CoACT initialize (#292)
This commit is contained in:
Linxin Song
187
mm_agents/coact/autogen/tools/tool.py
Normal file
187
mm_agents/coact/autogen/tools/tool.py
Normal file
@@ -0,0 +1,187 @@
|
||||
# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors
|
||||
#
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
|
||||
import inspect
|
||||
from typing import TYPE_CHECKING, Any, Callable, Optional, Union
|
||||
|
||||
from ..doc_utils import export_module
|
||||
from ..tools.function_utils import get_function_schema
|
||||
from .dependency_injection import ChatContext, get_context_params, inject_params
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from ..agentchat.conversable_agent import ConversableAgent
|
||||
|
||||
__all__ = ["Tool", "tool"]
|
||||
|
||||
|
||||
@export_module("autogen.tools")
|
||||
class Tool:
|
||||
"""A class representing a Tool that can be used by an agent for various tasks.
|
||||
|
||||
This class encapsulates a tool with a name, description, and an executable function.
|
||||
The tool can be registered with a ConversableAgent for use either with an LLM or for direct execution.
|
||||
|
||||
Attributes:
|
||||
name (str): The name of the tool.
|
||||
description (str): The description of the tool.
|
||||
func_or_tool (Union[Tool, Callable[..., Any]]): The function or Tool instance to create a Tool from.
|
||||
parameters_json_schema (Optional[ict[str, Any]]): A schema describing the parameters that the function accepts. If None, the schema will be generated from the function signature.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
*,
|
||||
name: Optional[str] = None,
|
||||
description: Optional[str] = None,
|
||||
func_or_tool: Union["Tool", Callable[..., Any]],
|
||||
parameters_json_schema: Optional[dict[str, Any]] = None,
|
||||
) -> None:
|
||||
"""Create a new Tool object.
|
||||
|
||||
Args:
|
||||
name (str): The name of the tool.
|
||||
description (str): The description of the tool.
|
||||
func_or_tool (Union[Tool, Callable[..., Any]]): The function or Tool instance to create a Tool from.
|
||||
parameters_json_schema (Optional[dict[str, Any]]): A schema describing the parameters that the function accepts. If None, the schema will be generated from the function signature.
|
||||
"""
|
||||
if isinstance(func_or_tool, Tool):
|
||||
self._name: str = name or func_or_tool.name
|
||||
self._description: str = description or func_or_tool.description
|
||||
self._func: Callable[..., Any] = func_or_tool.func
|
||||
self._chat_context_param_names: list[str] = func_or_tool._chat_context_param_names
|
||||
elif inspect.isfunction(func_or_tool) or inspect.ismethod(func_or_tool):
|
||||
self._chat_context_param_names = get_context_params(func_or_tool, subclass=ChatContext)
|
||||
self._func = inject_params(func_or_tool)
|
||||
self._name = name or func_or_tool.__name__
|
||||
self._description = description or func_or_tool.__doc__ or ""
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Parameter 'func_or_tool' must be a function, method or a Tool instance, it is '{type(func_or_tool)}' instead."
|
||||
)
|
||||
|
||||
self._func_schema = (
|
||||
{
|
||||
"type": "function",
|
||||
"function": {
|
||||
"name": name,
|
||||
"description": description,
|
||||
"parameters": parameters_json_schema,
|
||||
},
|
||||
}
|
||||
if parameters_json_schema
|
||||
else None
|
||||
)
|
||||
|
||||
@property
|
||||
def name(self) -> str:
|
||||
return self._name
|
||||
|
||||
@property
|
||||
def description(self) -> str:
|
||||
return self._description
|
||||
|
||||
@property
|
||||
def func(self) -> Callable[..., Any]:
|
||||
return self._func
|
||||
|
||||
def register_for_llm(self, agent: "ConversableAgent") -> None:
|
||||
"""Registers the tool for use with a ConversableAgent's language model (LLM).
|
||||
|
||||
This method registers the tool so that it can be invoked by the agent during
|
||||
interactions with the language model.
|
||||
|
||||
Args:
|
||||
agent (ConversableAgent): The agent to which the tool will be registered.
|
||||
"""
|
||||
if self._func_schema:
|
||||
agent.update_tool_signature(self._func_schema, is_remove=False)
|
||||
else:
|
||||
agent.register_for_llm()(self)
|
||||
|
||||
def register_for_execution(self, agent: "ConversableAgent") -> None:
|
||||
"""Registers the tool for direct execution by a ConversableAgent.
|
||||
|
||||
This method registers the tool so that it can be executed by the agent,
|
||||
typically outside of the context of an LLM interaction.
|
||||
|
||||
Args:
|
||||
agent (ConversableAgent): The agent to which the tool will be registered.
|
||||
"""
|
||||
agent.register_for_execution()(self)
|
||||
|
||||
def register_tool(self, agent: "ConversableAgent") -> None:
|
||||
"""Register a tool to be both proposed and executed by an agent.
|
||||
|
||||
Equivalent to calling both `register_for_llm` and `register_for_execution` with the same agent.
|
||||
|
||||
Note: This will not make the agent recommend and execute the call in the one step. If the agent
|
||||
recommends the tool, it will need to be the next agent to speak in order to execute the tool.
|
||||
|
||||
Args:
|
||||
agent (ConversableAgent): The agent to which the tool will be registered.
|
||||
"""
|
||||
self.register_for_llm(agent)
|
||||
self.register_for_execution(agent)
|
||||
|
||||
def __call__(self, *args: Any, **kwargs: Any) -> Any:
|
||||
"""Execute the tool by calling its underlying function with the provided arguments.
|
||||
|
||||
Args:
|
||||
*args: Positional arguments to pass to the tool
|
||||
**kwargs: Keyword arguments to pass to the tool
|
||||
|
||||
Returns:
|
||||
The result of executing the tool's function.
|
||||
"""
|
||||
return self._func(*args, **kwargs)
|
||||
|
||||
@property
|
||||
def tool_schema(self) -> dict[str, Any]:
|
||||
"""Get the schema for the tool.
|
||||
|
||||
This is the preferred way of handling function calls with OpeaAI and compatible frameworks.
|
||||
|
||||
"""
|
||||
return get_function_schema(self.func, name=self.name, description=self.description)
|
||||
|
||||
@property
|
||||
def function_schema(self) -> dict[str, Any]:
|
||||
"""Get the schema for the function.
|
||||
|
||||
This is the old way of handling function calls with OpenAI and compatible frameworks.
|
||||
It is provided for backward compatibility.
|
||||
|
||||
"""
|
||||
schema = get_function_schema(self.func, name=self.name, description=self.description)
|
||||
return schema["function"] # type: ignore[no-any-return]
|
||||
|
||||
@property
|
||||
def realtime_tool_schema(self) -> dict[str, Any]:
|
||||
"""Get the schema for the tool.
|
||||
|
||||
This is the preferred way of handling function calls with OpeaAI and compatible frameworks.
|
||||
|
||||
"""
|
||||
schema = get_function_schema(self.func, name=self.name, description=self.description)
|
||||
schema = {"type": schema["type"], **schema["function"]}
|
||||
|
||||
return schema
|
||||
|
||||
|
||||
@export_module("autogen.tools")
|
||||
def tool(name: Optional[str] = None, description: Optional[str] = None) -> Callable[[Callable[..., Any]], Tool]:
|
||||
"""Decorator to create a Tool from a function.
|
||||
|
||||
Args:
|
||||
name (str): The name of the tool.
|
||||
description (str): The description of the tool.
|
||||
|
||||
Returns:
|
||||
Callable[[Callable[..., Any]], Tool]: A decorator that creates a Tool from a function.
|
||||
"""
|
||||
|
||||
def decorator(func: Callable[..., Any]) -> Tool:
|
||||
return Tool(name=name, description=description, func_or_tool=func)
|
||||
|
||||
return decorator
|
||||
Reference in New Issue
Block a user