zeekay
1b367e2b62
The tree was a debranded snapshot of upstream taken around 2026-02-20, and upstream has moved about five months since. This replaces it with upstream master, mechanically re-derived: bin/debrand does the rename, and the pipeline and squashed migrations are restored from the shipped tree. Not a merge. The previous import replaced the tree wholesale in a single commit, so there is no shared content history to merge against. Reproducing the rename on the new tree is what actually converges. What survives: .hanzo/workflows, the Dockerfiles and bin/docker* entrypoints, compose files, LLM.md, and insights/migrations. The squashed initial migration is load-bearing — the live database records it by name, so upstream's ~918 individual migrations cannot come back. Nine products are dropped as unreferenced. Twenty-one more that we do not run are kept anyway because the core app still imports them; unpicking those is a refactor and does not belong in a rebase. This base does not build yet, and the reasons are not in the rename: upstream now wants Python 3.13.13 against our 3.12.12 and Django 5.2 against our 4.2, and the dependency manifests still name upstream packages that we republish under our own names. Those are decisions, not renames.
2.2 KiB
List the persons behind a paths insight — either everyone who traversed the path, or those at one specific node/edge.
Pair this with query-paths: first run the paths query to see the flows (each result row is an edge source → target with a user count), then call this tool with the same paths query as source.
Two modes:
1. Everyone on the path (A → B). Set startPoint / endPoint on the source pathsFilter and leave the path keys unset. Returns every actor whose journey matches that start/end constraint. Use this for "who went from a.com to b.com?".
2. Actors at a specific point. Each node in the path graph has a key of the form <stepIndex>_<value> (e.g. "3_https://example.com/checkout"). The source and target fields of a query-paths result row are these keys — copy them verbatim. Set on the source pathsFilter:
pathEndKey— persons who arrived at that node (use a row'starget).pathStartKey— persons who departed from that node (use a row'ssource).- Set both
pathStartKey+pathEndKeyto pin a single edge (the actors behind onesource → targetcount). pathDropoffKey— persons who dropped off at that node. Mutually exclusive with the other two.
Selectors:
includeRecordings: defaults totrue. Set tofalseto skip fetching matched session recordings (faster if recordings are not needed).
Response:
Each returned row contains distinct_id, name, email, and event_count (number of matching events for that actor). When includeRecordings is true (the default), a recordings column is also returned with Insights replay URLs. Results are limited to the top 100 actors ordered by event count.
Guidance:
- Keep the
sourcepaths query minimal — only include the filters needed to define the same population the user is asking about. - The path keys come straight from a
query-pathsresult row'ssource/target; do not hand-construct them. pathReplacementsandshowFullUrlsare not exposed — they don't change which actors are returned (showFullUrlsis display-only;pathReplacementsis covered bylocalPathCleaningFilters).- For large result sets, narrow the source (start/end point, date range, filters) rather than expecting more rows.