GoogleReviewsAI

A Python application for Windows that automates the process of responding to Google Business reviews using AI-generated responses. The application uses OpenAI's API with a fine-tuned model to generate contextually appropriate responses based on your business policies.

Features

• Extracts Google Business reviews from Outscraper-generated Excel files
• Generates AI responses using a fine-tuned OpenAI model
• Provides a GUI interface for review management
• Allows manual review and editing of AI-generated responses
• Automatically posts responses to Google Business reviews
• Supports background processing for seamless operation

Prerequisites

• Python 3.8+
• Google Chrome browser
• Windows OS
• OpenAI API access with a fine-tuned model
• Chrome profile with access to your Google Business account
• Outscraper.com account

Installation

1. Clone the repository:

git clone https://github.com/yourusername/GoogleReviewsAI.git
cd GoogleReviewsAI

2. Install required packages:

pip install -r requirements.txt

3. Create a .env file in the project root with the following structure:

# OpenAI API key for your fine-tuned model
OPENAI_API_KEY=your-api-key-here

# Chrome user profile path for Selenium
profile_path=C:\\Users\\YourUsername\\AppData\\Local\\Google\\Chrome\\User Data

# Chrome profile directory
profile_directory=Default

# Excel file download path (usually your Downloads folder)
Ruta_Archivo_Excel=C:\\Users\\YourUsername\\Downloads

Outscraper Configuration

1. Create an account at Outscraper.com

2. Set up a new scraping task for your Google Business reviews

3. Important: Select ALL available columns when configuring the export

4. Required columns for the script:

   • review_text
   • owner_answer
   • author_title
   • review_rating
   • review_datetime_utc
   • review_link
   • reviews_link
   • name
   • reviews
   • rating

5. Download the Excel file to the path specified in your .env file

Configuration

1. Setup your Chrome profile:

   • Make sure you're logged into your Google Business account
   • The profile path in .env should point to your Chrome user data directory

2. Fine-tune your OpenAI model:

   • Create a fine-tuned model with your business policies and response style
   • Update the model name in the code (currently set as "ft:gpt-3.5-turbo-1106:your-model-name")

Usage

1. Download your latest reviews from Outscraper.com
2. Run the application:

python main.py

3. The GUI will display:

   • Business information from the Outscraper export
   • Recent reviews
   • AI-generated responses
   • Options to edit responses
   • Buttons to navigate through reviews

4. For each review:

   • Review the AI-generated response
   • Edit if necessary
   • Click "Responder" to post the response
   • The response will be posted in the background

[Rest of the README remains the same...]

File Structure

GoogleReviewsAI/
├── main.py            # Main application file
├── requirements.txt   # Python dependencies
├── .env              # Environment variables
└── README.md         # Documentation

Dependencies

• wxPython: GUI framework
• pandas: Data manipulation
• selenium: Web automation
• openai: AI response generation
• python-dotenv: Environment variable management
• Additional dependencies listed in requirements.txt

Important Notes

• The application requires a logged-in Chrome profile with access to Google Business
• Responses are generated based on your fine-tuned model's training
• Background processing allows for continuous GUI interaction
• Excel files with reviews should be in the specified download directory

Security Considerations

• Keep your .env file secure and never commit it to version control
• Regularly update your API keys
• Use secure Chrome profiles
• Monitor API usage and costs

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request