PythonAgentAI

The PythonAgentAI project aims to leverage advanced OpenAI models (including gpt-4o-mini with a 128k context window) to perform a variety of AI-powered tasks. This project integrates Scrapeless for Google Maps and the llama-index library (version 0.12.22) along with its experimental extensions to enable large language models to provide real-time responses.

Features

• Integration with OpenAI’s gpt-4o-mini model, supporting a 128k context window.
• Modular code structure including components like main.py, pdf.py, prompts.py, and note_engine.py.
• Advanced indexing and querying via llama-index and llama-index-experimental libraries.

Installation

Prerequisites

• Python 3.11 must be installed on your system. You can download it from the official Python website.

Configuration

1. Create the .env File

   The project requires a .env file for storing environment variables, including the OpenAI API key. You can create it by running:

   cp .env.example .env

2. Set Your OpenAI API Key

   Open the .env file in a text editor and configure your OpenAI API key:

   OPENAI_API_KEY=your_openai_api_key_here
   

   Replace your_openai_api_key_here with your actual API key from OpenAI.

• Log into Scrapeless and obtain your API token.

Setup Instructions

1. Clone the Repository

   Open your terminal and run:

   git clone https://github.com/your-username/PythonAgentAI.git
   cd PythonAgentAI

2. Create a Virtual Environment

   It's recommended to use a virtual environment to manage dependencies. To create one using Python's venv module:

   python3.11 -m venv env

3. Activate the Virtual Environment

   • On Unix or macOS:

     source env/bin/activate

   • On Windows:

     .\env\Scripts\activate

4. Install Dependencies

   With the virtual environment activated, install the required packages:

   pip install -r requirements.txt

   This will install the following essential packages:

   • llama-index==0.12.22
   • llama-index-experimental==0.5.4
   • pypdf==5.3.1
   • python-dotenv==1.0.1
   • pandas==2.2.3

Usage

After setting up the environment and installing the dependencies, you can run the main script:

python main.py

Ensure that you have configured any necessary environment variables or settings required by the script. Refer to the prompts.py and note_engine.py files for customizable parameters and functionalities.

2. Input the provided prompts to receive results. After a short wait, you’ll see output similar to the images below:

• Find the highest rated coffee shop within 0.5km

• Find the closest coffee shop to the target location