## Get document

`documents.get(strid)  -> DocumentGetResponse`

**get** `/v3/documents/{id}`

Get a document by ID

### Parameters

- `id: str`

### Returns

- `class DocumentGetResponse: …`

  Document object

  - `id: str`

    Unique identifier of the document.

  - `connection_id: Optional[str]`

    Optional ID of connection the document was created from. This is useful for identifying the source of the document.

  - `content: Optional[str]`

    The content to extract and process into a document. This can be a URL to a website, a PDF, an image, or a video.

    Plaintext: Any plaintext format

    URL: A URL to a website, PDF, image, or video

    We automatically detect the content type from the url's response format.

  - `created_at: str`

    Creation timestamp

  - `custom_id: Optional[str]`

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

  - `dreaming_status: Literal["dreaming", "done"]`

    - `"dreaming"`

    - `"done"`

  - `filepath: Optional[str]`

  - `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.

    - `str`

    - `float`

    - `bool`

    - `Dict[str, object]`

    - `List[object]`

  - `og_image: Optional[str]`

  - `raw: object`

    Raw content of the document

  - `source: Optional[str]`

    Source of the document

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

    Status of the document

    - `"unknown"`

    - `"queued"`

    - `"extracting"`

    - `"chunking"`

    - `"embedding"`

    - `"indexing"`

    - `"done"`

    - `"failed"`

  - `summary: Optional[str]`

    Summary of the document content

  - `task_type: Literal["memory", "superrag"]`

    Task type: "memory" (default) for full context layer with SuperRAG built in, "superrag" for managed RAG as a service.

    - `"memory"`

    - `"superrag"`

  - `title: Optional[str]`

    Title of the document

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

    Type of the document

    - `"text"`

    - `"pdf"`

    - `"tweet"`

    - `"google_doc"`

    - `"google_slide"`

    - `"google_sheet"`

    - `"image"`

    - `"video"`

    - `"audio"`

    - `"notion_doc"`

    - `"webpage"`

    - `"onedrive"`

    - `"github_markdown"`

  - `updated_at: str`

    Last update timestamp

  - `container_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.

  - `url: Optional[str]`

    URL of the document

### Example

```python
import os
from supermemory import Supermemory

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

#### Response

```json
{
  "id": "acxV5LHMEsG2hMSNb4umbn",
  "connectionId": "xxxxxxxxxxxxxxxxxxxxxx",
  "content": "Our API rate limits are 100 req/min on free and 1000 on pro.",
  "createdAt": "2025-04-15T09:30:00.000Z",
  "customId": "doc-api-rate-limits",
  "dreamingStatus": "dreaming",
  "filepath": "filepath",
  "metadata": {
    "source": "bar",
    "language": "bar"
  },
  "ogImage": "ogImage",
  "raw": "Our API rate limits are 100 req/min on free and 1000 on pro. Clients should use exponential backoff on 429s.",
  "source": "text",
  "status": "done",
  "summary": "API rate limit policy: 100 req/min free, 1000 req/min pro.",
  "taskType": "memory",
  "title": "API Rate Limiting Policy",
  "type": "text",
  "updatedAt": "2025-04-15T09:31:00.000Z",
  "containerTags": [
    "string"
  ],
  "url": "https://docs.example.com/guides/rate-limits"
}
```