docs:Review and normalize docstrings - integrations.fastembed (#519)

* Review and normalize docstrings

* Fix linting errors

integrations/fastembed/src/haystack_integrations/components/embedders/fastembed/fastembed_document_embedder.py

@@ -8,7 +8,7 @@
 @component
 class FastembedDocumentEmbedder:
     """
-    A component for computing Document embeddings using Fastembed embedding models.
+    FastembedDocumentEmbedder computes Document embeddings using Fastembed embedding models.
     The embedding of each Document is stored in the `embedding` field of the Document.
 
     Usage example:
@@ -48,6 +48,7 @@ class FastembedDocumentEmbedder:
     print(f"Document Text: {result['documents'][0].content}")
     print(f"Document Embedding: {result['documents'][0].embedding}")
     print(f"Embedding Dimension: {len(result['documents'][0].embedding)}")
+    ```
     """  # noqa: E501
 
     def __init__(
@@ -97,7 +98,9 @@ def __init__(
 
     def to_dict(self) -> Dict[str, Any]:
         """
-        Serialize this component to a dictionary.
+        Serializes the component to a dictionary.
+        :returns:
+            Dictionary with serialized data.
         """
         return default_to_dict(
             self,
@@ -115,7 +118,7 @@ def to_dict(self) -> Dict[str, Any]:
 
     def warm_up(self):
         """
-        Load the embedding backend.
+        Initializes the component.
         """
         if not hasattr(self, "embedding_backend"):
             self.embedding_backend = _FastembedEmbeddingBackendFactory.get_embedding_backend(
@@ -138,8 +141,11 @@ def _prepare_texts_to_embed(self, documents: List[Document]) -> List[str]:
     @component.output_types(documents=List[Document])
     def run(self, documents: List[Document]):
         """
-        Embed a list of Documents.
-        The embedding of each Document is stored in the `embedding` field of the Document.
+        Embeds a list of Documents.
+
+        :param documents: List of Documents to embed.
+        :return: A dictionary with the following keys:
+            - `documents`: List of Documents with each Document's `embedding` field set to the computed embeddings.
         """
         if not isinstance(documents, list) or documents and not isinstance(documents[0], Document):
             msg = (

integrations/fastembed/src/haystack_integrations/components/embedders/fastembed/fastembed_text_embedder.py

@@ -8,7 +8,7 @@
 @component
 class FastembedTextEmbedder:
     """
-    A component for embedding strings using fastembed embedding models.
+    FastembedTextEmbedder computes string embedding using fastembed embedding models.
 
     Usage example:
     ```python
@@ -69,7 +69,10 @@ def __init__(
 
     def to_dict(self) -> Dict[str, Any]:
         """
-        Serialize this component to a dictionary.
+        Serializes the component to a dictionary.
+
+        :returns:
+            Dictionary with serialized data.
         """
         return default_to_dict(
             self,
@@ -85,7 +88,7 @@ def to_dict(self) -> Dict[str, Any]:
 
     def warm_up(self):
         """
-        Load the embedding backend.
+        Initializes the component.
         """
         if not hasattr(self, "embedding_backend"):
             self.embedding_backend = _FastembedEmbeddingBackendFactory.get_embedding_backend(
@@ -94,7 +97,15 @@ def warm_up(self):
 
     @component.output_types(embedding=List[float])
     def run(self, text: str):
-        """Embed a string."""
+        """
+        Embeds text using the Fastembed model.
+
+        :param text: A string to embed.
+        :return: A dictionary with the following keys:
+            - `embedding`: A list of floats representing the embedding of the input text.
+        :raises TypeError: If the input is not a string.
+        :raises RuntimeError: If the embedding model has not been loaded.
+        """
         if not isinstance(text, str):
             msg = (
                 "FastembedTextEmbedder expects a string as input. "