add llm functionality

2025-12-30 18:30:32 -06:00 · 2024-08-21 16:35:33 +02:00
parent da124bbbbe
commit a69df3baf0
22 changed files with 394 additions and 129 deletions
--- a/apps/web/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/actions.ts
+++ b/apps/web/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/actions.ts
@@ -1,20 +1,20 @@
 "use server";

 import { getEmailTemplateHtml } from "@/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/lib/emailTemplate";
+import { generateText } from "ai";
 import { customAlphabet } from "nanoid";
-import { AuthOptions } from "next-auth";
 import { z } from "zod";
 import { sendEmbedSurveyPreviewEmail } from "@formbricks/email";
 import { authenticatedActionClient } from "@formbricks/lib/actionClient";
 import { checkAuthorization } from "@formbricks/lib/actionClient/utils";
-import { authOptions } from "@formbricks/lib/authOptions";
-import { getEmbeddingsByTypeAndReferenceId } from "@formbricks/lib/embedding/service";
-import { getQuestionResponseReferenceId } from "@formbricks/lib/embedding/utils";
+import { llmModel } from "@formbricks/lib/ai";
+import { clusterDocuments } from "@formbricks/lib/document/kmeans";
+import { getDocumentsByTypeAndReferenceId } from "@formbricks/lib/document/service";
+import { getQuestionResponseReferenceId } from "@formbricks/lib/document/utils";
 import { getOrganizationIdFromSurveyId } from "@formbricks/lib/organization/utils";
-import { canUserAccessSurvey } from "@formbricks/lib/survey/auth";
 import { getSurvey, updateSurvey } from "@formbricks/lib/survey/service";
 import { ZId } from "@formbricks/types/environment";
-import { AuthorizationError, ResourceNotFoundError } from "@formbricks/types/errors";
+import { ResourceNotFoundError } from "@formbricks/types/errors";

 const ZSendEmbedSurveyPreviewEmailAction = z.object({
  surveyId: ZId,
@@ -160,12 +160,37 @@ export const getOpenTextSummaryAction = authenticatedActionClient
      rules: ["survey", "read"],
    });

-    const embeddings = await getEmbeddingsByTypeAndReferenceId(
+    const survey = await getSurvey(parsedInput.surveyId);
+
+    if (!survey) {
+      throw new ResourceNotFoundError("Survey", parsedInput.surveyId);
+    }
+
+    const documents = await getDocumentsByTypeAndReferenceId(
      "questionResponse",
      getQuestionResponseReferenceId(parsedInput.surveyId, parsedInput.questionId)
    );

-    console.log(embeddings);
+    const topics = await clusterDocuments(documents, 3);

-    return;
+    const question = survey.questions.find((q) => q.id === parsedInput.questionId);
+    const prompt = `You are an AI research assistant and answer the question: "${question?.headline.default}". Please provide a short summary sentence and provide 3 bullet points for insights you got from these samples:\n${topics.map((t) => t.centralDocument.text).join("\n")}`;
+
+    try {
+      const { text } = await generateText({
+        model: llmModel,
+        prompt,
+      });
+      return text;
+    } catch (error) {
+      console.error(error);
+      throw new Error("Failed to generate summary");
+    }
+
+    /*     return `Users report mixed experiences with the app's performance, with particular concerns about the dashboard's load time and afternoon slowdowns.
+
+### Insights:
+1. **Dashboard Performance**: The most common feedback is that the dashboard is slow to load, impacting user experience.
+2. **Afternoon Slowdown**: Several users notice that the app slows down in the afternoon, while it runs smoothly in the morning.
+3. **Varied Experiences**: Some users do not experience any performance issues, indicating that the problem may not be universal.`; */
  });
--- a/apps/web/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/components/OpenTextSummary.tsx
+++ b/apps/web/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/components/OpenTextSummary.tsx
@@ -1,12 +1,15 @@
 import { getOpenTextSummaryAction } from "@/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/actions";
+import Markdown from "markdown-to-jsx";
 import Link from "next/link";
 import { useState } from "react";
 import { getPersonIdentifier } from "@formbricks/lib/person/utils";
 import { timeSince } from "@formbricks/lib/time";
 import { TAttributeClass } from "@formbricks/types/attribute-classes";
 import { TSurvey, TSurveyQuestionSummaryOpenText } from "@formbricks/types/surveys/types";
+import { Alert, AlertDescription, AlertTitle } from "@formbricks/ui/Alert";
 import { PersonAvatar } from "@formbricks/ui/Avatars";
 import { Button } from "@formbricks/ui/Button";
+import { LoadingSpinner } from "@formbricks/ui/LoadingSpinner";
 import { QuestionSummaryHeader } from "./QuestionSummaryHeader";

 interface OpenTextSummaryProps {
@@ -14,6 +17,7 @@ interface OpenTextSummaryProps {
  environmentId: string;
  survey: TSurvey;
  attributeClasses: TAttributeClass[];
+  isAiEnabled: boolean;
 }

 export const OpenTextSummary = ({
@@ -21,8 +25,11 @@ export const OpenTextSummary = ({
  environmentId,
  survey,
  attributeClasses,
+  isAiEnabled,
 }: OpenTextSummaryProps) => {
  const [visibleResponses, setVisibleResponses] = useState(10);
+  const [isLoadingAiSummary, setIsLoadingAiSummary] = useState(false);
+  const [aiSummary, setAiSummary] = useState<string | null>(null);

  const handleLoadMore = () => {
    // Increase the number of visible responses by 10, not exceeding the total number of responses
@@ -32,8 +39,19 @@ export const OpenTextSummary = ({
  };

  const getOpenTextSummary = async () => {
+    setIsLoadingAiSummary(true);
    // This function is not implemented yet
-    await getOpenTextSummaryAction(survey.id, questionSummary.question.id);
+    const res = await getOpenTextSummaryAction({
+      surveyId: survey.id,
+      questionId: questionSummary.question.id,
+    });
+    const openTextSummary = res?.data;
+    if (openTextSummary) {
+      setAiSummary(openTextSummary);
+    } else {
+      setAiSummary("No summary available");
+    }
+    setIsLoadingAiSummary(false);
  };

  return (
@@ -43,7 +61,32 @@ export const OpenTextSummary = ({
        survey={survey}
        attributeClasses={attributeClasses}
      />
-      <Button onClick={() => getOpenTextSummary()}>Create Summary</Button>
+      <div className="p-4">
+        {isAiEnabled && (
+          <>
+            <Alert variant="info">
+              <AlertTitle>✨ AI Summary</AlertTitle>
+              {isLoadingAiSummary && <LoadingSpinner />}
+              {!isLoadingAiSummary && aiSummary && (
+                <>
+                  <hr className="my-4 text-slate-200" />
+                  <AlertDescription>
+                    <Markdown>{aiSummary}</Markdown>
+                  </AlertDescription>
+                </>
+              )}
+              <hr className="my-4 text-slate-200" />
+              {questionSummary.responseCount < 10 ? (
+                <p className="text-sm">This question needs at least 10 responses to access AI summaries</p>
+              ) : (
+                <Button onClick={() => getOpenTextSummary()} disabled={isLoadingAiSummary}>
+                  Generate Summary
+                </Button>
+              )}
+            </Alert>
+          </>
+        )}
+      </div>
      <div className="">
        <div className="grid h-10 grid-cols-4 items-center border-y border-slate-200 bg-slate-100 text-sm font-bold text-slate-600">
          <div className="pl-4 md:pl-6">User</div>
--- a/apps/web/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/components/SummaryList.tsx
+++ b/apps/web/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/components/SummaryList.tsx
@@ -37,6 +37,7 @@ interface SummaryListProps {
  survey: TSurvey;
  totalResponseCount: number;
  attributeClasses: TAttributeClass[];
+  isAiEnabled: boolean;
 }

 export const SummaryList = ({
@@ -46,6 +47,7 @@ export const SummaryList = ({
  survey,
  totalResponseCount,
  attributeClasses,
+  isAiEnabled,
 }: SummaryListProps) => {
  const { setSelectedFilter, selectedFilter } = useResponseFilter();
  const widgetSetupCompleted =
@@ -129,6 +131,7 @@ export const SummaryList = ({
                environmentId={environment.id}
                survey={survey}
                attributeClasses={attributeClasses}
+                isAiEnabled={isAiEnabled}
              />
            );
          }
--- a/apps/web/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/components/SummaryPage.tsx
+++ b/apps/web/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/components/SummaryPage.tsx
@@ -46,6 +46,7 @@ interface SummaryPageProps {
  user?: TUser;
  totalResponseCount: number;
  attributeClasses: TAttributeClass[];
+  isAiEnabled: boolean;
 }

 export const SummaryPage = ({
@@ -55,6 +56,7 @@ export const SummaryPage = ({
  webAppUrl,
  totalResponseCount,
  attributeClasses,
+  isAiEnabled,
 }: SummaryPageProps) => {
  const params = useParams();
  const sharingKey = params.sharingKey as string;
@@ -161,6 +163,7 @@ export const SummaryPage = ({
        environment={environment}
        totalResponseCount={totalResponseCount}
        attributeClasses={attributeClasses}
+        isAiEnabled={isAiEnabled}
      />
    </>
  );
--- a/apps/web/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/page.tsx
+++ b/apps/web/app/(app)/environments/[environmentId]/surveys/[surveyId]/(analysis)/summary/page.tsx
@@ -5,7 +5,7 @@ import { getServerSession } from "next-auth";
 import { notFound } from "next/navigation";
 import { getAttributeClasses } from "@formbricks/lib/attributeClass/service";
 import { authOptions } from "@formbricks/lib/authOptions";
-import { WEBAPP_URL } from "@formbricks/lib/constants";
+import { IS_FORMBRICKS_CLOUD, WEBAPP_URL } from "@formbricks/lib/constants";
 import { getEnvironment } from "@formbricks/lib/environment/service";
 import { getMembershipByUserIdOrganizationId } from "@formbricks/lib/membership/service";
 import { getAccessFlags } from "@formbricks/lib/membership/utils";
@@ -60,6 +60,9 @@ const Page = async ({ params }) => {
  const totalResponseCount = await getResponseCountBySurveyId(params.surveyId);

  const { isViewer } = getAccessFlags(currentUserMembership?.role);
+  const isAiEnabled =
+    IS_FORMBRICKS_CLOUD &&
+    (organization.billing.plan === "scale" || organization.billing.plan === "enterprise");

  return (
    <PageContentWrapper>
@@ -89,6 +92,7 @@ const Page = async ({ params }) => {
        user={user}
        totalResponseCount={totalResponseCount}
        attributeClasses={attributeClasses}
+        isAiEnabled={isAiEnabled}
      />
    </PageContentWrapper>
  );
--- a/apps/web/app/api/pipeline/route.ts
+++ b/apps/web/app/api/pipeline/route.ts
@@ -5,10 +5,9 @@ import { headers } from "next/headers";
 import { prisma } from "@formbricks/database";
 import { sendResponseFinishedEmail } from "@formbricks/email";
 import { embeddingsModel } from "@formbricks/lib/ai";
-import { IS_AI_ENABLED, IS_FORMBRICKS_CLOUD } from "@formbricks/lib/constants";
-import { CRON_SECRET } from "@formbricks/lib/constants";
-import { createEmbedding } from "@formbricks/lib/embedding/service";
-import { getQuestionResponseReferenceId } from "@formbricks/lib/embedding/utils";
+import { CRON_SECRET, IS_AI_ENABLED, IS_FORMBRICKS_CLOUD } from "@formbricks/lib/constants";
+import { createDocument } from "@formbricks/lib/document/service";
+import { getQuestionResponseReferenceId } from "@formbricks/lib/document/utils";
 import { getIntegrations } from "@formbricks/lib/integration/service";
 import { getOrganizationByEnvironmentId } from "@formbricks/lib/organization/service";
 import { getProductByEnvironmentId } from "@formbricks/lib/product/service";
@@ -167,17 +166,11 @@ export const POST = async (request: Request) => {

    // generate embeddings for all open text question responses for enterprise and scale plans
    const hasSurveyOpenTextQuestions = survey.questions.some((question) => question.type === "openText");
-    console.log("hasSurveyOpenTextQuestions", hasSurveyOpenTextQuestions);
-    console.log("is Cloud", hasSurveyOpenTextQuestions && IS_FORMBRICKS_CLOUD && IS_AI_ENABLED);
    if (hasSurveyOpenTextQuestions && IS_FORMBRICKS_CLOUD && IS_AI_ENABLED) {
      const organization = await getOrganizationByEnvironmentId(environmentId);
      if (!organization) {
        throw new Error("Organization not found");
      }
-      console.log(
-        "valid billing plan",
-        organization.billing.plan === "enterprise" || organization.billing.plan === "scale"
-      );
      if (organization.billing.plan === "enterprise" || organization.billing.plan === "scale") {
        for (const question of survey.questions) {
          if (question.type === "openText") {
@@ -186,13 +179,17 @@ export const POST = async (request: Request) => {
            if (!isQuestionAnswered) {
              continue;
            }
+            const text = `${question.headline.default} Answer: ${response.data[question.id]}`;
            const { embedding } = await embed({
              model: embeddingsModel,
-              value: `${question.headline.default} Answer: ${response.data[question.id]}`,
+              value: text,
            });
-            await createEmbedding({
+            console.log("creating embedding for question response", question.id);
+            await createDocument({
+              environmentId,
              referenceId: getQuestionResponseReferenceId(survey.id, question.id),
              type: "questionResponse",
+              text,
              vector: embedding,
            });
          }
--- a/apps/web/app/share/[sharingKey]/(analysis)/summary/page.tsx
+++ b/apps/web/app/share/[sharingKey]/(analysis)/summary/page.tsx
@@ -56,6 +56,7 @@ const Page = async ({ params }) => {
          webAppUrl={WEBAPP_URL}
          totalResponseCount={totalResponseCount}
          attributeClasses={attributeClasses}
+          isAiEnabled={false} // Disable AI for sharing page for now
        />
      </PageContentWrapper>
    </div>
--- a/apps/web/package.json
+++ b/apps/web/package.json
@@ -44,6 +44,7 @@
    "lodash": "^4.17.21",
    "lru-cache": "^11.0.0",
    "lucide-react": "^0.427.0",
+    "markdown-to-jsx": "^7.5.0",
    "mime": "^4.0.4",
    "next": "14.2.5",
    "next-safe-action": "^7.6.2",
--- a/packages/database/migrations/20240821105630_add_embeddings/migration.sql
+++ b/packages/database/migrations/20240821105630_add_embeddings/migration.sql
@@ -1,24 +0,0 @@
-- CreateExtension
-CREATE EXTENSION IF NOT EXISTS "vector";
-
-- CreateEnum
-CREATE TYPE "EmbeddingType" AS ENUM ('questionResponse');
-
-- CreateTable
-CREATE TABLE "Embedding" (
-    "id" TEXT NOT NULL,
-    "created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
-    "updated_at" TIMESTAMP(3) NOT NULL,
-    "environmentId" TEXT NOT NULL,
-    "type" "EmbeddingType" NOT NULL,
-    "referenceId" TEXT NOT NULL,
-    "vector" vector(512),
-
-    CONSTRAINT "Embedding_pkey" PRIMARY KEY ("id")
-);
-
-- CreateIndex
-CREATE INDEX "Embedding_type_referenceId_idx" ON "Embedding"("type", "referenceId");
-
-- AddForeignKey
-ALTER TABLE "Embedding" ADD CONSTRAINT "Embedding_environmentId_fkey" FOREIGN KEY ("environmentId") REFERENCES "Environment"("id") ON DELETE CASCADE ON UPDATE CASCADE;
--- a/packages/database/migrations/20240821132807_add_documents/migration.sql
+++ b/packages/database/migrations/20240821132807_add_documents/migration.sql
@@ -0,0 +1,25 @@
+-- CreateExtension
+CREATE EXTENSION IF NOT EXISTS "vector";
+
+-- CreateEnum
+CREATE TYPE "DocumentType" AS ENUM ('questionResponse');
+
+-- CreateTable
+CREATE TABLE "Document" (
+    "id" TEXT NOT NULL,
+    "created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
+    "updated_at" TIMESTAMP(3) NOT NULL,
+    "environmentId" TEXT NOT NULL,
+    "type" "DocumentType" NOT NULL,
+    "referenceId" TEXT NOT NULL,
+    "text" TEXT NOT NULL,
+    "vector" vector(512),
+
+    CONSTRAINT "Document_pkey" PRIMARY KEY ("id")
+);
+
+-- CreateIndex
+CREATE INDEX "Document_type_referenceId_idx" ON "Document"("type", "referenceId");
+
+-- AddForeignKey
+ALTER TABLE "Document" ADD CONSTRAINT "Document_environmentId_fkey" FOREIGN KEY ("environmentId") REFERENCES "Environment"("id") ON DELETE CASCADE ON UPDATE CASCADE;
--- a/packages/database/schema.prisma
+++ b/packages/database/schema.prisma
@@ -415,7 +415,7 @@ model Environment {
  tags                  Tag[]
  segments              Segment[]
  integration           Integration[]
-  embeddings            Embedding[]
+  documents             Document[]

  @@index([productId])
 }
@@ -661,18 +661,19 @@ model SurveyLanguage {
  @@index([languageId])
 }

-enum EmbeddingType {
+enum DocumentType {
  questionResponse
 }

-model Embedding {
+model Document {
  id            String                      @id @default(cuid())
  createdAt     DateTime                    @default(now()) @map(name: "created_at")
  updatedAt     DateTime                    @updatedAt @map(name: "updated_at")
  environmentId String
  environment   Environment                 @relation(fields: [environmentId], references: [id], onDelete: Cascade)
-  type          EmbeddingType
+  type          DocumentType
  referenceId   String
+  text          String
  vector        Unsupported("vector(512)")?

  @@index([type, referenceId])
--- a/packages/lib/ai.ts
+++ b/packages/lib/ai.ts
@@ -1,12 +1,14 @@
 import { createAzure } from "@ai-sdk/azure";
 import { env } from "./env";

-const azure = createAzure({
-  resourceName: env.AI_AZURE_RESSOURCE_NAME, // Azure resource name
-  apiKey: env.AI_AZURE_API_KEY, // Azure API key
-});
+export const llmModel = createAzure({
+  resourceName: env.AI_AZURE_LLM_RESSOURCE_NAME, // Azure resource name
+  apiKey: env.AI_AZURE_LLM_API_KEY, // Azure API key
+})(env.AI_AZURE_LLM_DEPLOYMENT_ID || "llm");

-export const llmModel = azure(env.AI_AZURE_LLM_DEPLOYMENT_ID || "llm");
-export const embeddingsModel = azure.embedding(env.AI_AZURE_EMBEDDINGS_DEPLOYMENT_ID || "embeddings", {
+export const embeddingsModel = createAzure({
+  resourceName: env.AI_AZURE_EMBEDDINGS_RESSOURCE_NAME, // Azure resource name
+  apiKey: env.AI_AZURE_EMBEDDINGS_API_KEY, // Azure API key
+}).embedding(env.AI_AZURE_EMBEDDINGS_DEPLOYMENT_ID || "embeddings", {
  dimensions: 512,
 });
--- a/packages/lib/constants.ts
+++ b/packages/lib/constants.ts
@@ -211,7 +211,10 @@ export const BILLING_LIMITS = {
 } as const;

 export const IS_AI_ENABLED = !!(
-  env.AI_AZURE_RESSOURCE_NAME &&
-  env.AI_AZURE_API_KEY &&
-  env.AI_AZURE_EMBEDDINGS_DEPLOYMENT_ID
+  env.AI_AZURE_EMBEDDINGS_API_KEY &&
+  env.AI_AZURE_EMBEDDINGS_DEPLOYMENT_ID &&
+  env.AI_AZURE_EMBEDDINGS_RESSOURCE_NAME &&
+  env.AI_AZURE_LLM_API_KEY &&
+  env.AI_AZURE_LLM_DEPLOYMENT_ID &&
+  env.AI_AZURE_LLM_RESSOURCE_NAME
 );
--- a/packages/lib/embedding/cache.ts
+++ b/packages/lib/embedding/cache.ts
@@ -6,13 +6,13 @@ interface RevalidateProps {
  referenceId?: string;
 }

-export const embeddingCache = {
+export const documentCache = {
  tag: {
    byId(id: string) {
-      return `embeddings-${id}`;
+      return `documents-${id}`;
    },
    byTypeAndReferenceId(type: string, id: string) {
-      return `embeddings-${type}-${id}`;
+      return `documents-${type}-${id}`;
    },
  },
  revalidate({ id, type, referenceId }: RevalidateProps): void {
--- a/packages/lib/document/kmeans.ts
+++ b/packages/lib/document/kmeans.ts
@@ -0,0 +1,132 @@
+import { TDocument } from "@formbricks/types/documents";
+
+class KMeans {
+  private k: number;
+  private maxIterations: number;
+  private centroids: number[][];
+
+  constructor(k: number, maxIterations: number = 100) {
+    this.k = k;
+    this.maxIterations = maxIterations;
+  }
+
+  fit(documents: TDocument[]): number[] {
+    // Extract the vectors from the documents
+    const points = documents.map((document) => document.vector);
+
+    // Initialize centroids randomly
+    this.centroids = this.initializeCentroids(points);
+
+    for (let i = 0; i < this.maxIterations; i++) {
+      const clusters: TDocument[][] = Array.from({ length: this.k }, () => []);
+
+      // Assign documents to nearest centroid
+      for (const document of documents) {
+        const closestCentroidIndex = this.getClosestCentroidIndex(document.vector);
+        clusters[closestCentroidIndex].push(document);
+      }
+
+      // Update centroids
+      const newCentroids = clusters.map((cluster) =>
+        cluster.length > 0
+          ? this.calculateCentroid(cluster.map((d) => d.vector))
+          : this.centroids[clusters.indexOf(cluster)]
+      );
+
+      // Check for convergence
+      if (this.hasConverged(newCentroids)) {
+        break;
+      }
+
+      this.centroids = newCentroids;
+    }
+
+    // Assign final clusters
+    return documents.map((document) => this.getClosestCentroidIndex(document.vector));
+  }
+
+  private initializeCentroids(points: number[][]): number[][] {
+    const centroids: number[][] = [];
+    const used = new Set<number>();
+
+    while (centroids.length < this.k) {
+      const index = Math.floor(Math.random() * points.length);
+      if (!used.has(index)) {
+        centroids.push([...points[index]]);
+        used.add(index);
+      }
+    }
+
+    return centroids;
+  }
+
+  private getClosestCentroidIndex(point: number[]): number {
+    let minDistance = Infinity;
+    let closestIndex = 0;
+
+    for (let i = 0; i < this.centroids.length; i++) {
+      const distance = this.euclideanDistance(point, this.centroids[i]);
+      if (distance < minDistance) {
+        minDistance = distance;
+        closestIndex = i;
+      }
+    }
+
+    return closestIndex;
+  }
+
+  private calculateCentroid(cluster: number[][]): number[] {
+    const dimensions = cluster[0].length;
+    const centroid = new Array(dimensions).fill(0);
+
+    for (const point of cluster) {
+      for (let i = 0; i < dimensions; i++) {
+        centroid[i] += point[i];
+      }
+    }
+
+    return centroid.map((sum) => sum / cluster.length);
+  }
+
+  private euclideanDistance(a: number[], b: number[]): number {
+    return Math.sqrt(a.reduce((sum, val, i) => sum + Math.pow(val - b[i], 2), 0));
+  }
+
+  private hasConverged(newCentroids: number[][]): boolean {
+    return newCentroids.every((centroid, i) => this.euclideanDistance(centroid, this.centroids[i]) < 1e-6);
+  }
+}
+
+export async function clusterDocuments(documents: TDocument[], numTopics: number) {
+  // 2. Perform clustering
+  const kmeans = new KMeans(numTopics);
+  const clusterAssignments = kmeans.fit(documents);
+
+  // 3. Analyze clusters
+  const clusters: TDocument[][] = Array.from({ length: numTopics }, () => []);
+  documents.forEach((document, index) => {
+    clusters[clusterAssignments[index]].push(document);
+  });
+
+  // 4. Find central documents and extract responses
+  const topics = await Promise.all(
+    clusters.map(async (cluster, index) => {
+      const centroid = kmeans["centroids"][index];
+      const centralDocument = cluster.reduce(
+        (central, document) => {
+          const distance = kmeans["euclideanDistance"](document.vector, centroid);
+          return distance < central.distance ? { document, distance } : central;
+        },
+        { document: cluster[0], distance: Infinity }
+      ).document;
+
+      return {
+        topicId: index,
+        centralDocument: centralDocument,
+        size: cluster.length,
+      };
+    })
+  );
+
+  return topics;
+}
--- a/packages/lib/embedding/service.ts
+++ b/packages/lib/embedding/service.ts
@@ -4,48 +4,50 @@ import { cache as reactCache } from "react";
 import { prisma } from "@formbricks/database";
 import { ZString } from "@formbricks/types/common";
 import {
-  TEmbedding,
-  TEmbeddingCreateInput,
-  ZEmbeddingCreateInput,
-  ZEmbeddingType,
-} from "@formbricks/types/embedding";
+  TDocument,
+  TDocumentCreateInput,
+  ZDocumentCreateInput,
+  ZDocumentType,
+} from "@formbricks/types/documents";
 import { DatabaseError } from "@formbricks/types/errors";
 import { cache } from "../cache";
 import { validateInputs } from "../utils/validate";
-import { embeddingCache } from "./cache";
+import { documentCache } from "./cache";

-export type TPrismaEmbedding = Omit<TEmbedding, "vector"> & {
+export type TPrismaDocument = Omit<TDocument, "vector"> & {
  vector: string;
 };

-export const createEmbedding = async (embeddingInput: TEmbeddingCreateInput): Promise<TEmbedding> => {
-  validateInputs([embeddingInput, ZEmbeddingCreateInput]);
+export const createDocument = async (documentInput: TDocumentCreateInput): Promise<TDocument> => {
+  validateInputs([documentInput, ZDocumentCreateInput]);

  try {
-    const { vector, ...data } = embeddingInput;
+    const { vector, ...data } = documentInput;

-    const prismaEmbedding = await prisma.embedding.create({
+    const prismaDocument = await prisma.document.create({
      data,
    });

-    const embedding = {
-      ...prismaEmbedding,
+    const document = {
+      ...prismaDocument,
      vector,
    };

    // update vector
    const vectorString = `[${vector.join(",")}]`;
    await prisma.$executeRaw`
-      UPDATE "Embedding"
+      UPDATE "Document"
      SET "vector" = ${vectorString}::vector(512)
-      WHERE "id" = ${embedding.id};
+      WHERE "id" = ${document.id};
    `;

-    embeddingCache.revalidate({
-      referenceId: embedding.referenceId,
+    documentCache.revalidate({
+      id: document.id,
+      type: document.type,
+      referenceId: document.referenceId,
    });

-    return embedding;
+    return document;
  } catch (error) {
    if (error instanceof Prisma.PrismaClientKnownRequestError) {
      throw new DatabaseError(error.message);
@@ -54,39 +56,40 @@ export const createEmbedding = async (embeddingInput: TEmbeddingCreateInput): Pr
  }
 };

-export const getEmbeddingsByTypeAndReferenceId = reactCache(
-  (type: string, referenceId: string): Promise<TEmbedding[]> =>
+export const getDocumentsByTypeAndReferenceId = reactCache(
+  (type: string, referenceId: string): Promise<TDocument[]> =>
    cache(
      async () => {
-        validateInputs([type, ZEmbeddingType], [referenceId, ZString]);
+        validateInputs([type, ZDocumentType], [referenceId, ZString]);

        try {
-          const prismaEmbeddings: TPrismaEmbedding[] = await prisma.$queryRaw`
+          const prismaDocuments: TPrismaDocument[] = await prisma.$queryRaw`
            SELECT
              id,
              created_at AS "createdAt",
              updated_at AS "updatedAt",
              type,
+              text,
              "referenceId",
              vector::text
-            FROM "Embedding" e
-            WHERE e."type" = ${type}::"EmbeddingType"
+            FROM "Document" e
+            WHERE e."type" = ${type}::"DocumentType"
              AND e."referenceId" = ${referenceId}
          `;

-          const embeddings = prismaEmbeddings.map((prismaEmbedding) => {
-            // Convert the string representation of the embedding back to an array of numbers
-            const vector = prismaEmbedding.vector
+          const documents = prismaDocuments.map((prismaDocument) => {
+            // Convert the string representation of the vector back to an array of numbers
+            const vector = prismaDocument.vector
              .slice(1, -1) // Remove the surrounding square brackets
              .split(",") // Split the string into an array of strings
              .map(Number); // Convert each string to a number
            return {
-              ...prismaEmbedding,
+              ...prismaDocument,
              vector,
            };
          });

-          return embeddings;
+          return documents;
        } catch (error) {
          if (error instanceof Prisma.PrismaClientKnownRequestError) {
            console.error(error);
@@ -95,9 +98,9 @@ export const getEmbeddingsByTypeAndReferenceId = reactCache(
          throw error;
        }
      },
-      [`getEmbeddingsByTypeAndReferenceId-${type}-${referenceId}`],
+      [`getDocumentsByTypeAndReferenceId-${type}-${referenceId}`],
      {
-        tags: [embeddingCache.tag.byTypeAndReferenceId(type, referenceId)],
+        tags: [documentCache.tag.byTypeAndReferenceId(type, referenceId)],
      }
    )()
 );
--- a/packages/lib/embedding/utils.ts
+++ b/packages/lib/embedding/utils.ts
--- a/packages/lib/env.ts
+++ b/packages/lib/env.ts
@@ -7,10 +7,12 @@ export const env = createEnv({
   * Will throw if you access these variables on the client.
   */
  server: {
-    AI_AZURE_API_KEY: z.string().optional(),
+    AI_AZURE_EMBEDDINGS_API_KEY: z.string().optional(),
+    AI_AZURE_LLM_API_KEY: z.string().optional(),
    AI_AZURE_EMBEDDINGS_DEPLOYMENT_ID: z.string().optional(),
    AI_AZURE_LLM_DEPLOYMENT_ID: z.string().optional(),
-    AI_AZURE_RESSOURCE_NAME: z.string().optional(),
+    AI_AZURE_EMBEDDINGS_RESSOURCE_NAME: z.string().optional(),
+    AI_AZURE_LLM_RESSOURCE_NAME: z.string().optional(),
    AIRTABLE_CLIENT_ID: z.string().optional(),
    AZUREAD_CLIENT_ID: z.string().optional(),
    AZUREAD_CLIENT_SECRET: z.string().optional(),
@@ -117,10 +119,12 @@ export const env = createEnv({
   * 💡 You'll get type errors if not all variables from `server` & `client` are included here.
   */
  runtimeEnv: {
-    AI_AZURE_API_KEY: process.env.AI_AZURE_API_KEY,
+    AI_AZURE_EMBEDDINGS_API_KEY: process.env.AI_AZURE_EMBEDDINGS_API_KEY,
+    AI_AZURE_LLM_API_KEY: process.env.AI_AZURE_LLM_API_KEY,
    AI_AZURE_EMBEDDINGS_DEPLOYMENT_ID: process.env.AI_AZURE_EMBEDDINGS_DEPLOYMENT_ID,
    AI_AZURE_LLM_DEPLOYMENT_ID: process.env.AI_AZURE_LLM_DEPLOYMENT_ID,
-    AI_AZURE_RESSOURCE_NAME: process.env.AI_AZURE_RESSOURCE_NAME,
+    AI_AZURE_EMBEDDINGS_RESSOURCE_NAME: process.env.AI_AZURE_EMBEDDINGS_RESSOURCE_NAME,
+    AI_AZURE_LLM_RESSOURCE_NAME: process.env.AI_AZURE_LLM_RESSOURCE_NAME,
    AIRTABLE_CLIENT_ID: process.env.AIRTABLE_CLIENT_ID,
    AZUREAD_CLIENT_ID: process.env.AZUREAD_CLIENT_ID,
    AZUREAD_CLIENT_SECRET: process.env.AZUREAD_CLIENT_SECRET,
--- a/packages/types/documents.ts
+++ b/packages/types/documents.ts
@@ -0,0 +1,28 @@
+import { z } from "zod";
+import { ZId } from "./environment";
+
+export const ZDocumentType = z.enum(["questionResponse"]);
+
+export type TDocumentType = z.infer<typeof ZDocumentType>;
+
+export const ZDocument = z.object({
+  environmentId: ZId,
+  referenceId: z.string(),
+  createdAt: z.date(),
+  updatedAt: z.date(),
+  type: ZDocumentType,
+  text: z.string(),
+  vector: z.array(z.number()).length(512),
+});
+
+export type TDocument = z.infer<typeof ZDocument>;
+
+export const ZDocumentCreateInput = z.object({
+  environmentId: ZId,
+  type: ZDocumentType,
+  referenceId: z.string(),
+  text: z.string(),
+  vector: z.array(z.number()).length(512),
+});
+
+export type TDocumentCreateInput = z.infer<typeof ZDocumentCreateInput>;
--- a/packages/types/embedding.ts
+++ b/packages/types/embedding.ts
@@ -1,21 +0,0 @@
-import { z } from "zod";
-
-export const ZEmbeddingType = z.enum(["questionResponse"]);
-
-export const ZEmbedding = z.object({
-  referenceId: z.string(),
-  createdAt: z.date(),
-  updatedAt: z.date(),
-  type: ZEmbeddingType,
-  vector: z.array(z.number()).length(512),
-});
-
-export type TEmbedding = z.infer<typeof ZEmbedding>;
-
-export const ZEmbeddingCreateInput = z.object({
-  type: ZEmbeddingType,
-  referenceId: z.string(),
-  vector: z.array(z.number()).length(512),
-});
-
-export type TEmbeddingCreateInput = z.infer<typeof ZEmbeddingCreateInput>;
--- a/pnpm-lock.yaml
+++ b/pnpm-lock.yaml
@@ -380,7 +380,7 @@ importers:
        version: 0.6.2
      '@vercel/speed-insights':
        specifier: ^1.0.12
-        version: 1.0.12(next@14.2.5(@opentelemetry/api@1.9.0)(@playwright/test@1.45.3)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)
+        version: 1.0.12(next@14.2.5(@opentelemetry/api@1.9.0)(@playwright/test@1.45.3)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)(svelte@4.2.18)(vue@3.4.38)
      bcryptjs:
        specifier: ^2.4.3
        version: 2.4.3
@@ -411,6 +411,9 @@ importers:
      lucide-react:
        specifier: ^0.427.0
        version: 0.427.0(react@18.3.1)
+      markdown-to-jsx:
+        specifier: ^7.5.0
+        version: 7.5.0(react@18.3.1)
      mime:
        specifier: ^4.0.4
        version: 4.0.4
@@ -546,13 +549,13 @@ importers:
    devDependencies:
      '@trivago/prettier-plugin-sort-imports':
        specifier: ^4.3.0
-        version: 4.3.0(prettier@3.3.3)
+        version: 4.3.0(@vue/compiler-sfc@3.4.38)(prettier@3.3.3)
      prettier:
        specifier: ^3.3.3
        version: 3.3.3
      prettier-plugin-tailwindcss:
        specifier: ^0.6.6
-        version: 0.6.6(@trivago/prettier-plugin-sort-imports@4.3.0(prettier@3.3.3))(prettier@3.3.3)
+        version: 0.6.6(@trivago/prettier-plugin-sort-imports@4.3.0(@vue/compiler-sfc@3.4.38)(prettier@3.3.3))(prettier@3.3.3)

  packages/config-tailwind:
    devDependencies:
@@ -8785,6 +8788,12 @@ packages:
    peerDependencies:
      react: '>= 0.14.0'

+  markdown-to-jsx@7.5.0:
+    resolution: {integrity: sha512-RrBNcMHiFPcz/iqIj0n3wclzHXjwS7mzjBNWecKKVhNTIxQepIix6Il/wZCn2Cg5Y1ow2Qi84+eJrryFRWBEWw==}
+    engines: {node: '>= 10'}
+    peerDependencies:
+      react: '>= 0.14.0'
+
  marked@7.0.4:
    resolution: {integrity: sha512-t8eP0dXRJMtMvBojtkcsA7n48BkauktUKzfkPSCq85ZMTJ0v76Rke4DYz01omYpPTUh4p/f7HePgRo3ebG8+QQ==}
    engines: {node: '>= 16'}
@@ -17610,7 +17619,7 @@ snapshots:
    dependencies:
      '@testing-library/dom': 10.1.0

-  '@trivago/prettier-plugin-sort-imports@4.3.0(prettier@3.3.3)':
+  '@trivago/prettier-plugin-sort-imports@4.3.0(@vue/compiler-sfc@3.4.38)(prettier@3.3.3)':
    dependencies:
      '@babel/generator': 7.17.7
      '@babel/parser': 7.24.7
@@ -17619,6 +17628,8 @@ snapshots:
      javascript-natural-sort: 0.7.1
      lodash: 4.17.21
      prettier: 3.3.3
+    optionalDependencies:
+      '@vue/compiler-sfc': 3.4.38
    transitivePeerDependencies:
      - supports-color

@@ -18169,10 +18180,12 @@ snapshots:
      satori: 0.10.9
      yoga-wasm-web: 0.3.3

-  '@vercel/speed-insights@1.0.12(next@14.2.5(@opentelemetry/api@1.9.0)(@playwright/test@1.45.3)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)':
+  '@vercel/speed-insights@1.0.12(next@14.2.5(@opentelemetry/api@1.9.0)(@playwright/test@1.45.3)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)(svelte@4.2.18)(vue@3.4.38)':
    optionalDependencies:
      next: 14.2.5(@opentelemetry/api@1.9.0)(@playwright/test@1.45.3)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)
      react: 18.3.1
+      svelte: 4.2.18
+      vue: 3.4.38

  '@vercel/style-guide@6.0.0(@next/eslint-plugin-next@14.2.5)(eslint@8.57.0)(prettier@3.3.3)(typescript@5.5.4)(vitest@2.0.5)':
    dependencies:
@@ -18361,6 +18374,13 @@ snapshots:
      '@vue/shared': 3.4.38
      vue: 3.4.38(typescript@5.5.4)

+  '@vue/server-renderer@3.4.38(vue@3.4.38)':
+    dependencies:
+      '@vue/compiler-ssr': 3.4.38
+      '@vue/shared': 3.4.38
+      vue: 3.4.38
+    optional: true
+
  '@vue/shared@3.4.29': {}

  '@vue/shared@3.4.38': {}
@@ -21869,6 +21889,10 @@ snapshots:
    dependencies:
      react: 18.3.1

+  markdown-to-jsx@7.5.0(react@18.3.1):
+    dependencies:
+      react: 18.3.1
+
  marked@7.0.4: {}

  md-to-react-email@5.0.2(react@18.3.1):
@@ -23225,11 +23249,11 @@ snapshots:
    optionalDependencies:
      prettier: 3.3.3

-  prettier-plugin-tailwindcss@0.6.6(@trivago/prettier-plugin-sort-imports@4.3.0(prettier@3.3.3))(prettier@3.3.3):
+  prettier-plugin-tailwindcss@0.6.6(@trivago/prettier-plugin-sort-imports@4.3.0(@vue/compiler-sfc@3.4.38)(prettier@3.3.3))(prettier@3.3.3):
    dependencies:
      prettier: 3.3.3
    optionalDependencies:
-      '@trivago/prettier-plugin-sort-imports': 4.3.0(prettier@3.3.3)
+      '@trivago/prettier-plugin-sort-imports': 4.3.0(@vue/compiler-sfc@3.4.38)(prettier@3.3.3)

  prettier@2.8.8: {}

@@ -25525,6 +25549,15 @@ snapshots:
      semver: 7.6.2
      typescript: 5.5.4

+  vue@3.4.38:
+    dependencies:
+      '@vue/compiler-dom': 3.4.38
+      '@vue/compiler-sfc': 3.4.38
+      '@vue/runtime-dom': 3.4.38
+      '@vue/server-renderer': 3.4.38(vue@3.4.38)
+      '@vue/shared': 3.4.38
+    optional: true
+
  vue@3.4.38(typescript@5.5.4):
    dependencies:
      '@vue/compiler-dom': 3.4.38
--- a/turbo.json
+++ b/turbo.json
@@ -51,10 +51,12 @@
      "dependsOn": ["^build"],
      "outputs": ["dist/**", ".next/**"],
      "env": [
-        "AI_AZURE_API_KEY",
+        "AI_AZURE_EMBEDDINGS_API_KEY",
+        "AI_AZURE_LLM_API_KEY",
        "AI_AZURE_EMBEDDINGS_DEPLOYMENT_ID",
+        "AI_AZURE_EMBEDDINGS_RESSOURCE_NAME",
        "AI_AZURE_LLM_DEPLOYMENT_ID",
-        "AI_AZURE_RESSOURCE_NAME",
+        "AI_AZURE_LLM_RESSOURCE_NAME",
        "AIRTABLE_CLIENT_ID",
        "ASSET_PREFIX_URL",
        "AZUREAD_CLIENT_ID",