Convert documents for RAG pipelines Leave feedback
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Retrieval-augmented generation (RAG) systems need documents in a clean, structured text format for chunking and embedding. Markdown is ideal – it preserves document structure (headings, lists, tables) while being easy to parse.
flowchart LR
A["PDF / DOCX / XLSX"]
B["GroupDocs.Markdown"]
C["Markdown"]
D["Text Chunking"]
E["Vector Embeddings"]
F["LLM Query"]
A --> B --> C --> D --> E --> F
import re
from groupdocs.markdown import MarkdownConverter, ConvertOptions, SkipImagesStrategy, MarkdownFlavor
def convert_for_rag():
"""Convert a PDF to Markdown for RAG pipelines, then split into chunks by heading."""
# Step 1: Configure conversion for text-only RAG (skip images)
options = ConvertOptions()
options.image_export_strategy = SkipImagesStrategy()
options.flavor = MarkdownFlavor.COMMON_MARK
# Step 2: Convert the document using keyword argument for options
markdown = MarkdownConverter.to_markdown("business-plan.pdf", convert_options=options)
# Step 3: Split the Markdown into chunks by heading markers
chunks = re.split(r"\n#{1,2} ", markdown)
# Step 4: Process each chunk (e.g., send to an embedding model)
for chunk in chunks:
if chunk.strip():
print(f"Chunk ({len(chunk)} chars): {chunk[:80]}...")
if __name__ == "__main__":
convert_for_rag()
business-plan.pdf is sample file used in this example. Click here to download it.
Chunk (36184 chars):
**HOME**** ****BASED**** ****PROFESSIONAL**** **
**SERVICES**** **
***...
Chunk (34602 chars):
**HOME BASED PROFESSIONAL SERVICES *Business Plan* TABLE OF CONTENTS**
I...
import os
import glob
from groupdocs.markdown import MarkdownConverter, ConvertOptions, SkipImagesStrategy, GroupDocsMarkdownException
def batch_convert_for_rag():
"""Batch-convert all PDFs in a folder to Markdown for RAG ingestion."""
# Step 1: Configure conversion to skip images (text-only RAG)
options = ConvertOptions()
options.image_export_strategy = SkipImagesStrategy()
# Step 2: Find all PDF files in the documents folder
files = glob.glob("documents/*.pdf")
# Step 3: Convert each file, handling errors gracefully
for file in files:
try:
markdown = MarkdownConverter.to_markdown(file, convert_options=options)
output_path = os.path.splitext(file)[0] + ".md"
with open(output_path, "w", encoding="utf-8") as f:
f.write(markdown)
print(f"Converted: {file}")
except GroupDocsMarkdownException as ex:
print(f"Skipped {file}: {ex}")
if __name__ == "__main__":
batch_convert_for_rag()
Converted: documents\business-plan.pdf
documents/business-plan.txt (32 KB)
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