Welcome to Obsidian Vault V2 for LLM Outputs! This project represents the second version of a model Obsidian vault designed specifically to store outputs from large language models (LLMs) like GPT. The primary goal of this vault is to store LLM-generated content locally in a logical, organized manner, allowing for easy retrieval, reference, and usage of that content in various contexts.
This repository contains a "dummy" vault filled with random information, providing a fully functional template to demonstrate how the system can work in practice. All content in this vault is sample data intended for demonstration purposes, making it easy for users to explore the layout, folder structure, templates, and workflows that have been set up.
The purpose of this vault is to provide a local solution for storing LLM outputs. Whether you are a researcher, writer, or enthusiast using tools like GPT to generate content, this vault helps maintain that content in an organized fashion, preventing it from being lost in the clutter of multiple files and applications.
Obsidian is used as the primary tool for managing the vault, leveraging its flexibility, markdown support, and powerful note-linking capabilities to create a truly interconnected repository of LLM content.
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Organized Folder Structure: The vault contains a well-designed folder structure to help store various types of LLM-related information, such as prompts, outputs, agent configurations, and context snippets.
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Templates: Ready-to-use templates for saving prompts, outputs, agent configurations, and research findings. These templates ensure a consistent format, making it easier to keep content organized and usable.
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Dummy Content: The vault is pre-filled with sample data across a variety of folders, demonstrating the possible use cases and best practices for storing LLM outputs in a systematic way.
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Logical System: Everything is organized in a logical manner, from prompts to context snippets to research, so that content can be easily linked, expanded, and referenced later.
The vault is organized into several key folders:
- Context: Contains snippets providing background information to improve the relevance of LLM outputs.
- Prompts: Stores reusable prompts, enabling consistent and refined LLM interactions.
- Outputs: Holds both raw and refined LLM outputs, categorized into subfolders for better clarity.
- Agents: Contains configurations of custom LLM agents with parameters that have been tuned for specific purposes.
- Resources: Stores reference materials and supporting documents.
- Research: Contains synthesized research and in-depth analyses generated through LLM interactions.
- Follow-Ups: A place to track action items derived from LLM outputs.
- Templates: Houses all the templates used for saving different types of information in a consistent format.
- Clone the Repository: Start by cloning this repository to your local machine.
- Open in Obsidian: Open the folder in Obsidian to explore the layout, folder structure, and dummy data.
- Customize Templates: Adapt the templates for your own workflows, such as storing prompts, outputs, or agent settings.
- Store LLM Outputs: Begin using this vault to store and organize your own LLM-generated content.
- Download and install Obsidian.
- Clone this repository or download the ZIP file and extract it.
- Open the extracted folder as a vault in Obsidian.
- Explore the folder structure and experiment with the provided dummy content.
This project is licensed under the MIT License. Feel free to modify and use it as a basis for your own LLM output management system.
Since this is a demonstration and template project, contributions are welcome for additional templates, organizational methods, or suggestions to improve workflow.
If you have any questions or suggestions, feel free to open an issue on this repository. Your feedback is always appreciated!
Daniel Rosehill
(public at danielrosehill dot com)
This repository is licensed under CC-BY-4.0 (Attribution 4.0 International) License
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