Directory Reader with LlamaIndex

A Python application that reads documents from a local directory and answers questions about their content using OpenAI's GPT models and LlamaIndex.

Features

• Read multiple documents from a local directory
• Convert document content into vector embeddings
• Query documents with natural language questions
• Uses OpenAI's GPT for intelligent responses
• Support for various file formats

Prerequisites

• Python 3.8+
• OpenAI API key

Installation

1. Clone or download this project
2. Install dependencies:

pip install llama-index llama-index-core llama-index-llms-openai python-dotenv

Setup

1. Create a .env file in the project root:

OPENAI_API_KEY=your_api_key_here

2. Get your API key from OpenAI Platform

Usage

Run the script:

python directoryreader.py

How It Works

1. Reads all documents from the specified directory
2. Creates vector embeddings of the content
3. Builds a searchable index
4. Answers your query using OpenAI's GPT model

Configuration

Update the main() function with your directory path:

main(url=r"your_directory_path_here")

Rate Limits

• Free tier: 3 requests per minute
• Upgrade your OpenAI account for higher limits

License

MIT License - See LICENSE file for details