Files
crewAI/src/crewai/tools/tool_usage.py
Brandon Hancock (bhancock_ai) b8d07fee83 Brandon/eng 290 make tool inputs actual objects and not strings (#1868)
* Improving tool calling to pass dictionaries instead of strings

* Fix issues with parsing none/null

* remove prints and unnecessary comments

* Fix crew_test issues with function calling

* improve prompting

* add back in support for add_image

* add tests for tool validation

* revert back to figure out why tests are timing out

* Update cassette

* trying to find what is timing out

* add back in guardrails

* add back in manager delegation tests

* Trying to fix tests

* Force test to pass

* Trying to fix tests

* add in more role tests

* add back old tool validation

* updating tests

* vcr

* Fix tests

* improve function llm logic

* vcr 2

* drop llm

* Failing test

* add more tests back in

* Revert tool validation
2025-01-10 17:16:46 -05:00

463 lines
18 KiB
Python

import ast
import datetime
import json
import re
import time
from difflib import SequenceMatcher
from textwrap import dedent
from typing import Any, Dict, List, Union
from json_repair import repair_json
import crewai.utilities.events as events
from crewai.agents.tools_handler import ToolsHandler
from crewai.task import Task
from crewai.telemetry import Telemetry
from crewai.tools import BaseTool
from crewai.tools.structured_tool import CrewStructuredTool
from crewai.tools.tool_calling import InstructorToolCalling, ToolCalling
from crewai.tools.tool_usage_events import ToolUsageError, ToolUsageFinished
from crewai.utilities import I18N, Converter, ConverterError, Printer
try:
import agentops # type: ignore
except ImportError:
agentops = None
OPENAI_BIGGER_MODELS = [
"gpt-4",
"gpt-4o",
"o1-preview",
"o1-mini",
"o1",
"o3",
"o3-mini",
]
class ToolUsageErrorException(Exception):
"""Exception raised for errors in the tool usage."""
def __init__(self, message: str) -> None:
self.message = message
super().__init__(self.message)
class ToolUsage:
"""
Class that represents the usage of a tool by an agent.
Attributes:
task: Task being executed.
tools_handler: Tools handler that will manage the tool usage.
tools: List of tools available for the agent.
original_tools: Original tools available for the agent before being converted to BaseTool.
tools_description: Description of the tools available for the agent.
tools_names: Names of the tools available for the agent.
function_calling_llm: Language model to be used for the tool usage.
"""
def __init__(
self,
tools_handler: ToolsHandler,
tools: List[BaseTool],
original_tools: List[Any],
tools_description: str,
tools_names: str,
task: Task,
function_calling_llm: Any,
agent: Any,
action: Any,
) -> None:
self._i18n: I18N = agent.i18n
self._printer: Printer = Printer()
self._telemetry: Telemetry = Telemetry()
self._run_attempts: int = 1
self._max_parsing_attempts: int = 3
self._remember_format_after_usages: int = 3
self.agent = agent
self.tools_description = tools_description
self.tools_names = tools_names
self.tools_handler = tools_handler
self.original_tools = original_tools
self.tools = tools
self.task = task
self.action = action
self.function_calling_llm = function_calling_llm
# Set the maximum parsing attempts for bigger models
if (
self.function_calling_llm
and self.function_calling_llm in OPENAI_BIGGER_MODELS
):
self._max_parsing_attempts = 2
self._remember_format_after_usages = 4
def parse_tool_calling(self, tool_string: str):
"""Parse the tool string and return the tool calling."""
return self._tool_calling(tool_string)
def use(
self, calling: Union[ToolCalling, InstructorToolCalling], tool_string: str
) -> str:
if isinstance(calling, ToolUsageErrorException):
error = calling.message
if self.agent.verbose:
self._printer.print(content=f"\n\n{error}\n", color="red")
self.task.increment_tools_errors()
return error
try:
tool = self._select_tool(calling.tool_name)
except Exception as e:
error = getattr(e, "message", str(e))
self.task.increment_tools_errors()
if self.agent.verbose:
self._printer.print(content=f"\n\n{error}\n", color="red")
return error
if isinstance(tool, CrewStructuredTool) and tool.name == self._i18n.tools("add_image")["name"]: # type: ignore
try:
result = self._use(tool_string=tool_string, tool=tool, calling=calling)
return result
except Exception as e:
error = getattr(e, "message", str(e))
self.task.increment_tools_errors()
if self.agent.verbose:
self._printer.print(content=f"\n\n{error}\n", color="red")
return error
return f"{self._use(tool_string=tool_string, tool=tool, calling=calling)}"
def _use(
self,
tool_string: str,
tool: Any,
calling: Union[ToolCalling, InstructorToolCalling],
) -> str: # TODO: Fix this return type
tool_event = agentops.ToolEvent(name=calling.tool_name) if agentops else None # type: ignore
if self._check_tool_repeated_usage(calling=calling): # type: ignore # _check_tool_repeated_usage of "ToolUsage" does not return a value (it only ever returns None)
try:
result = self._i18n.errors("task_repeated_usage").format(
tool_names=self.tools_names
)
self._telemetry.tool_repeated_usage(
llm=self.function_calling_llm,
tool_name=tool.name,
attempts=self._run_attempts,
)
result = self._format_result(result=result) # type: ignore # "_format_result" of "ToolUsage" does not return a value (it only ever returns None)
return result # type: ignore # Fix the return type of this function
except Exception:
self.task.increment_tools_errors()
started_at = time.time()
from_cache = False
result = None # type: ignore # Incompatible types in assignment (expression has type "None", variable has type "str")
# check if cache is available
if self.tools_handler.cache:
result = self.tools_handler.cache.read( # type: ignore # Incompatible types in assignment (expression has type "str | None", variable has type "str")
tool=calling.tool_name, input=calling.arguments
)
from_cache = result is not None
original_tool = next(
(ot for ot in self.original_tools if ot.name == tool.name), None
)
if result is None: #! finecwg: if not result --> if result is None
try:
if calling.tool_name in [
"Delegate work to coworker",
"Ask question to coworker",
]:
coworker = (
calling.arguments.get("coworker") if calling.arguments else None
)
self.task.increment_delegations(coworker)
if calling.arguments:
try:
acceptable_args = tool.args_schema.model_json_schema()["properties"].keys() # type: ignore
arguments = {
k: v
for k, v in calling.arguments.items()
if k in acceptable_args
}
result = tool.invoke(input=arguments)
except Exception:
arguments = calling.arguments
result = tool.invoke(input=arguments)
else:
result = tool.invoke(input={})
except Exception as e:
self.on_tool_error(tool=tool, tool_calling=calling, e=e)
self._run_attempts += 1
if self._run_attempts > self._max_parsing_attempts:
self._telemetry.tool_usage_error(llm=self.function_calling_llm)
error_message = self._i18n.errors("tool_usage_exception").format(
error=e, tool=tool.name, tool_inputs=tool.description
)
error = ToolUsageErrorException(
f'\n{error_message}.\nMoving on then. {self._i18n.slice("format").format(tool_names=self.tools_names)}'
).message
self.task.increment_tools_errors()
if self.agent.verbose:
self._printer.print(
content=f"\n\n{error_message}\n", color="red"
)
return error # type: ignore # No return value expected
self.task.increment_tools_errors()
if agentops:
agentops.record(
agentops.ErrorEvent(exception=e, trigger_event=tool_event)
)
return self.use(calling=calling, tool_string=tool_string) # type: ignore # No return value expected
if self.tools_handler:
should_cache = True
if (
hasattr(original_tool, "cache_function")
and original_tool.cache_function # type: ignore # Item "None" of "Any | None" has no attribute "cache_function"
):
should_cache = original_tool.cache_function( # type: ignore # Item "None" of "Any | None" has no attribute "cache_function"
calling.arguments, result
)
self.tools_handler.on_tool_use(
calling=calling, output=result, should_cache=should_cache
)
if agentops:
agentops.record(tool_event)
self._telemetry.tool_usage(
llm=self.function_calling_llm,
tool_name=tool.name,
attempts=self._run_attempts,
)
result = self._format_result(result=result) # type: ignore # "_format_result" of "ToolUsage" does not return a value (it only ever returns None)
data = {
"result": result,
"tool_name": tool.name,
"tool_args": calling.arguments,
}
self.on_tool_use_finished(
tool=tool,
tool_calling=calling,
from_cache=from_cache,
started_at=started_at,
)
if (
hasattr(original_tool, "result_as_answer")
and original_tool.result_as_answer # type: ignore # Item "None" of "Any | None" has no attribute "cache_function"
):
result_as_answer = original_tool.result_as_answer # type: ignore # Item "None" of "Any | None" has no attribute "result_as_answer"
data["result_as_answer"] = result_as_answer
self.agent.tools_results.append(data)
return result # type: ignore # No return value expected
def _format_result(self, result: Any) -> None:
self.task.used_tools += 1
if self._should_remember_format(): # type: ignore # "_should_remember_format" of "ToolUsage" does not return a value (it only ever returns None)
result = self._remember_format(result=result) # type: ignore # "_remember_format" of "ToolUsage" does not return a value (it only ever returns None)
return result
def _should_remember_format(self) -> bool:
return self.task.used_tools % self._remember_format_after_usages == 0
def _remember_format(self, result: str) -> None:
result = str(result)
result += "\n\n" + self._i18n.slice("tools").format(
tools=self.tools_description, tool_names=self.tools_names
)
return result # type: ignore # No return value expected
def _check_tool_repeated_usage(
self, calling: Union[ToolCalling, InstructorToolCalling]
) -> None:
if not self.tools_handler:
return False # type: ignore # No return value expected
if last_tool_usage := self.tools_handler.last_used_tool:
return (calling.tool_name == last_tool_usage.tool_name) and ( # type: ignore # No return value expected
calling.arguments == last_tool_usage.arguments
)
def _select_tool(self, tool_name: str) -> Any:
order_tools = sorted(
self.tools,
key=lambda tool: SequenceMatcher(
None, tool.name.lower().strip(), tool_name.lower().strip()
).ratio(),
reverse=True,
)
for tool in order_tools:
if (
tool.name.lower().strip() == tool_name.lower().strip()
or SequenceMatcher(
None, tool.name.lower().strip(), tool_name.lower().strip()
).ratio()
> 0.85
):
return tool
self.task.increment_tools_errors()
if tool_name and tool_name != "":
raise Exception(
f"Action '{tool_name}' don't exist, these are the only available Actions:\n{self.tools_description}"
)
else:
raise Exception(
f"I forgot the Action name, these are the only available Actions: {self.tools_description}"
)
def _render(self) -> str:
"""Render the tool name and description in plain text."""
descriptions = []
for tool in self.tools:
descriptions.append(tool.description)
return "\n--\n".join(descriptions)
def _function_calling(self, tool_string: str):
model = (
InstructorToolCalling
if self.function_calling_llm.supports_function_calling()
else ToolCalling
)
converter = Converter(
text=f"Only tools available:\n###\n{self._render()}\n\nReturn a valid schema for the tool, the tool name must be exactly equal one of the options, use this text to inform the valid output schema:\n\n### TEXT \n{tool_string}",
llm=self.function_calling_llm,
model=model,
instructions=dedent(
"""\
The schema should have the following structure, only two keys:
- tool_name: str
- arguments: dict (always a dictionary, with all arguments being passed)
Example:
{"tool_name": "tool name", "arguments": {"arg_name1": "value", "arg_name2": 2}}""",
),
max_attempts=1,
)
tool_object = converter.to_pydantic()
calling = ToolCalling(
tool_name=tool_object["tool_name"],
arguments=tool_object["arguments"],
log=tool_string, # type: ignore
)
if isinstance(calling, ConverterError):
raise calling
return calling
def _original_tool_calling(self, tool_string: str, raise_error: bool = False):
tool_name = self.action.tool
tool = self._select_tool(tool_name)
try:
arguments = self._validate_tool_input(self.action.tool_input)
except Exception:
if raise_error:
raise
else:
return ToolUsageErrorException(
f'{self._i18n.errors("tool_arguments_error")}'
)
if not isinstance(arguments, dict):
if raise_error:
raise
else:
return ToolUsageErrorException(
f'{self._i18n.errors("tool_arguments_error")}'
)
return ToolCalling(
tool_name=tool.name,
arguments=arguments,
log=tool_string,
)
def _tool_calling(
self, tool_string: str
) -> Union[ToolCalling, InstructorToolCalling]:
try:
try:
return self._original_tool_calling(tool_string, raise_error=True)
except Exception:
if self.function_calling_llm:
return self._function_calling(tool_string)
else:
return self._original_tool_calling(tool_string)
except Exception as e:
self._run_attempts += 1
if self._run_attempts > self._max_parsing_attempts:
self._telemetry.tool_usage_error(llm=self.function_calling_llm)
self.task.increment_tools_errors()
if self.agent.verbose:
self._printer.print(content=f"\n\n{e}\n", color="red")
return ToolUsageErrorException( # type: ignore # Incompatible return value type (got "ToolUsageErrorException", expected "ToolCalling | InstructorToolCalling")
f'{self._i18n.errors("tool_usage_error").format(error=e)}\nMoving on then. {self._i18n.slice("format").format(tool_names=self.tools_names)}'
)
return self._tool_calling(tool_string)
def _validate_tool_input(self, tool_input: str) -> Dict[str, Any]:
try:
# Replace Python literals with JSON equivalents
replacements = {
r"'": '"',
r"None": "null",
r"True": "true",
r"False": "false",
}
for pattern, replacement in replacements.items():
tool_input = re.sub(pattern, replacement, tool_input)
arguments = json.loads(tool_input)
except json.JSONDecodeError:
# Attempt to repair JSON string
repaired_input = repair_json(tool_input)
try:
arguments = json.loads(repaired_input)
except json.JSONDecodeError as e:
raise Exception(f"Invalid tool input JSON: {e}")
return arguments
def on_tool_error(self, tool: Any, tool_calling: ToolCalling, e: Exception) -> None:
event_data = self._prepare_event_data(tool, tool_calling)
events.emit(
source=self, event=ToolUsageError(**{**event_data, "error": str(e)})
)
def on_tool_use_finished(
self, tool: Any, tool_calling: ToolCalling, from_cache: bool, started_at: float
) -> None:
finished_at = time.time()
event_data = self._prepare_event_data(tool, tool_calling)
event_data.update(
{
"started_at": datetime.datetime.fromtimestamp(started_at),
"finished_at": datetime.datetime.fromtimestamp(finished_at),
"from_cache": from_cache,
}
)
events.emit(source=self, event=ToolUsageFinished(**event_data))
def _prepare_event_data(self, tool: Any, tool_calling: ToolCalling) -> dict:
return {
"agent_key": self.agent.key,
"agent_role": (self.agent._original_role or self.agent.role),
"run_attempts": self._run_attempts,
"delegations": self.task.delegations,
"tool_name": tool.name,
"tool_args": tool_calling.arguments,
"tool_class": tool.__class__.__name__,
}