LlamaIndex Readers Integration: Obsidian

Overview

Pass in the path to an Obsidian vault and it will parse all markdown files into a List of Documents. Documents are split by header in the Markdown Reader we use.

Each document will contain the following metadata:

• file_name: the name of the markdown file
• folder_path: the full path to the folder containing the file
• folder_name: the relative path to the folder containing the file
• note_name: the name of the note (without the .md extension)
• wikilinks: a list of all wikilinks found in the document
• backlinks: a list of all notes that link to this note

Optionally, tasks can be extracted from the text and stored in metadata.

Usage

from llama_index.readers.obsidian import ObsidianReader

# Initialize ObsidianReader with the path to the Obsidian vault
reader = ObsidianReader(
    input_dir="<Path to Obsidian Vault>",
    extract_tasks=False,
    remove_tasks_from_text=False,
)

# Load data from the Obsidian vault
documents = reader.load_data()

Arguments

• input_dir (str): Path to the Obsidian vault.
• extract_tasks (bool): If True, extract tasks from the text and store them in metadata. Default is False.
• remove_tasks_from_text (bool): If True and extract_tasks is True, remove the task lines from the main document text. Default is False.

Implementation for Obsidian reader can be found here

This loader is designed to be used as a way to load data into LlamaIndex and/or subsequently used as a Tool in a LangChain Agent.