https://github.com/metalshanked/pdf-extractor
A Streamlit web application that extracts and displays metadata and text content from PDF files.
https://github.com/metalshanked/pdf-extractor
ai document llm pdf streamlit
Last synced: 4 months ago
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A Streamlit web application that extracts and displays metadata and text content from PDF files.
- Host: GitHub
- URL: https://github.com/metalshanked/pdf-extractor
- Owner: metalshanked
- License: mit
- Created: 2025-06-20T18:19:19.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-24T21:56:49.000Z (12 months ago)
- Last Synced: 2025-06-30T02:43:28.635Z (12 months ago)
- Topics: ai, document, llm, pdf, streamlit
- Language: Python
- Homepage: https://pdf-miner.streamlit.app/
- Size: 246 KB
- Stars: 2
- Watchers: 0
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# PDF Extractor
A Streamlit web application that extracts and displays metadata and text content from PDF files.
## Features
- **Upload Multiple PDFs**: Upload one or more PDF files through a simple interface
- **Extract Metadata**: Automatically extract all available metadata from each PDF
- **View PDF Content**: View the full text content of each PDF
- **Tab Navigation**: Easily navigate between multiple PDFs using tabs
- **Export to CSV**: Export all metadata to a CSV file for further analysis
- **Clean UI**: Streamlined user interface with custom styling
## Installation
### Prerequisites
- Python 3.7 or higher
- pip (Python package installer)
### Setup
1. Clone this repository:
```
git clone https://github.com/username/pdf-extractor.git
cd pdf-extractor
```
2. Install the required dependencies:
```
pip install -r requirements.txt
```
## Usage
### Running the Application
Run the application with the following command:
```
streamlit run pdf_extractor.py
```
For deployment with a custom base URL path:
```
streamlit run pdf_extractor.py --server.baseUrlPath="/pdf"
```
### Using the Application
1. **Upload PDF Files**:
- Click the "Choose PDF files" button in the sidebar
- Select one or more PDF files from your computer
2. **View Metadata**:
- The application will automatically extract and display metadata for each PDF
- Navigate between PDFs using the tabs at the top
3. **View PDF Content**:
- Click the "PDF DATA" expander to view the full text content of the PDF
4. **Export Metadata**:
- Use the "Export Metadata" button in the sidebar to download a CSV file
- Optionally include the full PDF text content in the export
## Docker Support
A Dockerfile is included for containerized deployment:
```
docker build -t pdf-extractor .
docker run -p 8501:8501 pdf-extractor
```
To run the application with a custom base URL path in Docker:
```
docker run -p 8501:8501 -e BASE_URL_PATH="/pdf" pdf-extractor
```
The BASE_URL_PATH environment variable is optional. If not specified, the application will run at the root path.
## Technical Details
### Dependencies
- **streamlit**: Web application framework
- **pdfminer.six**: PDF parsing and text extraction
- **pandas**: Data manipulation and CSV export
### Code Structure
- **pdf_extractor.py**: Main application file containing:
- PDF metadata extraction functions
- Text content extraction
- Streamlit UI components
- CSV export functionality
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## License
This project is licensed under the MIT License - see the LICENSE file for details.