Spaces:
Running
Running
ivyblossom
commited on
Commit
•
9988861
1
Parent(s):
663bca5
Update app.py
Browse files
app.py
CHANGED
@@ -1,15 +1,8 @@
|
|
1 |
import os
|
2 |
import streamlit as st
|
3 |
from transformers import pipeline
|
4 |
-
import re
|
5 |
from PyPDF2 import PdfReader
|
6 |
|
7 |
-
# Function to truncate text to the nearest word boundary
|
8 |
-
def truncate_to_word_boundary(text, max_words=100):
|
9 |
-
words = re.findall(r'\w+', text)
|
10 |
-
truncated_text = ' '.join(words[:max_words])
|
11 |
-
return truncated_text
|
12 |
-
|
13 |
# Function to perform question-answering
|
14 |
def question_answering(question, pdf_path):
|
15 |
pdf_reader = PdfReader(pdf_path)
|
@@ -25,27 +18,20 @@ def question_answering(question, pdf_path):
|
|
25 |
question_answerer = pipeline("question-answering", model="distilbert-base-cased-distilled-squad", tokenizer="distilbert-base-cased-distilled-squad")
|
26 |
answer = question_answerer(question=question, context=pdf_text)
|
27 |
|
28 |
-
return answer
|
29 |
-
|
30 |
-
def get_context_text(pdf_text_with_pages, context_page_num, context_window=3):
|
31 |
-
context_start = max(0, context_page_num - context_window - 1)
|
32 |
-
context_end = min(len(pdf_text_with_pages), context_page_num + context_window)
|
33 |
-
context_lines = [text for _, text in pdf_text_with_pages[context_start:context_end]]
|
34 |
-
context_text = "\n".join(context_lines)
|
35 |
-
return context_text
|
36 |
|
37 |
def main():
|
38 |
st.title("Question Answering on a PDF File")
|
39 |
|
40 |
uploaded_file = st.file_uploader("Upload a PDF file:", type=["pdf"])
|
41 |
question = st.text_input("Ask your question:")
|
42 |
-
|
43 |
if st.button("Answer") and uploaded_file is not None:
|
44 |
pdf_path = os.path.join(os.getcwd(), uploaded_file.name)
|
45 |
with open(pdf_path, "wb") as f:
|
46 |
f.write(uploaded_file.read())
|
47 |
|
48 |
-
answer
|
49 |
|
50 |
# Delete the uploaded file after processing
|
51 |
os.remove(pdf_path)
|
@@ -54,11 +40,5 @@ def main():
|
|
54 |
st.write("Answer:", answer['answer'])
|
55 |
st.write("Score:", answer['score'])
|
56 |
|
57 |
-
# Display context where the answer came from
|
58 |
-
context_page_num = answer['start']
|
59 |
-
context_text = get_context_text(pdf_text_with_pages, context_page_num)
|
60 |
-
st.write("Context:")
|
61 |
-
st.write(context_text)
|
62 |
-
|
63 |
if __name__ == "__main__":
|
64 |
-
main()
|
|
|
1 |
import os
|
2 |
import streamlit as st
|
3 |
from transformers import pipeline
|
|
|
4 |
from PyPDF2 import PdfReader
|
5 |
|
|
|
|
|
|
|
|
|
|
|
|
|
6 |
# Function to perform question-answering
|
7 |
def question_answering(question, pdf_path):
|
8 |
pdf_reader = PdfReader(pdf_path)
|
|
|
18 |
question_answerer = pipeline("question-answering", model="distilbert-base-cased-distilled-squad", tokenizer="distilbert-base-cased-distilled-squad")
|
19 |
answer = question_answerer(question=question, context=pdf_text)
|
20 |
|
21 |
+
return answer
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
22 |
|
23 |
def main():
|
24 |
st.title("Question Answering on a PDF File")
|
25 |
|
26 |
uploaded_file = st.file_uploader("Upload a PDF file:", type=["pdf"])
|
27 |
question = st.text_input("Ask your question:")
|
28 |
+
|
29 |
if st.button("Answer") and uploaded_file is not None:
|
30 |
pdf_path = os.path.join(os.getcwd(), uploaded_file.name)
|
31 |
with open(pdf_path, "wb") as f:
|
32 |
f.write(uploaded_file.read())
|
33 |
|
34 |
+
answer = question_answering(question, pdf_path)
|
35 |
|
36 |
# Delete the uploaded file after processing
|
37 |
os.remove(pdf_path)
|
|
|
40 |
st.write("Answer:", answer['answer'])
|
41 |
st.write("Score:", answer['score'])
|
42 |
|
|
|
|
|
|
|
|
|
|
|
|
|
43 |
if __name__ == "__main__":
|
44 |
+
main()
|