Docs: Update docstrings lg (#6260)

* Update docstrings lg

* Update test_in_memory_bm25_retriever.py

* Update test_in_memory_embedding_retriever.py

---------

Co-authored-by: Massimiliano Pippi <mpippi@gmail.com>

haystack/preview/components/retrievers/in_memory_bm25_retriever.py

@@ -7,9 +7,9 @@
 @component
 class InMemoryBM25Retriever:
     """
-    A component for retrieving documents from a InMemoryDocumentStore using the BM25 algorithm.
+    Uses the BM25 algorithm to retrieve documents from the InMemoryDocumentStore.
 
-    Needs to be connected to a InMemoryDocumentStore to run.
+    Needs to be connected to the InMemoryDocumentStore to run.
     """
 
     def __init__(
@@ -20,22 +20,23 @@ def __init__(
         scale_score: bool = True,
     ):
         """
-        Create a InMemoryBM25Retriever component.
+        Create the InMemoryBM25Retriever component.
 
         :param document_store: An instance of InMemoryDocumentStore.
-        :param filters: A dictionary with filters to narrow down the search space. Default is None.
-        :param top_k: The maximum number of documents to retrieve. Default is 10.
-        :param scale_score: Whether to scale the BM25 score or not. Default is True.
+        :param filters: A dictionary with filters to narrow down the search space. Defaults to `None`.
+        :param top_k: The maximum number of documents to retrieve. Defaults to `10`.
+        :param scale_score: Scales the BM25 score to a unit interval in the range of 0 to 1, where 1 means extremely relevant. If set to `False`, uses raw similarity scores.
+        Defaults to `True`.
 
-        :raises ValueError: If the specified top_k is not > 0.
+        :raises ValueError: If the specified `top_k` is not > 0.
         """
         if not isinstance(document_store, InMemoryDocumentStore):
             raise ValueError("document_store must be an instance of InMemoryDocumentStore")
 
         self.document_store = document_store
 
         if top_k <= 0:
-            raise ValueError(f"top_k must be > 0, but got {top_k}")
+            raise ValueError(f"top_k must be greater than 0. Currently, the top_k is {top_k}")
 
         self.filters = filters
         self.top_k = top_k
@@ -85,10 +86,11 @@ def run(
         """
         Run the InMemoryBM25Retriever on the given input data.
 
-        :param query: The query string for the retriever.
+        :param query: The query string for the Retriever.
         :param filters: A dictionary with filters to narrow down the search space.
         :param top_k: The maximum number of documents to return.
-        :param scale_score: Whether to scale the BM25 scores or not.
+        :param scale_score: Scales the BM25 score to a unit interval in the range of 0 to 1, where 1 means extremely relevant. If set to `False`, uses raw similarity scores.
+        Defaults to `True`.
         :return: The retrieved documents.
 
         :raises ValueError: If the specified DocumentStore is not found or is not a InMemoryDocumentStore instance.

haystack/preview/components/retrievers/in_memory_embedding_retriever.py

@@ -7,9 +7,9 @@
 @component
 class InMemoryEmbeddingRetriever:
     """
-    A component for retrieving documents from a InMemoryDocumentStore using a vector similarity metric.
+    Uses a vector similarity metric to retrieve documents from the InMemoryDocumentStore.
 
-    Needs to be connected to a InMemoryDocumentStore to run.
+    Needs to be connected to the InMemoryDocumentStore to run.
     """
 
     def __init__(
@@ -21,13 +21,14 @@ def __init__(
         return_embedding: bool = False,
     ):
         """
-        Create a InMemoryEmbeddingRetriever component.
+        Create the InMemoryEmbeddingRetriever component.
 
         :param document_store: An instance of InMemoryDocumentStore.
-        :param filters: A dictionary with filters to narrow down the search space. Default is None.
-        :param top_k: The maximum number of documents to retrieve. Default is 10.
-        :param scale_score: Whether to scale the scores of the retrieved documents or not. Default is True.
-        :param return_embedding: Whether to return the embedding of the retrieved Documents. Default is False.
+        :param filters: A dictionary with filters to narrow down the search space. Defaults to `None`.
+        :param top_k: The maximum number of documents to retrieve. Defaults to `10`.
+        :param scale_score: Scales the BM25 score to a unit interval in the range of 0 to 1, where 1 means extremely relevant. If set to `False`, uses raw similarity scores.
+        Defaults to `True`.
+        :param return_embedding: Whether to return the embedding of the retrieved Documents. Default is `False`.
 
         :raises ValueError: If the specified top_k is not > 0.
         """
@@ -37,7 +38,7 @@ def __init__(
         self.document_store = document_store
 
         if top_k <= 0:
-            raise ValueError(f"top_k must be > 0, but got {top_k}")
+            raise ValueError(f"top_k must be greater than 0. Currently, top_k is {top_k}")
 
         self.filters = filters
         self.top_k = top_k
@@ -97,11 +98,12 @@ def run(
         :param query_embedding: Embedding of the query.
         :param filters: A dictionary with filters to narrow down the search space.
         :param top_k: The maximum number of documents to return.
-        :param scale_score: Whether to scale the scores of the retrieved documents or not.
+        :param scale_score: Scales the BM25 score to a unit interval in the range of 0 to 1, where 1 means extremely relevant. If set to `False`, uses raw similarity scores.
+        Defaults to `True`.
         :param return_embedding: Whether to return the embedding of the retrieved Documents.
         :return: The retrieved documents.
 
-        :raises ValueError: If the specified DocumentStore is not found or is not a InMemoryDocumentStore instance.
+        :raises ValueError: If the specified DocumentStore is not found or is not an InMemoryDocumentStore instance.
         """
         if filters is None:
             filters = self.filters

test/preview/components/retrievers/test_in_memory_bm25_retriever.py

@@ -39,7 +39,7 @@ def test_init_with_parameters(self):
 
     @pytest.mark.unit
     def test_init_with_invalid_top_k_parameter(self):
-        with pytest.raises(ValueError, match="top_k must be > 0, but got -2"):
+        with pytest.raises(ValueError):
             InMemoryBM25Retriever(InMemoryDocumentStore(), top_k=-2, scale_score=False)
 
     @pytest.mark.unit

test/preview/components/retrievers/test_in_memory_embedding_retriever.py

@@ -29,7 +29,7 @@ def test_init_with_parameters(self):
 
     @pytest.mark.unit
     def test_init_with_invalid_top_k_parameter(self):
-        with pytest.raises(ValueError, match="top_k must be > 0, but got -2"):
+        with pytest.raises(ValueError):
             InMemoryEmbeddingRetriever(InMemoryDocumentStore(), top_k=-2, scale_score=False)
 
     @pytest.mark.unit