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https://github.com/sammybams/gospel-companion

A cutting-edge digital assistant designed to enhance the experience of studying bible lessons and gospel materials
https://github.com/sammybams/gospel-companion

ai bible llm python rag

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A cutting-edge digital assistant designed to enhance the experience of studying bible lessons and gospel materials

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README

        

# GOSPEL COMPANION ✨

**Gospel Companion** is a cutting-edge digital assistant designed to enhance the experience of studying Bible lessons and gospel materials. This project leverages GPT-3.5 Turbo and the open-source ChromaDB as a vector store for a Retrieval-Augmented Generation (RAG) solution, providing a conversational assistant that is aware of conversation history and capable of performing deep dives into Bible lessons and stories.

## Features 🌟

- **Conversational Assistant** πŸ’¬: Gospel Companion acts as an intelligent assistant that understands context and conversation history, allowing users to engage in meaningful discussions about Bible lessons.
- **Age-Specific Context** πŸ‘ΆπŸ‘§πŸ§‘: The assistant tailors its responses based on the selected age category. The solution covers three categories:
- **Elementary**: For ages 2 to 12.
- **Junior**: For ages 13 to 17.
- **Senior**: For ages 18 and above.
- **Knowledge Base with References** πŸ“šπŸ”—: The knowledge base is built on a collection of Sunday school lessons by the Apostolic Faith Church. In addition to tailored responses, users receive up to three references, providing direct links to the specific Sunday school lessons where the answers to their questions are discussed in more detail. Access the full lesson library [here](https://apostolicfaithweca.org/sunday-school-lesson-library).

## Technology Stack πŸ› οΈ

- **Python** 🐍: Core programming language used for development.
- **Langchain** πŸ”—: Framework used to build the language model-based workflows.
- **Azure OpenAI Service** ☁️: Provides access to the GPT-3.5 Turbo model.
- **ChromaDB** πŸ—‚οΈ: An open-source vector database used to store and retrieve embeddings, enabling the RAG solution.

## License πŸ“„

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.