Files
letta-server/letta/schemas/tool.py
2024-11-03 11:42:01 -08:00

216 lines
9.1 KiB
Python

from typing import Dict, List, Optional
from composio import LogLevel
from pydantic import Field
from letta.functions.helpers import (
generate_composio_tool_wrapper,
generate_crewai_tool_wrapper,
generate_langchain_tool_wrapper,
)
from letta.functions.schema_generator import generate_schema_from_args_schema
from letta.schemas.letta_base import LettaBase
from letta.schemas.openai.chat_completions import ToolCall
class BaseTool(LettaBase):
__id_prefix__ = "tool"
class Tool(BaseTool):
"""
Representation of a tool, which is a function that can be called by the agent.
Parameters:
id (str): The unique identifier of the tool.
name (str): The name of the function.
tags (List[str]): Metadata tags.
source_code (str): The source code of the function.
json_schema (Dict): The JSON schema of the function.
"""
id: str = Field(..., description="The id of the tool.")
description: Optional[str] = Field(None, description="The description of the tool.")
source_type: Optional[str] = Field(None, description="The type of the source code.")
module: Optional[str] = Field(None, description="The module of the function.")
organization_id: str = Field(..., description="The unique identifier of the organization associated with the tool.")
name: str = Field(..., description="The name of the function.")
tags: List[str] = Field(..., description="Metadata tags.")
# code
source_code: str = Field(..., description="The source code of the function.")
json_schema: Dict = Field(default_factory=dict, description="The JSON schema of the function.")
# metadata fields
created_by_id: str = Field(..., description="The id of the user that made this Tool.")
last_updated_by_id: str = Field(..., description="The id of the user that made this Tool.")
def to_dict(self):
"""
Convert tool into OpenAI representation.
"""
return vars(
ToolCall(
tool_id=self.id,
tool_call_type="function",
function=self.module,
)
)
class ToolCreate(LettaBase):
name: Optional[str] = Field(None, description="The name of the function (auto-generated from source_code if not provided).")
description: Optional[str] = Field(None, description="The description of the tool.")
tags: List[str] = Field([], description="Metadata tags.")
module: Optional[str] = Field(None, description="The source code of the function.")
source_code: str = Field(..., description="The source code of the function.")
source_type: str = Field(..., description="The source type of the function.")
json_schema: Optional[Dict] = Field(
None, description="The JSON schema of the function (auto-generated from source_code if not provided)"
)
@classmethod
def from_composio(cls, action: "ActionType") -> "ToolCreate":
"""
Class method to create an instance of Letta-compatible Composio Tool.
Check https://docs.composio.dev/introduction/intro/overview to look at options for from_composio
This function will error if we find more than one tool, or 0 tools.
Args:
action ActionType: A action name to filter tools by.
Returns:
Tool: A Letta Tool initialized with attributes derived from the Composio tool.
"""
from composio_langchain import ComposioToolSet
composio_toolset = ComposioToolSet(logging_level=LogLevel.ERROR)
composio_tools = composio_toolset.get_tools(actions=[action])
assert len(composio_tools) > 0, "User supplied parameters do not match any Composio tools"
assert len(composio_tools) == 1, f"User supplied parameters match too many Composio tools; {len(composio_tools)} > 1"
composio_tool = composio_tools[0]
description = composio_tool.description
source_type = "python"
tags = ["composio"]
wrapper_func_name, wrapper_function_str = generate_composio_tool_wrapper(action)
json_schema = generate_schema_from_args_schema(composio_tool.args_schema, name=wrapper_func_name, description=description)
return cls(
name=wrapper_func_name,
description=description,
source_type=source_type,
tags=tags,
source_code=wrapper_function_str,
json_schema=json_schema,
)
@classmethod
def from_langchain(
cls,
langchain_tool: "LangChainBaseTool",
additional_imports_module_attr_map: dict[str, str] = None,
) -> "ToolCreate":
"""
Class method to create an instance of Tool from a Langchain tool (must be from langchain_community.tools).
Args:
langchain_tool (LangChainBaseTool): An instance of a LangChain BaseTool (BaseTool from LangChain)
additional_imports_module_attr_map (dict[str, str]): A mapping of module names to attribute name. This is used internally to import all the required classes for the langchain tool. For example, you would pass in `{"langchain_community.utilities": "WikipediaAPIWrapper"}` for `from langchain_community.tools import WikipediaQueryRun`. NOTE: You do NOT need to specify the tool import here, that is done automatically for you.
Returns:
Tool: A Letta Tool initialized with attributes derived from the provided LangChain BaseTool object.
"""
description = langchain_tool.description
source_type = "python"
tags = ["langchain"]
# NOTE: langchain tools may come from different packages
wrapper_func_name, wrapper_function_str = generate_langchain_tool_wrapper(langchain_tool, additional_imports_module_attr_map)
json_schema = generate_schema_from_args_schema(langchain_tool.args_schema, name=wrapper_func_name, description=description)
return cls(
name=wrapper_func_name,
description=description,
source_type=source_type,
tags=tags,
source_code=wrapper_function_str,
json_schema=json_schema,
)
@classmethod
def from_crewai(
cls,
crewai_tool: "CrewAIBaseTool",
additional_imports_module_attr_map: dict[str, str] = None,
) -> "ToolCreate":
"""
Class method to create an instance of Tool from a crewAI BaseTool object.
Args:
crewai_tool (CrewAIBaseTool): An instance of a crewAI BaseTool (BaseTool from crewai)
Returns:
Tool: A Letta Tool initialized with attributes derived from the provided crewAI BaseTool object.
"""
description = crewai_tool.description
source_type = "python"
tags = ["crew-ai"]
wrapper_func_name, wrapper_function_str = generate_crewai_tool_wrapper(crewai_tool, additional_imports_module_attr_map)
json_schema = generate_schema_from_args_schema(crewai_tool.args_schema, name=wrapper_func_name, description=description)
return cls(
name=wrapper_func_name,
description=description,
source_type=source_type,
tags=tags,
source_code=wrapper_function_str,
json_schema=json_schema,
)
@classmethod
def load_default_langchain_tools(cls) -> List["ToolCreate"]:
# For now, we only support wikipedia tool
from langchain_community.tools import WikipediaQueryRun
from langchain_community.utilities import WikipediaAPIWrapper
wikipedia_tool = ToolCreate.from_langchain(
WikipediaQueryRun(api_wrapper=WikipediaAPIWrapper()), {"langchain_community.utilities": "WikipediaAPIWrapper"}
)
return [wikipedia_tool]
@classmethod
def load_default_crewai_tools(cls) -> List["ToolCreate"]:
# For now, we only support scrape website tool
from crewai_tools import ScrapeWebsiteTool
web_scrape_tool = ToolCreate.from_crewai(ScrapeWebsiteTool())
return [web_scrape_tool]
@classmethod
def load_default_composio_tools(cls) -> List["ToolCreate"]:
from composio_langchain import Action
calculator = ToolCreate.from_composio(action=Action.MATHEMATICAL_CALCULATOR)
serp_news = ToolCreate.from_composio(action=Action.SERPAPI_NEWS_SEARCH)
serp_google_search = ToolCreate.from_composio(action=Action.SERPAPI_SEARCH)
serp_google_maps = ToolCreate.from_composio(action=Action.SERPAPI_GOOGLE_MAPS_SEARCH)
return [calculator, serp_news, serp_google_search, serp_google_maps]
class ToolUpdate(LettaBase):
description: Optional[str] = Field(None, description="The description of the tool.")
name: Optional[str] = Field(None, description="The name of the function.")
tags: Optional[List[str]] = Field(None, description="Metadata tags.")
module: Optional[str] = Field(None, description="The source code of the function.")
source_code: Optional[str] = Field(None, description="The source code of the function.")
source_type: Optional[str] = Field(None, description="The type of the source code.")
json_schema: Optional[Dict] = Field(
None, description="The JSON schema of the function (auto-generated from source_code if not provided)"
)