> ## Documentation Index
> Fetch the complete documentation index at: https://docs.landing.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Parse & Extract
export const splitJSON = 'split rules';
export const split = 'ADE Split';
export const adeTypeScriptLibrary = 'ade-typescript';
export const adePythonLibrary = 'ade-python';
export const dpt2mini = 'DPT-2 mini';
export const dpt2 = 'DPT-2';
export const dpt1 = 'DPT-1';
export const dpt = 'Document Pre-Trained Transformer';
export const companyName = 'LandingAI';
export const buildExtract = 'ADE Build Extract Schema';
export const extract = 'ADE Extract';
export const parse = 'ADE Parse';
export const ade = 'Agentic Document Extraction';
## Overview
This tutorial walks you through how to parse a document with the {parse} API and extract specific fields from it with the {extract} API.
This tutorial uses the [{adePythonLibrary} library](./ade-python) and [{adeTypeScriptLibrary} library](./ade-typescript).
In this tutorial, we will:
* Parse this PDF: Wire Transfer Form
* Extract these fields: **Bank Name** and **Total Invoice Amount**
These examples require the [Python](./ade-python) or [TypeScript](./ade-typescript) client library. Before running a script, set your API key and install the library and any required dependencies.
The scripts have been tested with PDF and PNG files and may work with other file types supported by {ade}.
## 1. Download the Document to Process
Download the Wire Transfer Form and save it to a local directory.
## 2. Create the Script
Copy the script for your language and save it as `parse-extract.py` or `parse-extract.ts` in the same directory as the PDF.
```python Python [expandable] theme={null}
import json
from pathlib import Path
from landingai_ade import LandingAIADE
# Initialize client (uses VISION_AGENT_API_KEY environment variable)
client = LandingAIADE()
# Define the extraction schema
schema = json.dumps({
"type": "object",
"properties": {
"bank_name": {
"description": "The official name of the bank where the account is held.",
"x-alternativeNames": ["Name of Bank", "Financial Institution", "Bank"],
"type": "string"
},
"total_invoice_amount": {
"description": "The total monetary amount of the invoice, including all charges and taxes.",
"x-alternativeNames": ["Grand Total", "Amount Due", "Invoice Total"],
"type": "number"
}
}
})
# Parse the document
# save_to is optional, but saves the full parse response, which is useful for
# keeping a record and for other downstream processing tasks
parse_response = client.parse(
document=Path('wire-transfer.pdf'),
model='dpt-2-latest',
save_to='output'
)
# Extract fields from the parsed output
extract_response = client.extract(
schema=schema,
markdown=parse_response.markdown,
model='extract-latest'
)
# Save the extract results to a JSON file
with open('output/wire-transfer_extract_output.json', 'w') as f:
json.dump(extract_response.to_dict(), f, indent=2)
```
```typescript TypeScript [expandable] theme={null}
import LandingAIADE, { toFile } from "landingai-ade";
import fs from "fs";
// Initialize client (uses VISION_AGENT_API_KEY environment variable)
const client = new LandingAIADE();
// Define the extraction schema
const schema = JSON.stringify({
type: "object",
properties: {
bank_name: {
description: "The official name of the bank where the account is held.",
"x-alternativeNames": ["Name of Bank", "Financial Institution", "Bank"],
type: "string"
},
total_invoice_amount: {
description: "The total monetary amount of the invoice, including all charges and taxes.",
"x-alternativeNames": ["Grand Total", "Amount Due", "Invoice Total"],
type: "number"
}
}
});
// Parse the document
// saveTo is optional, but saves the full parse response, which is useful for
// keeping a record and for other downstream processing tasks
const parseResponse = await client.parse({
document: fs.createReadStream("wire-transfer.pdf"),
model: "dpt-2-latest",
saveTo: "output"
});
// Extract fields from the parsed output
const extractResponse = await client.extract({
schema: schema,
markdown: await toFile(Buffer.from(parseResponse.markdown), "document.md"),
model: "extract-latest"
});
// Save the extract results to a JSON file
fs.mkdirSync("output", { recursive: true });
fs.writeFileSync(
"output/wire-transfer_extract_output.json",
JSON.stringify(extractResponse, null, 2)
);
```
## 3. Run the Script
Run the script from the same directory:
```bash Run Python theme={null}
python parse-extract.py
```
```bash Run TypeScript theme={null}
npx tsx parse-extract.ts
```
## 4. View Extraction Output
The results are saved to an `output` folder in the same directory. View the extracted fields and metadata in `wire-transfer_extract_output.json`.
```json [expandable] theme={null}
{
"extraction": {
"bank_name": "JPMorgan Chase Bank, N.A.",
"total_invoice_amount": 15750.0
},
"extraction_metadata": {
"bank_name": {
"references": [
"4f64f8d9-ff3a-4c47-aeb5-2ab6eaa9ce7a"
],
"value": "JPMorgan Chase Bank, N.A."
},
"total_invoice_amount": {
"references": [
"deeb001e-6b3e-4c4e-96b1-6f321521ad4f",
"0-h"
],
"value": 15750.0
}
},
"metadata": {
"credit_usage": 0.5396,
"duration_ms": 11536,
"filename": "upload.md",
"job_id": "bec005b58d144096b0525af3aa6ed12d",
"org_id": null,
"version": "extract-20260314",
"fallback_model_version": null,
"schema_violation_error": null,
"warnings": []
}
}
```
## Next Steps
Now that you have a working script, you can:
* Replace `wire-transfer.pdf` with any document you want to parse and extract from.
* Modify the `schema` dictionary to extract different fields. For guidance, see [Extraction Schema (JSON)](./ade-extract-schema-json).
* Use the Playground to build and test a schema before adding it to your code. See [Schema Wizard](./ade-extract-playground).
* Link extracted fields back to their locations in the original document. See [Link Extracted Data to Document Locations](./ade-extract-grounding-sample).