update readme

README.md

@@ -8,11 +8,86 @@ sdk_version: 1.27.2
 app_file: app.py
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-**Description:**  
-An ***e-commerce chatBot*** which goes through the Amazon dataset products and suggests the most suitable goods according to the user needs.  
-By utilizing the power of product embeddings and large language models exploiting Langchain and Redis technologies alongside the open source sentence-transformer embedding model and Falcon LLM, this chatbot acts as a real salesperson, can understand the client's request and efficiently search for relevant product recommendations based on the user description and present them in an engaging and informative manner.  
-**link to download the Amazon product dataset** : https://drive.google.com/file/d/1tHWB6u3yQCuAgOYc-DxtZ8Mru3uV5_lj/view 
+# Shopping Buddy
+
+## Overview:
+
+This project leverages [Falcon LLM](https://falconllm.tii.ae/), [OpenAI](openai.com) API, [Sentence Transformer](https://www.sbert.net/docs/installation.html#install-sentencetransformers), [Hugging Face Hub](https://huggingface.co/) and [Streamlit](https://docs.streamlit.io/) to build and deploy a chatbot shopping assistant application that processes Amazon products dataset to provide tailored product recommendations aligned with user's needs. The application uses [Langchain](https://www.langchain.com/) to integrate those diverse functionalities. Data preprocessing, embedding generation, and storage in Redis are also essential components of this project.
+More details about the project are provided in [this blog post](insertalink.com).
+
+## Table of Contents
+
+- [Shopping Buddy](#shopping-buddy)
+  * [Overview](#overview)
+  * [Installation & Setup](#installation--setup)
+    + [1. Clone the Repository](#1-clone-the-repository)
+    + [2. Install Dependencies](#2-install-dependencies)
+    + [3. Environment Variables](#3-environment-variables)
+    + [4. Data Preprocessing](#4-data-preprocessing)
+  * [Running the Application](#running-the-application)
+  * [Contributing](#contributing)
+
+
+## Installation & Setup
+
+### 1. Clone the Repository
+
+```bash
+git clone git@github.com:romaissaMe/shopping-buddy.git
+cd shopping-buddy
+```
+
+### 2. Install Dependencies
+
+```bash
+pip install -r requirements.txt
+```
+
+### 3. Environment Variables
+
+Set up your environment variables. This project uses the `dotenv` library to manage environment variables. Create a `.env` file in the root directory:
+```bash
+cp .env_example .env
+```
+
+and add the following variables:
+
+```bash
+HUGGINGFACEHUB_API_TOKEN=your_huggingface_api_token
+OPENAI_API_KEY=your_openai_api_key
+REDIS_HOST=your_redis_host
+REDIS_PORT=your_redis_port
+REDIS_KEY=your_redis_key
+```
+
+### 4. Data Preprocessing
+
+Before running the main application, preprocess and import your data into a database using:
+
+```bash
+python preprocess.py
+```
+[data_link](https://drive.google.com/file/d/1tHWB6u3yQCuAgOYc-DxtZ8Mru3uV5_lj/view)
+
+## Running the Application
+
+Once the setup is complete, you can run the main application using:
+
+```bash
+streamlit run app.py
+```
+
+This will launch the Streamlit application, and you can access the chatbot via the provided URL.
 
 <img
-  src="./display.png"
+  src="./ShoppingBudddy.png"
   style="display: inline-block;margin: 0 auto ; max-width:400px">
+
+## Contributing
+
+If you're looking to contribute to this project, kindly follow the standard GitHub workflow:
+
+1. Fork the repository.
+2. Create a new branch for your feature or fix.
+3. Commit your changes and open a pull request.
+4. Ensure that your code adheres to the project's style and standards.