> ## 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.

# Developer Quickstart

> Learn how to get started with Chunkr AI API

Chunkr AI is an API service to convert complex documents into LLM/RAG-ready data. We support a wide range of document types, including PDFs, Office files (Word, Excel, PowerPoint), and images.

## Getting Started

To get started with Chunkr AI, follow these simple steps to set up your account and integrate our API into your application.

### Step 1: Sign Up and Create an API Key

1. Visit [Chunkr AI](https://chunkr.ai)
2. Click on "Login" and create your account
3. Once logged in, navigate to "API Keys" in the dashboard

### Step 2: Install our client SDK

<CodeGroup>
  ```bash Python theme={"system"}
  pip install chunkr-ai
  ```
</CodeGroup>

### Step 3: Upload your document

<CodeGroup>
  ```python Python theme={"system"}
  from chunkr_ai import Chunkr

  # Initialize the Chunkr client with your API key - get this from https://chunkr.ai
  chunkr = Chunkr(api_key="your_api_key")

  # Upload a document via url or local file path
  url = "https://chunkr-web.s3.us-east-1.amazonaws.com/landing_page/input/specs.pdf"
  task = chunkr.upload(url) 
  ```
</CodeGroup>

### Step 4: Export the results

Chunkr AI will return a `TaskResponse` object. This object contains the results of the document conversion. You can export the results in various formats or load them into a variable.

<CodeGroup>
  ```python Python theme={"system"}
  # Export HTML of document
  html = task.html(output_file="output.html")

  # Export markdown of document
  markdown = task.markdown(output_file="output.md")

  # Export text of document
  content = task.content(output_file="output.txt")

  # Export result as JSON - TaskResponse is already in memory so no need to load it into a variable
  task.json(output_file="output.json")
  ```
</CodeGroup>

### Step 5: Explore the output

The output of the task can be used to build your RAG pipeline.
Checkout the [API Reference](/api-references/task/create-task#response-output-chunks) for more details.

<CodeGroup>
  ```python Python theme={"system"}
  # The output of the task is a list of chunks
  chunks = task.output.chunks

  # Each chunk is a list of segments
  for chunk in chunks:
      for segment in chunk.segments:
          print(segment.segment_type)

  # You can also access the `embed` field in the chunk 
  # for content to be used in RAG pipelines
  for chunk in chunks:
      print(chunk.embed)
  ```
</CodeGroup>

### Step 6: Clean up

You can clean up the open connections by calling the `close()` method on the `Chunkr` client.

<CodeGroup>
  ```python Python theme={"system"}
  chunkr.close()
  ```
</CodeGroup>

### Step 7: API References and support for other languages

To understand all the input configurations and output schema and models, please refer to the [API References](/api-references/task/create-task).
You can also use the API Reference Playground to generate cURL requests and code snippets for different languages like JavaScript/TypeScript to help you get started quickly.

## Authentication Options

You can authenticate with the Chunkr AI API in two ways:

1. **Direct API Key** - Pass your API key directly when initializing the client
2. **Environment Variable** - Set `CHUNKR_API_KEY` in your `.env` file

<CodeGroup>
  ```python Python theme={"system"}
  from chunkr_ai import Chunkr

  # Option 1: Initialize with API key directly
  chunkr = Chunkr(api_key="your_api_key")

  # Option 2: Initialize without api_key parameter - will use CHUNKR_API_KEY from environment
  chunkr = Chunkr()
  ```
</CodeGroup>

## Self Hosted

If you're using a self-hosted deployment of Chunkr AI, you can configure the API URL when initializing the client:

<CodeGroup>
  ```python Python theme={"system"}
  from chunkr_ai import Chunkr

  # Option 1: With direct API key
  chunkr = Chunkr(
      api_key="your_api_key",
      url="https://your-self-hosted-chunkr.ai"
  )

  # Option 2: Using environment variables
  # Set CHUNKR_API_KEY and CHUNKR_URL in your .env file
  chunkr = Chunkr()
  ```
</CodeGroup>

When using environment variables for self-hosted deployments, set both `CHUNKR_API_KEY` and `CHUNKR_URL` in your `.env` file.