extractflow-parser 1.0.0

Parse PDF documents into markdown formatted content using Vision LLMs

ExtractFlow Parse

SimplifyX - Document Processing

🚀 Getting Started

Prerequisites

• 🐍 Python >= 3.9
• 🖥️ Ollama (if you want to use local models)
• 🤖 API Key for OpenAI (OpenAI compatible models) or Google Gemini (if you want to use OpenAI or Google Gemini)

The easiest way to get started is by exploring the examples folder for additional sample use cases.

Azure LLama Vision

QWEN2-VL

OpenAI

Gemini

Ollama

Models Support

ExtractFlow supports various vision language models from different providers:

OpenAI Compatible Models

• You can use any model that is compatible with OpenAI API.
• By passing openai_compatible=True, and base_url to the parser, the parser will use the OpenAI API to process the image.

Ollama Models

• llama3.2-vision:11b
• llama3.2-vision:70b
• llava:13b
• llava:34b

OpenAI Models

• gpt-4o
• gpt-4o-mini

Gemini Models

• gemini-1.5-flash
• gemini-2.0-flash-exp
• gemini-1.5-pro

Installation

Install the package using pip (Recommended):

pip install extractflow_parser

Install the optional dependencies for OpenAI or Gemini:

pip install 'extractflow_parser[openai]'

pip install 'extractflow_parser[gemini]'

Setting up Ollama (Optional)

See examples/ollama_setup.md on how to setup Ollama locally.

⌛️ Usage

Basic Example Usage

from extractflow_parser import ExtractFlowParser

# Initialize parser
parser = ExtractFlowParser(
    openai_compatible=True,
    base_url="https://api.fireworks.ai/inference/v1",
    api_key="your_api_key",
    model_name="accounts/fireworks/models/qwen2-vl-72b-instruct",
    temperature=0.2,
    top_p=0.3,
    extraction_complexity=True # Set to True for more detailed extraction
)

# Convert PDF to markdown
pdf_path = "path/to/your/document.pdf"
markdown_pages = parser.convert_pdf(pdf_path)

# Process results
for i, page_content in enumerate(markdown_pages):
    print(f"\n--- Page {i+1} ---\n{page_content}")

PDF Page Configuration

from extractflow_parser import ExtractFlowParser, PDFPageConfig

# Configure PDF processing settings
page_config = PDFPageConfig(
    dpi=400,
    color_space="RGB",
    include_annotations=True,
    preserve_transparency=False
)

# Initialize parser with custom page config
parser = ExtractFlowParser(
    model_name="llama3.2-vision:11b",
    temperature=0.7,
    top_p=0.4,
    extraction_complexity=False,
    page_config=page_config
)

# Convert PDF to markdown
pdf_path = "path/to/your/document.pdf"
markdown_pages = parser.convert_pdf(pdf_path)

OpenAI or Gemini Model Usage

from extractflow_parser import ExtractFlowParser

# Initialize parser with OpenAI model
parser = ExtractFlowParser(
    model_name="gpt-4o",
    api_key="your-openai-api-key", # Get the OpenAI API key from https://platform.openai.com/api-keys
    temperature=0.7,
    top_p=0.4,
    extraction_complexity=True # Set to True for more detailed extraction
)

# Initialize parser with Google Gemini model
parser = ExtractFlowParser(
    model_name="gemini-1.5-flash",
    api_key="your-gemini-api-key", # Get the Gemini API key from https://aistudio.google.com/app/apikey
    temperature=0.7,
    top_p=0.4,
    extraction_complexity=True # Set to True for more detailed extraction
)

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.