docarray · JohannesMessner · Nov 30, 2022 · Nov 29, 2022 · Nov 29, 2022 · Nov 29, 2022
diff --git a/docarray/array/storage/milvus/backend.py b/docarray/array/storage/milvus/backend.py
@@ -18,6 +18,7 @@
 from docarray import Document, DocumentArray
 from docarray.array.storage.base.backend import BaseBackendMixin, TypeMap
 from docarray.helper import dataclass_from_dict, _safe_cast_int
+from docarray.score import NamedScore
 
 if TYPE_CHECKING:
     from docarray.typing import (
@@ -266,16 +267,15 @@ def _docs_from_query_response(response):
         return DocumentArray([Document.from_base64(d['serialized']) for d in response])
 
     @staticmethod
-    def _docs_from_search_response(
-        responses,
-    ) -> 'List[DocumentArray]':
+    def _docs_from_search_response(responses, distance: str) -> 'List[DocumentArray]':
         das = []
         for r in responses:
-            das.append(
-                DocumentArray(
-                    [Document.from_base64(hit.entity.get('serialized')) for hit in r]
-                )
-            )
+            da = []
+            for hit in r:
+                doc = Document.from_base64(hit.entity.get('serialized'))
+                doc.scores[distance] = NamedScore(value=hit.score)
+                da.append(doc)
+            das.append(DocumentArray(da))
         return das
 
     def _update_kwargs_from_config(self, field_to_update, **kwargs):

diff --git a/docarray/array/storage/milvus/find.py b/docarray/array/storage/milvus/find.py
@@ -42,7 +42,7 @@ def _find(
                 output_fields=['serialized'],
                 **kwargs,
             )
-        return self._docs_from_search_response(results)
+        return self._docs_from_search_response(results, distance=self._config.distance)
 
     def _filter(self, filter, limit=10, **kwargs):
         kwargs = self._update_kwargs_from_config('consistency_level', **kwargs)

diff --git a/docs/advanced/document-store/extend.md b/docs/advanced/document-store/extend.md
@@ -289,6 +289,7 @@ class FindMixin:
         ...
 ```
 
+Make sure to store the distance scores in the `.scores` dictionary of the Documents that are being returned with the `distance` value as key.
 
 ## Step 6: summarize everything in `__init__.py`.
 

diff --git a/docs/advanced/document-store/milvus.md b/docs/advanced/document-store/milvus.md
@@ -253,6 +253,21 @@ Embeddings Nearest Neighbours with "price" at most 7:
 	embedding=[5. 5. 5.],	 price=5
 	embedding=[4. 4. 4.],	 price=4
 ```
+
+You can access the scores as follows:
+
+````python
+for doc in results:
+    print(f"score = {doc.scores[distance].value}")
+````
+
+```
+score = 3.0
+score = 12.0
+score = 27.0
+score = 48.0
+```
+
 ### Example of `.find` with only a filter
 
 The following example shows how to use DocArray with Milvus Document Store in order to filter text documents.

diff --git a/tests/unit/array/storage/milvus/test_milvus.py b/tests/unit/array/storage/milvus/test_milvus.py
@@ -73,6 +73,8 @@ def test_memory_cntxt_mngr(start_storage):
 @pytest.fixture()
 def mock_response():
     class MockHit:
+        score = 1.0
+
         @property
         def entity(self):
             return {'serialized': Document().to_base64()}
-Original file line number
+Diff line change
@@ Expand Up / @@ -289,6 +289,7 @@ class FindMixin: @@
             ...
     ```
+    Make sure to store the distance scores in the `.scores` dictionary of the Documents that are being returned with the `distance` value as key.
     ## Step 6: summarize everything in `__init__.py`.
@@ Expand Down @@