anthropic: docstrings (#23145)

Added missed docstrings. Format docstrings to the consistent format
(used in the API Reference)

libs/partners/anthropic/langchain_anthropic/chat_models.py

@@ -231,7 +231,7 @@ def _format_messages(messages: List[BaseMessage]) -> Tuple[Optional[str], List[D
 
 
 class ChatAnthropic(BaseChatModel):
-    """Anthropic chat model integration.
+    """Anthropic chat models.
 
     See https://docs.anthropic.com/en/docs/models-overview for a list of the latest models.
 
@@ -1008,6 +1008,8 @@ class ChatAnthropic(BaseChatModel):
 
 
 class AnthropicTool(TypedDict):
+    """Anthropic tool definition."""
+
     name: str
     description: str
     input_schema: Dict[str, Any]
@@ -1016,6 +1018,7 @@ class AnthropicTool(TypedDict):
 def convert_to_anthropic_tool(
     tool: Union[Dict[str, Any], Type[BaseModel], Callable, BaseTool],
 ) -> AnthropicTool:
+    """Convert a tool-like object to an Anthropic tool definition."""
     # already in Anthropic tool format
     if isinstance(tool, dict) and all(
         k in tool for k in ("name", "description", "input_schema")

libs/partners/anthropic/langchain_anthropic/experimental.py

@@ -55,6 +55,7 @@ def _get_type(parameter: Dict[str, Any]) -> str:
 
 
 def get_system_message(tools: List[Dict]) -> str:
+    """Generate a system message that describes the available tools."""
     tools_data: List[Dict] = [
         {
             "tool_name": tool["name"],

libs/partners/anthropic/langchain_anthropic/llms.py

@@ -362,4 +362,6 @@ class AnthropicLLM(LLM, _AnthropicCommon):
 
 @deprecated(since="0.1.0", removal="0.3.0", alternative="AnthropicLLM")
 class Anthropic(AnthropicLLM):
+    """Anthropic large language model."""
+
     pass

libs/partners/anthropic/langchain_anthropic/output_parsers.py

@@ -7,9 +7,14 @@ from langchain_core.pydantic_v1 import BaseModel
 
 
 class ToolsOutputParser(BaseGenerationOutputParser):
+    """Output parser for tool calls."""
+
     first_tool_only: bool = False
+    """Whether to return only the first tool call."""
     args_only: bool = False
+    """Whether to return only the arguments of the tool calls."""
     pydantic_schemas: Optional[List[Type[BaseModel]]] = None
+    """Pydantic schemas to parse tool calls into."""
 
     class Config:
         extra = "forbid"
@@ -59,6 +64,7 @@ class ToolsOutputParser(BaseGenerationOutputParser):
 
 
 def extract_tool_calls(content: List[dict]) -> List[ToolCall]:
+    """Extract tool calls from a list of content blocks."""
     tool_calls = []
     for block in content:
         if block["type"] != "tool_use":