Aligning to micpst's comments.

packages/ragbits-cli/src/ragbits/cli/__init__.py

@@ -9,7 +9,8 @@
 
 
 def main() -> None:
-    """Main entry point for the CLI.
+    """
+    Main entry point for the CLI.
 
     This function registers all the CLI modules in the ragbits packages:
         - iterates over every package in the ragbits.* namespace

packages/ragbits-core/examples/llm_example.py

@@ -13,21 +13,27 @@
 
 
 class LoremPromptInput(BaseModel):
-    """Input format for the LoremPrompt."""
+    """
+    Input format for the LoremPrompt.
+    """
 
     theme: str
     pun_allowed: bool = False
 
 
 class LoremPromptOutput(BaseModel):
-    """Output format for the LoremPrompt."""
+    """
+    Output format for the LoremPrompt.
+    """
 
     joke: str
     joke_category: str
 
 
 class JokePrompt(Prompt[LoremPromptInput, LoremPromptOutput]):
-    """A prompt that generates jokes."""
+    """
+    A prompt that generates jokes.
+    """
 
     system_prompt = """
     You are a joke generator. The jokes you generate should be funny and not offensive.

packages/ragbits-core/src/ragbits/core/cli.py

@@ -7,7 +7,8 @@
 
 
 def register(app: typer.Typer) -> None:
-    """Register the CLI commands for the package.
+    """
+    Register the CLI commands for the package.
 
     Args:
         app: The Typer object to register the commands with.

packages/ragbits-core/src/ragbits/core/embeddings/base.py

@@ -8,7 +8,8 @@ class Embeddings(ABC):
 
     @abstractmethod
     async def embed_text(self, data: list[str]) -> list[list[float]]:
-        """Creates embeddings for the given strings.
+        """
+        Creates embeddings for the given strings.
 
         Args:
             data: List of strings to get embeddings for.

packages/ragbits-core/src/ragbits/core/llms/clients/litellm.py

@@ -19,7 +19,8 @@
 
 @dataclass
 class LiteLLMOptions(LLMOptions):
-    """Dataclass that represents all available LLM call options for the LiteLLM client.
+    """
+    Dataclass that represents all available LLM call options for the LiteLLM client.
     Each of them is described in the [LiteLLM documentation](https://docs.litellm.ai/docs/completion/input).
     """
 
@@ -35,7 +36,8 @@ class LiteLLMOptions(LLMOptions):
 
 
 class LiteLLMClient(LLMClient[LiteLLMOptions]):
-    """Client for the LiteLLM that supports calls to 100+ LLMs APIs, including OpenAI, Anthropic, VertexAI,
+    """
+    Client for the LiteLLM that supports calls to 100+ LLMs APIs, including OpenAI, Anthropic, VertexAI,
     Hugging Face and others.
     """
 
@@ -50,7 +52,8 @@ def __init__(
         api_version: str | None = None,
         use_structured_output: bool = False,
     ) -> None:
-        """Constructs a new LiteLLMClient instance.
+        """
+        Constructs a new LiteLLMClient instance.
 
         Args:
             model_name: Name of the model to use.
@@ -78,7 +81,8 @@ async def call(
         json_mode: bool = False,
         output_schema: type[BaseModel] | dict | None = None,
     ) -> str:
-        """Calls the appropriate LLM endpoint with the given prompt and options.
+        """
+        Calls the appropriate LLM endpoint with the given prompt and options.
 
         Args:
             conversation: List of dicts with "role" and "content" keys, representing the chat history so far.

packages/ragbits-core/src/ragbits/core/llms/clients/local.py

@@ -48,7 +48,8 @@ def __init__(
         *,
         hf_api_key: str | None = None,
     ) -> None:
-        """Constructs a new local LLMClient instance.
+        """
+        Constructs a new local LLMClient instance.
 
         Args:
             model_name: Name of the model to use.
@@ -74,7 +75,8 @@ async def call(
         json_mode: bool = False,
         output_schema: type[BaseModel] | dict | None = None,
     ) -> str:
-        """Makes a call to the local LLM with the provided prompt and options.
+        """
+        Makes a call to the local LLM with the provided prompt and options.
 
         Args:
             conversation: List of dicts with "role" and "content" keys, representing the chat history so far.

packages/ragbits-core/src/ragbits/core/llms/litellm.py

@@ -30,7 +30,8 @@ def __init__(
         api_version: str | None = None,
         use_structured_output: bool = False,
     ) -> None:
-        """Constructs a new LiteLLM instance.
+        """
+        Constructs a new LiteLLM instance.
 
         Args:
             model_name: Name of the [LiteLLM supported model](https://docs.litellm.ai/docs/providers) to be used.\
@@ -71,7 +72,8 @@ def client(self) -> LiteLLMClient:
         )
 
     def count_tokens(self, prompt: BasePrompt) -> int:
-        """Counts tokens in the prompt.
+        """
+        Counts tokens in the prompt.
 
         Args:
             prompt: Formatted prompt template with conversation and response parsing configuration.

packages/ragbits-core/src/ragbits/core/llms/local.py

@@ -27,7 +27,8 @@ def __init__(
         *,
         api_key: str | None = None,
     ) -> None:
-        """Constructs a new local LLM instance.
+        """
+        Constructs a new local LLM instance.
 
         Args:
             model_name: Name of the model to use. This should be a model from the CausalLM class.
@@ -46,15 +47,17 @@ def __init__(
 
     @cached_property
     def client(self) -> LocalLLMClient:
-        """Client for the LLM.
+        """
+        Client for the LLM.
 
         Returns:
             The client used to interact with the LLM.
         """
         return LocalLLMClient(model_name=self.model_name, hf_api_key=self.api_key)
 
     def count_tokens(self, prompt: BasePrompt) -> int:
-        """Counts tokens in the messages.
+        """
+        Counts tokens in the messages.
 
         Args:
             prompt: Messages to count tokens for.

packages/ragbits-core/src/ragbits/core/llms/types.py

@@ -5,7 +5,8 @@
 
 # Sentinel class used until PEP 0661 is accepted
 class NotGiven:
-    """A sentinel singleton class used to distinguish omitted keyword arguments
+    """
+    A sentinel singleton class used to distinguish omitted keyword arguments
     from those passed in with the value None (which may have different behavior).
 
     For example:

packages/ragbits-core/src/ragbits/core/prompt/discovery/prompt_discovery.py

@@ -9,7 +9,8 @@
 
 
 class PromptDiscovery:
-    """Discovers Prompt objects within Python modules.
+    """
+    Discovers Prompt objects within Python modules.
 
     Args:
         file_pattern (str): The file pattern to search for Prompt objects. Defaults to "**/prompt_*.py"
@@ -22,7 +23,8 @@ def __init__(self, file_pattern: str = core_config.prompt_path_pattern, root_pat
 
     @staticmethod
     def is_prompt_subclass(obj: Any) -> bool:  # noqa: ANN401
-        """Checks if an object is a class that is a subclass of Prompt (but not Prompt itself).
+        """
+        Checks if an object is a class that is a subclass of Prompt (but not Prompt itself).
 
         Args:
             obj (any): The object to check.
@@ -35,7 +37,8 @@ def is_prompt_subclass(obj: Any) -> bool:  # noqa: ANN401
         return inspect.isclass(obj) and not get_origin(obj) and issubclass(obj, Prompt) and obj != Prompt
 
     def discover(self) -> set[type[Prompt]]:
-        """Discovers Prompt objects within the specified file paths.
+        """
+        Discovers Prompt objects within the specified file paths.
 
         Returns:
             set[Prompt]: The discovered Prompt objects.

packages/ragbits-core/src/ragbits/core/prompt/parsers.py

@@ -88,9 +88,7 @@ def bool_parser(value: str) -> bool:
     raise ResponseParsingError(f"Could not parse '{value}' as a boolean")
 
 
-def build_pydantic_parser(
-    model: type[PydanticModelT],
-) -> Callable[[str], PydanticModelT]:
+def build_pydantic_parser(model: type[PydanticModelT]) -> Callable[[str], PydanticModelT]:
     """
     Builds a parser for a specific Pydantic model.
 

packages/ragbits-core/src/ragbits/core/vector_store/in_memory.py

@@ -12,7 +12,8 @@ def __init__(self) -> None:
         self._storage: dict[str, VectorDBEntry] = {}
 
     async def store(self, entries: list[VectorDBEntry]) -> None:
-        """Store entries in the vector store.
+        """
+        Store entries in the vector store.
 
         Args:
             entries: The entries to store.
@@ -21,7 +22,8 @@ async def store(self, entries: list[VectorDBEntry]) -> None:
             self._storage[entry.key] = entry
 
     async def retrieve(self, vector: list[float], k: int = 5) -> list[VectorDBEntry]:
-        """Retrieve entries from the vector store.
+        """
+        Retrieve entries from the vector store.
 
         Args:
             vector: The vector to search for.

packages/ragbits-document-search/src/ragbits/document_search/documents/document.py

@@ -8,7 +8,9 @@
 
 
 class DocumentType(str, Enum):
-    """Types of documents that can be stored."""
+    """
+    Types of documents that can be stored.
+    """
 
     MD = "md"
     TXT = "txt"
@@ -50,7 +52,8 @@ def id(self) -> str:
         return self.source.get_id()
 
     async def fetch(self) -> "Document":
-        """This method fetches the document from source (potentially remote) and creates an object to interface with it.
+        """
+        This method fetches the document from source (potentially remote) and creates an object to interface with it.
         Based on the document type, it will return a different object.
 
         Returns:
@@ -61,7 +64,8 @@ async def fetch(self) -> "Document":
 
     @classmethod
     def create_text_document_from_literal(cls, content: str) -> "DocumentMeta":
-        """Create a text document from a literal content.
+        """
+        Create a text document from a literal content.
 
         Args:
             content: The content of the document.
@@ -79,7 +83,8 @@ def create_text_document_from_literal(cls, content: str) -> "DocumentMeta":
 
     @classmethod
     def from_local_path(cls, local_path: Path) -> "DocumentMeta":
-        """Create a document metadata from a local path.
+        """
+        Create a document metadata from a local path.
 
         Args:
             local_path: The local path to the document.
@@ -94,14 +99,17 @@ def from_local_path(cls, local_path: Path) -> "DocumentMeta":
 
 
 class Document(BaseModel):
-    """An object representing a document which is downloaded and stored locally."""
+    """
+    An object representing a document which is downloaded and stored locally.
+    """
 
     local_path: Path
     metadata: DocumentMeta
 
     @classmethod
     def from_document_meta(cls, document_meta: DocumentMeta, local_path: Path) -> "Document":
-        """Create a document from a document metadata.
+        """
+        Create a document from a document metadata.
         Based on the document type, it will return a different object.
 
         Args:
@@ -117,11 +125,14 @@ def from_document_meta(cls, document_meta: DocumentMeta, local_path: Path) -> "D
 
 
 class TextDocument(Document):
-    """An object representing a text document."""
+    """
+    An object representing a text document.
+    """
 
     @property
     def content(self) -> str:
-        """Get the content of the document.
+        """
+        Get the content of the document.
 
         Returns:
             The content of the document.

packages/ragbits-document-search/src/ragbits/document_search/documents/element.py

@@ -19,7 +19,8 @@ class Element(BaseModel, ABC):
 
     @abstractmethod
     def get_key(self) -> str:
-        """Get the key of the element which will be used to generate the vector.
+        """
+        Get the key of the element which will be used to generate the vector.
 
         Returns:
             The key.
@@ -36,7 +37,8 @@ def __pydantic_init_subclass__(cls, **kwargs: Any) -> None:  # pylint: disable=u
 
     @classmethod
     def from_vector_db_entry(cls, db_entry: VectorDBEntry) -> "Element":
-        """Create an element from a vector database entry.
+        """
+        Create an element from a vector database entry.
 
         Args:
             db_entry: The vector database entry.
@@ -51,7 +53,8 @@ def from_vector_db_entry(cls, db_entry: VectorDBEntry) -> "Element":
         return element_cls(**meta)
 
     def to_vector_db_entry(self, vector: list[float]) -> VectorDBEntry:
-        """Create a vector database entry from the element.
+        """
+        Create a vector database entry from the element.
 
         Args:
             vector: The vector.
@@ -67,13 +70,16 @@ def to_vector_db_entry(self, vector: list[float]) -> VectorDBEntry:
 
 
 class TextElement(Element):
-    """An object representing a text element in a document."""
+    """
+    An object representing a text element in a document.
+    """
 
     element_type: str = "text"
     content: str
 
     def get_key(self) -> str:
-        """Get the key of the element which will be used to generate the vector.
+        """
+        Get the key of the element which will be used to generate the vector.
 
         Returns:
             The key.