chore: import upstream snapshot with attribution

This commit is contained in:
wehub-resource-sync
2026-07-13 12:39:17 +08:00
commit 4ed4e9ff99
1368 changed files with 334957 additions and 0 deletions
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from collections import defaultdict
from typing import Any
import pytest
from agents.agent import Agent
from agents.items import ItemHelpers, ModelResponse, TResponseInputItem
from agents.lifecycle import AgentHooks
from agents.run import Runner
from agents.run_context import AgentHookContext, RunContextWrapper, TContext
from agents.tool import Tool
from .fake_model import FakeModel
from .test_responses import (
get_function_tool,
get_text_message,
)
class AgentHooksForTests(AgentHooks):
def __init__(self):
self.events: dict[str, int] = defaultdict(int)
def reset(self):
self.events.clear()
async def on_start(self, context: AgentHookContext[TContext], agent: Agent[TContext]) -> None:
self.events["on_start"] += 1
async def on_end(
self, context: RunContextWrapper[TContext], agent: Agent[TContext], output: Any
) -> None:
self.events["on_end"] += 1
async def on_handoff(
self, context: RunContextWrapper[TContext], agent: Agent[TContext], source: Agent[TContext]
) -> None:
self.events["on_handoff"] += 1
async def on_tool_start(
self, context: RunContextWrapper[TContext], agent: Agent[TContext], tool: Tool
) -> None:
self.events["on_tool_start"] += 1
async def on_tool_end(
self,
context: RunContextWrapper[TContext],
agent: Agent[TContext],
tool: Tool,
result: object,
) -> None:
self.events["on_tool_end"] += 1
# NEW: LLM hooks
async def on_llm_start(
self,
context: RunContextWrapper[TContext],
agent: Agent[TContext],
system_prompt: str | None,
input_items: list[TResponseInputItem],
) -> None:
self.events["on_llm_start"] += 1
async def on_llm_end(
self,
context: RunContextWrapper[TContext],
agent: Agent[TContext],
response: ModelResponse,
) -> None:
self.events["on_llm_end"] += 1
# Example test using the above hooks:
@pytest.mark.asyncio
async def test_async_agent_hooks_with_llm():
hooks = AgentHooksForTests()
model = FakeModel()
agent = Agent(
name="A", model=model, tools=[get_function_tool("f", "res")], handoffs=[], hooks=hooks
)
# Simulate a single LLM call producing an output:
model.set_next_output([get_text_message("hello")])
await Runner.run(agent, input="hello")
# Expect one on_start, one on_llm_start, one on_llm_end, and one on_end
assert hooks.events == {"on_start": 1, "on_llm_start": 1, "on_llm_end": 1, "on_end": 1}
# test_sync_agent_hook_with_llm()
def test_sync_agent_hook_with_llm():
hooks = AgentHooksForTests()
model = FakeModel()
agent = Agent(
name="A", model=model, tools=[get_function_tool("f", "res")], handoffs=[], hooks=hooks
)
# Simulate a single LLM call producing an output:
model.set_next_output([get_text_message("hello")])
Runner.run_sync(agent, input="hello")
# Expect one on_start, one on_llm_start, one on_llm_end, and one on_end
assert hooks.events == {"on_start": 1, "on_llm_start": 1, "on_llm_end": 1, "on_end": 1}
# test_streamed_agent_hooks_with_llm():
@pytest.mark.asyncio
async def test_streamed_agent_hooks_with_llm():
hooks = AgentHooksForTests()
model = FakeModel()
agent = Agent(
name="A", model=model, tools=[get_function_tool("f", "res")], handoffs=[], hooks=hooks
)
# Simulate a single LLM call producing an output:
model.set_next_output([get_text_message("hello")])
stream = Runner.run_streamed(agent, input="hello")
async for event in stream.stream_events():
if event.type == "raw_response_event":
continue
if event.type == "agent_updated_stream_event":
print(f"[EVENT] agent_updated → {event.new_agent.name}")
elif event.type == "run_item_stream_event":
item = event.item
if item.type == "tool_call_item":
print("[EVENT] tool_call_item")
elif item.type == "tool_call_output_item":
print(f"[EVENT] tool_call_output_item → {item.output}")
elif item.type == "message_output_item":
text = ItemHelpers.text_message_output(item)
print(f"[EVENT] message_output_item → {text}")
# Expect one on_start, one on_llm_start, one on_llm_end, and one on_end
assert hooks.events == {"on_start": 1, "on_llm_start": 1, "on_llm_end": 1, "on_end": 1}