Create kitkat.py

kitkat.py

@@ -0,0 +1,93 @@
+import json
+import datasets
+
+_DESCRIPTION = "Catalan chatbot conversations from 10 different domains"
+_HOMEPAGE = "https://zenodo.org/records/7276036"
+_LICENSE  = "CC BY 4.0"
+_VERSION = "1.0.0"
+
+_DATAPATH = "KitKat.json"
+
+_CATEGORIES = [
+    "allotjament",
+    "banca",
+    "menjar_domicili",
+    "comerc",
+    "lloguer_vehicles",
+    "transports",
+    "assegurances",
+    "ajuntament",
+    "clinica",
+    "telefonia",
+]
+
+class KitKat(datasets.GeneratorBasedBuilder):
+    """ KitKat: Conversacional dataset for Catalan. """
+
+    VERSION = datasets.Version(_VERSION)
+
+    DEFAULT_CONFIG_NAME = "all"
+    BUILDER_CONFIGS = [datasets.BuilderConfig(name="all", version=VERSION, description="All categories.")]
+    for _CAT in _CATEGORIES:
+        BUILDER_CONFIGS.append(
+            datasets.BuilderConfig(name=_CAT, version=VERSION, description=f"Articles from category \"{_CAT}\"")
+        )
+
+    @staticmethod
+    def _info():
+        features = datasets.Features(
+            {
+                "id": datasets.Value("string"),
+                "category": datasets.Value("string"),
+                "conversation": [
+                    {
+                        # "id": datasets.Value("string"),
+                        "role": datasets.Value("string"),
+                        "text": datasets.Value("string"),
+                        "intent": datasets.Value("string"),
+                        "slots": [
+                            {
+                                "tag": datasets.Value("string"),
+                                "text": datasets.Value("string"),
+                                "Start_char": datasets.Value("int32"),
+                                "End_char": datasets.Value("int32"),
+                            }
+                        ]
+                    }
+                ]
+            }
+        )
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+        )
+
+    @staticmethod
+    def _split_generators(dl_manager):
+        data_dir = dl_manager.download_and_extract(_DATAPATH)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_dir,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        with open(filepath, encoding="utf-8") as f:
+            data = json.load(f)
+
+        _key = 0
+        for category,conversations in data["xats"].items():
+            if self.config.name in ["all", category]:
+                for conversation in conversations:
+                    yield _key, {
+                        "id": conversation["id"], # conversation["número"],
+                        "category": category,
+                        # "conversation": [{"id": x["id"], "role":x["actor"], "text":x["text"], "slots":x["slots"], "intent":x["intent"]} for x in conversation["frases"]]
+                        "conversation": [{"role":x["actor"], "text":x["text"], "slots":x["slots"], "intent":x["intent"]} for x in conversation["frases"]]
+                    }
+                    _key+=1