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---
title: Sentiment Analysis on Encrypted Data Using Fully Homomorphic Encryption
emoji: 🥷💬
colorFrom: yellow
colorTo: yellow
sdk: gradio
sdk_version: 3.2
app_file: app.py
pinned: true
tags: [FHE, PPML, privacy, privacy preserving machine learning, homomorphic encryption, security]
python_version: 3.9
---
# Sentiment Analysis With FHE
## Running the application on your machine
In this directory, ie `sentiment-analysis-with-transformer`, you can do the following steps.
### Do once
- First, create a virtual env and activate it:
```bash
python3.9 -m venv .venv
source .venv/bin/activate
```
- Then, install required packages:
```bash
pip3 install -U pip wheel setuptools --ignore-installed
pip3 install -r requirements.txt --ignore-installed
```
- If not on Linux, or if you want to compile the FHE algorithms by yourself:
```bash
python3 compile.py
```
Check it finish well (with a "Done!").
### Do each time you relaunch the application
- Then, in a terminal Tab 1:
```bash
source .venv/bin/activate
uvicorn server:app
```
Tab 1 will be for the Server side.
- And, in another terminal Tab 2:
```bash
source .venv/bin/activate
python3 app.py
```
Tab 2 will be for the Client side.
## Interacting with the application
Open the given URL link (search for a line like `Running on local URL: http://127.0.0.1:8888/` in your Terminal 2).
## Training a new model
The notebook SentimentClassification.ipynb provides a way to train a new model.
Before running the notebook, you need to download the data.
```bash
bash download_data.sh
```
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