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import os
import fitz
from pptx import Presentation
import subprocess
from datetime import datetime
from llama_index.core import Document
from utils import (
describe_image, is_graph, process_graph, extract_text_around_item,
process_text_blocks, save_uploaded_file
)
def get_pdf_documents(pdf_file):
"""Process a PDF file and extract text, tables, and images."""
all_pdf_documents = []
ongoing_tables = {}
try:
f = fitz.open(stream=pdf_file.read(), filetype="pdf")
except Exception as e:
print(f"Error opening or processing the PDF file: {e}")
return []
for i in range(len(f)):
page = f[i]
text_blocks = [block for block in page.get_text("blocks", sort=True)
if block[-1] == 0 and not (block[1] < page.rect.height * 0.1 or block[3] > page.rect.height * 0.9)]
grouped_text_blocks = process_text_blocks(text_blocks)
table_docs, table_bboxes, ongoing_tables = parse_all_tables(pdf_file.name, page, i, text_blocks, ongoing_tables)
all_pdf_documents.extend(table_docs)
image_docs = parse_all_images(pdf_file.name, page, i, text_blocks)
all_pdf_documents.extend(image_docs)
for text_block_ctr, (heading_block, content) in enumerate(grouped_text_blocks, 1):
heading_bbox = fitz.Rect(heading_block[:4])
if not any(heading_bbox.intersects(table_bbox) for table_bbox in table_bboxes):
bbox = {"x1": heading_block[0], "y1": heading_block[1], "x2": heading_block[2], "x3": heading_block[3]}
text_doc = Document(
text=f"{heading_block[4]}\n{content}",
metadata={
**bbox,
"type": "text",
"page_num": i,
"source": f"{pdf_file.name[:-4]}-page{i}-block{text_block_ctr}"
},
id_=f"{pdf_file.name[:-4]}-page{i}-block{text_block_ctr}"
)
all_pdf_documents.append(text_doc)
f.close()
return all_pdf_documents
def parse_all_tables(filename, page, pagenum, text_blocks, ongoing_tables):
"""Extract tables from a PDF page."""
table_docs = []
table_bboxes = []
try:
tables = page.find_tables(horizontal_strategy="lines_strict", vertical_strategy="lines_strict")
for tab in tables:
if not tab.header.external:
pandas_df = tab.to_pandas()
tablerefdir = os.path.join(os.getcwd(), "vectorstore/table_references")
os.makedirs(tablerefdir, exist_ok=True)
df_xlsx_path = os.path.join(tablerefdir, f"table{len(table_docs)+1}-page{pagenum}.xlsx")
pandas_df.to_excel(df_xlsx_path)
bbox = fitz.Rect(tab.bbox)
table_bboxes.append(bbox)
before_text, after_text = extract_text_around_item(text_blocks, bbox, page.rect.height)
table_img = page.get_pixmap(clip=bbox)
table_img_path = os.path.join(tablerefdir, f"table{len(table_docs)+1}-page{pagenum}.jpg")
table_img.save(table_img_path)
description = process_graph(table_img.tobytes())
caption = before_text.replace("\n", " ") + description + after_text.replace("\n", " ")
if before_text == "" and after_text == "":
caption = " ".join(tab.header.names)
table_metadata = {
"source": f"{filename[:-4]}-page{pagenum}-table{len(table_docs)+1}",
"dataframe": df_xlsx_path,
"image": table_img_path,
"caption": caption,
"type": "table",
"page_num": pagenum
}
all_cols = ", ".join(list(pandas_df.columns.values))
doc = Document(text=f"This is a table with the caption: {caption}\nThe columns are {all_cols}", metadata=table_metadata)
table_docs.append(doc)
except Exception as e:
print(f"Error during table extraction: {e}")
return table_docs, table_bboxes, ongoing_tables
def parse_all_images(filename, page, pagenum, text_blocks):
"""Extract images from a PDF page."""
image_docs = []
image_info_list = page.get_image_info(xrefs=True)
page_rect = page.rect
for image_info in image_info_list:
xref = image_info['xref']
if xref == 0:
continue
img_bbox = fitz.Rect(image_info['bbox'])
if img_bbox.width < page_rect.width / 20 or img_bbox.height < page_rect.height / 20:
continue
extracted_image = page.parent.extract_image(xref)
image_data = extracted_image["image"]
imgrefpath = os.path.join(os.getcwd(), "vectorstore/image_references")
os.makedirs(imgrefpath, exist_ok=True)
image_path = os.path.join(imgrefpath, f"image{xref}-page{pagenum}.png")
with open(image_path, "wb") as img_file:
img_file.write(image_data)
before_text, after_text = extract_text_around_item(text_blocks, img_bbox, page.rect.height)
if before_text == "" and after_text == "":
continue
image_description = " "
if is_graph(image_data):
image_description = process_graph(image_data)
caption = before_text.replace("\n", " ") + image_description + after_text.replace("\n", " ")
image_metadata = {
"source": f"{filename[:-4]}-page{pagenum}-image{xref}",
"image": image_path,
"caption": caption,
"type": "image",
"page_num": pagenum
}
image_docs.append(Document(text="This is an image with the caption: " + caption, metadata=image_metadata))
return image_docs
def process_ppt_file(ppt_path):
"""Process a PowerPoint file."""
pdf_path = convert_ppt_to_pdf(ppt_path)
images_data = convert_pdf_to_images(pdf_path)
slide_texts = extract_text_and_notes_from_ppt(ppt_path)
processed_data = []
for (image_path, page_num), (slide_text, notes) in zip(images_data, slide_texts):
if notes:
notes = "\n\nThe speaker notes for this slide are: " + notes
with open(image_path, 'rb') as image_file:
image_content = image_file.read()
image_description = " "
if is_graph(image_content):
image_description = process_graph(image_content)
image_metadata = {
"source": f"{os.path.basename(ppt_path)}",
"image": image_path,
"caption": slide_text + image_description + notes,
"type": "image",
"page_num": page_num
}
processed_data.append(Document(text="This is a slide with the text: " + slide_text + image_description, metadata=image_metadata))
return processed_data
def convert_ppt_to_pdf(ppt_path):
"""Convert a PowerPoint file to PDF using LibreOffice."""
base_name = os.path.basename(ppt_path)
ppt_name_without_ext = os.path.splitext(base_name)[0].replace(' ', '_')
new_dir_path = os.path.abspath("vectorstore/ppt_references")
os.makedirs(new_dir_path, exist_ok=True)
pdf_path = os.path.join(new_dir_path, f"{ppt_name_without_ext}.pdf")
command = ['libreoffice', '--headless', '--convert-to', 'pdf', '--outdir', new_dir_path, ppt_path]
subprocess.run(command, check=True)
return pdf_path
def convert_pdf_to_images(pdf_path):
"""Convert a PDF file to a series of images using PyMuPDF."""
doc = fitz.open(pdf_path)
base_name = os.path.basename(pdf_path)
pdf_name_without_ext = os.path.splitext(base_name)[0].replace(' ', '_')
new_dir_path = os.path.join(os.getcwd(), "vectorstore/ppt_references")
os.makedirs(new_dir_path, exist_ok=True)
image_paths = []
for page_num in range(len(doc)):
page = doc.load_page(page_num)
pix = page.get_pixmap()
output_image_path = os.path.join(new_dir_path, f"{pdf_name_without_ext}_{page_num:04d}.png")
pix.save(output_image_path)
image_paths.append((output_image_path, page_num))
doc.close()
return image_paths
def extract_text_and_notes_from_ppt(ppt_path):
"""Extract text and notes from a PowerPoint file."""
prs = Presentation(ppt_path)
text_and_notes = []
for slide in prs.slides:
slide_text = ' '.join([shape.text for shape in slide.shapes if hasattr(shape, "text")])
try:
notes = slide.notes_slide.notes_text_frame.text if slide.notes_slide else ''
except:
notes = ''
text_and_notes.append((slide_text, notes))
return text_and_notes
def load_multimodal_data(files):
"""Load and process multiple file types with timestamp metadata."""
documents = []
for file in files:
# Get current timestamp
current_timestamp = datetime.now().isoformat()
file_extension = os.path.splitext(file.lower())[1]
if file_extension in ('.png', '.jpg', '.jpeg'):
image_content = open(file, "rb").read()
image_text = describe_image(image_content)
doc = Document(
text=image_text,
metadata={
"source": file.lower(),
"type": "image",
"timestamp": current_timestamp
}
)
documents.append(doc)
elif file_extension == '.pdf':
try:
pdf_documents = get_pdf_documents(file)
# Add timestamp to each PDF document
for pdf_doc in pdf_documents:
pdf_doc.metadata['timestamp'] = current_timestamp
documents.extend(pdf_documents)
except Exception as e:
print(f"Error processing PDF {file.lower()}: {e}")
elif file_extension in ('.ppt', '.pptx'):
try:
ppt_documents = process_ppt_file(save_uploaded_file(file))
# Add timestamp to each PPT document
for ppt_doc in ppt_documents:
ppt_doc.metadata['timestamp'] = current_timestamp
documents.extend(ppt_documents)
except Exception as e:
print(f"Error processing PPT {file.lower()}: {e}")
else:
text = file.read().decode("utf-8")
doc = Document(
text=text,
metadata={
"source": file.lower(),
"type": "text",
"timestamp": current_timestamp
}
)
documents.append(doc)
return documents
def load_data_from_directory(directory):
"""Load and process multiple file types from a directory with timestamp metadata."""
documents = []
for filename in os.listdir(directory):
filepath = os.path.join(directory, filename)
# Get current timestamp
current_timestamp = datetime.now().isoformat()
file_extension = os.path.splitext(filename.lower())[1]
print(filename)
if file_extension in ('.png', '.jpg', '.jpeg'):
with open(filepath, "rb") as image_file:
image_content = image_file.read()
image_text = describe_image(image_content)
doc = Document(
text=image_text,
metadata={
"source": filename,
"type": "image",
"timestamp": current_timestamp
}
)
print(doc)
documents.append(doc)
elif file_extension == '.pdf':
with open(filepath, "rb") as pdf_file:
try:
pdf_documents = get_pdf_documents(pdf_file)
# Add timestamp to each PDF document
for pdf_doc in pdf_documents:
pdf_doc.metadata['timestamp'] = current_timestamp
documents.extend(pdf_documents)
except Exception as e:
print(f"Error processing PDF {filename}: {e}")
elif file_extension in ('.ppt', '.pptx'):
try:
ppt_documents = process_ppt_file(filepath)
# Add timestamp to each PPT document
for ppt_doc in ppt_documents:
ppt_doc.metadata['timestamp'] = current_timestamp
documents.extend(ppt_documents)
print(ppt_documents)
except Exception as e:
print(f"Error processing PPT {filename}: {e}")
else:
with open(filepath, "r", encoding="utf-8") as text_file:
text = text_file.read()
doc = Document(
text=text,
metadata={
"source": filename,
"type": "text",
"timestamp": current_timestamp
}
)
documents.append(doc)
return documents |