[pull] master from botpress:master

plugins/conversation-insights/plugin.definition.ts

@@ -3,7 +3,7 @@ import llm from './bp_modules/llm'
 
 export default new PluginDefinition({
   name: 'conversation-insights',
-  version: '0.2.1',
+  version: '0.2.2',
   configuration: {
     schema: z.object({ modelId: z.string() }),
   },
@@ -22,6 +22,10 @@ export default new PluginDefinition({
         title: 'Participant count',
         description: 'The count of users having participated in the conversation, including the bot. Type: int',
       },
+      sentiment: {
+        title: 'Sentiment',
+        description: 'The sentiment that best describes the conversation. Type: enum Sentiments',
+      },
     },
   },
   events: {

plugins/conversation-insights/src/index.ts

@@ -1,6 +1,6 @@
 import * as sdk from '@botpress/sdk'
-import * as summaryUpdater from './summaryUpdater'
 import * as updateScheduler from './summaryUpdateScheduler'
+import * as summaryUpdater from './tagsUpdater'
 import * as types from './types'
 import * as bp from '.botpress'
 
@@ -15,7 +15,7 @@ plugin.on.afterIncomingMessage('*', async (props) => {
   const { message_count } = await _onNewMessage({ ...props, conversation })
 
   if (updateScheduler.isTimeToUpdate(message_count)) {
-    props.client.createEvent({ payload: {}, type: 'updateSummary', conversationId: props.data.conversationId })
+    await props.events.updateSummary.withConversationId(props.data.conversationId).emit({})
   }
 
   return undefined
@@ -52,8 +52,10 @@ const _onNewMessage = async (
 }
 
 plugin.on.event('updateSummary', async (props) => {
-  const messages = await props.client.listMessages({ conversationId: props.event.conversationId })
-  const newMessages: string[] = messages.messages.map((message) => message.payload.text)
+  const firstMessagePage = await props.client
+    .listMessages({ conversationId: props.event.conversationId })
+    .then((res) => res.messages)
+
   if (!props.event.conversationId) {
     throw new sdk.RuntimeError(`The conversationId cannot be null when calling the event '${props.event.type}'`)
   }
@@ -62,7 +64,7 @@ plugin.on.event('updateSummary', async (props) => {
   await summaryUpdater.updateTitleAndSummary({
     ...props,
     conversation: conversation.conversation,
-    messages: newMessages,
+    messages: firstMessagePage,
   })
 })
 

plugins/conversation-insights/src/generate-content.ts → plugins/conversation-insights/src/prompt/parse-content.ts

@@ -1,7 +1,6 @@
 import * as sdk from '@botpress/sdk'
 import JSON5 from 'json5'
 import { jsonrepair } from 'jsonrepair'
-import { OutputFormat } from './summary-prompt'
 import * as bp from '.botpress'
 
 export type LLMInput = bp.interfaces.llm.actions.generateContent.input.Input
@@ -10,9 +9,9 @@ export type LLMOutput = bp.interfaces.llm.actions.generateContent.output.Output
 export type LLMMessage = LLMInput['messages'][number]
 export type LLMChoice = LLMOutput['choices'][number]
 
-type PredictResponse = {
+export type PredictResponse<T> = {
   success: boolean
-  json: OutputFormat
+  json: T
 }
 
 const tryParseJson = (str: string) => {
@@ -23,7 +22,7 @@ const tryParseJson = (str: string) => {
   }
 }
 
-export const parseLLMOutput = (output: LLMOutput): PredictResponse => {
+export const parseLLMOutput = <T>(output: LLMOutput): PredictResponse<T> => {
   const mappedChoices: LLMChoice['content'][] = output.choices.map((choice) => choice.content)
   if (!mappedChoices[0]) throw new sdk.RuntimeError('Could not parse LLM output')
   const firstChoice = mappedChoices[0]

plugins/conversation-insights/src/prompt/prompt.ts

@@ -0,0 +1,47 @@
+import { z } from '@botpress/sdk'
+import { LLMInput } from './parse-content'
+import * as bp from '.botpress'
+
+export type SentimentAnalysisOutput = z.infer<typeof SentimentAnalysisOutput>
+export const SentimentAnalysisOutput = z.object({
+  sentiment: z.string().describe('The sentiment that best describes the conversation'),
+})
+
+export type InputFormat = z.infer<typeof InputFormat>
+export const InputFormat = z.array(z.string())
+
+const formatMessages = (
+  messages: PromptArgs['messages'],
+  context: PromptArgs['context'],
+  botId: string
+): LLMInput['messages'] => {
+  const contextMessage: LLMInput['messages'][0] = {
+    role: 'assistant',
+    content: `Context: ${JSON.stringify(context)}`,
+  }
+
+  const messagesWithUser: LLMInput['messages'] = []
+  for (const message of messages) {
+    if (message.type !== 'text') continue // only text is supported to analyse messages
+    messagesWithUser.push({
+      role: message.userId === botId ? 'assistant' : 'user',
+      content: message.payload.text,
+    })
+  }
+  return [contextMessage, ...messagesWithUser.reverse()]
+}
+
+export type PromptArgs = {
+  systemPrompt: string
+  messages: bp.MessageHandlerProps['message'][]
+  model: { id: string }
+  context: object
+  botId: string
+}
+export const createPrompt = (args: PromptArgs): LLMInput => ({
+  responseFormat: 'json_object',
+  temperature: 0,
+  systemPrompt: args.systemPrompt.trim(),
+  messages: formatMessages(args.messages, args.context, args.botId),
+  model: args.model,
+})

plugins/conversation-insights/src/prompt/sentiment-prompt.ts

@@ -0,0 +1,89 @@
+import { z } from '@botpress/sdk'
+import { LLMInput } from './parse-content'
+import * as prompt from './prompt'
+
+export type SentimentAnalysisOutput = z.infer<typeof SentimentAnalysisOutput>
+export const SentimentAnalysisOutput = z.object({
+  sentiment: z
+    .enum(['very_negative', 'negative', 'neutral', 'positive', 'very_positive'])
+    .describe('The sentiment that best describes the conversation'),
+})
+
+export const SENTIMENT_OPTIONS = SentimentAnalysisOutput.shape.sentiment.options.map((opt) => ` "${opt}" `).join('|')
+
+export type PromptArgs = Omit<prompt.PromptArgs, 'systemPrompt'>
+export const createPrompt = (args: PromptArgs): LLMInput =>
+  prompt.createPrompt({
+    ...args,
+    systemPrompt: `
+You are a conversation analyser.
+You will be given:
+- A previous sentiment
+- An array of messages
+
+Your task is to reply the sentiment that best describes the overall conversation.
+
+Return your response only in valid JSON using the following type:
+
+\`\`\`json
+{
+  "sentiment": ${SENTIMENT_OPTIONS},   // The latest sentiment of the conversation
+}
+\`\`\`
+
+Instructions:
+
+- Consider the previous sentiment when choosing the new one — keep it if still relevant, or update it if needed.
+- Focus on the most recent sentiment of the conversation.
+- Only use the available sentiments
+- Do not include extra commentary, formatting, or explanation outside the JSON output.
+- The messages are in order, which means the most recent ones are at the end of the list.
+- Keep in mind that your own messages are included in the messages, but have the 'assistant' role
+
+The available sentiments are: ${SENTIMENT_OPTIONS}
+
+Examples:
+
+Input:
+
+\`\`\`json
+{
+  "messages": [
+    "Context: {'previousSentiment': 'negative'}",
+    "User: I hate your service. I want to unsubscribe right now!",
+    "Bot: I understand your frustation, but there is nothing we can do",
+    "User: I want a refund.",
+  ]
+}
+\`\`\`
+
+Output:
+
+\`\`\`json
+{
+  "sentiment": "very_negative"
+}
+\`\`\`
+
+Input:
+
+\`\`\`json
+{
+  "messages": [
+    "previousSentiment: neutral",
+    "User: Hi, how could I get a premium subscription?",
+    "Bot: You can get it by clicking on the link I just sent you.",
+    "User: Thank you so much, your help has changed my life",
+  ]
+}
+\`\`\`
+
+Output:
+
+\`\`\`json
+{
+  "sentiment": "very_positive"
+}
+\`\`\`
+`,
+  })

plugins/conversation-insights/src/summary-prompt.ts → plugins/conversation-insights/src/prompt/summary-prompt.ts

@@ -1,42 +1,18 @@
 import { z } from '@botpress/sdk'
-import { LLMInput } from './generate-content'
+import { LLMInput } from './parse-content'
+import * as prompt from './prompt'
 
 export type OutputFormat = z.infer<typeof OutputFormat>
 export const OutputFormat = z.object({
   title: z.string().describe('A fitting title for the conversation'),
   summary: z.string().describe('A short summary of the conversation'),
 })
 
-export type InputFormat = z.infer<typeof InputFormat>
-export const InputFormat = z.array(z.string())
-
-const formatMessages = (
-  messages: string[],
-  context: PromptArgs['context']
-): { role: 'user' | 'assistant'; content: string } => {
-  return {
-    role: 'user',
-    content: JSON.stringify(
-      {
-        previousTitle: context.previousTitle,
-        previousSummary: context.previousSummary,
-        messages: messages.reverse(),
-      },
-      null,
-      2
-    ),
-  }
-}
-
-export type PromptArgs = {
-  messages: string[]
-  model: { id: string }
-  context: { previousSummary?: string; previousTitle?: string }
-}
-export const createPrompt = (args: PromptArgs): LLMInput => ({
-  responseFormat: 'json_object',
-  temperature: 0,
-  systemPrompt: `
+export type PromptArgs = Omit<prompt.PromptArgs, 'systemPrompt'>
+export const createPrompt = (args: PromptArgs): LLMInput =>
+  prompt.createPrompt({
+    ...args,
+    systemPrompt: `
 You are a conversation summarizer.
 You will be given:
 - A previous title and summary
@@ -68,13 +44,12 @@ Input:
 
 \`\`\`json
 {
-  "previousTitle": "Used cars",
-  "previousSummary": "The user is talking abous a used Toyota Matrix",
   "messages": [
-    "What mileage should I expect from a car that was made two years ago?",
-    "What price should I expect from a car manufactured in 2011?",
-    "What should I look out for when buying a secondhand Toyota Matrix?",
-    "I am looking to buy a used car, what would you recommend?",
+    "Context: {'previousTitle': 'Used cars', 'previousSummary': 'The user is talking abous a used Toyota Matrix'}",
+    "User: What mileage should I expect from a car that was made two years ago?",
+    "User: What price should I expect from a car manufactured in 2011?",
+    "User: What should I look out for when buying a secondhand Toyota Matrix?",
+    "User: I am looking to buy a used car, what would you recommend?",
   ]
 }
 \`\`\`
@@ -87,7 +62,5 @@ Output:
   "summary": "The user is seeking advice on purchasing a used car."
 }
 \`\`\`
-`.trim(),
-  messages: [formatMessages(args.messages, args.context)],
-  model: args.model,
-})
+`,
+  })