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feat(gooddata-eval): grade takeaways the copilot leaves to the editor - #1928
The agentic document skill evaluation writes the takeaways the copilot leaves to the editor, the way the Publisher editor does, and grades the document with them. A no-op until gen-ai adds takeaway_editor_page_ids to the draft_document result: a draft without the field, or in v1, is graded as before.
PR 1 of 2 for LX-3246. The gdc-nas PR that makes the copilot leave takeaways to the editor stays a draft until this one merges.
What this implements
On a v2 draft that carries takeaway_editor_page_ids, the eval applies the editor's rule to every empty takeaway: one whose request matches the takeaway it replaces in the open document stays as that held it (empty, so no failure), every other one is written. It converts the draft to its declarative form, builds the request the editor sends, calls POST /api/v1/ai/workspaces/{ws}/takeaway as the chat turn's agent, writes the text into a copy of the part, then grades summaries and narrative. The field is checked against the pages the editor writes a takeaway on: a page the editor writes on that the draft does not list, and a listed page the editor writes nothing on, are failures.
Local stack, gen-ai with the copilot change, enableGenAiReportTakeaways on, real LLM judge:
[lx3246-flag-on] judge: LLM judge
[lx3246-flag-on] verdict: PASSED
[lx3246-flag-on] detail: {
"document_summaries_present": true,
"document_narrative_judged": true,
"summaries_from_data": 0,
"takeaways_by_editor": 3,
"judge_reasoning": "The actual output satisfies all criteria, with each page's summary addressing the requested content and providing takeaways specific to the West region's revenue in 2025.",
"failures": []
}
[lx3246-flag-on] count POST .../takeaway: 3
One of the three request bodies, at this head:
{"instructions": {"document": "Write for business leaders, highlighting the most important revenue movements and concentration points.", "slot": "Highlight the strongest and weakest periods, overall direction, and any notable shifts in the revenue trend."}, "data": {"visualizations": [{"visualizationId": "revenue_trend", "filters": [{"absoluteDateFilter": {"dataset": {"identifier": {"id": "date", "type": "dataset"}}, "from": "2025-01-01", "to": "2025-12-31"}}, {"positiveAttributeFilter": {"label": {"identifier": {"id": "region", "type": "label"}}, "in": {"values": ["West"]}}}]}], "filterContext": []}}
Same image, flag off: the copilot writes the takeaways itself and the eval makes no request:
$ make -C packages/gooddata-eval format lint type-check
146 files already formatted
All checks passed!
All checks passed!
$ TEST_ENVS=py314 make -C packages/gooddata-eval test
======================= 2841 passed, 1 skipped in 25.22s =======================
Decisions
The request is the editor's, not the copy in the spec.
Every visualization on the page in layout order, each under its own filters (the period on its date dataset unless it ignores the period, a document date filter on that dataset in its place, then the document attribute and text filters, with the rules gen-ai's report_filter_to_afm applies), filterContext: [], the slot and document instructions. Inspect core/agentic/_editor_takeaways.py.
No maxCharacters: the editor derives it from layout geometry, so the endpoint default applies. A judge failing on length would point here.
The takeaway request carries the run's agent_id, as the editor sends the agent of the chat turn that drafted the takeaway.
Text variables in instructions are sent as written.
A takeaway is written by the editor's own rule, not because its page is listed.
The editor never reads takeaway_editor_page_ids: an empty takeaway whose request matches the version it replaces keeps that version's text (or stays empty), every other one is generated. The eval applies that rule, with the version it replaces taken from user_context, and checks the list against it, so a change in what gen-ai lists is a failure here and not a silently graded document. The request equality does not include maxCharacters, which the eval does not send. _editor_takeaways.py names the editor commit it mirrors.
A transient endpoint failure leaves the run ungraded; any other endpoint failure raises.
429, 5xx and transport failures leave the run out of pass@K and keep pass^K from holding, as a judge failure does, unless the run already failed another check; they are reported under request_errors, apart from judge_errors, as document_takeaway does. A 404 whose detail says a chart does not exist or is not available to AI fails that run, with the detail in the failure. Any other 404 (flag off, unknown agent) or 422 raises out of run_agentic_document_skill: the eval cannot tell a draft fault from a request-builder fault. The runner records the item with no runs, and its other runs are discarded. The endpoint's detail is in the message. Inspect _fill_editor_takeaways and _EditorFill.ungraded_error in core/agentic/document_skill.py.
The fill runs only on items whose fixture states a narrative, and its time counts in agent_s.
The takeaway endpoint is gen-ai too, and a reader waits for it before the document is complete, so a document item's agent latency now includes the slowest takeaway request, as the editor starts them all at once. A document_takeaways_by_editor score counts the takeaways written.
What comes next
The gdc-nas copilot change for LX-3246, which adds takeaway_editor_page_ids, merges after this.
maxCharacters from layout geometry, if the judge starts failing on length.
Evaluations can fill unwritten takeaways on designated pages in version 2 documents before narrative grading. Generated text is included in the evaluation, and results report the number of takeaways written.
Empty takeaways can be exempted when they match the open document’s period and editor request.
Bug Fixes
Temporary takeaway-service errors are distinguished from other failures. If a temporary error is the only unresolved check, the run is marked ungraded and narrative grading is skipped.
Documentation
Evaluation details now include request errors when a document takeaway request fails.
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The document-skill evaluator now fills unwritten v2 takeaways designated for the editor before narrative grading. It records fill outcomes, applies transient-error handling, and reports editor-written takeaway counts and request errors.
The builder converts document filters, widget date filters, and instructions into takeaway inputs. It handles unsupported inputs and duplicate visualization placements. Tests cover these conversions and related cases.
Request and classify endpoint errors packages/gooddata-eval/src/gooddata_eval/core/takeaway/http_client.py, packages/gooddata-eval/src/gooddata_eval/core/takeaway/evaluate.py, packages/gooddata-eval/src/gooddata_eval/core/timing.py, packages/gooddata-eval/tests/test_takeaway_client.py
TakeawayClient.request accepts a TakeawayInput. The shared transient-error classifier replaces the local classifier in takeaway evaluation. The timing comment includes time spent in the takeaway endpoint.
Fill editor-designated takeaways packages/gooddata-eval/src/gooddata_eval/core/agentic/document_skill.py, packages/gooddata-eval/tests/test_agentic_document_skill.py
For eligible v2 drafts, the evaluator requests unwritten takeaways on editor-designated pages and writes successful response text into a copied document part before evaluation. Tests cover request data, exclusions, endpoint responses, and failures.
Record grading and fill outcomes packages/gooddata-eval/src/gooddata_eval/core/agentic/document_skill.py, packages/gooddata-eval/tests/test_agentic_document_skill.py, packages/gooddata-eval/README.md
Fill errors affect grading and ungraded-run handling. Results and evaluation details report editor-written counts and separate judge errors from request errors. The README describes request-error diagnostics.
Drafts that do not list editor pages can now pass the takeaway-presence check in some rework cases, where they previously failed. Computing the exemptions only when the draft names editor pages restores the intended behavior. The risk is limited to eval grading accuracy.
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A rabbit checks the chart dates bright Then packs each filter just right Takeaway words hop into place While grading follows at a steady pace Errors leave a trace behind And editor counts are easy to find
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only still-valid issues, skip the rest with a brief reason, keep changes
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1329-1330: Trivial · Maintainability & Code Quality · Low value
Update the README for the judge/request error split.
judge_errors now lists only judge failures, and takeaway-endpoint failures go to the new request_errors field. packages/gooddata-eval/README.md (lines 279-282) still says ungraded agentic runs appear as unscored_runs / judge_errors. It does not mention request_errors. A reader of the report will not find request-failed runs under judge_errors. Add request_errors to that paragraph.
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Review comment at
@packages/gooddata-eval/src/gooddata_eval/core/agentic/document_skill.py around
lines 1329 - 1330:
Update the README paragraph describing ungraded agentic runs to include
request_errors alongside unscored_runs and judge_errors. Keep the explanation
clear that judge_errors contains judge failures, while takeaway-endpoint
failures are reported in request_errors.
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Review comments at
@packages/gooddata-eval/src/gooddata_eval/core/agentic/document_skill.py:
- Around line 1329-1330: Update the README paragraph describing ungraded agentic
runs to include request_errors alongside unscored_runs and judge_errors. Keep
the explanation clear that judge_errors contains judge failures, while
takeaway-endpoint failures are reported in request_errors.
---
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packages/gooddata-eval/README.md
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`TakeawayClient.request(ti)` holds the body, post and retry code that
`ask(item)` had, and `ask` now validates the item's `takeaway_input`
and delegates, so a caller without a `DatasetItem` can request a
takeaway. The transient-or-setup split moves from
`core/takeaway/evaluate.py` to the client module as `is_transient`, so
the agentic document skill can share it without importing the takeaway
entry point. No behaviour change for `document_takeaway`.
jira: LX-3246
risk: low
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Actionable comments posted: 1
Fix comments: Fix CodeRabbit comments on this PR
Prompt to fix all issues
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Review comments at
@packages/gooddata-eval/src/gooddata_eval/core/agentic/document_skill.py:
- Around line 1222-1223: Update the exemption logic around _editor_page_ids and
_saved_empty_takeaways so saved empty takeaways are exempt only when the draft
provides a non-empty editor page ID list; absent or empty lists must retain the
existing grading behavior. Add coverage to
test_a_draft_that_leaves_nothing_to_the_editor_is_graded_as_before for an open
v2 document containing the same empty takeaway.
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The eval fills by gen-ai's list; the editor decides on its own. The editor never reads takeaway_editor_page_ids. It decides takeaway by takeaway:
an empty takeaway whose request matches the version it replaces gets that version's text back, or stays empty;
every other empty takeaway is generated.
Here the fill follows the list, and _saved_empty_takeaways approximates the editor's rule for pages outside it. Where the two disagree, the eval grades a document no reader sees:
If gen-ai lists a page whose takeaway the editor keeps empty, the eval writes fresh text and the run passes. A wrong list goes unnoticed.
The period changes, but a page's charts ignore it. The request is unchanged, so gen-ai leaves the page unlisted and the editor keeps it empty, yet document_skill.py:926 refuses the exemption. test_an_empty_takeaway_fails_when_the_open_document_had_another_period pins this; its page3 has no date dataset.
With nothing listed, the same page3 passes when some other page is listed and fails when none is (:1224). The list is [] both with the flag off and when gen-ai leaves empty only the takeaways the editor keeps empty, so the eval can't tell these apart.
Was grading on the list, rather than applying the editor's rule and checking the list against it, settled for a reason I'm missing? The rule needs only the request builder this PR already has, and gen-ai could then change what the list means without changing the eval.
Say what it mirrors._editor_takeaways.py copies the editor's takeaway request without saying which editor version it matches. The agent change (inline comment) is the first drift; naming the version it was checked against tells the next person what to re-check.
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Since Nov 9, the editor (on master, not released yet) writes the takeaways the copilot leaves as the agent of the chat turn that drafted them: it sends that turn's agentId with each takeaway request. Here the client gets no agent and editor_takeaway_input sets none, so under --agent-id the copilot runs as that agent and its takeaways run as the default one. The description's "the editor sends none" was true before that change.
Could agent_id, which is already in scope here, go through _fill_editor_takeaways onto each TakeawayInput? The field is there, and _request_body already sends it as agentId.
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Yes, you are right: the editor's copilot path passes the turn's agentId to each takeaway request (useDocumentCopilot), and the old description was out of date. agent_id now goes from run_agentic_document_skill through _execute_single_document_run onto every TakeawayInput the fill sends, so under --agent-id the takeaways run as the same agent as the copilot (04eec40). A test pins it, and the PR body no longer says the editor sends none.
🤖 Posted by pub-ops, an AI agent working on behalf of @chrisbonilla95.
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One gen-ai feature flag turns on both the takeaway endpoint and the copilot's takeaway_editor_page_ids. So once this loop runs, a flag-off 404 should not happen. The 404 that can happen is gen-ai's answer for a chart in the draft that does not exist or is not available to AI, for example a rework that keeps a chart since excluded from AI. The copilot got that wrong, and the reader sees the editor fail on it. Here it aborts the item and throws away the other runs.
Is aborting the item what you want in that case? Failing the run with gen-ai's detail, the way the noData branch does, would keep the other K-1 runs and count it against the copilot.
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No, aborting the item was not what we want for that case. A 404 whose detail says the chart does not exist or is not available to AI is now a failure of that run, with gen-ai's detail in the failure message, so the other K-1 runs are kept and it counts against the copilot (04eec40). I matched on the body, not on the bare status: gen-ai answers 404 for three causes (flag off, an agent that does not exist, an unavailable chart), and only the last is the copilot's. A flag-off or unknown-agent 404 still stops the item, because that is a setup problem and not a result.
🤖 Posted by pub-ops, an AI agent working on behalf of @chrisbonilla95.
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Two filter cases come out differently from what the editor sends. Its filters go through sdk-model's dashboardDateFilterToDateFilterByDateDataSet and tiger's FilterConverter.
A document date filter that takes the period's place loses emptyValueHandling, and a relative one also loses boundedFilter. Both change which rows the chart covers.
A text filter "is" with no values becomes positiveAttributeFilter with an empty in here (line 146). Tiger drops an arbitrary filter with no values, so the editor writes that takeaway over unfiltered data.
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Not deliberate, both fixed in 49e9335. A document date filter that takes the period's place now keeps its emptyValueHandling, and a relative one also keeps its boundedFilter (both are fields of gen-ai's AbsoluteDateFilterBody / RelativeDateFilterBody). A text filter with no values is now dropped, as tiger does, instead of becoming a positiveAttributeFilter with an empty in. Tests cover both, and the module docstring now says which editor commit it mirrors.
🤖 Posted by pub-ops, an AI agent working on behalf of @chrisbonilla95.
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The editor starts every copilot-left takeaway at once, without waiting for the one before. With the flag off, gen-ai writes them concurrently too. So the reader waits about as long as the slowest one. Here they run in sequence, and the whole fill, retry backoff included, goes into agent_s. A document with N listed pages reports roughly N takeaway calls where the reader waits for one.
Would issuing them concurrently, or adding the slowest call instead of the sum, fit what you want agent_s to mean?
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Agreed, agent_s should be what the reader waits for. The editor starts every takeaway at once (toGenerate.forEach(generateTakeaway)), so the fill now adds the slowest single request, retries included, instead of the sum (04eec40). I kept the requests sequential rather than concurrent: that keeps the run order and failure order deterministic, and the eval does not need to load gen-ai harder to report the right wait. The timer log shows both the total and the slowest.
🤖 Posted by pub-ops, an AI agent working on behalf of @chrisbonilla95.
`editor_takeaway_input(document, page, takeaway)` reproduces gdc-ui's
`documentTakeawayRequest` for a v2 document: every visualization on the
page in layout order, deduplicated by id and filters, each under the
period on its own date dataset (or a document date filter with both ends
on that dataset in its place, or none when the widget ignores the period
or has no date dataset) plus the document's attribute and text filters,
`filterContext` empty, and the takeaway's and the document's
instructions trimmed. Pure, no network.
The document filters follow gen-ai's `report_filter_to_afm` rule for
rule: an attribute filter reads its elements from `uris`, else from
`values`, the shape the converter writes; a text filter on whole values
becomes an element filter and one on a fragment a
`matchAttributeFilter`; an exclusion of nothing and any other kind
(measure value filters) are left out, since the renderer draws no chart
differently for them. The function returns a reason instead when the
page has no visualization or a filter has no AFM form (an empty positive
selection, an unknown match operator or date granularity).
`maxCharacters` is left to the endpoint default and text variables are
sent as written.
jira: LX-3246
risk: low
When a v2 draft's `draft_document` result lists pages in
`takeaway_editor_page_ids` and the fixture states a narrative, the run
writes each unwritten takeaway on those pages through the takeaway
endpoint, the way the editor does, and grades the document with that
text. The copilot sends the document as code, so each request is built
from its declarative form (`aac_document_to_declarative`), which is
what the editor reads: the period lands on each chart's own date
dataset and the document filters arrive in the converter's shape. A
draft that does not convert fails the run with the converter's reason.
The published `document_part` stays the one the copilot sent. An empty
takeaway on any other page still fails as before, and a v1 draft or a
v2 draft without the field (every draft today) makes no request and is
graded unchanged.
A takeaway the endpoint does not write (`noData`, empty text) or whose
request the eval cannot build stays empty and adds a failure line that
says why. A non-transient 4xx (the takeaway flag off answers 404)
raises as a setup problem. A transient failure after the client's
retries leaves that takeaway empty and the fill goes on; the run is
ungraded (`fill_error`, like a judge error: out of pass@K and keeping
pass^K from holding) only when nothing but transient failures left a
takeaway empty, and otherwise fails on the summaries check. An item
whose every run is ungraded raises naming both sources. The count of
written takeaways is published as the diagnostic
`document_takeaways_by_editor` score and in the run detail. The
endpoint time counts toward `agent_s`.
jira: LX-3246
risk: low
@Mara3l on your review of the grading: you are right, and it is changed in 04eec40 (the request builder in 49e9335).
I checked the editor's copilotTakeaways and useDocumentCopilot on gdc-ui master (7e0f3719ca2): it never reads takeaway_editor_page_ids. An empty takeaway whose request matches the version it replaces keeps that version's text or stays empty, every other empty one is generated. The eval now does the same for every empty takeaway of a v2 draft that carries the field:
The open document's exemption no longer depends on the list, and no longer on the period being equal: the request already holds the period on each chart's date dataset, so a period change that no chart uses leaves the request equal and the takeaway empty (test_a_new_period_changes_only_the_request_of_a_takeaway_whose_chart_uses_it).
The fill writes every other empty takeaway, so an empty list no longer decides whether page3 passes.
The list is checked against that rule: a page the editor writes on that the draft does not list, and a listed page the editor writes nothing on, each fail with the page named.
Left out on purpose: the editor's request equality also compares maxCharacters and instructions with their variables resolved, which the eval does not send or resolve, so a takeaway the editor would regenerate only because its box changed size is still kept empty here.
_editor_takeaways.py now names the gdc-ui commit it mirrors, for the next person to re-check.
🤖 Posted by pub-ops, an AI agent working on behalf of @chrisbonilla95.
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The agentic document skill evaluation writes the takeaways the copilot leaves to the editor, the way the Publisher editor does, and grades the document with them. A no-op until gen-ai adds
takeaway_editor_page_idsto thedraft_documentresult: a draft without the field, or in v1, is graded as before.PR 1 of 2 for LX-3246. The gdc-nas PR that makes the copilot leave takeaways to the editor stays a draft until this one merges.
What this implements
On a v2 draft that carries
takeaway_editor_page_ids, the eval applies the editor's rule to every empty takeaway: one whose request matches the takeaway it replaces in the open document stays as that held it (empty, so no failure), every other one is written. It converts the draft to its declarative form, builds the request the editor sends, callsPOST /api/v1/ai/workspaces/{ws}/takeawayas the chat turn's agent, writes the text into a copy of the part, then grades summaries and narrative. The field is checked against the pages the editor writes a takeaway on: a page the editor writes on that the draft does not list, and a listed page the editor writes nothing on, are failures.Local stack, gen-ai with the copilot change,
enableGenAiReportTakeawayson, real LLM judge:One of the three request bodies, at this head:
Same image, flag off: the copilot writes the takeaways itself and the eval makes no request:
Unit gates:
Decisions
Every visualization on the page in layout order, each under its own filters (the period on its date dataset unless it ignores the period, a document date filter on that dataset in its place, then the document attribute and text filters, with the rules gen-ai's
report_filter_to_afmapplies),filterContext: [], the slot and document instructions. Inspectcore/agentic/_editor_takeaways.py.maxCharacters: the editor derives it from layout geometry, so the endpoint default applies. A judge failing on length would point here.agent_id, as the editor sends the agent of the chat turn that drafted the takeaway.A takeaway is written by the editor's own rule, not because its page is listed.
The editor never reads
takeaway_editor_page_ids: an empty takeaway whose request matches the version it replaces keeps that version's text (or stays empty), every other one is generated. The eval applies that rule, with the version it replaces taken fromuser_context, and checks the list against it, so a change in what gen-ai lists is a failure here and not a silently graded document. The request equality does not includemaxCharacters, which the eval does not send._editor_takeaways.pynames the editor commit it mirrors.A transient endpoint failure leaves the run ungraded; any other endpoint failure raises.
429, 5xx and transport failures leave the run out of pass@K and keep pass^K from holding, as a judge failure does, unless the run already failed another check; they are reported under
request_errors, apart fromjudge_errors, asdocument_takeawaydoes. A 404 whosedetailsays a chart does not exist or is not available to AI fails that run, with thedetailin the failure. Any other 404 (flag off, unknown agent) or 422 raises out ofrun_agentic_document_skill: the eval cannot tell a draft fault from a request-builder fault. The runner records the item with no runs, and its other runs are discarded. The endpoint'sdetailis in the message. Inspect_fill_editor_takeawaysand_EditorFill.ungraded_errorincore/agentic/document_skill.py.The fill runs only on items whose fixture states a narrative, and its time counts in
agent_s.The takeaway endpoint is gen-ai too, and a reader waits for it before the document is complete, so a document item's agent latency now includes the slowest takeaway request, as the editor starts them all at once. A
document_takeaways_by_editorscore counts the takeaways written.What comes next
takeaway_editor_page_ids, merges after this.maxCharactersfrom layout geometry, if the judge starts failing on length.🤖 Generated with Claude Code
https://claude.ai/code/session_01Qg3jRWLKvvYJAQWA8mpQAm
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