feat: log usage tools when called by LLM (#2916)
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* feat: log usage tools when called by LLM

* feat: print llm tool usage in console
This commit is contained in:
Lucas Gomide
2025-05-29 15:34:34 -03:00
committed by GitHub
parent e676c83d7f
commit 55ed91e313
7 changed files with 363 additions and 21 deletions

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@@ -5,7 +5,7 @@ import sys
import threading
import warnings
from collections import defaultdict
from contextlib import contextmanager, redirect_stderr, redirect_stdout
from contextlib import contextmanager
from typing import (
Any,
DefaultDict,
@@ -18,7 +18,7 @@ from typing import (
Union,
cast,
)
from datetime import datetime
from dotenv import load_dotenv
from litellm.types.utils import ChatCompletionDeltaToolCall
from pydantic import BaseModel, Field
@@ -30,6 +30,11 @@ from crewai.utilities.events.llm_events import (
LLMCallType,
LLMStreamChunkEvent,
)
from crewai.utilities.events.tool_usage_events import (
ToolUsageStartedEvent,
ToolUsageFinishedEvent,
ToolUsageErrorEvent,
)
with warnings.catch_warnings():
warnings.simplefilter("ignore", UserWarning)
@@ -833,7 +838,26 @@ class LLM(BaseLLM):
fn = available_functions[function_name]
# --- 3.2) Execute function
assert hasattr(crewai_event_bus, "emit")
started_at = datetime.now()
crewai_event_bus.emit(
self,
event=ToolUsageStartedEvent(
tool_name=function_name,
tool_args=function_args,
),
)
result = fn(**function_args)
crewai_event_bus.emit(
self,
event=ToolUsageFinishedEvent(
output=result,
tool_name=function_name,
tool_args=function_args,
started_at=started_at,
finished_at=datetime.now(),
),
)
# --- 3.3) Emit success event
self._handle_emit_call_events(result, LLMCallType.TOOL_CALL)
@@ -849,6 +873,14 @@ class LLM(BaseLLM):
self,
event=LLMCallFailedEvent(error=f"Tool execution error: {str(e)}"),
)
crewai_event_bus.emit(
self,
event=ToolUsageErrorEvent(
tool_name=function_name,
tool_args=function_args,
error=f"Tool execution error: {str(e)}"
),
)
return None
def call(

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@@ -2,7 +2,7 @@ from io import StringIO
from typing import Any, Dict
from pydantic import Field, PrivateAttr
from crewai.llm import LLM
from crewai.task import Task
from crewai.telemetry.telemetry import Telemetry
from crewai.utilities import Logger
@@ -283,27 +283,43 @@ class EventListener(BaseEventListener):
@crewai_event_bus.on(ToolUsageStartedEvent)
def on_tool_usage_started(source, event: ToolUsageStartedEvent):
self.formatter.handle_tool_usage_started(
self.formatter.current_agent_branch,
event.tool_name,
if isinstance(source, LLM):
self.formatter.handle_llm_tool_usage_started(
event.tool_name,
)
else:
self.formatter.handle_tool_usage_started(
self.formatter.current_agent_branch,
event.tool_name,
self.formatter.current_crew_tree,
)
@crewai_event_bus.on(ToolUsageFinishedEvent)
def on_tool_usage_finished(source, event: ToolUsageFinishedEvent):
self.formatter.handle_tool_usage_finished(
self.formatter.current_tool_branch,
event.tool_name,
self.formatter.current_crew_tree,
)
if isinstance(source, LLM):
self.formatter.handle_llm_tool_usage_finished(
event.tool_name,
)
else:
self.formatter.handle_tool_usage_finished(
self.formatter.current_tool_branch,
event.tool_name,
self.formatter.current_crew_tree,
)
@crewai_event_bus.on(ToolUsageErrorEvent)
def on_tool_usage_error(source, event: ToolUsageErrorEvent):
self.formatter.handle_tool_usage_error(
self.formatter.current_tool_branch,
event.tool_name,
event.error,
self.formatter.current_crew_tree,
if isinstance(source, LLM):
self.formatter.handle_llm_tool_usage_error(
event.tool_name,
event.error,
)
else:
self.formatter.handle_tool_usage_error(
self.formatter.current_tool_branch,
event.tool_name,
event.error,
self.formatter.current_crew_tree,
)
# ----------- LLM EVENTS -----------

View File

@@ -7,11 +7,11 @@ from .base_events import BaseEvent
class ToolUsageEvent(BaseEvent):
"""Base event for tool usage tracking"""
agent_key: str
agent_role: str
agent_key: Optional[str] = None
agent_role: Optional[str] = None
tool_name: str
tool_args: Dict[str, Any] | str
tool_class: str
tool_class: Optional[str] = None
run_attempts: int | None = None
delegations: int | None = None
agent: Optional[Any] = None

View File

@@ -17,6 +17,7 @@ class ConsoleFormatter:
current_lite_agent_branch: Optional[Tree] = None
tool_usage_counts: Dict[str, int] = {}
current_reasoning_branch: Optional[Tree] = None # Track reasoning status
current_llm_tool_tree: Optional[Tree] = None
def __init__(self, verbose: bool = False):
self.console = Console(width=None)
@@ -426,6 +427,51 @@ class ConsoleFormatter:
self.print()
return method_branch
def get_llm_tree(self, tool_name: str):
text = Text()
text.append(f"🔧 Using {tool_name} from LLM available_function", style="yellow")
tree = self.current_flow_tree or self.current_crew_tree
if tree:
tree.add(text)
return tree or Tree(text)
def handle_llm_tool_usage_started(
self,
tool_name: str,
):
tree = self.get_llm_tree(tool_name)
self.add_tree_node(tree, "🔄 Tool Usage Started", "green")
self.print(tree)
self.print()
return tree
def handle_llm_tool_usage_finished(
self,
tool_name: str,
):
tree = self.get_llm_tree(tool_name)
self.add_tree_node(tree, "✅ Tool Usage Completed", "green")
self.print(tree)
self.print()
def handle_llm_tool_usage_error(
self,
tool_name: str,
error: str,
):
tree = self.get_llm_tree(tool_name)
self.add_tree_node(tree, "❌ Tool Usage Failed", "red")
self.print(tree)
self.print()
error_content = self.create_status_content(
"Tool Usage Failed", tool_name, "red", Error=error
)
self.print_panel(error_content, "Tool Error", "red")
def handle_tool_usage_started(
self,
agent_branch: Optional[Tree],

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@@ -2,7 +2,6 @@ import os
from time import sleep
from unittest.mock import MagicMock, patch
import litellm
import pytest
from pydantic import BaseModel
@@ -11,7 +10,11 @@ from crewai.llm import CONTEXT_WINDOW_USAGE_RATIO, LLM
from crewai.utilities.events import (
LLMCallCompletedEvent,
LLMStreamChunkEvent,
ToolUsageStartedEvent,
ToolUsageFinishedEvent,
ToolUsageErrorEvent,
)
from crewai.utilities.token_counter_callback import TokenCalcHandler
@@ -222,7 +225,7 @@ def test_get_custom_llm_provider_gemini():
def test_get_custom_llm_provider_openai():
llm = LLM(model="gpt-4")
assert llm._get_custom_llm_provider() == None
assert llm._get_custom_llm_provider() is None
def test_validate_call_params_supported():
@@ -511,12 +514,18 @@ def assert_event_count(
expected_completed_tool_call: int = 0,
expected_stream_chunk: int = 0,
expected_completed_llm_call: int = 0,
expected_tool_usage_started: int = 0,
expected_tool_usage_finished: int = 0,
expected_tool_usage_error: int = 0,
expected_final_chunk_result: str = "",
):
event_count = {
"completed_tool_call": 0,
"stream_chunk": 0,
"completed_llm_call": 0,
"tool_usage_started": 0,
"tool_usage_finished": 0,
"tool_usage_error": 0,
}
final_chunk_result = ""
for _call in mock_emit.call_args_list:
@@ -535,12 +544,21 @@ def assert_event_count(
and event.call_type.value == "llm_call"
):
event_count["completed_llm_call"] += 1
elif isinstance(event, ToolUsageStartedEvent):
event_count["tool_usage_started"] += 1
elif isinstance(event, ToolUsageFinishedEvent):
event_count["tool_usage_finished"] += 1
elif isinstance(event, ToolUsageErrorEvent):
event_count["tool_usage_error"] += 1
else:
continue
assert event_count["completed_tool_call"] == expected_completed_tool_call
assert event_count["stream_chunk"] == expected_stream_chunk
assert event_count["completed_llm_call"] == expected_completed_llm_call
assert event_count["tool_usage_started"] == expected_tool_usage_started
assert event_count["tool_usage_finished"] == expected_tool_usage_finished
assert event_count["tool_usage_error"] == expected_tool_usage_error
assert final_chunk_result == expected_final_chunk_result
@@ -574,6 +592,34 @@ def test_handle_streaming_tool_calls(get_weather_tool_schema, mock_emit):
expected_completed_tool_call=1,
expected_stream_chunk=10,
expected_completed_llm_call=1,
expected_tool_usage_started=1,
expected_tool_usage_finished=1,
expected_final_chunk_result=expected_final_chunk_result,
)
@pytest.mark.vcr(filter_headers=["authorization"])
def test_handle_streaming_tool_calls_with_error(get_weather_tool_schema, mock_emit):
def get_weather_error(location):
raise Exception("Error")
llm = LLM(model="openai/gpt-4o", stream=True)
response = llm.call(
messages=[
{"role": "user", "content": "What is the weather in New York?"},
],
tools=[get_weather_tool_schema],
available_functions={
"get_weather": get_weather_error
},
)
assert response == ""
expected_final_chunk_result = '{"location":"New York, NY"}'
assert_event_count(
mock_emit=mock_emit,
expected_stream_chunk=9,
expected_completed_llm_call=1,
expected_tool_usage_started=1,
expected_tool_usage_error=1,
expected_final_chunk_result=expected_final_chunk_result,
)