Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -3,16 +3,24 @@ from PyPDF2 import PdfReader
|
|
3 |
import docx
|
4 |
from pptx import Presentation
|
5 |
from transformers import pipeline
|
6 |
-
import os
|
7 |
|
8 |
-
|
|
|
9 |
|
|
|
10 |
qa_pipeline = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad")
|
11 |
|
12 |
-
|
|
|
|
|
|
|
|
|
|
|
13 |
|
|
|
14 |
all_text = ""
|
15 |
|
|
|
16 |
def extract_text_from_pdf(file):
|
17 |
reader = PdfReader(file)
|
18 |
return "\n".join([page.extract_text() or "" for page in reader.pages])
|
@@ -30,6 +38,7 @@ def extract_text_from_pptx(file):
|
|
30 |
text.append(shape.text)
|
31 |
return "\n".join(text)
|
32 |
|
|
|
33 |
for file in uploaded_files:
|
34 |
file_type = file.name.split('.')[-1].lower()
|
35 |
if file_type == "pdf":
|
@@ -39,10 +48,14 @@ for file in uploaded_files:
|
|
39 |
elif file_type == "pptx":
|
40 |
all_text += extract_text_from_pptx(file) + "\n"
|
41 |
|
|
|
42 |
if all_text:
|
43 |
-
st.success("Files processed.
|
44 |
-
question = st.text_input("Ask a question
|
45 |
|
46 |
if question:
|
47 |
result = qa_pipeline(question=question, context=all_text)
|
48 |
-
st.write("**Answer:**", result['answer'])
|
|
|
|
|
|
|
|
3 |
import docx
|
4 |
from pptx import Presentation
|
5 |
from transformers import pipeline
|
|
|
6 |
|
7 |
+
# Title of the app
|
8 |
+
st.title("π Multi-Document Q&A App")
|
9 |
|
10 |
+
# Load question-answering pipeline from Hugging Face
|
11 |
qa_pipeline = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad")
|
12 |
|
13 |
+
# File uploader for multiple file types
|
14 |
+
uploaded_files = st.file_uploader(
|
15 |
+
"Upload PDF, Word (.docx), or PPT (.pptx) files",
|
16 |
+
type=["pdf", "docx", "pptx"],
|
17 |
+
accept_multiple_files=True
|
18 |
+
)
|
19 |
|
20 |
+
# Combine text from all files
|
21 |
all_text = ""
|
22 |
|
23 |
+
# File processing functions
|
24 |
def extract_text_from_pdf(file):
|
25 |
reader = PdfReader(file)
|
26 |
return "\n".join([page.extract_text() or "" for page in reader.pages])
|
|
|
38 |
text.append(shape.text)
|
39 |
return "\n".join(text)
|
40 |
|
41 |
+
# Extract text from uploaded files
|
42 |
for file in uploaded_files:
|
43 |
file_type = file.name.split('.')[-1].lower()
|
44 |
if file_type == "pdf":
|
|
|
48 |
elif file_type == "pptx":
|
49 |
all_text += extract_text_from_pptx(file) + "\n"
|
50 |
|
51 |
+
# Show input for question if files were processed
|
52 |
if all_text:
|
53 |
+
st.success("β
Files processed. Ask your question below.")
|
54 |
+
question = st.text_input("β Ask a question:")
|
55 |
|
56 |
if question:
|
57 |
result = qa_pipeline(question=question, context=all_text)
|
58 |
+
st.write("π **Answer:**", result['answer'])
|
59 |
+
else:
|
60 |
+
st.info("Upload some files to begin...")
|
61 |
+
|