The tool follows a Retrieval Augmented Generation (RAG) architecture, where the Bible text is indexed in a Chroma vector database using BGE sentence embeddings. When a user searches for a topic, relevant passages are retrieved based on semantic similarity and the top results are summarized using Claude. The user interface is built with Streamlit for easy exploration and the Python code is modularized for maintainability. Biblos can be run locally by installing the requirements, downloading and preprocessing the Bible text into a Chroma database, and launching the Streamlit app.
Key takeaways:
- Biblos is a tool that allows semantic search and summarization of Bible passages using advanced NLP techniques.
- It uses Chroma and BAAI BGE embeddings for vector search and Anthropic's Claude large language model for summarizing search results.
- The tool follows a RAG (Retrieval Augmented Generation) architecture, combining dense vector search for retrieval with a powerful LLM for summarization.
- Biblos leverages several open source projects including Langchain, Chroma, Anthropic, BAAI BGE Embeddings, and Streamlit.