Update README.md

README.md

@@ -1,8 +1,8 @@
 ---
-title: PDFtoPodcast
+title: Pdf2audio
 emoji: 📚
-colorFrom: blue
-colorTo: gray
+colorFrom: yellow
+colorTo: pink
 sdk: gradio
 sdk_version: 4.44.0
 app_file: app.py
@@ -10,4 +10,61 @@ pinned: false
 license: apache-2.0
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# 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
+
+[![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)
+
+## 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},
+}
+```
+