--- title: Patient Feedback Analysis emoji: 🤒 colorFrom: purple colorTo: pink sdk: streamlit sdk_version: 1.37.1 app_file: app.py pinned: false --- # Patient Feedback Analysis ## Overview Patient Feedback Analysis is a Python-based project designed to provide a simple interface for users to analyse patient feedback data. The application allows users to upload a CSV file containing patient feedback data or input feedback manually. The feedback data is then analysed using a pre-trained model to determine the main topics, sentiments, and recommendations. The application is built using the Streamlit library and Hugging Face Inference API, together with a Llama-family model. ## Contents - `functions.py`: Contains various functions used in the project. - `config.py`: Configuration settings for the project. - `requirements.txt`: Lists the dependencies required to run the project. - `app.py`: The main application file. - `.gitignore`: Specifies files and directories to be ignored by git. - `.gitattributes`: Configuration for git attributes. ## Getting Started ### Prerequisites Ensure you have the following installed: - Python 3.x - pip (Python package installer) ### Installation 1. Clone the repository: 2. Navigate to the project directory: ```sh cd patient_feedback_analysis ``` 3. Install the required dependencies: ```sh pip install -r requirements.txt ``` ### Running the Application Run the main application file: ```sh streamlit run app.py ```