Bible Context Server

A lightweight API server that provides contextual information for Bible verses using AI models.

Overview

Bible Context Server is a FastAPI application that offers quick Bible verse context lookup through two different AI backends:

• Local Ollama server with Gemma 3 12B model
• Google Gemini API (requires API key)

For any given Bible reference (book, chapter, verse), the service returns:

• The verse content (NASB 1995 translation)
• Author information
• Approximate time of writing
• Brief contextual description
• Main themes
• Related verses (quotations and allusions)

Sample Screenshots - Gen 3:20

Gemini

Ollama

Features

• Fast API endpoints for Bible verse context lookup
• Support for local AI inference via Ollama
• Integration with Google Gemini API
• HTML response formatting with Markdown support

Prerequisites

• Python 3.13+
• Ollama server running locally with Gemma 3 12B model (for /ol/ endpoint)
• Google Gemini API key (for /ggl/ endpoint)

Installation

1. Clone the repository:

git clone https://github.com/yourusername/bible-context-server.git
cd bible-context-server

2. Set up a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies:

pip install fastapi uvicorn requests markdown google-generativeai python-dotenv

4. Create a .env file in the project root with your Google Gemini API key:

GEMINI_API_KEY=your_api_key_here

Usage

1. Start the Ollama server locally (if using the /ol/ endpoint)

2. Run the FastAPI server:

uvicorn server:app --reload

3. Access the API endpoints:
   • Ollama endpoint: http://localhost:8000/ol/{book_chapter_verse}
   • Gemini endpoint: http://localhost:8000/ggl/{book_chapter_verse}

Example:

http://localhost:8000/ol/John 3:16
http://localhost:8000/ggl/Romans 8:28

API Endpoints

/ol/{bcv}

Uses a local Ollama server with the Gemma 3 12B model to provide Bible verse context.

/ggl/{bcv}

Uses the Google Gemini API to provide Bible verse context. Requires a valid API key in the .env file.

Development

The project is built with:

• FastAPI - Modern, fast web framework
• Ollama - Run large language models locally
• Google Generative AI - Google's Gemini API

License

MIT License

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request