chore: make ai standups more concise and add context (#10689)

packages/client/types/constEnums.ts

@@ -522,7 +522,7 @@ export const enum PollsAriaLabels {
 }
 
 export const enum AIExplainer {
-  STARTER = `AI generated summaries 🤖 are a premium feature. We'll share them with you for a few retros so you can see what they're like.`,
+  STARTER = `AI generated summaries 🤖 are a premium feature, but we'll share a few summaries with you so you can see what they're like.`,
   PREMIUM_MEETING = `Our friendly AI 🤖 is here to save you time by summarizing your meeting`,
   PREMIUM_REFLECTIONS = `Our friendly AI 🤖 is here to save you time by summarizing your reflections`
 }

packages/server/graphql/mutations/helpers/generateStandupMeetingSummary.ts

@@ -2,6 +2,7 @@ import {getTeamPromptResponsesByMeetingId} from '../../../postgres/queries/getTe
 import {TeamPromptMeeting} from '../../../postgres/types/Meeting'
 import OpenAIServerManager from '../../../utils/OpenAIServerManager'
 import {DataLoaderWorker} from '../../graphql'
+import isValid from '../../isValid'
 import canAccessAI from './canAccessAI'
 
 const generateStandupMeetingSummary = async (
@@ -14,11 +15,18 @@ const generateStandupMeetingSummary = async (
 
   const responses = await getTeamPromptResponsesByMeetingId(meeting.id)
 
-  const contentToSummarize = responses.map((response) => response.plaintextContent)
-  if (contentToSummarize.length === 0) return
+  const userIds = responses.map((response) => response.userId)
+  const users = (await dataLoader.get('users').loadMany(userIds)).filter(isValid)
+
+  const contentWithUsers = responses.map((response, idx) => ({
+    content: response.plaintextContent,
+    user: users[idx]?.preferredName ?? 'Anonymous'
+  }))
+
+  if (contentWithUsers.length === 0) return
 
   const manager = new OpenAIServerManager()
-  const summary = await manager.getStandupSummary(contentToSummarize, meeting.meetingPrompt)
+  const summary = await manager.getStandupSummary(contentWithUsers, meeting.meetingPrompt)
   if (!summary) return
   return summary
 }

packages/server/utils/OpenAIServerManager.ts

@@ -22,32 +22,34 @@ class OpenAIServerManager {
     })
   }
 
-  async getStandupSummary(plaintextResponses: string[], meetingPrompt: string) {
+  async getStandupSummary(
+    responses: Array<{content: string; user: string}>,
+    meetingPrompt: string
+  ) {
     if (!this.openAIApi) return null
-    // :TODO: (jmtaber129): Include info about who made each response in the prompt, so that the LLM
-    // can include that in the response, e.g. "James is working on AI Summaries" vs. "Someone is
-    // working on AI Summaries".
-    const prompt = `Below is a list of responses submitted by team members to the question "${meetingPrompt}". If there are multiple responses, the responses are delimited by the string "NEW_RESPONSE". Identify up to 5 themes found within the responses. For each theme, provide a 2 to 3 sentence summary. In the summaries, only include information specified in the responses. When referring to people in the output, do not assume their gender and default to using the pronouns "they" and "them".
+
+    const prompt = `Below is a list of responses submitted by team members to the question "${meetingPrompt}". Each response includes the team member's name. Identify up to 3 key themes found within the responses. For each theme, provide a single concise sentence that includes who is working on what. Use "they/them" pronouns when referring to people.
 
     Desired format:
-    - <theme title>: <theme summary>
-    - <theme title>: <theme summary>
-    - <theme title>: <theme summary>
+    - <theme>: <brief summary including names>
+    - <theme>: <brief summary including names>
+    - <theme>: <brief summary including names>
 
     Responses: """
-    ${plaintextResponses.join('\nNEW_RESPONSE\n')}
+    ${responses.map(({content, user}) => `${user}: ${content}`).join('\nNEW_RESPONSE\n')}
     """`
+
     try {
       const response = await this.openAIApi.chat.completions.create({
-        model: 'gpt-4o-mini',
+        model: 'gpt-4o',
         messages: [
           {
             role: 'user',
             content: prompt
           }
         ],
         temperature: 0.7,
-        max_tokens: 1000,
+        max_tokens: 500,
         top_p: 1,
         frequency_penalty: 0,
         presence_penalty: 0