fix: narrow DeerFlow observability integration

Author: sipercai

instrumentation-loongsuite/README.md

@@ -11,7 +11,7 @@
 | [loongsuite-instrumentation-crewai](./loongsuite-instrumentation-crewai) | crewai >= 0.80.0 | No | development
 | [loongsuite-instrumentation-dashscope](./loongsuite-instrumentation-dashscope) | dashscope >= 1.0.0 | No | development
 | [loongsuite-instrumentation-deepagents](./loongsuite-instrumentation-deepagents) | deepagents >= 0.6.0, < 0.7.0 | No | development
-| [loongsuite-instrumentation-deerflow](./loongsuite-instrumentation-deerflow) | deerflow | No | development
+| [loongsuite-instrumentation-deerflow](./loongsuite-instrumentation-deerflow) | deerflow-harness >= 2, < 3 (official source distribution) | No | development
 | [loongsuite-instrumentation-dify](./loongsuite-instrumentation-dify) | dify | No | development
 | [loongsuite-instrumentation-google-adk](./loongsuite-instrumentation-google-adk) | google-adk >= 0.1.0 | No | development
 | [loongsuite-instrumentation-hermes-agent](./loongsuite-instrumentation-hermes-agent) | openai >= 1.0.0 | No | development
@@ -30,4 +30,4 @@
 | [loongsuite-instrumentation-vita](./loongsuite-instrumentation-vita) | vita >= 0.0.1 | No | development
 | [loongsuite-instrumentation-webarena](./loongsuite-instrumentation-webarena) | webarena >= 0.0.1 | No | development
 | [loongsuite-instrumentation-widesearch](./loongsuite-instrumentation-widesearch) | widesearch >= 0.1.0 | No | development
-| [loongsuite-instrumentation-wildtool](./loongsuite-instrumentation-wildtool) | openai >= 1.0.0 | No | development
+| [loongsuite-instrumentation-wildtool](./loongsuite-instrumentation-wildtool) | openai >= 1.0.0 | No | development

instrumentation-loongsuite/loongsuite-instrumentation-deepagents/CHANGELOG.md

@@ -7,12 +7,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## Unreleased
 
-### Changed
-
-- Mark DeepAgents graphs with the explicit `deepagents` agent flavor so their
-  `model` nodes remain the sole ReAct `STEP` boundary when multiple compatible
-  instrumentors are enabled.
-
 ## Version 0.7.0 (2026-07-03)
 
 ### Added

instrumentation-loongsuite/loongsuite-instrumentation-deepagents/src/opentelemetry/instrumentation/deepagents/internal/patch.py

@@ -16,9 +16,10 @@
 
 DeepAgents builds on ``langchain.agents.create_agent`` and returns
 ``create_agent(...).with_config(...)``. That final ``with_config`` call creates
-a new graph object and drops the flavor that LangChain instrumentation places
-on the original graph. This module marks the returned graph as ``deepagents``
-and injects that flavor into call-time config.
+a new graph object and drops the marker that LangChain instrumentation places
+on the original graph. This module restores the marker on the returned graph
+and injects the marker into call-time config, mirroring LangGraph's lightweight
+metadata handoff.
 """
 
 from __future__ import annotations
@@ -39,8 +40,6 @@
 
 CREATE_DEEP_AGENT_MODULE = "deepagents.graph"
 CREATE_DEEP_AGENT_NAME = "create_deep_agent"
-AGENT_FLAVOR_METADATA_KEY = "_loongsuite_agent_flavor"
-DEEPAGENTS_AGENT_FLAVOR = "deepagents"
 REACT_AGENT_METADATA_KEY = "_loongsuite_react_agent"
 DEEPAGENTS_METADATA_KEY = "_loongsuite_deepagents_agent"
 GRAPH_METHODS_WRAPPED_ATTR = "_loongsuite_deepagents_methods_wrapped"
@@ -182,7 +181,6 @@ def _restore_top_level_create_deep_agent() -> None:
 
 def _mark_graph(graph: Any) -> None:
     with suppress(Exception):
-        setattr(graph, AGENT_FLAVOR_METADATA_KEY, DEEPAGENTS_AGENT_FLAVOR)
         setattr(graph, REACT_AGENT_METADATA_KEY, True)
         setattr(graph, DEEPAGENTS_METADATA_KEY, True)
 
@@ -243,7 +241,6 @@ def _restore_graph_methods(graph: Any) -> None:
     for attr_name in (
         GRAPH_ORIGINAL_METHODS_ATTR,
         GRAPH_METHODS_WRAPPED_ATTR,
-        AGENT_FLAVOR_METADATA_KEY,
         REACT_AGENT_METADATA_KEY,
         DEEPAGENTS_METADATA_KEY,
     ):
@@ -316,8 +313,6 @@ def _inject_react_metadata(config: Any) -> Any:
     config = ensure_config(config)
     config = {**config}
     metadata = dict(config.get("metadata") or {})
-    metadata[AGENT_FLAVOR_METADATA_KEY] = DEEPAGENTS_AGENT_FLAVOR
-    metadata.setdefault(REACT_AGENT_METADATA_KEY, True)
     metadata.setdefault(DEEPAGENTS_METADATA_KEY, True)
     config["metadata"] = metadata
     return config

instrumentation-loongsuite/loongsuite-instrumentation-deepagents/tests/test_deepagents_spans.py

@@ -28,12 +28,6 @@
 from langchain_core.outputs import ChatGeneration, ChatResult
 from langchain_core.tools import tool
 
-from opentelemetry.instrumentation.langchain.internal._agent_flavor import (
-    AGENT_FLAVOR_METADATA_KEY,
-    DEEPAGENTS_AGENT_FLAVOR,
-    LANGCHAIN_CREATE_AGENT_FLAVOR,
-)
-
 
 class _SequenceToolCallingModel(BaseChatModel):
     def __init__(self, responses: list[AIMessage]):
@@ -162,148 +156,6 @@ def _assert_kind_under_step(
     return matches
 
 
-def test_langchain_create_agent_model_node_creates_single_step(
-    instrument, span_exporter
-):
-    """LangChain 1.x ``create_agent`` uses ``model``, not ``agent``, nodes."""
-    from langchain.agents import create_agent  # noqa: PLC0415
-
-    agent = create_agent(
-        model=_SequenceToolCallingModel(
-            [AIMessage(content="Plain LangChain final answer.")]
-        ),
-        tools=[lookup_city],
-        name="plain_langchain_agent",
-    )
-
-    assert (
-        getattr(agent, AGENT_FLAVOR_METADATA_KEY)
-        == LANGCHAIN_CREATE_AGENT_FLAVOR
-    )
-    assert not hasattr(agent, "_loongsuite_deepagents_agent")
-
-    result = agent.invoke({"messages": [{"role": "user", "content": "hello"}]})
-
-    assert result["messages"][-1].content == "Plain LangChain final answer."
-    spans = span_exporter.get_finished_spans()
-    agent_span = _assert_single_agent(spans, "plain_langchain_agent")
-    step_spans = _spans_by_kind(spans, "STEP")
-    assert len(step_spans) == 1
-    _assert_step_is_under_agent(agent_span, step_spans[0])
-
-
-def test_langchain_create_agent_tool_loop_creates_two_steps(
-    instrument, span_exporter
-):
-    from langchain.agents import create_agent  # noqa: PLC0415
-
-    agent = create_agent(
-        model=_SequenceToolCallingModel(
-            [
-                AIMessage(
-                    content="",
-                    tool_calls=[
-                        {
-                            "name": "lookup_city",
-                            "args": {"query": "where"},
-                            "id": "plain_call_1",
-                        }
-                    ],
-                ),
-                AIMessage(content="Plain answer: Hangzhou."),
-            ]
-        ),
-        tools=[lookup_city],
-        name="plain_langchain_tool_agent",
-    )
-
-    result = agent.invoke({"messages": [{"role": "user", "content": "where"}]})
-
-    assert result["messages"][-1].content == "Plain answer: Hangzhou."
-    spans = span_exporter.get_finished_spans()
-    _assert_single_agent(spans, "plain_langchain_tool_agent")
-    step_spans = sorted(
-        _spans_by_kind(spans, "STEP"),
-        key=lambda span: span.attributes.get("gen_ai.react.round", 0),
-    )
-    assert len(step_spans) == 2
-    assert [
-        span.attributes.get("gen_ai.react.finish_reason")
-        for span in step_spans
-    ] == ["tool_calls", "stop"]
-
-
-def test_langchain_create_agent_stream_creates_single_step(
-    instrument,
-    span_exporter,
-):
-    from langchain.agents import create_agent  # noqa: PLC0415
-
-    agent = create_agent(
-        model=_SequenceToolCallingModel(
-            [AIMessage(content="Plain streamed answer.")]
-        ),
-        tools=[lookup_city],
-        name="plain_langchain_stream_agent",
-    )
-
-    chunks = list(
-        agent.stream({"messages": [{"role": "user", "content": "hello"}]})
-    )
-
-    assert chunks
-    spans = span_exporter.get_finished_spans()
-    agent_span = _assert_single_agent(spans, "plain_langchain_stream_agent")
-    step_spans = _spans_by_kind(spans, "STEP")
-    assert len(step_spans) == 1
-    _assert_step_is_under_agent(agent_span, step_spans[0])
-
-
-@pytest.mark.asyncio
-async def test_langchain_create_agent_async_tool_loop_creates_two_steps(
-    instrument,
-    span_exporter,
-):
-    from langchain.agents import create_agent  # noqa: PLC0415
-
-    agent = create_agent(
-        model=_SequenceToolCallingModel(
-            [
-                AIMessage(
-                    content="",
-                    tool_calls=[
-                        {
-                            "name": "lookup_city",
-                            "args": {"query": "where"},
-                            "id": "plain_async_call_1",
-                        }
-                    ],
-                ),
-                AIMessage(content="Async answer: Hangzhou."),
-            ]
-        ),
-        tools=[lookup_city],
-        name="plain_langchain_async_agent",
-    )
-
-    result = await agent.ainvoke(
-        {"messages": [{"role": "user", "content": "where"}]}
-    )
-
-    assert result["messages"][-1].content == "Async answer: Hangzhou."
-    spans = span_exporter.get_finished_spans()
-    _assert_single_agent(spans, "plain_langchain_async_agent")
-    step_spans = sorted(
-        _spans_by_kind(spans, "STEP"),
-        key=lambda span: span.attributes.get("gen_ai.react.round", 0),
-    )
-    assert len(step_spans) == 2
-    assert [
-        span.attributes.get("gen_ai.react.finish_reason")
-        for span in step_spans
-    ] == ["tool_calls", "stop"]
-
-
 def test_deepagents_root_span_is_agent_and_single_step(
     instrument, span_exporter
 ):
@@ -314,7 +166,6 @@ def test_deepagents_root_span_is_agent_and_single_step(
 
     assert getattr(agent, "_loongsuite_react_agent") is True
     assert getattr(agent, "_loongsuite_deepagents_agent") is True
-    assert getattr(agent, AGENT_FLAVOR_METADATA_KEY) == DEEPAGENTS_AGENT_FLAVOR
 
     result = agent.invoke({"messages": [{"role": "user", "content": "hello"}]})
 

instrumentation-loongsuite/loongsuite-instrumentation-deepagents/tests/test_instrumentor.py

@@ -18,8 +18,6 @@
 
 from opentelemetry.instrumentation.deepagents import DeepAgentsInstrumentor
 from opentelemetry.instrumentation.deepagents.internal.patch import (
-    AGENT_FLAVOR_METADATA_KEY,
-    DEEPAGENTS_AGENT_FLAVOR,
     DEEPAGENTS_METADATA_KEY,
     GRAPH_METHODS_WRAPPED_ATTR,
     GRAPH_ORIGINAL_METHODS_ATTR,
@@ -101,18 +99,10 @@ def test_uninstrument_restores_wrapped_graph_methods():
         _wrap_graph_methods(graph)
 
         assert getattr(graph, GRAPH_METHODS_WRAPPED_ATTR) is True
-        assert (
-            getattr(graph, AGENT_FLAVOR_METADATA_KEY)
-            == DEEPAGENTS_AGENT_FLAVOR
-        )
         assert getattr(graph, REACT_AGENT_METADATA_KEY) is True
         assert getattr(graph, DEEPAGENTS_METADATA_KEY) is True
 
         invoke_config = graph.invoke("hello")
-        assert (
-            invoke_config["metadata"][AGENT_FLAVOR_METADATA_KEY]
-            == DEEPAGENTS_AGENT_FLAVOR
-        )
         assert invoke_config["metadata"][DEEPAGENTS_METADATA_KEY] is True
 
         stream_iter = graph.stream("hello")
@@ -124,29 +114,19 @@ def test_uninstrument_restores_wrapped_graph_methods():
 
         child_graph = graph.with_config({"metadata": {"customer": "kept"}})
         assert getattr(child_graph, GRAPH_METHODS_WRAPPED_ATTR) is True
-        assert (
-            getattr(child_graph, AGENT_FLAVOR_METADATA_KEY)
-            == DEEPAGENTS_AGENT_FLAVOR
-        )
         assert getattr(child_graph, DEEPAGENTS_METADATA_KEY) is True
         child_config = child_graph.invoke("hello")
         assert child_config["metadata"]["customer"] == "kept"
-        assert (
-            child_config["metadata"][AGENT_FLAVOR_METADATA_KEY]
-            == DEEPAGENTS_AGENT_FLAVOR
-        )
         assert child_config["metadata"][DEEPAGENTS_METADATA_KEY] is True
 
         uninstrument_create_deep_agent()
 
         assert not hasattr(graph, GRAPH_METHODS_WRAPPED_ATTR)
         assert not hasattr(graph, GRAPH_ORIGINAL_METHODS_ATTR)
-        assert not hasattr(graph, AGENT_FLAVOR_METADATA_KEY)
         assert not hasattr(graph, REACT_AGENT_METADATA_KEY)
         assert not hasattr(graph, DEEPAGENTS_METADATA_KEY)
         assert not hasattr(child_graph, GRAPH_METHODS_WRAPPED_ATTR)
         assert not hasattr(child_graph, GRAPH_ORIGINAL_METHODS_ATTR)
-        assert not hasattr(child_graph, AGENT_FLAVOR_METADATA_KEY)
         assert not hasattr(child_graph, REACT_AGENT_METADATA_KEY)
         assert not hasattr(child_graph, DEEPAGENTS_METADATA_KEY)
         assert graph.invoke("hello") is None

instrumentation-loongsuite/loongsuite-instrumentation-deerflow/CHANGELOG.md

@@ -12,6 +12,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Treat user cancellation, early stream closure, and DeerFlow interrupted runs
   as non-error entry completions while retaining their interrupted status.
 - Clarify the initial sandbox, skill, and memory observability boundaries.
+- Document verified local, daemon, Docker, and embedded integration paths,
+  including DeerFlow's exact `uv sync` behavior.
+- Keep DeerFlow trace-correlation helper failures from interrupting embedded
+  client streams.
 
 ## Version 0.8.0 (2026-07-14)