README.md

metadata

license: cc0-1.0
task_categories:
  - text-generation
  - feature-extraction
language:
  - en
tags:
  - corpus
  - leadership
  - historical
  - deku-corpus-builder
size_categories:
  - 1K<n<10K

Julius Caesar Agent

This corpus was automatically generated by the Deku Corpus Builder for use in RAG-based AI applications.

Dataset Description

• Subject: JUlius Caesar
• Subject Type: personality
• Total Items: 729
• Has Embeddings: Yes (all-MiniLM-L6-v2)
• Created: 2026-01-09

Dataset Structure

Each record contains:

• text: The content text
• source_url: Original source URL
• source_title: Title of the source document
• source_domain: Domain of the source
• relevance_score: Relevance to the subject (0-1)
• quality_score: Content quality score (0-1)
• topics: JSON array of detected topics
• character_count: Length of the text
• subject_name: The subject this content relates to
• subject_type: "personality" or "topic"
• extraction_date: When the content was extracted
• embedding: Pre-computed 384-dimensional embedding vector

Usage

from datasets import load_dataset

dataset = load_dataset("PhillyMac/JUlius_Caesar_Corpus")

# Access the data
for item in dataset["train"]:
    print(item["text"][:100])

Integration with RAG

This dataset is designed to be integrated with existing embedded corpuses. The embeddings use the sentence-transformers/all-MiniLM-L6-v2 model, compatible with FAISS indexing.

License

Content is sourced from public domain and Creative Commons licensed materials.

Generated By

Deku Corpus Builder - An automated corpus building system for AI applications.