Fix to Return Similarity Scores Along with Records (#5778)

# Description
<!-- Please include a summary of the changes and the related issue.
Please also include relevant motivation and context. List any
dependencies that are required for this change. -->

Closes #5777 

**Type of change**
<!-- Please delete options that are not relevant. Remember to title the
PR according to the type of change -->

- Improvement (change adding some improvement to an existing
functionality)

**How Has This Been Tested**
<!-- Please add some reference about how your feature has been tested.
-->
Passes similar param in query method while fetching records and could
see returning similarity score.

**Checklist**
<!-- Please go over the list and make sure you've taken everything into
account -->

- I added relevant documentation
- I followed the style guidelines of this project
- I did a self-review of my code
- I made corresponding changes to the documentation
- I confirm My changes generate no new warnings
- I have added tests that prove my fix is effective or that my feature
works
- I have added relevant notes to the CHANGELOG.md file (See
https://keepachangelog.com/)

---------

Co-authored-by: Sai Kiran Bonu <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Francisco Aranda <[email protected]>
Co-authored-by: Paco Aranda <[email protected]>

argilla/CHANGELOG.md

@@ -16,6 +16,10 @@ These are the section headers that we use:
 
 ## [Unreleased]()
 
+### Added
+
+- Return similarity score when searching by similarity. ([#5778](https://github.com/argilla-io/argilla/pull/5778))
+
 ## [2.6.0](https://github.com/argilla-io/argilla/compare/v2.5.0...v2.6.0)
 
 ### Fixed

argilla/src/argilla/records/_dataset_records.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 import warnings
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Sequence, Union
+from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Sequence, Tuple, Union
 from uuid import UUID
 from enum import Enum
 
@@ -86,7 +86,7 @@ def _limit_reached(self) -> bool:
             return False
         return self.__limit <= 0
 
-    def _next_record(self) -> Record:
+    def _next_record(self) -> Union[Record, Tuple[Record, float]]:
         if self._limit_reached() or self._no_records():
             raise StopIteration()
 
@@ -104,15 +104,23 @@ def _fetch_next_batch(self) -> None:
         self.__records_batch = list(self._list())
         self.__offset += len(self.__records_batch)
 
-    def _list(self) -> Sequence[Record]:
-        for record_model in self._fetch_from_server():
-            yield Record.from_model(model=record_model, dataset=self.__dataset)
-
-    def _fetch_from_server(self) -> List[RecordModel]:
+    def _list(self) -> Sequence[Union[Record, Tuple[Record, float]]]:
         if not self.__client.api.datasets.exists(self.__dataset.id):
             warnings.warn(f"Dataset {self.__dataset.id!r} does not exist on the server. Skipping...")
             return []
-        return self._fetch_from_server_with_search() if self._is_search_query() else self._fetch_from_server_with_list()
+
+        if self._is_search_query():
+            records = self._fetch_from_server_with_search()
+
+            if self.__query.has_similar():
+                for record_model, score in records:
+                    yield Record.from_model(model=record_model, dataset=self.__dataset), score
+            else:
+                for record_model, _ in records:
+                    yield Record.from_model(model=record_model, dataset=self.__dataset)
+        else:
+            for record_model in self._fetch_from_server_with_list():
+                yield Record.from_model(model=record_model, dataset=self.__dataset)
 
     def _fetch_from_server_with_list(self) -> List[RecordModel]:
         return self.__client.api.records.list(
@@ -124,7 +132,7 @@ def _fetch_from_server_with_list(self) -> List[RecordModel]:
             with_vectors=self.__with_vectors,
         )
 
-    def _fetch_from_server_with_search(self) -> List[RecordModel]:
+    def _fetch_from_server_with_search(self) -> List[Tuple[RecordModel, float]]:
         search_items, total = self.__client.api.records.search(
             dataset_id=self.__dataset.id,
             query=self.__query.api_model(),
@@ -134,7 +142,7 @@ def _fetch_from_server_with_search(self) -> List[RecordModel]:
             with_suggestions=self.__with_suggestions,
             with_vectors=self.__with_vectors,
         )
-        return [record_model for record_model, _ in search_items]
+        return search_items
 
     def _is_search_query(self) -> bool:
         return self.__query.has_search()

argilla/src/argilla/records/_io/_datasets.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 import warnings
-from typing import TYPE_CHECKING, Any, Dict, List, Union, Optional
+from typing import TYPE_CHECKING, Any, Dict, List, Union, Optional, Tuple
 
 from datasets import Dataset as HFDataset, Sequence
 from datasets import Image, ClassLabel, Value
@@ -194,7 +194,7 @@ def _is_hf_dataset(dataset: Any) -> bool:
         return isinstance(dataset, HFDataset)
 
     @staticmethod
-    def to_datasets(records: List["Record"], dataset: "Dataset") -> HFDataset:
+    def to_datasets(records: List[Union["Record", Tuple["Record", float]]], dataset: "Dataset") -> HFDataset:
         """
         Export the records to a Hugging Face dataset.
 

argilla/src/argilla/records/_io/_generic.py

@@ -13,7 +13,7 @@
 # limitations under the License.
 
 from collections import defaultdict
-from typing import Any, Dict, List, TYPE_CHECKING, Union
+from typing import Any, Dict, List, Tuple, TYPE_CHECKING, Union
 
 if TYPE_CHECKING:
     from argilla import Record
@@ -24,7 +24,9 @@ class GenericIO:
     It handles methods for exporting records to generic python formats."""
 
     @staticmethod
-    def to_list(records: List["Record"], flatten: bool = False) -> List[Dict[str, Union[str, float, int, list]]]:
+    def to_list(
+        records: List[Union["Record", Tuple["Record", float]]], flatten: bool = False
+    ) -> List[Dict[str, Union[str, float, int, list]]]:
         """Export records to a list of dictionaries with either names or record index as keys.
         Args:
             flatten (bool): The structure of the exported dictionary.
@@ -48,7 +50,7 @@ def to_list(records: List["Record"], flatten: bool = False) -> List[Dict[str, Un
 
     @classmethod
     def to_dict(
-        cls, records: List["Record"], flatten: bool = False, orient: str = "names"
+        cls, records: List[Union["Record", Tuple["Record", float]]], flatten: bool = False, orient: str = "names"
     ) -> Dict[str, Union[str, float, int, list]]:
         """Export records to a dictionary with either names or record index as keys.
         Args:
@@ -79,10 +81,10 @@ def to_dict(
     ############################
 
     @staticmethod
-    def _record_to_dict(record: "Record", flatten=False) -> Dict[str, Any]:
+    def _record_to_dict(record: Union["Record", Tuple["Record", float]], flatten=False) -> Dict[str, Any]:
         """Converts a Record object to a dictionary for export.
         Args:
-            record (Record): The Record object to convert.
+            record (Record): The Record object or the record and the linked score to convert.
             flatten (bool): The structure of the exported dictionary.
                 - True: The record fields, metadata, suggestions and responses will be flattened
                         so that their keys becomes the keys of the record dictionary, using
@@ -92,6 +94,12 @@ def _record_to_dict(record: "Record", flatten=False) -> Dict[str, Any]:
         Returns:
             A dictionary representing the record.
         """
+        if isinstance(record, tuple):
+            record, score = record
+
+            record_dict = GenericIO._record_to_dict(record, flatten)
+            record_dict["score"] = score
+            return record_dict
 
         record_dict = record.to_dict()
         if flatten:

argilla/src/argilla/records/_io/_json.py

@@ -13,15 +13,15 @@
 # limitations under the License.
 import json
 from pathlib import Path
-from typing import List, Union
+from typing import List, Tuple, Union
 
 from argilla.records._resource import Record
 from argilla.records._io import GenericIO
 
 
 class JsonIO:
     @staticmethod
-    def to_json(records: List["Record"], path: Union[Path, str]) -> Path:
+    def to_json(records: List[Union["Record", Tuple["Record", float]]], path: Union[Path, str]) -> Path:
         """
         Export the records to a file on disk. This is a convenient shortcut for dataset.records(...).to_disk().
 
@@ -37,6 +37,7 @@ def to_json(records: List["Record"], path: Union[Path, str]) -> Path:
             path = Path(path)
         if path.exists():
             raise FileExistsError(f"File {path} already exists.")
+
         record_dicts = GenericIO.to_list(records, flatten=False)
         with open(path, "w") as f:
             json.dump(record_dicts, f)

argilla/src/argilla/records/_search.py

@@ -175,7 +175,10 @@ def __init__(
         self.similar = similar
 
     def has_search(self) -> bool:
-        return bool(self.query or self.similar or self.filter)
+        return bool(self.query or self.has_similar() or self.filter)
+
+    def has_similar(self) -> bool:
+        return bool(self.similar)
 
     def api_model(self) -> SearchQueryModel:
         model = SearchQueryModel()

argilla/tests/integration/test_search_records.py

@@ -173,7 +173,7 @@ def test_search_records_by_similar_value(self, client: Argilla, dataset: Dataset
             )
         )
         assert len(records) == 1000
-        assert records[0].id == str(data[3]["id"])
+        assert records[0][0].id == str(data[3]["id"])
 
     def test_search_records_by_least_similar_value(self, client: Argilla, dataset: Dataset):
         data = [
@@ -194,7 +194,7 @@ def test_search_records_by_least_similar_value(self, client: Argilla, dataset: D
                 )
             )
         )
-        assert records[-1].id == str(data[3]["id"])
+        assert records[-1][0].id == str(data[3]["id"])
 
     def test_search_records_by_similar_record(self, client: Argilla, dataset: Dataset):
         data = [
@@ -218,7 +218,7 @@ def test_search_records_by_similar_record(self, client: Argilla, dataset: Datase
             )
         )
         assert len(records) == 1000
-        assert records[0].id != str(record.id)
+        assert records[0][0].id != str(record.id)
 
     def test_search_records_by_least_similar_record(self, client: Argilla, dataset: Dataset):
         data = [
@@ -241,4 +241,4 @@ def test_search_records_by_least_similar_record(self, client: Argilla, dataset:
                 )
             )
         )
-        assert all(r.id != str(record.id) for r in records)
+        assert all(r.id != str(record.id) for r, s in records)

argilla/tests/unit/test_io/test_generic.py

@@ -60,3 +60,38 @@ def test_to_list_flatten(self):
                 "q2.suggestion.agent": None,
             }
         ]
+
+    def test_records_tuple_to_list(self):
+        record = rg.Record(fields={"field": "The field"}, metadata={"key": "value"})
+
+        records_list = GenericIO.to_list(
+            [
+                (record, 1.0),
+                (record, 0.5),
+            ]
+        )
+
+        assert records_list == [
+            {
+                "id": str(record.id),
+                "status": record.status,
+                "_server_id": record._server_id,
+                "fields": {"field": "The field"},
+                "metadata": {"key": "value"},
+                "responses": {},
+                "vectors": {},
+                "suggestions": {},
+                "score": 1.0,
+            },
+            {
+                "id": str(record.id),
+                "status": record.status,
+                "_server_id": record._server_id,
+                "fields": {"field": "The field"},
+                "metadata": {"key": "value"},
+                "responses": {},
+                "vectors": {},
+                "suggestions": {},
+                "score": 0.5,
+            },
+        ]