metadata

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.

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

Clone the repository:
Navigate to the project directory:
```
cd patient_feedback_analysis
```
Install the required dependencies:
```
pip install -r requirements.txt
```

Running the Application

Run the main application file:

streamlit run app.py

Spaces:

wilame
/

patient_feedback_analysis

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