> ## Documentation Index
> Fetch the complete documentation index at: https://docs.chonkie.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# TextChef

> Process plain text files into Document objects.

The `TextChef` processes plain text files and returns structured `Document` objects for further processing.

## Installation

TextChef is included in the base installation of Chonkie. No additional dependencies are required.

<Info>
  For installation instructions, see the [Installation
  Guide](/oss/installation).
</Info>

## Initialization

```python theme={"system"}
from chonkie import TextChef

# Simple initialization - no parameters required
chef = TextChef()
```

## Methods

### process()

Process a text file and return a `Document` object.

#### Parameters

<ParamField path="path" type="Union[str, Path]" required>
  Path to the text file (string or Path object)
</ParamField>

#### Returns

`Document` object containing the file content

### process\_batch()

Process multiple text files at once.

#### Parameters

<ParamField path="paths" type="list[Union[str, Path]]" required>
  List of file paths to process
</ParamField>

#### Returns

`list[Document]` where each `Document` contains a file's contents.

## Usage

```python theme={"system"}
from chonkie import TextChef

# Initialize the chef
chef = TextChef()

# Process a text file
doc = chef.process("example.txt")

# Access the content
print(doc.content)
print(f"Document ID: {doc.id}")
```

## Integration with Chunkers

TextChef is designed to work seamlessly with Chonkie's chunkers:

```python theme={"system"}
from chonkie import TextChef, TokenChunker

# Step 1: Load text file
chef = TextChef()
doc = chef.process("article.txt")

# Step 2: Chunk the content
chunker = TokenChunker(chunk_size=512, chunk_overlap=50)
chunks = chunker.chunk(doc.content)

# Step 3: Store chunks back in the document
doc.chunks = chunks

# Now your document has both content and chunks
print(f"Document {doc.id}:")
print(f"  Content: {len(doc.content)} characters")
print(f"  Chunks: {len(doc.chunks)}")
```

## Encoding

TextChef reads files with UTF-8 encoding by default, ensuring proper handling of:

* Unicode characters
* International text
* Special symbols
* Emoji and other non-ASCII characters

All text is read as strings and preserved exactly as it appears in the source file.