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AI Note Suggestion Plugin for Obsidian

AI Note Suggestion plugin for Obsidian is designed to make your note-taking experience even more seamless. It harnesses the power of AI vector search using Weaviate to suggest similar and related notes as you type, reducing your dependency on traditional tagging systems. You can also filter notes by tags, giving you the flexibility you need.

Features:

  • AI-Powered Suggestions: The plugin suggests similar notes based on the content you're currently typing.
  • Related Notes: Discover related notes that you might have missed, enhancing your note-taking context.
  • Tag Filtering: If you still prefer using tags, you can filter notes by tags as well.
  • Quick search: Also you can quickly search anytime with command palette

Setting Up AI Note Suggestion

To use the AI Note Suggestion plugin, you'll need to set up Weaviate, an AI vector search engine. We recommend using Docker Compose for an easier setup. You can also use weaviate cloud service if you don't want to use your local machine as a server. Here are the steps to get started:

Step 1: Install Docker If you don't have Docker installed on your machine, you'll need to do so. Docker provides a platform for running Weaviate

Step 2: Download Weaviate Using Docker Compose You can check out weaviate's install guides for in depth information or if you are new to this follow instruction bellow,

  1. Create a docker-compose.yml file with the following content:
version: '3'

services:
  weaviate-obsidian:
    container_name: weaviate-obsidian
    depends_on:
      # - t2v-transformers-obsidian
      - contextionary
    command:
    - --host
    - 0.0.0.0
    - --port
    - '8080'
    - --scheme
    - http
    image: semitechnologies/weaviate
    ports:
    - 3636:8080
    volumes:
      - ./weaviate-data:/var/lib/weaviate
    restart: unless-stopped
    environment:
      QUERY_DEFAULTS_LIMIT: 25
      AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED: 'true'
      PERSISTENCE_DATA_PATH: '/var/lib/weaviate'
      CLUSTER_HOSTNAME: 'node1'
      CONTEXTIONARY_URL: contextionary:9999
      ENABLE_MODULES: 'text2vec-contextionary'
      DEFAULT_VECTORIZER_MODULE: 'text2vec-contextionary'

  # for light weight model (preferable if you are using cpu)
  contextionary:
    container_name: contextionary-obsidian
    environment:
      OCCURRENCE_WEIGHT_LINEAR_FACTOR: 0.75
      EXTENSIONS_STORAGE_MODE: weaviate
      EXTENSIONS_STORAGE_ORIGIN: http://weaviate:8080
      NEIGHBOR_OCCURRENCE_IGNORE_PERCENTILE: 5
      ENABLE_COMPOUND_SPLITTING: 'false'
    image: semitechnologies/contextionary:en0.16.0-v1.2.1
    ports:
    - 9999:9999

here is the full compose file with other options compose.yml

  1. In the directory where you saved the docker-compose.yml file, run the following command
docker-compose up -d

This command pulls the Weaviate image from Docker Hub and runs it as a container on your local machine.

Step 3: Configure AI Note Suggestion

  1. Once you have Weaviate up and running, go to the settings of the AI Note Suggestion plugin in Obsidian.
  2. In the plugin settings, provide the Weaviate Address where your Weaviate instance is running (usually http://localhost:3636 if you followed the default settings)

Now, you're all set to enjoy the enhanced note-taking experience provided by the AI Note Suggestion plugin!

Code blocks for query

This is a simple code blocks for querying similar notes based on given texts

```match
text: one
limit: 10
distanceLimit: .98
autoCut: 2
```

Todo's

  • Side pane list
  • add yaml for code query for tags
  • Code query inside files like
  • remove code blocks when update files on weaviate
  • extract tags and update file with tags
  • Similar notes inside note
  • add autocut settings and yaml code
  • add distance threshold on settings and yaml code
  • add a search command to search by similar text
  • cached search result for faster query
  • Split notes by regex and upload splits note in vector for long notes
  • show status on every events (update,sync etc)