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* Add Application Insights Provider * Change from CRLF to LF * Change biceps line ending * Refactor ApplicationInsightsProvider and initializeTelemetry * Add session parameter to initializeTelemetry function * Add logger and track metrics for prompt and completion tokens * Add OpenTelemetry instrumentation for metrics tracking * Update model encoding to "gpt-4" * Add OpenTelemetry metrics instrumentation * Remove cleanup step * Add chat metrics tracking and token service
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,20 @@ | ||
| 'use client' | ||
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| import { AppInsightsContext } from '@microsoft/applicationinsights-react-js' | ||
| import { createContext } from 'react' | ||
| import { initializeTelemetry } from './application-insights-service' | ||
| import { useSession } from 'next-auth/react' | ||
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| export const ApplicationInsightsContext = createContext({}) | ||
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| export default function ApplicationInsightsProvider({ | ||
| instrumentationKey, | ||
| children, | ||
| }: { | ||
| instrumentationKey: string, | ||
| children: React.ReactNode | ||
| }) { | ||
| const session = useSession() | ||
| const { reactPlugin } = initializeTelemetry(instrumentationKey, session) | ||
| return <AppInsightsContext.Provider value={reactPlugin}>{children}</AppInsightsContext.Provider> | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,55 @@ | ||
| "use client" | ||
| import {ApplicationInsights, ITelemetryItem} from '@microsoft/applicationinsights-web'; | ||
| import {ReactPlugin} from '@microsoft/applicationinsights-react-js'; | ||
| import { SessionContextValue } from 'next-auth/react'; | ||
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| let logger: ApplicationInsights; | ||
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| function initializeTelemetry(instrumentationKey: string, session: SessionContextValue): { reactPlugin: ReactPlugin, appInsights: ApplicationInsights } { | ||
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| const defaultBrowserHistory = { | ||
| url: "/", | ||
| location: { pathname: ""}, | ||
| state: { url: "" }, | ||
| listen: () => {}, | ||
| }; | ||
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| let browserHistory = defaultBrowserHistory; | ||
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| if (typeof window !== "undefined") { | ||
| browserHistory = { ...browserHistory, ...window.history }; | ||
| browserHistory.location.pathname = browserHistory?.state?.url; | ||
| } | ||
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| const reactPlugin = new ReactPlugin(); | ||
| const appInsights = new ApplicationInsights({ | ||
| config: { | ||
| instrumentationKey: instrumentationKey, | ||
| extensions: [reactPlugin], | ||
| extensionConfig: { | ||
| [reactPlugin.identifier]: { history: browserHistory }, | ||
| }, | ||
| enableAutoRouteTracking: true, | ||
| disableAjaxTracking: false, | ||
| autoTrackPageVisitTime: true, | ||
| enableCorsCorrelation: true, | ||
| enableRequestHeaderTracking: true, | ||
| enableResponseHeaderTracking: true, | ||
| } | ||
| }); | ||
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| appInsights.loadAppInsights(); | ||
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| appInsights.addTelemetryInitializer((env:ITelemetryItem) => { | ||
| env.tags = env.tags || []; | ||
| env.tags["ai.cloud.role"] = "Bühler ChatGPT"; | ||
| env.data = env.data || []; | ||
| env.data["email"] = session?.data?.user?.email; | ||
| }); | ||
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| logger = appInsights; | ||
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| return { reactPlugin, appInsights }; | ||
| } | ||
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| export { initializeTelemetry, logger }; |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,50 @@ | ||
| import { metrics } from "@opentelemetry/api"; | ||
| import { userHashedId, userSession } from "@/features/auth/helpers"; | ||
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| function getChatMeter(){ | ||
| const meter = metrics.getMeter("chat"); | ||
| return meter; | ||
| } | ||
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| async function getAttributes(chatModel: string){ | ||
| const user = await userSession(); | ||
| const userId = await userHashedId(); | ||
| const attributes = { "email": user?.email, "name": user?.name, "userHashedId": userId, "chatModel": chatModel || "unknown", "userId": userId }; | ||
| return attributes; | ||
| } | ||
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| export async function reportPromptTokens(tokenCount: number, model: string) { | ||
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| const meter = getChatMeter(); | ||
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| const promptTokensUsed = meter.createHistogram("promptTokensUsed", { | ||
| description: "Number of tokens used in the input prompt", | ||
| unit: "tokens", | ||
| }); | ||
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| promptTokensUsed.record(tokenCount, await getAttributes(model)); | ||
| } | ||
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| export async function reportCompletionTokens(tokenCount: number, model: string) { | ||
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| const meter = getChatMeter(); | ||
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| const completionsTokensUsed = meter.createHistogram("completionsTokensUsed", { | ||
| description: "Number of tokens used in the completions", | ||
| unit: "tokens", | ||
| }); | ||
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| completionsTokensUsed.record(tokenCount, await getAttributes(model)); | ||
| } | ||
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| export async function reportUserChatMessage(model: string) { | ||
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| const meter = getChatMeter(); | ||
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| const userChatMessage = meter.createCounter("userChatMessage", { | ||
| description: "Number of messages", | ||
| unit: "messages", | ||
| }); | ||
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| userChatMessage.add(1, await getAttributes(model)); | ||
| } |
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