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

# Document Reader Node

> Read and extract text content from various document formats

## Overview

The Document Reader Node extracts text content from uploaded documents. This node enables you to:

* Read text from PDFs, Word documents, PowerPoint, Excel, and more
* Extract content from images using OCR
* Control reading position with start index and max length
* Process large documents incrementally
* Support numerous document formats

<Note>
  **Reading files with an LLM:** For most workflows that need to read document content and use it with an LLM (summarize, answer questions, extract), we recommend using the **Agent node** with the **Document Reader** tool. You can connect the node that produces the file in **series** to that agent, or use an **Agent Swarm** if the producer is also an agent. See [Files in Workflows — Reading files: Agent with Document Reader](/docs/guides/files-in-workflows#reading-files-agent-with-document-reader) for details.
</Note>

## Configuration Parameters

### Node Configuration

* **Upload File**:

  Upload a document to read. Supported formats include:

  * PDF (.pdf)
  * Microsoft Office (.docx, .xlsx, .pptx)
  * Text files (.txt, .md, .csv)
  * Images with text (.jpg, .png)
  * And many more

* **Start Index**:

  Character position to start reading from. Use negative values to start from the end (default: 0)

* **Max Length**:

  Maximum number of characters to read from the file. Useful for processing large documents in chunks.

## Expected Inputs and Outputs

* **Inputs**:

  * The node accepts file uploads via the file selection input

* **Outputs**:

  * **content**: Extracted text content from the document

## Use Case Examples

1. **Document Processing**:

   Extract text from uploaded documents for analysis, summarization, or data extraction workflows.

2. **Incremental Reading**:

   Process very large documents by reading in chunks using start\_index and max\_length parameters.

3. **OCR Text Extraction**:

   Extract text from scanned documents or images for digitization and searchability.

## Error Handling and Troubleshooting

* **Unsupported File Format**:

  Verify the uploaded file format is in the list of supported document types.

* **Empty Content**:

  If no content is extracted, the file may be corrupted, password-protected, or contain only images without OCR.

* **Large File Performance**:

  For very large files, consider using start\_index and max\_length to process the document in smaller chunks.

If you encounter any issues not covered in this documentation, please reach out to our [support team](mailto:dev@pathlit.ai) for assistance.

## Relevant Nodes

<CardGroup>
  <Card title="VLM Document Extraction" href="/docs/nodes/vlm-document-extraction">
    Extract structured data using vision models
  </Card>

  <Card title="Document Data Node" href="/docs/nodes/document-data">
    Process PDFs and images with OCR or VLM
  </Card>

  <Card title="LLM Node" href="/docs/nodes/llm">
    Process extracted content with AI
  </Card>
</CardGroup>