feat: support list of strings for Weaviate

docarray/index/backends/weaviate.py

@@ -18,6 +18,8 @@
     TypeVar,
     Union,
     cast,
+    get_origin,
+    get_args,
 )
 
 import numpy as np
@@ -43,7 +45,6 @@
 TSchema = TypeVar('TSchema', bound=BaseDoc)
 T = TypeVar('T', bound='WeaviateDocumentIndex')
 
-
 DEFAULT_BATCH_CONFIG = {
     "batch_size": 20,
     "dynamic": False,
@@ -210,6 +211,8 @@
                 self.bytes_columns.append(column_name)
             if column_info.db_type == 'number[]':
                 self.nonembedding_array_columns.append(column_name)
+            if column_info.db_type == 'text[]':
+                self.nonembedding_array_columns.append(column_name)
             prop = {
                 "name": column_name
                 if column_name != 'id'
@@ -253,6 +256,8 @@
                 'number': {},
                 'boolean': {},
                 'number[]': {},
+                'int[]': {},
+                'text[]': {},
                 'blob': {},
             }
         )
@@ -717,6 +722,23 @@
             bytes: 'blob',
         }
 
+        if get_origin(python_type) == list:
+            py_weaviate_list_type_map = {
+                int: 'int[]',
+                float: 'number[]',
+                str: 'text[]',
+            }
+
+            container_type = None
+            args = get_args(python_type)
+            if args:
+                container_type = args[0]
+            if (
+                container_type is not None
+                and container_type in py_weaviate_list_type_map
+            ):
+                return py_weaviate_list_type_map[container_type]
+
         for py_type, weaviate_type in py_weaviate_type_map.items():
             if safe_issubclass(python_type, py_type):
                 return weaviate_type

tests/index/weaviate/docker-compose.yml

@@ -1,4 +1,4 @@
-version: '3.8'
+version: '3.3'
 
 services:
 
@@ -10,7 +10,7 @@ services:
     - '8080'
     - --scheme
     - http
-  image: semitechnologies/weaviate:1.18.3
+  image: semitechnologies/weaviate:1.21.1
   ports:
     - "8080:8080"
   restart: on-failure:0
@@ -24,4 +24,4 @@ services:
     LOG_LEVEL: debug # verbose
     LOG_FORMAT: text
     # LOG_LEVEL: trace # very verbose
-    GODEBUG: gctrace=1 # make go garbage collector verbose
+    GODEBUG: gctrace=1 # make go garbage collector verbose

tests/index/weaviate/test_index_get_del_weaviate.py

@@ -6,6 +6,7 @@
 import numpy as np
 import pytest
 from pydantic import Field
+from typing import List
 
 from docarray import BaseDoc
 from docarray.documents import ImageDoc, TextDoc
@@ -31,6 +32,9 @@ class SimpleDoc(BaseDoc):
 class Document(BaseDoc):
     embedding: NdArray[2] = Field(dim=2, is_embedding=True)
     text: str = Field()
+    texts: List[str] = Field(default=[])
+    # integers: List[int] = Field(default=[])
+    floats: List[float] = Field(default=[])
 
 
 class NestedDocument(BaseDoc):
@@ -50,7 +54,14 @@ def documents():
 
     # create the docs by enumerating from 1 and use that as the id
     docs = [
-        Document(id=str(i), embedding=embedding, text=text)
+        Document(
+            id=str(i),
+            embedding=embedding,
+            text=text,
+            texts=[f'text{i}_0', f'text{i}_1'],
+            integers=[i, i],
+            floats=[1.5 * i, 2.5 * i],
+        )
         for i, (embedding, text) in enumerate(zip(embeddings, texts))
     ]
 
@@ -170,6 +181,8 @@ class Document(BaseDoc):
         ({"path": ["text"], "operator": "Equal", "valueText": "lorem ipsum"}, 1),
         ({"path": ["text"], "operator": "Equal", "valueText": "foo"}, 0),
         ({"path": ["id"], "operator": "Equal", "valueString": "1"}, 1),
+        ({"path": ["texts"], "operator": "ContainsAny", "valueText": ["text"]}, 3),
+        ({"path": ["texts"], "operator": "ContainsAny", "valueText": ["text1_"]}, 1),
     ],
 )
 def test_filter(test_index, filter_query, expected_num_docs):