fix(qwenpaw): align session propagation and quiet bootstrap (#215)

Author: sipercai

README-zh.md

@@ -429,6 +429,9 @@ loongsuite-instrument \
 
   ```bash
   export LOONGSUITE_PYTHON_SITE_BOOTSTRAP=True
+  # 交互式 CLI / 应用可选：不要把通用成功提示写入 stdout。
+  export LOONGSUITE_PYTHON_SITE_BOOTSTRAP_LOG_SUCCESS=False
+  export LOONGSUITE_PYTHON_SITE_BOOTSTRAP_STATUS_FILE=/tmp/loongsuite-site-bootstrap-status.json
   ```
 
 **步骤 4 — 创建 `~/.loongsuite/bootstrap-config.json`**
@@ -445,7 +448,7 @@ loongsuite-instrument \
   }
   ```
 
-  然后执行 `python demo.py`。如需使用 **console** exporter、其他后端、改用 **`loongsuite-instrument`**（而非直接 `python`），或查看完整优先级/边界场景，请阅读 [loongsuite-site-bootstrap/README.md](loongsuite-site-bootstrap/README.md)。
+  然后执行 `python demo.py`。如需使用 **console** exporter、其他后端、改用 **`loongsuite-instrument`**（而非直接 `python`）、控制成功提示输出，或查看完整优先级/边界场景，请阅读 [loongsuite-site-bootstrap/README.md](loongsuite-site-bootstrap/README.md)。
 
 > **Beta：**Site-bootstrap 会影响其启用环境中的所有 Python 进程，生产环境使用前请先阅读包 README。
 

README.md

@@ -423,6 +423,9 @@ Run **without** changing codes or bootstrap commands: a **`.pth` hook** loads Lo
 
   ```bash
   export LOONGSUITE_PYTHON_SITE_BOOTSTRAP=True
+  # Optional for interactive CLIs/apps: suppress the generic success line on stdout.
+  export LOONGSUITE_PYTHON_SITE_BOOTSTRAP_LOG_SUCCESS=False
+  export LOONGSUITE_PYTHON_SITE_BOOTSTRAP_STATUS_FILE=/tmp/loongsuite-site-bootstrap-status.json
   ```
 
 **Step 4 — Create `~/.loongsuite/bootstrap-config.json`** with the OpenTelemetry environments keys you need.
@@ -437,7 +440,7 @@ Run **without** changing codes or bootstrap commands: a **`.pth` hook** loads Lo
   }
   ```
 
-  Then run `python demo.py`. For **console** exporters, other backends, using **`loongsuite-instrument`** instead of plain `python`, or full precedence / edge cases, see [loongsuite-site-bootstrap/README.md](loongsuite-site-bootstrap/README.md).
+  Then run `python demo.py`. For **console** exporters, other backends, using **`loongsuite-instrument`** instead of plain `python`, success logging controls, or full precedence / edge cases, see [loongsuite-site-bootstrap/README.md](loongsuite-site-bootstrap/README.md).
 
 > **Beta:** Site-bootstrap affects every Python process in the environment where it is enabled; read the package README before using it in production.
 

instrumentation-genai/opentelemetry-instrumentation-langchain/src/opentelemetry/instrumentation/langchain/callback_handler.py

@@ -115,7 +115,7 @@ def on_chat_model_start(
         for sub_messages in messages:
             for message in sub_messages:
                 # Cast to Any to avoid type checking issues with LangChain's complex content type
-                raw_content: Any = message.content  # type: ignore[misc]
+                raw_content: Any = message.content
                 role = message.type
                 parts: list[Text] = []
 

instrumentation-loongsuite/loongsuite-instrumentation-agentscope/src/opentelemetry/instrumentation/agentscope/_wrapper.py

@@ -70,6 +70,7 @@
 from opentelemetry.util.genai.types import Error, LLMInvocation
 
 from .utils import (
+    apply_entry_baggage_identity,
     convert_agent_response_to_output_messages,
     convert_chatresponse_to_output_messages,
     create_agent_invocation,
@@ -182,6 +183,7 @@ def hook(agent_self: Any, kwargs: dict) -> None:
 
         state.react_round += 1
         inv = ReactStepInvocation(round=state.react_round)
+        apply_entry_baggage_identity(inv)
         handler.start_react_step(inv, context=state.original_context)
         state.active_step = inv
         state.pending_acting_count = 0

instrumentation-loongsuite/loongsuite-instrumentation-agentscope/src/opentelemetry/instrumentation/agentscope/patch.py

@@ -34,6 +34,11 @@
 from opentelemetry.util.genai.span_utils import _apply_error_attributes
 from opentelemetry.util.genai.types import Error
 
+from .utils import (
+    apply_entry_baggage_identity,
+    entry_baggage_identity_attributes,
+)
+
 logger = logging.getLogger(__name__)
 
 
@@ -407,6 +412,7 @@ async def wrap_tool_call(wrapped, instance, args, kwargs, handler):
         tool_description=tool_description,
         tool_call_arguments=tool_args,
     )
+    apply_entry_baggage_identity(invocation)
 
     # --- Skill attributes ---
     #
@@ -479,6 +485,7 @@ async def wrap_formatter_format(wrapped, instance, args, kwargs, tracer=None):
         try:
             # Record only basic information
             span.set_attribute("gen_ai.operation.name", "format")
+            span.set_attributes(entry_baggage_identity_attributes())
 
             # Execute the wrapped async call
             result = await wrapped(*args, **kwargs)

instrumentation-loongsuite/loongsuite-instrumentation-agentscope/src/opentelemetry/instrumentation/agentscope/utils.py

@@ -35,9 +35,14 @@
 from agentscope.model import ChatModelBase, ChatResponse
 from pydantic import BaseModel
 
+from opentelemetry import baggage
 from opentelemetry.semconv._incubating.attributes import (
     gen_ai_attributes as GenAIAttributes,
 )
+from opentelemetry.util.genai.extended_semconv.gen_ai_extended_attributes import (
+    GEN_AI_SESSION_ID,
+    GEN_AI_USER_ID,
+)
 from opentelemetry.util.genai.extended_types import (
     EmbeddingInvocation,
     InvokeAgentInvocation,
@@ -87,6 +92,43 @@ class AgentScopeGenAiProviderName(str, Enum):
 ]
 
 
+def _current_baggage_value(key: str) -> str | None:
+    try:
+        value = baggage.get_baggage(key)
+    except Exception:
+        return None
+    if value is None:
+        return None
+    text = str(value).strip()
+    return text or None
+
+
+def entry_baggage_identity_attributes() -> dict[str, str]:
+    """Return entry-level identity from current OpenTelemetry Baggage.
+
+    QwenPaw opens an Entry span before AgentScope runs and writes
+    ``gen_ai.session.id`` / ``gen_ai.user.id`` into Baggage. AgentScope has
+    its own ``run_id``; when both instrumentations are active, entry baggage is
+    the request-level identity and should color downstream spans.
+    """
+    attributes: dict[str, str] = {}
+    session_id = _current_baggage_value(GEN_AI_SESSION_ID)
+    user_id = _current_baggage_value(GEN_AI_USER_ID)
+    if session_id:
+        attributes[GEN_AI_SESSION_ID] = session_id
+    if user_id:
+        attributes[GEN_AI_USER_ID] = user_id
+    return attributes
+
+
+def apply_entry_baggage_identity(invocation: Any) -> str | None:
+    """Copy entry-level identity baggage onto a GenAI invocation."""
+    attributes = entry_baggage_identity_attributes()
+    for key, value in attributes.items():
+        invocation.attributes.setdefault(key, value)
+    return attributes.get(GEN_AI_SESSION_ID)
+
+
 def get_provider_name(chat_model: ChatModelBase) -> str:
     """Parse chat model provider name"""
     classname = chat_model.__class__.__name__
@@ -318,6 +360,9 @@ def create_llm_invocation(
         provider=provider_name,
         input_messages=input_messages,
     )
+    entry_session_id = apply_entry_baggage_identity(invocation)
+    if entry_session_id and invocation.conversation_id is None:
+        invocation.conversation_id = entry_session_id
 
     # Set optional request parameters if present
     if call_kwargs.get("max_tokens"):
@@ -353,6 +398,7 @@ def create_embedding_invocation(
         request_model=request_model,
         provider=provider_name,
     )
+    apply_entry_baggage_identity(invocation)
 
     # Set encoding formats if present
     if call_kwargs.get("encoding_formats"):
@@ -392,16 +438,18 @@ def create_agent_invocation(
         except Exception as e:
             logger.debug(f"Error converting agent input messages: {e}")
 
+    entry_session_id = _current_baggage_value(GEN_AI_SESSION_ID)
     invocation = InvokeAgentInvocation(
         provider=provider_name,
         agent_name=getattr(reply_instance, "name", "unknown_agent"),
         agent_id=getattr(reply_instance, "id", "unknown"),
         agent_description=inspect.getdoc(reply_instance.__class__)
         or "No description available",
-        conversation_id=_config.run_id,
+        conversation_id=entry_session_id or _config.run_id,
         request_model=request_model,
         input_messages=input_messages,
     )
+    apply_entry_baggage_identity(invocation)
 
     # Set system instruction if available
     if hasattr(reply_instance, "sys_prompt") and reply_instance.sys_prompt:

instrumentation-loongsuite/loongsuite-instrumentation-agentscope/tests/test_utils.py

@@ -17,17 +17,32 @@
 Tests for utility functions in opentelemetry.instrumentation.agentscope.utils
 """
 
+from types import SimpleNamespace
+
 from agentscope.message import Msg, ToolResultBlock
 from agentscope.tracing._converter import (
     _convert_block_to_part as _convert_block_to_part_framework,
 )
 
+from opentelemetry import baggage
+from opentelemetry import context as otel_context
+from opentelemetry.instrumentation.agentscope import utils as utils_module
 from opentelemetry.instrumentation.agentscope.utils import (
     _convert_block_to_part as _convert_block_to_part_local,
 )
 from opentelemetry.instrumentation.agentscope.utils import (
+    apply_entry_baggage_identity,
     convert_agentscope_messages_to_genai_format,
+    create_agent_invocation,
+    create_embedding_invocation,
+    create_llm_invocation,
+    entry_baggage_identity_attributes,
+)
+from opentelemetry.util.genai.extended_semconv.gen_ai_extended_attributes import (
+    GEN_AI_SESSION_ID,
+    GEN_AI_USER_ID,
 )
+from opentelemetry.util.genai.extended_types import ReactStepInvocation
 from opentelemetry.util.genai.types import ToolCallResponse
 
 
@@ -103,3 +118,106 @@ def test_convert_with_framework_converter(self):
         part_obj = converted[0].parts[0]
         assert isinstance(part_obj, ToolCallResponse)
         assert part_obj.response == "framework output"
+
+    def test_create_agent_invocation_prefers_entry_baggage_identity(
+        self, monkeypatch
+    ):
+        monkeypatch.setattr(
+            utils_module._config, "run_id", "agentscope-run-id"
+        )
+        ctx = baggage.set_baggage(GEN_AI_SESSION_ID, "entry-session")
+        ctx = baggage.set_baggage(GEN_AI_USER_ID, "entry-user", ctx)
+        token = otel_context.attach(ctx)
+        try:
+            invocation = create_agent_invocation(
+                SimpleNamespace(
+                    model=None,
+                    name="TestAgent",
+                    id="agent-id",
+                    sys_prompt=None,
+                ),
+                tuple(),
+                {},
+            )
+        finally:
+            otel_context.detach(token)
+
+        assert invocation.conversation_id == "entry-session"
+        assert invocation.attributes[GEN_AI_SESSION_ID] == "entry-session"
+        assert invocation.attributes[GEN_AI_USER_ID] == "entry-user"
+
+    def test_entry_baggage_identity_attributes(self):
+        ctx = baggage.set_baggage(GEN_AI_SESSION_ID, "entry-session")
+        ctx = baggage.set_baggage(GEN_AI_USER_ID, "entry-user", ctx)
+        token = otel_context.attach(ctx)
+        try:
+            attributes = entry_baggage_identity_attributes()
+        finally:
+            otel_context.detach(token)
+
+        assert attributes == {
+            GEN_AI_SESSION_ID: "entry-session",
+            GEN_AI_USER_ID: "entry-user",
+        }
+
+    def test_create_agent_invocation_falls_back_to_agentscope_run_id(
+        self, monkeypatch
+    ):
+        monkeypatch.setattr(
+            utils_module._config, "run_id", "agentscope-run-id"
+        )
+
+        invocation = create_agent_invocation(
+            SimpleNamespace(
+                model=None,
+                name="TestAgent",
+                id="agent-id",
+                sys_prompt=None,
+            ),
+            tuple(),
+            {},
+        )
+
+        assert invocation.conversation_id == "agentscope-run-id"
+        assert GEN_AI_SESSION_ID not in invocation.attributes
+        assert GEN_AI_USER_ID not in invocation.attributes
+
+    def test_model_invocations_copy_entry_baggage_identity(self):
+        ctx = baggage.set_baggage(GEN_AI_SESSION_ID, "entry-session")
+        ctx = baggage.set_baggage(GEN_AI_USER_ID, "entry-user", ctx)
+        token = otel_context.attach(ctx)
+        try:
+            llm_invocation = create_llm_invocation(
+                SimpleNamespace(model_name="qwen-max"),
+                tuple(),
+                {},
+            )
+            embedding_invocation = create_embedding_invocation(
+                SimpleNamespace(model_name="text-embedding-v4"),
+                tuple(),
+                {},
+            )
+        finally:
+            otel_context.detach(token)
+
+        assert llm_invocation.conversation_id == "entry-session"
+        assert llm_invocation.attributes[GEN_AI_SESSION_ID] == "entry-session"
+        assert llm_invocation.attributes[GEN_AI_USER_ID] == "entry-user"
+        assert (
+            embedding_invocation.attributes[GEN_AI_SESSION_ID]
+            == "entry-session"
+        )
+        assert embedding_invocation.attributes[GEN_AI_USER_ID] == "entry-user"
+
+    def test_react_step_invocation_copies_entry_baggage_identity(self):
+        ctx = baggage.set_baggage(GEN_AI_SESSION_ID, "entry-session")
+        ctx = baggage.set_baggage(GEN_AI_USER_ID, "entry-user", ctx)
+        token = otel_context.attach(ctx)
+        try:
+            invocation = ReactStepInvocation(round=1)
+            apply_entry_baggage_identity(invocation)
+        finally:
+            otel_context.detach(token)
+
+        assert invocation.attributes[GEN_AI_SESSION_ID] == "entry-session"
+        assert invocation.attributes[GEN_AI_USER_ID] == "entry-user"

instrumentation-loongsuite/loongsuite-instrumentation-langchain/src/opentelemetry/instrumentation/langchain/internal/_tracer.py

@@ -270,7 +270,7 @@ def _handle_llm_start(self, run: Run) -> None:
             rd = _RunData(
                 run_kind="llm",
                 span=invocation.span,
-                context=set_span_in_context(invocation.span)
+                context=otel_context.get_current()
                 if invocation.span
                 else None,
                 invocation=invocation,
@@ -413,9 +413,7 @@ def _start_agent(self, run: Run) -> None:
         rd = _RunData(
             run_kind="agent",
             span=invocation.span,
-            context=set_span_in_context(invocation.span)
-            if invocation.span
-            else None,
+            context=otel_context.get_current() if invocation.span else None,
             invocation=invocation,
             is_langgraph_react=_has_langgraph_react_metadata(run),
         )
@@ -437,7 +435,12 @@ def _start_chain(self, run: Run) -> None:
             span.set_attribute(INPUT_VALUE, _safe_json(inputs))
 
         # Attach chain span context so non-LangChain children nest correctly.
-        ctx = set_span_in_context(span)
+        current_context = (
+            parent_ctx
+            if parent_ctx is not None
+            else otel_context.get_current()
+        )
+        ctx = set_span_in_context(span, current_context)
         token = otel_context.attach(ctx)
 
         # Propagate inside_langgraph_react from parent so that
@@ -576,7 +579,7 @@ def _on_tool_start(self, run: Run) -> None:
             rd = _RunData(
                 run_kind="tool",
                 span=invocation.span,
-                context=set_span_in_context(invocation.span)
+                context=otel_context.get_current()
                 if invocation.span
                 else None,
                 invocation=invocation,
@@ -634,7 +637,7 @@ def _on_retriever_start(self, run: Run) -> None:
             rd = _RunData(
                 run_kind="retriever",
                 span=invocation.span,
-                context=set_span_in_context(invocation.span)
+                context=otel_context.get_current()
                 if invocation.span
                 else None,
                 invocation=invocation,
@@ -724,7 +727,7 @@ def _enter_react_step(self, agent_run_id: UUID) -> None:
         self._handler.start_react_step(inv, context=agent_rd.original_context)
 
         step_ctx = (
-            set_span_in_context(inv.span)
+            otel_context.get_current()
             if inv.span
             else agent_rd.original_context
         )