For the complete documentation index, see llms.txt. This page is also available as Markdown.

List, Fetch, and Download Documents

This snippet mirrors the document retrieval recipe using Python.

import os
import requests


token = os.getenv("AUTOCONTENT_TOKEN", "YOUR_API_TOKEN")
document_id = os.getenv("DOCUMENT_ID", "YOUR_REQUEST_ID")
base_url = "https://api.autocontentapi.com"
headers = {"Authorization": f"Bearer {token}"}


def extension_from_content_type(content_type: str) -> str:
    if "pdf" in content_type:
        return ".pdf"
    if "html" in content_type:
        return ".html"
    return ".txt"


list_response = requests.get(f"{base_url}/documents/get", headers=headers, params={"page": 1, "pageSize": 10}, timeout=30)
list_response.raise_for_status()
print("Documents page:")
print(list_response.json())

single_response = requests.get(f"{base_url}/documents/{document_id}", headers=headers, timeout=30)
single_response.raise_for_status()
print("Single document:")
print(single_response.json())

download_response = requests.get(f"{base_url}/documents/{document_id}/download", headers=headers, timeout=60)
download_response.raise_for_status()

extension = extension_from_content_type(download_response.headers.get("content-type", "text/plain"))
output_path = f"briefing-document-{document_id}{extension}"
with open(output_path, "wb") as file_handle:
    file_handle.write(download_response.content)

print(f"Saved {output_path}")

Set YOUR_API_TOKEN (or AUTOCONTENT_TOKEN) and DOCUMENT_ID before running.

See also

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