doctomarkdown 0.2.0

Convert PDF, DOCX, PPTX, Images, URLs like Medium, Wikipedia and CSV documents to text or Markdown. Extracts text, images, and tables. Supports LLM-based extraction.

🚀 Doctomarkdown

Convert PDFs, DOCX, PPTX, CSV, images, and URLs to clean, readable Markdown in seconds!
Now with LLM-powered extraction, image & table support, and blazing-fast performance.

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✨ What's New

• v0.2.0 (2025-06):
  • 🖼️ Improved image extraction for PDFs and DOCX
  • 🤖 Enhanced LLM support: Gemini, Groq, Ollama
  • 🏷️ Custom output directory and file type
  • 🐍 Python 3.10+ compatibility
  • ⚡ Performance and stability improvements

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Doctomarkdown

Doctomarkdown is a robust Python library for converting documents—including PDF, DOCX, PPTX, CSV, images, and URLs—into clean, readable Markdown. It supports extracting text, images, and tables, and is easily extensible for more document types. Advanced extraction is available via LLM (Large Language Model) clients.

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Features

• 📄 Convert PDF, DOCX, PPTX, CSV, URL, and Images to Markdown
• 🖼️ Extract images from documents (optional)
• 📊 Extract tables from documents (optional)
• 🤖 LLM support: Azure OpenAI, OpenAI, Groq, Gemini, Ollama
• 🗂️ Extensible: Add support for more document types
• 🏷️ Custom output directory

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Supported File Types

File Type	Function Name	Example File Extension
PDF	convert_pdf_to_markdown	.pdf
DOCX	convert_docx_to_markdown	.docx
PPTX	convert_pptx_to_markdown	.pptx
CSV	convert_csv_to_markdown	.csv
Image	convert_image_to_markdown	.png, .jpg, .jpeg
URL	convert_url_to_markdown	(web link)

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Supported LLM Clients

LLM Client	How to Initialize
OpenAI	See below
Azure OpenAI	See below
Groq	See below
Gemini	See below
Ollama	See below

OpenAI

from openai import OpenAI
client = OpenAI(api_key="your-api-key")

Azure OpenAI

from openai import AzureOpenAI
client = AzureOpenAI(
    api_key="your-api-key",
    azure_endpoint="https://your-resource-name.openai.azure.com/",
    api_version="2023-05-15"
)

Groq

from groq import Groq
client = Groq(api_key="your-api-key")

Gemini

import google.generativeai as genai
genai.configure(api_key="your-api-key")
client = genai.GenerativeModel("gemini-pro")

Ollama

from openai import OpenAI
client = OpenAI(base_url='http://localhost:11434/v1', api_key='ollama')

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Installation

pip install doctomarkdown

Note: Requires Python 3.10+

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Basic Usage

Below is the main usage pattern with the specific function to call for each file type:

from doctomarkdown import DocToMarkdown
# Import and initialize your LLM client if needed (see table above)

app = DocToMarkdown(
    llm_client=client,        # Optional: pass your LLM client here
    llm_model='your-model'    # Optional: pass your LLM model name
)

# Choose the appropriate function for your file type:
# PDF:   app.convert_pdf_to_markdown()
# DOCX:  app.convert_docx_to_markdown()
# PPTX:  app.convert_pptx_to_markdown()
# CSV:   app.convert_csv_to_markdown()
# Image: app.convert_image_to_markdown()
# URL:   app.convert_url_to_markdown()

result = app.convert_pdf_to_markdown(  # Change function based on file type
    filepath="path/to/your/file.pdf",  # Change extension based on file type
    extract_images=True,      # Optional
    extract_tables=True,      # Optional
    output_path="markdown_output",  # Optional
    output_type="markdown"   # or 'text' for .txt output
)

for page in result.pages:
    print(f"Page Number: {page.page_number} | Page Content: {page.page_content}")

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Examples: Using OpenAI Client for All File Types

1. PDF to Markdown

from openai import OpenAI
from doctomarkdown import DocToMarkdown
import os
from dotenv import load_dotenv
load_dotenv()

client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
app = DocToMarkdown(llm_client=client, llm_model='gpt-4o')

result = app.convert_pdf_to_markdown(
    filepath="sample_docs/sample-1.pdf",
    extract_images=True,
    extract_tables=True,
    output_path="markdown_output",
    output_type="markdown"
)
for page in result.pages:
    print(f"Page Number: {page.page_number} | Page Content: {page.page_content}")

2. DOCX to Markdown

from openai import OpenAI
from doctomarkdown import DocToMarkdown
import os
from dotenv import load_dotenv
load_dotenv()

client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
app = DocToMarkdown(llm_client=client, llm_model='gpt-4o')

result = app.convert_docx_to_markdown(
    filepath="sample_docs/sample_document.docx",
    extract_images=True,
    extract_tables=True,
    output_path="markdown_output",
    output_type="markdown"
)
for page in result.pages:
    print(f"Page Number: {page.page_number} | Page Content: {page.page_content}")

3. PPTX to Markdown

from openai import OpenAI
from doctomarkdown import DocToMarkdown
import os
from dotenv import load_dotenv
load_dotenv()

client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
app = DocToMarkdown(llm_client=client, llm_model='gpt-4o')

result = app.convert_pptx_to_markdown(
    filepath="sample_docs/sample_ppt_2.pptx",
    extract_images=True,
    extract_tables=True,
    output_path="markdown_output",
    output_type="markdown"
)
for page in result.pages:
    print(f"Page Number: {page.page_number} | Page Content: {page.page_content}")

4. CSV to Markdown

from openai import OpenAI
from doctomarkdown import DocToMarkdown
import os
from dotenv import load_dotenv
load_dotenv()

client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
app = DocToMarkdown(llm_client=client, llm_model='gpt-4o')

result = app.convert_csv_to_markdown(
    filepath="sample_docs/sample.csv",
    extract_images=True,
    extract_tables=True,
    output_path="markdown_output",
    output_type="markdown"
)
for page in result.pages:
    print(f"Page Number: {page.page_number} | Page Content: {page.page_content}")

5. Image to Markdown

from openai import OpenAI
from doctomarkdown import DocToMarkdown
import os
from dotenv import load_dotenv
load_dotenv()

client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
app = DocToMarkdown(llm_client=client, llm_model='gpt-4o')

result = app.convert_image_to_markdown(
    filepath="sample_docs/sample_image.png",
    extract_images=True,
    extract_tables=True,
    output_path="markdown_output",
    output_type="text"
)
for page in result.pages:
    print(f"Page Number: {page.page_number} | Page Content: {page.page_content}")

6. URL to Markdown

from openai import OpenAI
from doctomarkdown import DocToMarkdown
import os
from dotenv import load_dotenv
load_dotenv()

client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
app = DocToMarkdown(llm_client=client, llm_model='gpt-4o')

result = app.convert_url_to_markdown(
    urlpath="https://medium.com/the-ai-forum/build-a-local-reliable-rag-agent-using-crewai-and-groq-013e5d557bcd",
    extract_images=True,
    extract_tables=True,
    output_path="markdown_output",
    output_type="markdown"
)
for page in result.pages:
    print(f"Page Number: {page.page_number}")
    print(f"Content Preview: {page.page_content[:500]}...")
    print(f"Total Length: {len(page.page_content)} characters")

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License

This project is licensed under the MIT License.