fix: format suggestions for ranking values (#4628)

<!-- Thanks for your contribution! As part of our Community Growers
initiative 🌱, we're donating Justdiggit bunds in your name to reforest
sub-Saharan Africa. To claim your Community Growers certificate, please
contact David Berenstein in our Slack community or fill in this form
https://tally.so/r/n9XrxK once your PR has been merged. -->

# Description

This PR fixes problems with HF format when passing ranking value objects
(instead of raw dictionaries).


**Type of change**

(Please delete options that are not relevant. Remember to title the PR
according to the type of change)

- [X] Bug fix (non-breaking change which fixes an issue)
- [ ] Breaking change (fix or feature that would cause existing
functionality to not work as expected)

**How Has This Been Tested**

(Please describe the tests that you ran to verify your changes. And
ideally, reference `tests`)

Tested locally

- [ ] Test A
- [ ] Test B

**Checklist**

- [ ] I followed the style guidelines of this project
- [ ] I did a self-review of my code
- [ ] My changes generate no new warnings
- [x] I have added tests that prove my fix is effective or that my
feature works
- [ ] I filled out [the contributor form](https://tally.so/r/n9XrxK)
(see text above)
- [x] I have added relevant notes to the `CHANGELOG.md` file (See
https://keepachangelog.com/)

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

CHANGELOG.md

@@ -16,6 +16,10 @@ These are the section headers that we use:
 
 ## [Unreleased]()
 
+### Fixed
+
+- Fixed prepare for training when passing `RankingValueSchema` instances to suggestions. ([#4628](https://github.com/argilla-io/argilla/pull/4628))
+
 ## [1.25.0](https://github.com/argilla-io/argilla/compare/v1.24.0...v1.25.0)
 
 > [!NOTE]

src/argilla/client/feedback/integrations/huggingface/dataset.py

@@ -148,7 +148,7 @@ def _huggingface_format(dataset: Union["FeedbackDataset", "RemoteFeedbackDataset
                 if record.suggestions:
                     for suggestion in record.suggestions:
                         if question.name == suggestion.question_name:
-                            suggestion_value = suggestion.value
+                            suggestion_value = suggestion.dict(include={"value"})["value"]
                             suggestion_metadata = {
                                 "type": suggestion.type,
                                 "score": suggestion.score,

src/argilla/client/feedback/schemas/records.py

@@ -130,15 +130,10 @@ class Config:
     def to_server_payload(self, question_name_to_id: Dict[str, UUID]) -> Dict[str, Any]:
         """Method that will be used to create the payload that will be sent to Argilla
         to create a `SuggestionSchema` for a `FeedbackRecord`."""
-        payload = {}
+        # We can do this because there is no default values for the fields
+        payload = self.dict(exclude_unset=True, include={"type", "score", "value", "agent"})
         payload["question_id"] = str(question_name_to_id[self.question_name])
-        payload["value"] = self.value
-        if self.type:
-            payload["type"] = self.type
-        if self.score:
-            payload["score"] = self.score
-        if self.agent:
-            payload["agent"] = self.agent
+
         return payload
 
 

src/argilla/client/feedback/training/schemas/base.py

@@ -410,7 +410,7 @@ def for_supervised_fine_tuning(
             >>> from argilla import TrainingTask
             >>> dataset = rg.FeedbackDataset.from_argilla(name="...")
             >>> def formatting_func(sample: Dict[str, Any]):
-            ...     annotations = sample["good]
+            ...     annotations = sample["good"]
             ...     if annotations and annotations[0]["value"] == "Bad":
             ...         return
             ...     return template.format(prompt=sample["prompt"][0]["value"], response=sample["response"][0]["value"])
@@ -973,7 +973,7 @@ class TrainingTaskForSFT(BaseModel, TrainingData):
         >>> from argilla import TrainingTaskForSFT
         >>> dataset = rg.FeedbackDataset.from_argilla(name="...")
         >>> def formatting_func(sample: Dict[str, Any]):
-        ...     annotations = sample["good]
+        ...     annotations = sample["good"]
         ...     if annotations and annotations[0]["value"] == "Bad":
         ...         return
         ...     yield template.format(prompt=sample["prompt"][0]["value"], response=sample["response"][0]["value"])

tests/integration/client/conftest.py

@@ -25,6 +25,7 @@
     LabelQuestion,
     MultiLabelQuestion,
     RankingQuestion,
+    RankingValueSchema,
     RatingQuestion,
     TextField,
     TextQuestion,
@@ -481,7 +482,9 @@ def feedback_dataset_records() -> List[FeedbackRecord]:
                         "question-2": {"value": 2},
                         "question-3": {"value": "b"},
                         "question-4": {"value": ["b", "c"]},
-                        "question-5": {"value": [{"rank": 1, "value": "a"}, {"rank": 2, "value": "b"}]},
+                        "question-5": {
+                            "value": [RankingValueSchema(rank=1, value="a"), RankingValueSchema(rank=2, value="b")]
+                        },
                     },
                     "status": "submitted",
                 }
@@ -517,7 +520,7 @@ def feedback_dataset_records() -> List[FeedbackRecord]:
                 },
                 {
                     "question_name": "question-5",
-                    "value": [{"rank": 1, "value": "a"}, {"rank": 2, "value": "b"}],
+                    "value": [RankingValueSchema(rank=1, value="a"), RankingValueSchema(rank=2, value="b")],
                     "type": "human",
                     "score": 0.0,
                     "agent": "agent-1",