> For the complete documentation index, see [llms.txt](https://lamatic.ai/llms.txt).

# Doc Extractor Node (Deprecated)

**This node is deprecated.** You can no longer add a *new* Doc Extractor node from the palette. Existing flows keep running unchanged, nothing breaks. For new extraction work, use **[Agentic Doc Extraction](/docs/nodes/ai/agentic-doc-extraction)**, which supports the same job plus native structured extraction, stored images with bounding boxes, and a per-run isolated container. See [Migrating from Doc Extractor](/docs/nodes/ai/agentic-doc-extraction#migrating-from-doc-extractor) if you want to move an existing flow.

<NodeOverview slug="doc-extractor" type="ai" />

## Overview

The Doc Extractor node extracts content from a document URL (PDF or image), sends it to a selected LLM, and applies prompt-based instructions during extraction. You can control both the extraction behavior and the final response shape so downstream nodes receive output in the format you need.

<NodeTypeInfo
  batchTrigger={false}
  eventTrigger={false}
  action={true}
  description="This node is an Action node that reads document content, applies LLM-guided extraction prompts, and returns structured output."
/>

## Features

<details>
  <summary>**Key Functionalities**</summary>

1. **LLM-Guided Extraction**: Select an LLM model to interpret document content and extract relevant information intelligently.
2. **Instruction-Driven Parsing**: Provide extraction instructions with a custom prompt so the model returns only the fields and structure you need.
3. **Document URL Input**: Use a direct PDF/image URL or pass a URL dynamically from an upstream node.
4. **Configurable Output Format**: Return output as `markdown`, `json`, or `plain text` based on your workflow requirements.
5. **Page Handling Control**: Choose whether to join multi-page documents into a single response.

</details>

<details>
  <summary>**Benefits**</summary>

1. **Flexible Automation**: Adapt extraction logic for invoices, reports, forms, receipts, and other document types.
2. **Consistent Downstream Processing**: Standardized output format simplifies chaining into parser, logic, and storage nodes.
3. **Reduced Manual Parsing**: Replace brittle OCR-only pipelines with prompt-guided extraction.
4. **Reusable Configuration**: Keep prompts and model settings reusable across multiple flows.

</details>

## What Can I Build?

1. Invoice and receipt data extraction pipelines
2. Resume and profile parsing automations
3. Contract or policy document summarization workflows
4. Document-to-JSON enrichment pipelines for databases and APIs

## Prompt Examples

### Invoice Data Extractor

Extracts key fields from an invoice PDF.

**Document URL**
```
{{triggerNode_1.document_url}}
```

**System Prompt**
```
Extract the following fields from this invoice:
- Invoice number
- Vendor name
- Invoice date
- Due date
- Line items (description, quantity, unit price)
- Total amount

Return as JSON. Use null for any field not found in the document.
```

**Settings**
- Output Format: `JSON`
- Join Pages: `On`

---

### Resume Parser

Extracts candidate details from a resume PDF.

**Document URL**
```
{{triggerNode_1.document_url}}
```

**System Prompt**
```
Extract the following details from this resume:
- Full name
- Email address
- Phone number
- Current job title
- Years of experience
- Top 5 skills

Return as JSON. Use null for any field not found.
```

**Settings**
- Output Format: `JSON`
- Join Pages: `On`

> Use `JSON` output format when passing data to downstream nodes. Switch to `Markdown` only for human-readable reports.

## Setup

### Select the Doc Extractor Node

1. Add the Doc Extractor node to your flow.
2. Select the LLM model for extraction.
3. Enter a document URL (PDF or image), or map it from an upstream node.
4. Add extraction instructions and optional custom extraction prompt.
5. Select the output format and page-join behavior.
6. Run and validate the output in node logs or downstream nodes.

## Configuration Reference

| Parameter | Description | Required | Example |
| --- | --- | --- | --- |
| LLM Model | Model used to extract and structure document content. | Yes | Gemini 2.5 Flast Lite |
| Prompt | Instructions that define what to extract and how to structure it. | Yes | Extract invoice number, vendor, line items, totals, and due date. |
| Document URL | URL of the document (PDF or image). Accepts direct URL or variable input from upstream node. | Yes | `{{trigger.document_url}}` |
| Custom Extraction Prompt | Overrides the default OCR prompt sent to the Gemini model. Leave empty to use the built-in prompt. | No | Focus on tabular data and preserve numeric precision. |
| Output Format | Output response format: `markdown`, `json`, or `plain text`. | Yes | json |
| Join Pages | If `true`, combines all pages into one extraction output. If `false`, keeps page-level granularity. | Yes | true |

## Prompting Tips

- Be explicit about required fields, output keys, and formatting rules.
- For JSON output, list expected keys and types to reduce malformed responses.
- Add fallback instructions for missing values (for example: `"null"` when field not found).
- If precision matters (amounts, IDs, dates), explicitly tell the model to avoid normalization.

## Low-Code Example

```yaml
nodeName: Doc Extractor
documentUrl: '{{triggerNode_1.output.url}}'
customPrompt: ''
mistralIncludeAnnotations: false
mistralTableFormat: markdown
outputFormat: markdown
joinPages: true
schema: ''
ocrModelName:
  - configName: configA
    type: ocr/document
    provider_name: gemini
    credential_name: MODEL_CRED_NAME
    credentialId: 1f2d5b1e-9e8e-4b82-9996-70e351f8f720
    model_name: gemini/gemini-2.5-flash-lite
    params: {}
prompts:
  - id: ID
    role: user
    content:""

```

## Output

The node returns extracted content in the format you selected:

- **`markdown`**: Useful for human-readable summaries and reports.
- **`json`**: Best for structured automation and downstream programmatic parsing.
- **`plain text`**: Lightweight output for quick processing or logging.

## Troubleshooting

### Common Issues

| Problem | Solution |
| --- | --- |
| Document URL not accessible | Verify URL is public/reachable and points to a valid PDF or image file. |
| Missing fields in output | Tighten extraction instructions and add explicit required keys in your prompt. |
| Output format mismatch | Confirm `Output Format` selection and ensure prompt aligns with that format. |
| Weak OCR quality | Use a clearer source document and add a `Custom Extraction Prompt` emphasizing OCR precision. |

### Debugging

1. Test with a known sample document before production input.
2. Start with JSON output for easier validation.
3. Check node logs to compare prompt, model response, and final parsed output.