| | --- |
| | title: PDF2Audio |
| | emoji: 📚 |
| | colorFrom: yellow |
| | colorTo: pink |
| | sdk: gradio |
| | sdk_version: 5.25.2 |
| | app_file: app.py |
| | pinned: false |
| | license: apache-2.0 |
| | --- |
| | |
| | # PDF to Audio Converter |
| |
|
| | This Gradio app converts PDFs into audio podcasts, lectures, summaries, and more. It uses OpenAI's GPT models for text generation and text-to-speech conversion. |
| |
|
| | ## Features |
| |
|
| | - Upload multiple PDF files |
| | - Choose from different instruction templates (podcast, lecture, summary, etc.) |
| | - Customize text generation and audio models |
| | - Select different voices for speakers |
| |
|
| | ## How to Use |
| |
|
| | 1. Upload one or more PDF files |
| | 2. Select the desired instruction template |
| | 3. Customize the instructions if needed |
| | 4. Click "Generate Audio" to create your audio content |
| |
|
| | ## Use in Colab |
| |
|
| | [](https://colab.research.google.com/github/lamm-mit/PDF2Audio/blob/main/PDF2Audio.ipynb) |
| |
|
| | ## Audio Example |
| |
|
| | <audio controls> |
| | <source src="https://raw.githubusercontent.com/lamm-mit/PDF2Audio/main/SciAgents%20discovery%20summary%20-%20example.mp3" type="audio/mpeg"> |
| | Your browser does not support the audio element. |
| | </audio> |
| |
|
| | ## Note |
| |
|
| | This app requires an OpenAI API key to function. |
| |
|
| | ## Credits |
| |
|
| | This project was inspired by and based on the code available at [https://github.com/knowsuchagency/pdf-to-podcast](https://github.com/knowsuchagency/pdf-to-podcast) and [https://github.com/knowsuchagency/promptic](https://github.com/knowsuchagency/promptic). |
| |
|
| | GitHub repo: [lamm-mit/PDF2Audio](https://github.com/lamm-mit/PDF2Audio) |
| |
|
| | ```bibtex |
| | @article{ghafarollahi2024sciagentsautomatingscientificdiscovery, |
| | title={SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoning}, |
| | author={Alireza Ghafarollahi and Markus J. Buehler}, |
| | year={2024}, |
| | eprint={2409.05556}, |
| | archivePrefix={arXiv}, |
| | primaryClass={cs.AI}, |
| | url={https://arxiv.org/abs/2409.05556}, |
| | } |
| | @article{buehler2024graphreasoning, |
| | title={Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph Reasoning}, |
| | author={Markus J. Buehler}, |
| | journal={Machine Learning: Science and Technology}, |
| | year={2024}, |
| | url={http://iopscience.iop.org/article/10.1088/2632-2153/ad7228}, |
| | } |
| | ``` |
| |
|
| |
|
