CSV Analysis Chatbot

Table of Contents

1. Introduction
2. Project Overview
3. Features
4. Installation
5. Requirements
6. Setup
7. Usage
8. Troubleshooting
9. Contributing
10. License

Introduction

Welcome to the CSV Analysis Chatbot project! This project aims to provide a user-friendly interface for analyzing CSV files using a chatbot. The chatbot uses natural language processing (NLP) to understand user queries and provides relevant results based on the data in the CSV file.

Project Overview

The CSV Analysis Chatbot project is built using the following technologies:

• Gradio: A Python library for building web-based interfaces for machine learning models.
• Langchain: A Python library for building conversational AI models.
• OpenRouter: A cloud-based API for NLP tasks.

The project consists of the following components:

• CSV Chatbot: A Gradio-based interface for uploading CSV files and interacting with the chatbot.
• Agent: A Langchain-based model that uses NLP to understand user queries and provide relevant results.
• OpenRouter API: A cloud-based API that provides NLP capabilities for the agent.

Features

The CSV Analysis Chatbot project offers the following features:

• CSV File Upload: Users can upload CSV files to the chatbot.
• Natural Language Queries: Users can ask natural language queries about the data in the CSV file.
• Relevant Results: The chatbot provides relevant results based on the user's query.
• Visualization: The chatbot can provide visualizations of the data in the CSV file.

Installation

To install the CSV Analysis Chatbot project, follow these steps:

Requirements

• Python 3.8 or higher: The project requires Python 3.8 or higher to run.
• Gradio: The project requires Gradio to build the web-based interface.
• Langchain: The project requires Langchain to build the conversational AI model.
• OpenRouter API Key: The project requires an OpenRouter API key to use the NLP capabilities.

Setup

1. Install Python: Install Python 3.8 or higher from the official Python website.
2. Install Gradio: Install Gradio using pip: pip install gradio.
3. Install Langchain: Install Langchain using pip: pip install langchain.
4. Get OpenRouter API Key: Sign up for an OpenRouter API key on the OpenRouter website.
5. Clone the Repository: Clone the CSV Analysis Chatbot repository using Git: git clone https://github.com/username/csv-analysis-chatbot.git.
6. Install Dependencies: Install the dependencies required by the project using pip: pip install -r requirements.txt.
7. Set Environment Variables: Set the OPENROUTER_API_KEY environment variable to your OpenRouter API key.

Usage

1. Run the Chatbot: Run the chatbot using the following command: python app.py.
2. Upload CSV File: Upload a CSV file to the chatbot using the Gradio interface.
3. Ask Queries: Ask natural language queries about the data in the CSV file.
4. View Results: View the relevant results provided by the chatbot.

Output

Troubleshooting

If you encounter any issues while running the project, refer to the following troubleshooting steps:

• Check Environment Variables: Ensure that the OPENROUTER_API_KEY environment variable is set correctly.
• Check Dependencies: Ensure that all dependencies required by the project are installed correctly.
• Check CSV File: Ensure that the CSV file is uploaded correctly and is in the correct format.

Contributing

If you'd like to contribute to the CSV Analysis Chatbot project, follow these steps:

• Fork the Repository: Fork the CSV Analysis Chatbot repository using Git.
• Make Changes: Make changes to the project code.
• Submit a Pull Request: Submit a pull request to the original repository.

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