pga-gpt-tools 0.1.0

A collection of tools for PGA AI products

PGA GPT Tools

A collection of tools for PGA AI projects. This repository contains various utilities designed to enhance automation and provide advanced AI capabilities for different applications.

Tools

• Generate Image: Create images from textual descriptions using the OpenAI DALL-E 3 model.
• Remove Background: Remove the background from images for better focus on the subject.
• Web Scrape: Scrape web content from given URLs and extract specific HTML elements.
• Web Search: Perform web searches using SerpAPI and return comprehensive search results.

Installation

Clone the repository and install dependencies using pipenv:

git clone https://github.com/pgahq/pga-gpt-tools.git
cd pga-gpt-tools
pipenv install

Environment Variables

To use the tools effectively, you need to set the following environment variables:

• SERPAPI_API_KEY: Your SerpAPI API key for web search.
• FIRECRAWL_API_KEY: Your FireCrawl API key for web scrape.
• OPENAI_API_KEY: Your OpenAI API key for image generation using DALL-E 3.
• FALAI_API_KEY: Your fal.ai API key for image transformations.

You can manage these environment variables by creating a .env file in the root of your project (for development environments) or setting them up in your CI/CD pipeline.

Example .env File

SERPAPI_API_KEY=your_serpapi_api_key_here
FIRECRAWL_API_KEY=your_firecrawl_api_key_here
OPENAI_API_KEY=your_openai_api_key_here
FALAI_API_KEY=your_falai_api_key_here

Load the .env file in your script using python-dotenv:

Loading Environment Variables

from dotenv import load_dotenv
import os

load_dotenv()

Loading Environment Variables from AWS SSM

Alternatively, you can load these environment variables directly from AWS SSM Parameters. Ensure you have the necessary permissions to access these SSM parameters.

Example SSM Helper

import boto3

def ssm_get(parameter_name):
    ssm = boto3.client('ssm')
    response = ssm.get_parameter(
        Name=parameter_name,
        WithDecryption=True
    )
    if 'Parameter' in response:
        if 'Value' in response['Parameter']:
            return response['Parameter']['Value']
    return None

Loading Environment Variables

import os
from src.helpers import ssm_get

os.environ['SERPAPI_API_KEY'] = ssm_get('/pga-gpt/serpapi_api_key')
os.environ['FIRECRAWL_API_KEY'] = ssm_get('/pga-gpt/firecrawl_api_key')
os.environ['OPENAI_API_KEY'] = ssm_get('/pga-gpt/openai_api_key')
os.environ['FALAI_API_KEY'] = ssm_get('/pga-gpt/falai_api_key')

Usage

Import All Tools

You can import all tools in a single statement:

from pga_gpt_tools import GenerateImage, RemoveBackground, WebScrape, WebSearch

Import Individual Tools

Generate Image

from pga_gpt_tools.generate_image import GenerateImage

tool = GenerateImage(prompt="A scenic view of mountains during sunset")
image_details = tool.run()
print(image_details)

Remove Background

from pga_gpt_tools.remove_background import RemoveBackground

tool = RemoveBackground(image_url="https://example.com/image.jpg")
result = tool.run()
print(result)

Web Scrape

from pga_gpt_tools.web_scrape import WebScrape

tool = WebScrape(url="https://www.example.com", element="title")
scraped_content = tool.run()
print(scraped_content)

Web Search

from pga_gpt_tools.web_search import WebSearch

tool = WebSearch(query="PGA Championship 2023")
search_results = tool.run()
print(search_results)

Development

Setting Up

First, clone the repository and navigate into the project directory:

git clone https://github.com/pgahq/pga-gpt-tools.git
cd pga-gpt-tools

Installing Dependencies

Install dependencies using pipenv:

pipenv install

Running Tests

Run tests to ensure everything is working correctly:

pipenv run pytest

Contributing

We welcome contributions from the community! To contribute:

1. Create a new branch (git checkout -b my-feature-branch).
2. Make your changes and commit them (git commit -am 'Add new feature').
3. Push the feature branch to origin (git push origin my-feature-branch).
4. Create a new Pull Request into main.

Guidelines

• Ensure your code follows the PEP 8 style guide.
• Write tests for any new features or changes.
• Make sure all tests pass before submitting a PR.

Continuous Integration and Deployment

This repository uses CircleCI for continuous integration and deployment. Packages are automatically deployed to PyPI when PRs are merged into the main branch.