Initial commit

Former-commit-id: 5ca8e1d63727e7bcb8cab16542c763c47e48184a

data/ultra_chat/ultra_chat.py

@@ -0,0 +1,76 @@
+import json
+import datasets
+from typing import Any, Dict, List
+
+
+_DESCRIPTION = "UltraChat: Large-scale, Informative, and Diverse Multi-round Dialogue Data."
+
+_CITATION = """\
+@misc{UltraChat,
+  author = {Ding, Ning and Chen, Yulin and Xu, Bokai and Hu, Shengding and Qin, Yujia and Liu, Zhiyuan and Sun, Maosong and Zhou, Bowen},
+  title = {UltraChat: A Large-scale Auto-generated Multi-round Dialogue Data},
+  year = {2023},
+  publisher = {GitHub},
+  journal = {GitHub repository},
+  howpublished = {\\url{https://github.com/thunlp/ultrachat}},
+}
+"""
+
+_HOMEPAGE = "https://huggingface.co/datasets/stingning/ultrachat"
+_LICENSE = "cc-by-nc-4.0"
+_BASE_DATA_URL = "https://huggingface.co/datasets/stingning/ultrachat/resolve/main/train_{idx}.jsonl"
+
+
+class BelleMultiturn(datasets.GeneratorBasedBuilder):
+
+    VERSION = datasets.Version("0.0.0")
+
+    def _info(self) -> datasets.DatasetInfo:
+        features = datasets.Features({
+            "instruction": datasets.Value("string"),
+            "output": datasets.Value("string"),
+            "history": datasets.Sequence(datasets.Sequence(datasets.Value("string")))
+        })
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        file_paths = [dl_manager.download(_BASE_DATA_URL.format(idx=idx)) for idx in range(9)] # multiple shards
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepaths": file_paths
+                }
+            )
+        ]
+
+    def _generate_examples(self, filepaths: List[str]) -> Dict[int, Dict[str, Any]]: # generate multi-turn chat for ChatGLM
+        for filepath in filepaths:
+            with open(filepath, "r", encoding="utf-8") as f:
+                for row in f:
+                    try:
+                        data = json.loads(row)
+                    except:
+                        continue
+                    key = data["id"]
+                    content = data["data"]
+                    if len(content) % 2 == 1:
+                        content.pop(-1)
+                    if len(content) < 2:
+                        continue
+
+                    query = content[-2]
+                    response = content[-1]
+                    history = [[content[2*i], content[2*i+1]] for i in range(len(content) // 2 - 1)]
+
+                    yield key, {
+                        "instruction": query,
+                        "output": response,
+                        "history": history
+                    }