Configuration and Setup

Installing Open Notebook

⚠️ Important: Be sure to edit the .env file before running the app.

🐳 Docker Setup (recommended)

We recommend using Docker as this will get you all the services installed and configured with no hassle.

Copy the .env.example file and name it docker.env

version: '3'

services:
  surrealdb:
    image: surrealdb/surrealdb:v2
    ports:
      - "8000:8000"
    volumes:
      - surreal_data:/mydata
    command: start --log trace --user root --pass root rocksdb:/mydata/mydatabase.db
    pull_policy: always
    user: root

  open_notebook:
    image: lfnovo/open_notebook:latest
    ports:
      - "8080:8502"
    env_file:
      - ./docker.env
    depends_on:
      - surrealdb
    pull_policy: always
    volumes:
      - notebook_data:/app/data

volumes:
  surreal_data:
  notebook_data:

or with the environment variables:

version: '3'

services:
  surrealdb:
    image: surrealdb/surrealdb:v2
    ports:
      - "8000:8000"
    volumes:
      - surreal_data:/mydata
    command: start --log trace --user root --pass root rocksdb:/mydata/mydatabase.db
    pull_policy: always
    user: root

  open_notebook:
    image: lfnovo/open_notebook:latest
    ports:
      - "8080:8502"
    environment:
        - OPENAI_API_KEY=API_KEY
        - SURREAL_ADDRESSsurrealdb
        - SURREAL_PORT=8000
        - SURREAL_USER=root
        - SURREAL_PASS=root
        - SURREAL_NAMESPACE=open_notebook
        - SURREAL_DATABASE=staging
    depends_on:
      - surrealdb
    pull_policy: always
    volumes:
      - notebook_data:/app/data

volumes:
  surreal_data:
  notebook_data:

📦 Installing from Source

If you really want to play with the source code.

git clone https://github.com/lfnovo/open_notebook.git
cd open_notebook
poetry install
cp .env.example .env
poetry run streamlit run app_home.py

Run the app with:

poetry run streamlit run app_home.py

or the shourcut

make run

Setting up the providers and models

Several new providers are supported now:

OpenAI
Anthropic
Open Router
LiteLLM
Vertex AI
Gemini
Ollama

All providers are installed out of the box. All you need to do is to setup the environment variable configurations (API Keys, etc) for your selected provider and decide which models to use.

Please refer to the .env.example file for instructions on which ENV variables are necessary for each.

Create models on the Settings page

Go to the settings page and create your different models.

Model Type	Supported Providers
Language	OpenAI, Anthropic, Open Router, LiteLLM, Vertex AI, Vertex AI, Anthropic, Gemini, Ollama
Embedding	OpenAI, Gemini, Vertex AI, Ollama
Speech to Text	OpenAI
Text to Speech	OpenAI, ElevenLabs

📝 Notice: For complete usage of all the features, you need to setup at least 4 models (one of each type).

After setting up the models, head to the Model Defaults tab to define the default models. There are several defaults to setup.

Model Default	Purpose
Chat Model	Will be used on all chats
Transformation Model	Will be used for summaries, insights, etc
Large Context	For content higher then 110k tokens (use Gemini here)
Speech to Text	For transcribing text from your audio/video uploads
Text to Speech	For generating podcasts
Embedding	For creating vector representation of content

All model types and defaults are required for now. If you are not sure which to pick, go with OpenAI, the only one that covers all possible model types.

The reason for opting for this route is because different LLMs, will behave better/worse depending on the type of request and type of tools offered. So it makes sense to build a more refined system to decide which model should process which task.

For instance, we can use an Ollama based model, like gemma2 to do summarization and document query, and use openai/claude for the chat. The whole idea is to allow you to experiment on cost/performance.

Running the app

After the app is running, you can access it at http://localhost:8080.

The first time you connect, it will check for the database and see if the schema is ready. If not, it will create the database for you.

Go to the Usage page to learn how to use all features.

Upgrading Open Notebook

Running from source

Just run git pull on the root project folder and then poetry install to update dependencies.

Running from docker

Just pull the latest image with docker pull lfnovo/open_notebook:latest and restart your containers with docker-compose up -d

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