Memory models

Retrieve answers a question from individual memories. A memory model answers a standing question from all of them, and keeps that answer current as new memories arrive. Give a model a question (“how does this user like to be communicated with?”, “what is this customer’s account history?”) and the memory layer synthesizes an answer across everything the space knows, then rewrites it as the space learns more. Read it back as markdown and drop it straight into a system prompt.

A model’s content is generated in the background. Creating or refreshing one returns a job_id; poll GET /v1/spaces/{space_id}/jobs/{job_id}, then read the model to get its content.

Everything on this page is also on the Models tab of a space in the dashboard: the profile, each model’s rendered content, and create, edit, refresh, clear and delete. Useful for reading what a space has concluded without writing a line of code.

Create a model

POST /v1/spaces/{space_id}/models
Authorization: Bearer anona_live_YOUR_KEY
Content-Type: application/json

{
  "name": "Communication style",
  "query": "How does this user prefer to be communicated with?",
  "model_id": "comms",
  "tags": ["prefs"],
  "max_tokens": 2048,
  "trigger": { "mode": "delta", "refresh_on_new_memories": true }
}

Field	Type	Default	Description
`name`	string	required	Human-readable name.
`query`	string	required	The question this model answers from the space’s memories.
`model_id`	string	generated	Optional stable id. Lowercase alphanumeric and hyphens.
`tags`	string[]	none	Only build the model from memories carrying these tags.
`max_tokens`	integer	2048	Ceiling on generated content length, 256 to 8192.
`trigger.mode`	`full` \| `delta`	`full`	How a refresh rewrites the content. See refresh modes.
`trigger.refresh_on_new_memories`	boolean	`false`	Refresh automatically once newly recorded memories are consolidated.
`trigger.memory_type`	string[]	all	Restrict to `fact`, `experience` and/or `note`.

Response 202 Accepted

{ "model_id": "comms", "job_id": "job_9f2a", "status": "processing" }

List models

GET /v1/spaces/{space_id}/models?limit=50&offset=0&tags=prefs
Authorization: Bearer anona_live_YOUR_KEY

Response 200 OK

{
  "items": [
    {
      "id": "comms",
      "space_id": "customer-support-bot",
      "name": "Communication style",
      "query": "How does this user prefer to be communicated with?",
      "content": "Prefers short, direct answers. Has asked for brevity in several sessions and disengages past about three paragraphs.",
      "tags": ["prefs"],
      "max_tokens": 2048,
      "trigger": {
        "mode": "delta",
        "refresh_on_new_memories": true,
        "memory_type": null
      },
      "last_refreshed_at": "2026-08-01T10:00:00Z",
      "created_at": "2026-07-01T10:00:00Z",
      "is_stale": false
    }
  ],
  "total": 1,
  "limit": 50,
  "offset": 0
}

Field	Type	Description
`content`	string or null	The current answer, as markdown. Null until the first refresh finishes, or after a clear. A model that has never been refreshed reports `null`, never a partial or placeholder answer.
`is_stale`	boolean or null	True when memories have been recorded since the last refresh, so the content is behind.
`last_refreshed_at`	string or null	ISO timestamp of the last rewrite.

Get a model

GET /v1/spaces/{space_id}/models/{model_id}
Authorization: Bearer anona_live_YOUR_KEY

Returns the same object as a list item.

Update a model

Changes the definition. Existing content is left alone. Change the query and the answer only catches up on the next refresh.

PATCH /v1/spaces/{space_id}/models/{model_id}
Authorization: Bearer anona_live_YOUR_KEY

{ "name": "Communication preferences", "max_tokens": 4096 }

Response 200 OK, the updated model.

Refresh a model

Re-answers the model’s question from everything the space knows now.

POST /v1/spaces/{space_id}/models/{model_id}/refresh
Authorization: Bearer anona_live_YOUR_KEY

Response 202 Accepted

{ "model_id": "comms", "job_id": "job_be71", "status": "queued" }

Refresh modes

Mode	Behaviour
`full`	Regenerates the content from scratch every time. Predictable, and the right default.
`delta`	Edits in place: untouched sections are preserved verbatim, stale parts are dropped, new material is added. Cheaper on long documents. A model with no content yet, or whose `query` changed, falls back to a full regeneration automatically.

A delta model that has drifted over many incremental edits can be reset: clear it, then refresh for a clean rebuild.

Clear a model’s content

Drops the content, keeps the definition.

POST /v1/spaces/{space_id}/models/{model_id}/clear
Authorization: Bearer anona_live_YOUR_KEY

Response 200 OK, the model, with content now null.

Delete a model

Removes the model. The memories it was built from are untouched.

DELETE /v1/spaces/{space_id}/models/{model_id}
Authorization: Bearer anona_live_YOUR_KEY

Response 204 No Content

Model history

Every refresh archives the content it replaced, most recent first, showing how the space’s view of the question changed as it learned more.

GET /v1/spaces/{space_id}/models/{model_id}/history
Authorization: Bearer anona_live_YOUR_KEY

Response 200 OK

{
  "entries": [
    {
      "previous_content": "Prefers detailed explanations.",
      "changed_at": "2026-07-15T09:00:00Z"
    }
  ],
  "total": 1
}

Space profile

The space’s standing description: what it is for, and how it weighs what it is told.

GET /v1/spaces/{space_id}/profile
Authorization: Bearer anona_live_YOUR_KEY

Response 200 OK

{
  "space_id": "customer-support-bot",
  "name": "Alice",
  "mission": "Keep Alice's team organized and shipping.",
  "disposition": { "skepticism": 3, "literalism": 4, "empathy": 5 }
}

Field	Type	Description
`mission`	string	What this space is for. Empty if never set.
`disposition.skepticism`	integer	1 takes statements at face value, 5 questions them.
`disposition.literalism`	integer	1 reads intent loosely, 5 reads literally.
`disposition.empathy`	integer	1 ignores emotional context, 5 weighs it heavily.

Disposition shapes how the space interprets what it is told when it synthesizes. It does not affect plain retrieval.

Cost

Creating and refreshing a model each run a synthesis pass over the space’s memories and are billed like reason. Reading models, history and the profile is free.

Error responses

Status	Code	Cause
401	`unauthorized`	Missing or invalid API key.
403	`forbidden`	The space is not owned by your organization.
404	`model_error`	The space or model does not exist.
422	`validation_error`	Unknown or malformed field in the request body.
429	`rate_limited`	Credit quota or rate limit exceeded.

See the full error reference.

Next steps

Reason API

Answer a one-off question across memories.

MCP integration

Let an agent read a space’s profile and models directly.

API Essentials

Memory (data plane)

LLM Proxy (drop-in)

Account (control plane)

Create a model

List models

Get a model

Update a model

Refresh a model

Refresh modes

Clear a model’s content

Delete a model

Model history

Space profile

Cost

Error responses

Next steps

Reason API

MCP integration

​Create a model

​List models

​Get a model

​Update a model

​Refresh a model

​Refresh modes

​Clear a model’s content

​Delete a model

​Model history

​Space profile

​Cost

​Error responses

​Next steps

Reason API

MCP integration

Create a model

List models

Get a model

Update a model

Refresh a model

Refresh modes

Clear a model’s content

Delete a model

Model history

Space profile

Cost

Error responses

Next steps