d4c7a23e1d
### Summary: Towards #767. We were caching the list of tools for an agent, so if you did `agent.tools.append(...)` from a tool call, the next call to the model wouldn't include the new tool. THis is a bug. ### Test Plan: Unit tests. Note that now MCP tools are listed each time the agent runs (users can still cache the `list_tools` however).
782 lines
23 KiB
Python
782 lines
23 KiB
Python
from __future__ import annotations
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import json
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from typing import Any
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import pytest
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from typing_extensions import TypedDict
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from agents import (
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Agent,
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GuardrailFunctionOutput,
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Handoff,
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HandoffInputData,
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InputGuardrail,
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InputGuardrailTripwireTriggered,
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ModelBehaviorError,
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ModelSettings,
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OutputGuardrail,
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OutputGuardrailTripwireTriggered,
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RunConfig,
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RunContextWrapper,
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Runner,
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UserError,
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handoff,
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)
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from agents.agent import ToolsToFinalOutputResult
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from agents.tool import FunctionToolResult, function_tool
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from .fake_model import FakeModel
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from .test_responses import (
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get_final_output_message,
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get_function_tool,
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get_function_tool_call,
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get_handoff_tool_call,
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get_text_input_item,
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get_text_message,
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)
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@pytest.mark.asyncio
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async def test_simple_first_run():
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model = FakeModel()
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agent = Agent(
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name="test",
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model=model,
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)
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model.set_next_output([get_text_message("first")])
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result = await Runner.run(agent, input="test")
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assert result.input == "test"
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assert len(result.new_items) == 1, "exactly one item should be generated"
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assert result.final_output == "first"
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assert len(result.raw_responses) == 1, "exactly one model response should be generated"
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assert result.raw_responses[0].output == [get_text_message("first")]
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assert result.last_agent == agent
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assert len(result.to_input_list()) == 2, "should have original input and generated item"
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model.set_next_output([get_text_message("second")])
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result = await Runner.run(
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agent, input=[get_text_input_item("message"), get_text_input_item("another_message")]
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)
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assert len(result.new_items) == 1, "exactly one item should be generated"
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assert result.final_output == "second"
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assert len(result.raw_responses) == 1, "exactly one model response should be generated"
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assert len(result.to_input_list()) == 3, "should have original input and generated item"
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@pytest.mark.asyncio
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async def test_subsequent_runs():
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model = FakeModel()
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agent = Agent(
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name="test",
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model=model,
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)
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model.set_next_output([get_text_message("third")])
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result = await Runner.run(agent, input="test")
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assert result.input == "test"
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assert len(result.new_items) == 1, "exactly one item should be generated"
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assert len(result.to_input_list()) == 2, "should have original input and generated item"
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model.set_next_output([get_text_message("fourth")])
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result = await Runner.run(agent, input=result.to_input_list())
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assert len(result.input) == 2, f"should have previous input but got {result.input}"
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assert len(result.new_items) == 1, "exactly one item should be generated"
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assert result.final_output == "fourth"
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assert len(result.raw_responses) == 1, "exactly one model response should be generated"
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assert result.raw_responses[0].output == [get_text_message("fourth")]
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assert result.last_agent == agent
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assert len(result.to_input_list()) == 3, "should have original input and generated items"
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@pytest.mark.asyncio
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async def test_tool_call_runs():
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model = FakeModel()
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agent = Agent(
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name="test",
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model=model,
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tools=[get_function_tool("foo", "tool_result")],
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)
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model.add_multiple_turn_outputs(
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[
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# First turn: a message and tool call
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[get_text_message("a_message"), get_function_tool_call("foo", json.dumps({"a": "b"}))],
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# Second turn: text message
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[get_text_message("done")],
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]
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)
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result = await Runner.run(agent, input="user_message")
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assert result.final_output == "done"
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assert len(result.raw_responses) == 2, (
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"should have two responses: the first which produces a tool call, and the second which"
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"handles the tool result"
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)
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assert len(result.to_input_list()) == 5, (
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"should have five inputs: the original input, the message, the tool call, the tool result "
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"and the done message"
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)
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@pytest.mark.asyncio
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async def test_handoffs():
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model = FakeModel()
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agent_1 = Agent(
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name="test",
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model=model,
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)
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agent_2 = Agent(
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name="test",
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model=model,
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)
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agent_3 = Agent(
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name="test",
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model=model,
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handoffs=[agent_1, agent_2],
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tools=[get_function_tool("some_function", "result")],
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)
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model.add_multiple_turn_outputs(
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[
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# First turn: a tool call
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[get_function_tool_call("some_function", json.dumps({"a": "b"}))],
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# Second turn: a message and a handoff
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[get_text_message("a_message"), get_handoff_tool_call(agent_1)],
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# Third turn: text message
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[get_text_message("done")],
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]
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)
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result = await Runner.run(agent_3, input="user_message")
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assert result.final_output == "done"
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assert len(result.raw_responses) == 3, "should have three model responses"
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assert len(result.to_input_list()) == 7, (
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"should have 7 inputs: orig input, tool call, tool result, message, handoff, handoff"
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"result, and done message"
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)
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assert result.last_agent == agent_1, "should have handed off to agent_1"
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class Foo(TypedDict):
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bar: str
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@pytest.mark.asyncio
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async def test_structured_output():
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model = FakeModel()
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agent_1 = Agent(
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name="test",
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model=model,
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tools=[get_function_tool("bar", "bar_result")],
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output_type=Foo,
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)
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agent_2 = Agent(
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name="test",
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model=model,
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tools=[get_function_tool("foo", "foo_result")],
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handoffs=[agent_1],
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)
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model.add_multiple_turn_outputs(
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[
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# First turn: a tool call
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[get_function_tool_call("foo", json.dumps({"bar": "baz"}))],
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# Second turn: a message and a handoff
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[get_text_message("a_message"), get_handoff_tool_call(agent_1)],
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# Third turn: tool call and structured output
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[
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get_function_tool_call("bar", json.dumps({"bar": "baz"})),
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get_final_output_message(json.dumps(Foo(bar="baz"))),
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],
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]
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)
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result = await Runner.run(
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agent_2,
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input=[
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get_text_input_item("user_message"),
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get_text_input_item("another_message"),
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],
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)
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assert result.final_output == Foo(bar="baz")
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assert len(result.raw_responses) == 3, "should have three model responses"
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assert len(result.to_input_list()) == 10, (
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"should have input: 2 orig inputs, function call, function call result, message, handoff, "
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"handoff output, tool call, tool call result, final output message"
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)
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assert result.last_agent == agent_1, "should have handed off to agent_1"
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assert result.final_output == Foo(bar="baz"), "should have structured output"
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def remove_new_items(handoff_input_data: HandoffInputData) -> HandoffInputData:
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return HandoffInputData(
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input_history=handoff_input_data.input_history,
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pre_handoff_items=(),
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new_items=(),
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)
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@pytest.mark.asyncio
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async def test_handoff_filters():
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model = FakeModel()
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agent_1 = Agent(
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name="test",
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model=model,
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)
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agent_2 = Agent(
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name="test",
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model=model,
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handoffs=[
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handoff(
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agent=agent_1,
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input_filter=remove_new_items,
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)
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],
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)
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model.add_multiple_turn_outputs(
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[
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[get_text_message("1"), get_text_message("2"), get_handoff_tool_call(agent_1)],
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[get_text_message("last")],
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]
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)
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result = await Runner.run(agent_2, input="user_message")
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assert result.final_output == "last"
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assert len(result.raw_responses) == 2, "should have two model responses"
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assert len(result.to_input_list()) == 2, (
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"should only have 2 inputs: orig input and last message"
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)
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@pytest.mark.asyncio
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async def test_async_input_filter_fails():
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# DO NOT rename this without updating pyproject.toml
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model = FakeModel()
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agent_1 = Agent(
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name="test",
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model=model,
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)
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async def on_invoke_handoff(_ctx: RunContextWrapper[Any], _input: str) -> Agent[Any]:
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return agent_1
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async def invalid_input_filter(data: HandoffInputData) -> HandoffInputData:
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return data # pragma: no cover
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agent_2 = Agent[None](
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name="test",
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model=model,
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handoffs=[
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Handoff(
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tool_name=Handoff.default_tool_name(agent_1),
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tool_description=Handoff.default_tool_description(agent_1),
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input_json_schema={},
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on_invoke_handoff=on_invoke_handoff,
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agent_name=agent_1.name,
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# Purposely ignoring the type error here to simulate invalid input
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input_filter=invalid_input_filter, # type: ignore
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)
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],
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)
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model.add_multiple_turn_outputs(
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[
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[get_text_message("1"), get_text_message("2"), get_handoff_tool_call(agent_1)],
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[get_text_message("last")],
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]
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)
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with pytest.raises(UserError):
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await Runner.run(agent_2, input="user_message")
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@pytest.mark.asyncio
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async def test_invalid_input_filter_fails():
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model = FakeModel()
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agent_1 = Agent(
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name="test",
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model=model,
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)
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async def on_invoke_handoff(_ctx: RunContextWrapper[Any], _input: str) -> Agent[Any]:
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return agent_1
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def invalid_input_filter(data: HandoffInputData) -> HandoffInputData:
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# Purposely returning a string to simulate invalid output
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return "foo" # type: ignore
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agent_2 = Agent[None](
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name="test",
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model=model,
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handoffs=[
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Handoff(
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tool_name=Handoff.default_tool_name(agent_1),
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tool_description=Handoff.default_tool_description(agent_1),
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input_json_schema={},
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on_invoke_handoff=on_invoke_handoff,
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agent_name=agent_1.name,
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input_filter=invalid_input_filter,
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)
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],
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)
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model.add_multiple_turn_outputs(
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[
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[get_text_message("1"), get_text_message("2"), get_handoff_tool_call(agent_1)],
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[get_text_message("last")],
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]
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)
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with pytest.raises(UserError):
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await Runner.run(agent_2, input="user_message")
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@pytest.mark.asyncio
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async def test_non_callable_input_filter_causes_error():
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model = FakeModel()
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agent_1 = Agent(
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name="test",
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model=model,
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)
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async def on_invoke_handoff(_ctx: RunContextWrapper[Any], _input: str) -> Agent[Any]:
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return agent_1
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agent_2 = Agent[None](
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name="test",
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model=model,
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handoffs=[
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Handoff(
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tool_name=Handoff.default_tool_name(agent_1),
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tool_description=Handoff.default_tool_description(agent_1),
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input_json_schema={},
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on_invoke_handoff=on_invoke_handoff,
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agent_name=agent_1.name,
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# Purposely ignoring the type error here to simulate invalid input
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input_filter="foo", # type: ignore
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)
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],
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)
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model.add_multiple_turn_outputs(
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[
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[get_text_message("1"), get_text_message("2"), get_handoff_tool_call(agent_1)],
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[get_text_message("last")],
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]
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)
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with pytest.raises(UserError):
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await Runner.run(agent_2, input="user_message")
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@pytest.mark.asyncio
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async def test_handoff_on_input():
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call_output: str | None = None
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def on_input(_ctx: RunContextWrapper[Any], data: Foo) -> None:
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nonlocal call_output
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call_output = data["bar"]
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model = FakeModel()
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agent_1 = Agent(
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name="test",
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model=model,
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)
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agent_2 = Agent(
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name="test",
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model=model,
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handoffs=[
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handoff(
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agent=agent_1,
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on_handoff=on_input,
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input_type=Foo,
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)
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],
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)
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model.add_multiple_turn_outputs(
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[
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[
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get_text_message("1"),
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get_text_message("2"),
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get_handoff_tool_call(agent_1, args=json.dumps(Foo(bar="test_input"))),
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],
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[get_text_message("last")],
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]
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)
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result = await Runner.run(agent_2, input="user_message")
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assert result.final_output == "last"
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assert call_output == "test_input", "should have called the handoff with the correct input"
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@pytest.mark.asyncio
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async def test_async_handoff_on_input():
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call_output: str | None = None
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async def on_input(_ctx: RunContextWrapper[Any], data: Foo) -> None:
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nonlocal call_output
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call_output = data["bar"]
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model = FakeModel()
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agent_1 = Agent(
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name="test",
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model=model,
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)
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agent_2 = Agent(
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name="test",
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model=model,
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handoffs=[
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handoff(
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agent=agent_1,
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on_handoff=on_input,
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input_type=Foo,
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)
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],
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)
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model.add_multiple_turn_outputs(
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[
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[
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get_text_message("1"),
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get_text_message("2"),
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get_handoff_tool_call(agent_1, args=json.dumps(Foo(bar="test_input"))),
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],
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[get_text_message("last")],
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]
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)
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result = await Runner.run(agent_2, input="user_message")
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assert result.final_output == "last"
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assert call_output == "test_input", "should have called the handoff with the correct input"
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@pytest.mark.asyncio
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async def test_wrong_params_on_input_causes_error():
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agent_1 = Agent(
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name="test",
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)
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def _on_handoff_too_many_params(ctx: RunContextWrapper[Any], foo: Foo, bar: str) -> None:
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pass
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with pytest.raises(UserError):
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handoff(
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agent_1,
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input_type=Foo,
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# Purposely ignoring the type error here to simulate invalid input
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on_handoff=_on_handoff_too_many_params, # type: ignore
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)
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def on_handoff_too_few_params(ctx: RunContextWrapper[Any]) -> None:
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pass
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with pytest.raises(UserError):
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handoff(
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agent_1,
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input_type=Foo,
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# Purposely ignoring the type error here to simulate invalid input
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on_handoff=on_handoff_too_few_params, # type: ignore
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)
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@pytest.mark.asyncio
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async def test_invalid_handoff_input_json_causes_error():
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agent = Agent(name="test")
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h = handoff(agent, input_type=Foo, on_handoff=lambda _ctx, _input: None)
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with pytest.raises(ModelBehaviorError):
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await h.on_invoke_handoff(
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RunContextWrapper(None),
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# Purposely ignoring the type error here to simulate invalid input
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None, # type: ignore
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)
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with pytest.raises(ModelBehaviorError):
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await h.on_invoke_handoff(RunContextWrapper(None), "invalid")
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@pytest.mark.asyncio
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async def test_input_guardrail_tripwire_triggered_causes_exception():
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def guardrail_function(
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context: RunContextWrapper[Any], agent: Agent[Any], input: Any
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) -> GuardrailFunctionOutput:
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return GuardrailFunctionOutput(
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output_info=None,
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tripwire_triggered=True,
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)
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agent = Agent(
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name="test", input_guardrails=[InputGuardrail(guardrail_function=guardrail_function)]
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)
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model = FakeModel()
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model.set_next_output([get_text_message("user_message")])
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with pytest.raises(InputGuardrailTripwireTriggered):
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await Runner.run(agent, input="user_message")
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|
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@pytest.mark.asyncio
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async def test_output_guardrail_tripwire_triggered_causes_exception():
|
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def guardrail_function(
|
|
context: RunContextWrapper[Any], agent: Agent[Any], agent_output: Any
|
|
) -> GuardrailFunctionOutput:
|
|
return GuardrailFunctionOutput(
|
|
output_info=None,
|
|
tripwire_triggered=True,
|
|
)
|
|
|
|
model = FakeModel()
|
|
agent = Agent(
|
|
name="test",
|
|
output_guardrails=[OutputGuardrail(guardrail_function=guardrail_function)],
|
|
model=model,
|
|
)
|
|
model.set_next_output([get_text_message("user_message")])
|
|
|
|
with pytest.raises(OutputGuardrailTripwireTriggered):
|
|
await Runner.run(agent, input="user_message")
|
|
|
|
|
|
@function_tool
|
|
def test_tool_one():
|
|
return Foo(bar="tool_one_result")
|
|
|
|
|
|
@function_tool
|
|
def test_tool_two():
|
|
return "tool_two_result"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_tool_use_behavior_first_output():
|
|
model = FakeModel()
|
|
agent = Agent(
|
|
name="test",
|
|
model=model,
|
|
tools=[get_function_tool("foo", "tool_result"), test_tool_one, test_tool_two],
|
|
tool_use_behavior="stop_on_first_tool",
|
|
output_type=Foo,
|
|
)
|
|
|
|
model.add_multiple_turn_outputs(
|
|
[
|
|
# First turn: a message and tool call
|
|
[
|
|
get_text_message("a_message"),
|
|
get_function_tool_call("test_tool_one", None),
|
|
get_function_tool_call("test_tool_two", None),
|
|
],
|
|
]
|
|
)
|
|
|
|
result = await Runner.run(agent, input="user_message")
|
|
|
|
assert result.final_output == Foo(bar="tool_one_result"), (
|
|
"should have used the first tool result"
|
|
)
|
|
|
|
|
|
def custom_tool_use_behavior(
|
|
context: RunContextWrapper[Any], results: list[FunctionToolResult]
|
|
) -> ToolsToFinalOutputResult:
|
|
if "test_tool_one" in [result.tool.name for result in results]:
|
|
return ToolsToFinalOutputResult(is_final_output=True, final_output="the_final_output")
|
|
else:
|
|
return ToolsToFinalOutputResult(is_final_output=False, final_output=None)
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_tool_use_behavior_custom_function():
|
|
model = FakeModel()
|
|
agent = Agent(
|
|
name="test",
|
|
model=model,
|
|
tools=[get_function_tool("foo", "tool_result"), test_tool_one, test_tool_two],
|
|
tool_use_behavior=custom_tool_use_behavior,
|
|
)
|
|
|
|
model.add_multiple_turn_outputs(
|
|
[
|
|
# First turn: a message and tool call
|
|
[
|
|
get_text_message("a_message"),
|
|
get_function_tool_call("test_tool_two", None),
|
|
],
|
|
# Second turn: a message and tool call
|
|
[
|
|
get_text_message("a_message"),
|
|
get_function_tool_call("test_tool_one", None),
|
|
get_function_tool_call("test_tool_two", None),
|
|
],
|
|
]
|
|
)
|
|
|
|
result = await Runner.run(agent, input="user_message")
|
|
|
|
assert len(result.raw_responses) == 2, "should have two model responses"
|
|
assert result.final_output == "the_final_output", "should have used the custom function"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_model_settings_override():
|
|
model = FakeModel()
|
|
agent = Agent(
|
|
name="test", model=model, model_settings=ModelSettings(temperature=1.0, max_tokens=1000)
|
|
)
|
|
|
|
model.add_multiple_turn_outputs(
|
|
[
|
|
[
|
|
get_text_message("a_message"),
|
|
],
|
|
]
|
|
)
|
|
|
|
await Runner.run(
|
|
agent,
|
|
input="user_message",
|
|
run_config=RunConfig(model_settings=ModelSettings(0.5)),
|
|
)
|
|
|
|
# temperature is overridden by Runner.run, but max_tokens is not
|
|
assert model.last_turn_args["model_settings"].temperature == 0.5
|
|
assert model.last_turn_args["model_settings"].max_tokens == 1000
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_previous_response_id_passed_between_runs():
|
|
"""Test that previous_response_id is passed to the model on subsequent runs."""
|
|
model = FakeModel()
|
|
model.set_next_output([get_text_message("done")])
|
|
agent = Agent(name="test", model=model)
|
|
|
|
assert model.last_turn_args.get("previous_response_id") is None
|
|
await Runner.run(agent, input="test", previous_response_id="resp-non-streamed-test")
|
|
assert model.last_turn_args.get("previous_response_id") == "resp-non-streamed-test"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_multi_turn_previous_response_id_passed_between_runs():
|
|
"""Test that previous_response_id is passed to the model on subsequent runs."""
|
|
|
|
model = FakeModel()
|
|
agent = Agent(
|
|
name="test",
|
|
model=model,
|
|
tools=[get_function_tool("foo", "tool_result")],
|
|
)
|
|
|
|
model.add_multiple_turn_outputs(
|
|
[
|
|
# First turn: a message and tool call
|
|
[get_text_message("a_message"), get_function_tool_call("foo", json.dumps({"a": "b"}))],
|
|
# Second turn: text message
|
|
[get_text_message("done")],
|
|
]
|
|
)
|
|
|
|
assert model.last_turn_args.get("previous_response_id") is None
|
|
await Runner.run(agent, input="test", previous_response_id="resp-test-123")
|
|
assert model.last_turn_args.get("previous_response_id") == "resp-test-123"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_previous_response_id_passed_between_runs_streamed():
|
|
"""Test that previous_response_id is passed to the model on subsequent streamed runs."""
|
|
model = FakeModel()
|
|
model.set_next_output([get_text_message("done")])
|
|
agent = Agent(
|
|
name="test",
|
|
model=model,
|
|
)
|
|
|
|
assert model.last_turn_args.get("previous_response_id") is None
|
|
result = Runner.run_streamed(agent, input="test", previous_response_id="resp-stream-test")
|
|
async for _ in result.stream_events():
|
|
pass
|
|
|
|
assert model.last_turn_args.get("previous_response_id") == "resp-stream-test"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_previous_response_id_passed_between_runs_streamed_multi_turn():
|
|
"""Test that previous_response_id is passed to the model on subsequent streamed runs."""
|
|
|
|
model = FakeModel()
|
|
agent = Agent(
|
|
name="test",
|
|
model=model,
|
|
tools=[get_function_tool("foo", "tool_result")],
|
|
)
|
|
|
|
model.add_multiple_turn_outputs(
|
|
[
|
|
# First turn: a message and tool call
|
|
[get_text_message("a_message"), get_function_tool_call("foo", json.dumps({"a": "b"}))],
|
|
# Second turn: text message
|
|
[get_text_message("done")],
|
|
]
|
|
)
|
|
|
|
assert model.last_turn_args.get("previous_response_id") is None
|
|
result = Runner.run_streamed(agent, input="test", previous_response_id="resp-stream-test")
|
|
async for _ in result.stream_events():
|
|
pass
|
|
|
|
assert model.last_turn_args.get("previous_response_id") == "resp-stream-test"
|
|
|
|
|
|
@pytest.mark.asyncio
|
|
async def test_dynamic_tool_addition_run() -> None:
|
|
"""Test that tools can be added to an agent during a run."""
|
|
model = FakeModel()
|
|
|
|
executed: dict[str, bool] = {"called": False}
|
|
|
|
agent = Agent(name="test", model=model, tool_use_behavior="run_llm_again")
|
|
|
|
@function_tool(name_override="tool2")
|
|
def tool2() -> str:
|
|
executed["called"] = True
|
|
return "result2"
|
|
|
|
@function_tool(name_override="add_tool")
|
|
async def add_tool() -> str:
|
|
agent.tools.append(tool2)
|
|
return "added"
|
|
|
|
agent.tools.append(add_tool)
|
|
|
|
model.add_multiple_turn_outputs(
|
|
[
|
|
[get_function_tool_call("add_tool", json.dumps({}))],
|
|
[get_function_tool_call("tool2", json.dumps({}))],
|
|
[get_text_message("done")],
|
|
]
|
|
)
|
|
|
|
result = await Runner.run(agent, input="start")
|
|
|
|
assert executed["called"] is True
|
|
assert result.final_output == "done"
|