Update README.md

README.md

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 ---
 title: Eden Multimodal
-emoji: 🐢
-colorFrom: green
+emoji: 🏆
+colorFrom: blue
 colorTo: gray
 sdk: gradio
 sdk_version: 5.1.0
 app_file: app.py
-pinned: false
+pinned: true
+license: mit
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Eden Multimodal 
+[![Hugging Face Spaces](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue)](https://huggingface.co/spaces) [![Gradio](https://img.shields.io/badge/Gradio-5.1.0-orange)](https://gradio.app/)
+
+## Overview
+
+Eden Multimodal is an innovative project that leverages the power of multimodal AI to create a unique and interactive experience. It processes and analyzes text, image, and audio inputs to provide comprehensive insights. This application is hosted on **Hugging Face Spaces** and utilizes the **Gradio** framework for its user interface.
+
+## Features
+
+- **Multimodal AI Processing**: Simultaneous handling of text, image, and audio data.
+- **Interactive Interface**: User-friendly interface powered by Gradio.
+- **Real-time Analysis**: Provides instant feedback and results.
+- **Scalable and Extensible**: Modular code structure for easy expansion.
+
+## Technical Details
+
+### Project Structure
+
+The project is organized as follows:
+eden-multimodal/
+├── app.py
+├── models/
+│ ├── text_model.py
+│ ├── image_model.py
+│ ├── audio_model.py
+├── utils/
+│ ├── preprocessor.py
+│ ├── postprocessor.py
+├── requirements.txt
+└── README.md
+
+### Code Breakdown
+
+**Key Components:**
+
+- **Model Initialization**: Loads and prepares the text, image, and audio models located in the `models/` folder. These models are responsible for processing their respective data types.
+
+- **Preprocessing Functions**: Contains functions from `utils/preprocessor.py` that clean and format user inputs before they are fed into the models. This ensures compatibility and improves model performance.
+
+- **Main Processing Functions**: Defines functions that handle the core logic of the application. These functions take preprocessed inputs, pass them through the appropriate models, and generate outputs.
+
+- **Postprocessing Functions**: Utilizes functions from `utils/postprocessor.py` to refine and format the model outputs, making them suitable for display in the user interface.
+
+- **Gradio Interface Setup**: Configures the Gradio interface components, specifying input and output types for text, images, and audio. It also designs the layout and appearance of the web application.
+
+- **User Interaction Handlers**: Implements callbacks and event handlers that respond to user inputs in real-time, ensuring a seamless interactive experience.
+
+- **Application Launch Code**: Contains the `if __name__ == "__main__":` block that launches the Gradio app, allowing users to access the application via a web browser.
+
+**Role of Key Modules:**
+
+- **Projection Layer**: Although not explicitly named in `app.py`, if a projection layer is used within the models, it serves as a dimensionality reduction step, transforming high-dimensional data into a lower-dimensional space while preserving essential features. This is crucial for improving computational efficiency and focusing on the most relevant data aspects.
+
+- **Integration with Models**: `app.py` acts as the orchestrator, integrating text, image, and audio models into a cohesive system. It ensures that each model receives the correct input and that their outputs are combined or presented appropriately.
+
+- **Scalability Considerations**: The modular structure in `app.py` allows for easy addition of new modalities or models. By abstracting functionalities into separate functions and leveraging modules from `models/` and `utils/`, the code remains clean and maintainable.
+
+**Summary of Functioning:**
+
+- **Input Reception**: Accepts user inputs in the form of text, images, or audio through the Gradio interface.
+
+- **Data Processing Pipeline**:
+  1. **Preprocessing**: Cleans and prepares inputs.
+  2. **Model Prediction**: Processes inputs using the appropriate modality-specific model.
+  3. **Postprocessing**: Formats and refines the outputs.
+
+- **Output Presentation**: Displays the results back to the user in an intuitive and informative manner.
+
+Overall, `app.py` is the central hub of the Eden Multimodal application, managing the flow of data from user input to model processing and finally to output presentation.
+
+## Installation and Usage
+
+To run this project locally:
+
+1. **Clone the repository:**
+   ```bash
+   git clone https://github.com/yourusername/eden-multimodal.git
+   cd eden-multimodal
+   ```
+
+2. **Install the required dependencies:**
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+3. **Run the application:**
+   ```bash
+   python app.py
+   ```
+
+4. **Access the application:**
+   Open your web browser and navigate to `http://localhost:7860` to interact with the application.
+
+## Deployment
+
+This project is designed to be deployed on **Hugging Face Spaces**. The configuration specified in the YAML front matter of the `README.md` is used by Hugging Face to set up the environment and run the application.
+
+**Steps to Deploy:**
+
+1. **Push the repository to GitHub** (or another Git hosting service).
+2. **Create a new Space on Hugging Face Spaces** and select Gradio as the SDK.
+3. **Link your repository** to the new Space.
+4. The application will automatically build and deploy using the provided configuration.
+
+## Contributing
+
+Contributions to Eden Multimodal are welcome! Please follow these steps:
+
+1. **Fork the repository** to your own GitHub account.
+2. **Create a new branch** for your feature or bug fix:
+   ```bash
+   git checkout -b feature/your-feature-name
+   ```
+3. **Commit your changes** with clear messages:
+   ```bash
+   git commit -m "Add feature X"
+   ```
+4. **Push to your branch:**
+   ```bash
+   git push origin feature/your-feature-name
+   ```
+5. **Create a Pull Request** on the main repository.
+
+## License
+
+[Specify your license here, e.g., MIT, GPL, etc.]
+
+---
+
+For more information on configuring Hugging Face Spaces, please refer to the [official documentation](https://huggingface.co/docs/hub/spaces-config-reference).