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feat: Generate a fallback report upon recursion limit hit (#838)

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* finish handle_recursion_limit_fallback

* fix

* renmae test file

* fix

* doc

---------

Co-authored-by: lxl0413 <lixinling2021@gmail.com>
This commit is contained in:
Xun
2026-01-26 21:10:18 +08:00
committed by GitHub
parent 9a34e32252
commit ee02b9f637
7 changed files with 895 additions and 12 deletions
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79
tests/integration/test_nodes.py
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@@ -1107,7 +1107,12 @@ def mock_agent():
# Simulate agent returning a message list
return {"messages": [MagicMock(content="result content")]}
def stream(input, config, stream_mode):
# Simulate agent.stream() yielding messages
yield {"messages": [MagicMock(content="result content")]}
agent.ainvoke = ainvoke
agent.stream = stream
return agent
@@ -1172,7 +1177,12 @@ async def test_execute_agent_step_with_resources_and_researcher(mock_step):
assert any("DO NOT include inline citations" in m.content for m in messages)
return {"messages": [MagicMock(content="resource result")]}
def stream(input, config, stream_mode):
# Simulate agent.stream() yielding messages
yield {"messages": [MagicMock(content="resource result")]}
agent.ainvoke = ainvoke
agent.stream = stream
with patch(
"src.graph.nodes.HumanMessage",
side_effect=lambda content, name=None: MagicMock(content=content, name=name),
@@ -2414,7 +2424,43 @@ async def test_execute_agent_step_preserves_multiple_tool_messages():
]
return {"messages": messages}
def stream(input, config, stream_mode):
# Simulate agent.stream() yielding the final messages
messages = [
AIMessage(
content="I'll search for information about this topic.",
tool_calls=[{
"id": "call_1",
"name": "web_search",
"args": {"query": "first search query"}
}]
),
ToolMessage(
content="First search result content here",
tool_call_id="call_1",
name="web_search",
),
AIMessage(
content="Let me search for more specific information.",
tool_calls=[{
"id": "call_2",
"name": "web_search",
"args": {"query": "second search query"}
}]
),
ToolMessage(
content="Second search result content here",
tool_call_id="call_2",
name="web_search",
),
AIMessage(
content="Based on my research, here is the comprehensive answer..."
),
]
yield {"messages": messages}
agent.ainvoke = mock_ainvoke
agent.stream = stream
# Execute the agent step
with patch(
@@ -2510,7 +2556,30 @@ async def test_execute_agent_step_single_tool_call_still_works():
]
return {"messages": messages}
def stream(input, config, stream_mode):
# Simulate agent.stream() yielding the messages
messages = [
AIMessage(
content="I'll search for information.",
tool_calls=[{
"id": "call_1",
"name": "web_search",
"args": {"query": "search query"}
}]
),
ToolMessage(
content="Search result content",
tool_call_id="call_1",
name="web_search",
),
AIMessage(
content="Here is the answer based on the search result."
),
]
yield {"messages": messages}
agent.ainvoke = mock_ainvoke
agent.stream = stream
with patch(
"src.graph.nodes.HumanMessage",
@@ -2570,7 +2639,17 @@ async def test_execute_agent_step_no_tool_calls_still_works():
]
return {"messages": messages}
def stream(input, config, stream_mode):
# Simulate agent.stream() yielding messages without tool calls
messages = [
AIMessage(
content="Based on my knowledge, here is the answer without needing to search."
),
]
yield {"messages": messages}
agent.ainvoke = mock_ainvoke
agent.stream = stream
with patch(
"src.graph.nodes.HumanMessage",