Update README.md

README.md

@@ -1,14 +1,69 @@
 ---
 title: AQuaBot
-emoji: 🚀
-colorFrom: indigo
-colorTo: pink
+emoji: 💧
+colorFrom: blue
+colorTo: green
 sdk: gradio
-sdk_version: 5.4.0
+sdk_version: 5.3.0
 app_file: app.py
 pinned: false
-license: apache-2.0
-short_description: Assistant that helps raise awareness about water consumption
+accelerator: gpu
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# AQuaBot - AI Water Consumption Awareness Chat
+
+AQuaBot is an artificial intelligence assistant that helps raise awareness about water consumption in large language models while providing helpful responses to user queries. It uses Microsoft's Phi-1 model and tracks water consumption in real-time during conversations.
+
+## Author
+**Camilo Vega Barbosa**
+- AI Professor and Artificial Intelligence Solutions Consultant
+- Connect with me:
+  - [LinkedIn](https://www.linkedin.com/in/camilo-vega-169084b1/)
+  - [GitHub](https://github.com/CamiloVga)
+
+## Features
+- Real-time water consumption tracking for each interaction
+- Interactive chat interface using Gradio
+- Water usage calculations based on academic research
+- Educational information about AI's environmental impact
+
+## How It Works
+The application calculates water consumption based on the research paper "Making AI Less Thirsty: Uncovering and Addressing the Secret Water Footprint of AI Models" by Li, P. et al. (2023). It tracks both:
+- Water consumption during training per token
+- Water consumption during inference per token
+
+For each interaction, the application calculates:
+1. Water consumption for input tokens
+2. Water consumption for output tokens
+3. Total accumulated water usage
+
+## Technical Details
+- **Model**: Meta-llama/Llama-2-7b-hf
+- **Framework**: Gradio
+- **Dependencies**: Managed through `requirements.txt`
+- **Device Configuration**: Automatically detects GPU availability and assigns appropriate device
+- **Optimization**: Configured for efficient running on Hugging Face Spaces
+
+## Citation
+```
+Li, P. et al. (2023). Making AI Less Thirsty: Uncovering and Addressing the Secret 
+Water Footprint of AI Models. ArXiv Preprint, https://arxiv.org/abs/2304.03271
+```
+
+## Installation
+To run this application locally:
+1. Clone the repository
+2. Install dependencies:
+   ```bash
+   pip install -r requirements.txt
+   ```
+3. Run the application:
+   ```bash
+   python app.py
+   ```
+
+## Note
+This application uses Phi-2 model instead of GPT-3 for availability and cost reasons. However, the water consumption calculations per token (input/output) are based on the conclusions from the cited research paper.
+
+---
+Created by Camilo Vega Barbosa, AI Professor and Solutions Consultant. For more AI projects and collaborations, feel free to connect on [LinkedIn](https://www.linkedin.com/in/camilo-vega-169084b1/) or visit my [GitHub](https://github.com/CamiloVga).