diff --git a/src/RAG_pipeline.py b/src/RAG_pipeline.py
new file mode 100644
index 0000000..5bee608
--- /dev/null
+++ b/src/RAG_pipeline.py
@@ -0,0 +1,49 @@
+from typing import List, Optional, Dict
+from dataclasses import dataclass
+from .interface.base_datastore import BaseDatastore
+from .interface.base_evaluator import BaseEvaluator
+from .interface.base_indexer import BaseIndexer
+from .interface.base_response_generator import BaseResponseGenerator
+from .interface.base_retriever import BaseRetriever
+
+@dataclass
+class RAGpipeline:
+    
+    indexer: BaseIndexer
+    datastore: BaseDatastore
+    retriever: BaseRetriever
+    response_generator: BaseResponseGenerator
+    evaluator: Optional[BaseEvaluator] = None
+    
+    def reset(self) -> None:
+        self.datastore.reset_table()
+    
+    def add_documents(self, documents: List[str]) -> None:
+        items = self.indexer.index(documents)
+        self.datastore.add_items(items= items)
+        return
+    
+    def process_query(self, query: str, top_k: int = 5, source: bool = False) -> str:
+        """Génère la réponse à la requête à partir du contexte récupéré.
+        Affiche éventuellement les sources.
+        Args:
+            query (str): Requête
+            top_k (int, optional): Nombre de documents à renvoyer. Defaults to 5.
+            source (bool, optional): Afficher ou non les sources. Default to false
+        Returns:
+            str: Réponse générée
+        """
+        context = self.retriever.search_retriever(query, top_k= top_k)
+        
+        if( source):
+            for i, doc in enumerate(context):
+                print(f"Based on the document {i+1}: {doc} \n")
+        
+        response = self.response_generator.generate_response(query= query, context= context)
+        return response
+    
+    def evaluate(self) -> None:
+        """A compléter lors de l'ajout de l'évaluateur
+        """
+        print("Function not completed.")
+        pass
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