🤖 GPT PDF Processor 📚

A Python application that extracts text from PDF documents and processes it using OpenAI's GPT models to answer questions about the document content.

🔎 Overview

This application provides a simple interface to:

1. 📄 Extract text from PDF documents
2. 🧠 Process the text using LangChain and OpenAI's GPT models
3. ❓ Ask questions about the document contents and receive AI-generated answers

👨‍🏫 Attribution

This code was originally created by Professor Daniel Cavalieri and adapted by Paulo Sergio dos Santos Júnior.

✅ Prerequisites

• 🐍 Python 3.6+
• 🔑 OpenAI API key

💻 Installation

1. Clone the repository:

git clone https://github.com/paulossjunior/OpenAIandPDF.git
cd OpenAIandPDF

2. Install required dependencies:

pip install -r requirements.txt

3. Create a .env file in the root directory with your OpenAI API key:

OPENAI_API_KEY=your_openai_api_key_here

🚀 Usage

1. Place your PDF file in the project directory or specify the path in the code.
2. Run the main program:

python program_gpt.py

3. The program will:
   • 🔐 Load your OpenAI API key from the .env file
   • 📝 Process the PDF file specified in the code (default: "edital.pdf")
   • 🧩 Ask a predefined question about the document ("Qual o objetivo do Edital")
   • 📊 Print the answer from GPT

⚙️ Customization

To ask different questions, modify the send_question parameter in program_gpt.py:

answer = gpt.send_question("Your question here")

To use a different PDF file, change the pdf_path variable:

pdf_path = "your_document.pdf"

📁 Project Structure

• program_gpt.py: Main entry point for the application
• fapes_gpt.py: Contains the GPT class with methods for processing PDFs and interacting with the OpenAI API

✨ Features

• 📄 PDF text extraction
• 🔌 Integration with OpenAI's GPT models (default: gpt-4o-mini)
• 🧩 Simple API for asking questions about document content
• 🔒 Environment variable support for secure API key storage

⚠️ Known Issues

• The code has an error in the __create_chain method, where the chain assignment is missing.
• The private methods __create_prompt, __chunkify_txt, and __get_vector are defined but not used in the current workflow.