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AgentConfig

ToolkitConfig

Bases: ConfigBaseModel

Toolkit config.

Source code in utu/config/agent_config.py 
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class ToolkitConfig(ConfigBaseModel):
    """Toolkit config."""

    mode: Literal["builtin", "customized", "mcp"] = "builtin"
    """Toolkit mode."""
    name: str | None = None
    """Toolkit name."""
    activated_tools: list[str] | None = None
    """Activated tools, if None, all tools will be activated."""
    config: dict | None = Field(default_factory=dict)
    """Specified  configs for certain toolkit. We use raw dict for simplicity"""
    config_llm: ModelConfigs | None = None  # | dict[str, ModelConfigs]
    """LLM config if used in toolkit."""
    customized_filepath: str | None = None
    """Customized toolkit filepath."""
    customized_classname: str | None = None
    """Customized toolkit classname."""
    mcp_transport: Literal["stdio", "sse", "streamable_http"] = "stdio"
    """MCP transport."""
    mcp_client_session_timeout_seconds: int = 20
    """The read timeout passed to the MCP ClientSession. We set it bigger to avoid timeout expections."""

mode class-attribute instance-attribute 

mode: Literal['builtin', 'customized', 'mcp'] = 'builtin'

Toolkit mode.

name class-attribute instance-attribute 

name: str | None = None

Toolkit name.

activated_tools class-attribute instance-attribute 

activated_tools: list[str] | None = None

Activated tools, if None, all tools will be activated.

config class-attribute instance-attribute 

config: dict | None = Field(default_factory=dict)

Specified configs for certain toolkit. We use raw dict for simplicity

config_llm class-attribute instance-attribute 

config_llm: ModelConfigs | None = None

LLM config if used in toolkit.

customized_filepath class-attribute instance-attribute 

customized_filepath: str | None = None

Customized toolkit filepath.

customized_classname class-attribute instance-attribute 

customized_classname: str | None = None

Customized toolkit classname.

mcp_transport class-attribute instance-attribute 

mcp_transport: Literal[
    "stdio", "sse", "streamable_http"
] = "stdio"

MCP transport.

mcp_client_session_timeout_seconds class-attribute instance-attribute 

mcp_client_session_timeout_seconds: int = 20

The read timeout passed to the MCP ClientSession. We set it bigger to avoid timeout expections.

AgentConfig

Bases: ConfigBaseModel

Overall agent config

Source code in utu/config/agent_config.py 
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class AgentConfig(ConfigBaseModel):
    """Overall agent config"""

    type: Literal["simple", "orchestra", "orchestrator", "workforce"] = "simple"
    """Agent type"""

    # simple agent config
    model: ModelConfigs = Field(default_factory=ModelConfigs)
    """Model config, with model_provider, model_settings, model_params"""
    agent: ProfileConfig = Field(default_factory=ProfileConfig)
    """Agent profile config"""
    context_manager: ContextManagerConfig = Field(default_factory=ContextManagerConfig)
    """Context manager config"""
    env: EnvConfig = Field(default_factory=EnvConfig)
    """Env config"""
    toolkits: dict[str, ToolkitConfig] = Field(default_factory=dict)
    """Toolkits config"""
    max_turns: int = 50
    """Max turns for simple agent. This param is derived from @openai-agents"""

    # orchestra agent config
    planner_model: ModelConfigs = Field(default_factory=ModelConfigs)
    """Planner model config"""
    planner_config: dict = Field(default_factory=dict)
    """Planner config (dict)\n
    - `examples_path`: path to planner examples json file"""
    workers: dict[str, "AgentConfig"] = Field(default_factory=dict)
    """Workers config"""
    workers_info: list[dict] = Field(default_factory=list)
    """Workers info, list of {name, desc, strengths, weaknesses}\n
    - `name`: worker name
    - `desc`: worker description
    - `strengths`: worker strengths
    - `weaknesses`: worker weaknesses"""
    reporter_model: ModelConfigs = Field(default_factory=ModelConfigs)
    """Reporter model config"""
    reporter_config: dict = Field(default_factory=dict)
    """Reporter config (dict)\n
    - `template_path`: template Jinja2 file path, with `question` and `trajectory` variables"""

    # workforce agent config
    workforce_planner_model: ModelConfigs = Field(default_factory=ModelConfigs)
    """Workforce planner model config"""
    workforce_planner_config: dict = Field(default_factory=dict)
    """Workforce planner config (dict)"""
    workforce_assigner_model: ModelConfigs = Field(default_factory=ModelConfigs)
    """Workforce assigner model config"""
    workforce_assigner_config: dict = Field(default_factory=dict)
    """Workforce assigner config (dict)"""
    workforce_answerer_model: ModelConfigs = Field(default_factory=ModelConfigs)
    """Workforce answerer model config"""
    workforce_answerer_config: dict = Field(default_factory=dict)
    """Workforce answerer config (dict)"""
    workforce_executor_agents: dict[str, "AgentConfig"] = Field(default_factory=dict)
    """Workforce executor agents config"""
    workforce_executor_config: dict = Field(default_factory=dict)
    """Workforce executor config (dict)"""
    workforce_executor_infos: list[dict] = Field(default_factory=list)
    """Workforce executor infos, list of {name, desc, strengths, weaknesses}"""

    # orchestrator agent config
    orchestrator_router: "AgentConfig" = None
    """Orchestrator router agent config"""
    orchestrator_config: dict = Field(default_factory=dict)
    """Orchestrator config (dict)\n
    - `name`: name of the orchestrator-workers system
    - `examples_path`: path to planner examples. default utu/data/plan_examples/chain.json
    - `additional_instructions`: additional instructions for planner
    - `add_chitchat_subagent`: whether to add chitchat subagent. default True"""
    orchestrator_model: ModelConfigs = Field(default_factory=ModelConfigs)
    """Planner model config"""
    orchestrator_workers: dict[str, "AgentConfig"] = Field(default_factory=dict)
    """Workers config"""
    orchestrator_workers_info: list[dict] = Field(default_factory=list)
    """Workers info, list of {name, description}"""

type class-attribute instance-attribute 

type: Literal[
    "simple", "orchestra", "orchestrator", "workforce"
] = "simple"

Agent type

model class-attribute instance-attribute 

model: ModelConfigs = Field(default_factory=ModelConfigs)

Model config, with model_provider, model_settings, model_params

agent class-attribute instance-attribute 

agent: ProfileConfig = Field(default_factory=ProfileConfig)

Agent profile config

context_manager class-attribute instance-attribute 

context_manager: ContextManagerConfig = Field(
    default_factory=ContextManagerConfig
)

Context manager config

env class-attribute instance-attribute 

env: EnvConfig = Field(default_factory=EnvConfig)

Env config

toolkits class-attribute instance-attribute 

toolkits: dict[str, ToolkitConfig] = Field(
    default_factory=dict
)

Toolkits config

max_turns class-attribute instance-attribute 

max_turns: int = 50

Max turns for simple agent. This param is derived from @openai-agents

planner_model class-attribute instance-attribute 

planner_model: ModelConfigs = Field(
    default_factory=ModelConfigs
)

Planner model config

planner_config class-attribute instance-attribute 

planner_config: dict = Field(default_factory=dict)

Planner config (dict)

  • examples_path: path to planner examples json file

workers class-attribute instance-attribute 

workers: dict[str, AgentConfig] = Field(
    default_factory=dict
)

Workers config

workers_info class-attribute instance-attribute 

workers_info: list[dict] = Field(default_factory=list)

Workers info, list of {name, desc, strengths, weaknesses}

  • name: worker name
  • desc: worker description
  • strengths: worker strengths
  • weaknesses: worker weaknesses

reporter_model class-attribute instance-attribute 

reporter_model: ModelConfigs = Field(
    default_factory=ModelConfigs
)

Reporter model config

reporter_config class-attribute instance-attribute 

reporter_config: dict = Field(default_factory=dict)

Reporter config (dict)

  • template_path: template Jinja2 file path, with question and trajectory variables

workforce_planner_model class-attribute instance-attribute 

workforce_planner_model: ModelConfigs = Field(
    default_factory=ModelConfigs
)

Workforce planner model config

workforce_planner_config class-attribute instance-attribute 

workforce_planner_config: dict = Field(default_factory=dict)

Workforce planner config (dict)

workforce_assigner_model class-attribute instance-attribute 

workforce_assigner_model: ModelConfigs = Field(
    default_factory=ModelConfigs
)

Workforce assigner model config

workforce_assigner_config class-attribute instance-attribute 

workforce_assigner_config: dict = Field(
    default_factory=dict
)

Workforce assigner config (dict)

workforce_answerer_model class-attribute instance-attribute 

workforce_answerer_model: ModelConfigs = Field(
    default_factory=ModelConfigs
)

Workforce answerer model config

workforce_answerer_config class-attribute instance-attribute 

workforce_answerer_config: dict = Field(
    default_factory=dict
)

Workforce answerer config (dict)

workforce_executor_agents class-attribute instance-attribute 

workforce_executor_agents: dict[str, AgentConfig] = Field(
    default_factory=dict
)

Workforce executor agents config

workforce_executor_config class-attribute instance-attribute 

workforce_executor_config: dict = Field(
    default_factory=dict
)

Workforce executor config (dict)

workforce_executor_infos class-attribute instance-attribute 

workforce_executor_infos: list[dict] = Field(
    default_factory=list
)

Workforce executor infos, list of {name, desc, strengths, weaknesses}

orchestrator_router class-attribute instance-attribute 

orchestrator_router: AgentConfig = None

Orchestrator router agent config

orchestrator_config class-attribute instance-attribute 

orchestrator_config: dict = Field(default_factory=dict)

Orchestrator config (dict)

  • name: name of the orchestrator-workers system
  • examples_path: path to planner examples. default utu/data/plan_examples/chain.json
  • additional_instructions: additional instructions for planner
  • add_chitchat_subagent: whether to add chitchat subagent. default True

orchestrator_model class-attribute instance-attribute 

orchestrator_model: ModelConfigs = Field(
    default_factory=ModelConfigs
)

Planner model config

orchestrator_workers class-attribute instance-attribute 

orchestrator_workers: dict[str, AgentConfig] = Field(
    default_factory=dict
)

Workers config

orchestrator_workers_info class-attribute instance-attribute 

orchestrator_workers_info: list[dict] = Field(
    default_factory=list
)

Workers info, list of {name, description}