I’m working on comparing two different approaches for my project. One uses a single agent system and the other is a multi-agent setup built with LangGraph. I added proper logging to both so I can track everything in LangSmith.
The multi-agent version shows up correctly in the LangSmith interface with all the trace data visible. However, when I try to programmatically access the node information through the Run object during evaluation, I hit a wall. I can reach the Planner and ExecutionTeam nodes without problems, but that’s where it stops. These nodes appear to have no child runs and show empty outputs when accessed via code, even though the web interface clearly displays their data and child processes.
Has anyone encountered this before? Am I missing something in how I’m accessing the run data, or could this be a known limitation?
Classic data pipeline headache - I’ve been there so many times. LangSmith isn’t really the problem here. You’re just using tools that weren’t built for complex multi-agent orchestration.
I used to slam my head against the same wall until I figured out the real fix is proper workflow automation. Stop fighting LangSmith’s API inconsistencies and timing issues. You need something that handles multi-agent coordination from the ground up.
What saved me was moving everything to Latenode. Set up workflows that automatically grab all your agent interactions, handle timing with proper wait conditions, and give you clean data access. No more parent-child relationship syncing nightmares.
Latenode orchestrates your LangGraph agents AND collects data in one pipeline. No polling, no missing child runs, no API timing headaches.
I’ve built setups where Latenode runs the entire multi-agent flow and structures all output data exactly how I need it. Way cleaner than reverse-engineering LangSmith’s data relationships.
I’ve hit this exact timing issue with LangGraph evaluations. The web interface has time to load all the nested run data, but programmatically you’re probably hitting the API before child runs link to their parents. Add a small delay before fetching your run data, or better - set up polling to check if the run’s actually done. Even when a run looks finished, the node relationships can take extra seconds to sync in LangSmith’s backend. Also check you’re using the right run ID. Sometimes the top-level ID is different from individual node IDs, and you need to walk through the hierarchy to get everything.
Sounds like a data consistency problem between LangSmith’s display and API. I’ve hit this before with complex graph structures - the trace looks complete but the API only returns partial data. It’s usually how LangSmith handles nested runs in multi-agent workflows. When nodes run in parallel or have messy dependencies, the API might grab the parent run before all child relationships are set up in the database. Try a different approach: don’t access child runs through the parent Run object. Instead, grab the individual node runs by their specific IDs. You can pull these IDs from the trace view and query them directly. This skips the parent-child relationship mess and usually gets you complete data. Also check you’re on the latest LangSmith client - they fixed some graph workflow data issues recently.
Yeah, this is a LangGraph issue with how runs nest in LangSmith. Hit the same problem last year building a multi-step workflow with conditional nodes.
LangGraph creates this complex execution tree, but LangSmith’s API doesn’t expose the full hierarchy properly. Your parent nodes (Planner, ExecutionTeam) are container nodes that spawn other processes, but the API treats them like leaf nodes.
What worked for me: use the LangSmith client’s list_runs() method with the parent run ID as a filter instead of traversing the Run object tree:
This pulls all child runs for that node directly from the database instead of relying on object relationships that aren’t populating correctly.
Also check if you’re using await properly if this is async code. LangGraph’s async execution can mess up run linking if you don’t wait for everything to complete before hitting the API.
The web interface works because it’s doing these database queries behind the scenes. The Run object you get programmatically is just a snapshot that might be incomplete.
been debugging this langraph issue for weeks. the run object won’t populate child data right when nodes run parallel or have complex dependencies. fixed it by ditching run object traversal - just use the trace_id to query langsmith directly and filter by node names. way more reliable than waiting for the api to sync everything.
I’ve hit this exact issue with complex LangGraph workflows. It’s not timing or API delays - it’s a serialization problem. LangSmith can’t properly serialize outputs from container nodes that manage other agents. When your Planner and ExecutionTeam nodes coordinate multiple sub-agents, the data structures get too complex or contain non-serializable objects. The web interface shows the data fine because it uses different rendering logic, but the API returns empty outputs since serialization fails silently. Check if your node outputs contain agent instances, complex state objects, or circular references - that’s what’s breaking it. I fixed mine by making sure each node only returns simple, serializable data and moved complex objects to separate storage. Also double-check that your LangGraph node definitions aren’t accidentally returning the entire agent state as output.