feat: add PATCH /api/v1/dataset/{dataset_id}/records endpoint

[gabrielmbmb]

Description

This PR adds the following:

• Updates PATCH /api/v1/records/{record_id} added in feat: add PATCH /api/v1/records/{record_id} endpoint #3920 allowing also to update the suggestions of a record. The suggestions in the input payload will replace the old suggestions.
• Add new PATCH /api/v1/datasets/{dataset_id}/records endpoint allowing to batch/bulk update the records of a dataset. The endpoint allow to update the same attributes from the record as in the PATCH /api/v1/records/{record_id} endpoint.
• Slightly modify the SearchDocument getter dict to do not try to populate the SearchDocument.responses attribute if the relationship has not been loaded (this allows us to not to have to load the Record.responses when updating the record document in the SearchEngine using add_records)
• Removes SearchEngine.update_record_metadata method as the same logic is covered by SearchEngine.add_records method, which can be also used to update the fields of an existing document.
• Rename SearchEngine.add_records method to SearchEngine.index_records as it can be used to both add and update records.

Type of change

• New feature (non-breaking change which adds functionality)

How Has This Been Tested

I made an small benchmark to test the latency of the new endpoint. I've created a dataset with 100000 records and all the possible questions and metadata properties. Then I built batches of 1000 records, updating all the responses and metadata fields, and sent them to the API. The average response time of the bulk PATCH endpoint was ~= 0.8 seconds.

Code used for benchmark

import uuid
import random
import argilla as rg

LABELS = ["a", "b", "c"]
RANKS = ["top-1", "top-2", "top-3"]

dataset = rg.FeedbackDataset(
  fields=[rg.TextField(name="text")],
  questions=[
      rg.TextQuestion(name="text"),
      rg.RatingQuestion(name="rating", values=[1, 2, 3, 4, 5]),
      rg.LabelQuestion(name="label", labels=LABELS),
      rg.MultiLabelQuestion(name="multi-label", labels=LABELS),
      rg.RankingQuestion(name="ranking", values=RANKS),
  ],
  metadata_properties=[
      rg.TermsMetadataProperty(name="label", values=LABELS),
      rg.IntegerMetadataProperty(name="integer", min=0, max=10),
      rg.FloatMetadataProperty(name="float", min=0, max=10),
  ],
)

dataset.add_records([rg.FeedbackRecord(fields={"text": "Hello"}, metadata={"extra": "yes"}) for _ in range(100000)])

remote = dataset.push_to_argilla(name=f"benchmark-{uuid.uuid4()}", workspace="gabriel")


def random_rank_order():
  ranks = RANKS.copy()
  ranks.sort(key=lambda x: random.random())
  return [{"value": rank, "rank": i + 1} for i, rank in enumerate(ranks)]


def build_update_payload(record):
  return {
      "id": str(record.id),
      "external_id": str(uuid.uuid4()),
      "metadata": {
          "label": random.choice(["a", "b", "c"]),
          "integer": random.randint(0, 10),
          "float": random.uniform(0, 10),
      },
      "suggestions": [
          {"question_id": str(remote.questions[0].id), "value": "hello world" * random.randint(1, 15)},
          {"question_id": str(remote.questions[1].id), "value": random.randint(1, 5)},
          {"question_id": str(remote.questions[2].id), "value": random.choice(["a", "b", "c"])},
          {"question_id": str(remote.questions[3].id), "value": [random.choice(["a", "b", "c"])]},
          {"question_id": str(remote.questions[4].id), "value": random_rank_order()},
      ],
  }

http_client = rg.active_client().http_client

elapseds = []

batch = []
for record in remote.records:
  batch.append(build_update_payload(record))

  if len(batch) == 1000:
      response = http_client.httpx.patch(f"/api/v1/datasets/{remote.id}/records", json={"items": batch})
      elapseds.append(response.elapsed.total_seconds())
      batch = []

average_elapsed_time = sum(elapseds) / len(elapseds)

print("Average elapsed time", average_elapsed_time)

Checklist

• 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
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• I filled out the contributor form (see text above)
• I have added relevant notes to the CHANGELOG.md file (See https://keepachangelog.com/)

[github-actions]

The URL of the deployed environment for this PR is https://argilla-quickstart-pr-3934-ki24f765kq-no.a.run.app