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Enhance event handling for tool usage and agent execution
- Add new events for tool usage: ToolSelectionErrorEvent, ToolValidateInputErrorEvent - Improve error tracking and event emission in ToolUsage and LLM classes - Update AgentExecutionStartedEvent to use task_prompt instead of inputs - Add comprehensive test coverage for new event types and error scenarios
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@@ -7,7 +7,8 @@ from pydantic import BaseModel
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from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
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from crewai.llm import LLM
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from crewai.tools import tool
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from crewai.utilities.events import crewai_event_bus
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from crewai.utilities.events.tool_usage_events import ToolExecutionErrorEvent
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from crewai.utilities.token_counter_callback import TokenCalcHandler
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@@ -291,32 +292,36 @@ def anthropic_llm():
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"""Fixture providing an Anthropic LLM instance."""
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return LLM(model="anthropic/claude-3-sonnet")
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@pytest.fixture
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def system_message():
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"""Fixture providing a system message."""
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return {"role": "system", "content": "test"}
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@pytest.fixture
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def user_message():
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"""Fixture providing a user message."""
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return {"role": "user", "content": "test"}
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def test_anthropic_message_formatting_edge_cases(anthropic_llm):
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"""Test edge cases for Anthropic message formatting."""
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# Test None messages
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with pytest.raises(TypeError, match="Messages cannot be None"):
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anthropic_llm._format_messages_for_provider(None)
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# Test empty message list
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formatted = anthropic_llm._format_messages_for_provider([])
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assert len(formatted) == 1
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assert formatted[0]["role"] == "user"
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assert formatted[0]["content"] == "."
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# Test invalid message format
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with pytest.raises(TypeError, match="Invalid message format"):
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anthropic_llm._format_messages_for_provider([{"invalid": "message"}])
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def test_anthropic_model_detection():
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"""Test Anthropic model detection with various formats."""
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models = [
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@@ -327,11 +332,12 @@ def test_anthropic_model_detection():
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("", False),
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("anthropomorphic", False), # Should not match partial words
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]
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for model, expected in models:
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llm = LLM(model=model)
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assert llm.is_anthropic == expected, f"Failed for model: {model}"
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def test_anthropic_message_formatting(anthropic_llm, system_message, user_message):
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"""Test Anthropic message formatting with fixtures."""
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# Test when first message is system
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@@ -371,3 +377,51 @@ def test_deepseek_r1_with_open_router():
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result = llm.call("What is the capital of France?")
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assert isinstance(result, str)
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assert "Paris" in result
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@pytest.mark.vcr(filter_headers=["authorization"])
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def test_tool_execution_error_event():
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llm = LLM(model="gpt-4o-mini")
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def failing_tool(param: str) -> str:
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"""This tool always fails."""
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raise Exception("Tool execution failed!")
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tool_schema = {
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"type": "function",
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"function": {
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"name": "failing_tool",
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"description": "This tool always fails.",
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"parameters": {
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"type": "object",
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"properties": {
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"param": {"type": "string", "description": "A test parameter"}
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},
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"required": ["param"],
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},
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},
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}
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received_events = []
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@crewai_event_bus.on(ToolExecutionErrorEvent)
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def event_handler(source, event):
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received_events.append(event)
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available_functions = {"failing_tool": failing_tool}
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messages = [{"role": "user", "content": "Use the failing tool"}]
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llm.call(
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messages,
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tools=[tool_schema],
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available_functions=available_functions,
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)
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assert len(received_events) == 1
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event = received_events[0]
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assert isinstance(event, ToolExecutionErrorEvent)
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assert event.tool_name == "failing_tool"
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assert event.tool_args == {"param": "test"}
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assert event.tool_class == failing_tool
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assert "Tool execution failed!" in event.error
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