tooluniverse.agentic_tool module

class tooluniverse.agentic_tool.AgenticTool(tool_config: Dict[str, Any])

Bases: BaseTool

Generic wrapper around LLM prompting supporting JSON-defined configs with prompts and input arguments.

__init__(tool_config: Dict[str, Any])

_format_prompt(arguments: Dict[str, Any]) → str

_get_global_fallback_chain() → List[Dict[str, str]]

Get the global fallback chain from environment or use default.

_try_api(api_type: str, model_id: str) → bool

Try to initialize a specific API and model.

_try_initialize_api()

Try to initialize the primary API, fallback to secondary if configured.

_validate_arguments(arguments: Dict[str, Any])

_validate_model_config()

estimate_token_usage(arguments: Dict[str, Any]) → Dict[str, int]

get_availability_status() → Dict[str, Any]

Get detailed availability status of the tool.

get_input_arguments() → List[str]

get_model_info() → Dict[str, Any]

get_prompt_preview(arguments: Dict[str, Any]) → str

get_prompt_template() → str

static has_any_api_keys() → bool

Check if any API keys are available across all supported API types.

Returns:

True if at least one API type has all required keys, False otherwise

Return type:

bool

is_available() → bool

Check if the tool is available for use.

retry_initialization() → bool

Attempt to reinitialize the tool (useful if API keys were updated).

run(arguments: Dict[str, Any]) → Dict[str, Any]

Execute the tool.

The default BaseTool implementation accepts an optional arguments mapping to align with most concrete tool implementations which expect a dictionary of inputs.

validate_configuration() → Dict[str, Any]