Mastra - Firecrawl Docs

将 Firecrawl 与 Mastra 集成。Mastra 是一个用于构建 AI 智能体和工作流的 TypeScript 框架。

设置#

npm install @mastra/core firecrawl zod

创建 .env 文件：

FIRECRAWL_API_KEY=your_firecrawl_keyOPENAI_API_KEY=your_openai_key

注意： 如果使用 Node 版本低于 20，请安装 dotenv，并在代码中添加 import 'dotenv/config'。

多步骤工作流#

此示例展示了一个完整的工作流，使用 Firecrawl 和 Mastra 对文档进行搜索、抓取和总结。

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",});// 步骤 1:使用 Firecrawl SDK 搜索const 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(`搜索中:${inputData.query}`);    const searchResults = await firecrawl.search(inputData.query, { limit: 1 });    const webResults = (searchResults as any)?.web;    if (!webResults || !Array.isArray(webResults) || webResults.length === 0) {      throw new Error("未找到搜索结果");    }    const firstResult = webResults[0];    console.log(`找到:${firstResult.title}`);    return {      url: firstResult.url,      title: firstResult.title,    };  },});// 步骤 2:使用 Firecrawl SDK 抓取 URLconst 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(`抓取中:${inputData.url}`);    const scrapeResult = await firecrawl.scrape(inputData.url, {      formats: ["markdown"],    });    console.log(`已抓取:${scrapeResult.markdown?.length || 0} 个字符`);    return {      markdown: scrapeResult.markdown || "",      title: inputData.title,    };  },});// 步骤 3:使用 Claude 生成摘要const 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(`生成摘要中:${inputData.title}`);    const prompt = `用 2-3 句话总结以下文档:\n\n标题:${inputData.title}\n\n${inputData.markdown}`;    const result = await agent.generate(prompt);    console.log(`摘要已生成`);    return { summary: result.text };  },});// 创建工作流export const workflow = createWorkflow({  id: "firecrawl-workflow",  inputSchema: z.object({    query: z.string(),  }),  outputSchema: z.object({    summary: z.string(),  }),  steps: [searchStep, scrapeStep, summarizeStep],})  .then(searchStep)  .then(scrapeStep)  .then(summarizeStep)  .commit();async function testWorkflow() {  const run = await workflow.createRunAsync();  const result = await run.start({    inputData: { query: "Firecrawl documentation" }  });  if (result.status === "success") {    const { summarize } = result.steps;    if (summarize.status === "success") {      console.log(`\n${summarize.output.summary}`);    }  } else {    console.error("工作流失败:", result.status);  }}testWorkflow().catch(console.error);

更多示例请参见 Mastra 文档。