PhillyMac/Fractional_Consultiong_Corpus

Fractional Consulting

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

Dataset Description

• —Subject: Fractional Consultiong
• —Subject Type: topic
• —Total Items: 949
• —Has Embeddings: Yes (all-MiniLM-L6-v2)
• —Created: 2026-02-10

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/Fractional_Consultiong_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.