fix: Fix docs warnings (#303)

Author: Unshure

src/strands/agent/agent.py

@@ -413,9 +413,9 @@ def structured_output(self, output_model: Type[T], prompt: Optional[str] = None)
         instruct the model to output the structured data.
 
         Args:
-            output_model(Type[BaseModel]): The output model (a JSON schema written as a Pydantic BaseModel)
+            output_model: The output model (a JSON schema written as a Pydantic BaseModel)
                 that the agent will use when responding.
-            prompt(Optional[str]): The prompt to use for the agent.
+            prompt: The prompt to use for the agent.
         """
         messages = self.messages
         if not messages and not prompt:

src/strands/agent/conversation_manager/null_conversation_manager.py

@@ -23,15 +23,15 @@ def apply_management(self, _agent: "Agent") -> None:
         """Does nothing to the conversation history.
 
         Args:
-            agent: The agent whose conversation history will remain unmodified.
+            _agent: The agent whose conversation history will remain unmodified.
         """
         pass
 
     def reduce_context(self, _agent: "Agent", e: Optional[Exception] = None) -> None:
         """Does not reduce context and raises an exception.
 
         Args:
-            agent: The agent whose conversation history will remain unmodified.
+            _agent: The agent whose conversation history will remain unmodified.
             e: The exception that triggered the context reduction, if any.
 
         Raises:

src/strands/models/anthropic.py

@@ -382,8 +382,8 @@ def structured_output(
         """Get structured output from the model.
 
         Args:
-            output_model(Type[BaseModel]): The output model to use for the agent.
-            prompt(Messages): The prompt messages to use for the agent.
+            output_model: The output model to use for the agent.
+            prompt: The prompt messages to use for the agent.
 
         Yields:
             Model events with the last being the structured output.

src/strands/models/bedrock.py

@@ -525,8 +525,8 @@ def structured_output(
         """Get structured output from the model.
 
         Args:
-            output_model(Type[BaseModel]): The output model to use for the agent.
-            prompt(Messages): The prompt messages to use for the agent.
+            output_model: The output model to use for the agent.
+            prompt: The prompt messages to use for the agent.
 
         Yields:
             Model events with the last being the structured output.

src/strands/models/litellm.py

@@ -110,8 +110,8 @@ def structured_output(
         """Get structured output from the model.
 
         Args:
-            output_model(Type[BaseModel]): The output model to use for the agent.
-            prompt(Messages): The prompt messages to use for the agent.
+            output_model: The output model to use for the agent.
+            prompt: The prompt messages to use for the agent.
 
         Yields:
             Model events with the last being the structured output.

src/strands/models/llamaapi.py

@@ -395,8 +395,8 @@ def structured_output(
         """Get structured output from the model.
 
         Args:
-            output_model(Type[BaseModel]): The output model to use for the agent.
-            prompt(Messages): The prompt messages to use for the agent.
+            output_model: The output model to use for the agent.
+            prompt: The prompt messages to use for the agent.
 
         Yields:
             Model events with the last being the structured output.

src/strands/models/ollama.py

@@ -321,8 +321,8 @@ def structured_output(
         """Get structured output from the model.
 
         Args:
-            output_model(Type[BaseModel]): The output model to use for the agent.
-            prompt(Messages): The prompt messages to use for the agent.
+            output_model: The output model to use for the agent.
+            prompt: The prompt messages to use for the agent.
 
         Yields:
             Model events with the last being the structured output.

src/strands/models/openai.py

@@ -145,8 +145,8 @@ def structured_output(
         """Get structured output from the model.
 
         Args:
-            output_model(Type[BaseModel]): The output model to use for the agent.
-            prompt(Messages): The prompt messages to use for the agent.
+            output_model: The output model to use for the agent.
+            prompt: The prompt messages to use for the agent.
 
         Yields:
             Model events with the last being the structured output.

src/strands/tools/decorator.py

@@ -530,15 +530,14 @@ def tool(  # type: ignore
         ```python
         @tool
         def my_tool(name: str, count: int = 1) -> str:
-            '''Does something useful with the provided parameters.
-
-    Args:
-                name: The name to process
-                count: Number of times to process (default: 1)
-
-    Returns:
-                A message with the result
-            '''
+            # Does something useful with the provided parameters.
+            #
+            # Parameters:
+            #   name: The name to process
+            #   count: Number of times to process (default: 1)
+            #
+            # Returns:
+            #   A message with the result
             return f"Processed {name} {count} times"
 
         agent = Agent(tools=[my_tool])

src/strands/types/models/model.py

@@ -50,8 +50,8 @@ def structured_output(
         """Get structured output from the model.
 
         Args:
-            output_model(Type[BaseModel]): The output model to use for the agent.
-            prompt(Messages): The prompt messages to use for the agent.
+            output_model: The output model to use for the agent.
+            prompt: The prompt messages to use for the agent.
 
         Yields:
             Model events with the last being the structured output.