---
title: RAG for Vrikshayurveda
emoji: 🌿
colorFrom: green
colorTo: green
sdk: gradio
sdk_version: "4.44.1"
app_file: app.py
pinned: false
license: mit
---

# 🌿 RAG for Vrikshayurveda

**Retrieval-Augmented Generation for Surapala's Science of Plant Life (वृक्षायुर्वेद)**

A full-stack AI system that diagnoses plant disorders and recommends traditional Ayurvedic treatments based on the ancient Vrikshayurveda text by Surapala. Combines modern RAG architecture with a classical forward + backward chaining inference engine.

![Python](https://img.shields.io/badge/Python-3.10+-blue?logo=python&logoColor=white)
![Gradio](https://img.shields.io/badge/Gradio-4.x-orange?logo=gradio&logoColor=white)
![License](https://img.shields.io/badge/License-MIT-green)

---

## 🏗️ Architecture

```
User Query
    │
    ▼
┌──────────────────┐
│  Query Expansion  │  ← Groq (Llama 3.3 70B) generates 3 rephrasings
│  (4 variants)     │
└────────┬─────────┘
         │
         ▼
┌──────────────────┐
│  BGE-large-en    │  ← BAAI/bge-large-en-v1.5 (1024-dim embeddings)
│  Encoding        │
└────────┬─────────┘
         │
         ▼
┌──────────────────┐
│  Pinecone Vector │  ← Top-K retrieval + deduplication by parent ID
│  Search          │
└────────┬─────────┘
         │
    ┌────┴────┐
    ▼         ▼
┌────────┐ ┌─────────────────────┐
│ Context│ │  Inference Engine    │
│ Build  │ │  • Symptom Extractor │
│        │ │  • Forward Chaining  │
│        │ │  • Backward Chaining │
│        │ │  • 42 Ayurvedic Rules│
└───┬────┘ └──────────┬──────────┘
    │                 │
    └────────┬────────┘
             ▼
┌──────────────────┐
│  Groq LLM        │  ← Llama 3.3 70B generates final response
│  (RAG + Inference │
│   grounded)       │
└──────────────────┘
```

---

## ✨ Features

### 🩺 Diagnose Tab
- Describe plant symptoms in natural language
- Get Ayurvedic diagnosis with dosha classification (Vata/Pitta/Kapha)
- View the full reasoning chain from the inference engine
- Receive traditional treatment recommendations from Vrikshayurveda
- See retrieved source passages with relevance scores

### 🔗 Symptom Chain Explorer
- Interactive visual inference engine
- Select symptoms from 27 observable indicators
- Watch forward chaining fire rules in real-time on a canvas
- Step through rules one at a time or auto-run the full chain
- See proof trace with colored condition/conclusion pills
- Stats bar showing fact count, rules fired, and diagnosed disorders

---

## 🧠 Inference Engine

The inference engine implements **42 Ayurvedic diagnostic rules** from the Vrikshayurveda text:

| Component | Description |
|-----------|-------------|
| **Symptom Extractor** | NLP-based extraction of atomic facts from natural language |
| **Forward Chaining** | Priority-sorted rule firing to derive disorders and remedies |
| **Backward Chaining** | Differential diagnosis across 10 disorder categories |
| **Rule Base** | 42 YAML-defined rules covering 3 doshas, 10 disorders, 8 causes |

### Disorder Categories
- **Internal**: Vata, Pitta, Kapha disorders
- **External**: Heat/Frost, Stormy Wind, Fire/Lightning/Drought
- **Other**: Mechanical Wound, Faulty Seed, Insect Infestation, Excessive Watering

---

## 🚀 Setup

### Prerequisites
- Python 3.10+
- API keys for Pinecone, Groq

### Installation

```bash
git clone https://github.com/Viraj-77/RAG4Vrikshayurveda.git
cd RAG4Vrikshayurveda
pip install -r requirements.txt
```

### Environment Variables

Create a `.env` file:

```env
GROQ_API_KEY=your_groq_api_key
PINECONE_API_KEY=your_pinecone_api_key
PINECONE_INDEX_NAME=jaim3
```

### Run

```bash
python app.py
```

The app launches at `http://127.0.0.1:7860`

---

## 📁 Project Structure

```
RAG4Vrikshayurveda/
├── app.py                      # Gradio web interface + Symptom Chain Explorer
├── rag_pipeline.py             # Core RAG pipeline (embed → retrieve → generate)
├── inference/
│   ├── engine.py               # Unified inference entry point
│   ├── forward_chain.py        # Forward chaining engine
│   ├── backward_chain.py       # Backward chaining + differential diagnosis
│   └── symptom_extractor.py    # NLP fact extraction from text
├── vrikshayurveda_rules.yaml   # 42 Ayurvedic diagnostic rules
├── db.pdf                      # Vrikshayurveda source text
├── embed_pdf.py                # PDF → Pinecone indexing script
├── augment_and_reindex.py      # Data augmentation + reindexing
├── requirements.txt
└── .env                        # API keys (not committed)
```

---

## 🔧 Tech Stack

| Component | Technology |
|-----------|-----------|
| **Embeddings** | BAAI/bge-large-en-v1.5 (1024 dimensions) |
| **Vector DB** | Pinecone |
| **LLM** | Llama 3.3 70B via Groq |
| **Inference** | Custom forward + backward chaining engine |
| **Frontend** | Gradio 4.x |
| **Knowledge Base** | Vrikshayurveda by Surapala |

---

## 📚 References

- **Vrikshayurveda** — *The Science of Plant Life* by Surapala (ancient Indian botanical text)
- Surapala's Vrikshayurveda covers plant diseases, their causes (doshas), and Ayurvedic treatments using natural materials

---

## 📄 License

This project is licensed under the MIT License.