> ## Documentation Index
> Fetch the complete documentation index at: https://student-213fb9fc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# LangChain

> 将 Firecrawl 与 LangChain 集成，用于网页抓取与 AI 工作流

将 Firecrawl 与 LangChain 集成，构建由网页数据驱动的 AI 应用。

<div id="setup">
  ## 安装与设置
</div>

```bash theme={null}
npm install @langchain/openai @mendable/firecrawl-js 
```

创建 `.env` 文件：

```bash theme={null}
FIRECRAWL_API_KEY=your_firecrawl_key
OPENAI_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'`。

<div id="scrape-chat">
  ## 抓取 + 对话
</div>

本示例展示一个简单的工作流：抓取网站，并使用 LangChain 处理抓取到的内容。

```typescript theme={null}
import FirecrawlApp from '@mendable/firecrawl-js';
import { ChatOpenAI } from '@langchain/openai';
import { HumanMessage } from '@langchain/core/messages';

const firecrawl = new FirecrawlApp({ apiKey: process.env.FIRECRAWL_API_KEY });
const chat = new ChatOpenAI({
    model: 'gpt-5-nano',
    apiKey: process.env.OPENAI_API_KEY
});

const scrapeResult = await firecrawl.scrape('https://firecrawl.dev', {
    formats: ['markdown']
});

console.log('Scraped content length:', scrapeResult.markdown?.length);

const response = await chat.invoke([
    new HumanMessage(`Summarize: ${scrapeResult.markdown}`)
]);

console.log('Summary:', response.content);
```

<div id="chains">
  ## Chains
</div>

本示例演示如何构建一个 LangChain 链，用于处理和分析抓取到的内容。

```typescript theme={null}
import FirecrawlApp from '@mendable/firecrawl-js';
import { ChatOpenAI } from '@langchain/openai';
import { ChatPromptTemplate } from '@langchain/core/prompts';
import { StringOutputParser } from '@langchain/core/output_parsers';

const firecrawl = new FirecrawlApp({ apiKey: process.env.FIRECRAWL_API_KEY });
const model = new ChatOpenAI({
    model: 'gpt-5-nano',
    apiKey: process.env.OPENAI_API_KEY
});

const scrapeResult = await firecrawl.scrape('https://stripe.com', {
    formats: ['markdown']
});

console.log('Scraped content length:', scrapeResult.markdown?.length);

// 创建处理链
const prompt = ChatPromptTemplate.fromMessages([
    ['system', '你是分析公司网站的专家。'],
    ['user', '从以下内容中提取公司名称和主要产品:{content}']
]);

const chain = prompt.pipe(model).pipe(new StringOutputParser());

// 执行链
const result = await chain.invoke({
    content: scrapeResult.markdown
});

console.log('Chain result:', result);
```

<div id="tool-calling">
  ## 工具调用
</div>

此示例演示如何使用 LangChain 的工具调用功能，让模型自动决定何时抓取网站。

```typescript theme={null}
import FirecrawlApp from '@mendable/firecrawl-js';
import { ChatOpenAI } from '@langchain/openai';
import { DynamicStructuredTool } from '@langchain/core/tools';
import { z } from 'zod';

const firecrawl = new FirecrawlApp({ apiKey: process.env.FIRECRAWL_API_KEY });

// 创建抓取工具
const scrapeWebsiteTool = new DynamicStructuredTool({
    name: 'scrape_website',
    description: '从任何网站 URL 抓取内容',
    schema: z.object({
        url: z.string().url().describe('要抓取的 URL')
    }),
    func: async ({ url }) => {
        console.log('正在抓取:', url);
        const result = await firecrawl.scrape(url, {
            formats: ['markdown']
        });
        console.log('抓取内容预览:', result.markdown?.substring(0, 200) + '...');
        return result.markdown || '未抓取到内容';
    }
});

const model = new ChatOpenAI({
    model: 'gpt-5-nano',
    apiKey: process.env.OPENAI_API_KEY
}).bindTools([scrapeWebsiteTool]);

const response = await model.invoke('什么是 Firecrawl?访问 firecrawl.dev 并告诉我相关信息。');

console.log('响应:', response.content);
console.log('工具调用:', response.tool_calls);
```

<div id="structured-data-extraction">
  ## 结构化数据提取
</div>

此示例演示如何使用 LangChain 的结构化输出功能来提取结构化数据。

```typescript theme={null}
import FirecrawlApp from '@mendable/firecrawl-js';
import { ChatOpenAI } from '@langchain/openai';
import { z } from 'zod';

const firecrawl = new FirecrawlApp({ apiKey: process.env.FIRECRAWL_API_KEY });

const scrapeResult = await firecrawl.scrape('https://stripe.com', {
    formats: ['markdown']
});

console.log('抓取的内容长度:', scrapeResult.markdown?.length);

const CompanyInfoSchema = z.object({
    name: z.string(),
    industry: z.string(),
    description: z.string(),
    products: z.array(z.string())
});

const model = new ChatOpenAI({
    model: 'gpt-5-nano',
    apiKey: process.env.OPENAI_API_KEY
}).withStructuredOutput(CompanyInfoSchema);

const companyInfo = await model.invoke([
    {
        role: 'system',
        content: '从网站内容中提取公司信息。'
    },
    {
        role: 'user',
        content: `提取数据: ${scrapeResult.markdown}`
    }
]);

console.log('已提取的公司信息:', companyInfo);
```

更多示例，请参阅 [LangChain 文档](https://js.langchain.com/docs)。