Obsidian Gemini Tagging & Linking Agent

This Python script is a powerful agent designed to automatically organize your Obsidian vault. It leverages the power of Google's Gemini 2.5 Flash model to analyze your notes, generate context-aware tags, and create links between related notes, turning your vault into a dynamic, interconnected knowledge graph.

Features

• Automated Tagging: Analyzes the content of your notes and suggests relevant tags, including both topic tags (e.g., #python, #AI) and type tags (e.g., #article, #project).
• Context-Aware Suggestions: Uses not only the note's content but also data from related notes to provide highly relevant and consistent tags.
• Key Concept Extraction: Identifies and extracts key concepts from your notes to provide better context for tag generation.
• Related Notes Linking: Automatically creates a "Related Notes" section in each note, linking to other relevant notes based on shared tags.
• Flexible Configuration: A simple config.yaml file allows you to customize the script's behavior, including your vault path, API keys, and model settings.
• Dry Run Mode: Run the script in a "read-only" mode to see what changes it would make without modifying any of your files.

Prerequisites

• Python 3.7+
• An Obsidian vault
• A Google AI API key

Setup

1. Clone the Repository:

   git clone <repository-url>
   cd <repository-name>

2. Install Dependencies:

   pip install pyyaml google-generativeai

3. Configure the Script:

   • Rename config.example.yaml to config.yaml.
   • Open config.yaml and set the following:
     • obsidian_vault_path: The full path to your Obsidian vault.
     • dry_run: Set to true for the first run to ensure everything is working as expected.
     • gemini.api_key: Your Google AI API key. For better security, you can set this as an environment variable and reference it as !env GOOGLE_API_KEY.

Running the Script

Once you've completed the setup, you can run the script from your terminal:

python obsidianTag.py

The script will perform the following steps:

1. Analyze Vault: Read all of your notes and parse their content and frontmatter.
2. Compute Relationships: Identify relationships between notes based on shared tags.
3. Generate Tags & Links: For each note, it will:
   • Extract key concepts.
   • Generate suggested tags using the Gemini model.
   • Create a list of related notes.
4. Update Notes: If dry_run is false, it will update your notes with the new tags and related notes section.

How It Works

The script is divided into several key components:

• Configuration Loading: Securely loads your settings, including your API key.
• Vault Analysis: Scans your vault to build a comprehensive understanding of your notes.
• Relationship Mapping: Creates a map of how your notes are connected.
• LLM Interaction: Communicates with the Gemini API to get intelligent tag suggestions.
• Note Modification: Carefully updates your notes while preserving their original content.

This agent is designed to be a smart, automated assistant for your knowledge management, helping you to uncover hidden connections and build a more powerful personal knowledge base.

License

MIT

Acknowledgements

• Google's Gemini API for the AI capabilities
• The Obsidian community for inspiration