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graph() caches the built graph per context so repeated runs skip re-evaluating every node's flag. The build also created the graph's track data, run id included, so every run for the same context reported the same runId on its $ld:ai:graph:* events. Each run now copies the cached track data with a fresh runId and passes it to route and stream_route through their opts, so the node, handoff and graph-level events of one run share one id and the next run gets another. The flag evaluations stay cached.
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Summary
Running the same
graph()twice for the same context reported both runs under one run id, so separate runs looked like one in the$ld:ai:graph:*events.graph()caches the built graph per context so it doesn't re-evaluate every node's flag on each call. The run id was created in that build, so it was cached too. Each run now gets a fresh id. Every graph event within a run still shares it, and the flag evaluations stay cached.JS twin: launchdarkly/js-ai-sdk#109. Source branch:
fix/graph-run-id-per-run.Testing
test_graph_stream.py, for bothinvokeandstream: two runs on onegraph()instance and context get different ids, and all graph events in a run (node, handoff, success) share one. It fails on main.Note
Overview
Fixes duplicate
runIdacross separategraph()runs when the same instance and LD context reuse the cached graph build.Each
invoke/streamnow merges the cached build track payload with a new UUIDrunId, passes that copy on route options via_run_track_data, and uses it for handoff success/failure events inside the cached closures so analytics still group node, handoff, and invocation events per run without rebuilding the graph.Adds
TestGraphRunId(invoke + stream): two runs on onegraph()share one id within a run and get different ids across runs.Reviewed by Cursor Bugbot for commit 12ad1ff. Bugbot is set up for automated code reviews on this repo. Configure here.