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Retrieve document contents

GET /documents/{document_id}/contents/

Retrieve contents of a document by its ID.

Returns the content of the document with the specified ID, along with the index of the latest retrieved chunk. Each call fetches up to 20 chunks. To get more, use the end_chunk value from the response as the start_chunk for the next call.

Parameter In Type Required Description
document_id path integer yes The ID of the document to retrieve contents for.
start_chunk query integer Indicate the starting chunk that you want to retrieve. If not specified, the default value is 0.
end_chunk query integer Indicate the ending chunk that you want to retrieve. If not specified, the default value is start_chunk + 20.

Responses

  • 200 — Content of the document and index of the latest retrieved chunk.
  • 404 — Document not found.
  • 500 — Internal server error.

Example Requests

curl -X GET   
  "https://api.rememberizer.ai/api/v1/documents/12345/contents/?start_chunk=0&end_chunk=20"   
  -H "Authorization: Bearer YOUR_JWT_TOKEN"

Info

Replace YOUR_JWT_TOKEN with your actual JWT token and 12345 with an actual document ID.

const getDocumentContents = async (documentId, startChunk = 0, endChunk = 20) => {
  const url = new URL(`https://api.rememberizer.ai/api/v1/documents/${documentId}/contents/`);
  url.searchParams.append('start_chunk', startChunk);
  url.searchParams.append('end_chunk', endChunk);

  const response = await fetch(url.toString(), {
    method: 'GET',
    headers: {
      'Authorization': 'Bearer YOUR_JWT_TOKEN'
    }
  });

  const data = await response.json();
  console.log(data);

  // If there are more chunks, you can fetch them
  if (data.end_chunk < totalChunks) {
    // Fetch the next set of chunks
    await getDocumentContents(documentId, data.end_chunk, data.end_chunk + 20);
  }
};

getDocumentContents(12345);

Info

Replace YOUR_JWT_TOKEN with your actual JWT token and 12345 with an actual document ID.

import requests

def get_document_contents(document_id, start_chunk=0, end_chunk=20):
    headers = {
        "Authorization": "Bearer YOUR_JWT_TOKEN"
    }

    params = {
        "start_chunk": start_chunk,
        "end_chunk": end_chunk
    }

    response = requests.get(
        f"https://api.rememberizer.ai/api/v1/documents/{document_id}/contents/",
        headers=headers,
        params=params
    )

    data = response.json()
    print(data)

    # If there are more chunks, you can fetch them
    # This is a simplistic example - you might want to implement a proper recursion check
    if 'end_chunk' in data and data['end_chunk'] < total_chunks:
        get_document_contents(document_id, data['end_chunk'], data['end_chunk'] + 20)

get_document_contents(12345)

Info

Replace YOUR_JWT_TOKEN with your actual JWT token and 12345 with an actual document ID.

Path Parameters

Parameter Type Description
document_id integer Required. The ID of the document to retrieve contents for.

Query Parameters

Parameter Type Description
start_chunk integer The starting chunk index. Default is 0.
end_chunk integer The ending chunk index. Default is start_chunk + 20.

Response Format

{
  "content": "The full text content of the document chunks...",
  "end_chunk": 20
}

Error Responses

Status Code Description
404 Document not found
500 Internal server error

Pagination for Large Documents

For large documents, the content is split into chunks. You can retrieve the full document by making multiple requests:

  1. Make an initial request with start_chunk=0
  2. Use the returned end_chunk value as the start_chunk for the next request
  3. Continue until you have retrieved all chunks

This endpoint returns the raw text content of a document, allowing you to access the full information for detailed processing or analysis.