DEMO LINK [https://youtu.be/Ai991Ywr664]
project assignment from MERCOR [https://work.mercor.io/projects.html]
This project implements a semantic search engine that uses AI to search for product information based on user input. The search engine is implemented using Python and pandas, and uses a sentence_transformers model to match user queries to product descriptions.
The dataset used for this project is a Amazon ML challenge 2023 dataset [https://www.kaggle.com/datasets/ashisparida/amazon-ml-challenge-2023] a product catalog, which is stored in a CSV file named. The dataset contains information about over 2 million products, including their title, bullet points, description, product ID, product type ID, and product length. But to run this on our laptops efficiently I have dropped some of the tuples from the dataset,
To run this project, you'll need to install the following dependencies:
Python 3
sentence_transformers
Pandas
Tqdm
You can install these dependencies using pip, like so:
pip install sentence_transformers model pandas tqdm
The script will preprocess the user input and use the learning model to match it to product descriptions in the dataset. The script will then return a list of products that match the user query, along with their descriptions.