naveentnj/electric-vehicle-db-query-response-with-palm-and-langchain

Web App developed to query the SQL Database which stores Electric vehicle information using PaLM LLM with Langchain tools for prompt engineering

Electric-Vehicle-DB-Query-Response-with-PaLM-and-Langchain

Web App developed to query the SQL Database which stores Electric vehicle information using PaLM LLM with Langchain tools for prompt engineering

Nav EV Cars: Query to a Database

This is an end to end LLM project based on Google Palm and Langchain. We are building a system that can talk to MySQL database. User asks questions in a natural language and the system generates answers by converting those questions to an SQL query and then executing that query on MySQL database. Nav EV Cars is a EV Cars showroom where they maintain their inventory, sales and discounts data in Microsoft SQL database. A store manager will may ask questions such as,

• How many white color Adidas t shirts do we have left in the stock?
• How much sales our store will generate if we can sell all extra-small size t shirts after applying discounts? The system is intelligent enough to generate accurate queries for given question and execute them on MySQL database

Project Highlights

• Nav EV is a multi brand car showroom that sells Tesla, Tata, Mahindra, Vel, Ford, Amigo electric cars
• Their inventory, sales and discounts data is stored in a MySQL database
• We will build an LLM based question and answer system that will use following,
  • Google Palm LLM
  • Hugging face embeddings
  • Streamlit for UI
  • Langchain framework
  • FAISS as a vector store
  • Few shot learning
• In the UI, store manager will ask questions in a natural language and it will produce the answers

Installation

1.Clone this repository to your local machine using:

  git clone https://github.com/naveentnj/Electric-Vehicle-DB-Query-Response-with-PaLM-and-Langchain.git

2.Navigate to the project directory:

2. Install the required dependencies using pip:

  pip install -r requirements.txt

3.Acquire an api key through makersuite.google.com and put it in .env file

  GOOGLE_API_KEY="your_api_key_here"

4. For database setup, run database/db_creation_atliq_t_shirts.sql in your MySQL workbench

Usage

1. Run the Streamlit app by executing:

streamlit run main.py

2.The web app will open in your browser where you can ask questions

Sample Questions

• How many ev_cars do we have left for Tata in premium_customized model and white color??
• How much is the total price of the inventory for all base-model evcars?
• How much sales amount will be generated if we sell all small size adidas shirts today after discounts?

Project Structure

• main.py: The main Streamlit application script.
• langchain_helper.py: This has all the langchain code
• requirements.txt: A list of required Python packages for the project.
• few_shots.py: Contains few shot prompts
• .env: Configuration file for storing your Google API key.