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

# Configuration

> Configure the API to your needs

Different applications have different needs. Chunkr AI API is designed to be flexible and customizable to meet your specific requirements.

We support the following configuration options:

* `chunk_processing`: Controls the setting for the chunking and post-processing of each chunk.
* `expires_in`: The number of seconds until task is deleted.
* `ocr_strategy`: Controls the Optical Character Recognition (OCR) strategy.
* `pipeline`: Options for layout analysis and OCR providers.
* `segment_processing`: Controls the post-processing of each segment type. Allows you to generate HTML, markdown and run custom VLM prompts.
* `segmentation_strategy`: Controls the segmentation strategy

The configuration options can be combined to create a customized processing pipeline. When a `Task` is created, the configuration is done through the `Configuration` object.

Here is an example of how to configure the API to run a custom VLM prompt on each picture in a document:

<CodeGroup>
  ```python Python theme={"system"}
  from chunkr_ai import Chunkr
  from chunkr_ai.models import (
      Configuration, 
      GenerationConfig, 
      GenerationStrategy, 
      SegmentProcessing, 
      SegmentationStrategy,
      SegmentFormat
  )

  chunkr = Chunkr()

  chunkr.upload("path/to/file", Configuration(
      segment_processing=SegmentProcessing(
          picture=GenerationConfig(
              format=SegmentFormat.MARKDOWN,
              strategy=GenerationStrategy.LLM,
              llm="Does this picture have a cat in it? Answer must be true or false."
          )
      ),
  ))
  ```

  ```bash cURL theme={"system"}
  curl --request POST \
    --url https://api.chunkr.ai/api/v1/task/parse \
    --header 'Authorization: YOUR_API_KEY' \
    --header 'Content-Type: application/json' \
    --data '{
      "file": "base64_or_url_to_file",
      "file_name": "document.pdf",
      "segment_processing": {
        "picture": {
          "format": "Markdown",
          "strategy": "LLM",
          "llm": "Does this picture have a cat in it? Answer must be true or false."
        }
      }
    }'
  ```
</CodeGroup>