add setup file

data_setup.py

@@ -0,0 +1,87 @@
+import os
+import csv
+import datasets
+
+class DatasetConfig(datasets.BuilderConfig):
+    """BuilderConfig for MyCustomDataset."""
+    def __init__(self, name: str, subset_dir: str, **kwargs):
+        """
+        Args:
+            name: The name of the dataset configuration (e.g., '4k', '8k').
+                  This is crucial for datasets to identify the config.
+            subset_dir: The name of the subdirectory within 'data/' for this subset (e.g., "4k").
+            **kwargs: Keyword arguments passed to the base BuilderConfig (e.g., 'description').
+        """
+        super().__init__(name, **kwargs)
+        self.subset_dir = subset_dir
+
+
+# Main dataset builder class
+class MLNeedle(datasets.GeneratorBasedBuilder):
+  
+    VERSION = datasets.Version("1.0.0")
+    BUILDER_CONFIGS = [
+        DatasetConfig(name="baseline", subset_dir="baseline", description="Baseline subset data."),
+        DatasetConfig(name="4k", subset_dir="4k", description="Dataset subset with 4k context size."),
+        DatasetConfig(name="8k", subset_dir="8k", description="Dataset subset with 8k context size."),
+        DatasetConfig(name="16k", subset_dir="16k", description="Dataset subset with 16k context size."),
+        DatasetConfig(name="32k", subset_dir="32k", description="Dataset subset with 32k context size."),
+    ]
+
+    DEFAULT_CONFIG_NAME = "baseline"
+
+    _BUILDER_CONFIGS_GROUPED_BY_DATASET_NAME = {
+        config.name: config for config in BUILDER_CONFIGS
+    }
+
+    def _info(self):
+        """Defines the dataset schema and metadata."""
+        return datasets.DatasetInfo(
+            description="""
+            Multilingual Needle in a Haystack dataset for evaluating large language models
+            on their ability to retrieve specific information from long contexts across multiple languages.
+            Each subset (e.g., 4k, 8k) corresponds to different context lengths, and each split
+            (e.g., en, es) represents a language.
+            """,
+            features=datasets.Features({
+                "id": datasets.Value("string"),
+                "needle_lang": datasets.Value("string"),
+                "question_lang": datasets.Value("string"),
+                "distractor_lang": datasets.Value("string"),
+                "needle_position": datasets.Value("string"),
+                "answer_text_format": datasets.Value("string"),
+                "answer_start_index": datasets.Value("int32"),
+                "answer_sentence": datasets.Value("string"),
+                "prompt": datasets.Value("string"),
+            }),
+            supervised_keys=None,
+            homepage="https://huggingface.co/datasets/ameyhengle/Multilingual-Needle-in-a-Haystack",
+            license="MIT",
+        )
+
+    def _generate_examples(self, filepath):
+        """
+        Args:
+            filepath: The full path to the CSV file to be processed.
+        """
+        with open(filepath, encoding="utf-8") as f:
+            reader = csv.DictReader(f)
+            for i, row in enumerate(reader):
+                try:
+                    answer_start_index = int(row["answer_start_index"])
+                except (ValueError, TypeError):
+                    print(f"Warning: Could not convert 'answer_start_index' to int for row {i} in {filepath}. Defaulting to 0.")
+                    answer_start_index = 0
+
+                # Yield the example, mapping CSV columns to dataset features
+                yield i, {
+                    "id": row["id"],
+                    "needle_lang": row["needle_lang"],
+                    "question_lang": row["question_lang"],
+                    "distractor_lang": row["distractor_lang"],
+                    "needle_position": row["needle_position"],
+                    "answer_text_format": row["answer_text_format"],
+                    "answer_start_index": answer_start_index,
+                    "answer_sentence": row["answer_sentence"],
+                    "prompt": row["prompt"],
+                }