docs: add detailed README with installation instructions

Author: Nigma-Ks

README.md

@@ -1,2 +1,71 @@
 # PySymBench
-Infrastructure for models comparison and evalustion
+Infrastructure for **model comparison and evaluation in symbolic execution workflows**.
+
+This project is a **local web application** designed to compare symbolic execution results of an uploaded trained model (in `.onnx` format) on a selected dataset with a **baseline symbolic execution approach (non-AI)**.
+
+The system uses **PySymGym tools** to run symbolic execution on the dataset and evaluate the results. After execution completes, the results are sent to the **email address you provide**.
+
+# Installation
+
+The repository contains **both frontend and backend components**, and **both must be launched** for the application to work.
+
+---
+
+## Email Communication (Gmail)
+
+To enable email delivery of results, create a `.env` file containing your Gmail credentials:
+
+```
+EMAIL=your_email@gmail.com
+APP_PASSWORD=your_app_password
+```
+
+`EMAIL` — your Gmail address  
+`APP_PASSWORD` — your Gmail **App Password** (not your regular account password)
+
+---
+
+## Backend Setup
+
+1. Install **Python 3.14** and **Docker**, then install the project dependencies:
+
+```
+pip install -r requirements.txt
+```
+
+2. Run the application setup script (this builds a Docker container with the **PySymGym repository** and downloads the required dataset):
+
+```
+python -m backend.launch_service.app_setup
+```
+
+3. Start the **Celery broker (Redis)**:
+
+```
+docker run --name redis-for-celery -p 6379:6379 -d redis
+```
+
+4. Start the **Celery worker** and the **application server**:
+
+```
+celery -A backend.utils.task worker --loglevel=info && uvicorn backend.main:app
+```
+
+---
+
+## Frontend Setup
+
+1. Install **Node.js** with **npm**.
+
+2. Install frontend dependencies:
+
+```
+cd frontend
+npm install
+```
+
+3. Start the frontend development server:
+
+```
+npm run build
+```