Mastra

npm install @mastra/core firecrawl zod

FIRECRAWL_API_KEY=your_firecrawl_keyOPENAI_API_KEY=your_openai_key

import { createWorkflow, createStep } from "@mastra/core/workflows";import { z } from "zod";import { Firecrawl } from "firecrawl";import { Agent } from "@mastra/core/agent";const firecrawl = new Firecrawl({  apiKey: process.env.FIRECRAWL_API_KEY || "fc-YOUR_API_KEY"});const agent = new Agent({  name: "summarizer",  instructions: "You are a helpful assistant that creates concise summaries of documentation.",  model: "openai/gpt-5-nano",});// Étape 1 : Rechercher avec le SDK Firecrawlconst searchStep = createStep({  id: "search",  inputSchema: z.object({    query: z.string(),  }),  outputSchema: z.object({    url: z.string(),    title: z.string(),  }),  execute: async ({ inputData }: { inputData: { query: string } }) => {    console.log(`Searching: ${inputData.query}`);    const searchResults = await firecrawl.search(inputData.query, { limit: 1 });    const webResults = (searchResults as any)?.web;    if (!webResults || !Array.isArray(webResults) || webResults.length === 0) {      throw new Error("No search results found");    }    const firstResult = webResults[0];    console.log(`Found: ${firstResult.title}`);    return {      url: firstResult.url,      title: firstResult.title,    };  },});// Étape 2 : Scraper l'URL avec le SDK Firecrawlconst scrapeStep = createStep({  id: "scrape",  inputSchema: z.object({    url: z.string(),    title: z.string(),  }),  outputSchema: z.object({    markdown: z.string(),    title: z.string(),  }),  execute: async ({ inputData }: { inputData: { url: string; title: string } }) => {    console.log(`Scraping: ${inputData.url}`);    const scrapeResult = await firecrawl.scrape(inputData.url, {      formats: ["markdown"],    });    console.log(`Scraped: ${scrapeResult.markdown?.length || 0} characters`);    return {      markdown: scrapeResult.markdown || "",      title: inputData.title,    };  },});// Étape 3 : Résumer avec Claudeconst summarizeStep = createStep({  id: "summarize",  inputSchema: z.object({    markdown: z.string(),    title: z.string(),  }),  outputSchema: z.object({    summary: z.string(),  }),  execute: async ({ inputData }: { inputData: { markdown: string; title: string } }) => {    console.log(`Summarizing: ${inputData.title}`);    const prompt = `Summarize the following documentation in 2-3 sentences:\n\nTitle: ${inputData.title}\n\n${inputData.markdown}`;    const result = await agent.generate(prompt);    console.log(`Summary generated`);    return { summary: result.text };  },});// Créer le workflowexport const workflow = createWorkflow({  id: "firecrawl-workflow",  inputSchema: z.object({    query: z.string(),  }),  outputSchema: z.object({    summary: z.string(),  }),  steps: [searchStep, scrapeStep, summarizeStep],})  .then(searchStep)  .then(scrapeStep)  .then(summarizeStep)  .commit();async function testWorkflow() {  const run = await workflow.createRunAsync();  const result = await run.start({    inputData: { query: "Firecrawl documentation" }  });  if (result.status === "success") {    const { summarize } = result.steps;    if (summarize.status === "success") {      console.log(`\n${summarize.output.summary}`);    }  } else {    console.error("Workflow failed:", result.status);  }}testWorkflow().catch(console.error);