@@ -21,10 +20,16 @@ nlp = spacy.load("en_core_web_sm")
|
|
21 |
user_agent = 'QGen/1.0 ([email protected])'
|
22 |
wiki_wiki = wikipediaapi.Wikipedia(user_agent= user_agent,language='en')
|
23 |
|
24 |
-
|
25 |
-
|
26 |
-
|
27 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
28 |
|
29 |
# Function to extract keywords using combined techniques
|
30 |
def extract_keywords(text):
|
@@ -114,6 +119,7 @@ downlaod_csv = st.toggle('Download CSV',value=True)
|
|
114 |
download_pdf = st.toggle('Download PDF',value=True)
|
115 |
if st.button("Generate Questions"):
|
116 |
if text:
|
|
|
117 |
keywords = extract_keywords(text)
|
118 |
keyword_sentence_mapping = map_keywords_to_sentences(text, keywords, context_window_size)
|
119 |
|
|
|
7 |
import pandas as pd
|
8 |
from fpdf import FPDF
|
9 |
import wikipediaapi
|
10 |
+
from functools import lru_cache
|
|
|
11 |
nltk.download('punkt')
|
12 |
nltk.download('stopwords')
|
13 |
nltk.download('brown')
|
|
|
20 |
user_agent = 'QGen/1.0 ([email protected])'
|
21 |
wiki_wiki = wikipediaapi.Wikipedia(user_agent= user_agent,language='en')
|
22 |
|
23 |
+
|
24 |
+
model = None
|
25 |
+
tokenizer = None
|
26 |
+
def load_model():
|
27 |
+
global model, tokenizer
|
28 |
+
if model is None or tokenizer is None:
|
29 |
+
# Load T5 model and tokenizer
|
30 |
+
model_name = "DevBM/t5-large-squad"
|
31 |
+
model = T5ForConditionalGeneration.from_pretrained(model_name)
|
32 |
+
tokenizer = T5Tokenizer.from_pretrained(model_name)
|
33 |
|
34 |
# Function to extract keywords using combined techniques
|
35 |
def extract_keywords(text):
|
|
|
119 |
download_pdf = st.toggle('Download PDF',value=True)
|
120 |
if st.button("Generate Questions"):
|
121 |
if text:
|
122 |
+
load_model()
|
123 |
keywords = extract_keywords(text)
|
124 |
keyword_sentence_mapping = map_keywords_to_sentences(text, keywords, context_window_size)
|
125 |
|