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- **Help Agent** — A new agent that answers questions about Talemate itself — settings, agents, clients, the world editor — grounded in the bundled documentation, and able to change agent and application settings on request. - **Timeline Rollback** — Scrub a slider across a scene's automatic version history, preview the message history at any revision, then roll the scene back in place or fork the revision into a new save. - **Pi Bridge Client** — A new client type that drives generations through the pi coding agent's headless RPC mode, making any model pi can reach usable in Talemate. - **Application Settings** — Settings move out of their modal into an always-available Settings tab, with a single topic-grouped sidebar, a settings search, all API keys on one page, and unsaved-change tracking. - **Scene Library** — The home screen is rebuilt as a full-page landing view with a file-tree scene library, cover thumbnails and per-save metadata, scene and save deletion, and a drag-and-drop import dropzone. - **Fast Character Creation** — Generate a character in a single request instead of one prompt per aspect, with a Consolidate multi-select, a token budget, and a Fill in misses pass. Off by default. - **Scene Backdrop** — Set any scene illustration as a backdrop filling the scene view behind the messages, saved with the scene, with configurable text legibility and an Immersive quick-toggle. - **Scene Visual Manager** — World Editor → Scene gains a Visuals tab to browse, upload, generate and delete the scene's backgrounds and illustrations, and set the cover image and backdrop. - **Visual Prompt Finalization** — Post-processing actions — match and replace, or a free-form AI instruction — rewrite image prompts right before they reach the image backend, with per-scene and per-character overrides and reusable template sets. - fixes #271 - fixes #275 Plus 25 improvements and 39 bug fixes — see [CHANGELOG.md](https://github.com/vegu-ai/talemate/blob/prep-0.39.0/CHANGELOG.md#0390) for the full list.
2.5 KiB
2.5 KiB
Memory Agent Nodes
Query the long-term memory database (RAG) and unpack the returned memory documents.
2 nodes.
| Node | Registry path |
|---|---|
| Query Context DB | agents/memory/QueryContextDB |
| Unpack Memory Document | agents/memory/UnpackMemoryDocument |
Query Context DB
agents/memory/QueryContextDB
Queries the memory agent's context database with one or more queries and collects the matching documents, up to a total token budget.
Inputs
| Input | Type | Description |
|---|---|---|
state |
any |
The graph state |
queries |
list,str |
(optional) The queries to run (list, or a single query string) |
meta_filters |
dict |
Metadata filters to constrain the results (optional) |
max_tokens |
int |
The maximum total tokens of results to return (optional) |
fn_filter |
function |
Function that receives a result and returns whether to keep it (optional) |
fn_formatter |
function |
Function that receives a result and returns its formatted replacement (optional) |
Outputs
| Output | Type | Description |
|---|---|---|
state |
any |
The state input, passed through |
results |
list |
The list of matching documents |
Properties
| Property | Type | Default | Description |
|---|---|---|---|
queries |
list |
[] |
The queries to use to query the context database |
meta_filters |
dict |
{} |
The meta filters to apply to the results |
max_tokens |
int |
1024 |
The maximum number of tokens to return |
limit |
int |
10 |
The number of N best results to consider per query |
iterate |
int |
3 |
The number of results to return per query |
Unpack Memory Document
agents/memory/UnpackMemoryDocument
Unpacks a memory document into its individual fields.
Inputs
| Input | Type | Description |
|---|---|---|
document |
memory/document |
The memory document to unpack |
Outputs
| Output | Type | Description |
|---|---|---|
document |
memory/document |
The memory document, passed through |
meta |
dict |
The document's metadata dict |
id |
str |
The document's ID in the memory database |
raw |
dict |
The document's raw content |
as_text |
str |
The document rendered as text |
as_dict |
dict |
The document as a dict |
context_id |
context_id |
The document's context ID |