|
| 1 | +from collections import defaultdict |
| 2 | +from typing import Any, Optional |
| 3 | + |
| 4 | +import pytest |
| 5 | + |
| 6 | +from agents.agent import Agent |
| 7 | +from agents.items import ItemHelpers, ModelResponse, TResponseInputItem |
| 8 | +from agents.lifecycle import RunHooks |
| 9 | +from agents.models.interface import Model |
| 10 | +from agents.run import Runner |
| 11 | +from agents.run_context import RunContextWrapper, TContext |
| 12 | +from agents.tool import Tool |
| 13 | +from tests.test_agent_llm_hooks import AgentHooksForTests |
| 14 | + |
| 15 | +from .fake_model import FakeModel |
| 16 | +from .test_responses import ( |
| 17 | + get_function_tool, |
| 18 | + get_text_message, |
| 19 | +) |
| 20 | + |
| 21 | + |
| 22 | +class RunHooksForTests(RunHooks): |
| 23 | + def __init__(self): |
| 24 | + self.events: dict[str, int] = defaultdict(int) |
| 25 | + |
| 26 | + def reset(self): |
| 27 | + self.events.clear() |
| 28 | + |
| 29 | + async def on_agent_start( |
| 30 | + self, context: RunContextWrapper[TContext], agent: Agent[TContext] |
| 31 | + ) -> None: |
| 32 | + self.events["on_agent_start"] += 1 |
| 33 | + |
| 34 | + async def on_agent_end( |
| 35 | + self, context: RunContextWrapper[TContext], agent: Agent[TContext], output: Any |
| 36 | + ) -> None: |
| 37 | + self.events["on_agent_end"] += 1 |
| 38 | + |
| 39 | + async def on_handoff( |
| 40 | + self, |
| 41 | + context: RunContextWrapper[TContext], |
| 42 | + from_agent: Agent[TContext], |
| 43 | + to_agent: Agent[TContext], |
| 44 | + ) -> None: |
| 45 | + self.events["on_handoff"] += 1 |
| 46 | + |
| 47 | + async def on_tool_start( |
| 48 | + self, context: RunContextWrapper[TContext], agent: Agent[TContext], tool: Tool |
| 49 | + ) -> None: |
| 50 | + self.events["on_tool_start"] += 1 |
| 51 | + |
| 52 | + async def on_tool_end( |
| 53 | + self, |
| 54 | + context: RunContextWrapper[TContext], |
| 55 | + agent: Agent[TContext], |
| 56 | + tool: Tool, |
| 57 | + result: str, |
| 58 | + ) -> None: |
| 59 | + self.events["on_tool_end"] += 1 |
| 60 | + |
| 61 | + async def on_llm_start( |
| 62 | + self, |
| 63 | + context: RunContextWrapper[TContext], |
| 64 | + agent: Agent[TContext], |
| 65 | + system_prompt: Optional[str], |
| 66 | + input_items: list[TResponseInputItem], |
| 67 | + ) -> None: |
| 68 | + self.events["on_llm_start"] += 1 |
| 69 | + |
| 70 | + async def on_llm_end( |
| 71 | + self, |
| 72 | + context: RunContextWrapper[TContext], |
| 73 | + agent: Agent[TContext], |
| 74 | + response: ModelResponse, |
| 75 | + ) -> None: |
| 76 | + self.events["on_llm_end"] += 1 |
| 77 | + |
| 78 | + |
| 79 | +# Example test using the above hooks |
| 80 | +@pytest.mark.asyncio |
| 81 | +async def test_async_run_hooks_with_llm(): |
| 82 | + hooks = RunHooksForTests() |
| 83 | + model = FakeModel() |
| 84 | + |
| 85 | + agent = Agent(name="A", model=model, tools=[get_function_tool("f", "res")], handoffs=[]) |
| 86 | + # Simulate a single LLM call producing an output: |
| 87 | + model.set_next_output([get_text_message("hello")]) |
| 88 | + await Runner.run(agent, input="hello", hooks=hooks) |
| 89 | + # Expect one on_agent_start, one on_llm_start, one on_llm_end, and one on_agent_end |
| 90 | + assert hooks.events == { |
| 91 | + "on_agent_start": 1, |
| 92 | + "on_llm_start": 1, |
| 93 | + "on_llm_end": 1, |
| 94 | + "on_agent_end": 1, |
| 95 | + } |
| 96 | + |
| 97 | + |
| 98 | +# test_sync_run_hook_with_llm() |
| 99 | +def test_sync_run_hook_with_llm(): |
| 100 | + hooks = RunHooksForTests() |
| 101 | + model = FakeModel() |
| 102 | + agent = Agent(name="A", model=model, tools=[get_function_tool("f", "res")], handoffs=[]) |
| 103 | + # Simulate a single LLM call producing an output: |
| 104 | + model.set_next_output([get_text_message("hello")]) |
| 105 | + Runner.run_sync(agent, input="hello", hooks=hooks) |
| 106 | + # Expect one on_agent_start, one on_llm_start, one on_llm_end, and one on_agent_end |
| 107 | + assert hooks.events == { |
| 108 | + "on_agent_start": 1, |
| 109 | + "on_llm_start": 1, |
| 110 | + "on_llm_end": 1, |
| 111 | + "on_agent_end": 1, |
| 112 | + } |
| 113 | + |
| 114 | + |
| 115 | +# test_streamed_run_hooks_with_llm(): |
| 116 | +@pytest.mark.asyncio |
| 117 | +async def test_streamed_run_hooks_with_llm(): |
| 118 | + hooks = RunHooksForTests() |
| 119 | + model = FakeModel() |
| 120 | + agent = Agent(name="A", model=model, tools=[get_function_tool("f", "res")], handoffs=[]) |
| 121 | + # Simulate a single LLM call producing an output: |
| 122 | + model.set_next_output([get_text_message("hello")]) |
| 123 | + stream = Runner.run_streamed(agent, input="hello", hooks=hooks) |
| 124 | + |
| 125 | + async for event in stream.stream_events(): |
| 126 | + if event.type == "raw_response_event": |
| 127 | + continue |
| 128 | + if event.type == "agent_updated_stream_event": |
| 129 | + print(f"[EVENT] agent_updated → {event.new_agent.name}") |
| 130 | + elif event.type == "run_item_stream_event": |
| 131 | + item = event.item |
| 132 | + if item.type == "tool_call_item": |
| 133 | + print("[EVENT] tool_call_item") |
| 134 | + elif item.type == "tool_call_output_item": |
| 135 | + print(f"[EVENT] tool_call_output_item → {item.output}") |
| 136 | + elif item.type == "message_output_item": |
| 137 | + text = ItemHelpers.text_message_output(item) |
| 138 | + print(f"[EVENT] message_output_item → {text}") |
| 139 | + |
| 140 | + # Expect one on_agent_start, one on_llm_start, one on_llm_end, and one on_agent_end |
| 141 | + assert hooks.events == { |
| 142 | + "on_agent_start": 1, |
| 143 | + "on_llm_start": 1, |
| 144 | + "on_llm_end": 1, |
| 145 | + "on_agent_end": 1, |
| 146 | + } |
| 147 | + |
| 148 | + |
| 149 | +# test_async_run_hooks_with_agent_hooks_with_llm |
| 150 | +@pytest.mark.asyncio |
| 151 | +async def test_async_run_hooks_with_agent_hooks_with_llm(): |
| 152 | + hooks = RunHooksForTests() |
| 153 | + agent_hooks = AgentHooksForTests() |
| 154 | + model = FakeModel() |
| 155 | + |
| 156 | + agent = Agent( |
| 157 | + name="A", model=model, tools=[get_function_tool("f", "res")], handoffs=[], hooks=agent_hooks |
| 158 | + ) |
| 159 | + # Simulate a single LLM call producing an output: |
| 160 | + model.set_next_output([get_text_message("hello")]) |
| 161 | + await Runner.run(agent, input="hello", hooks=hooks) |
| 162 | + # Expect one on_agent_start, one on_llm_start, one on_llm_end, and one on_agent_end |
| 163 | + assert hooks.events == { |
| 164 | + "on_agent_start": 1, |
| 165 | + "on_llm_start": 1, |
| 166 | + "on_llm_end": 1, |
| 167 | + "on_agent_end": 1, |
| 168 | + } |
| 169 | + # Expect one on_start, one on_llm_start, one on_llm_end, and one on_end |
| 170 | + assert agent_hooks.events == {"on_start": 1, "on_llm_start": 1, "on_llm_end": 1, "on_end": 1} |
| 171 | + |
| 172 | + |
| 173 | +@pytest.mark.asyncio |
| 174 | +async def test_run_hooks_llm_error_non_streaming(monkeypatch): |
| 175 | + hooks = RunHooksForTests() |
| 176 | + model = FakeModel() |
| 177 | + agent = Agent(name="A", model=model, tools=[get_function_tool("f", "res")], handoffs=[]) |
| 178 | + |
| 179 | + async def boom(*args, **kwargs): |
| 180 | + raise RuntimeError("boom") |
| 181 | + |
| 182 | + monkeypatch.setattr(FakeModel, "get_response", boom, raising=True) |
| 183 | + |
| 184 | + with pytest.raises(RuntimeError, match="boom"): |
| 185 | + await Runner.run(agent, input="hello", hooks=hooks) |
| 186 | + |
| 187 | + # Current behavior is that hooks will not fire on LLM failure |
| 188 | + assert hooks.events["on_agent_start"] == 1 |
| 189 | + assert hooks.events["on_llm_start"] == 1 |
| 190 | + assert hooks.events["on_llm_end"] == 0 |
| 191 | + assert hooks.events["on_agent_end"] == 0 |
| 192 | + |
| 193 | + |
| 194 | +class BoomModel(Model): |
| 195 | + async def get_response(self, *a, **k): |
| 196 | + raise AssertionError("get_response should not be called in streaming test") |
| 197 | + |
| 198 | + async def stream_response(self, *a, **k): |
| 199 | + yield {"foo": "bar"} |
| 200 | + raise RuntimeError("stream blew up") |
| 201 | + |
| 202 | + |
| 203 | +@pytest.mark.asyncio |
| 204 | +async def test_streamed_run_hooks_llm_error(monkeypatch): |
| 205 | + """ |
| 206 | + Verify that when the streaming path raises, we still emit on_llm_start |
| 207 | + but do NOT emit on_llm_end (current behavior), and the exception propagates. |
| 208 | + """ |
| 209 | + hooks = RunHooksForTests() |
| 210 | + agent = Agent(name="A", model=BoomModel(), tools=[get_function_tool("f", "res")], handoffs=[]) |
| 211 | + |
| 212 | + stream = Runner.run_streamed(agent, input="hello", hooks=hooks) |
| 213 | + |
| 214 | + # Consuming the stream should surface the exception |
| 215 | + with pytest.raises(RuntimeError, match="stream blew up"): |
| 216 | + async for _ in stream.stream_events(): |
| 217 | + pass |
| 218 | + |
| 219 | + # Current behavior: success-only on_llm_end; ensure starts fired but ends did not. |
| 220 | + assert hooks.events["on_agent_start"] == 1 |
| 221 | + assert hooks.events["on_llm_start"] == 1 |
| 222 | + assert hooks.events["on_llm_end"] == 0 |
| 223 | + assert hooks.events["on_agent_end"] == 0 |
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