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381fcf5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 | # cypher4sql
Neo4j-enhanced context engineering for SQL generation.
## Overview
cypher4sql uses Neo4j schema graphs to provide rich context for text-to-SQL models:
- **Semantic table retrieval** via vector embeddings
- **FK statistics** (fanout, cardinality, risk tags)
- **Join path finding** for multi-hop queries
- **Planner hints** for complex joins
## Architecture
```
User Question
↓
┌─────────────────────────────────────┐
│ Neo4j Schema Graph (cypher4sql) │
│ - Vector search → relevant tables │
│ - FK stats → join risk/hints │
│ - Path finding → join options │
└─────────────────────────────────────┘
↓
Enhanced Context + FK Stats
↓
SQL Model → Query
```
## Usage
### Training
- FK stats for reward shaping
- Mutation validation (Phase 3.5)
- Context engineering for training data
### Production
- Live schema retrieval
- Semantic table ranking
- FK stats for query planning
## FK Stats Format (v4)
```
Join Options:
1. orders.customer_id -> customers.id [1:N, fk_u=0.85, n=50000, fanout=3.2, risk=MED]
2. order_items.order_id -> orders.id [1:N, fk_u=1.00, n=150000, fanout=2.8, risk=LOW]
Safe (no-dup) joins: order_items->orders
```
## License
MIT
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