> ## Documentation Index
> Fetch the complete documentation index at: https://langchain-zh.cn/llms.txt
> Use this file to discover all available pages before exploring further.

# 代码文本分割器集成指南

[RecursiveCharacterTextSplitter](https://reference.langchain.com/javascript/langchain-textsplitters/RecursiveCharacterTextSplitter) 内置了适用于特定编程语言的[文本分割](/oss/javascript/integrations/splitters/)分隔符列表。

支持的语言保存在 `SupportedTextSplitterLanguages` 类型中。包括：

```
"cpp",
"go",
"java",
"js",
"php",
"proto",
"python",
"rst",
"ruby",
"rust",
"scala",
"swift",
"markdown",
"latex",
"html",
"sol",
```

要查看特定语言的分隔符列表，请将此枚举中的值传递给：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
RecursiveCharacterTextSplitter.getSeparatorsForLanguage()
```

要实例化针对特定语言定制的分割器，请将此枚举中的值传递给：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
RecursiveCharacterTextSplitter.fromLanguage()
```

下面我们展示各种语言的示例。

<CodeGroup>
  ```bash npm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  npm install @langchain/textsplitters
  ```

  ```bash pnpm theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  pnpm install @langchain/textsplitters
  ```

  ```bash yarn theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  yarn add @langchain/textsplitters
  ```

  ```bash bun theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
  bun add @langchain/textsplitters
  ```
</CodeGroup>

## Python

以下是使用 Python 文本分割器的示例：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const pythonSplitter = RecursiveCharacterTextSplitter.fromLanguage(
    "python",
    { chunkSize: 50, chunkOverlap: 0 }
);
const pythonDocs = pythonSplitter.createDocuments([{ pageContent: PYTHON_CODE }]);
console.log(pythonDocs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: 'def hello_world():\n    print("Hello, World!")' },
    Document { metadata: {}, pageContent: '# Call the function\nhello_world()' }
]
```

## JS

以下是使用 JS 文本分割器的示例：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const JS_CODE = `
function helloWorld() {
  console.log("Hello, World!");
}

// Call the function
helloWorld();
`;

const jsSplitter = RecursiveCharacterTextSplitter.fromLanguage(
    "js",
    { chunkSize: 60, chunkOverlap: 0 }
);
const jsDocs = jsSplitter.createDocuments([{ pageContent: JS_CODE }]);
console.log(jsDocs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: 'function helloWorld() {\n  console.log("Hello, World!");\n}' },
    Document { metadata: {}, pageContent: '// Call the function\nhelloWorld()' }
]
```

## TS

以下是使用 TypeScript 文本分割器的示例：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const TS_CODE = `
function helloWorld(): void {
  console.log("Hello, World!");
}

// Call the function
helloWorld();
`;

const tsSplitter = RecursiveCharacterTextSplitter.fromLanguage(
    "ts",
    { chunkSize: 60, chunkOverlap: 0 }
);
const tsDocs = tsSplitter.createDocuments([{ pageContent: TS_CODE }]);
console.log(tsDocs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: 'function helloWorld(): void {' },
    Document { metadata: {}, pageContent: 'console.log("Hello, World!");\n}' },
    Document { metadata: {}, pageContent: '// Call the function\nhelloWorld()' }
]
```

## Markdown

以下是使用 Markdown 文本分割器的示例：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const markdownText = `
# 🦜️🔗 LangChain

⚡ Building applications with LLMs through composability ⚡

## What is LangChain?

# Hopefully this code block isn't split
LangChain is a framework for...

As an open-source project in a rapidly developing field, we are extremely open to contributions.
`;

const mdSplitter = RecursiveCharacterTextSplitter.fromLanguage(
    "markdown",
    { chunkSize: 60, chunkOverlap: 0 }
);
const mdDocs = mdSplitter.createDocuments([ markdownText ]);
console.log(mdDocs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: '# 🦜️🔗 LangChain' },
    Document { metadata: {}, pageContent: '⚡ Building applications with LLMs through composability ⚡' },
    Document { metadata: {}, pageContent: '## What is LangChain?' },
    Document { metadata: {}, pageContent: "# Hopefully this code block isn't split" },
    Document { metadata: {}, pageContent: 'LangChain is a framework for...' },
    Document { metadata: {}, pageContent: 'As an open-source project in a rapidly developing field, we' },
    Document { metadata: {}, pageContent: 'are extremely open to contributions.' }
]
```

## Latex

以下是 Latex 文本的示例：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const latexText = `
\\documentclass{article}

\\begin{document}

\\maketitle

\\section{Introduction}
Large language models (LLMs) are a type of machine learning model that can be trained on vast amounts of text data to generate human-like language. In recent years, LLMs have made significant advances in a variety of natural language processing tasks, including language translation, text generation, and sentiment analysis.

\\subsection{History of LLMs}
The earliest LLMs were developed in the 1980s and 1990s, but they were limited by the amount of data that could be processed and the computational power available at the time. In the past decade, however, advances in hardware and software have made it possible to train LLMs on massive datasets, leading to significant improvements in performance.

\\subsection{Applications of LLMs}
LLMs have many applications in industry, including chatbots, content creation, and virtual assistants. They can also be used in academia for research in linguistics, psychology, and computational linguistics.

\\end{document}
`;

const latexSplitter = RecursiveCharacterTextSplitter.fromLanguage(
    "latex",
    { chunkSize: 60, chunkOverlap: 0 }
);
const latexDocs = latexSplitter.createDocuments([{ pageContent: latexText }]);
console.log(latexDocs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: '\\documentclass{article}\n\n\\begin{document}\n\n\\maketitle' },
    Document { metadata: {}, pageContent: '\\section{Introduction}' },
    Document { metadata: {}, pageContent: 'Large language models (LLMs) are a type of machine learning' },
    Document { metadata: {}, pageContent: 'model that can be trained on vast amounts of text data to' },
    Document { metadata: {}, pageContent: 'generate human-like language. In recent years, LLMs have' },
    Document { metadata: {}, pageContent: 'made significant advances in a variety of natural language' },
    Document { metadata: {}, pageContent: 'processing tasks, including language translation, text' },
    Document { metadata: {}, pageContent: 'generation, and sentiment analysis.' },
    Document { metadata: {}, pageContent: '\\subsection{History of LLMs}' },
    Document { metadata: {}, pageContent: 'The earliest LLMs were developed in the 1980s and 1990s,' },
    Document { metadata: {}, pageContent: 'but they were limited by the amount of data that could be' },
    Document { metadata: {}, pageContent: 'processed and the computational power available at the' },
    Document { metadata: {}, pageContent: 'time. In the past decade, however, advances in hardware and' },
    Document { metadata: {}, pageContent: 'software have made it possible to train LLMs on massive' },
    Document { metadata: {}, pageContent: 'datasets, leading to significant improvements in' },
    Document { metadata: {}, pageContent: 'performance.' },
    Document { metadata: {}, pageContent: '\\subsection{Applications of LLMs}' },
    Document { metadata: {}, pageContent: 'LLMs have many applications in industry, including' },
    Document { metadata: {}, pageContent: 'chatbots, content creation, and virtual assistants. They' },
    Document { metadata: {}, pageContent: 'can also be used in academia for research in linguistics,' },
    Document { metadata: {}, pageContent: 'psychology, and computational linguistics.' },
    Document { metadata: {}, pageContent: '\\end{document}' }
]
```

## HTML

以下是使用 HTML 文本分割器的示例：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const htmlText = `
<!DOCTYPE html>
<html>
    <head>
        <title>🦜️🔗 LangChain</title>
        <style>
            body {
                font-family: Arial, sans-serif;
            }
            h1 {
                color: darkblue;
            }
        </style>
    </head>
    <body>
        <div>
            <h1>🦜️🔗 LangChain</h1>
            <p>⚡ Building applications with LLMs through composability ⚡</p>
        </div>
        <div>
            As an open-source project in a rapidly developing field, we are extremely open to contributions.
        </div>
    </body>
</html>
`;

const htmlSplitter = RecursiveCharacterTextSplitter.fromLanguage(
    "html",
    { chunkSize: 60, chunkOverlap: 0 }
);
const htmlDocs = htmlSplitter.createDocuments([{ pageContent: htmlText }]);
console.log(htmlDocs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: '<!DOCTYPE html>\n<html>' },
    Document { metadata: {}, pageContent: '<head>\n        <title>🦜️🔗 LangChain</title>' },
    Document { metadata: {}, pageContent: '<style>\n            body {\n                font-family: Aria' },
    Document { metadata: {}, pageContent: 'l, sans-serif;\n            }\n            h1 {' },
    Document { metadata: {}, pageContent: 'color: darkblue;\n            }\n        </style>\n    </head' },
    Document { metadata: {}, pageContent: '>' },
    Document { metadata: {}, pageContent: '<body>' },
    Document { metadata: {}, pageContent: '<div>\n            <h1>🦜️🔗 LangChain</h1>' },
    Document { metadata: {}, pageContent: '<p>⚡ Building applications with LLMs through composability ⚡' },
    Document { metadata: {}, pageContent: '</p>\n        </div>' },
    Document { metadata: {}, pageContent: '<div>\n            As an open-source project in a rapidly dev' },
    Document { metadata: {}, pageContent: 'eloping field, we are extremely open to contributions.' },
    Document { metadata: {}, pageContent: '</div>\n    </body>\n</html>' }
]
```

## Solidity

以下是使用 Solidity 文本分割器的示例：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const SOL_CODE = `
pragma solidity ^0.8.20;
contract HelloWorld {
   function add(uint a, uint b) pure public returns(uint) {
       return a + b;
   }
}
`;

const solSplitter = RecursiveCharacterTextSplitter.fromLanguage(
    "sol",
    { chunkSize: 128, chunkOverlap: 0 }
);
const solDocs = solSplitter.createDocuments([{ pageContent: SOL_CODE }]);
console.log(solDocs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: 'pragma solidity ^0.8.20;' },
    Document { metadata: {}, pageContent: 'contract HelloWorld {\n   function add(uint a, uint b) pure public returns(uint) {\n       return a + b;\n   }\n}' }
]
```

## C\#

以下是使用 C# 文本分割器的示例：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const C_CODE = `
using System;
class Program
{
    static void Main()
    {
        int age = 30; // Change the age value as needed

        // Categorize the age without any console output
        if (age < 18)
        {
            // Age is under 18
        }
        else if (age >= 18 && age < 65)
        {
            // Age is an adult
        }
        else
        {
            // Age is a senior citizen
        }
    }
}
`;

const csharpSplitter = RecursiveCharacterTextSplitter.fromLanguage(
    "csharp",
    { chunkSize: 128, chunkOverlap: 0 }
);
const csharpDocs = csharpSplitter.createDocuments([{ pageContent: C_CODE }]);
console.log(csharpDocs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: 'using System;' },
    Document { metadata: {}, pageContent: 'class Program\n{\n    static void Main()\n    {\n        int age = 30; // Change the age value as needed' },
    Document { metadata: {}, pageContent: '// Categorize the age without any console output\n        if (age < 18)\n        {\n            // Age is under 18' },
    Document { metadata: {}, pageContent: '}\n        else if (age >= 18 && age < 65)\n        {\n            // Age is an adult\n        }\n        else\n        {' },
    Document { metadata: {}, pageContent: '// Age is a senior citizen\n        }\n    }\n}' }
]
```

## Haskell

以下是使用 Haskell 文本分割器的示例：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const HASKELL_CODE = `
main :: IO ()
main = do
    putStrLn "Hello, World!"
-- Some sample functions
add :: Int -> Int -> Int
add x y = x + y
`;

const haskellSplitter = RecursiveCharacterTextSplitter.fromLanguage(
    "haskell",
    { chunkSize: 50, chunkOverlap: 0 }
);
const haskellDocs = haskellSplitter.createDocuments([{ pageContent: HASKELL_CODE }]);
console.log(haskellDocs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: 'main :: IO ()' },
    Document { metadata: {}, pageContent: 'main = do\n    putStrLn "Hello, World!"\n-- Some' },
    Document { metadata: {}, pageContent: 'sample functions\nadd :: Int -> Int -> Int\nadd x y' },
    Document { metadata: {}, pageContent: '= x + y' }
]
```

## PHP

以下是使用 PHP 文本分割器的示例：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const PHP_CODE = `<?php
namespace foo;
class Hello {
    public function __construct() { }
}
function hello() {
    echo "Hello World!";
}
interface Human {
    public function breath();
}
trait Foo { }
enum Color
{
    case Red;
    case Blue;
}`;

const phpSplitter = RecursiveCharacterTextSplitter.fromLanguage(
    "php",
    { chunkSize: 50, chunkOverlap: 0 }
);
const phpDocs = phpSplitter.createDocuments([{ pageContent: PHP_CODE }]);
console.log(phpDocs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: '<?php\nnamespace foo;' },
    Document { metadata: {}, pageContent: 'class Hello {' },
    Document { metadata: {}, pageContent: 'public function __construct() { }\n}' },
    Document { metadata: {}, pageContent: 'function hello() {\n    echo "Hello World!";\n}' },
    Document { metadata: {}, pageContent: 'interface Human {\n    public function breath();\n}' },
    Document { metadata: {}, pageContent: 'trait Foo { }\nenum Color\n{\n    case Red;' },
    Document { metadata: {}, pageContent: 'case Blue;\n}' }
]
```

## PowerShell

以下是使用 PowerShell 文本分割器的示例：

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const POWERSHELL_CODE = `
$directoryPath = Get-Location

$items = Get-ChildItem -Path $directoryPath

$files = $items | Where-Object { -not $_.PSIsContainer }

$sortedFiles = $files | Sort-Object LastWriteTime

foreach ($file in $sortedFiles) {
    Write-Output ("Name: " + $file.Name + " | Last Write Time: " + $file.LastWriteTime)
}
`;

const powershellSplitter = RecursiveCharacterTextSplitter.fromLanguage(
    "powershell",
    { chunkSize: 100, chunkOverlap: 0 }
);
const powershellDocs = powershellSplitter.createDocuments([{ pageContent: POWERSHELL_CODE }]);
console.log(powershellDocs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: '$directoryPath = Get-Location\n\n$items = Get-ChildItem -Path $directoryPath' },
    Document { metadata: {}, pageContent: '$files = $items | Where-Object { -not $_.PSIsContainer }' },
    Document { metadata: {}, pageContent: '$sortedFiles = $files | Sort-Object LastWriteTime' },
    Document { metadata: {}, pageContent: 'foreach ($file in $sortedFiles) {' },
    Document { metadata: {}, pageContent: 'Write-Output ("Name: " + $file.Name + " | Last Write Time: " + $file.LastWriteTime)\n}' }
]
```

## Visual basic 6

```ts theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
const VISUALBASIC6_CODE = `Option Explicit

Public Sub HelloWorld()
    MsgBox "Hello, World!"
End Sub

Private Function Add(a As Integer, b As Integer) As Integer
    Add = a + b
End Function
`;

const visualbasic6Splitter = RecursiveCharacterTextSplitter.fromLanguage(
    "visualbasic6",
    { chunkSize: 128, chunkOverlap: 0 }
);
const visualbasic6Docs = visualbasic6Splitter.createDocuments([{ pageContent: VISUALBASIC6_CODE }]);
console.log(visualbasic6Docs);
```

```javascript theme={"theme":{"light":"catppuccin-latte","dark":"catppuccin-mocha"}}
[
    Document { metadata: {}, pageContent: 'Option Explicit' },
    Document { metadata: {}, pageContent: 'Public Sub HelloWorld()\n    MsgBox "Hello, World!"\nEnd Sub' },
    Document { metadata: {}, pageContent: 'Private Function Add(a As Integer, b As Integer) As Integer\n    Add = a + b\nEnd Function' }
]
```

***

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