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Exios66 / Literary-Vault

Active Catalog of the Documentation, Backend, and Infrastructure for Neuroscience Research Expansion. || [https://exios66.github.io/Literary-Vault/]
https://morningstar-developments.gitbook.io/morningstar-docs-storage/
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Literary Vault Documentation Guide

Exios66 - Literary-Vault stars - Literary-Vault Docs - GitBook Dox Netlify Status dependency - Python

https://morningstar-developments.gitbook.io/morningstar-developments-publishing/

License

Released under MIT by @Exios66.

License Commits Issues Contributors Last Commit

Made with Python Flask HTML5 CSS3 JavaScript Markdown GitBook GitHub Actions Netlify

🗂️ Repository Structure

literary-vault/
├── analysis/              # Detailed analysis of research papers
│   ├── AI-Research/      # AI-related research analysis
│   ├── EEG/             # EEG research analysis
│   └── Manipulation-Deception/ # Studies on manipulation/deception
├── docs/                 # Repository documentation
│   ├── Analysis/        # Detailed research analysis
│   ├── api/            # API documentation and implementation
│   ├── Integration/    # Integration guides
│   ├── openai-functions/ # OpenAI function schemas
│   └── pdfs/           # PDF documentation
├── external-resources/   # Additional resources
│   ├── Math-PDFs/      # Mathematics resources
│   └── questions/      # Question datasets
├── scripts/             # Utility scripts
├── CHANGELOG.md         # Project change history
├── CONTRIBUTING.md      # Contribution guidelines
├── LICENSE             # MIT License
└── README.md           # Repository documentation

Literary Vault

An active catalog and toolkit supporting neuroscience research with organized documentation, backend services, and infrastructure for comprehensive analysis and API services.

Table of Contents

Overview

Literary Vault is structured to support data-driven neuroscience research. It provides categorized research analysis, curated datasets, external resources, and REST APIs for accessing and managing these resources. With detailed integration tools and utility scripts, it is designed for scalable and secure deployment in research and development environments.

Features

Research Analysis

The repository organizes neuroscience-related research into well-defined categories:

API Services

Questions API

A REST API that allows categorized access to a curated dataset of questions on topics including astronomy, literature, mathematics, and general knowledge.

Changelog API

Programmatic management of the project's changelog, supporting:

External Resources

The repository contains additional documentation and datasets to support research:

Integration Tools

Tools to simplify integrations:

Utility Scripts

Scripts provided for streamlined repository management, including:

Installation

  1. Clone the repository: 
    
git clone https://github.com/Exios66/Literary-Vault.git
cd Literary-Vault

2.Install dependencies:

pip install -r requirements.txt

Usage

Run API servers for different modules:

Start Questions API

python docs/api/questions_api.py

Start Changelog API

python docs/api/changelog_api.py

Changelog Management

Use the provided scripts to add entries or create releases:

Add an entry to the changelog

python scripts/update_changelog.py add "Added" "Description of new feature"

Create a release entry

python scripts/update_changelog.py release "1.0.0"

Access Question Datasets

The repository includes various question sets in CSV format, accessible either via the API or directly:

•   Refined_Astronomy_Questions.csv
•   Refined_Literature_Questions.csv
•   Refined_Mathematics_Questions.csv
•   Refined_General_Knowledge_Questions.csv

Development

•   Python: Ensure Python 3.x is installed.
•   Framework: FastAPI powers the API services.
•   JSON Validation: JSON schema validation is used across APIs.
•   Documentation: Markdown format for documentation.
•   Version Control: Use Git for tracking changes.

Contribution Guidelines

We welcome contributions to enhance the Literary Vault. Please follow these guidelines:

1.  Fork the repository and create a new branch for your feature or bug fix.
2.  Follow existing naming conventions and structure.
3.  Document any new additions or changes.
4.  Submit a pull request with a clear description of the updates.

For more details, see CONTRIBUTING.md.

📚 Components

1. Analysis Directory

Comprehensive research analysis organized by topic:

2. API Services

Questions API

REST API for accessing curated question datasets:

Features:

Endpoints:

GET /api/v1/questions/{category}
GET /api/v1/questions/{category}/random
GET /api/v1/health

Changelog API

Programmatic changelog management:

3. External Resources

4. Integration Tools

5. Scripts

Utility scripts for repository management:

🔧 Usage

1. API Services

Start the API servers:

# Questions API
python docs/api/questions_api.py

# Changelog API
python docs/api/changelog_api.py

Access documentation:

2. Changelog Management

# Add entry
python scripts/update_changelog.py add "Added" "New feature"

# Create release
python scripts/update_changelog.py release "1.0.0"

3. Question Datasets

Access structured questions via API or direct CSV files:

📋 Guidelines

🔒 Security

📚 Documentation

🛠️ Development

🤝 Contributing

See CONTRIBUTING.md for guidelines.

📄 License

Released under MIT License.

Last Updated: 2024-10-30