KokoroChat / kokorochat.py
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import json
from datasets import DatasetInfo, GeneratorBasedBuilder, SplitGenerator, Split, Value, Sequence
class KokoroChat(GeneratorBasedBuilder):
def _info(self):
return DatasetInfo(
description="KokoroChat: A Japanese psychological counseling dialogue dataset.",
features={
"dialogue": Sequence({
"role": Value("string"),
"time": Value("string"),
"utterance": Value("string")
}),
"topic": {
"main_jp": Value("string"),
"main_en": Value("string"),
"sub": Value("string")
},
"review_by_client_jp": {
"評価ID": Value("int32"),
"評価作成日時": Value("string"),
"クライアント役ID": Value("int32"),
"カウンセラー役ID": Value("int32"),
"点数": Value("int32"),
"聴いてもらえた、わかってもらえたと感じた": Value("int32"),
"尊重されたと感じた": Value("int32"),
"新しい気づきや体験があった": Value("int32"),
"希望や期待を感じられた": Value("int32"),
"取り組みたかったことを扱えた": Value("int32"),
"一緒に考えながら取り組めた": Value("int32"),
"やりとりのリズムがあっていた": Value("int32"),
"居心地のよいやりとりだった": Value("int32"),
"全体として適切でよかった": Value("int32"),
"今回の相談は価値があった": Value("int32"),
"相談開始の円滑さ": Value("int32"),
"相談終了のタイミング(不必要に聴きすぎていないか)、円滑さ": Value("int32"),
"受容・共感": Value("int32"),
"肯定・承認": Value("int32"),
"的確な質問による会話の促進": Value("int32"),
"要約": Value("int32"),
"問題の明確化": Value("int32"),
"この相談での目標の明確化": Value("int32"),
"次の行動につながる提案": Value("int32"),
"勇気づけ・希望の喚起": Value("int32"),
"無理解と軽率さによる傷つけ発言": Value("string"),
"その他の倫理違反が疑われる発言": Value("string"),
"離脱": Value("string")
},
"review_by_client_en": {
"evaluation_id": Value("int32"),
"evaluation_created_at": Value("string"),
"client_id": Value("int32"),
"counselor_id": Value("int32"),
"score": Value("int32"),
"felt_heard_and_understood": Value("int32"),
"felt_respected": Value("int32"),
"gained_new_insights": Value("int32"),
"felt_hopeful_or_expectant": Value("int32"),
"concerns_were_addressed": Value("int32"),
"thought_through_concerns_together": Value("int32"),
"conversation_had_good_rhythm": Value("int32"),
"conversation_felt_comfortable": Value("int32"),
"felt_appropriate_and_satisfying": Value("int32"),
"conversation_was_valuable": Value("int32"),
"conversation_started_smoothly": Value("int32"),
"conversation_ended_well": Value("int32"),
"showed_acceptance_and_empathy": Value("int32"),
"provided_acknowledgment_and_affirmation": Value("int32"),
"asked_effective_questions": Value("int32"),
"summarized_key_points_effectively": Value("int32"),
"clarified_issues_cleraly": Value("int32"),
"helped_identify_goals": Value("int32"),
"offered_actionable_suggestions": Value("int32"),
"encouraged_and_instilled_hope": Value("int32"),
"harmful_due_to_ignorance": Value("string"),
"other_potentially_unethical": Value("string"),
"unwilling_to_continue": Value("string")
}
},
supervised_keys=None
)
def _split_generators(self, dl_manager):
data_path = dl_manager.download_and_extract("Kokorochat_dialogues.jsonl")
return [
SplitGenerator(name=Split.TRAIN, gen_kwargs={"filepath": data_path})
]
def _generate_examples(self, filepath):
with open(filepath, encoding="utf-8") as f:
for i, line in enumerate(f):
yield i, json.loads(line)