AtliQ Brand Store Stocke Management Using LangChain LLM

https://brandstorellm.streamlit.app/

Overview

The AtliQ Brand Store Management Database Q&A Tool is a web application designed to provide users with a convenient way to interact with a clothing store database. Developed by Shubham Khairmode, this project leverages a powerful stack of technologies, including Google Cloud APIs, GoogleMakesuite API, GooglePalm, Google-GenerativeAI, Streamlit, Flask, and a MySQL database. It offers users the ability to ask questions related to the clothing inventory and receive informative responses.

Key Features

• Intuitive Querying: Users can simply type questions in natural language, and the tool interprets and processes these queries to extract meaningful information from the database.

• Fast Response Times: The tool employs advanced language models and efficient data processing to provide quick and accurate answers to user queries.

• Informative Answers: Users receive detailed responses, including relevant data and explanations, ensuring a thorough understanding of the queried information.

• Modern User Interface: The tool features a user-friendly interface powered by Streamlit and Flask, making it easy for users to interact with the database.

Technologies Used

1. GoogleMakesuite API: This API is employed to access Google's suite of cloud services, which provides essential functionality for the project, including language processing and data retrieval.

2. GooglePalm: GooglePalm is a powerful language model from Google that assists in processing user queries and generating informative responses.

3. Google-GenerativeAI: This technology, likely associated with Google, contributes to the generation of human-like text, which is crucial for providing detailed answers to user queries.

4. Streamlit: The web application's user interface is built using Streamlit, a popular Python library for creating interactive and user-friendly data applications.

5. Flask: Flask is used as a web framework for routing and handling user requests, allowing for a smooth user experience.

6. MySQL Database: The project integrates with a MySQL database to store and manage the clothing store's inventory data.

Prerequisite

• langchain
• streamlit

Create the Environment

conda create -p venv python=3.10 -y

Activate the environment

conda activate venv/

Install the requirements

pip install -r requirements.txt

create the GooglePalm API key

1. Login you gmail account in

• makersuite

  GET GooglePalm API

Parameter	Type	Description
api_key	string	Required. Your API key

create the api key and copy paste in your .env file

    GOOGLE_API_KEY = 'Your API key'

run the app

using streamlit

  streamlit run main.py

using Flask

  python app.py

Database

For sql data contact me on Linkedin

• Linkedin

Contact

• Developer: Shubham Khairmode
• Email: [email protected]

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