by atoy0m0 · v1.0.1
Convert PDF pages to images using PyMuPDF. Cloud/Docker compatible. Supports v1.4.3 and later.
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Available inside your emploidai workspace after installation.
Available inside your emploidai workspace after installation.
PDF to Images is a powerful Dify plugin that converts PDF files to high-quality images using PyMuPDF. It enables seamless integration of PDF processing capabilities into your AI applications, making it easy to extract visual information from documents for further analysis by LLM vision models. Perfect for document processing workflows that need to analyze visual content, forms, diagrams, and charts.
If you can't find the file input palamater, please update dify to latest version. please use Dify v1.6.0 or later when running this plugin.
I hope files in /docs will help you.
To set up the PDF to Images plugin, follow these steps:
Install PDF to Images Plugin
No Authentication Required
Ready to Use
The PDF to Images tool provides three configurable parameters:
PDF Files: Select one or multiple PDF files to convert to images.
DPI (Dots Per Inch): Control output image quality and file size.
Image Format: Choose between PNG and JPEG output formats.
The plugin automatically handles different file input methods:
PDF to Images can be seamlessly integrated into both Chatflow / Workflow Apps and Agent Apps.
Integrate PDF to Images into your pipeline by following these steps:
The plugin can handle multiple PDF files simultaneously, processing them sequentially for stability while providing detailed progress information.
Supports various file input methods:
Each converted image includes comprehensive metadata:
| Aspect | Specification | Notes |
|---|---|---|
| File Size Support | Limited by available RAM | No artificial size limits |
| Supported DPI Range | 72-300 DPI | Higher DPI = larger output files |
| Concurrent Processing | Sequential | Ensures memory stability |
For detailed development setup, deployment instructions, troubleshooting, and advanced configuration options, please refer to the Plugin Deployment Guide.
This project is licensed under the MIT License - see the LICENSE file for details.
For support, bug reports, or feature requests: