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summarization.py
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summarization.py
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import fitz # PyMuPDF
import cohere
from PIL import Image
import io
import pytesseract
def get_text_and_images_from_pdf(uploaded_file):
text = ""
images = []
pdf_document = fitz.open(stream=uploaded_file.read(), filetype="pdf")
for page_num in range(pdf_document.page_count):
page = pdf_document.load_page(page_num)
text += page.get_text()
for img_index, img in enumerate(page.get_images(full=True)):
xref = img[0]
base_image = pdf_document.extract_image(xref)
image_bytes = base_image["image"]
image = Image.open(io.BytesIO(image_bytes))
image_text = pytesseract.image_to_string(image)
images.append(image_text)
return text, images
def summarize_large_text(text, co):
if len(text) > 5000:
chunks = [text[i:i + 5000] for i in range(0, len(text), 5000)]
summary = ""
for chunk in chunks:
response = co.summarize(
text=chunk,
model="summarize-xlarge", # Use an available summarization model
length="long"
)
summary += response.summary + " "
return summary
else:
response = co.summarize(
text=text,
model="summarize-xlarge", # Use an available summarization model
length="long"
)
return response.summary