---
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
```