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# Copyright 2025 the LlamaFactory team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
import os
from dataclasses import dataclass
from typing import Any, Literal, Optional
from huggingface_hub import hf_hub_download
from ..extras.constants import DATA_CONFIG
from ..extras.misc import use_modelscope, use_openmind
@dataclass
class DatasetAttr:
r"""Dataset attributes."""
# basic configs
load_from: Literal["hf_hub", "ms_hub", "om_hub", "script", "file"]
dataset_name: str
formatting: Literal["alpaca", "sharegpt"] = "alpaca"
ranking: bool = False
# extra configs
subset: Optional[str] = None
split: str = "train"
folder: Optional[str] = None
num_samples: Optional[int] = None
# common columns
system: Optional[str] = None
tools: Optional[str] = None
images: Optional[str] = None
videos: Optional[str] = None
audios: Optional[str] = None
# dpo columns
chosen: Optional[str] = None
rejected: Optional[str] = None
kto_tag: Optional[str] = None
# alpaca columns
prompt: Optional[str] = "instruction"
query: Optional[str] = "input"
response: Optional[str] = "output"
history: Optional[str] = None
# sharegpt columns
messages: Optional[str] = "conversations"
# sharegpt tags
role_tag: Optional[str] = "from"
content_tag: Optional[str] = "value"
user_tag: Optional[str] = "human"
assistant_tag: Optional[str] = "gpt"
observation_tag: Optional[str] = "observation"
function_tag: Optional[str] = "function_call"
system_tag: Optional[str] = "system"
def __repr__(self) -> str:
return self.dataset_name
def set_attr(self, key: str, obj: dict[str, Any], default: Optional[Any] = None) -> None:
setattr(self, key, obj.get(key, default))
def join(self, attr: dict[str, Any]) -> None:
self.set_attr("formatting", attr, default="alpaca")
self.set_attr("ranking", attr, default=False)
self.set_attr("subset", attr)
self.set_attr("split", attr, default="train")
self.set_attr("folder", attr)
self.set_attr("num_samples", attr)
if "columns" in attr:
column_names = ["prompt", "query", "response", "history", "messages", "system", "tools"]
column_names += ["images", "videos", "audios", "chosen", "rejected", "kto_tag"]
for column_name in column_names:
self.set_attr(column_name, attr["columns"])
if "tags" in attr:
tag_names = ["role_tag", "content_tag"]
tag_names += ["user_tag", "assistant_tag", "observation_tag", "function_tag", "system_tag"]
for tag in tag_names:
self.set_attr(tag, attr["tags"])
def get_dataset_list(dataset_names: Optional[list[str]], dataset_dir: str) -> list["DatasetAttr"]:
r"""Get the attributes of the datasets."""
if dataset_names is None:
dataset_names = []
if dataset_dir == "ONLINE":
dataset_info = None
else:
if dataset_dir.startswith("REMOTE:"):
config_path = hf_hub_download(repo_id=dataset_dir[7:], filename=DATA_CONFIG, repo_type="dataset")
else:
config_path = os.path.join(dataset_dir, DATA_CONFIG)
try:
with open(config_path) as f:
dataset_info = json.load(f)
except Exception as err:
if len(dataset_names) != 0:
raise ValueError(f"Cannot open {config_path} due to {str(err)}.")
dataset_info = None
dataset_list: list[DatasetAttr] = []
for name in dataset_names:
if dataset_info is None: # dataset_dir is ONLINE
if use_modelscope():
load_from = "ms_hub"
elif use_openmind():
load_from = "om_hub"
else:
load_from = "hf_hub"
dataset_attr = DatasetAttr(load_from, dataset_name=name)
dataset_list.append(dataset_attr)
continue
if name not in dataset_info:
raise ValueError(f"Undefined dataset {name} in {DATA_CONFIG}.")
has_hf_url = "hf_hub_url" in dataset_info[name]
has_ms_url = "ms_hub_url" in dataset_info[name]
has_om_url = "om_hub_url" in dataset_info[name]
if has_hf_url or has_ms_url or has_om_url:
if has_ms_url and (use_modelscope() or not has_hf_url):
dataset_attr = DatasetAttr("ms_hub", dataset_name=dataset_info[name]["ms_hub_url"])
elif has_om_url and (use_openmind() or not has_hf_url):
dataset_attr = DatasetAttr("om_hub", dataset_name=dataset_info[name]["om_hub_url"])
else:
dataset_attr = DatasetAttr("hf_hub", dataset_name=dataset_info[name]["hf_hub_url"])
elif "script_url" in dataset_info[name]:
dataset_attr = DatasetAttr("script", dataset_name=dataset_info[name]["script_url"])
elif "cloud_file_name" in dataset_info[name]:
dataset_attr = DatasetAttr("cloud_file", dataset_name=dataset_info[name]["cloud_file_name"])
else:
dataset_attr = DatasetAttr("file", dataset_name=dataset_info[name]["file_name"])
dataset_attr.join(dataset_info[name])
dataset_list.append(dataset_attr)
return dataset_list
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