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PATCH
/
v2
/
memory-stores
/
{memory_store_key}
/
memories
/
{memory_entity_id}
/
documents
/
{document_id}
Update a specific memory document
curl --request PATCH \
  --url https://api.orq.ai/v2/memory-stores/{memory_store_key}/memories/{memory_entity_id}/documents/{document_id} \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "text": "<string>",
  "metadata": {}
}
'
{
  "_id": "<string>",
  "memory_id": "<string>",
  "store_id": "<string>",
  "text": "<string>",
  "created": "<string>",
  "updated": "<string>",
  "workspace_id": "<string>",
  "created_by_id": "<string>",
  "updated_by_id": "<string>",
  "metadata": {}
}

Documentation Index

Fetch the complete documentation index at: https://docs.orq.ai/llms.txt

Use this file to discover all available pages before exploring further.

Authorizations

​
Authorization
string
header
required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Path Parameters

​
memory_store_key
string
required

The unique key identifier of the memory store

​
memory_entity_id
string
required

The unique identifier of the memory

​
document_id
string
required

The unique identifier of the document

Body

application/json
​
text
string

The content of the memory document (whitespace trimmed).

Minimum string length: 1
​
metadata
object

Flexible key-value pairs for custom filtering and categorization. Clients can add arbitrary string metadata to enable future filtering of memory documents based on their specific needs (e.g., document type, source, topic, relevance score, or any custom taxonomy).

Response

Memory document successfully updated.

​
_id
string
required
​
memory_id
string
required
​
store_id
string
required
​
text
string
required

The content of the memory document (whitespace trimmed).

Minimum string length: 1
​
created
string
required
​
updated
string
required
​
workspace_id
string
required
​
created_by_id
string
​
updated_by_id
string
​
metadata
object

Flexible key-value pairs for custom filtering and categorization. Clients can add arbitrary string metadata to enable future filtering of memory documents based on their specific needs (e.g., document type, source, topic, relevance score, or any custom taxonomy).