From 0217d3fd58c09633eefbd3059bfccc86c9da8b5d Mon Sep 17 00:00:00 2001
From: Albert Villanova del Moral
 <8515462+albertvillanova@users.noreply.github.com>
Date: Thu, 23 Jan 2025 17:38:09 +0100
Subject: [PATCH] Fix MultiStepAgent docstring (#336)

* Fix MultiStepAgent docstring

* Force PR doc build
---
 docs/source/en/reference/agents.md | 3 ---
 src/smolagents/agents.py           | 8 ++++----
 2 files changed, 4 insertions(+), 7 deletions(-)

diff --git a/docs/source/en/reference/agents.md b/docs/source/en/reference/agents.md
index bfe41fe..77a0df1 100644
--- a/docs/source/en/reference/agents.md
+++ b/docs/source/en/reference/agents.md
@@ -35,17 +35,14 @@ We provide two types of agents, based on the main [`Agent`] class.
 
 Both require arguments `model` and list of tools `tools` at initialization.
 
-
 ### Classes of agents
 
-
 [[autodoc]] MultiStepAgent
 
 [[autodoc]] CodeAgent
 
 [[autodoc]] ToolCallingAgent
 
-
 ### ManagedAgent
 
 [[autodoc]] ManagedAgent
diff --git a/src/smolagents/agents.py b/src/smolagents/agents.py
index 416d221..0123a3d 100644
--- a/src/smolagents/agents.py
+++ b/src/smolagents/agents.py
@@ -164,8 +164,8 @@ class MultiStepAgent:
     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.
+        tools (`list[Tool]`): [`Tool`]s 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.
@@ -173,8 +173,8 @@ class MultiStepAgent:
         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.
+        managed_agents (`list`, *optional*): Managed agents that the agent can call.
+        step_callbacks (`list[Callable]`, *optional*): Callbacks that will be called at each step.
         planning_interval (`int`, *optional*): Interval at which the agent will run a planning step.
     """