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---
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
```python
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](https://github.com/PhillyMac/deku-corpus-builder) - An automated corpus building system for AI applications.
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