shinigamiRaj/IndianVedasOriginal

📖 Indian Vedas and Ayurveda Corpus (Rig Veda, Sama Veda, Yajur Veda, Atharva Veda, Charaka Samhita, Sushruta Samhita, Rasa Jala Nidhi, IRJAY)

Languages: English (en), Sanskrit (sa), Hindi (hi) Dataset size: ~10K < n < ~100K records (chunks, verses, chapters, and articles combined)

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Dataset Summary

This corpus is a comprehensive, highly structured dataset comprising the four primary pillars of ancient Indian literature (the Rig Veda, Sama Veda, Yajur Veda, and Atharva Veda) along with foundational classical works of Ayurveda and Indian medicine (the Charaka Samhita, Sushruta Samhita, and Rasa Jala Nidhi) and modern research papers from the International Research Journal of Ayurveda and Yoga (IRJAY). It integrates multiple authoritative translations, offering Sanskrit source verses, English interpretations, and modern Ayurvedic physiological reviews.

The dataset is formatted for continuous pre-training, fine-tuning, and Retrieval-Augmented Generation (RAG) applications in Indology, computational linguistics, historical analysis, ancient medicine, and ancient language model development.

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🏛️ Corpus Composition & Authorship

The dataset brings together works from highly respected translators, scholars, and medical journals:

1. Rig Veda:

   • Translator: Ralph T.H. Griffith (1896).
   • Language: English (en).
   • Structure: 10 Mandalas (Books), organized by Suktas (Hymns) and verses.

2. Sama Veda:

   • Translators:
     • Ralph T.H. Griffith (1895) - English translation.
     • PDF Manuscripts - High-resolution digital renderings.
   • Languages: English (en) | Sanskrit (sa) | Hindi (hi).
   • Structure: Part I (Mula/Decades) & Part II (Hymns).

3. Yajur Veda:

   • Translators:
     • Black Yajur Veda (Taittiriya Samhita): Arthur Berriedale Keith (1914) - English.
     • White Yajur Veda (Vajasaneya Samhita): Ralph T.H. Griffith (1899) - English.
   • Languages: English (en).
   • Structure: Kandas & Prapathakas (Black) | 40 Books & Verses (White).

4. Atharva Veda:

   • Translators:
     • Ralph T.H. Griffith (1895) - English.
   • Languages: English (en).
   • Structure: 20 Books, Suktas, and Verses.

5. Charaka Samhita:

   • Translator: Shree Gulabkunverba Ayurvedic Society.
   • Language: English (en).
   • Structure: Comprehensive classical text on medicine, covering general principles (Sutrasthana), diagnosis, treatment, and pharmaceutics.

6. Sushruta Samhita:

   • Translator: Kaviraj Kunja Lal Bhishagratna (1907).
   • Language: English (en) | Sanskrit (sa).
   • Structure: Core ancient treatise on surgery, anatomy, midwifery, and therapeutics.

7. Rasa Jala Nidhi:

   • Translator: Rasacharya Kaviraj Bhudeb Mookerji (1926).
   • Language: English (en).
   • Structure: Comprehensive Sanskrit treatise on alchemical metallurgy (Rasa Shastra) and chemistry of medicine.

8. International Research Journal of Ayurveda and Yoga (IRJAY):

   • Source: irjay.com.
   • Language: English (en).
   • Structure: Scientific research articles, reviews, and clinical studies on Ayurvedic physiology, immunization, and Yoga practices.

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⚙️ Chunking & Preprocessing Strategies

Two specialized pipelines are used to prepare the Vedic and Ayurvedic data for LLM ingestion:

1. Document Page Chunking (PDF pipeline)

Used for the bilingual translation documents (e.g., Sharma's Atharva Veda and PDF versions of Sama Veda) to ensure balanced context sizes.

Parameter	Value	Description
Chunk Overlap	150 characters	Ensures smooth transitions and preserves semantic boundaries
Chunk Size	4 chunks per page	Optimizes sequence length for embedding and context retrieval
Strategy	Page-level overlapping splits	Preserves adjacent translation pairs (Sanskrit-Hindi)

2. Semantic Structural Scraping (Web pipeline)

Used for the web-scraped books to preserve original ritualistic, musical, narrative, and medical divisions:

• Rig Veda & Atharva Veda: Chunked at the Hymn (Sukta) level. This encapsulates full structural themes as single database rows.
• Sama Veda: Chunked at the Decade/Hymn level, aligning with Vedic musical metres.
• Black Yajur Veda: Chunked at the Anuvaka level, maintaining ritual instruction blocks.
• White Yajur Veda: Chunked at the individual Verse level with high-resolution metadata tags.
• Charaka, Sushruta & Rasa Jala Nidhi: Chunked at the Chapter / Part level, ensuring holistic medical context is retained.
• IRJAY: Chunked at the Page level with summary annotations for dense scientific text.

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📁 Data Structure

Dataset records follow a unified JSON schema containing the text payload alongside hierarchical metadata:

Scraped Structural Record Example (JSONL)

{
  "text": "[[ Collection: Charaka Samhita | Translator: Shree Gulabkunverba Ayurvedic Society | Title: The Quest for Longevity (dirgha-jivita) ]]\n\nCharaka Samhita (English Translation)\nSutrasthana (Sutra Sthana) — General Principles\nChapter 1 - The Quest for Longevity (dirgha-jivita)\n\n1. We shall now expound the chapter entitled “The Quest for Longevity.”\n\n2. Thus declared the worshipful Atreya...\n..."
}

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🚀 Purpose & Applications

• Ancient Text Pre-Training: Ideal for injecting Vedic and Ayurvedic domain knowledge into deep learning models (e.g., VedaGPT).
• Bilingual RAG (Retrieval-Augmented Generation): High-quality translations allow cross-lingual semantic searches between English, Hindi, and Sanskrit.
• Linguistic & Digital Humanities: Facilitates statistical studies of ancient Sanskrit syntax, meter, and translation structures.
• Medical History Research: Enables research into historical clinical practices, pharmaceutical formulations, and surgical history of ancient India.