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@@ -9,62 +9,5 @@ app_file: app.py
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  license: apache-2.0
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- # PDF to Audio Converter
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-
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- 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.
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-
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- ## Features
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-
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- - Upload multiple PDF files
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- - Choose from different instruction templates (podcast, lecture, summary, etc.)
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- - Customize text generation and audio models
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- - Select different voices for speakers
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-
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- ## How to Use
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-
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- 1. Upload one or more PDF files
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- 2. Select the desired instruction template
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- 3. Customize the instructions if needed
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- 4. Click "Generate Audio" to create your audio content
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-
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- ## Use in Colab
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-
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- [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lamm-mit/PDF2Audio/blob/main/PDF2Audio.ipynb)
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-
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- ## Audio Example
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-
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- <audio controls>
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- <source src="https://raw.githubusercontent.com/lamm-mit/PDF2Audio/main/SciAgents%20discovery%20summary%20-%20example.mp3" type="audio/mpeg">
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- Your browser does not support the audio element.
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- </audio>
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-
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- ## Note
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- This app requires an OpenAI API key to function.
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-
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- ## Credits
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-
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- 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).
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- GitHub repo: [lamm-mit/PDF2Audio](https://github.com/lamm-mit/PDF2Audio)
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-
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- ```bibtex
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- @article{ghafarollahi2024sciagentsautomatingscientificdiscovery,
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- title={SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoning},
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- author={Alireza Ghafarollahi and Markus J. Buehler},
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- year={2024},
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- eprint={2409.05556},
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- archivePrefix={arXiv},
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- primaryClass={cs.AI},
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- url={https://arxiv.org/abs/2409.05556},
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- }
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- @article{buehler2024graphreasoning,
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- title={Accelerating Scientific Discovery with Generative Knowledge Extraction, Graph-Based Representation, and Multimodal Intelligent Graph Reasoning},
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- author={Markus J. Buehler},
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- journal={Machine Learning: Science and Technology},
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- year={2024},
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- url={http://iopscience.iop.org/article/10.1088/2632-2153/ad7228},
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- }
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- ```
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  license: apache-2.0
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  ---
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+ $$$ Money $$$
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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