test_tool_choice_reset.py

import pytest

from agents import Agent, ModelSettings, Runner, Tool
from agents._run_impl import RunImpl

from .fake_model import FakeModel
from .test_responses import (
    get_function_tool,
    get_function_tool_call,
    get_text_message,
)


class TestToolChoiceReset:

    def test_should_reset_tool_choice_direct(self):
        """
        Test the _should_reset_tool_choice method directly with various inputs
        to ensure it correctly identifies cases where reset is needed.
        """
        # Case 1: tool_choice = None should not reset
        model_settings = ModelSettings(tool_choice=None)
        tools1: list[Tool] = [get_function_tool("tool1")]
        # Cast to list[Tool] to fix type checking issues
        assert not RunImpl._should_reset_tool_choice(model_settings, tools1)

        # Case 2: tool_choice = "auto" should not reset
        model_settings = ModelSettings(tool_choice="auto")
        assert not RunImpl._should_reset_tool_choice(model_settings, tools1)

        # Case 3: tool_choice = "none" should not reset
        model_settings = ModelSettings(tool_choice="none")
        assert not RunImpl._should_reset_tool_choice(model_settings, tools1)

        # Case 4: tool_choice = "required" with one tool should reset
        model_settings = ModelSettings(tool_choice="required")
        assert RunImpl._should_reset_tool_choice(model_settings, tools1)

        # Case 5: tool_choice = "required" with multiple tools should not reset
        model_settings = ModelSettings(tool_choice="required")
        tools2: list[Tool] = [get_function_tool("tool1"), get_function_tool("tool2")]
        assert not RunImpl._should_reset_tool_choice(model_settings, tools2)

        # Case 6: Specific tool choice should reset
        model_settings = ModelSettings(tool_choice="specific_tool")
        assert RunImpl._should_reset_tool_choice(model_settings, tools1)

    @pytest.mark.asyncio
    async def test_required_tool_choice_with_multiple_runs(self):
        """
        Test scenario 1: When multiple runs are executed with tool_choice="required"
        Ensure each run works correctly and doesn't get stuck in infinite loop
        Also verify that tool_choice remains "required" between runs
        """
        # Set up our fake model with responses for two runs
        fake_model = FakeModel()
        fake_model.add_multiple_turn_outputs([
            [get_text_message("First run response")],
            [get_text_message("Second run response")]
        ])

        # Create agent with a custom tool and tool_choice="required"
        custom_tool = get_function_tool("custom_tool")
        agent = Agent(
            name="test_agent",
            model=fake_model,
            tools=[custom_tool],
            model_settings=ModelSettings(tool_choice="required"),
        )

        # First run should work correctly and preserve tool_choice
        result1 = await Runner.run(agent, "first run")
        assert result1.final_output == "First run response"
        assert agent.model_settings.tool_choice == "required", "tool_choice should stay required"

        # Second run should also work correctly with tool_choice still required
        result2 = await Runner.run(agent, "second run")
        assert result2.final_output == "Second run response"
        assert agent.model_settings.tool_choice == "required", "tool_choice should stay required"

    @pytest.mark.asyncio
    async def test_required_with_stop_at_tool_name(self):
        """
        Test scenario 2: When using required tool_choice with stop_at_tool_names behavior
        Ensure it correctly stops at the specified tool
        """
        # Set up fake model to return a tool call for second_tool
        fake_model = FakeModel()
        fake_model.set_next_output([
            get_function_tool_call("second_tool", "{}")
        ])

        # Create agent with two tools and tool_choice="required" and stop_at_tool behavior
        first_tool = get_function_tool("first_tool", return_value="first tool result")
        second_tool = get_function_tool("second_tool", return_value="second tool result")

        agent = Agent(
            name="test_agent",
            model=fake_model,
            tools=[first_tool, second_tool],
            model_settings=ModelSettings(tool_choice="required"),
            tool_use_behavior={"stop_at_tool_names": ["second_tool"]},
        )

        # Run should stop after using second_tool
        result = await Runner.run(agent, "run test")
        assert result.final_output == "second tool result"

    @pytest.mark.asyncio
    async def test_specific_tool_choice(self):
        """
        Test scenario 3: When using a specific tool choice name
        Ensure it doesn't cause infinite loops
        """
        # Set up fake model to return a text message
        fake_model = FakeModel()
        fake_model.set_next_output([get_text_message("Test message")])

        # Create agent with specific tool_choice
        tool1 = get_function_tool("tool1")
        tool2 = get_function_tool("tool2")
        tool3 = get_function_tool("tool3")

        agent = Agent(
            name="test_agent",
            model=fake_model,
            tools=[tool1, tool2, tool3],
            model_settings=ModelSettings(tool_choice="tool1"),  # Specific tool
        )

        # Run should complete without infinite loops
        result = await Runner.run(agent, "first run")
        assert result.final_output == "Test message"

    @pytest.mark.asyncio
    async def test_required_with_single_tool(self):
        """
        Test scenario 4: When using required tool_choice with only one tool
        Ensure it doesn't cause infinite loops
        """
        # Set up fake model to return a tool call followed by a text message
        fake_model = FakeModel()
        fake_model.add_multiple_turn_outputs([
            # First call returns a tool call
            [get_function_tool_call("custom_tool", "{}")],
            # Second call returns a text message
            [get_text_message("Final response")]
        ])

        # Create agent with a single tool and tool_choice="required"
        custom_tool = get_function_tool("custom_tool", return_value="tool result")
        agent = Agent(
            name="test_agent",
            model=fake_model,
            tools=[custom_tool],
            model_settings=ModelSettings(tool_choice="required"),
        )

        # Run should complete without infinite loops
        result = await Runner.run(agent, "first run")
        assert result.final_output == "Final response"