Troubleshooting trace nesting

versioned_docs/version-2.0/how_to_guides/tracing/nest_traces.mdx

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+sidebar_position: 21
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+import {
+  CodeTabs,
+  PythonBlock,
+  TypeScriptBlock,
+} from "@site/src/components/InstructionsWithCode";
+import { RegionalUrl } from "@site/src/components/RegionalUrls";
+
+# Troubleshoot trace nesting
+
+When tracing with the LangSmith SDK, LangGraph, and LangChain, tracing should automatically propagate the correct context so that code executed within a parent trace will be rendered in the expected location in the UI.
+
+If you see a child run go to a separate trace (and appear on the top level), it may be caused by one of the following known "edge cases".
+
+## Python
+
+The following outlines common causes for "split" traces when building with python.
+
+### Context propagation using asyncio
+
+When using async calls (especially with streaming) in Python versions < 3.11, you may encounter issues with trace nesting. This is because Python's `asyncio` only [added full support for passing context](https://docs.python.org/3/library/asyncio-task.html#asyncio.create_task) in version 3.11.
+
+#### Understanding the Issue
+
+LangChain and LangSmith SDK use [contextvars](https://docs.python.org/3/library/contextvars.html) to propagate tracing information implicitly. In Python 3.11 and above, this works seamlessly. However, in earlier versions (3.8, 3.9, 3.10), `asyncio` tasks lack proper `contextvar` support, which can lead to disconnected traces.
+
+#### Resolution Steps
+
+1. **Upgrade Python Version (Recommended)**
+   If possible, upgrade to Python 3.11 or later for automatic context propagation.
+
+2. **Manual Context Propagation**
+   If upgrading isn't an option, you'll need to manually propagate the tracing context. The method varies depending on your setup:
+
+   a) **Using LangGraph or LangChain**
+   Pass the parent `config` to the child call:
+
+   ```python
+   import asyncio
+   from langchain_core.runnables import RunnableConfig, RunnableLambda
+
+   @RunnableLambda
+   async def my_child_runnable(
+                 inputs: str,
+                 # The config arg (present in parent_runnable below) is optional
+                 ):
+       yield "A"
+       yield "response"
+
+   @RunnableLambda
+   async def parent_runnable(inputs: str, config: RunnableConfig):
+       # highlight-next-line
+       async for chunk in my_child_runnable.astream(inputs, config):
+           yield chunk
+
+   async def main():
+       return [val async for val in parent_runnable.astream("call")]
+
+   asyncio.run(main())
+   ```
+
+   b) **Using LangSmith Directly**
+   Pass the run tree directly:
+
+   ```python
+   import asyncio
+   import langsmith as ls
+
+   @ls.traceable
+   async def my_child_function(inputs: str):
+       yield "A"
+       yield "response"
+
+   @ls.traceable
+   async def parent_function(
+                 inputs: str,
+                 # The run tree can be auto-populated by the decorator
+                 run_tree: ls.RunTree,
+             ):
+       # highlight-next-line
+       async for chunk in my_child_function(inputs, langsmith_extra={"parent": run_tree}):
+           yield chunk
+
+   async def main():
+       return [val async for val in parent_function("call")]
+
+   asyncio.run(main())
+   ```
+
+   c) **Combining Decorated Code with LangGraph/LangChain**
+   Use a combination of techniques for manual handoff:
+
+   ```python
+   import asyncio
+   import langsmith as ls
+   from langchain_core.runnables import RunnableConfig, RunnableLambda
+
+   @RunnableLambda
+   async def my_child_runnable(inputs: str):
+       yield "A"
+       yield "response"
+
+   @ls.traceable
+   async def my_child_function(inputs: str, run_tree: ls.RunTree):
+       # highlight-next-line
+       with ls.tracing_context(parent=run_tree):
+           async for chunk in my_child_runnable.astream(inputs):
+               yield chunk
+
+   @RunnableLambda
+   async def parent_runnable(inputs: str, config: RunnableConfig):
+       # @traceable decorated functions can directly accept a RunnableConfig when passed in via "config"
+       # highlight-next-line
+       async for chunk in my_child_function(inputs, langsmith_extra={"config": config}):
+           yield chunk
+
+   @ls.traceable
+   async def parent_function(inputs: str, run_tree: ls.RunTree):
+       # You can set the tracing context manually
+       # highlight-next-line
+       with ls.tracing_context(parent=run_tree):
+           async for chunk in parent_runnable.astream(inputs):
+               yield chunk
+
+   async def main():
+       return [val async for val in parent_function("call")]
+
+   asyncio.run(main())
+   ```
+
+### Context propagation using threading
+
+It's common to start tracing and want to apply some parallelism on child tasks all within a single trace. Python's stdlib `ThreadPoolExecutor` by default breaks tracing.
+
+#### Understanding the Issue
+
+Python's contextvars start empty within new threads. Here are two approaches to handle maintain trace contiguity:
+
+1. **Using LangSmith's ContextThreadPoolExecutor**
+
+   LangSmith provides a `ContextThreadPoolExecutor` that automatically handles context propagation:
+
+   ```python
+   from langsmith.utils import ContextThreadPoolExecutor
+   from langsmith import traceable
+
+   @traceable
+   def outer_func():
+       with ContextThreadPoolExecutor() as executor:
+           inputs = [1, 2]
+           r = list(executor.map(inner_func, inputs))
+
+   @traceable
+   def inner_func(x):
+       print(x)
+
+   outer_func()
+   ```
+
+2. **Manually providing the parent run tree**
+
+   Alternatively, you can manually pass the parent run tree to the inner function:
+
+   ```python
+   from langsmith import traceable, get_current_run_tree
+   from concurrent.futures import ThreadPoolExecutor
+
+   @traceable
+   def outer_func():
+       rt = get_current_run_tree()
+       with ThreadPoolExecutor() as executor:
+           r = list(
+               executor.map(
+                   lambda x: inner_func(x, langsmith_extra={"parent": rt}), [1, 2]
+               )
+           )
+
+   @traceable
+   def inner_func(x):
+       print(x)
+
+   outer_func()
+   ```
+
+   In this approach, we use `get_current_run_tree()` to obtain the current run tree and pass it to the inner function using the `langsmith_extra` parameter.
+
+Both methods ensure that the inner function calls are correctly aggregated under the initial trace stack, even when executed in separate threads.