Upload Conversations.py

Conversations.py

@@ -1,14 +1,63 @@
+import datasets
+import os
 from datasets import Dataset, DatasetDict
 import gzip
 import json
 
 
-def load_dataset():
-    data = []
-    with gzip.open("conversations.jsonl.gz", "rt", encoding="utf-8") as f:
-        for line in f:
-            data.append(json.loads(line))
-    return Dataset.from_list(data)
+_CITATION = """\
+@misc{Conversations,
+  author       = {Ilya Koziev},
+  title        = {Russian-Language Dialogues Dataset},
+  year         = {2025},
+  publisher    = {Hugging Face},
+  howpublished = {\url{https://huggingface.co/datasets/inkoziev/Conversations}},
+}
+"""
 
 
-dataset = load_dataset()
+_DESCRIPTION = """\
+Russian-Language Dialogues Dataset
+"""
+
+
+class DatasetConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super(DatasetConfig, self).__init__(**kwargs)
+
+
+class Conversations(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIG_CLASS = DatasetConfig
+    BUILDER_CONFIGS = [
+        DatasetConfig(name="Conversations", version=datasets.Version("27.02.2025"), description=_DESCRIPTION),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+               {
+                   "domain": datasets.Value("string"),
+                   "conversation": datasets.Value("string"),
+               }
+            ),
+            supervised_keys=None,
+            homepage="",
+            citation=_CITATION,
+        )
+
+    def _split_generators(self,abc):
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    'path': "conversations.jsonl.gz"
+                }
+            ),
+        ]
+
+    def _generate_examples(self, path):
+        with gzip.open(path, "rt", encoding="utf-8") as f:
+            for iline, line in f:
+                yield json.loads(line)
+