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BookMind

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BookMind is a web application that allows users to explore character relationships and storylines in books using AI-powered visualizations. The application provides interactive mind maps, AI chatbots for deep questions, book summaries, and community contributions.

Features

  • Interactive Mind Maps: Visualize relationships between characters and plot elements.
  • AI Chatbot: Ask deep questions about the book and get insightful answers.
  • Book Summaries: Get concise overviews of plots and themes.
  • Community Contributions: Add and refine maps with fellow book lovers.

Prerequisites

  • Node.js
  • Python >= 3.10
  • LlamaStack server running locally
  • Environment variables:
    • LLAMA_STACK_PORT
    • INFERENCE_MODEL
    • REACT_APP_GOOGLE_BOOKS_API_KEY

Getting Started

Run llama-stack

  1. Setting up Ollama server
    Please check the Ollama Documentation on how to install and run Ollama. After installing Ollama, you need to run ollama serve to start the server.
export INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct"

# ollama names this model differently, and we must use the ollama name when loading the model
export OLLAMA_INFERENCE_MODEL="llama3.2:3b-instruct-fp16"
ollama run $OLLAMA_INFERENCE_MODEL --keepalive 60m
  1. Running llama-stack server
pip install llama-stack

export LLAMA_STACK_PORT=5000

# This builds llamastack-ollama conda environment
llama stack build --template ollama --image-type conda

conda activate llamastack-ollama

llama stack run \
  --port $LLAMA_STACK_PORT \
  --env INFERENCE_MODEL=$INFERENCE_MODEL \
  --env OLLAMA_URL=http://localhost:11434 \
  ollama

Backend Setup

  1. Install dependencies:
cd server
pip install -r requirements.txt
  1. Set .env in the server directory

You should modify the name of example.env to .env in the server directory.
Modify INFERENCE_MODEL in example.env with yours.

  1. Run the server:
python server.py

Frontend Setup

  1. Set up GOOGLE_BOOKS_API_KEY:

You should rename example.env with .env and replace {YOUR_API_KEY} with your google_books_api_key after getting your api key.

REACT_APP_GOOGLE_BOOKS_API_KEY={YOUR_API_KEY}
  1. Install dependencies and run the application:
npm install
npm start

Usage

  1. Initialize Memory: Upload your book or choose from the library to initialize memory.
  2. AI Analysis: The AI analyzes the book and generates a mind map.
  3. Explore Insights: Explore relationships, themes, and Q&A insights.

What did we use Llama-stack in BookMind?

1️⃣ Llama Inference models: You can start a LLM application using various LLM services easily.
2️⃣ RAG with FAISS: We leveraged FAISS in Llama-stack for Retrieval-Augmented Generation, enabling real-time responses to character relationship questions.
3️⃣ Multi-Hop Reasoning: Our system performs sequential inference—first extracting characters and relationships, then generating graphized mind map data in JSON for visual storytelling.

Contributors

Original Repo
seyeong-han
sunjinj
WonHaLee