Gemini Image Demo Application

Gemini Image Demo is a Streamlit-based web application that utilizes Google's Gemini AI model to analyze and interpret images, specifically invoices, and generate relevant responses based on user input prompts.

Features

• User Input Prompt: Enter custom text prompts to guide the AI's analysis.
• Image Upload: Upload images in JPG, JPEG, or PNG formats for analysis.
• AI Analysis: Utilizes the Gemini AI model to process images and generate detailed responses.
• Responsive Interface: Real-time feedback with displayed images and AI-generated responses.

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/gemini-image-demo.git
   cd gemini-image-demo

2. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install dependencies:

   pip install -r requirements.txt

4. Set up environment variables:

   • Create a .env file in the root directory.
   • Add your Google API key:

     GOOGLE_API_KEY=your_google_api_key
     

Usage

1. Run the Streamlit app: ->bash streamlit run app.py

2. Open the app in your web browser:

   • Navigate to http://localhost:portnumber.
   • Input a prompt and upload an image (invoice).
   • Click "Tell me about the image" to get an AI-generated response.

Code Overview

• Configuration: Load environment variables and configure the Gemini AI model.
• Function to Load Model: Initialize the Gemini AI model and generate responses based on input.
• Image Upload: Handle uploaded images for AI analysis.
• Streamlit Interface: Setup user interface for prompt input and image upload.

Contributing

Contributions are welcome! Please feel free to submit issues, feature requests, or pull requests.

License

This project is licensed under the MIT License - see the LICENSE file for details.