---
title: LSI
emoji: 📊
colorFrom: blue
colorTo: indigo
sdk: streamlit
sdk_version: 1.40.1
app_file: app.py
pinned: false
---
# **Car Search Engine Based on LSI (Latent Semantic Indexing)**

## **Description**
This interactive search engine uses the **LSI (Latent Semantic Indexing)** algorithm to search for cars based on keywords provided by the user. It is designed to explore a car dataset and display the most relevant results based on the search query.

The application presents results in card format, including details such as the car model, year, price, and a link for more information.

---

## **Features**
- Search for cars using keywords (e.g., "Peugeot Diesel Manual").
- Displays relevant results using advanced natural language processing techniques.
- Interactive user interface developed with **Streamlit**.
- Results pagination with cards.

---

## **How to Use the Application**
1. Enter your search query in the input field.
2. Use the slider to set the number of results to display per page.
3. Click on the **Search** button.
4. Navigate between result pages using the **Previous Page** and **Next Page** buttons.

---

## **Installation and Dependencies**
To run this application locally, you will need **Python** and the following libraries:
- **Streamlit**: For the user interface.
- **scikit-learn**: For LSI algorithms and similarity calculations.
- **pandas**: For dataset manipulation.

### **Installation Steps**
1. Clone the repository:
   ```bash
   git clone https://huggingface.co/spaces/sanaa-11/LSI
   cd your-app-repository
   
2-Install the required dependencies:
   ```bash
    pip install -r requirements.txt

3 - Run the application:

   ```bash
   streamlit run app.py

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference