def to_dict()

in src/smolagents/agents.py [0:0]

• 32 lines of code
• 13 McCabe index (conditional complexity)

    def to_dict(self) -> dict[str, Any]:
        """Convert the agent to a dictionary representation.

        Returns:
            `dict`: Dictionary representation of the agent.
        """
        # TODO: handle serializing step_callbacks and final_answer_checks
        for attr in ["final_answer_checks", "step_callbacks"]:
            if getattr(self, attr, None):
                self.logger.log(f"This agent has {attr}: they will be ignored by this method.", LogLevel.INFO)

        tool_dicts = [tool.to_dict() for tool in self.tools.values()]
        tool_requirements = {req for tool in self.tools.values() for req in tool.to_dict()["requirements"]}
        managed_agents_requirements = {
            req for managed_agent in self.managed_agents.values() for req in managed_agent.to_dict()["requirements"]
        }
        requirements = tool_requirements | managed_agents_requirements
        if hasattr(self, "authorized_imports"):
            requirements.update(
                {package.split(".")[0] for package in self.authorized_imports if package not in BASE_BUILTIN_MODULES}
            )

        agent_dict = {
            "class": self.__class__.__name__,
            "tools": tool_dicts,
            "model": {
                "class": self.model.__class__.__name__,
                "data": self.model.to_dict(),
            },
            "managed_agents": [managed_agent.to_dict() for managed_agent in self.managed_agents.values()],
            "prompt_templates": self.prompt_templates,
            "max_steps": self.max_steps,
            "verbosity_level": int(self.logger.level),
            "grammar": self.grammar,
            "planning_interval": self.planning_interval,
            "name": self.name,
            "description": self.description,
            "requirements": sorted(requirements),
        }
        return agent_dict