webcoderz commented on issue #1121:
URL: https://github.com/apache/age/issues/1121#issuecomment-3728015238
WIP as i mess with it more
# Apache AGE + pgvector
- **Apache AGE** (`age`) for Cypher queries
- **pgvector** (`vector`) for vector operations + ANN indexes
## Required session setup
AGE requires loading the extension and setting `search_path`:
```sql
LOAD 'age';
SET search_path = ag_catalog, public;
```
Why `public`?
- `vector` is installed into the `public` schema in our stack
- Cypher queries that cast to `::vector` (or call distance functions) need
`public` visible
- vector ops fail when `public` isn’t in the `search_path`, and start
working once it is.
## Basic Cypher execution from SQL
AGE is called through `cypher(graph_name, $$ ... $$)` and you must provide
an `AS (...)` return type list:
```sql
SELECT * FROM cypher('my_graph', $$ MATCH (n) RETURN n $$) AS (n agtype);
```
## Vector casts and operators inside Cypher
From the regression test, these casts are supported:
- `"[1.22,2.22,3.33]"::vector`
- `[1.22,2.22,3.33]::vector`
- `...::vector(3)` (dimension constrained)
And ordering by cosine distance works via the `<=>` operator:
```sql
SELECT * FROM cypher('graph', $$
MATCH (m:Movie)
RETURN m.title
ORDER BY m.embedding::vector(4) <=> [-0.1, 0.2, 0.3, -0.4]::vector(4)
ASC LIMIT 10
$$) AS (title agtype);
```
## Vector indexes (HNSW) on AGE vertex properties
The regression test demonstrates creating a HNSW index on a vertex property
by building an expression that extracts the property and casts it to
`vector(N)`:
1) Find the internal schema OID for the AGE graph
2) `CREATE INDEX ... USING hnsw ((... )::vector(N)) vector_cosine_ops;`
This is the core recipe to make vector similarity in AGE fast.
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