Add args to MultiStepAgent docstring (#332)

* Add args to MultiStepAgent docstring

docs/source/en/reference/agents.md

@@ -38,6 +38,7 @@ Both require arguments `model` and list of tools `tools` at initialization.
 
 ### Classes of agents
 
+
 [[autodoc]] MultiStepAgent
 
 [[autodoc]] CodeAgent

src/smolagents/agents.py

@@ -162,6 +162,20 @@ class MultiStepAgent:
     """
     Agent class that solves the given task step by step, using the ReAct framework:
     While the objective is not reached, the agent will perform a cycle of action (given by the LLM) and observation (obtained from the environment).
+
+    Args:
+        tools (`list[[`Tool`]]`): List of tools that the agent can use.
+        model (Callable[[list[dict[str, str]]], [`ChatMessage`]]): Model that will generate the agent's actions.
+        system_prompt (`str`, *optional*): System prompt that will be used to generate the agent's actions.
+        tool_description_template (`str`, *optional*): Template used to describe the tools in the system prompt.
+        max_steps (`int`, default `6`): Maximum number of steps the agent can take to solve the task.
+        tool_parser (`Callable`, *optional*): Function used to parse the tool calls from the LLM output.
+        add_base_tools (`bool`, default `False`): Whether to add the base tools to the agent's tools.
+        verbosity_level (`int`, default `1`): Level of verbosity of the agent's logs.
+        grammar (`dict[str, str]`, *optional*): Grammar used to parse the LLM output.
+        managed_agents (`list`, *optional*): List of managed agents that the agent can call.
+        step_callbacks (`list[Callable]`, *optional*): List of callbacks that will be called at each step.
+        planning_interval (`int`, *optional*): Interval at which the agent will run a planning step.
     """
 
     def __init__(