elastic · viduni94 · Aug 11, 2025 · Jun 11, 2025 · Jun 16, 2025 · Jun 16, 2025
@@ -5,8 +5,7 @@
  * 2.0.
  */
 
-import { Message } from '@kbn/observability-ai-assistant-plugin/common';
-import { CONTEXT_FUNCTION_NAME } from '@kbn/observability-ai-assistant-plugin/server/functions/context/context';
+import { CONTEXT_FUNCTION_NAME, Message } from '@kbn/observability-ai-assistant-plugin/common';
 import { reverseToLastUserMessage } from './chat_body';
 
 describe('<ChatBody>', () => {

@@ -12,7 +12,7 @@ import { __IntlProvider as IntlProvider } from '@kbn/i18n-react';
 import { ChatState, Message, MessageRole } from '@kbn/observability-ai-assistant-plugin/public';
 import { createMockChatService } from './create_mock_chat_service';
 import { KibanaContextProvider } from '@kbn/triggers-actions-ui-plugin/public/common/lib/kibana';
-import { CONTEXT_FUNCTION_NAME } from '@kbn/observability-ai-assistant-plugin/server/functions/context/context';
+import { CONTEXT_FUNCTION_NAME } from '@kbn/observability-ai-assistant-plugin/common';
 
 const mockChatService = createMockChatService();
 

@@ -0,0 +1,44 @@
+/*
+ * Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
+ * or more contributor license agreements. Licensed under the Elastic License
+ * 2.0; you may not use this file except in compliance with the Elastic License
+ * 2.0.
+ */
+
+// Context tools
+export const CONTEXT_FUNCTION_NAME = 'context';
+export const GET_DATA_ON_SCREEN_FUNCTION_NAME = 'get_data_on_screen';
+
+// Alerts tools
+export const GET_ALERTS_DATASET_INFO_FUNCTION_NAME = 'get_alerts_dataset_info';
+export const ALERTS_FUNCTION_NAME = 'alerts';
+
+// Query tools
+export const QUERY_FUNCTION_NAME = 'query';
+export const EXECUTE_QUERY_FUNCTION_NAME = 'execute_query';
+export const VISUALIZE_QUERY_FUNCTION_NAME = 'visualize_query';
+
+// Dataset tools
+export const GET_DATASET_INFO_FUNCTION_NAME = 'get_dataset_info';
+export const SELECT_RELEVANT_FIELDS_NAME = 'select_relevant_fields';
+
+export const ELASTICSEARCH_FUNCTION_NAME = 'elasticsearch';
+
+export const EXECUTE_CONNECTOR_FUNCTION_NAME = 'execute_connector';
+
+export const KIBANA_FUNCTION_NAME = 'kibana';
+
+export const SUMMARIZE_FUNCTION_NAME = 'summarize';
+
+export const CHANGES_FUNCTION_NAME = 'changes';
+
+export const RETRIEVE_ELASTIC_DOC_FUNCTION_NAME = 'retrieve_elastic_doc';
+
+// APM tools
+export const GET_APM_DATASET_INFO_FUNCTION_NAME = 'get_apm_dataset_info';
+export const GET_APM_DOWNSTREAM_DEPENDENCIES_FUNCTION_NAME = 'get_apm_downstream_dependencies';
+export const GET_APM_SERVICES_LIST_FUNCTION_NAME = 'get_apm_services_list';
+
+// Deprecated tools
+export const GET_APM_TIMESERIES_FUNCTION_NAME = 'get_apm_timeseries';
+export const LENS_FUNCTION_NAME = 'lens';
@@ -59,3 +59,26 @@ export {
   E5_LARGE_IN_EIS_INFERENCE_ID,
   EIS_PRECONFIGURED_INFERENCE_IDS,
 } from './preconfigured_inference_ids';
+
+export {
+  GET_ALERTS_DATASET_INFO_FUNCTION_NAME,
+  ALERTS_FUNCTION_NAME,
+  QUERY_FUNCTION_NAME,
+  EXECUTE_QUERY_FUNCTION_NAME,
+  GET_DATA_ON_SCREEN_FUNCTION_NAME,
+  CONTEXT_FUNCTION_NAME,
+  ELASTICSEARCH_FUNCTION_NAME,
+  EXECUTE_CONNECTOR_FUNCTION_NAME,
+  GET_DATASET_INFO_FUNCTION_NAME,
+  SELECT_RELEVANT_FIELDS_NAME,
+  KIBANA_FUNCTION_NAME,
+  SUMMARIZE_FUNCTION_NAME,
+  VISUALIZE_QUERY_FUNCTION_NAME,
+  CHANGES_FUNCTION_NAME,
+  RETRIEVE_ELASTIC_DOC_FUNCTION_NAME,
+  GET_APM_DATASET_INFO_FUNCTION_NAME,
+  GET_APM_DOWNSTREAM_DEPENDENCIES_FUNCTION_NAME,
+  GET_APM_SERVICES_LIST_FUNCTION_NAME,
+  GET_APM_TIMESERIES_FUNCTION_NAME,
+  LENS_FUNCTION_NAME,
+} from './function_names';
@@ -16,7 +16,8 @@
       "security",
       "taskManager",
       "dataViews",
-      "inference"
+      "inference",
+      "llmTasks"
     ],
     "optionalPlugins": ["cloud", "serverless"],
     "requiredBundles": ["kibanaReact", "kibanaUtils"],

@@ -6,11 +6,9 @@
  */
 
 import { last } from 'lodash';
-import { Message, MessageRole } from '../../../common';
+import { CONTEXT_FUNCTION_NAME, Message, MessageRole } from '../../../common';
 import { removeContextToolRequest } from './context';
 
-const CONTEXT_FUNCTION_NAME = 'context';
-
 describe('removeContextToolRequest', () => {
   const baseMessages: Message[] = [
     {

@@ -10,15 +10,14 @@ import { encode } from 'gpt-tokenizer';
 import { compact, last } from 'lodash';
 import { Observable } from 'rxjs';
 import { FunctionRegistrationParameters } from '..';
+import { CONTEXT_FUNCTION_NAME } from '../../../common';
 import { MessageAddEvent } from '../../../common/conversation_complete';
 import { Message } from '../../../common/types';
 import { createFunctionResponseMessage } from '../../../common/utils/create_function_response_message';
 import { recallAndScore } from './utils/recall_and_score';
 
 const MAX_TOKEN_COUNT_FOR_DATA_ON_SCREEN = 1000;
 
-export const CONTEXT_FUNCTION_NAME = 'context';
-
 export function registerContextFunction({
   client,
   functions,
@@ -39,8 +38,8 @@ export function registerContextFunction({
         const screenDescription = compact(
           screenContexts.map((context) => context.screenDescription)
         ).join('\n\n');
-        // any data that falls within the token limit, send it automatically
 
+        // any data that falls within the token limit, send it automatically
         const dataWithinTokenLimit = compact(
           screenContexts.flatMap((context) => context.data)
         ).filter(

@@ -6,8 +6,7 @@
  */
 
 import type { FunctionRegistrationParameters } from '.';
-
-export const ELASTICSEARCH_FUNCTION_NAME = 'elasticsearch';
+import { ELASTICSEARCH_FUNCTION_NAME } from '..';
 
 export function registerElasticsearchFunction({
   functions,

@@ -6,8 +6,7 @@
  */
 
 import { FunctionRegistrationParameters } from '.';
-
-export const EXECUTE_CONNECTOR_FUNCTION_NAME = 'execute_connector';
+import { EXECUTE_CONNECTOR_FUNCTION_NAME } from '..';
 
 export function registerExecuteConnectorFunction({
   functions,

@@ -9,8 +9,7 @@ import { compact } from 'lodash';
 import dedent from 'dedent';
 import { ObservabilityAIAssistantScreenContextRequest } from '../../common/types';
 import { ChatFunctionClient } from '../service/chat_function_client';
-
-export const GET_DATA_ON_SCREEN_FUNCTION_NAME = 'get_data_on_screen';
+import { GET_DATA_ON_SCREEN_FUNCTION_NAME, CONTEXT_FUNCTION_NAME } from '../../common';
 
 export function registerGetDataOnScreenFunction(
   functions: ChatFunctionClient,
@@ -49,11 +48,19 @@ export function registerGetDataOnScreenFunction(
     }
   );
 
-  functions.registerInstruction(({ availableFunctionNames }) =>
-    availableFunctionNames.includes(GET_DATA_ON_SCREEN_FUNCTION_NAME)
-      ? `The ${GET_DATA_ON_SCREEN_FUNCTION_NAME} function will retrieve specific content from the user's screen by specifying a data key. Use this tool to provide context-aware responses. Available data: ${dedent(
+  functions.registerInstruction(({ availableFunctionNames }) => {
+    if (availableFunctionNames.includes(GET_DATA_ON_SCREEN_FUNCTION_NAME)) {
+      return `You have access to data on the screen by calling the "${GET_DATA_ON_SCREEN_FUNCTION_NAME}" tool.
+        Use it to help the user understand what they are looking at. 
+
+        This tool will retrieve specific content from the user's screen by specifying a data key. Use this tool to provide context-aware responses. Available data: ${dedent(
           allData.map((data) => `${data.name}: ${data.description}`).join('\n')
-        )}`
-      : undefined
-  );
+        )}
+
+        A short summary of what they are looking at is available in the return of the "${CONTEXT_FUNCTION_NAME}" function.
+        Data that is compact enough automatically gets included in the response for the "${CONTEXT_FUNCTION_NAME}" function.`;
+    }
+
+    return undefined;
+  });
 }
@@ -9,11 +9,15 @@ import type { ElasticsearchClient, SavedObjectsClientContract } from '@kbn/core/
 import type { DataViewsServerPluginStart } from '@kbn/data-views-plugin/server';
 import { castArray, chunk, groupBy, uniq } from 'lodash';
 import { lastValueFrom } from 'rxjs';
-import { MessageRole, ShortIdTable, type Message } from '../../../common';
+import {
+  MessageRole,
+  ShortIdTable,
+  type Message,
+  SELECT_RELEVANT_FIELDS_NAME,
+} from '../../../common';
 import { concatenateChatCompletionChunks } from '../../../common/utils/concatenate_chat_completion_chunks';
 import { FunctionCallChatFunction } from '../../service/types';
 
-export const SELECT_RELEVANT_FIELDS_NAME = 'select_relevant_fields';
 export const GET_RELEVANT_FIELD_NAMES_SYSTEM_MESSAGE = `You are a helpful assistant for Elastic Observability. 
 Your task is to determine which fields are relevant to the conversation by selecting only the field IDs from the provided list. 
 The list in the user message consists of JSON objects that map a human-readable field "name" to its unique "id". 

@@ -6,13 +6,11 @@
  */
 
 import { IScopedClusterClient, Logger } from '@kbn/core/server';
-import { Message } from '../../../common';
+import { GET_DATASET_INFO_FUNCTION_NAME, Message } from '../../../common';
 import { FunctionRegistrationParameters } from '..';
 import { FunctionCallChatFunction, RespondFunctionResources } from '../../service/types';
 import { getRelevantFieldNames } from './get_relevant_field_names';
 
-export const GET_DATASET_INFO_FUNCTION_NAME = 'get_dataset_info';
-
 export function registerGetDatasetInfoFunction({
   resources,
   functions,

@@ -5,23 +5,19 @@
  * 2.0.
  */
 
-import dedent from 'dedent';
 import { KnowledgeBaseState } from '../../common';
-import { CONTEXT_FUNCTION_NAME, registerContextFunction } from './context/context';
-import { registerSummarizationFunction, SUMMARIZE_FUNCTION_NAME } from './summarize';
+import { registerContextFunction } from './context/context';
+import { registerSummarizationFunction } from './summarize';
 import type { RegistrationCallback } from '../service/types';
 import { registerElasticsearchFunction } from './elasticsearch';
-import { GET_DATASET_INFO_FUNCTION_NAME, registerGetDatasetInfoFunction } from './get_dataset_info';
+import { registerGetDatasetInfoFunction } from './get_dataset_info';
 import { registerKibanaFunction } from './kibana';
 import { registerExecuteConnectorFunction } from './execute_connector';
-import { GET_DATA_ON_SCREEN_FUNCTION_NAME } from './get_data_on_screen';
-
-// cannot be imported from x-pack/solutions/observability/plugins/observability_ai_assistant_app/server/functions/query/index.ts due to circular dependency
-export const QUERY_FUNCTION_NAME = 'query';
+import { getObservabilitySystemPrompt } from '../prompts/system_prompt';
 
 export type FunctionRegistrationParameters = Omit<
   Parameters<RegistrationCallback>[0],
-  'registerContext' | 'hasFunction'
+  'registerContext' | 'hasFunction' | 'pluginsStart'
 >;
 
 export const registerFunctions: RegistrationCallback = async ({
@@ -30,6 +26,7 @@ export const registerFunctions: RegistrationCallback = async ({
   resources,
   signal,
   scopes,
+  pluginsStart,
 }) => {
   const registrationParameters: FunctionRegistrationParameters = {
     client,
@@ -44,102 +41,38 @@ export const registerFunctions: RegistrationCallback = async ({
   const isObservabilityDeployment = scopes.includes('observability');
   const isGenericDeployment = scopes.length === 0 || (scopes.length === 1 && scopes[0] === 'all');
 
-  if (isObservabilityDeployment || isGenericDeployment) {
-    functions.registerInstruction(`
-${
-  isObservabilityDeployment
-    ? `You are a helpful assistant for Elastic Observability. Your goal is to help the Elastic Observability users to quickly assess what is happening in their observed systems. You can help them visualise and analyze data, investigate their systems, perform root cause analysis or identify optimisation opportunities.`
-    : `You are a helpful assistant for Elasticsearch. Your goal is to help Elasticsearch users accomplish tasks using Kibana and Elasticsearch. You can help them construct queries, index data, search data, use Elasticsearch APIs, generate sample data, visualise and analyze data.`
-}
-      It's very important to not assume what the user means. Ask them for clarification if needed.
-
-      If you are unsure about which function should be used and with what arguments, ask the user for clarification or confirmation.
-
-      In KQL ("kqlFilter")) escaping happens with double quotes, not single quotes. Some characters that need escaping are: ':()\\\
-      /\". Always put a field value in double quotes. Best: service.name:\"opbeans-go\". Wrong: service.name:opbeans-go. This is very important!
-
-      You can use Github-flavored Markdown in your responses. If a function returns an array, consider using a Markdown table to format the response.
-
-      ${
-        isObservabilityDeployment
-          ? 'Note that ES|QL (the Elasticsearch Query Language which is a new piped language) is the preferred query language.'
-          : ''
-      }
-
-      If you want to call a function or tool, only call it a single time per message. Wait until the function has been executed and its results
-      returned to you, before executing the same tool or another tool again if needed.
-
-
-      ${
-        isObservabilityDeployment
-          ? 'DO NOT UNDER ANY CIRCUMSTANCES USE ES|QL syntax (`service.name == "foo"`) with "kqlFilter" (`service.name:"foo"`).'
-          : ''
-      }
-
-      The user is able to change the language which they want you to reply in on the settings page of the AI Assistant for Observability and Search, which can be found in the ${
-        isServerless ? `Project settings.` : `Stack Management app under the option AI Assistants`
-      }.
-      If the user asks how to change the language, reply in the same language the user asked in.`);
-  }
-
   const { kbState } = await client.getKnowledgeBaseStatus();
   const isKnowledgeBaseReady = kbState === KnowledgeBaseState.READY;
 
-  functions.registerInstruction(({ availableFunctionNames }) => {
-    const instructions: string[] = [];
-
-    if (
-      availableFunctionNames.includes(QUERY_FUNCTION_NAME) &&
-      availableFunctionNames.includes(GET_DATASET_INFO_FUNCTION_NAME)
-    ) {
-      instructions.push(`You MUST use the "${GET_DATASET_INFO_FUNCTION_NAME}" ${
-        functions.hasFunction('get_apm_dataset_info') ? 'or the get_apm_dataset_info' : ''
-      } function before calling the "${QUERY_FUNCTION_NAME}" or the "changes" functions.
-
-      If a function requires an index, you MUST use the results from the dataset info functions.`);
-    }
+  // determine if product documentation is installed
+  const llmTasks = pluginsStart?.llmTasks;
+  const isProductDocsAvailable = llmTasks ? await llmTasks.retrieveDocumentationAvailable() : false;
 
-    if (availableFunctionNames.includes(GET_DATA_ON_SCREEN_FUNCTION_NAME)) {
-      instructions.push(`You have access to data on the screen by calling the "${GET_DATA_ON_SCREEN_FUNCTION_NAME}" function.
-        Use it to help the user understand what they are looking at. A short summary of what they are looking at is available in the return of the "${CONTEXT_FUNCTION_NAME}" function.
-        Data that is compact enough automatically gets included in the response for the "${CONTEXT_FUNCTION_NAME}" function.`);
-    }
-
-    if (isKnowledgeBaseReady) {
-      if (availableFunctionNames.includes(SUMMARIZE_FUNCTION_NAME)) {
-        instructions.push(`You can use the "${SUMMARIZE_FUNCTION_NAME}" function to store new information you have learned in a knowledge database.
-          If the user asks to remember or store some information, always use this function.
-          All summaries MUST be created in English, even if the conversation was carried out in a different language.`);
-      }
-
-      if (availableFunctionNames.includes(CONTEXT_FUNCTION_NAME)) {
-        instructions.push(
-          `You can use the "${CONTEXT_FUNCTION_NAME}" function to retrieve relevant information from the knowledge database. The response will include a "learnings" field containing information
-          from the knowledge base that is most relevant to the user's current query. You should incorporate these learnings into your responses when answering the user's questions.
-          The information in the "learnings" field contains up-to-date information that you should consider when formulating your responses. DO NOT add disclaimers about the currency or certainty of this information.
-          Present this information directly without qualifiers like "I don't have specific, up-to-date information" or "I can't be completely certain".
-
-          Stick strictly to the information provided in the "learnings" field. DO NOT assume, infer, or add any details that are not explicitly stated in the response.
-          If the user asks for information that is not covered in the "learnings" field, acknowledge the gap and ask for clarification rather than making assumptions or offering suggestions that aren't based on the provided knowledge.`
-        );
-      }
-    } else {
-      instructions.push(
-        `You do not have a working memory. If the user expects you to remember the previous conversations, tell them they can set up the knowledge base.`
-      );
-    }
-    return instructions.map((instruction) => dedent(instruction));
-  });
+  if (isObservabilityDeployment || isGenericDeployment) {
+    functions.registerInstruction(({ availableFunctionNames }) =>
+      getObservabilitySystemPrompt({
+        availableFunctionNames,
+        isServerless,
+        isKnowledgeBaseReady,
+        isObservabilityDeployment,
+        isProductDocsAvailable,
+      })
+    );
+  }
 
   if (isKnowledgeBaseReady) {
     registerSummarizationFunction(registrationParameters);
+  } else {
+    functions.registerInstruction(
+      `You do not have a working memory. If the user expects you to remember the previous conversations, tell them they can set up the knowledge base.`
+    );
   }
 
   registerContextFunction({ ...registrationParameters, isKnowledgeBaseReady });
 
   registerElasticsearchFunction(registrationParameters);
-  const request = registrationParameters.resources.request;
 
+  const request = registrationParameters.resources.request;
   if ('id' in request) {
     registerKibanaFunction({
       ...registrationParameters,
@@ -149,6 +82,7 @@ ${
       },
     });
   }
+
   registerGetDatasetInfoFunction(registrationParameters);
 
   registerExecuteConnectorFunction(registrationParameters);