examples: use uniform api #29

Author: dan-obx

example/ollama/llamas.py

@@ -57,10 +57,8 @@ class DocumentEmbedding:
   model="mxbai-embed-large"
 )
 
-
-embedding_prop: Property = DocumentEmbedding.get_property("embedding")
 query = box.query(
-    embedding_prop.nearest_neighbor(response["embedding"], 1)
+    DocumentEmbedding.embedding.nearest_neighbor(response["embedding"], 1)
 ).build()
 
 results = query.find_with_scores()

example/vectorsearch-cities/__main__.py

@@ -25,8 +25,6 @@ def __init__(self, *args):
         new_db = not os.path.exists(dbdir)
         self._store = objectbox.Store(model=get_objectbox_model(),directory=dbdir)
         self._box = self._store.box(City)
-        self._name_prop: Property = City.get_property("name")
-        self._location_prop: Property = City.get_property("location")
         if new_db: 
             with open(os.path.join(os.path.dirname(__file__), 'cities.csv')) as f:
                 r = csv.reader(f) 
@@ -40,8 +38,7 @@ def __init__(self, *args):
 
     def do_ls(self, name: str = ""):
         """list all cities or starting with <prefix>\nusage: ls [<prefix>]"""
-        qb = self._box.query()
-        qb.starts_with_string(self._name_prop, name)
+        qb = self._box.query( City.name.starts_with(name) )
         query = qb.build()
         list_cities(query.find())
 
@@ -57,15 +54,15 @@ def do_city_neighbors(self, args: str):
             num = 5
             if len(args) == 2:
                 num = int(args[1])
-            qb = self._box.query()
-            qb.equals_string(self._name_prop, city)
+            qb = self._box.query( City.name.equals(city) )
             query = qb.build()
             cities = query.find()
             if len(cities) == 1:
                 location = cities[0].location
-                qb = self._box.query()
-                qb.nearest_neighbors_f32(self._location_prop, location, num+1) # +1 for the city
-                qb.not_equals_string(self._name_prop, city)
+                # +1 for the city
+                qb = self._box.query(
+                    City.location.nearest_neighbor(location, num+1) & City.name.not_equals(city)
+                )
                 neighbors = qb.build().find_with_scores()
                 list_cities_with_scores(neighbors)
             else:
@@ -81,8 +78,9 @@ def do_neighbors(self, args):
                 raise ValueError()
             num = int(args[0])
             geocoord = [ float(args[1]), float(args[2]) ]
-            qb = self._box.query()
-            qb.nearest_neighbors_f32(self._location_prop, geocoord, num)
+            qb = self._box.query(
+                City.location.nearest_neighbor(geocoord, num)
+            )
             neighbors = qb.build().find_with_scores()
             list_cities_with_scores(neighbors)
         except ValueError: