Extract structured data from any web page with a plain-language instruction. Returns JSON plus a validation block that checks numeric values against the page text and their history.
Run in Postman
{
"data": [
{
"value": "4010.00",
"raw_text": "4,010.00"
}
],
"validation": {
"status": "ok",
"reason": "no_reference",
"value": 4010,
"model_value": 4010,
"raw_text": "4,010.00",
"reference": null,
"change_pct": null,
"suspect_pct": 10,
"reject_pct": 30,
"on_page": true,
"votes": [],
"mode": "shadow",
"reference_source": null
}
}
curl --location --request GET 'https://zylalabs.com/api/14428/natural+language+web+scraper+api/36437/extract+from+page?url=https://www.investing.com/commodities/gold&expiration_seconds=600&raw_text=true&parse_description=Current gold futures price as a plain number, in a field called value&expiration_seconds=600&value_field=value&raw_text=true&last_value=4012.5&max_chars=6000&value_field=value&last_value=4012.5&max_chars=6000' --header 'Authorization: Bearer YOUR_API_KEY'
{
"data": [
{
"value": 4066.5
}
],
"validation": {
"status": "ok",
"reason": "no_reference",
"value": 4066.5,
"model_value": 4066.5,
"raw_text": null,
"suspect_pct": 10,
"reject_pct": 30,
"on_page": null,
"votes": [],
"mode": "shadow"
}
}
curl --location --request GET 'https://zylalabs.com/api/14428/natural+language+web+scraper+api/36438/extract+from+screenshot?url=https://www.investing.com/commodities/gold&llm_instructions=Current gold price in USD as a number, in a field called value&expiration_seconds=600&value_field=value&last_value=4012.5' --header 'Authorization: Bearer YOUR_API_KEY'
After signing up, every developer is assigned a personal API access key, a unique combination of letters and digits provided to access to our API endpoint. To authenticate with the Natural Language Web Scraper API simply include your bearer token in the Authorization header.
| Header | Description |
|---|---|
Authorization
|
Required
Should be Bearer access_key. See "Your API Access Key" above when you are subscribed.
|
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A JSON object with two parts: data, the fields you asked for in your instruction, and validation, a check of the main numeric value (status ok, suspect, rejected or unchecked, the reason, the raw text as written on the page and the thresholds used).
In plain language, through parse_description (text endpoint) or llm_instructions (screenshot endpoint). Name the fields you want back, for example "product name, price in USD as a number and availability, in fields called name, price and in_stock".
Use Extract From Page by default: it is faster and works on the page text. Switch to Extract From Screenshot when the data only shows once the page is rendered, such as charts, widgets, canvas tables or JavaScript-heavy apps.
Whether the number is actually written on the page (on_page), whether it looks like a decimal shift (x10, x100), and how far it moved from the last accepted value for the same URL and instruction. You always receive the answer; the status tells you how much to trust it.
Yes. Send last_value with the last number you stored for that URL and instruction and the validation compares against it instead of the service history. Use value_field when your answer has several numbers.
No. The page and the answer are reused for the same URL and instruction while they are younger than expiration_seconds (default 600 seconds). Send 0 to force a fresh fetch.
Extract From Page reads the server-rendered text. For content that only appears after the page runs its scripts, use Extract From Screenshot, which renders the page in a browser before reading it.
The response comes with error true and a message describing the problem (blocked page, timeout, upstream error). The call is not counted as successful.
Both endpoints return structured JSON data. The "Extract From Page" endpoint provides fields based on the page's text, while "Extract From Screenshot" returns data from rendered visuals. Each response includes a "data" section with requested fields and a "validation" section for numeric checks.
The key fields in the response data include "value" (the extracted numeric data), "raw_text" (the text as it appears on the page), and the "validation" object, which contains status, reason, and checks related to the accuracy of the extracted value.
The response data is organized into two main sections: "data" and "validation." The "data" section contains the extracted fields, while the "validation" section provides insights into the accuracy and reliability of the extracted numeric values, including status and reasons for any discrepancies.
The "Extract From Page" endpoint can retrieve text-based data like prices, product specifications, and availability. The "Extract From Screenshot" endpoint is suitable for visual data such as charts, graphs, and dynamic content that requires rendering to be visible.
Users can customize requests by specifying the "parse_description" for the "Extract From Page" endpoint or "llm_instructions" for the "Extract From Screenshot" endpoint. They can define the fields they want to extract and provide optional parameters like "expiration_seconds" and "last_value."
The data is sourced from publicly accessible web pages. The API fetches the content directly from the specified URL, ensuring that the information is current and relevant. The validation process further enhances data reliability by cross-referencing extracted values with page text.
Data accuracy is maintained through a validation layer that checks extracted numeric values against the page text, historical data, and potential decimal shifts. Each response includes a validation status, allowing users to assess the reliability of the extracted information.
Typical use cases include price monitoring for commodities, competitor analysis, extracting product specifications from e-commerce sites, and gathering data from reports or dashboards. The API is designed to streamline data extraction for various applications, enhancing decision-making processes.
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