Data

Agent memory is modelled in src/smolagents/memory.py as a typed step list on AgentMemory. Step types form a hierarchy:

• SystemPromptStep — the initial system prompt
• TaskStep — the user task, with optional attached images
• PlanningStep — an optional planning message produced at planning_interval
• ActionStep — one ReAct cycle: model input messages, code/tool call, observations, error, token usage, and step timing
• FinalAnswerStep — the terminal step holding the agent's answer

Each step implements to_messages(summary_mode: bool) which renders it as a list of ChatMessage dicts suitable for the next LLM call. summary_mode=True is used during planning updates to strip previous plan messages and shrink context.

Step callbacks are registered via CallbackRegistry and are dispatched per step type; this is the integration point for custom logging, evaluation harnesses, or live UI updates.

• src/smolagents/memory.py
• src/smolagents/agents.py