add demo

Author: reluctanthero104

crates/skardi/src/sources/providers/sqlx/pg/postgres.rs

@@ -247,18 +247,6 @@ async fn register_postgres_catalog(
     let catalog_provider = Arc::new(MemoryCatalogProvider::new());
 
     for (schema, table_name) in &schema_tables {
-<<<<<<< HEAD
-        let table_reference = TableReference::partial(schema.as_str(), table_name.as_str());
-        let table_provider =
-            build_postgres_table_provider(&read_pool, table_reference, read_write, &sqlx_pool)
-                .await
-                .with_context(|| {
-                    format!(
-                        "Failed to build table provider for '{}.{}' in catalog '{}'",
-                        schema, table_name, catalog_name
-                    )
-                })?;
-=======
         let knn_key = format!("{}.{}.{}", catalog_name, schema, table_name);
         let table_provider = build_and_register_table(
             &read_pool,
@@ -276,7 +264,6 @@ async fn register_postgres_catalog(
                 schema, table_name, catalog_name
             )
         })?;
->>>>>>> b1fec0d (update postgres)
 
         if catalog_provider.schema(schema).is_none() {
             catalog_provider

demo/postgres/pipelines_for_catalog_example/vector_search_catalog.yaml

@@ -0,0 +1,21 @@
+metadata:
+  name: "vector-search-catalog"
+  version: "1.0.0"
+  description: >
+    KNN similarity search against a pgvector column loaded as part of a catalog entry.
+    In catalog mode the pg_knn registry key is "catalog.schema.table", so the first
+    argument must use the fully-qualified three-part name.
+    Pass a literal float array as {query_vector} — e.g. [0.6, 0.8, 0.0, 0.0].
+    Score is cosine distance in [0, 2] — lower means more similar.
+
+# Parameters:
+#   {query_vector} - Float array to search against, e.g. [0.6, 0.8, 0.0, 0.0]
+#   {limit}        - Maximum number of results to return
+
+query: |
+  SELECT id, content, metadata, _score
+  FROM pg_knn('mydb.public.documents', 'embedding',
+      {query_vector},
+      '<=>', 10)
+  ORDER BY _score
+  LIMIT {limit}