Add ruff doctring linting

Author: StefanBogdan

pyproject.toml

@@ -39,3 +39,18 @@ exclude = [
 
 [tool.setuptools]
 license-files = []
+
+[tool.ruff.lint]
+select = ["E", "F", "I", "D"]
+ignore = ["D100", "D101", "D102", "D103", "D104", "D105", "D107", "E501"]
+
+# D100: Missing docstring in a public module
+# D101: Missing docstring in a public class
+# D102: Missing docstring in a public method
+# D103: Missing docstring in a public function
+# D104: Missing docstring in a public package
+# D105: Missing docstring in a magic method
+# D107: Missing docstring in an __init__ method
+
+[tool.ruff.lint.pydocstyle]
+convention = "google"

weaviate_agents/base.py

@@ -4,17 +4,14 @@
 
 
 class _BaseAgent:
-    """
-    Base class for all agents.
-    """
+    """Base class for all agents."""
 
     def __init__(
         self,
         client: WeaviateClient,
         agents_host: Union[str, None] = None,
     ):
-        """
-        Initialize the base agent.
+        """Initialize the base agent.
 
         Args:
             client: A Weaviate client instance, either sync or async.

weaviate_agents/personalization/personalization_agent.py

@@ -55,9 +55,11 @@ def create(
             reference_collection: The name of the collection to personalize
             user_properties: Optional dictionary of user properties and their data types
             agents_host: Optional host URL for the agents service
+            vector_name: Optional name of the vector field to use
             timeout: Optional timeout for the request
+
         Returns:
-            PersonalizationAgent: A new instance of the Personalization Agent
+            A new instance of the Personalization Agent
         """
         agent = cls(
             client=client,
@@ -89,9 +91,11 @@ def connect(
             client: The Weaviate client
             reference_collection: The name of the collection to connect to
             agents_host: Optional host URL for the agents service
+            vector_name: Optional name of the vector field to use
             timeout: Optional timeout for the request
+
         Returns:
-            PersonalizationAgent: An instance of the Personalization Agent
+            An instance of the Personalization Agent
         """
         agent = cls(
             client=client,
@@ -116,8 +120,10 @@ def _initialize(
 
         Args:
             reference_collection: The name of the collection to personalize
+            create: Whether to create a new personalization agent
             user_properties: Optional dictionary of user properties and their data types
             vector_name: Optional name of the vector field to use
+            timeout: Optional timeout for the request
         """
         request_data = {
             "collection_name": reference_collection,
@@ -146,7 +152,6 @@ def add_persona(self, persona: Persona) -> None:
             persona: The persona to add. The persona must have a persona_id and properties that match the user properties
             defined when the Personalization Agent was created.
         """
-
         request_data = {
             "persona": persona.model_dump(mode="json"),
             "personalization_request": {
@@ -198,7 +203,7 @@ def get_persona(self, persona_id: UUID) -> Persona:
             persona_id: The ID of the persona to retrieve
 
         Returns:
-            Persona: The retrieved persona
+            The retrieved persona
         """
         request_data = {
             "collection_name": self._reference_collection,
@@ -249,7 +254,7 @@ def has_persona(self, persona_id: UUID) -> bool:
             persona_id: The ID of the persona to check
 
         Returns:
-            bool: True if the persona exists, False otherwise
+            True if the persona exists, False otherwise
         """
         request_data = {
             "collection_name": self._reference_collection,
@@ -325,7 +330,7 @@ def get_interactions(
             interaction_type: The type of interaction to filter by (e.g. "positive", "negative")
 
         Returns:
-            list[PersonaInteractionResponse]: List of matching interactions for the persona
+            List of matching interactions for the persona
         """
         request_data = {
             "interaction_request": {
@@ -372,6 +377,12 @@ def get_objects(
             persona_id: The ID of the persona to get objects for
             limit: The maximum number of objects to return
             recent_interactions_count: The number of recent interactions to consider
+            exclude_interacted_items: Whether to exclude items that have been interacted with
+            decay_rate: The decay rate for the personalization algorithm
+            exclude_items: List of items to exclude from the results
+            use_agent_ranking: Whether to use agent ranking for the results
+            explain_results: Whether to explain the results
+            instruction: Optional instruction to guide the personalization process
         """
         request_data = {
             "objects_request": {
@@ -422,7 +433,7 @@ def exists(
             timeout: Optional timeout for the request
 
         Returns:
-            bool: True if the persona collection exists, False otherwise
+            True if the persona collection exists, False otherwise
         """
         # Initialize base values from client
         base_agent = cls(client, reference_collection, agents_host=agents_host)

weaviate_agents/query/classes/response.py

@@ -30,15 +30,15 @@ class IntegerPropertyFilter(BaseModel):
 
 
 class TextPropertyFilter(BaseModel):
-    """Filter text properties using equality or LIKE operators"""
+    """Filter text properties using equality or LIKE operators."""
 
     property_name: str
     operator: ComparisonOperator
     value: str
 
 
 class BooleanPropertyFilter(BaseModel):
-    """Filter boolean properties using equality operators"""
+    """Filter boolean properties using equality operators."""
 
     property_name: str
     operator: ComparisonOperator
@@ -80,30 +80,29 @@ class BooleanMetrics(str, Enum):
 
 
 class IntegerPropertyAggregation(BaseModel):
-    """Aggregate numeric properties using statistical functions"""
+    """Aggregate numeric properties using statistical functions."""
 
     property_name: str
     metrics: NumericMetrics
 
 
 class TextPropertyAggregation(BaseModel):
-    """Aggregate text properties using frequency analysis"""
+    """Aggregate text properties using frequency analysis."""
 
     property_name: str
     metrics: TextMetrics
     top_occurrences_limit: Optional[int] = None
 
 
 class BooleanPropertyAggregation(BaseModel):
-    """Aggregate boolean properties using statistical functions"""
+    """Aggregate boolean properties using statistical functions."""
 
     property_name: str
     metrics: BooleanMetrics
 
 
 class AggregationResult(BaseModel):
-    """
-    The aggregations to be performed on a collection in a vector database.
+    """The aggregations to be performed on a collection in a vector database.
 
     They should be based on the original user query and can include multiple
     aggregations across different properties and metrics.
@@ -160,11 +159,6 @@ class QueryAgentResponse(BaseModel):
     sources: list[Source]
 
     def display(self) -> None:
-        """
-        Display a pretty-printed summary of the QueryAgentResponse object.
-
-        Returns:
-            None
-        """
+        """Display a pretty-printed summary of the QueryAgentResponse object."""
         print_query_agent_response(self)
         return None

weaviate_agents/query/query_agent.py

@@ -27,12 +27,6 @@ def __init__(
     ):
         """Initialize the QueryAgent.
 
-        Warning:
-            Weaviate Agents - Query Agent is an early stage alpha product. The API is subject to
-            breaking changes. Please ensure you are using the latest version.
-
-            For more information, see the [Weaviate Agents - Query Agent Docs](https://weaviate.io/developers/agents/query)
-
         Args:
             client: The Weaviate client connected to a Weaviate Cloud cluster.
             collections: The collections to query.
@@ -55,8 +49,7 @@ def run(
         view_properties: Optional[List[str]] = None,
         context: Optional[QueryAgentResponse] = None,
     ) -> QueryAgentResponse:
-        """
-        Run the query agent.
+        """Run the query agent.
 
         Args:
             query: The natural language query string for the agent.

weaviate_agents/transformation/transformation_agent.py

@@ -33,12 +33,6 @@ def __init__(
     ):
         """Initialize the TransformationAgent.
 
-        Warning:
-            Weaviate Agents - Transformation Agent is an early stage alpha product. The API is subject to
-            breaking changes. Please ensure you are using the latest version of the client.
-
-            For more information, see the [Weaviate Agents - Transformation Agent Docs](https://weaviate.io/developers/agents/transformation)
-
         Args:
             client: The Weaviate client connected to a Weaviate Cloud cluster.
             collection: The collection to perform transformations on.
@@ -61,7 +55,7 @@ def update_all(self) -> TransformationResponse:
         """Triggers all configured transformation operations on the collection.
 
         Returns:
-            TransformationResponse: response with workflow ID for tracking transformation progress.
+            Response with workflow ID for tracking transformation progress.
 
         Raises:
             httpx.HTTPError: If there is an error communicating with the transformation service.
@@ -130,7 +124,7 @@ def get_status(self, workflow_id: str) -> dict:
             workflow_id: The ID of the workflow to check, obtained from TransformationResponse
 
         Returns:
-            dict: The status response from the transformation service
+            The status response from the transformation service
 
         Raises:
             httpx.HTTPError: If there is an error communicating with the transformation service

weaviate_agents/utils.py

@@ -13,7 +13,6 @@
 
 def print_query_agent_response(response: "QueryAgentResponse"):
     """Prints a formatted response from the Query Agent using rich."""
-
     console.print(
         Panel(
             response.original_query,