GeminiAPI Project

Overview

GeminiAPI is a web application that leverages the Google Generative AI to perform various tasks such as text translation, summarization, content creation, paraphrasing, and question answering. The application provides a user-friendly interface for inputting text, processing it through the AI model, and displaying the output.

Features

• Text Translation: Translate text using the Google Generative AI.
• Text Summarization: Summarize long pieces of text into concise summaries.
• Content Creation: Generate articles, blog posts, and other written content.
• Paraphrasing: Rephrase sentences or paragraphs to improve readability or avoid plagiarism.
• Question Answering: Provide answers to questions based on provided context.
• Character Count: Displays the character count of the input text.
• Custom Text Limit: Set a custom limit for the input text length.
• Copy to Clipboard: Copy the translated text to the clipboard with a single click.
• Loading Spinner: Visual feedback while the translation is being processed.

Prerequisites

• Docker
• Docker Compose
• Node.js

Installation

1. Clone the repository:

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

2. Set up environment variables: Create a .env file in the root directory and add the following variables:

   # Environment Variables
   
   # Your Gemini API key
   GEMINI_API_KEY=your_gemini_api_key
   
   # Model selection (fine-tuned or standard)
   GEN=your_model
   
   # Page title for the web interface
   PAGE_TITLE=Your Page Title
   
   # Page description for the web interface
   PAGE_DES=Your Page Description
   
   # Custom limit for input text length
   LIMIT=1000
   
   # Port number for the application
   PORT=37742
   
   # Temperature setting for the AI model (controls creativity)
   TEMP=0.7
   
   # Title for the input text box
   INP_TITLE=Input
   
   # Title for the output text box
   OUT_TITLE=Output

3. Build and run the Docker container:

   docker-compose up --build

Usage

1. Access the application: Open your web browser and navigate to http://localhost:37742.

2. Process text:

   • Enter the text you want to process in the input box.
   • Click the "Process" button to perform the selected task (e.g., translation, summarization, content creation, paraphrasing, or question answering).
   • The processed text will be displayed in the output box.

3. Copy processed text:

   • Click the "Copy" button to copy the processed text to the clipboard.

4. Clear input:

   • Click the "Clear" button to clear the input text box.

File Structure

• .dockerignore: Specifies files and directories to be ignored by Docker.
• compose.yml: Docker Compose configuration file.
• .gitignore: Specifies files and directories to be ignored by Git.
• package.json: Lists the project dependencies.
• Dockerfile: Docker configuration file for building the application image.
• public/interface.ejs: EJS template for the web interface.
• index.js: Main server file that handles API requests and serves the web interface.

Contributing

Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.

License

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

Acknowledgements

• Google Generative AI for providing the translation model.
• Express for the web framework.
• EJS for the templating engine.

Supported Models

GeminiAPI supports both fine-tuned and standard models of the Google Generative AI. Users can choose the appropriate model based on their specific needs for content generation and translation.

Model Selection

Users can select between fine-tuned and standard models by setting the GEN environment variable in the .env file. Fine-tuned models are optimized for specific tasks, while standard models offer general-purpose capabilities.