zk-rag 1.2.0

zk-rag is a command-line chat tool for your zettelkasten

Chat With Your Zettelkasten

This is a simple tool that lets you chat with an "AI" that has access to the documents in your Zettelkasten. It will index your markdown documents, and in your chat session it may choose to query your content, retrieve excerpts, read entire documents, and generate responses based on the content in your Zettelkasten.

For "AI" it communicates with a local running instance of Ollama. Ollama must be installed and running for zkchat to function.

Features

• Command-line interface for quick access
• Graphical user interface for a more user-friendly experience
• RAG queries across your document base
• Interactive chat with context from your Zettelkasten
• Configurable LLM model selection
• Easy Zettelkasten folder configuration

Tools

The chat interface provides access to several tools that enhance its capabilities:

• Document Search Tools

  • Find Documents: Locates relevant documents in your Zettelkasten based on your query
  • Find Excerpts: Retrieves specific passages from your documents that match your search criteria
  • Read Document: Accesses the full content of a specific document in your Zettelkasten
  • Write Document: Creates or updates documents in your Zettelkasten (requires --unsafe flag)

• Smart Memory Tools

  • Store Information: Saves important facts and context from conversations for future reference
  • Retrieve Information: Recalls previously stored information to provide more personalized responses

• External Knowledge Tools

  • Wikipedia Lookup: Retrieves information about entities, concepts, and topics from Wikipedia to supplement your Zettelkasten content

Requirements

You must have ollama installed and running.

You must have a local knowledgebase / zettelkasten with content in markdown format. I use Obsidian, because I favour working locally, and I favour using the markdown format for notes - because everything's local, and in plain text, I can simply point this tool at a Vault folder.

Workstation setup

Right now, while this tool should run on Windows, we've only written instructions for Mac.

I recommend you setting up a local virtual Python environment, to keep it clean, but you can install it globally.

Setting up a local environment, and activating it (recommended):

cd $HOME
python3 -mvenv .venv
source .venv/bin/activate

Installing the zk-rag module from PyPi:

pip install zk-rag

Setting up Ollama and installing a local model:

brew install ollama
ollama pull qwen2.5:14b

Usage

Command-line Interface

Run zkchat to start the command-line interface.

Command-line options:

• --model [model_name]: Change the LLM model to use for chat
  • With model name: zkchat --model llama2 - configure to use specified model
  • Without model name: zkchat --model - interactively select from available models
• --reindex: Reindex the Zettelkasten vault, will attempt to do so incrementally
• --full: Force full reindex (only used with --reindex)
• --unsafe: Enable operations that can write to your Zettelkasten. This flag is required for using tools that modify your Zettelkasten content, such as the Write Document tool. Use with caution as it allows the AI to make changes to your files.
• --reset-memory: Clear the smart memory storage

Smart Memory

The tool includes a Smart Memory mechanism that allows the AI to store and retrieve information during conversations. This memory:

• Persists between chat sessions
• Uses vector embeddings for semantic similarity search
• Enables the AI to recall previous context and information
• Can be cleared using the --reset-memory CLI option

Graphical Interface (Experimental)

The GUI is experimental and may not work as expected. It is provided as a preview feature only.

Run zkchat-gui to start the graphical interface. The GUI provides:

• A multi-line chat input for composing messages
• A scrollable chat history showing the entire conversation
• A resizable divider between chat history and input areas
• Settings menu (accessible via Settings -> Configure...) for:
  • Selecting the LLM model from available Ollama models
  • Configuring the Zettelkasten folder location
• Asynchronous chat responses that keep the interface responsive

When first run, both zkchat and zkchat-gui will prompt for initial configuration. You will need to provide:

• The path to your root Zettelkasten / Obsidian vault folder
• The LLM model you want to use from your Ollama installation

In the command-line interface, you'll be prompted for this information directly. In the GUI, you can configure these settings through the Settings menu. After initial configuration, the tool will start a full index build of your Zettelkasten.