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import json
from pathlib import Path
from typing import Dict, List, Tuple
import datasets
from seacrowd.utils import schemas
from seacrowd.utils.configs import SEACrowdConfig
from seacrowd.utils.constants import Tasks, Licenses
_CITATION = """\
@article{kautsar2023indotod,
author={Kautsar, Muhammad Dehan Al and Nurdini, Rahmah Khoirussyifa' and Cahyawijaya, Samuel and Winata, Genta Indra and Purwarianti, Ayu},
title={IndoToD: A Multi-Domain Indonesian Benchmark For End-to-End Task-Oriented Dialogue Systems},
journal={arXiv preprint arXiv:2311.00958},
year={2023},
}
"""
_LANGUAGES = ["ind"]
_LOCAL = False
_DATASETNAME = "indocamrest"
_DESCRIPTION = """\
IndoCamRest is a synthetic task-oriented dialogue system dataset that translated from Cambridge Restaurant 676 (CamRest) dataset (Wen et al., 2016) into the new Indonesian parallel dataset using the translation pipeline method including the delexicalization, translation, and delexicalization.
The dataset consists of 676 dialogues in the restaurant reservation domain, with a user and an agent talking to each other to search the restaurant near the user.
It also consists of slots and dialogue acts from the user and the agent.
"""
_HOMEPAGE = "https://github.com/dehanalkautsar/IndoToD/tree/main/IndoCamRest"
_LICENSE = Licenses.CC_BY_SA_4_0.value
_URLS = {
_DATASETNAME: "https://raw.githubusercontent.com/dehanalkautsar/IndoToD/main/IndoCamRest/IndoCamRest676.json",
}
_SUPPORTED_TASKS = [Tasks.E2E_TASK_ORIENTED_DIALOGUE]
_SOURCE_VERSION = "1.0.0"
_SEACROWD_VERSION = "2024.06.20"
class IndoCamRest(datasets.GeneratorBasedBuilder):
"""IndoToD: A Multi-Domain Indonesian Benchmark For End-to-End Task-Oriented Dialogue Systems"""
SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
BUILDER_CONFIGS = [
SEACrowdConfig(
name="indocamrest_source",
version=SOURCE_VERSION,
description="IndoToD: IndoCamRest source schema",
schema="source",
subset_id="indocamrest",
),
SEACrowdConfig(
name="indocamrest_seacrowd_tod",
version=SEACROWD_VERSION,
description="IndoToD: IndoCamRest SEACrowd End-to-end Task Oriented Dialogue schema",
schema="seacrowd_tod",
subset_id="indocamrest",
),
]
DEFAULT_CONFIG_NAME = "indocamrest_source"
def _info(self) -> datasets.DatasetInfo:
if self.config.schema == "source":
features = datasets.Features(
{
"index": datasets.Value("string"),
"dialogue_id": datasets.Value("int32"),
"finished": datasets.Value("string"),
"goal": {"constraints": [[datasets.Value("string")]], "request-slots": [datasets.Value("string")], "text": datasets.Value("string")},
"dial": [
{
"turn": datasets.Value("int32"),
"usr": {
"transcript": datasets.Value("string"),
"delex_transcript": datasets.Value("string"),
"slu": [{"act": datasets.Value("string"), "slots": [[datasets.Value("string")]]}],
},
"sys": {"sent": datasets.Value("string"), "delex_sent": datasets.Value("string"), "DA": [datasets.Value("string")]},
}
],
}
)
elif self.config.schema == "seacrowd_tod":
features = schemas.tod_features
else:
raise NotImplementedError(f"Schema {self.config.schema} has not been implemented")
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
urls = _URLS[_DATASETNAME]
data_dir = dl_manager.download_and_extract(urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": data_dir,
"split": "train",
},
),
]
def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
with open(filepath, "r+") as fw:
data = json.loads(fw.read())
if self.config.schema == "source":
for idx, example in enumerate(data):
example["index"] = str(idx)
yield str(idx), example
elif self.config.schema == "seacrowd_tod":
for idx, tod_dialogue in enumerate(data):
example = {}
example["dialogue_idx"] = idx
dialogue = []
for i in range(len(tod_dialogue["dial"]) + 1):
dial = {}
dial["turn_idx"] = i
# system_utterance properties
if i == 0:
# case if turn_idx == 0
dial["system_utterance"] = ""
dial["system_acts"] = []
else:
dial["system_utterance"] = tod_dialogue["dial"][i - 1]["sys"]["sent"]
# some system_acts is either to string or list of strings,
# converting all to list of strings
dial["system_acts"] = [[act] if isinstance(act, str) else act for act in tod_dialogue["dial"][i - 1]["sys"]["DA"]]
# user_utterance properties
dial["turn_label"] = []
dial["belief_state"] = []
if i == len(tod_dialogue["dial"]):
# case if turn_idx > len(dialogue) --> add dummy user_utterance
dial["user_utterance"] = ""
else:
dial["user_utterance"] = tod_dialogue["dial"][i]["usr"]["transcript"]
for j in range(len(tod_dialogue["dial"][i]["usr"]["slu"])):
dial["belief_state"].append({"slots": tod_dialogue["dial"][i]["usr"]["slu"][j]["slots"], "act": tod_dialogue["dial"][i]["usr"]["slu"][j]["act"]})
# append to dialogue
dialogue.append(dial)
example["dialogue"] = dialogue
yield str(idx), example
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