# DuckPGQ Knowledge Graph Implementation
**Date**: 2025-10-26
**Status**: In Progress
______________________________________________________________________
## Overview
Adding semantic memory (knowledge graph) to session-buddy using:
- **DuckDB + DuckPGQ** extension (no external database required!)
- **Separate database file**: `~/.claude/data/knowledge_graph.duckdb`
- **SQL/PGQ standard** (Property Graph Queries - SQL:2023)
- **Auto entity extraction** from conversations
______________________________________________________________________
## Architecture
### Dual Memory System
```
session-buddy Memory System
├── Episodic Memory (reflection.duckdb)
│ ├── conversations (vector search)
│ ├── reflections
│ └── Full conversation history
│
└── Semantic Memory (knowledge_graph.duckdb)
├── kg_entities (graph nodes)
├── kg_relationships (graph edges)
└── Knowledge graph structure
```
### Why Separate Databases?
1. **Clean separation of concerns** - Conversations vs structured knowledge
1. **Independent scaling** - Can optimize each database separately
1. **Easier backup/restore** - Can backup knowledge graph independently
1. **Follows single responsibility principle**
______________________________________________________________________
## DuckPGQ Extension
### What is DuckPGQ?
DuckPGQ is a **community extension** for DuckDB that adds:
- SQL/PGQ support (Property Graph Queries - official SQL:2023 standard)
- Graph pattern matching with Cypher-like syntax
- Property graphs with nodes and edges
- Graph algorithms (shortest path, etc.)
- Persistent graphs
### Installation
```python
import duckdb
conn = duckdb.connect("~/.claude/data/knowledge_graph.duckdb")
conn.execute("INSTALL duckpgq FROM community")
conn.execute("LOAD duckpgq")
```
That's it! No external database needed.
### SQL/PGQ Query Examples
```sql
-- Find all projects that use Python
SELECT *
FROM GRAPH_TABLE (knowledge_graph
MATCH (proj:Project)-[r:uses]->(lang:Language)
WHERE lang.name = 'Python'
COLUMNS (proj.name AS project_name, lang.name AS language)
);
-- Find paths between entities
SELECT *
FROM GRAPH_TABLE (knowledge_graph
MATCH (start:Project)-[path:*1..3]->(end:Technology)
WHERE start.name = 'session-buddy'
AND end.name = 'ACB'
COLUMNS (start.name AS from, end.name AS to, path)
);
```
______________________________________________________________________
## Implementation Components
### 1. KnowledgeGraphDatabase Class
**File**: `session_buddy/knowledge_graph_db.py`
**Key Methods**:
- `create_entity(name, entity_type, observations)` - Add node
- `create_relation(from, to, relation_type)` - Add edge
- `search_entities(query)` - Find nodes
- `find_path(from, to, max_depth)` - SQL/PGQ path finding
- `get_stats()` - Graph statistics
### 2. MCP Tools (10 total)
**File**: `session_buddy/tools/knowledge_graph_tools.py`
1. `create_entity` - Create node
1. `create_relation` - Create edge
1. `add_observation` - Add fact to entity
1. `search_entities` - Find entities
1. `find_relationships` - Get connections
1. `find_path` - Path between entities
1. `get_entity_details` - Full entity info
1. `list_entity_types` - Show all types
1. `list_relation_types` - Show all relations
1. `knowledge_graph_stats` - Statistics
### 3. Auto Entity Extraction
**File**: `session_buddy/extractors/entity_extractor.py`
Automatically extracts entities from conversations using:
- Regex patterns for projects, libraries, technologies
- Confidence scoring
- Integration with conversation storage
______________________________________________________________________
## Design Decisions
✅ **Separate database file** - Clean isolation
✅ **Separate KnowledgeGraphDatabase class** - Single responsibility
✅ **Auto entity extraction** - Knowledge graph builds automatically
✅ **Full testing** - Unit tests + integration tests
______________________________________________________________________
## Timeline
- **Phase 1**: Foundation & Schema (2-3 hours) - ✅ IN PROGRESS
- **Phase 2**: MCP Tools (3-4 hours)
- **Phase 3**: Auto Entity Extraction (4-5 hours)
- **Phase 4**: Testing (3-4 hours)
- **Phase 5**: Documentation & Migration (1-2 hours)
**Total**: ~14 hours over 4 days
______________________________________________________________________
## Benefits
1. ✅ **Zero installation** - DuckDB already in dependencies
1. ✅ **No external processes** - Everything embedded
1. ✅ **SQL standard** - SQL/PGQ is official SQL:2023
1. ✅ **Active development** - DuckDB blog post Oct 2025
1. ✅ **Perfect for local development**
1. ✅ **Auto-builds from conversations**
______________________________________________________________________
## References
- DuckPGQ: https://duckpgq.org/
- DuckDB Blog (Oct 2025): https://duckdb.org/2025/10/22/duckdb-graph-queries-duckpgq
- SQL/PGQ Documentation: https://duckpgq.org/documentation/sql_pgq/
