chore: Update ts-mastraai template and dependencies

templates/ts-mastraai/package.json

@@ -7,23 +7,23 @@
         "node": ">=18.0.0"
     },
     "dependencies": {
-        "@ai-sdk/openai": "^2.0.3",
-        "@mastra/core": "^0.24.9",
-        "apify": "^3.5.2",
-        "mastra": "^0.18.9",
-        "zod": "^3.25.67"
+        "@ai-sdk/openai": "^3.0.23",
+        "@mastra/core": "^1.1.0",
+        "apify": "^3.5.3",
+        "mastra": "^1.1.0",
+        "zod": "^4.3.6"
     },
     "devDependencies": {
         "@apify/eslint-config": "^1.0.0",
         "@apify/tsconfig": "^0.1.1",
-        "@types/node": "^22.15.32",
-        "eslint": "^9.29.0",
-        "eslint-config-prettier": "^10.1.5",
-        "globals": "^17.0.0",
-        "prettier": "^3.5.3",
-        "tsx": "^4.20.3",
+        "@types/node": "^25.1.0",
+        "eslint": "^9.39.2",
+        "eslint-config-prettier": "^10.1.8",
+        "globals": "^17.2.0",
+        "prettier": "^3.8.1",
+        "tsx": "^4.21.0",
         "typescript": "^5.9.3",
-        "typescript-eslint": "^8.34.1"
+        "typescript-eslint": "^8.54.0"
     },
     "scripts": {
         "start": "npm run start:dev",

templates/ts-mastraai/src/agents.ts

@@ -6,6 +6,7 @@ import { instagramScraperTool } from './tools.js';
 
 export const createSocialMediaAgent = (modelName: string): Agent =>
     new Agent({
+        id: 'social-media-agent',
         name: 'Social Media Agent',
         instructions: `You are an expert social media analyst specializing in Instagram analysis.
         You help users understand social media data and extract meaningful insights from

templates/ts-mastraai/src/main.ts

@@ -38,7 +38,7 @@ const agent = createSocialMediaAgent(modelName);
 log.info(`Querying the agent with the following query: ${query}`);
 
 // Query the agent and get the response
-const response = await agent.generateVNext([{ role: 'user', content: query }]);
+const response = await agent.generate([{ role: 'user', content: query }]);
 
 log.info(`Agent response: ${response.text}`);
 

templates/ts-mastraai/src/tools.ts

@@ -1,6 +1,4 @@
 // eslint-disable-next-line import/extensions
-import type { Tool } from '@mastra/core/tools';
-// eslint-disable-next-line import/extensions
 import { createTool } from '@mastra/core/tools';
 import { ApifyClient, log } from 'apify';
 import { z } from 'zod';
@@ -17,46 +15,45 @@ const instagramScraperOutputSchema = z.object({
 });
 
 // Define the Instagram Scraper Tool
-export const instagramScraperTool: Tool<typeof instagramScraperInputSchema, typeof instagramScraperOutputSchema> =
-    createTool({
-        id: 'instagram-profile-posts-scraper',
-        description: "Tool to scrape Instagram profile posts using Apify's Instagram Scraper.",
-        inputSchema: instagramScraperInputSchema,
-        outputSchema: instagramScraperOutputSchema,
-        execute: async ({ context }) => {
-            const token = process.env.APIFY_TOKEN;
-            if (!token) {
-                throw new Error('APIFY_TOKEN environment variable is missing!');
-            }
-
-            const { handle, maxPosts } = context;
-            const runInput = {
-                directUrls: [`https://www.instagram.com/${handle}/`],
-                resultsLimit: maxPosts,
-                resultsType: 'posts',
-                searchLimit: 1,
-            };
-
-            const apifyClient = new ApifyClient({ token });
-
-            // Call the Apify Instagram Scraper Actor
-            const run = await apifyClient.actor('apify/instagram-scraper').call(runInput);
-            if (!run) {
-                throw new Error('Failed to start the Actor apify/instagram-scraper');
-            }
-
-            // Fetch dataset items
-            const datasetId = run.defaultDatasetId;
-            const dataset = await apifyClient.dataset(datasetId).listItems();
-            const datasetItems: unknown[] = dataset.items;
-
-            // Validate and convert dataset items to InstagramPosts
-            try {
-                const posts: InstagramPosts = InstagramPosts.fromRaw(datasetItems);
-                return { posts: posts.root };
-            } catch (error) {
-                log.warning(`Received invalid dataset items: ${JSON.stringify(datasetItems)}. Error: ${error}`);
-                throw new Error('Received invalid dataset items.');
-            }
-        },
-    });
+export const instagramScraperTool = createTool({
+    id: 'instagram-profile-posts-scraper',
+    description: "Tool to scrape Instagram profile posts using Apify's Instagram Scraper.",
+    inputSchema: instagramScraperInputSchema,
+    outputSchema: instagramScraperOutputSchema,
+    execute: async (inputData) => {
+        const token = process.env.APIFY_TOKEN;
+        if (!token) {
+            throw new Error('APIFY_TOKEN environment variable is missing!');
+        }
+
+        const { handle, maxPosts } = inputData;
+        const runInput = {
+            directUrls: [`https://www.instagram.com/${handle}/`],
+            resultsLimit: maxPosts,
+            resultsType: 'posts',
+            searchLimit: 1,
+        };
+
+        const apifyClient = new ApifyClient({ token });
+
+        // Call the Apify Instagram Scraper Actor
+        const run = await apifyClient.actor('apify/instagram-scraper').call(runInput);
+        if (!run) {
+            throw new Error('Failed to start the Actor apify/instagram-scraper');
+        }
+
+        // Fetch dataset items
+        const datasetId = run.defaultDatasetId;
+        const dataset = await apifyClient.dataset(datasetId).listItems();
+        const datasetItems: unknown[] = dataset.items;
+
+        // Validate and convert dataset items to InstagramPosts
+        try {
+            const posts: InstagramPosts = InstagramPosts.fromRaw(datasetItems);
+            return { posts: posts.root };
+        } catch (error) {
+            log.warning(`Received invalid dataset items: ${JSON.stringify(datasetItems)}. Error: ${error}`);
+            throw new Error('Received invalid dataset items.');
+        }
+    },
+});