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title: Pdf2audio | |
emoji: 📚 | |
colorFrom: yellow | |
colorTo: pink | |
sdk: gradio | |
sdk_version: 4.44.0 | |
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 | |
## 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). | |
```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}, | |
} | |
``` | |