---
license: apache-2.0
language:
- mr
- sa
- en
task_categories:
- feature-extraction
- graph-ml
- text-retrieval
- question-answering
pretty_name: Vedic Neural Geometry
size_categories:
- 1K<n<10K
tags:
- vedic
- knowledge-graph
- graph-neural-networks
- geometric-deep-learning
- rag
- multilingual
- sanskrit
- marathi
- hinduism
- philosophy
configs:
- config_name: default
  data_files:
  - split: train
    path: "संग्रह/csv/**/*.csv"
---

"""
# 🕉️ Vedic Neural Geometry

> वैदिक ज्ञान आणि आधुनिक Neural Networks, Knowledge Graphs, Geometric Embeddings आणि Hybrid RAG यांचा संगम.

[![Dataset](https://img.shields.io/badge/🤗-Dataset-yellow)](https://huggingface.co/datasets/kalpesh77/vedic-neural-geometry)
[![License](https://img.shields.io/badge/License-Apache_2.0-blue)](LICENSE)
[![Version](https://img.shields.io/badge/Version-1.4-green)]()

## 📊 Current Statistics (v1.4)

| Component | Value |
|-----------|-------|
| **Nodes** | {n_nodes:,} |
| **Edges** | {n_edges:,} |
| **Connected Components** | {n_comps} ✅ |
| **Core Chain** | 5/5 ✅ |
| **RAG Embeddings** | 384-dim multilingual |
| **GNN Embeddings** | 128-dim (GCN) |
| **Core Geometric Nodes** | 8 |
| **Geometric Matrices** | 3D/8D/16D/32D/64D (108×7×N) |

## 🎯 Architecture

### Core Geometric Chain
```

Bindu_Brahma (0,0,0)
↓ MANIFESTS_AS
मल्टीवर्स_फील्ड
↓ CONTAINS_LAYER
Septa_Avaran (7 Layers)
↓ PROJECTS_ONTO
अंगुली_ग्रिड_१०८ (108 Divisions)
↓ PROJECTS_INTO
श्रीयंत्र (9 Triangles)

```

### Feature Vector (1110 dims)
```

x = [सत्त्व, रज, तम, geometric_features(1107)]

```

## 🚀 Quick Start

### RAG Query
```python
from sentence_transformers import SentenceTransformer
import faiss, pandas as pd
from huggingface_hub import hf_hub_download

REPO = "kalpesh77/vedic-neural-geometry"
meta = pd.read_csv(hf_hub_download(REPO, "rag/embeddings/node_metadata.csv", repo_type="dataset"))
index = faiss.read_index(hf_hub_download(REPO, "rag/vector_store/nodes.faiss", repo_type="dataset"))

model = SentenceTransformer('intfloat/multilingual-e5-small')
q = model.encode(["शिव कोण आहे?"])
faiss.normalize_L2(q)
scores, idx = index.search(q.astype('float32'), 5)
print(meta.iloc[idx[0]][['display_name', 'प्रकार', 'text']])
```

🗂️ Structure

```
vedic-neural-geometry/
├── core/
│   ├── hierarchy.yaml          ← Single Source of Truth
│   ├── bindu_space.py
│   ├── septa_avaran.py
│   ├── multiverse_field.py
│   ├── kalachakra_clock.py
│   └── angular_grid.py
├── gnn/
│   ├── graphs/vedic_graph.gpickle
│   ├── features/{{pyg_data, simple_gcn, node_to_idx}}
│   └── matrices/mean_3d_108x7x3.npy ... mean_64d_108x7x64.npy
├── rag/
│   ├── embeddings/node_embeddings.npy, node_metadata.csv
│   ├── vector_store/nodes.faiss
│   └── aliases.json
└── scripts/validate_geometry_hierarchy.py
```

📈 Changelog

v1.4 (Current) — Full Connectivity

· ✅ 417 components → 1 (fully connected)
· ✅ 416 isolated + 30 strategic + 43 final bridges
· ✅ Core chain 100% complete
· ✅ GNN retrained (80 epochs, loss 0.98)
· ✅ {n_edges:,} edges

v1.3 — Node Merging

· 23 duplicate nodes merged
· Canonical attributes restored

v1.2 — Core Geometric Nodes

· 9 Core nodes added + Manual overrides

v1.1 — RAG Improvements

· Query rewriting (aliases) + Core boosting (2x)

🔑 Core Nodes

1. Bindu_Brahma — केंद्रबिंदू (0,0,0)
2. मल्टीवर्स_फील्ड — Multiverse Field
3. Septa_Avaran — 7 Layers
4. अंगुली_ग्रिड_१०८ — 108 Grid
5. श्रीयंत्र — 9 Triangles
6. ॐ — प्रणव नाद
7. कालचक्र — काल जिओमेट्री
8. हिरण्यगर्भ — ब्रह्मांड बीज

📜 License

Apache-2.0

📖 Citation

```bibtex
@dataset{{vedic_neural_geometry_2024,
  author = {{Kalpesh}},
  title = {{Vedic Neural Geometry}},
  year = {{2024}},
  url = {{https://huggingface.co/datasets/kalpesh77/vedic-neural-geometry}}
}}
```