import { pick } from 'lodash'; import { llm } from '@grafana/llm'; import { config } from '@grafana/runtime'; import { Panel } from '@grafana/schema'; import { DashboardModel } from '../../state/DashboardModel'; import { PanelModel } from '../../state/PanelModel'; import { NEW_PANEL_TITLE } from '../../utils/dashboard'; import { getDashboardStringDiff } from './jsonDiffText'; export enum Role { // System content cannot be overwritten by user prompts. 'system' = 'system', // User content is the content that the user has entered. // This content can be overwritten by following prompt. 'user' = 'user', } export type Message = llm.Message; export enum QuickFeedbackType { Shorter = 'Even shorter', MoreDescriptive = 'More descriptive', Regenerate = 'Please, regenerate', } /** * The LLM model to be used. * * The LLM app abstracts the actual model name since it depends on the provider. * We want to default to whatever the 'large' model is. */ export const DEFAULT_LLM_MODEL: llm.Model = llm.Model.LARGE; /** * Sanitize the reply from OpenAI by removing the leading and trailing quotes. */ export const sanitizeReply = (reply: string) => { return reply.replace(/^"|"$/g, ''); }; /** * Diff the current dashboard with the original dashboard and the dashboard after migration * to split the changes into user changes and migration changes. * * User changes: changes made by the user * * Migration changes: changes made by the DashboardMigrator after opening the dashboard * * @param dashboard current dashboard to be saved * @returns user changes and migration changes */ export function getDashboardChanges(dashboard: DashboardModel): { userChanges: string; migrationChanges: string; } { const { migrationDiff, userDiff } = getDashboardStringDiff(dashboard); return { userChanges: userDiff, migrationChanges: migrationDiff, }; } // Shared healthcheck promise so avoid multiple calls llm app settings and health check APIs let llmHealthCheck: Promise<boolean> | undefined; /** * Check if the LLM plugin is enabled. * @returns true if the LLM plugin is enabled. */ export async function isLLMPluginEnabled(): Promise<boolean> { if (!config.apps['grafana-llm-app']) { return false; } if (llmHealthCheck) { return llmHealthCheck; } // Check if the LLM plugin is enabled. // If not, we won't be able to make requests, so return early. llmHealthCheck = new Promise((resolve) => { llm.health().then((response) => { if (!response.ok) { // Health check fail clear cached promise so we can try again later llmHealthCheck = undefined; } resolve(response.ok); }); }); return llmHealthCheck; } /** * Get the message to be sent to OpenAI to generate a new response. * @param previousResponse * @param feedback * @returns Message[] to be sent to OpenAI to generate a new response */ export const getFeedbackMessage = (previousResponse: string, feedback: string | QuickFeedbackType): Message[] => { return [ { role: Role.system, content: `Your previous response was: ${previousResponse}. The user has provided the following feedback: ${feedback}. Re-generate your response according to the provided feedback.`, }, ]; }; /** * * @param dashboard Dashboard to generate a title or description for * @returns String for inclusion in prompts stating what the dashboard's panels are */ export function getDashboardPanelPrompt(dashboard: DashboardModel): string { const panelStrings: string[] = getPanelStrings(dashboard); let panelPrompt: string; if (panelStrings.length <= 10) { panelPrompt = `The panels in the dashboard are:\n${panelStrings.join('\n')}`; } else { const withDescriptions = dashboard.panels.filter((panel) => panel.description); const withoutDescriptions = dashboard.panels.filter((panel) => !panel.description); let concatenatedPanelStrings; if (withDescriptions.length >= 10) { concatenatedPanelStrings = withDescriptions.slice(10).map(getPanelString).join('\n'); } else { concatenatedPanelStrings = withDescriptions.map(getPanelString).join('\n'); concatenatedPanelStrings += '\n'; concatenatedPanelStrings += withoutDescriptions .slice(10 - withDescriptions.length) .map(getPanelString) .join('n'); } panelPrompt = `There are ${panelStrings.length} panels.\n` + 'Due to space constraints, only the information for ten of them is presented.\n' + 'These ten are not necessarily the first ten, but prioritized to those with descriptions.\n' + `The panels in the dashboard are:\n${concatenatedPanelStrings}`; } // This truncation should prevent exceeding the allowed size for GPT calls. // Additionally, context windows that are too long degrade performance, // So it is possibly that if we can condense it further it would be better return panelPrompt; } export function getFilteredPanelString(panel: Panel): string { const keysToKeep: Array<keyof Panel> = ['datasource', 'title', 'description', 'targets', 'type']; const filteredPanel: Partial<Panel> = { ...pick(panel, keysToKeep), options: pick(panel.options, [ // For text panels, the content property helps generate the panel metadata 'content', ]), }; return JSON.stringify(filteredPanel, null, 2); } export const DASHBOARD_NEED_PANEL_TITLES_AND_DESCRIPTIONS_MESSAGE = 'To generate this content your dashboard must contain at least one panel with a valid title or description.'; export function getPanelStrings(dashboard: DashboardModel): string[] { const panelStrings = dashboard.panels .filter( (panel) => (panel.title && panel.title !== NEW_PANEL_TITLE) || (panel.description && panel.description.length > 0) ) .map(getPanelString); return panelStrings; } const getPanelString = (panel: PanelModel, idx: number) => `- Panel ${idx} - Title: ${panel.title}${panel.description ? `\n- Description: ${panel.description}` : ''}`;