[Discover] Fix jest tests of unified histogram pr #2
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
davismcphee
approved these changes
Nov 5, 2022
davismcphee
pushed a commit
that referenced
this pull request
Nov 7, 2022
* Misc enhancements following PR comments * Adding functional tests * Fixing types * Fixing tests * Removing unnecessary Promise.all * Cleanup * Misc fixes and simplifications * Add missing tsconfig.json * [CI] Auto-commit changed files from 'node scripts/build_plugin_list_docs' * Add dependency to Actions plugin in tsconfig.json * Separate setup logic from start logic * Fix bulkEnqueueExecution params structure * Update README * Add UTs * Check license type >platinum for email notifications * Fix incorrect UTs * Import types when possible * Misc enhancements and code cleanup * Transform factory => provider, update start contract * Code cleanup, update README * Fix TS error * Fix CI types error * Address PR remarks * Address PR remarks #2 Co-authored-by: Ying Mao <[email protected]> Co-authored-by: kibanamachine <[email protected]>
davismcphee
pushed a commit
that referenced
this pull request
Nov 10, 2022
* Updated EUI to version 67.1.2. Updated instaces of ButtonColor from EUI to EuiButtonColor. * Updated to EuiCard instances that utilize the betaBadgeProps object to return an empty string instead of undefined when the label is unavailable * Removed two instances of the deprecated internetExplorerOnly() mixin * Updated two instances of the ButtonColor import to EuiButtonColor as is was renamed in PR elastic#6150 * Updated snapshots in Jest Test Suite #1 to account for EuiButton and EuiCard Emotion conversions. Updated snapshots for EuiTooltip as it now contains the new EuiToolTipAnchor component that replaced the tooltip anchor styles * Updated snapshots in Jest Test Suite #2 to account forEuiButton, EuiDescriptionList, EuiButtonIcon, and EuiBadge Emotion conversions. * Updated snapshots in Jest Test Suite #3 to account for EuiDescriptionList, EuiButton, and EuiBadge Emotion conversions. Updated snapshots for EuiTooltip as if now contains the new EuiTooltipAnchor component that replaced the tooltop anchor styles * Updated snapshots in Jest Test Suite #4 to account for EuiButton Emotion conversion. * Updated snapshots in Jest Test Suite #5 to account for EuiButton Emotion conversion. * Updated snapshots in Jest Test Suite #8 to account for EuiButtonIcon and EuiButton Emotion conversions. Updated snapshots for EuiTooltip as it now contains the new EuiTooltipAnchor component that replaced the tooltip anchor styles. * Updated snapshots in Jest Test Suite #9 to account for EuiFlyout and EuiButton Emotion conversions. * Updated snapshots in Jest Test Suite elastic#10 to account for EuiButton, EuiBadge, EuiButtonIcon, and EuiCard Emotion conversions. Updated snapshots for EuiToolTtip as it now contains the new EuiTooltipAnchor component that replaced the tooltip anchor styles * Updated instances of EuiButtonIconColor to use EuiButtonIconProps['color'] as it was removed in PR elastic#6150 * Updated tests that target EuiButton to simulate click events to target a generic button to prevent undefined click event errors * Updated snapshots in Jest Test Suite #1 to account for EuiButton and EuiCard Emotion conversions * Added the EuiFlyout mixins and variables to Lens Sass file as EuiFlyout has been converted to Emotion and the Sass styles are no longer available in EUI * Added the EuiCallOutTypes variable to Step Progress Sass file as EuiCallOut has been converted to Emotion and the Sass styles are no longer available in EUI * Updated snapshots in Jest Test Suite #2 to account for recent Emotion conversions. Updated snapshots in server_status.test.tsx to render EuiBadge before checking the snapshots to reduce the snapshot churn caused by Emotion. Updated tests that target EuiButton to simulate click events to target a generic button to prevent undefined click event errors * [CI] Auto-commit changed files from 'node scripts/precommit_hook.js --ref HEAD~1..HEAD --fix' * Added imports for the added flyout mixin. Removed references to EuiCallOut mixin as the component has been converted to Emotion and is no longer available for use. * Updated unit tests and snapshots in Jest Test Suite elastic#10. Updated snaphshots to account for EuiBadge, EuiDescriptionList, EuiFlyout, and EuiCard Emotion conversions. Updated snapshots for EuiTooltip as it now contains the new EuiTooltipAnchor component that replaced the tooltip anchor styles. Updated tests that target EuiButton to simulate click events to target a generic button element to prevent undefined click event errors * Updated unit tests in Jest Test Suite elastic#11 that target EuiButton to simulate click events to target a generic button to prevent undefined click event errors * Updated unit tests in Jest Test Suite elastic#12 by updating tests that target EuiButton to simulate click events. Instead, these tests now target a generic button element to prevent undefined click event errors * Updated unit tests in Jest Test Suite #1 by updating tests that target EuiButton to simulate click events. Instead, these tests now target a generic button element to prevent undefined click event errors * Updated unit tests in Jest Test Suite #2 by updating tests that use EuiButton to simulate click events. Instead, these test have been updated to target a button element to prevent undefined click event errors. * [CI] Auto-commit changed files from 'node scripts/eslint --no-cache --fix' * Updated reference to mixins Sass file. Updated snapshots for Jest Test Suite #5 to account for EuiButton Emotion conversion. Updated unit tests that target EuiButton to simulate click events. These tests have been updated to target a button element to prevent undefined click event errors * Updated unit tests in Jest Test Suites 3, 7, 8, 13, and 14. Updated snapshot to account for EuiButton Emotion conversion. Updated tests that target EuiButton to simulate click events. These tests now target a generic button element to prevent undefined click event errors. Updated a few snapshots by adding .render() before checking the snapshot. This will prevent large snapshots coming from recent Emotion conversions * Updated snapshots in Jest Test Suite elastic#10 to account for the recent EuiButton Emotion conversion * Updated unit tests in Jest Test Suite #2 by editing tests that target EuiButton to simulate click events. These tests now target a button element in order to prevent undefinde click event errors * Updated snapshots in Jest Test Suite elastic#10 to account for EuiButton and EuiDescriptionList Emotion conversions * Updated test cases in Jest Test Suites 3, 7, and 8. Updated snapshots to account for EuiButton and EuiPagination Emotion conversions. Updated tests that target EuiButton to simulate click events. These tests now target a button element to prevent undefined click errors * Updated test cases in Jest Test Suite 14. Updated snapshots to account for EuiButton Emotion conversion. Opted to use .render() when updating a few snapshots to reduce the large length of snapshots caused by Emotion * [CI] Auto-commit changed files from 'node scripts/eslint --no-cache --fix' * Revised a change to betaBadgeProps to ensure that the label is available. If not, the value for the badge with be set to undefined. * Resolved two linting errors * Resolved two linting errors * Updated Jest unit tests in various suites. Updated snapshots to account for EuiButton Emotion conversion. Updated snapshots for EuiTooltip as it now contains the new EuiTooltipAnchor component that replaced the tooltip anchor styles. * Updated EuiFlyout in query_flyout.tsx to remove the onClick function from maskProps as it is no longer available. Updated this flyout to use ownFocus and not to close when the overlay mask is clicked. * Removed the use of EuiButtonIconColor in favor of EuiButtonIconProps['color'] * [CI] Auto-commit changed files from 'node scripts/eslint --no-cache --fix' * Updated Cypress test looking for strict equality on EuiPaginationButton class names to match a substring of the Emotion generated class name * Removed unneeded debugging code. Updated snapshots for various test suites to account for the recent EuiButton Emotion conversion * Updated a few EuiButton, EuiButtonEmpty, and EuiText components that set the color as ghost. The ghost color mode has been deprecated as of PR elastic#6150. These components now are wrapped in EuiThemeProvider with a dark colorMode to create the previous ghost color. * Resolved TS error with EuiCard betaBadgeProps * [CI] Auto-commit changed files from 'node scripts/eslint --no-cache --fix' * Remove references to now-removed EuiFlyout CSS classes/vars * Remove now-removed euiBadge className references - Convert directly to EuiBadge instead of using CSS - Remove confusing and now-possibly-irrelevant CSS badge overrides - left/right icons are now set via JSX and not via flex-direction * Pre-emptively fix various euiOverlayMask CSS overrides - this data attr isn't technically in yet but will be once elastic/eui#6289 merges - at the very least this isn't breaking any more than it currently already is! * Update to v67.1.3 * v67.1.4 * Resolved test failing test case in Security/Manage/Blocklist. The test did not remove focus from the last combo box in the form, which didn't allow the disbaled attribute to be removed from the flyout submit button. I've updated the mock file for Blocklist to return focus to the first form element in the flyout to allow the disabled attribute to be removed. * Updated snapshots to account for the recent EuiText Emotion conversion * Fix Log's custom tooltips relying on EuiTooltip classNames that no longer exist * Fix Vega vis custom tooltips relying on EuiTooltip classNames that no longer exist - this one is trickier than Log's as it's not using React, so we need to use Emotion's Global to set a static className * Convert remaining vega_vis.scss to Emotion - as an example of how other global + non global styles could be handled in the future * Fix references to removed `euiPaginationButton-isActive` className - use aria-current attribute instead * Added missing EuiFlyoutAnimation keyframes for EuiFlyout. This resolved test that failed because they used onAnimationEnd because the FlyoutAnimation could not be found. * Reolved Jest Tests in suites 1 and 5. Updated snapshots to account for the recent EuiButton Emotion conversion. Updated snapshots for EuiToolTip as it now contains the new EuiToolTipAnchor component that replaced the tooltip anchor styles. * iterate on rules_list.test.tsx * bump eui to v67.1.5 * Updatde snapshots for jest test suites to account for the recent EuiButton, EuiOverlayMask, EuiTooltip, and EuiBadge Emotion conversions * Resolved failing security test by updating the target element for CONNECTOR_TITLE. EuiCard has recently been converted to Emotion and the card title is no longer wrapper in a span. * Resolved failing test case in Runtime Fields. The modify runtime field test was failing because the combobox responsbible for adding and updating scripts was not appearing. The textbox did not appear because the shared setFieldScript function targets and toggles the script textbox when opening the flyout. When a runtime field is being modified, the toggle is already active and using the shared function will trigger the toggle again (losing access to the script textbox). Also resolved an issue that prevented the warning EuiCallout to appear when changing the type of a runtime field from its original type. Resolved this by adding an enter keypress at the end of setFieldType function to confirm the type selection, thus triggering the EuiCallout * Resolved two tests that were failing in Lens. These test were failing because they were checking for equality in class names that no longer exist within EuiButtonGroup as it was recently converted to Emotion. These tests were updated to check for a substring of the new and longer class name * Quick fix in test case failing because of misspelling in data-test-sub * Updated snapshot for Jest test case as EuiButton as recently been converted to Emotion * Removed console.log statement. Oops! * Resolved a failing test case in Lens. They were failing because they were checking for equality in class names that no longer exist within EuiButtonGroup as it was recently converted to Emotion. These tests were updated to check for a substring of the new and longer class name. Updated a Security test case by giving a target button the data-test-subj attribute for easier querying * Removed reference to EuiFlyout mixin as it has been converted to Emotion. Updated the reference to an interal copy of EuiFlyout styles * Corrected spelling error in EuiFlyout animation in Lens app * Update EUI with latest backport * Update button snapshots * fix another button snapshot * More snapshot fixes * [EuiButton][Security] Fix button relying on now-removed `euiButton__text` CSS - replace removed CSS with `eui-textTruncate` util instead - combine/DRY out unnecessary span - was affecting min-width of truncation util + increase screenshot diff limit - this was smaller than updating the actual baseline screenshots for whatever reason (likely render diff between local and CI) * Fix remaining Jest tests affected by Emotion conversions - because Emotion creates its own wrapper, `.first()` can no longer be used - prefer `.last()` instead * Fix Jest test affected by EuiButton Emotion conversion + removed modifier class - targeting the native DOM node + filtering by disabled true/false gets us back to the 'correct' lengths * Fix + improve flyout test - `.last()` changes to account for EuiButton Emotion conversion is needed, but the last onClose assertion still fails due to us having modified inputs, and the confirm modal being displayed - split test into two separate tests - one testing the onClose call, and the other testing the confirm modal * derpin * Skip rules_list Jest suite * Update new EuiButton snapshot * Upgraded EUI version to 67.1.7 * [EuiCard] Update snapshots * [EuiPopover] Update snapshots * [QA] Fix missing Vega warn/error message colors ;_; * [CI] Auto-commit changed files from 'node scripts/generate codeowners' * Fix Lens kbnToolbarButton regressions - Caused by flattening of EUI button CSS specificity - background-color was previously relying on isDisabled CSS specificity to override its #fff color - `text` color modifier & `!important` is no longer needed and overrides Emotion CSS flatly - isDisabled class is no longer needed - euiButton no longer sets `pointer-events: none` on disabled buttons (fixes tooltip bug in webkit as well) * Backport EUI 67.1.8 fixes * Update EuiCard snapshots * Fix EuiModal form wrapper causing overflow issues - see https://elastic.github.io/eui/#/layout/modal#forms-in-a-modal * Workaround for `.kbnOverlayMountWrapper` mount point causing overflow issues - not sure what all is using this modal service to be honest, but the wrapper is causing issues with the modal layout, this fixes overflow issues but will not fix any mask-image issues as a result * more snapshot updates * EuiButton - added textProps to EuiButton to prevent very long button names from spilling over outside of the container * EuiButton - Update EuiButton related snapshots. Updated tests that target EuiButton directly to use a data-telementary-id for more specific element querying required by Emotion * QA - Removed unnecessary comment in code * Temporary fix for EuiCard[selectable][layout=horizontal] instances on security solutions' rule page * Temporary fix for EuiCard[selectable][layout=horizontal] instances on osquery live query and canvas's datasource selector * [CI] Auto-commit changed files from 'node scripts/precommit_hook.js --ref HEAD~1..HEAD --fix' * Fix CSS specificity, where canvas's solutionToolbarButton's background-color now takes precedence over EuiButton's primary styles * Removed update to search_marker_tooltip that removed the euiTooltip styles and replaced then with Emotion styling. Added EuiTooltip Sass styles for the component to rely on to test for a styling bug that is causing the tooltip and the tooltip arrow to be out of sync with each other. * Lint Sass file * Lint Sass file * Removed overflow:hidden style from .vgaVis_view as it was causing euiScrollStyles not to present the scroll bars in Vega Vis * Remove typo from EuiButton textProps object. 'className' should not have been included in the actual class name * Revert tooltip Sass This reverts commit 20e6ead, a5cd2de, and c605cbd * Fix Emotion tooltip arrows Co-authored-by: kibanamachine <[email protected]> Co-authored-by: Constance Chen <[email protected]> Co-authored-by: Chandler Prall <[email protected]>
davismcphee
pushed a commit
that referenced
this pull request
Jan 4, 2023
## Summary Fixes elastic#144161 As discussed [here](elastic#144161 (comment)), the existing implementation of update tags doesn't work well with real agents, as there are many conflicts with checkin, even when trying to add/remove one tag. Refactored the logic to make retries more efficient: - Instead of aborting the whole bulk action on conflicts, changed the conflict strategy to 'proceed'. This means, if an action of 50k agents has 1k conflicts, not all 50k is retried, but only the 1k conflicts, this makes it less likely to conflict on retry. - Because of this, on retry we have to know which agents don't yet have the tag added/removed. For this, added an additional filter to the `updateByQuery` request. Only adding the filter if there is exactly one `tagsToAdd` or one `tagsToRemove`. This is the main use case from the UI, and handling other cases would complicate the logic more (each additional tag to add/remove would result in another OR query, which would match more agents, making conflicts more likely). - Added this additional query on the initial request as well (not only retries) to save on unnecessary work e.g. if the user tries to add a tag on 50k agents, but 48k already have it, it is enough to update the remaining 2k agents. - This improvement has the effect that 'Agent activity' shows the real updated agent count, not the total selected. I think this is not really a problem for update tags. - Cleaned up some of the UI logic, because the conflicts are fully handled now on the backend. - Locally I couldn't reproduce the conflict with agent checkins, even with 1k horde agents. I'll try to test in cloud with more real agents. To verify: - Enroll 50k agents (I used 50k with create_agents script, and 1k with horde). Enroll 50k with horde if possible. - Select all on UI and try to add/remove one or more tags - Expect the changes to propagate quickly (up to 1m). It might take a few refreshes to see the result on agent list and tags list, because the UI polls the agents every 30s. It is expected that the tags list temporarily shows incorrect data because the action is async. E.g. removed `test3` tag and added `add` tag quickly: <img width="1776" alt="image" src="https://user-images.githubusercontent.com/90178898/207824481-411f0f70-d7e8-42a6-b73f-ed80e77b7700.png"> <img width="422" alt="image" src="https://user-images.githubusercontent.com/90178898/207824550-582d43fc-87db-45e1-ba58-15915447fefd.png"> The logs show the details of how many `version_conflicts` were there, and it decreased with retries. ``` [2022-12-15T10:32:12.937+01:00][INFO ][plugins.fleet] Running action asynchronously, actionId: 90acd541-19ac-4738-b3d3-db32789233de, total agents: 52000 [2022-12-15T10:32:12.981+01:00][INFO ][plugins.fleet] Scheduling task fleet:update_agent_tags:retry:check:90acd541-19ac-4738-b3d3-db32789233de [2022-12-15T10:32:16.477+01:00][INFO ][plugins.fleet] Running action asynchronously, actionId: 29e9da70-7194-4e52-8004-2c1b19f6dfd5, total agents: 52000 [2022-12-15T10:32:16.537+01:00][INFO ][plugins.fleet] Scheduling task fleet:update_agent_tags:retry:check:29e9da70-7194-4e52-8004-2c1b19f6dfd5 [2022-12-15T10:32:22.893+01:00][DEBUG][plugins.fleet] {"took":9886,"timed_out":false,"total":52000,"updated":41143,"deleted":0,"batches":52,"version_conflicts":10857,"noops":0,"retries":{"bulk":0,"search":0},"throttled_millis":0,"requests_per_second":-1,"throttled_until_millis":0,"failures":[]} [2022-12-15T10:32:26.066+01:00][DEBUG][plugins.fleet] {"took":9518,"timed_out":false,"total":52000,"updated":25755,"deleted":0,"batches":52,"version_conflicts":26245,"noops":0,"retries":{"bulk":0,"search":0},"throttled_millis":0,"requests_per_second":-1,"throttled_until_millis":0,"failures":[]} [2022-12-15T10:32:27.401+01:00][ERROR][plugins.fleet] Action failed: version conflict of 10857 agents [2022-12-15T10:32:27.461+01:00][INFO ][plugins.fleet] Scheduling task fleet:update_agent_tags:retry:90acd541-19ac-4738-b3d3-db32789233de [2022-12-15T10:32:27.462+01:00][INFO ][plugins.fleet] Retrying in task: fleet:update_agent_tags:retry:90acd541-19ac-4738-b3d3-db32789233de [2022-12-15T10:32:29.274+01:00][ERROR][plugins.fleet] Action failed: version conflict of 26245 agents [2022-12-15T10:32:29.353+01:00][INFO ][plugins.fleet] Scheduling task fleet:update_agent_tags:retry:29e9da70-7194-4e52-8004-2c1b19f6dfd5 [2022-12-15T10:32:29.353+01:00][INFO ][plugins.fleet] Retrying in task: fleet:update_agent_tags:retry:29e9da70-7194-4e52-8004-2c1b19f6dfd5 [2022-12-15T10:32:31.480+01:00][INFO ][plugins.fleet] Running bulk action retry task [2022-12-15T10:32:31.481+01:00][DEBUG][plugins.fleet] Retry #1 of task fleet:update_agent_tags:retry:90acd541-19ac-4738-b3d3-db32789233de [2022-12-15T10:32:31.481+01:00][INFO ][plugins.fleet] Running action asynchronously, actionId: 90acd541-19ac-4738-b3d3-db32789233de, total agents: 52000 [2022-12-15T10:32:31.481+01:00][INFO ][plugins.fleet] Completed bulk action retry task [2022-12-15T10:32:31.485+01:00][INFO ][plugins.fleet] Scheduling task fleet:update_agent_tags:retry:check:90acd541-19ac-4738-b3d3-db32789233de [2022-12-15T10:32:33.841+01:00][DEBUG][plugins.fleet] {"took":2347,"timed_out":false,"total":10857,"updated":9857,"deleted":0,"batches":11,"version_conflicts":1000,"noops":0,"retries":{"bulk":0,"search":0},"throttled_millis":0,"requests_per_second":-1,"throttled_until_millis":0,"failures":[]} [2022-12-15T10:32:34.556+01:00][INFO ][plugins.fleet] Running bulk action retry task [2022-12-15T10:32:34.557+01:00][DEBUG][plugins.fleet] Retry #1 of task fleet:update_agent_tags:retry:29e9da70-7194-4e52-8004-2c1b19f6dfd5 [2022-12-15T10:32:34.557+01:00][INFO ][plugins.fleet] Running action asynchronously, actionId: 29e9da70-7194-4e52-8004-2c1b19f6dfd5, total agents: 52000 [2022-12-15T10:32:34.557+01:00][INFO ][plugins.fleet] Completed bulk action retry task [2022-12-15T10:32:34.560+01:00][INFO ][plugins.fleet] Scheduling task fleet:update_agent_tags:retry:check:29e9da70-7194-4e52-8004-2c1b19f6dfd5 [2022-12-15T10:32:35.388+01:00][ERROR][plugins.fleet] Retry #1 of task fleet:update_agent_tags:retry:90acd541-19ac-4738-b3d3-db32789233de failed: version conflict of 1000 agents [2022-12-15T10:32:35.468+01:00][INFO ][plugins.fleet] Scheduling task fleet:update_agent_tags:retry:90acd541-19ac-4738-b3d3-db32789233de [2022-12-15T10:32:35.468+01:00][INFO ][plugins.fleet] Retrying in task: fleet:update_agent_tags:retry:90acd541-19ac-4738-b3d3-db32789233de {"took":5509,"timed_out":false,"total":26245,"updated":26245,"deleted":0,"batches":27,"version_conflicts":0,"noops":0,"retries":{"bulk":0,"search":0},"throttled_millis":0,"requests_per_second":-1,"throttled_until_millis":0,"failures":[]} [2022-12-15T10:32:42.722+01:00][INFO ][plugins.fleet] processed 26245 agents, took 5509ms [2022-12-15T10:32:42.723+01:00][INFO ][plugins.fleet] Removing task fleet:update_agent_tags:retry:check:29e9da70-7194-4e52-8004-2c1b19f6dfd5 [2022-12-15T10:32:46.705+01:00][INFO ][plugins.fleet] Running bulk action retry task [2022-12-15T10:32:46.706+01:00][DEBUG][plugins.fleet] Retry #2 of task fleet:update_agent_tags:retry:90acd541-19ac-4738-b3d3-db32789233de [2022-12-15T10:32:46.707+01:00][INFO ][plugins.fleet] Running action asynchronously, actionId: 90acd541-19ac-4738-b3d3-db32789233de, total agents: 52000 [2022-12-15T10:32:46.707+01:00][INFO ][plugins.fleet] Completed bulk action retry task [2022-12-15T10:32:46.711+01:00][INFO ][plugins.fleet] Scheduling task fleet:update_agent_tags:retry:check:90acd541-19ac-4738-b3d3-db32789233de [2022-12-15T10:32:47.099+01:00][DEBUG][plugins.fleet] {"took":379,"timed_out":false,"total":1000,"updated":1000,"deleted":0,"batches":1,"version_conflicts":0,"noops":0,"retries":{"bulk":0,"search":0},"throttled_millis":0,"requests_per_second":-1,"throttled_until_millis":0,"failures":[]} [2022-12-15T10:32:47.623+01:00][INFO ][plugins.fleet] processed 1000 agents, took 379ms [2022-12-15T10:32:47.623+01:00][INFO ][plugins.fleet] Removing task fleet:update_agent_tags:retry:check:90acd541-19ac-4738-b3d3-db32789233de ``` ### Checklist - [x] [Unit or functional tests](https://www.elastic.co/guide/en/kibana/master/development-tests.html) were updated or added to match the most common scenarios Co-authored-by: Kibana Machine <[email protected]>
davismcphee
pushed a commit
that referenced
this pull request
Jun 8, 2023
…lastic#159352) ## Summary Skip `Security Solution Tests #2 / rule snoozing Rule editing page / actions tab adds an action to a snoozed rule` [This test failed on `main` as soon as it was merged.](https://buildkite.com/elastic/kibana-on-merge-unsupported-ftrs/builds/2952) ### For maintainers - [ ] This was checked for breaking API changes and was [labeled appropriately](https://www.elastic.co/guide/en/kibana/master/contributing.html#kibana-release-notes-process)
davismcphee
pushed a commit
that referenced
this pull request
Sep 25, 2023
… integration for ES|QL query generation via ELSER (elastic#167097) ## [Security Solution] [Elastic AI Assistant] LangChain Agents and Tools integration for ES|QL query generation via ELSER This PR integrates [LangChain](https://www.langchain.com/) [Agents](https://js.langchain.com/docs/modules/agents/) and [Tools](https://js.langchain.com/docs/modules/agents/tools/) with the [Elastic AI Assistant](https://www.elastic.co/blog/introducing-elastic-ai-assistant). These abstractions enable the LLM to dynamically choose whether or not to query, via [ELSER](https://www.elastic.co/guide/en/machine-learning/current/ml-nlp-elser.html), an [ES|QL](https://www.elastic.co/blog/elasticsearch-query-language-esql) knowledge base. Context from the knowledge base is used to generate `ES|QL` queries, or answer questions about `ES|QL`. Registration of the tool occurs in `x-pack/plugins/elastic_assistant/server/lib/langchain/execute_custom_llm_chain/index.ts`: ```typescript const tools: Tool[] = [ new ChainTool({ name: 'esql-language-knowledge-base', description: 'Call this for knowledge on how to build an ESQL query, or answer questions about the ES|QL query language.', chain, }), ]; ``` The `tools` array above may be updated in future PRs to include, for example, an `ES|QL` query validator endpoint. ### Details The `callAgentExecutor` function in `x-pack/plugins/elastic_assistant/server/lib/langchain/execute_custom_llm_chain/index.ts`: 1. Creates a `RetrievalQAChain` from an `ELSER` backed `ElasticsearchStore`, which serves as a knowledge base for `ES|QL`: ```typescript // ELSER backed ElasticsearchStore for Knowledge Base const esStore = new ElasticsearchStore(esClient, KNOWLEDGE_BASE_INDEX_PATTERN, logger); const chain = RetrievalQAChain.fromLLM(llm, esStore.asRetriever()); ``` 2. Registers the chain as a tool, which may be invoked by the LLM based on its description: ```typescript const tools: Tool[] = [ new ChainTool({ name: 'esql-language-knowledge-base', description: 'Call this for knowledge on how to build an ESQL query, or answer questions about the ES|QL query language.', chain, }), ]; ``` 3. Creates an Agent executor that combines the `tools` above, the `ActionsClientLlm` (an abstraction that calls `actionsClient.execute`), and memory of the previous messages in the conversation: ```typescript const executor = await initializeAgentExecutorWithOptions(tools, llm, { agentType: 'chat-conversational-react-description', memory, verbose: false, }); ``` Note: Set `verbose` above to `true` to for detailed debugging output from LangChain. 4. Calls the `executor`, kicking it off with `latestMessage`: ```typescript await executor.call({ input: latestMessage[0].content }); ``` ### Changes to `x-pack/packages/kbn-elastic-assistant` A client side change was required to the assistant, because the response returned from the agent executor is JSON. This response is parsed on the client in `x-pack/packages/kbn-elastic-assistant/impl/assistant/api.tsx`: ```typescript return assistantLangChain ? getFormattedMessageContent(result) : result; ``` Client-side parsing of the response only happens when then `assistantLangChain` feature flag is `true`. ## Desk testing Set ```typescript assistantLangChain={true} ``` in `x-pack/plugins/security_solution/public/assistant/provider.tsx` to enable this experimental feature in development environments. Also (optionally) set `verbose` to `true` in the following code in ``x-pack/plugins/elastic_assistant/server/lib/langchain/execute_custom_llm_chain/index.ts``: ```typescript const executor = await initializeAgentExecutorWithOptions(tools, llm, { agentType: 'chat-conversational-react-description', memory, verbose: true, }); ``` After setting the feature flag and optionally enabling verbose debugging output, you may ask the assistant to generate an `ES|QL` query, per the example in the next section. ### Example output When the Elastic AI Assistant is asked: ``` From employees, I want to see the 5 earliest employees (hire_date), I want to display only the month and the year that they were hired in and their employee number (emp_no). Format the date as e.g. "September 2019". Only show the query ``` it replies: ``` Here is the query to get the employee number and the formatted hire date for the 5 earliest employees by hire_date: FROM employees | KEEP emp_no, hire_date | EVAL month_year = DATE_FORMAT(hire_date, "MMMM YYYY") | SORT hire_date | LIMIT 5 ``` Per the screenshot below:  The `verbose: true` output from LangChain logged to the console reveals that the prompt sent to the LLM includes text like the following: ``` Assistant can ask the user to use tools to look up information that may be helpful in answering the users original question. The tools the human can use are:\\n\\nesql-language-knowledge-base: Call this for knowledge on how to build an ESQL query, or answer questions about the ES|QL query language. ``` along with instructions for "calling" the tool like a function. The debugging output also reveals the agent selecting the tool, and returning results from ESLR: ``` [agent/action] [1:chain:AgentExecutor] Agent selected action: { "tool": "esql-language-knowledge-base", "toolInput": "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.", "log": "```json\n{\n \"action\": \"esql-language-knowledge-base\",\n \"action_input\": \"Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.\"\n}\n```" } [tool/start] [1:chain:AgentExecutor > 4:tool:ChainTool] Entering Tool run with input: "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'." [chain/start] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain] Entering Chain run with input: { "query": "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'." } [retriever/start] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain > 6:retriever:VectorStoreRetriever] Entering Retriever run with input: { "query": "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'." } [retriever/end] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain > 6:retriever:VectorStoreRetriever] [115ms] Exiting Retriever run with output: { "documents": [ { "pageContent": "[[esql-date_format]]\n=== `DATE_FORMAT`\nReturns a string representation of a date in the provided format. If no format\nis specified, the `yyyy-MM-dd'T'HH:mm:ss.SSSZ` format is used.\n\n[source,esql]\n----\nFROM employees\n| KEEP first_name, last_name, hire_date\n| EVAL hired = DATE_FORMAT(hire_date, \"YYYY-MM-dd\")\n----\n", ``` The documents containing `ES|QL` examples, retrieved from ELSER, are sent back to the LLM to answer the original question, per the abridged output below: ``` [llm/start] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain > 7:chain:StuffDocumentsChain > 8:chain:LLMChain > 9:llm:ActionsClientLlm] Entering LLM run with input: { "prompts": [ "Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\n\n[[esql-date_format]]\n=== `DATE_FORMAT`\nReturns a string representation of a date in the provided format. If no format\nis specified, the `yyyy-MM-dd'T'HH:mm:ss.SSSZ` format is used.\n\n[source,esql]\n----\nFROM employees\n| KEEP first_name, last_name, hire_date\n| EVAL hired = DATE_FORMAT(hire_date, \"YYYY-MM-dd\")\n----\n\n\n[[esql-date_trunc]]\n=== `DATE_TRUNC`\nRounds down a date to the closest interval. Intervals can be expressed using the\n<<esql-timespan-literals,timespan literal syntax>>.\n\n[source,esql]\n----\nFROM employees\n| EVAL year_hired = DATE_TRUNC(1 year, hire_date)\n| STATS count(emp_no) BY year_hired\n| SORT year_hired\n----\n\n\n[[esql-from]]\n=== `FROM`\n\nThe `FROM` source command returns a table with up to 10,000 documents from a\ndata stream, index, ``` ### Complete (verbose) LangChain output from the example The following `verbose: true` output from LangChain below was produced via the example in the previous section: ``` [chain/start] [1:chain:AgentExecutor] Entering Chain run with input: { "input": "\n\n\n\nFrom employees, I want to see the 5 earliest employees (hire_date), I want to display only the month and the year that they were hired in and their employee number (emp_no). Format the date as e.g. \"September 2019\". Only show the query", "chat_history": [] } [chain/start] [1:chain:AgentExecutor > 2:chain:LLMChain] Entering Chain run with input: { "input": "\n\n\n\nFrom employees, I want to see the 5 earliest employees (hire_date), I want to display only the month and the year that they were hired in and their employee number (emp_no). Format the date as e.g. \"September 2019\". Only show the query", "chat_history": [], "agent_scratchpad": [], "stop": [ "Observation:" ] } [llm/start] [1:chain:AgentExecutor > 2:chain:LLMChain > 3:llm:ActionsClientLlm] Entering LLM run with input: { "prompts": [ "[{\"lc\":1,\"type\":\"constructor\",\"id\":[\"langchain\",\"schema\",\"SystemMessage\"],\"kwargs\":{\"content\":\"Assistant is a large language model trained by OpenAI.\\n\\nAssistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, Assistant is able to generate human-like text based on the input it receives, allowing it to engage in natural-sounding conversations and provide responses that are coherent and relevant to the topic at hand.\\n\\nAssistant is constantly learning and improving, and its capabilities are constantly evolving. It is able to process and understand large amounts of text, and can use this knowledge to provide accurate and informative responses to a wide range of questions. Additionally, Assistant is able to generate its own text based on the input it receives, allowing it to engage in discussions and provide explanations and descriptions on a wide range of topics.\\n\\nOverall, Assistant is a powerful system that can help with a wide range of tasks and provide valuable insights and information on a wide range of topics. Whether you need help with a specific question or just want to have a conversation about a particular topic, Assistant is here to assist. However, above all else, all responses must adhere to the format of RESPONSE FORMAT INSTRUCTIONS.\",\"additional_kwargs\":{}}},{\"lc\":1,\"type\":\"constructor\",\"id\":[\"langchain\",\"schema\",\"HumanMessage\"],\"kwargs\":{\"content\":\"TOOLS\\n------\\nAssistant can ask the user to use tools to look up information that may be helpful in answering the users original question. The tools the human can use are:\\n\\nesql-language-knowledge-base: Call this for knowledge on how to build an ESQL query, or answer questions about the ES|QL query language.\\n\\nRESPONSE FORMAT INSTRUCTIONS\\n----------------------------\\n\\nOutput a JSON markdown code snippet containing a valid JSON object in one of two formats:\\n\\n**Option 1:**\\nUse this if you want the human to use a tool.\\nMarkdown code snippet formatted in the following schema:\\n\\n```json\\n{\\n \\\"action\\\": string, // The action to take. Must be one of [esql-language-knowledge-base]\\n \\\"action_input\\\": string // The input to the action. May be a stringified object.\\n}\\n```\\n\\n**Option #2:**\\nUse this if you want to respond directly and conversationally to the human. Markdown code snippet formatted in the following schema:\\n\\n```json\\n{\\n \\\"action\\\": \\\"Final Answer\\\",\\n \\\"action_input\\\": string // You should put what you want to return to use here and make sure to use valid json newline characters.\\n}\\n```\\n\\nFor both options, remember to always include the surrounding markdown code snippet delimiters (begin with \\\"```json\\\" and end with \\\"```\\\")!\\n\\n\\nUSER'S INPUT\\n--------------------\\nHere is the user's input (remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else):\\n\\n\\n\\n\\n\\nFrom employees, I want to see the 5 earliest employees (hire_date), I want to display only the month and the year that they were hired in and their employee number (emp_no). Format the date as e.g. \\\"September 2019\\\". Only show the query\",\"additional_kwargs\":{}}}]" ] } [llm/end] [1:chain:AgentExecutor > 2:chain:LLMChain > 3:llm:ActionsClientLlm] [3.08s] Exiting LLM run with output: { "generations": [ [ { "text": "```json\n{\n \"action\": \"esql-language-knowledge-base\",\n \"action_input\": \"Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.\"\n}\n```" } ] ] } [chain/end] [1:chain:AgentExecutor > 2:chain:LLMChain] [3.09s] Exiting Chain run with output: { "text": "```json\n{\n \"action\": \"esql-language-knowledge-base\",\n \"action_input\": \"Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.\"\n}\n```" } [agent/action] [1:chain:AgentExecutor] Agent selected action: { "tool": "esql-language-knowledge-base", "toolInput": "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.", "log": "```json\n{\n \"action\": \"esql-language-knowledge-base\",\n \"action_input\": \"Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.\"\n}\n```" } [tool/start] [1:chain:AgentExecutor > 4:tool:ChainTool] Entering Tool run with input: "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'." [chain/start] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain] Entering Chain run with input: { "query": "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'." } [retriever/start] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain > 6:retriever:VectorStoreRetriever] Entering Retriever run with input: { "query": "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'." } [retriever/end] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain > 6:retriever:VectorStoreRetriever] [115ms] Exiting Retriever run with output: { "documents": [ { "pageContent": "[[esql-date_format]]\n=== `DATE_FORMAT`\nReturns a string representation of a date in the provided format. If no format\nis specified, the `yyyy-MM-dd'T'HH:mm:ss.SSSZ` format is used.\n\n[source,esql]\n----\nFROM employees\n| KEEP first_name, last_name, hire_date\n| EVAL hired = DATE_FORMAT(hire_date, \"YYYY-MM-dd\")\n----\n", "metadata": { "source": "/Users/andrew.goldstein/Projects/forks/spong/kibana/x-pack/plugins/elastic_assistant/server/knowledge_base/esql/docs/functions/date_format.asciidoc" } }, { "pageContent": "[[esql-date_trunc]]\n=== `DATE_TRUNC`\nRounds down a date to the closest interval. Intervals can be expressed using the\n<<esql-timespan-literals,timespan literal syntax>>.\n\n[source,esql]\n----\nFROM employees\n| EVAL year_hired = DATE_TRUNC(1 year, hire_date)\n| STATS count(emp_no) BY year_hired\n| SORT year_hired\n----\n", "metadata": { "source": "/Users/andrew.goldstein/Projects/forks/spong/kibana/x-pack/plugins/elastic_assistant/server/knowledge_base/esql/docs/functions/date_trunc.asciidoc" } }, { "pageContent": "[[esql-from]]\n=== `FROM`\n\nThe `FROM` source command returns a table with up to 10,000 documents from a\ndata stream, index, or alias. Each row in the resulting table represents a\ndocument. Each column corresponds to a field, and can be accessed by the name\nof that field.\n\n[source,esql]\n----\nFROM employees\n----\n\nYou can use <<api-date-math-index-names,date math>> to refer to indices, aliases\nand data streams. This can be useful for time series data, for example to access\ntoday's index:\n\n[source,esql]\n----\nFROM <logs-{now/d}>\n----\n\nUse comma-separated lists or wildcards to query multiple data streams, indices,\nor aliases:\n\n[source,esql]\n----\nFROM employees-00001,employees-*\n----\n", "metadata": { "source": "/Users/andrew.goldstein/Projects/forks/spong/kibana/x-pack/plugins/elastic_assistant/server/knowledge_base/esql/docs/source_commands/from.asciidoc" } }, { "pageContent": "[[esql-where]]\n=== `WHERE`\n\nUse `WHERE` to produce a table that contains all the rows from the input table\nfor which the provided condition evaluates to `true`:\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=where]\n----\n\nWhich, if `still_hired` is a boolean field, can be simplified to:\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=whereBoolean]\n----\n\n[discrete]\n==== Operators\n\nRefer to <<esql-operators>> for an overview of the supported operators.\n\n[discrete]\n==== Functions\n`WHERE` supports various functions for calculating values. Refer to\n<<esql-functions,Functions>> for more information.\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=whereFunction]\n----\n", "metadata": { "source": "/Users/andrew.goldstein/Projects/forks/spong/kibana/x-pack/plugins/elastic_assistant/server/knowledge_base/esql/docs/processing_commands/where.asciidoc" } } ] } [chain/start] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain > 7:chain:StuffDocumentsChain] Entering Chain run with input: { "question": "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.", "input_documents": [ { "pageContent": "[[esql-date_format]]\n=== `DATE_FORMAT`\nReturns a string representation of a date in the provided format. If no format\nis specified, the `yyyy-MM-dd'T'HH:mm:ss.SSSZ` format is used.\n\n[source,esql]\n----\nFROM employees\n| KEEP first_name, last_name, hire_date\n| EVAL hired = DATE_FORMAT(hire_date, \"YYYY-MM-dd\")\n----\n", "metadata": { "source": "/Users/andrew.goldstein/Projects/forks/spong/kibana/x-pack/plugins/elastic_assistant/server/knowledge_base/esql/docs/functions/date_format.asciidoc" } }, { "pageContent": "[[esql-date_trunc]]\n=== `DATE_TRUNC`\nRounds down a date to the closest interval. Intervals can be expressed using the\n<<esql-timespan-literals,timespan literal syntax>>.\n\n[source,esql]\n----\nFROM employees\n| EVAL year_hired = DATE_TRUNC(1 year, hire_date)\n| STATS count(emp_no) BY year_hired\n| SORT year_hired\n----\n", "metadata": { "source": "/Users/andrew.goldstein/Projects/forks/spong/kibana/x-pack/plugins/elastic_assistant/server/knowledge_base/esql/docs/functions/date_trunc.asciidoc" } }, { "pageContent": "[[esql-from]]\n=== `FROM`\n\nThe `FROM` source command returns a table with up to 10,000 documents from a\ndata stream, index, or alias. Each row in the resulting table represents a\ndocument. Each column corresponds to a field, and can be accessed by the name\nof that field.\n\n[source,esql]\n----\nFROM employees\n----\n\nYou can use <<api-date-math-index-names,date math>> to refer to indices, aliases\nand data streams. This can be useful for time series data, for example to access\ntoday's index:\n\n[source,esql]\n----\nFROM <logs-{now/d}>\n----\n\nUse comma-separated lists or wildcards to query multiple data streams, indices,\nor aliases:\n\n[source,esql]\n----\nFROM employees-00001,employees-*\n----\n", "metadata": { "source": "/Users/andrew.goldstein/Projects/forks/spong/kibana/x-pack/plugins/elastic_assistant/server/knowledge_base/esql/docs/source_commands/from.asciidoc" } }, { "pageContent": "[[esql-where]]\n=== `WHERE`\n\nUse `WHERE` to produce a table that contains all the rows from the input table\nfor which the provided condition evaluates to `true`:\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=where]\n----\n\nWhich, if `still_hired` is a boolean field, can be simplified to:\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=whereBoolean]\n----\n\n[discrete]\n==== Operators\n\nRefer to <<esql-operators>> for an overview of the supported operators.\n\n[discrete]\n==== Functions\n`WHERE` supports various functions for calculating values. Refer to\n<<esql-functions,Functions>> for more information.\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=whereFunction]\n----\n", "metadata": { "source": "/Users/andrew.goldstein/Projects/forks/spong/kibana/x-pack/plugins/elastic_assistant/server/knowledge_base/esql/docs/processing_commands/where.asciidoc" } } ], "query": "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'." } [chain/start] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain > 7:chain:StuffDocumentsChain > 8:chain:LLMChain] Entering Chain run with input: { "question": "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.", "query": "Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.", "context": "[[esql-date_format]]\n=== `DATE_FORMAT`\nReturns a string representation of a date in the provided format. If no format\nis specified, the `yyyy-MM-dd'T'HH:mm:ss.SSSZ` format is used.\n\n[source,esql]\n----\nFROM employees\n| KEEP first_name, last_name, hire_date\n| EVAL hired = DATE_FORMAT(hire_date, \"YYYY-MM-dd\")\n----\n\n\n[[esql-date_trunc]]\n=== `DATE_TRUNC`\nRounds down a date to the closest interval. Intervals can be expressed using the\n<<esql-timespan-literals,timespan literal syntax>>.\n\n[source,esql]\n----\nFROM employees\n| EVAL year_hired = DATE_TRUNC(1 year, hire_date)\n| STATS count(emp_no) BY year_hired\n| SORT year_hired\n----\n\n\n[[esql-from]]\n=== `FROM`\n\nThe `FROM` source command returns a table with up to 10,000 documents from a\ndata stream, index, or alias. Each row in the resulting table represents a\ndocument. Each column corresponds to a field, and can be accessed by the name\nof that field.\n\n[source,esql]\n----\nFROM employees\n----\n\nYou can use <<api-date-math-index-names,date math>> to refer to indices, aliases\nand data streams. This can be useful for time series data, for example to access\ntoday's index:\n\n[source,esql]\n----\nFROM <logs-{now/d}>\n----\n\nUse comma-separated lists or wildcards to query multiple data streams, indices,\nor aliases:\n\n[source,esql]\n----\nFROM employees-00001,employees-*\n----\n\n\n[[esql-where]]\n=== `WHERE`\n\nUse `WHERE` to produce a table that contains all the rows from the input table\nfor which the provided condition evaluates to `true`:\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=where]\n----\n\nWhich, if `still_hired` is a boolean field, can be simplified to:\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=whereBoolean]\n----\n\n[discrete]\n==== Operators\n\nRefer to <<esql-operators>> for an overview of the supported operators.\n\n[discrete]\n==== Functions\n`WHERE` supports various functions for calculating values. Refer to\n<<esql-functions,Functions>> for more information.\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=whereFunction]\n----\n" } [llm/start] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain > 7:chain:StuffDocumentsChain > 8:chain:LLMChain > 9:llm:ActionsClientLlm] Entering LLM run with input: { "prompts": [ "Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer.\n\n[[esql-date_format]]\n=== `DATE_FORMAT`\nReturns a string representation of a date in the provided format. If no format\nis specified, the `yyyy-MM-dd'T'HH:mm:ss.SSSZ` format is used.\n\n[source,esql]\n----\nFROM employees\n| KEEP first_name, last_name, hire_date\n| EVAL hired = DATE_FORMAT(hire_date, \"YYYY-MM-dd\")\n----\n\n\n[[esql-date_trunc]]\n=== `DATE_TRUNC`\nRounds down a date to the closest interval. Intervals can be expressed using the\n<<esql-timespan-literals,timespan literal syntax>>.\n\n[source,esql]\n----\nFROM employees\n| EVAL year_hired = DATE_TRUNC(1 year, hire_date)\n| STATS count(emp_no) BY year_hired\n| SORT year_hired\n----\n\n\n[[esql-from]]\n=== `FROM`\n\nThe `FROM` source command returns a table with up to 10,000 documents from a\ndata stream, index, or alias. Each row in the resulting table represents a\ndocument. Each column corresponds to a field, and can be accessed by the name\nof that field.\n\n[source,esql]\n----\nFROM employees\n----\n\nYou can use <<api-date-math-index-names,date math>> to refer to indices, aliases\nand data streams. This can be useful for time series data, for example to access\ntoday's index:\n\n[source,esql]\n----\nFROM <logs-{now/d}>\n----\n\nUse comma-separated lists or wildcards to query multiple data streams, indices,\nor aliases:\n\n[source,esql]\n----\nFROM employees-00001,employees-*\n----\n\n\n[[esql-where]]\n=== `WHERE`\n\nUse `WHERE` to produce a table that contains all the rows from the input table\nfor which the provided condition evaluates to `true`:\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=where]\n----\n\nWhich, if `still_hired` is a boolean field, can be simplified to:\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=whereBoolean]\n----\n\n[discrete]\n==== Operators\n\nRefer to <<esql-operators>> for an overview of the supported operators.\n\n[discrete]\n==== Functions\n`WHERE` supports various functions for calculating values. Refer to\n<<esql-functions,Functions>> for more information.\n\n[source,esql]\n----\ninclude::{esql-specs}/docs.csv-spec[tag=whereFunction]\n----\n\n\nQuestion: Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.\nHelpful Answer:" ] } [llm/end] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain > 7:chain:StuffDocumentsChain > 8:chain:LLMChain > 9:llm:ActionsClientLlm] [2.23s] Exiting LLM run with output: { "generations": [ [ { "text": "FROM employees\n| KEEP emp_no, hire_date\n| EVAL month_year = DATE_FORMAT(hire_date, \"MMMM YYYY\")\n| SORT hire_date\n| LIMIT 5" } ] ] } [chain/end] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain > 7:chain:StuffDocumentsChain > 8:chain:LLMChain] [2.23s] Exiting Chain run with output: { "text": "FROM employees\n| KEEP emp_no, hire_date\n| EVAL month_year = DATE_FORMAT(hire_date, \"MMMM YYYY\")\n| SORT hire_date\n| LIMIT 5" } [chain/end] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain > 7:chain:StuffDocumentsChain] [2.23s] Exiting Chain run with output: { "text": "FROM employees\n| KEEP emp_no, hire_date\n| EVAL month_year = DATE_FORMAT(hire_date, \"MMMM YYYY\")\n| SORT hire_date\n| LIMIT 5" } [chain/end] [1:chain:AgentExecutor > 4:tool:ChainTool > 5:chain:RetrievalQAChain] [2.35s] Exiting Chain run with output: { "text": "FROM employees\n| KEEP emp_no, hire_date\n| EVAL month_year = DATE_FORMAT(hire_date, \"MMMM YYYY\")\n| SORT hire_date\n| LIMIT 5" } [tool/end] [1:chain:AgentExecutor > 4:tool:ChainTool] [2.35s] Exiting Tool run with output: "FROM employees | KEEP emp_no, hire_date | EVAL month_year = DATE_FORMAT(hire_date, "MMMM YYYY") | SORT hire_date | LIMIT 5" [chain/start] [1:chain:AgentExecutor > 10:chain:LLMChain] Entering Chain run with input: { "input": "\n\n\n\nFrom employees, I want to see the 5 earliest employees (hire_date), I want to display only the month and the year that they were hired in and their employee number (emp_no). Format the date as e.g. \"September 2019\". Only show the query", "chat_history": [], "agent_scratchpad": [ { "lc": 1, "type": "constructor", "id": [ "langchain", "schema", "AIMessage" ], "kwargs": { "content": "```json\n{\n \"action\": \"esql-language-knowledge-base\",\n \"action_input\": \"Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.\"\n}\n```", "additional_kwargs": {} } }, { "lc": 1, "type": "constructor", "id": [ "langchain", "schema", "HumanMessage" ], "kwargs": { "content": "TOOL RESPONSE:\n---------------------\nFROM employees\n| KEEP emp_no, hire_date\n| EVAL month_year = DATE_FORMAT(hire_date, \"MMMM YYYY\")\n| SORT hire_date\n| LIMIT 5\n\nUSER'S INPUT\n--------------------\n\nOkay, so what is the response to my last comment? If using information obtained from the tools you must mention it explicitly without mentioning the tool names - I have forgotten all TOOL RESPONSES! Remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else.", "additional_kwargs": {} } } ], "stop": [ "Observation:" ] } [llm/start] [1:chain:AgentExecutor > 10:chain:LLMChain > 11:llm:ActionsClientLlm] Entering LLM run with input: { "prompts": [ "[{\"lc\":1,\"type\":\"constructor\",\"id\":[\"langchain\",\"schema\",\"SystemMessage\"],\"kwargs\":{\"content\":\"Assistant is a large language model trained by OpenAI.\\n\\nAssistant is designed to be able to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. As a language model, Assistant is able to generate human-like text based on the input it receives, allowing it to engage in natural-sounding conversations and provide responses that are coherent and relevant to the topic at hand.\\n\\nAssistant is constantly learning and improving, and its capabilities are constantly evolving. It is able to process and understand large amounts of text, and can use this knowledge to provide accurate and informative responses to a wide range of questions. Additionally, Assistant is able to generate its own text based on the input it receives, allowing it to engage in discussions and provide explanations and descriptions on a wide range of topics.\\n\\nOverall, Assistant is a powerful system that can help with a wide range of tasks and provide valuable insights and information on a wide range of topics. Whether you need help with a specific question or just want to have a conversation about a particular topic, Assistant is here to assist. However, above all else, all responses must adhere to the format of RESPONSE FORMAT INSTRUCTIONS.\",\"additional_kwargs\":{}}},{\"lc\":1,\"type\":\"constructor\",\"id\":[\"langchain\",\"schema\",\"HumanMessage\"],\"kwargs\":{\"content\":\"TOOLS\\n------\\nAssistant can ask the user to use tools to look up information that may be helpful in answering the users original question. The tools the human can use are:\\n\\nesql-language-knowledge-base: Call this for knowledge on how to build an ESQL query, or answer questions about the ES|QL query language.\\n\\nRESPONSE FORMAT INSTRUCTIONS\\n----------------------------\\n\\nOutput a JSON markdown code snippet containing a valid JSON object in one of two formats:\\n\\n**Option 1:**\\nUse this if you want the human to use a tool.\\nMarkdown code snippet formatted in the following schema:\\n\\n```json\\n{\\n \\\"action\\\": string, // The action to take. Must be one of [esql-language-knowledge-base]\\n \\\"action_input\\\": string // The input to the action. May be a stringified object.\\n}\\n```\\n\\n**Option #2:**\\nUse this if you want to respond directly and conversationally to the human. Markdown code snippet formatted in the following schema:\\n\\n```json\\n{\\n \\\"action\\\": \\\"Final Answer\\\",\\n \\\"action_input\\\": string // You should put what you want to return to use here and make sure to use valid json newline characters.\\n}\\n```\\n\\nFor both options, remember to always include the surrounding markdown code snippet delimiters (begin with \\\"```json\\\" and end with \\\"```\\\")!\\n\\n\\nUSER'S INPUT\\n--------------------\\nHere is the user's input (remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else):\\n\\n\\n\\n\\n\\nFrom employees, I want to see the 5 earliest employees (hire_date), I want to display only the month and the year that they were hired in and their employee number (emp_no). Format the date as e.g. \\\"September 2019\\\". Only show the query\",\"additional_kwargs\":{}}},{\"lc\":1,\"type\":\"constructor\",\"id\":[\"langchain\",\"schema\",\"AIMessage\"],\"kwargs\":{\"content\":\"```json\\n{\\n \\\"action\\\": \\\"esql-language-knowledge-base\\\",\\n \\\"action_input\\\": \\\"Display the 'emp_no', month and year of the 5 earliest employees by 'hire_date'. Format the date as 'Month Year'.\\\"\\n}\\n```\",\"additional_kwargs\":{}}},{\"lc\":1,\"type\":\"constructor\",\"id\":[\"langchain\",\"schema\",\"HumanMessage\"],\"kwargs\":{\"content\":\"TOOL RESPONSE:\\n---------------------\\nFROM employees\\n| KEEP emp_no, hire_date\\n| EVAL month_year = DATE_FORMAT(hire_date, \\\"MMMM YYYY\\\")\\n| SORT hire_date\\n| LIMIT 5\\n\\nUSER'S INPUT\\n--------------------\\n\\nOkay, so what is the response to my last comment? If using information obtained from the tools you must mention it explicitly without mentioning the tool names - I have forgotten all TOOL RESPONSES! Remember to respond with a markdown code snippet of a json blob with a single action, and NOTHING else.\",\"additional_kwargs\":{}}}]" ] } [llm/end] [1:chain:AgentExecutor > 10:chain:LLMChain > 11:llm:ActionsClientLlm] [6.47s] Exiting LLM run with output: { "generations": [ [ { "text": "```json\n{\n \"action\": \"Final Answer\",\n \"action_input\": \"Here is the query to get the employee number and the formatted hire date for the 5 earliest employees by hire_date:\\n\\nFROM employees\\n| KEEP emp_no, hire_date\\n| EVAL month_year = DATE_FORMAT(hire_date, \\\"MMMM YYYY\\\")\\n| SORT hire_date\\n| LIMIT 5\"\n}\n```" } ] ] } [chain/end] [1:chain:AgentExecutor > 10:chain:LLMChain] [6.47s] Exiting Chain run with output: { "text": "```json\n{\n \"action\": \"Final Answer\",\n \"action_input\": \"Here is the query to get the employee number and the formatted hire date for the 5 earliest employees by hire_date:\\n\\nFROM employees\\n| KEEP emp_no, hire_date\\n| EVAL month_year = DATE_FORMAT(hire_date, \\\"MMMM YYYY\\\")\\n| SORT hire_date\\n| LIMIT 5\"\n}\n```" } [chain/end] [1:chain:AgentExecutor] [11.91s] Exiting Chain run with output: { "output": "Here is the query to get the employee number and the formatted hire date for the 5 earliest employees by hire_date:\n\nFROM employees\n| KEEP emp_no, hire_date\n| EVAL month_year = DATE_FORMAT(hire_date, \"MMMM YYYY\")\n| SORT hire_date\n| LIMIT 5" } ```
davismcphee
pushed a commit
that referenced
this pull request
Dec 4, 2023
## Summary ### This PR enables user roles testing in FTR We use SAML authentication to get session cookie for user with the specific role. The cookie is cached on FTR service side so we only make SAML auth one time per user within FTR config run. For Kibana CI service relies on changes coming in elastic#170852 In order to run FTR tests locally against existing MKI project: - add `.ftr/role_users.json` in Kibana root dir ``` { "viewer": { "email": "...", "password": "..." }, "developer": { "email": "...", "password": "..." } } ``` - set Cloud hostname (!not project hostname!) with TEST_CLOUD_HOST_NAME, e.g. `export TEST_CLOUD_HOST_NAME=console.qa.cld.elstc.co` ### How to use: - functional tests: ``` const svlCommonPage = getPageObject('svlCommonPage'); before(async () => { // login with Viewer role await svlCommonPage.loginWithRole('viewer'); // you are logged in in browser and on project home page, start the test }); it('has project header', async () => { await svlCommonPage.assertProjectHeaderExists(); }); ``` - API integration tests: ``` const svlUserManager = getService('svlUserManager'); const supertestWithoutAuth = getService('supertestWithoutAuth'); let credentials: { Cookie: string }; before(async () => { // get auth header for Viewer role credentials = await svlUserManager.getApiCredentialsForRole('viewer'); }); it('returns full status payload for authenticated request', async () => { const { body } = await supertestWithoutAuth .get('/api/status') .set(credentials) .set('kbn-xsrf', 'kibana'); expect(body.name).to.be.a('string'); expect(body.uuid).to.be.a('string'); expect(body.version.number).to.be.a('string'); }); ``` Flaky-test-runner: #1 https://buildkite.com/elastic/kibana-flaky-test-suite-runner/builds/4081 #2 https://buildkite.com/elastic/kibana-flaky-test-suite-runner/builds/4114 --------- Co-authored-by: Robert Oskamp <[email protected]> Co-authored-by: kibanamachine <[email protected]> Co-authored-by: Aleh Zasypkin <[email protected]>
davismcphee
pushed a commit
that referenced
this pull request
Jan 4, 2024
davismcphee
pushed a commit
that referenced
this pull request
Jan 4, 2024
## Summary The previous PR elastic#161813 was reverted due to the broken webpack config elastic@eef1afc --------- Co-authored-by: Tiago Costa <[email protected]> Co-authored-by: kibanamachine <[email protected]> Co-authored-by: Jon <[email protected]>
davismcphee
pushed a commit
that referenced
this pull request
Jan 22, 2024
…ic#175194) ## Summary This PR fixes the issue causing (mostly) [login journey](https://buildkite.com/elastic/kibana-single-user-performance/builds/12398#018d1149-cc2e-4591-a61c-176768081e2c) stuck for 14 min waiting for Telemetry call response. <img width="964" alt="Screenshot 2024-01-22 at 11 12 24" src="https://github.com/elastic/kibana/assets/10977896/8cadc2ec-ee84-42f6-8a0c-ad949367429c"> I believe the issue was in how we handle the Observables for request events. I added extra comment in the particular code change. I no longer can reproduce it, all the events are reported correctly: <img width="964" alt="image" src="https://github.com/elastic/kibana/assets/10977896/fa2c4b27-dcf2-480b-a07f-aeb23045149a"> Logs cleaning is to log in console only performance metrics event but not all EBT elements. Also not to report some browser errors that not Kibana specific. Testing: run the following script 3-4 times ``` PERFORMANCE_ENABLE_TELEMETRY=1 node scripts/run_performance.js --journey-path x-pack/performance/journeys/login.ts ``` - script is completed without delays (e.g. doesn't hang on after hook in TEST phase) - telemetry requests are logged with correct counter and all finished, e.g. `Waiting for telemetry request #2 to complete` is followed by `Telemetry request #2 complete` - only events started with `Report event "performance_metric"` are in console output
davismcphee
pushed a commit
that referenced
this pull request
May 18, 2024
## Summary Set `security.session.cleanupInterval` to 5h for session concurrency test. ### **Prerequisites** - Task for session cleanup with [default schedule set to 1h](https://github.com/elastic/kibana/blob/main/x-pack/plugins/security/server/config.ts#L222). - Task polling interval is set to [3000ms](https://github.com/elastic/kibana/blob/main/x-pack/plugins/task_manager/server/config.ts#L13). - We override `scheduledAt` once we make a request in [runCleanupTaskSoon](https://github.com/elastic/kibana/blob/main/x-pack/test/security_api_integration/tests/session_concurrent_limit/cleanup.ts#L145). ### **Hypothesis** Taking into consideration that: - `session_cleanup` task is not the only one scheduled during test run. - There is sort of an exponential backoff implemented for task polling if there are too many retries. - Clock jitter. I had a hypothesis that if our whole test run exceeds 1h or polling interval gets adjusted because of retries we might end up executing the scheduled cleanup before we trigger `runCleanupTaskSoon` (this is there we drop 1 session already). ### **FTR runs (x55 each)** - `cleanupInterval` set to 5h: [#1](https://buildkite.com/elastic/kibana-flaky-test-suite-runner/builds/5986) :green_circle:, [#2](https://buildkite.com/elastic/kibana-flaky-test-suite-runner/builds/5987) :green_circle: - `cleanupInterval` set to default 1h: [#1](https://buildkite.com/elastic/kibana-flaky-test-suite-runner/builds/5983) :green_circle:, [#2](https://buildkite.com/elastic/kibana-flaky-test-suite-runner/builds/5982) :red_circle: (has 2 failures out of 55) ### Checklist - [x] [Flaky Test Runner](https://ci-stats.kibana.dev/trigger_flaky_test_runner/1) was used on any tests changed ### For maintainers - [x] This was checked for breaking API changes and was [labeled appropriately](https://www.elastic.co/guide/en/kibana/master/contributing.html#kibana-release-notes-process) __Fixes: https://github.com/elastic/kibana/issues/149091__
davismcphee
pushed a commit
that referenced
this pull request
Aug 13, 2024
## Summary Resolves elastic#143905. This PR adds support for integration-level outputs. This means that different integrations within the same agent policy can now be configured to send data to different locations. This feature is gated behind `enterprise` level subscription. For each input, the agent policy will configure sending data to the following outputs in decreasing order of priority: 1. Output set specifically on the integration policy 2. Output set specifically on the integration's parent agent policy (including the case where an integration policy belongs to multiple agent policies) 3. Global default data output set via Fleet Settings Integration-level outputs will respect the same rules as agent policy-level outputs: - Certain integrations are disallowed from using certain output types, attempting to add them to each other via creation, updating, or "defaulting", will fail - `fleet-server`, `synthetics`, and `apm` can only use same-cluster Elasticsearch output - When an output is deleted, any integrations that were specifically using it will "clear" their output configuration and revert back to either `#2` or `#3` in the above list - When an output is edited, all agent policies across all spaces that use it will be bumped to a new revision, this includes: - Agent policies that have that output specifically set in their settings (existing behavior) - Agent policies that contain integrations which specifically has that output set (new behavior) - When a proxy is edited, the same new revision bump above will apply for any outputs using that proxy The final agent policy YAML that is generated will have: - `outputs` block that includes: - Data and monitoring outputs set at the agent policy level (existing behavior) - Any additional outputs set at the integration level, if they differ from the above - `outputs_permissions` block that includes permissions for each Elasticsearch output depending on which integrations and/or agent monitoring are assigned to it Integration policies table now includes `Output` column. If the output is defaulting to agent policy-level output, or global setting output, a tooltip is shown: <img width="1392" alt="image" src="https://github.com/user-attachments/assets/5534716b-49b5-402a-aa4a-4ba6533e0ca8"> Configuring an integration-level output is done under Advanced options in the policy editor. Setting to the blank value will "clear" the output configuration. The list of available outputs is filtered by what outputs are available for that integration (see above): <img width="799" alt="image" src="https://github.com/user-attachments/assets/617af6f4-e8f8-40b1-b476-848f8ac96e76"> An example of failure: ES output cannot be changed to Kafka while there is an integration <img width="1289" alt="image" src="https://github.com/user-attachments/assets/11847eb5-fd5d-4271-8464-983d7ab39218"> ## TODO - [x] Adjust side effects of editing/deleting output when policies use it across different spaces - [x] Add API integration tests - [x] Update OpenAPI spec - [x] Create doc issue ### Checklist Delete any items that are not applicable to this PR. - [x] Any text added follows [EUI's writing guidelines](https://elastic.github.io/eui/#/guidelines/writing), uses sentence case text and includes [i18n support](https://github.com/elastic/kibana/blob/main/packages/kbn-i18n/README.md) - [ ] [Documentation](https://www.elastic.co/guide/en/kibana/master/development-documentation.html) was added for features that require explanation or tutorials - [x] [Unit or functional tests](https://www.elastic.co/guide/en/kibana/master/development-tests.html) were updated or added to match the most common scenarios --------- Co-authored-by: kibanamachine <[email protected]>
davismcphee
pushed a commit
that referenced
this pull request
Sep 20, 2024
…193441) ## Summary More files to be regenerated with a different shape since the js-yaml update: elastic#190678
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Summary