[Feature] Make NeedleBench available on HF (#1364)

* update_lint

* update_huggingface format

* fix bug

* update docs

docs/en/advanced_guides/needleinahaystack_eval.md

@@ -18,6 +18,8 @@ Within the `NeedleBench` framework of `OpenCompass`, we have designed a series o
 
 ### Evaluation Steps
 
+> Note: In the latest code, OpenCompass has been set to automatically load the dataset from [Huggingface API](https://huggingface.co/datasets/opencompass/NeedleBench), so you can **skip directly** the following steps of manually downloading and placing the dataset.
+
 1. Download the dataset from [here](https://github.com/open-compass/opencompass/files/14741330/needlebench.zip).
 
 2. Place the downloaded files in the `opencompass/data/needlebench/` directory. The expected file structure in the `needlebench` directory is shown below:

docs/zh_cn/advanced_guides/needleinahaystack_eval.md

@@ -18,6 +18,8 @@
 
 ### 评估步骤
 
+> 注意：在最新代码中，OpenCompass已经设置数据集从[Huggingface的接口](https://huggingface.co/datasets/opencompass/NeedleBench)中自动加载，可以直接跳过下面的手动下载安放数据集。
+
 1. 从[这里](https://github.com/open-compass/opencompass/files/14741330/needlebench.zip)下载数据集。
 
 2. 将下载的文件放置于`opencompass/data/needlebench/`目录下。`needlebench`目录中预期的文件结构如下所示：

opencompass/datasets/needlebench/multi.py

@@ -1,10 +1,10 @@
 import json
 import os
 import random
-from pathlib import Path
 
 import tiktoken
 from datasets import Dataset
+from huggingface_hub import hf_hub_download
 
 from opencompass.datasets.base import BaseDataset
 from opencompass.openicl import BaseEvaluator
@@ -37,7 +37,7 @@ class NeedleBenchMultiDataset(BaseDataset):
 
     @staticmethod
     def load(
-        path: str,
+        path: str,  # depreciated
         length: int,
         depth: int,
         tokenizer_model: str,
@@ -152,13 +152,28 @@ def _generate_prompt(context, retrieval_question):
 
             return prompt
 
-        files = Path(path).glob('*.jsonl')
-        needle_file_path = os.path.join(path, needle_file_name)
-        for file in files:
-            if file.name not in file_list:
+        repo_id = 'opencompass/NeedleBench'
+        file_names = [
+            'PaulGrahamEssays.jsonl', 'multi_needle_reasoning_en.json',
+            'multi_needle_reasoning_zh.json', 'zh_finance.jsonl',
+            'zh_game.jsonl', 'zh_general.jsonl', 'zh_government.jsonl',
+            'zh_movie.jsonl', 'zh_tech.jsonl'
+        ]
+        downloaded_files = []
+        base_file_path = ''
+        for file_name in file_names:
+            file_path = hf_hub_download(repo_id=repo_id,
+                                        filename=file_name,
+                                        repo_type='dataset')
+            downloaded_files.append(file_path)
+            base_file_path = '/'.join(file_path.split('/')[:-1])
+
+        needle_file_path = os.path.join(base_file_path, needle_file_name)
+        for file_path in downloaded_files:
+            if file_path.split('/')[-1] not in file_list:
                 continue
 
-            with open(file, 'r', encoding='utf-8') as f:
+            with open(file_path, 'r', encoding='utf-8') as f:
                 lines_bak = [json.loads(line.strip()) for line in f]
             lines = lines_bak.copy()
             for counter in range(num_repeats_per_file):

opencompass/datasets/needlebench/origin.py

@@ -2,10 +2,10 @@
 import os
 import random
 import re
-from pathlib import Path
 
 import tiktoken
 from datasets import Dataset
+from huggingface_hub import hf_hub_download
 
 from opencompass.datasets.base import BaseDataset
 from opencompass.openicl import BaseEvaluator
@@ -36,7 +36,7 @@ class NeedleBenchOriginDataset(BaseDataset):
 
     @staticmethod
     def load(
-        path: str,
+        path: str,  # depreciated
         length: int,
         depth: int,
         tokenizer_model: str,
@@ -128,18 +128,33 @@ def _generate_prompt(context, retrieval_question):
 
             return prompt
 
-        files = Path(path).glob('*.jsonl')
-        for file in files:
-            if file.name not in file_list:
-                continue
+        repo_id = 'opencompass/NeedleBench'
+        file_names = [
+            'PaulGrahamEssays.jsonl', 'needles.jsonl', 'zh_finance.jsonl',
+            'zh_game.jsonl', 'zh_general.jsonl', 'zh_government.jsonl',
+            'zh_movie.jsonl', 'zh_tech.jsonl'
+        ]
 
-            with open(file, 'r', encoding='utf-8') as f:
+        downloaded_files = []
+        base_file_path = ''
+        for file_name in file_names:
+            file_path = hf_hub_download(repo_id=repo_id,
+                                        filename=file_name,
+                                        repo_type='dataset')
+            downloaded_files.append(file_path)
+            base_file_path = '/'.join(file_path.split('/')[:-1])
+
+        for file_path in downloaded_files:
+            if file_path.split('/')[-1] not in file_list:
+                continue
+            with open(file_path, 'r', encoding='utf-8') as f:
                 lines_bak = [json.loads(line.strip()) for line in f]
             lines = lines_bak.copy()
             for counter in range(num_repeats_per_file):
                 random.seed(counter)
                 random.shuffle(lines)
-                needle_file_path = os.path.join(path, needle_file_name)
+                needle_file_path = os.path.join(base_file_path,
+                                                needle_file_name)
                 random_needle = get_random_line_by_language(
                     counter, needle_file_path, language)
                 needle = '\n' + random_needle['needle'] + '\n'

opencompass/datasets/needlebench/parallel.py

@@ -1,9 +1,9 @@
 import json
 import random
-from pathlib import Path
 
 import tiktoken
 from datasets import Dataset
+from huggingface_hub import hf_hub_download
 
 from opencompass.datasets.base import BaseDataset
 from opencompass.openicl import BaseEvaluator
@@ -57,7 +57,7 @@ class NeedleBenchParallelDataset(BaseDataset):
 
     @staticmethod
     def load(
-        path: str,
+        path: str,  # depreciated
         needle_file_name: str,
         length: int,
         depths: list[int],
@@ -72,9 +72,22 @@ def load(
         data = {'prompt': [], 'answer': []}
         tokenizer = tiktoken.encoding_for_model(tokenizer_model)
 
-        files = Path(path).glob('*.jsonl')
-        for file in files:
-            if file.name == needle_file_name:
+        repo_id = 'opencompass/NeedleBench'
+        file_names = [
+            'PaulGrahamEssays.jsonl', 'needles.jsonl', 'zh_finance.jsonl',
+            'zh_game.jsonl', 'zh_general.jsonl', 'zh_government.jsonl',
+            'zh_movie.jsonl', 'zh_tech.jsonl'
+        ]
+
+        downloaded_files = []
+        for file_name in file_names:
+            file_path = hf_hub_download(repo_id=repo_id,
+                                        filename=file_name,
+                                        repo_type='dataset')
+            downloaded_files.append(file_path)
+
+        for file in downloaded_files:
+            if file.split('/')[-1] == needle_file_name:
                 needle_file_path = file
 
         predefined_needles_bak = get_unique_entries(needle_file_path,
@@ -178,12 +191,11 @@ def _generate_prompt(context, retrieval_question):
 
             return prompt
 
-        files = Path(path).glob('*.jsonl')
-        for file in files:
-            if file.name not in file_list:
+        for file_path in downloaded_files:
+            if file_path.split('/')[-1] not in file_list:
                 continue
 
-            with open(file, 'r', encoding='utf-8') as f:
+            with open(file_path, 'r', encoding='utf-8') as f:
                 lines_bak = [json.loads(line.strip()) for line in f]
             lines = lines_bak.copy()
             for counter in range(num_repeats_per_file):