docinfer 0.1.1

Extract and infer metadata from PDF documents using AI-powered analysis

docinfer

A Python package for extracting and inferring metadata from PDF documents using AI-powered analysis.

Features

• Extract metadata from PDF files
• AI-powered document analysis using LLMs
• CLI tool for easy batch processing
• Flexible configuration and output formatting
• Structured metadata models using Pydantic

Requirements

• Python 3.12 or higher
• Ollama - Required for AI-powered analysis
  • Install Ollama
  • Pull a model: ollama pull gemma3:4b
• See pyproject.toml for full Python dependency list

Installation

From GitHub Repository

pip install git+https://github.com/tidyeval/docinfer.git

From Local Development

Clone the repository and install in editable mode:

git clone https://github.com/tidyeval/docinfer.git
cd docinfer
pip install -e .

Quick Start

Using uvx (Recommended)

Run directly without installation using uvx:

uvx --from git+https://github.com/tidyeval/docinfer.git docinfer <path-to-pdf>

Note: Once published to PyPI, you'll be able to run uvx docinfer <path-to-pdf> directly.

CLI Usage

If you've installed the package locally, run directly:

docinfer <path-to-pdf>

Options

• --model MODEL - Specify the Ollama model (default: gemma3:4b)
  • Example: docinfer document.pdf --model gemma2
• --json - Output as JSON instead of formatted text
• --no-ai - Skip AI analysis and show embedded metadata only
• --export FILE - Export results to JSON file
• --quiet - Suppress progress output

Python API

from docinfer.services.pdf_extractor import PDFExtractor
from docinfer.services.ai_analyzer import AIAnalyzer

# Extract PDF content
extractor = PDFExtractor()
content = extractor.extract("document.pdf")

# Analyze with AI
analyzer = AIAnalyzer()
metadata = analyzer.analyze(content)

Project Structure

docinfer/
├── src/
│   ├── cli.py              # Command-line interface
│   ├── models/             # Pydantic data models
│   ├── services/           # Core services (PDF extraction, AI analysis)
│   └── prompts/            # AI prompt templates
├── tests/                  # Unit and integration tests
├── specs/                  # Project specifications
├── pyproject.toml          # Project configuration
└── README.md               # This file

Development

Setting up Development Environment

1. Clone the repository:

   git clone https://github.com/tidyeval/docinfer.git
   cd docinfer
   

2. Create and activate virtual environment:

   python -m venv .venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
   

3. Install in development mode:

   pip install -e ".[dev]"
   

Running Tests

pytest

Code Quality

The project uses:

• black for code formatting
• ruff for linting
• pytest for testing

Contributing

Contributions are welcome! Please ensure:

• Code passes linting and formatting checks
• Tests pass with good coverage
• Commit messages are descriptive

License

See LICENSE file for details.

Author

Tino Kanngiesser ([e-mail])