Get processing documents

documents.list_processing() -> DocumentListProcessingResponse

GET/v3/documents/processing

Get documents that are currently being processed

ReturnsExpand Collapse

class DocumentListProcessingResponse: …

List of documents currently being processed

documents: List[Document]

id: str

Unique identifier of the document.

minLength22

maxLength22

created_at: str

Creation timestamp

formatdatetime

custom_id: Optional[str]

Optional custom ID of the document. This could be an ID from your database that will uniquely identify this document.

maxLength255

metadata: Union[str, float, bool, 3 more]

Optional metadata for the document. This is used to store additional information about the document. You can use this to store any additional information you need about the document. Metadata can be filtered through. Keys must be strings and are case sensitive. Values can be strings, numbers, or booleans. You cannot nest objects.

One of the following:

str

float

bool

Dict[str, object]

List[object]

status: Literal["unknown", "queued", "extracting", 5 more]

Status of the document

One of the following:

"unknown"

"queued"

"extracting"

"chunking"

"embedding"

"indexing"

"done"

"failed"

title: Optional[str]

Title of the document

type: Literal["text", "pdf", "tweet", 10 more]

Type of the document

One of the following:

"text"

"pdf"

"tweet"

"google_doc"

"google_slide"

"google_sheet"

"image"

"video"

"audio"

"notion_doc"

"webpage"

"onedrive"

"github_markdown"

updated_at: str

Last update timestamp

formatdatetime

Deprecatedcontainer_tags: Optional[List[str]]

Optional tags this document should be containerized by. This can be an ID for your user, a project ID, or any other identifier you wish to use to group documents.

total_count: float

Total number of processing documents

Get processing documents

import os
from supermemory import Supermemory

client = Supermemory(
    api_key=os.environ.get("SUPERMEMORY_API_KEY"),  # This is the default and can be omitted
)
response = client.documents.list_processing()
print(response.documents)

{
  "documents": [
    {
      "id": "xxxxxxxxxxxxxxxxxxxxxx",
      "createdAt": "2024-12-27T12:00:00Z",
      "customId": "doc-api-rate-limits",
      "metadata": {
        "source": "bar",
        "language": "bar"
      },
      "status": "extracting",
      "title": "My Document",
      "type": "text",
      "updatedAt": "2024-12-27T12:01:00Z",
      "containerTags": [
        "string"
      ]
    }
  ],
  "totalCount": 5
}

Returns Examples

{
  "documents": [
    {
      "id": "xxxxxxxxxxxxxxxxxxxxxx",
      "createdAt": "2024-12-27T12:00:00Z",
      "customId": "doc-api-rate-limits",
      "metadata": {
        "source": "bar",
        "language": "bar"
      },
      "status": "extracting",
      "title": "My Document",
      "type": "text",
      "updatedAt": "2024-12-27T12:01:00Z",
      "containerTags": [
        "string"
      ]
    }
  ],
  "totalCount": 5
}