Files
turnstone/docs/memory.md
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Patrick Buckley 67f43a7ee0 feat: [memory] REST API endpoints + SDK methods + docs (#56)
* feat: [memory] REST API endpoints + SDK methods + docs

Server API (4 endpoints):
- GET /v1/api/memories — list with type/scope/scope_id/limit filters
- POST /v1/api/memories — save (upsert) with validation
- POST /v1/api/memories/search — search by query (read scope)
- DELETE /v1/api/memories/{name} — delete by name+scope

Console admin API (4 endpoints):
- GET /v1/api/admin/memories — list all memories
- GET /v1/api/admin/memories/search — search with ?q= param
- GET /v1/api/admin/memories/{memory_id} — get by ID
- DELETE /v1/api/admin/memories/{memory_id} — delete by ID with audit

Storage: add delete_structured_memory_by_id, add mem_type filter to
count_structured_memories. Auth: memory DELETE requires write scope,
admin.memories permission added to valid set + builtin-admin role.

Python SDK: list_memories, save_memory, search_memories, delete_memory
on both server (async+sync) and console (async+sync) clients.

TypeScript SDK: matching methods + types on both clients.

Pydantic schemas with Literal type/scope validation, OpenAPI endpoint
specs on both servers. 33 endpoint tests + 8 auth scope tests.

Docs: docs/memory.md feature guide, api-reference.md endpoint docs,
23-memory-architecture.puml diagram.

Also fixes stray `total: int` on CreateChannelUserRequest.

* fix: [memory] address PR review — cross-user scope, schema types, snapshots

Security: user-scoped memory endpoints now bind scope_id to the
authenticated user's identity.  Providing a mismatched scope_id
returns 403, preventing cross-user memory access on all 4 server
endpoints.

Schema: MemoryInfo response uses MemoryType/MemoryScope Literals.
SearchMemoriesRequest uses filter Literals (empty string allowed).
Limit query params declare schema_type="integer" for correct OpenAPI.

Regenerate sdk/typescript/openapi-{server,console}.json snapshots.
Update count_structured_memories docstring for mem_type param.
Fix fallback response to use normalized name after save.

6 new security tests for user-scope access control.
2026-03-14 02:28:47 -07:00

570 lines
16 KiB
Markdown

# Structured Memory
> See also: [Memory Architecture diagram](diagrams/png/23-memory-architecture.png)
The structured memory system gives the AI persistent, typed, scoped memories
that survive across sessions and workstreams. Memories are automatically
surfaced in the system message via BM25 relevance scoring, so the model has
contextual recall without explicit search.
## Overview
Each memory has three dimensions:
- **Type** -- categorizes the memory's purpose
- **Scope** -- controls visibility boundaries
- **Name** -- unique identifier within a scope (snake_case, normalized)
### Memory types
| Type | Purpose |
|-------------|------------------------------------------------------------|
| `user` | User preferences, conventions, working style |
| `project` | Project-specific knowledge, architecture, patterns |
| `feedback` | Corrections, lessons learned, things to avoid |
| `reference` | Reference material, documentation, specifications |
### Memory scopes
| Scope | Visibility |
|--------------|-----------------------------------------------------------|
| `global` | Visible to all workstreams and users |
| `workstream` | Visible only within the originating workstream |
| `user` | Follows the authenticated user across workstreams |
A memory's identity is the tuple `(name, scope, scope_id)`. Saving a memory
with the same identity upserts -- updating content while preserving the ID.
### BM25 relevance injection
On every conversation turn, the system:
1. Fetches up to `fetch_limit` memories visible in the current scope
2. Extracts context from the last 3 user messages
3. Scores memories against that context using a BM25 index
4. Injects the top `relevance_k` memories into the system message as
`<memories>` XML tags
5. Appends a hint telling the model how many memories are in scope
This means the model always has its most relevant memories available without
explicit recall -- but can still use `memory(action='search')` for deeper
lookup.
### Nudges
The metacognition layer can nudge the model to save memories at appropriate
moments (e.g., after a correction or when resuming a workstream). Nudges are
rate-limited by `nudge_cooldown` and can be disabled entirely.
---
## Configuration
### config.toml
```toml
[memory]
relevance_k = 5 # top-k memories injected per turn
fetch_limit = 50 # max memories fetched from storage for scoring
max_content = 32768 # max content length per memory (characters)
nudge_cooldown = 300 # minimum seconds between memory nudges
nudges = true # enable/disable metacognitive nudges
```
All fields are optional. Defaults are shown above.
---
## Tool Usage
The `memory` tool supports four actions:
### save
Store or update a memory.
```json
{
"action": "save",
"name": "project_architecture",
"content": "The project uses a hexagonal architecture with...",
"description": "Core architecture patterns",
"type": "project",
"scope": "global"
}
```
| Parameter | Required | Default | Description |
|---------------|----------|-------------|------------------------------------------|
| `name` | yes | -- | Snake_case identifier (max 256 chars) |
| `content` | yes | -- | Memory content (max `max_content` chars) |
| `description` | no | `""` | Short description for relevance matching |
| `type` | no | `"project"` | One of: user, project, feedback, reference |
| `scope` | no | `"global"` | One of: global, workstream, user |
### search
Find memories by query (BM25 full-text search).
```json
{
"action": "search",
"query": "authentication patterns",
"type": "project",
"limit": 10
}
```
| Parameter | Required | Default | Description |
|-----------|----------|---------|--------------------------------------|
| `query` | yes | -- | Search query |
| `type` | no | `""` | Filter by type |
| `scope` | no | `""` | Filter by scope |
| `limit` | no | `20` | Max results (capped at 50) |
### delete
Remove a memory by name.
```json
{
"action": "delete",
"name": "outdated_pattern",
"scope": "global"
}
```
| Parameter | Required | Default | Description |
|------------|----------|------------|--------------------------|
| `name` | yes | -- | Memory name to delete |
| `scope` | no | `"global"` | Scope of the memory |
### list
List all memories with optional filters.
```json
{
"action": "list",
"type": "feedback",
"limit": 50
}
```
| Parameter | Required | Default | Description |
|-----------|----------|---------|----------------------------|
| `type` | no | `""` | Filter by type |
| `scope` | no | `""` | Filter by scope |
| `limit` | no | `20` | Max results (capped at 50) |
---
## Server API
Four endpoints on the server for programmatic memory access.
### `GET /v1/api/memories`
List memories with optional filters.
**Query parameters:**
| Parameter | Type | Required | Default | Description |
|------------|--------|----------|---------|------------------------------|
| `type` | string | no | `""` | Filter by memory type |
| `scope` | string | no | `""` | Filter by scope |
| `scope_id` | string | no | `""` | Filter by scope ID |
| `limit` | int | no | `100` | Max results (capped at 200) |
When `scope=user` and `scope_id` is omitted, the authenticated user's ID is
used automatically.
**Response:** `200`
```json
{
"memories": [
{
"memory_id": "a1b2c3d4-e5f6-...",
"name": "project_architecture",
"description": "Core architecture patterns",
"type": "project",
"scope": "global",
"scope_id": "",
"content": "The project uses a hexagonal architecture...",
"created": "2026-03-10T10:00:00",
"updated": "2026-03-12T14:30:00"
}
],
"total": 1
}
```
---
### `POST /v1/api/memories`
Save or upsert a structured memory.
**Request body:**
```json
{
"name": "deployment_process",
"content": "Deploy via GitHub Actions. Staging auto-deploys on push to main.",
"description": "CI/CD deployment workflow",
"type": "project",
"scope": "global",
"scope_id": ""
}
```
| Field | Type | Required | Default | Description |
|--------------|--------|----------|-------------|--------------------------------------|
| `name` | string | yes | -- | Memory name (max 256 chars) |
| `content` | string | yes | -- | Memory content (max 65536 chars) |
| `description`| string | no | `""` | Short description for search ranking |
| `type` | string | no | `"project"` | One of: user, project, feedback, reference |
| `scope` | string | no | `"global"` | One of: global, workstream, user |
| `scope_id` | string | no | `""` | Scope qualifier (auto-resolved for user scope) |
**Response (created):** `201`
```json
{
"memory_id": "a1b2c3d4-e5f6-...",
"name": "deployment_process",
"description": "CI/CD deployment workflow",
"type": "project",
"scope": "global",
"scope_id": "",
"content": "Deploy via GitHub Actions...",
"created": "2026-03-14T10:00:00",
"updated": "2026-03-14T10:00:00"
}
```
**Response (updated):** `200` -- same schema, returned when a memory with the
same `(name, scope, scope_id)` already existed.
**Errors:**
| Status | Condition |
|--------|------------------------------------|
| 400 | Missing name, empty content, invalid type/scope, content too long |
---
### `POST /v1/api/memories/search`
Search memories by query. Uses POST for the request body but is non-mutating
(requires only `read` scope).
**Request body:**
```json
{
"query": "authentication",
"type": "project",
"scope": "",
"scope_id": "",
"limit": 20
}
```
| Field | Type | Required | Default | Description |
|------------|--------|----------|---------|--------------------------------|
| `query` | string | yes | -- | Search query |
| `type` | string | no | `""` | Filter by type |
| `scope` | string | no | `""` | Filter by scope |
| `scope_id` | string | no | `""` | Filter by scope ID |
| `limit` | int | no | `20` | Max results (capped at 50) |
**Response:** `200`
```json
{
"memories": [
{
"memory_id": "a1b2c3d4-e5f6-...",
"name": "auth_patterns",
"description": "Authentication architecture",
"type": "project",
"scope": "global",
"scope_id": "",
"content": "JWT tokens with HS256...",
"created": "2026-03-10T10:00:00",
"updated": "2026-03-12T14:30:00"
}
],
"total": 1
}
```
---
### `DELETE /v1/api/memories/{name}`
Delete a memory by name and scope.
**Path parameters:**
| Parameter | Type | Description |
|-----------|--------|----------------------|
| `name` | string | Memory name |
**Query parameters:**
| Parameter | Type | Required | Default | Description |
|------------|--------|----------|------------|---------------------|
| `scope` | string | no | `"global"` | Scope of the memory |
| `scope_id` | string | no | `""` | Scope qualifier |
**Response (success):** `200`
```json
{"status": "ok", "name": "deployment_process"}
```
**Response (not found):** `404`
```json
{"error": "Memory 'deployment_process' not found"}
```
---
## Console Admin API
Four admin endpoints for cross-workstream memory management. All require the
`admin.memories` permission.
### `GET /v1/api/admin/memories`
List memories across all scopes (no automatic scope resolution).
**Query parameters:**
| Parameter | Type | Required | Default | Description |
|------------|--------|----------|---------|------------------------------|
| `type` | string | no | `""` | Filter by type |
| `scope` | string | no | `""` | Filter by scope |
| `scope_id` | string | no | `""` | Filter by scope ID |
| `limit` | int | no | `100` | Max results (capped at 200) |
**Response:** `200`
```json
{
"memories": [
{
"memory_id": "a1b2c3d4-e5f6-...",
"name": "project_architecture",
"description": "Core architecture patterns",
"type": "project",
"scope": "global",
"scope_id": "",
"content": "The project uses...",
"created": "2026-03-10T10:00:00",
"updated": "2026-03-12T14:30:00"
}
],
"total": 1
}
```
---
### `GET /v1/api/admin/memories/search`
Search memories by query (uses query parameters, not POST body).
**Query parameters:**
| Parameter | Type | Required | Default | Description |
|------------|--------|----------|---------|-------------------------------|
| `q` | string | yes | -- | Search query |
| `type` | string | no | `""` | Filter by type |
| `scope` | string | no | `""` | Filter by scope |
| `scope_id` | string | no | `""` | Filter by scope ID |
| `limit` | int | no | `20` | Max results (capped at 50) |
**Response:** `200` -- same schema as `GET /v1/api/admin/memories`.
---
### `GET /v1/api/admin/memories/{memory_id}`
Get a single memory by ID.
**Path parameters:**
| Parameter | Type | Description |
|-------------|--------|------------------------|
| `memory_id` | string | Memory UUID |
**Response (success):** `200`
```json
{
"memory_id": "a1b2c3d4-e5f6-...",
"name": "project_architecture",
"description": "Core architecture patterns",
"type": "project",
"scope": "global",
"scope_id": "",
"content": "The project uses...",
"created": "2026-03-10T10:00:00",
"updated": "2026-03-12T14:30:00"
}
```
**Response (not found):** `404`
```json
{"error": "Memory not found"}
```
---
### `DELETE /v1/api/admin/memories/{memory_id}`
Delete a memory by ID. Records an audit event (`memory.delete`).
**Path parameters:**
| Parameter | Type | Description |
|-------------|--------|------------------------|
| `memory_id` | string | Memory UUID |
**Response (success):** `200`
```json
{"status": "ok"}
```
**Response (not found):** `404`
```json
{"error": "Memory not found"}
```
---
## SDK
### Python
The server SDK uses `mem_type` (not `type`) to avoid shadowing the Python
builtin.
```python
from turnstone.sdk import TurnstoneServer
with TurnstoneServer("http://localhost:8080", token="tok_xxx") as client:
# Save a memory
mem = client.save_memory(
"api_conventions",
"All endpoints use /v1/ prefix. JSON responses.",
description="API design patterns",
mem_type="project",
scope="global",
)
print(mem.memory_id)
# Search memories
results = client.search_memories("authentication", mem_type="project", limit=10)
for m in results.memories:
print(f"{m['name']}: {m['description']}")
# List memories
all_mems = client.list_memories(mem_type="feedback", limit=50)
# Delete a memory
client.delete_memory("api_conventions", scope="global")
```
Console admin SDK:
```python
from turnstone.sdk import TurnstoneConsole
with TurnstoneConsole("http://localhost:9090", token="tok_xxx") as admin:
# List all memories (admin view, no scope auto-resolution)
result = admin.list_memories(scope="global", limit=100)
# Search
result = admin.search_memories("architecture", mem_type="project")
# Get by ID
mem = admin.get_memory("a1b2c3d4-e5f6-...")
# Delete by ID
admin.delete_memory("a1b2c3d4-e5f6-...")
```
### TypeScript
```typescript
import { TurnstoneServer } from "@turnstone/sdk";
const client = new TurnstoneServer({
baseUrl: "http://localhost:8080",
token: "tok_xxx",
});
// Save a memory
const mem = await client.saveMemory({
name: "api_conventions",
content: "All endpoints use /v1/ prefix. JSON responses.",
description: "API design patterns",
type: "project",
scope: "global",
});
// Search memories
const results = await client.searchMemories({
query: "authentication",
type: "project",
limit: 10,
});
// List memories
const all = await client.listMemories({ type: "feedback", limit: 50 });
// Delete a memory
await client.deleteMemory("api_conventions", { scope: "global" });
```
Console admin SDK:
```typescript
import { TurnstoneConsole } from "@turnstone/sdk";
const admin = new TurnstoneConsole({
baseUrl: "http://localhost:9090",
token: "tok_xxx",
});
// List, search, get, delete by ID
const mems = await admin.listMemories({ scope: "global" });
const found = await admin.searchMemories({ q: "auth", limit: 20 });
const one = await admin.getMemory("a1b2c3d4-e5f6-...");
await admin.deleteMemory("a1b2c3d4-e5f6-...");
```
---
## Storage
Memories are stored in the `structured_memories` table (migration 013).
The unique constraint on `(name, scope, scope_id)` ensures upsert semantics.
The name is normalized on save: lowercased, hyphens and spaces replaced with
underscores.
## Architecture
See [Memory Architecture diagram](diagrams/png/23-memory-architecture.png) for
the full data flow covering the session tool path, API path, admin path, and
BM25 relevance injection.