Jina - review docstrings

integrations/jina/src/haystack_integrations/components/embedders/jina/document_embedder.py

@@ -19,13 +19,15 @@ class JinaDocumentEmbedder:
 
     Usage example:
     ```python
+    import os
     from haystack import Document
-    from jina_haystack import JinaDocumentEmbedder
-
-    doc = Document(content="I love pizza!")
+    from haystack_integrations.components.embedders.jina import JinaDocumentEmbedder
 
+    os.environ("JINA_API_KEY") = "YOUR_JINA_API_KEY"
     document_embedder = JinaDocumentEmbedder()
 
+    doc = Document(content="I love pizza!")
+
     result = document_embedder.run([doc])
     print(result['documents'][0].embedding)
 
@@ -45,9 +47,9 @@ def __init__(
         embedding_separator: str = "\n",
     ):
         """
-        Create a JinaDocumentEmbedder component.
         :param api_key: The Jina API key.
-        :param model: The name of the Jina model to use. Check the list of available models on `https://jina.ai/embeddings/`
+        :param model: The name of the Jina model to use.
+            Check the list of available models on [Jina documentation](https://jina.ai/embeddings/).
         :param prefix: A string to add to the beginning of each text.
         :param suffix: A string to add to the end of each text.
         :param batch_size: Number of Documents to encode at once.
@@ -83,8 +85,9 @@ def _get_telemetry_data(self) -> Dict[str, Any]:
 
     def to_dict(self) -> Dict[str, Any]:
         """
-        This method overrides the default serializer in order to avoid leaking the `api_key` value passed
-        to the constructor.
+        Serializes the component to a dictionary.
+        :returns:
+            Dictionary with serialized data.
         """
         return default_to_dict(
             self,
@@ -100,6 +103,13 @@ def to_dict(self) -> Dict[str, Any]:
 
     @classmethod
     def from_dict(cls, data: Dict[str, Any]) -> "JinaDocumentEmbedder":
+        """
+        Deserializes the component from a dictionary.
+        :param data:
+            Dictionary to deserialize from.
+        :returns:
+            Deserialized component.
+        """
         deserialize_secrets_inplace(data["init_parameters"], keys=["api_key"])
         return default_from_dict(cls, data)
 
@@ -151,10 +161,13 @@ def _embed_batch(self, texts_to_embed: List[str], batch_size: int) -> Tuple[List
     @component.output_types(documents=List[Document], meta=Dict[str, Any])
     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.
+        Compute the embeddings for a list of Documents.
 
         :param documents: A list of Documents to embed.
+        :returns: A dictionary with following keys:
+            - `documents`: List of Documents, each with an `embedding` field containing the computed embedding.
+            - `meta`: A dictionary with metadata including the model name and usage statistics.
+        :raises TypeError: If the input is not a list of Documents.
         """
         if not isinstance(documents, list) or documents and not isinstance(documents[0], Document):
             msg = (

integrations/jina/src/haystack_integrations/components/embedders/jina/text_embedder.py

@@ -13,16 +13,19 @@
 @component
 class JinaTextEmbedder:
     """
-    A component for embedding strings using Jina models.
+    A component for embedding strings using Jina AI models.
 
     Usage example:
     ```python
-    from jina_haystack import JinaTextEmbedder
+    import os
+    from haystack_integrations.components.embedders.jina import JinaTextEmbedder
 
-    text_to_embed = "I love pizza!"
+    os.environ("JINA_API_KEY") = "YOUR_JINA_API_KEY"
 
     text_embedder = JinaTextEmbedder()
 
+    text_to_embed = "I love pizza!"
+
     print(text_embedder.run(text_to_embed))
 
     # {'embedding': [0.017020374536514282, -0.023255806416273117, ...],
@@ -39,11 +42,10 @@ def __init__(
         suffix: str = "",
     ):
         """
-        Create an JinaTextEmbedder component.
-
         :param api_key: The Jina API key. It can be explicitly provided or automatically read from the
-            environment variable JINA_API_KEY (recommended).
-        :param model: The name of the Jina model to use. Check the list of available models on `https://jina.ai/embeddings/`
+            environment variable `JINA_API_KEY` (recommended).
+        :param model: The name of the Jina model to use.
+            Check the list of available models on [Jina documentation](https://jina.ai/embeddings/).
         :param prefix: A string to add to the beginning of each text.
         :param suffix: A string to add to the end of each text.
         """
@@ -71,22 +73,37 @@ def _get_telemetry_data(self) -> Dict[str, Any]:
 
     def to_dict(self) -> Dict[str, Any]:
         """
-        This method overrides the default serializer in order to avoid leaking the `api_key` value passed
-        to the constructor.
+        Serializes the component to a dictionary.
+        :returns:
+            Dictionary with serialized data.
         """
-
         return default_to_dict(
             self, api_key=self.api_key.to_dict(), model=self.model_name, prefix=self.prefix, suffix=self.suffix
         )
 
     @classmethod
     def from_dict(cls, data: Dict[str, Any]) -> "JinaTextEmbedder":
+        """
+        Deserializes the component from a dictionary.
+        :param data:
+            Dictionary to deserialize from.
+        :returns:
+            Deserialized component.
+        """
         deserialize_secrets_inplace(data["init_parameters"], keys=["api_key"])
         return default_from_dict(cls, data)
 
     @component.output_types(embedding=List[float], meta=Dict[str, Any])
     def run(self, text: str):
-        """Embed a string."""
+        """
+        Embed a string.
+
+        :param text: The string to embed.
+        :returns: A dictionary with following keys:
+            - `embedding`: The embedding of the input string.
+            - `meta`: A dictionary with metadata including the model name and usage statistics.
+        :raises TypeError: If the input is not a string.
+        """
         if not isinstance(text, str):
             msg = (
                 "JinaTextEmbedder expects a string as an input."