“BeeRad”andClaude Opus 4.6
ec3ab74efe
- Switch rah_search_nodes and rah_search_content from LIKE to FTS5 with word-split LIKE fallback
- Rebuild nodes_fts and chunks_fts indexes on server startup
- Cap chunk field at 10K chars in rah_get_nodes (adds chunk_truncated, chunk_length)
- Multi-word queries now work ("Tesla manufacturing" finds both words anywhere)
- Relevance-ranked results when FTS available
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
3.1 KiB
3.1 KiB
name, description, immutable
| name | description | immutable |
|---|---|---|
| Schema | Full database schema, tables, columns, query patterns. | true |
Database Schema
Tables
nodes
| Column | Type | Notes |
|---|---|---|
| id | INTEGER | Primary key, auto-increment |
| title | TEXT | Required |
| description | TEXT | AI-generated grounding context (~1 sentence) |
| content | TEXT | User's notes/thoughts (not source content) |
| chunk | TEXT | Full verbatim source content |
| chunk_status | TEXT | 'pending', 'chunked', 'failed' |
| link | TEXT | External URL (only for nodes representing external content) |
| type | TEXT | Nullable (reserved for future use) |
| metadata | TEXT | JSON blob (map_position, transcript_length, etc.) |
| is_pinned | INTEGER | Legacy — use hub node queries instead |
| created_at | TEXT | ISO timestamp |
| updated_at | TEXT | ISO timestamp |
edges
| Column | Type | Notes |
|---|---|---|
| id | INTEGER | Primary key |
| from_node_id | INTEGER | FK → nodes.id |
| to_node_id | INTEGER | FK → nodes.id |
| context | TEXT | JSON: { explanation, category, type, confidence, created_via } |
| source | TEXT | 'user', 'ai_similarity', or helper name |
| explanation | TEXT | Human-readable reason for connection |
| created_at | TEXT | ISO timestamp |
dimensions
| Column | Type | Notes |
|---|---|---|
| name | TEXT | Primary key |
| description | TEXT | Purpose description |
| is_priority | INTEGER | 1 = priority dimension (auto-assigns to new nodes) |
| updated_at | TEXT | ISO timestamp |
node_dimensions (junction)
| Column | Type |
|---|---|
| node_id | INTEGER FK → nodes.id |
| dimension | TEXT (dimension name) |
chunks (for semantic search)
| Column | Type | Notes |
|---|---|---|
| id | INTEGER | Primary key |
| node_id | INTEGER | FK → nodes.id |
| chunk_idx | INTEGER | Position in sequence |
| text | TEXT | Chunk content |
| created_at | TEXT | ISO timestamp |
| embedding_type | TEXT | Embedding model used |
| metadata | TEXT | JSON blob |
FTS Tables
chunks_fts— full-text search on chunk textnodes_fts— full-text search on node title + content
Common Query Patterns
Top connected nodes (hubs):
SELECT n.id, n.title, n.description, COUNT(DISTINCT e.id) AS edge_count
FROM nodes n
LEFT JOIN edges e ON (e.from_node_id = n.id OR e.to_node_id = n.id)
GROUP BY n.id ORDER BY edge_count DESC LIMIT 5
Nodes in a dimension:
SELECT n.* FROM nodes n
JOIN node_dimensions nd ON n.id = nd.node_id
WHERE nd.dimension = ?
Edges for a node (both directions):
SELECT e.*, n1.title as from_title, n2.title as to_title
FROM edges e
JOIN nodes n1 ON e.from_node_id = n1.id
JOIN nodes n2 ON e.to_node_id = n2.id
WHERE e.from_node_id = ? OR e.to_node_id = ?
Search source content (chunks):
SELECT c.id, c.node_id, c.chunk_idx, c.text, n.title
FROM chunks c
JOIN nodes n ON c.node_id = n.id
WHERE c.text LIKE '%search term%' COLLATE NOCASE
ORDER BY c.chunk_idx ASC
LIMIT 10
Use rah_search_content to search chunks by keyword, or rah_sqlite_query for any read operation not covered by structured tools.