CSV-LLM

CSV-LLM is an innovative language model (LLM) tool designed to interact with CSV files using LangChain agents. This tool enables users to leverage advanced natural language processing techniques to query, analyze, and manipulate data stored in CSV formats directly. Whether you are conducting data analysis, managing datasets, or integrating language model capabilities into your CSV workflows, CSV-LLM provides a user-friendly and powerful interface for all your data needs.

Prerequisites

Before you begin, ensure you have met the following requirements:

• Python Version: This application is developed and tested with Python 3.9. Ensure that you have Python 3.9 installed on your machine. You can download Python 3.9 from here.

Installation

To get a local copy up and running, follow these simple steps:

1. Clone the repository:

   git clone https://github.com/penguyen72/csv-llm.git

2. Install the necessary dependencies:

   pip install -r requirements.txt

3. Set up your environment variables:

   • Copy the .env.example file to a new file named .env
   • Modify the .env file with your settings

Getting Started

Here's how to get started with the application:

streamlit run main.py

What is .env.example?

The .env.example file is a template containing all the necessary environment variables required for the project. It serves as a guideline for setting up your own .env file. Simply copy .env.example to .env and fill in your specific details to get started

Motivation

Trying to learn LangChain Agents. Followed a tutorial by Alejandro AO.