Upload kokorochat.py

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)