fix: model update

.github/workflows/build.yml

@@ -16,7 +16,7 @@ jobs:
       - name: Use Node.js
         uses: actions/setup-node@v4
         with:
-          node-version: 18.x
+          node-version: 22.x
       - run: npm ci
       - run: npm run audit
       - run: npm test

README.md

@@ -10,7 +10,7 @@ This an AWS SAM project that takes podcast transcripts generated by [Podwhispere
 An example of a Pull Request generated by this project can be found [here](https://github.com/awsbites/aws-bites-site/pull/143).
 
 ## GenAI / LLM use
-We currently use the [Anthropic Claude V2](https://www.anthropic.com/index/claude-2) Large Language Model (LLM) in Amazon Bedrock
+We currently use an [Anthropic Claude](https://www.anthropic.com) Large Language Model (LLM) in Amazon Bedrock
 
 ## System Overview
 

lib/summarisation.ts

@@ -3,7 +3,7 @@ import envs from './envs'
 import { createPrompt } from './prompt-template'
 import type { Summary, Transcript } from './types'
 
-const MODEL_ID = 'anthropic.claude-v2'
+const MODEL_ID = 'eu.anthropic.claude-sonnet-4-20250514-v1:0'
 
 /**
  * Based on a Podwhisperer transcript, use the LLM to create an episode summary and chapters
@@ -15,18 +15,30 @@ export async function createSummary(
   options: { bedrockRegion?: string } = {},
 ): Promise<Summary> {
   const { bedrockRegion } = options
+
   const brClient = new BedrockRuntimeClient({
-    region: bedrockRegion === undefined ? envs.BEDROCK_REGION : bedrockRegion,
+    region: bedrockRegion ?? envs.BEDROCK_REGION,
   })
 
   const prompt = createPrompt(transcript)
+
   const modelInput = JSON.stringify({
-    prompt,
-    max_tokens_to_sample: 5000,
+    anthropic_version: 'bedrock-2023-05-31',
+    max_tokens: 5000,
     temperature: 0.5,
-    top_k: 250,
     top_p: 1,
     stop_sequences: [],
+    messages: [
+      {
+        role: 'user',
+        content: [
+          {
+            type: 'text',
+            text: prompt,
+          },
+        ],
+      },
+    ],
   })
 
   const invokeModelCommand = new InvokeModelCommand({
@@ -37,10 +49,24 @@ export async function createSummary(
   })
 
   const modelResponse = await brClient.send(invokeModelCommand)
-  const { completion } = JSON.parse(modelResponse.body.transformToString('utf8'))
-  const jsonStart: number = completion.indexOf('{')
-  const jsonEnd: number = completion.lastIndexOf('}')
-  const jsonPart = completion.substring(jsonStart, jsonEnd + 1)
-  const summary = JSON.parse(jsonPart)
+
+  const raw = await modelResponse.body.transformToString('utf8')
+  const parsed = JSON.parse(raw) as {
+    content?: Array<{ type: string; text?: string }>
+    stop_reason?: string
+    usage?: unknown
+  }
+
+  const outputText = parsed?.content?.find((c) => c.type === 'text')?.text ?? ''
+
+  const jsonStart = outputText.indexOf('{')
+  const jsonEnd = outputText.lastIndexOf('}')
+  if (jsonStart === -1 || jsonEnd === -1 || jsonEnd <= jsonStart) {
+    throw new Error('Model did not return JSON content as expected.')
+  }
+
+  const jsonPart = outputText.substring(jsonStart, jsonEnd + 1)
+  const summary: Summary = JSON.parse(jsonPart)
+
   return summary
 }