Add dataset configuration script

multilingual_indic_rag.py

@@ -0,0 +1,87 @@
+# coding=utf-8
+import datasets
+
+class MultilingualIndicRagConfig(datasets.BuilderConfig):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+class MultilingualIndicRag(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+    
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(name="as", version=VERSION, description="Dataset for as"),
+        datasets.BuilderConfig(name="bn", version=VERSION, description="Dataset for bn"),
+        datasets.BuilderConfig(name="en", version=VERSION, description="Dataset for en"),
+        datasets.BuilderConfig(name="gu", version=VERSION, description="Dataset for gu"),
+        datasets.BuilderConfig(name="hi", version=VERSION, description="Dataset for hi"),
+        datasets.BuilderConfig(name="ks", version=VERSION, description="Dataset for ks"),
+        datasets.BuilderConfig(name="mai", version=VERSION, description="Dataset for mai"),
+        datasets.BuilderConfig(name="ml", version=VERSION, description="Dataset for ml"),
+        datasets.BuilderConfig(name="mni", version=VERSION, description="Dataset for mni"),
+        datasets.BuilderConfig(name="mr", version=VERSION, description="Dataset for mr"),
+        datasets.BuilderConfig(name="ne", version=VERSION, description="Dataset for ne"),
+        datasets.BuilderConfig(name="or", version=VERSION, description="Dataset for or"),
+        datasets.BuilderConfig(name="pa", version=VERSION, description="Dataset for pa"),
+        datasets.BuilderConfig(name="sat", version=VERSION, description="Dataset for sat"),
+        datasets.BuilderConfig(name="ta", version=VERSION, description="Dataset for ta"),
+        datasets.BuilderConfig(name="te", version=VERSION, description="Dataset for te"),
+    ]
+    
+    DEFAULT_CONFIG_NAME = "hi"  # Default to Hindi
+    
+    def _info(self):
+        features = datasets.Features({
+            "question": datasets.Value("string"),
+            "answer": datasets.Value("string"),
+            "reasoning": datasets.Value("string"),
+            "paragraph": datasets.Value("string"),
+            "title": datasets.Value("string"),
+            "wiki_id": datasets.Value("string"),
+            "url": datasets.Value("string"),
+            "language": datasets.Value("string"),
+            "source_lang": datasets.Value("string"),
+            "model_name": datasets.Value("string"),
+            "temperature": datasets.Value("string"),
+            "max_tokens": datasets.Value("string"),
+            "text": datasets.Value("string"),
+        })
+        
+        return datasets.DatasetInfo(
+            description="Multilingual Indic RAG Suite",
+            features=features,
+            supervised_keys=None,
+        )
+    
+    def _split_generators(self, dl_manager):
+        # Use the language-specific parquet file
+        lang_code = self.config.name
+        data_file = dl_manager.download(f"data/{lang_code}_data.parquet")
+        
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": data_file}
+            )
+        ]
+    
+    def _generate_examples(self, filepath):
+        import pandas as pd
+        
+        df = pd.read_parquet(filepath)
+        
+        for idx, row in df.iterrows():
+            yield idx, {
+                "question": row["question"],
+                "answer": row["answer"],
+                "reasoning": row["reasoning"],
+                "paragraph": row["paragraph"],
+                "title": row["title"],
+                "wiki_id": row["wiki_id"],
+                "url": row["url"],
+                "language": row["language"],
+                "source_lang": row["source_lang"],
+                "model_name": row["model_name"],
+                "temperature": row["temperature"],
+                "max_tokens": row["max_tokens"],
+                "text": row["text"],
+            }