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Author SHA1 Message Date
ztimson 263a65c192 Fix open-ai early termination & memory improvements
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2026-09-19 19:27:00 -04:00
ztimson 1e8c7c6662 Fix open-ai early termination
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2026-09-19 13:22:48 -04:00
ztimson 1f1a4662d4 Entity based notes
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2026-09-18 22:37:05 -04:00
ztimson ee4147e24e Fixed opanai early termination from tool calls
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2026-09-18 16:07:58 -04:00
ztimson d29c0ca389 Fixed opanai early termination from tool calls
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2026-09-18 02:15:02 -04:00
ztimson 4203cb34ef Better fact organization
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2026-09-14 12:22:49 -04:00
ztimson d42c240362 Memorization optimziations
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2026-08-31 12:38:40 -04:00
ztimson c1a16096ae Keep message progress on abort
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2026-08-29 21:18:28 -04:00
ztimson ff0ee0b60e Patched memory merging
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2026-08-28 16:48:46 -04:00
8 changed files with 654 additions and 312 deletions
+6 -6
View File
@@ -1,19 +1,19 @@
{
"name": "@ztimson/ai-utils",
"version": "1.5.0",
"version": "1.6.6",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "@ztimson/ai-utils",
"version": "1.5.0",
"version": "1.6.6",
"license": "MIT",
"dependencies": {
"@anthropic-ai/sdk": "^0.102.0",
"@huggingface/transformers": "^4.2.0",
"@tensorflow/tfjs": "^4.22.0",
"@ztimson/node-utils": "^1.0.7",
"@ztimson/utils": "^0.29.4",
"@ztimson/utils": "^0.30.8",
"cheerio": "^1.2.0",
"openai": "^6.42.0",
"pdf-parse": "^2.4.5",
@@ -1525,9 +1525,9 @@
"license": "MIT"
},
"node_modules/@ztimson/utils": {
"version": "0.29.7",
"resolved": "https://registry.npmjs.org/@ztimson/utils/-/utils-0.29.7.tgz",
"integrity": "sha512-cjQ9+RjC5X7gKNA/hJHDf7OtyYCa+5E0PDc76lIaATwNAxXCSx2IO9r2wHiHtZGV5bldjnFmw7aOV8Jmq7SgKQ==",
"version": "0.30.8",
"resolved": "https://registry.npmjs.org/@ztimson/utils/-/utils-0.30.8.tgz",
"integrity": "sha512-+vBjcinqckqMHkP95xWiQeQz2E7Q1oS0b+Odjp+F9rvQ4z0US4JdodjqhEaqh+RAO/yP77x4Eu0a04yBB4HNdw==",
"license": "MIT",
"dependencies": {
"var-persist": "^1.0.1"
+2 -2
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@@ -1,6 +1,6 @@
{
"name": "@ztimson/ai-utils",
"version": "1.6.4",
"version": "1.6.12",
"description": "AI Utility library",
"author": "Zak Timson",
"license": "MIT",
@@ -29,7 +29,7 @@
"@huggingface/transformers": "^4.2.0",
"@tensorflow/tfjs": "^4.22.0",
"@ztimson/node-utils": "^1.0.7",
"@ztimson/utils": "^0.29.4",
"@ztimson/utils": "^0.30.8",
"cheerio": "^1.2.0",
"openai": "^6.42.0",
"pdf-parse": "^2.4.5",
+1 -1
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@@ -4,7 +4,7 @@ import { Audio } from './audio.ts';
import {Vision} from './vision.ts';
export type AbortablePromise<T> = Promise<T> & {
abort: () => any
abort: (keep?: boolean) => any
};
export type AiOptions = {
+50
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@@ -13,6 +13,56 @@ export function extractLinks(content: string): string[] {
return [...new Set([...matches].map(m => m[1].trim()))];
}
/**
* Incrementally patch the graph for a set of changed memories, instead of
* re-scanning every document. Only the changed memories' own content is
* re-parsed for links; affected targets have their backlinks patched.
* Does NOT handle node deletion — full rebuildGraph() is still required
* when a memory is removed, since that needs a backlink sweep across
* everyone who might reference it.
*/
export function patchGraph(mems: Memory[], nodes: MemoryNode[], changed: Memory[]): MemoryNode[] {
const nameSet = new Set(mems.map(m => m.name));
const byName = new Map(nodes.map(n => [n.name, n]));
const ensureNode = (name: string): MemoryNode => {
let n = byName.get(name);
if (!n) {
n = {name, missing: !nameSet.has(name), links: [], backlinks: []};
byName.set(name, n);
}
return n;
};
for (const m of changed) {
const node = ensureNode(m.name);
node.missing = false; // real memory, promotes any pre-existing ghost entry
const oldLinks = m.links ?? [];
const newLinks = extractLinks(m.content).filter(l => l !== m.name);
for (const target of oldLinks.filter(l => !newLinks.includes(l))) {
const t = byName.get(target);
if (!t) continue;
t.backlinks = t.backlinks.filter(n => n !== m.name);
if (t.missing && !t.backlinks.length) byName.delete(target); // fully dereferenced ghost
}
for (const target of newLinks.filter(l => !oldLinks.includes(l))) {
const t = ensureNode(target);
if (!t.backlinks.includes(m.name)) t.backlinks.push(m.name);
}
m.links = newLinks;
node.links = newLinks;
}
for (const m of mems) {
const n = byName.get(m.name);
if (n) m.backlinks = n.backlinks;
}
return [...byName.values()];
}
export function rebuildGraph(memories: Memory[] | MemoryCache): MemoryNode[] {
const mems = memories instanceof MemoryCache ? memories.memories : memories;
const nameSet = new Set(mems.map(m => m.name));
+53 -12
View File
@@ -15,6 +15,7 @@ interface KDNode<T> {
axis: number;
left: KDNode<T> | null;
right: KDNode<T> | null;
deleted?: boolean;
}
// ─── Distance helpers ─────────────────────────────────────────────────────────
@@ -95,6 +96,7 @@ class BoundedMaxHeap<T> {
*
* Supports:
* - Insertion of labeled points
* - Lazy (tombstone) removal, physically purged on rebalance()
* - k-nearest-neighbor (KNN) search
* - Radius search (all points within a given distance)
* - Euclidean and cosine distance metrics
@@ -103,6 +105,7 @@ class BoundedMaxHeap<T> {
export class KDTree<T = unknown> {
private root: KDNode<T> | null = null;
private _size = 0;
private _tombstones = 0;
private readonly distanceFn: (a: number[], b: number[]) => number;
readonly dims: number;
@@ -129,9 +132,15 @@ export class KDTree<T = unknown> {
}
}
/** Total number of points stored in the tree. */
/** Total number of live points stored in the tree (excludes tombstoned). */
get size(): number { return this._size; }
/** Fraction of physical nodes that are tombstoned (pending removal on next rebalance). */
get tombstoneRatio(): number {
const total = this._size + this._tombstones;
return total ? this._tombstones / total : 0;
}
// ── Insertion ──────────────────────────────────────────────────────────────
/**
@@ -144,10 +153,36 @@ export class KDTree<T = unknown> {
this._size++;
}
// ── Removal ────────────────────────────────────────────────────────────────
/**
* Lazily remove all live points whose payload matches `predicate`.
* O(n) traversal, but avoids a full tree rebuild. Call `rebalance()`
* periodically (e.g. once tombstoneRatio crosses ~0.25) to reclaim space
* and restore optimal query depth.
* @returns number of points removed
*/
remove(predicate: (payload: T) => boolean): number {
let removed = 0;
const visit = (node: KDNode<T> | null): void => {
if (!node) return;
if (!node.deleted && predicate(node.point.payload)) {
node.deleted = true;
removed++;
}
visit(node.left);
visit(node.right);
};
visit(this.root);
this._size -= removed;
this._tombstones += removed;
return removed;
}
// ── KNN search ─────────────────────────────────────────────────────────────
/**
* Find the k nearest neighbors to `query`.
* Find the k nearest live neighbors to `query`.
* Returns results sorted by distance ascending.
*/
knn(query: number[], k: number): KNNResult<T>[] {
@@ -171,7 +206,7 @@ export class KDTree<T = unknown> {
// ── Radius search ──────────────────────────────────────────────────────────
/**
* Return all points whose distance to `query` is ≤ `radius`,
* Return all live points whose distance to `query` is ≤ `radius`,
* sorted by distance ascending.
*/
radiusSearch(query: number[], radius: number): KNNResult<T>[] {
@@ -186,7 +221,7 @@ export class KDTree<T = unknown> {
// ── Conversion ─────────────────────────────────────────────────────────────
/** Collect all points in the tree (order not guaranteed). */
/** Collect all live points in the tree (order not guaranteed). */
toArray(): KDPoint<T>[] {
const out: KDPoint<T>[] = [];
this.collect(this.root, out);
@@ -194,12 +229,14 @@ export class KDTree<T = unknown> {
}
/**
* Rebuild the tree from its current points as a balanced tree.
* Useful after many individual insertions to restore O(log n) query time.
* Rebuild the tree from its current live points as a balanced tree.
* Physically purges tombstones and restores O(log n) query time.
*/
rebalance(): void {
const points = this.toArray();
this.root = points.length ? this.buildBalanced(points, 0) : null;
this._size = points.length;
this._tombstones = 0;
}
// ── Private: build ─────────────────────────────────────────────────────────
@@ -251,8 +288,10 @@ export class KDTree<T = unknown> {
): void {
if (node === null) return;
const dist = this.distanceFn(query, node.point.vector);
heap.push({ point: node.point, distance: dist });
if (!node.deleted) {
const dist = this.distanceFn(query, node.point.vector);
heap.push({ point: node.point, distance: dist });
}
const axis = node.axis;
const diff = query[axis] - node.point.vector[axis];
@@ -285,9 +324,11 @@ export class KDTree<T = unknown> {
): void {
if (node === null) return;
const dist = this.distanceFn(query, node.point.vector);
if (dist <= radius) {
results.push({ point: node.point, distance: dist });
if (!node.deleted) {
const dist = this.distanceFn(query, node.point.vector);
if (dist <= radius) {
results.push({ point: node.point, distance: dist });
}
}
const axis = node.axis;
@@ -310,7 +351,7 @@ export class KDTree<T = unknown> {
private collect(node: KDNode<T> | null, out: KDPoint<T>[]): void {
if (node === null) return;
out.push(node.point);
if (!node.deleted) out.push(node.point);
this.collect(node.left, out);
this.collect(node.right, out);
}
+35 -11
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@@ -265,7 +265,7 @@ class LLM {
};
}
private setupAgent(agents: Agent[] = [], allAgents: Agent[], history: LLMMessage[], aborts: (() => void)[], depth = 0, delegateState: {resp: string | null}): AiTool[] {
private setupAgent(agents: Agent[] = [], allAgents: Agent[], history: LLMMessage[], aborts: ((keep?: boolean) => void)[], depth = 0, delegateState: {resp: string | null}): AiTool[] {
return agents.map(a => {
const toolName = `${a.delegate ? '' : 'sub'}agent_${snakeCase(a.name)}`;
return {
@@ -397,11 +397,13 @@ ${a.system}`,
if(!this.models[m]) throw new Error(`Model does not exist: ${m}`);
let request: AbortablePromise<string> | null = null;
let aborted = false;
const nestedAborts: (() => void)[] = [];
const abort = () => {
let keepOnAbort = true;
const nestedAborts: ((keep?: boolean) => void)[] = [];
const abort = (keep = true) => {
aborted = true;
request?.abort?.();
nestedAborts.forEach(a => a());
keepOnAbort = keep;
request?.abort?.(keep);
nestedAborts.forEach(a => a(keep));
};
let promise: any;
@@ -411,9 +413,25 @@ ${a.system}`,
let tools: AiTool[] = options.tools || this.ai.options.llm?.tools || [];
const prompts: string[] = [];
let history = options.history || [];
const historyStart = history.length;
const files = options.files || [];
if(message || files.length) history.push({role: 'user', content: message || '', timestamp: Date.now()});
// Accumulate streamed text so it can be committed to history if aborted mid-generation
let partialText = '';
const onStream = options.stream;
const stream = (chunk: {text?: string, tool?: string, done?: true}) => {
if(chunk.text) partialText += chunk.text;
return onStream?.(chunk);
};
/** Commit (keep) or discard this turn's progress on abort, then throw */
const abortNow = (): never => {
if(keepOnAbort) { if(partialText) history.push({role: 'assistant', content: partialText, timestamp: Date.now()}); }
else history.splice(historyStart, history.length - historyStart);
throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
};
// MCP
const mcp = options.mcp || this.ai.options?.llm?.mcp;
if(mcp?.length) {
@@ -441,8 +459,8 @@ ${a.system}`,
const mems = mem.memory instanceof MemoryCache ? mem.memory.memories : mem.memory;
if(mems.length) {
if(mem.inject) {
const pool = 15; // candidates considered, cheap since only refs are listed
const budget = mem.maxTokens ?? 2000; // actual content injected
const pool = 15;
const budget = mem.maxTokens ?? 2000;
const relevant = await this.memoryManager.recollect(message, mem.memory, pool);
let used = 0;
@@ -481,7 +499,7 @@ Linked: ${makeUnique([...r.links, ...r.backlinks]).join(', ')}
}
}
if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
if(aborted) abortNow();
const lastMsg = history[history.length - 1];
if(files.length && lastMsg?.role === 'user') lastMsg.files = files;
@@ -500,11 +518,17 @@ Linked: ${makeUnique([...r.links, ...r.backlinks]).join(', ')}
const toolTimings = new Map<string, {duration: number, tps: number}>();
tools = this.wrapToolTiming(tools, toolTimings);
if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
if(aborted) abortNow();
prompts.unshift(options.system || this.ai.options.llm?.system || '');
request = this.models[m].ask('', {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
let resp = await request;
request = this.models[m].ask('', {...options, tools, stream, system: prompts.filter(Boolean).join('\n\n')});
let resp: string;
try {
resp = await request;
} catch(err: any) {
if(aborted) return abortNow();
throw err;
}
// Strip the file injection shim
restores.forEach(({msg, content}) => msg.content = content);
+389 -239
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@@ -1,24 +1,21 @@
import {MemoryNode, rebuildGraph} from './helpers.ts';
import {MemoryNode, patchGraph, rebuildGraph} from './helpers.ts';
import {LLMRequest, LLMMessage} from './llm.ts';
import {AiTool} from './tools.ts';
import {KDPoint, KDTree} from './kd-tree.ts';
import {escapeRegex} from '@ztimson/utils';
import {KDTree} from './kd-tree.ts';
const MERGE_THRESHOLD = 0.88;
const FACT_SIMILARITY_THRESHOLD = 0.62;
const PENDING_HEADING = '## Pending';
const GENERIC_TEMPLATE = `# {{Title}}
## Summary
## Details
## Related`;
const TODO_HEADING = '## Todo list';
const TREE_TOMBSTONE_LIMIT = 0.25;
const ALIAS_MATCH_THRESHOLD = 0.55;
export type Memory = {
name: string;
description: string;
content: string;
embedding: number[];
titleEmbedding?: number[];
bodyEmbeddings?: number[][];
links: string[];
backlinks: string[];
}
@@ -26,6 +23,7 @@ export type Memory = {
type MemoryRef = {
name: string;
description: string;
distance?: number;
}
type FactBucket = {
@@ -33,24 +31,32 @@ type FactBucket = {
facts: string[];
}
type MemoryTask = {
/** Exact node name / new persistent entity path this task belongs to, or '' for a personal task with no entity (goes to the journal) */
subject: string;
task: string;
done: boolean;
}
type FactAgentResult = {
buckets: FactBucket[];
journal: string;
tasks: MemoryTask[];
}
function dedupeFacts(facts: string[]): string[] {
const seen = new Map<string, string>();
for (const f of facts) {
for(const f of facts) {
const clean = f.trim();
if (clean) seen.set(clean.toLowerCase(), clean);
if(clean) seen.set(clean.toLowerCase(), clean);
}
return [...seen.values()];
}
function cosineDistance(a: number[], b: number[]): number {
let dot = 0, normA = 0, normB = 0;
for (let i = 0; i < a.length; i++) {
dot += a[i] * b[i];
for(let i = 0; i < a.length; i++) {
dot += a[i] * b[i];
normA += a[i] * a[i];
normB += b[i] * b[i];
}
@@ -61,18 +67,34 @@ function cosineDistance(a: number[], b: number[]): number {
function cosineSearch(query: number[], memories: Memory[], limit: number): MemoryRef[] {
return memories
.filter(m => m.embedding?.length)
.map(m => ({ref: {name: m.name, description: m.description}, distance: cosineDistance(query, m.embedding)}))
.map(m => ({name: m.name, description: m.description, distance: cosineDistance(query, m.embedding)}))
.sort((a, b) => a.distance - b.distance)
.slice(0, limit)
.map(s => s.ref);
.slice(0, limit);
}
async function embedMemoryFields(node: Memory, llm: any): Promise<void> {
const body = stripHeader(node.content);
const [titleE] = await llm.embedding(node.name.split('/').pop() || node.name);
const [descE] = await llm.embedding(node.description || '');
const bodyChunks = body ? await llm.embedding(body) : [];
if(titleE) node.titleEmbedding = titleE.embedding;
if(descE) node.embedding = descE.embedding;
node.bodyEmbeddings = bodyChunks.map((c: any) => c.embedding).filter(Boolean);
}
export function stripHeader(content: string): string {
return content.replace(/^---[\s\S]*?\n---\n?/, '').trimStart();
}
/** True if a task has no persistent entity of its own and belongs in the journal instead. */
function isPersonalTask(t: MemoryTask): boolean {
const s = (t.subject ?? '').trim().toLowerCase();
return !s || s === 'journal' || s.startsWith('journal/');
}
export class MemoryCache {
private tree!: KDTree<MemoryRef>;
private indexed = new Map<string, number[]>();
public memories: Memory[];
public nodes: MemoryNode[] = [];
@@ -80,50 +102,62 @@ export class MemoryCache {
constructor(memories: Memory[]) {
this.memories = memories;
this.tree = new KDTree<MemoryRef>(0);
this.rebuild();
}
private buildTree(): KDTree<MemoryRef> {
const embedded = this.memories.filter(m => m.embedding?.length);
if (!embedded.length) return new KDTree<MemoryRef>(0);
private syncTree(): void {
const current = new Set(this.memories.map(m => m.name));
const dims = embedded[0].embedding.length;
const points: KDPoint<MemoryRef>[] = embedded.map(m => ({
vector: m.embedding,
payload: {name: m.name, description: m.description},
}));
for(const [name, emb] of [...this.indexed]) {
const mem = this.memories.find(m => m.name === name);
if(!mem || !current.has(name) || mem.embedding !== emb) {
this.tree.remove(p => p.name === name);
this.indexed.delete(name);
}
}
return new KDTree<MemoryRef>(dims, 'cosine', points);
for(const mem of this.memories) {
if(!mem.embedding?.length || this.indexed.has(mem.name)) continue;
if(this.tree.dims === 0) this.tree = new KDTree<MemoryRef>(mem.embedding.length, 'cosine');
if(mem.embedding.length !== this.tree.dims) continue; // guard against embedding model/dim drift
this.tree.insert({vector: mem.embedding, payload: {name: mem.name, description: mem.description}});
this.indexed.set(mem.name, mem.embedding);
}
if(this.tree.tombstoneRatio > TREE_TOMBSTONE_LIMIT) this.tree.rebalance();
}
search(query: number[], limit: number): MemoryRef[] {
if (!this.tree || this.tree.dims === 0) return [];
return this.tree.knn(query, limit).map(r => r.point.payload);
if(!this.tree || this.tree.dims === 0) return [];
return this.tree.knn(query, limit).map(r => ({...r.point.payload, distance: r.distance}));
}
add(memory: Memory): void {
this.memories.push(memory);
this.rebuild();
this.rebuild([memory]);
}
update(memory: Memory): void {
const existing = this.memories.find(m => m.name === memory.name);
if (existing) Object.assign(existing, memory);
if(existing) Object.assign(existing, memory);
else this.memories.push(memory);
this.rebuild();
this.rebuild([existing ?? memory]);
}
remove(name: string): void {
const idx = this.memories.findIndex(m => m.name === name);
if (idx !== -1) {
if(idx !== -1) {
this.memories.splice(idx, 1);
this.rebuild();
}
}
rebuild(): void {
this.nodes = rebuildGraph(this.memories);
this.tree = this.buildTree();
rebuild(changed?: Memory[]): void {
this.nodes = (changed?.length && this.nodes.length)
? patchGraph(this.memories, this.nodes, changed)
: rebuildGraph(this.memories);
this.syncTree();
}
}
@@ -140,9 +174,9 @@ class MemoryAccessor {
return this.list.find(m => m.name === name);
}
commit(): MemoryNode[] {
if (this.cache) {
this.cache.rebuild();
commit(changed?: Memory[]): MemoryNode[] {
if(this.cache) {
this.cache.rebuild(changed);
return this.cache.nodes;
}
return rebuildGraph(this.list);
@@ -159,7 +193,7 @@ class MemoryAccessor {
forget(name: string): boolean {
const idx = this.list.findIndex(m => m.name === name);
if (idx === -1) return false;
if(idx === -1) return false;
this.list.splice(idx, 1);
this.commit();
return true;
@@ -167,11 +201,8 @@ class MemoryAccessor {
async backfillEmbeddings(llm: any): Promise<number> {
const missing = this.list.filter(m => !m.embedding?.length);
if (!missing.length) return 0;
await Promise.all(missing.map(async node => {
const [e] = await llm.embedding(`${node.description}\n\n${stripHeader(node.content)}`.trim());
if (e) node.embedding = e.embedding;
}));
if(!missing.length) return 0;
await Promise.all(missing.map(node => embedMemoryFields(node, llm)));
this.commit();
return missing.length;
}
@@ -191,13 +222,13 @@ export type MemoryOptions = {
}
export class MemoryManager {
private recentlyTouched = new Map<string, number>();
private mergeLock: Promise<any> = Promise.resolve();
private queues = new Map<string, {
dirty: boolean,
request: {abort?: () => void} | null,
task: Promise<void>,
}>();
private recentlyTouched = new Map<string, number>();
tools = {
forget: (memories: Memory[] | MemoryCache): AiTool => ({
@@ -216,11 +247,11 @@ export class MemoryManager {
name: 'memory_recall',
description: 'Read the full content of a memory document',
args: {
name: {type: 'string', description: 'Exact memory name', required: true},
name: {type: 'string', description: 'Exact memory name', required: true}
},
fn: (args: any) => {
const mem = this.access(memories).find(args.name);
if (!mem) return 'Document not found';
const mem = new MemoryAccessor(memories).find(args.name);
if(!mem) return 'Document not found';
this.touch(mem.name);
return mem.content;
},
@@ -234,7 +265,7 @@ export class MemoryManager {
limit: {type: 'number', description: 'Number of memories to return', default: 1},
},
fn: async ({query, limit}) => {
const mem = await this.recollect(query, memories, limit)
const mem = await this.recollect(query, memories, limit);
return mem.map(m => `Memory: ${m.name}
Description: ${m.description}
Links: ${[...m.links, ...m.backlinks].join(', ')}
@@ -248,17 +279,16 @@ ${m.content}
constructor(private llm: any) {}
static normalize(m?: Memory[] | MemoryCache | MemoryOptions) {
if (!m) return null;
if(!m) return null;
const raw = m instanceof MemoryCache || Array.isArray(m);
return raw ? {memory: <Memory[] | MemoryCache>m, inject: true, tool: true, update: true} : {inject: true, tool: true, update: true, ...m};
}
private access(memories: Memory[] | MemoryCache): MemoryAccessor {
return new MemoryAccessor(memories);
}
private stage(node: Memory, block: string): void {
this.ensureDoc(node);
if(!node.content) {
const title = node.name.split('/').pop() ?? node.name;
node.content = this.touchHeader(node, `# ${title}\n`);
}
const body = stripHeader(node.content);
const idx = body.indexOf(PENDING_HEADING);
const newBody = idx === -1
@@ -267,19 +297,30 @@ ${m.content}
node.content = this.touchHeader(node, newBody);
}
private ensureDoc(node: Memory): void {
if (node.content) return;
const title = node.name.split('/').pop() ?? node.name;
node.content = this.touchHeader(node, `# ${title}\n`);
}
private resolveSubject(subject: string, store: MemoryAccessor): string {
function normalize(name: string): string {
return name.trim().toLowerCase().replace(/\s+/g, ' ');
}
private sanitizeDescription(text: string): string {
return (text ?? '').replace(/\s+/g, ' ').trim().slice(0, 240);
}
const trimmed = subject.trim();
const exact = store.find(trimmed);
if(exact) return exact.name;
private relink(memories: Memory[], from: string, to: string): void {
const pattern = new RegExp(`\\[\\[${escapeRegex(from)}\\]\\]`, 'g');
for (const m of memories) if (pattern.test(m.content)) m.content = m.content.replace(pattern, `[[${to}]]`);
const normalized = normalize(trimmed);
const caseInsensitive = store.list.find(m => normalize(m.name) === normalized);
if(caseInsensitive) return caseInsensitive.name;
const root = trimmed.split('/')[0];
const leaf = trimmed.split('/').slice(1).join('/') || trimmed;
const candidates = store.list.filter(m => m.name.split('/')[0] === root && m.name !== trimmed);
if(!candidates.length) return trimmed;
const leaves = candidates.map(m => m.name.split('/').slice(1).join('/') || m.name);
const probe = leaves.length > 1 ? leaves : [...leaves, ''];
const {max, similarities} = this.llm.fuzzyMatch(leaf, ...probe);
if(max >= ALIAS_MATCH_THRESHOLD) return candidates[similarities.indexOf(max)].name;
return trimmed;
}
private async factAgent(conversation: string, store: MemoryAccessor, options: LLMRequest): Promise<FactAgentResult> {
@@ -288,36 +329,70 @@ ${m.content}
const response = await this.llm.ask(conversation, {
model: options.model,
temperature: 0.2,
system: `You are a fact extractor for Obsidian-style knowledge vaults. Analyze the conversation and produce:
system: `Turn this conversation into a persistent memory file by extracting information into organized bullet points
1. Journal recap (single paragraph)
- "Captains Log" style record keeping
- What was discussed/worked on, decisions, user's events/state/mood, general context
- Leave empty only for trivial/empty exchanges/small talk
Think of this like an Obsidian vault with a clear division of responsibility:
- The JOURNAL is a timeline. It answers "what happened, and when" and is the only place with a sense of time.
- ENTITY DOSSIERS are a wiki. They answer "what is currently true about this subject", with no sense of time — only current state.
- Never blur the two: a one-off event, conversation, or debugging session is a journal entry, not an entity, even if it's detailed.
2. Fact buckets
- ONLY facts the USER explicitly stated about themselves, their work, projects, or decisions made during this conversation
- NEVER extract greetings, pleasantries, or anything the assistant itself said
- Extract the final/end state, not deltas
1. Journal Log
- A chronological, skimmable log of what actually happened: real discussions, decisions made, progress on projects, problems worked through
- This is NOT a transcript, and it is NOT a step-by-step record, its a compressed log of notable events & developments
- One line per development is usually enough: what was worked on and the outcome, not the blow-by-blow of how
- Skip small talk and trivial exchanges entirely. Skip anything that's purely a todo item (goes in Todo Tasks) or a durable fact about a subject (goes in Entity Dossiers)
Path assignment rules:
- Reuse existing node names whenever possible
- Documents should be grouped and named by the root subject
- Person → People/Name
- Project → Projects/Name
- Concept → Concepts/Name
- A bug report, its investigation, should be nested and attached to the same root subject node
- Tickets/one-off tasks → file under the project/name/component they belong to
- Only create a new top-level node when the fact belongs to a genuinely new subject (person/project/concept)\`
2. Todo Tasks
- Extract concrete tasks the user says need to be done, should be done, or were completed
- Return the task text and whether it is still todo or is done
- A completed task should be marked done, not recreated as a new todo
- Only extract actionable tasks, not general goals or observations
- Assign each task a subject:
- If the task belongs to a persistent entity (a project, a class, etc.), use that entity's exact node name, or a new entity path if it doesn't exist yet
- If it's a personal/life task with no entity of its own (reach out to someone, reply to an email, pay a bill, etc.), leave subject as an empty string — it belongs in the journal, not a new document
3. Entity Dossiers
- Detailed dossiers with all information regarding a subject
- Record the final/end state, not intermediate changes
- Ignore assistant claims, guesses, greetings, or temporary details
- NEVER create a document for something that's only meaningful as a point in time — a single conversation, a one-off decision, a debugging session, a date. That's a journal entry, not an entity
- identify its HOME ENTITY:
- The HOME ENTITY name should always be a [abstract|pro]noun
- The grammatical subject/owner of the fact is the strongest clue
- Always preference an existing entity over creating a new one
- New child entities are appropriate only when they are themselves distinct persistent entities
- A document represents a persistent entity, not a topic, feature, bug, event, decision, setting, or conversation fragment
- Put project facts under the project they belong to, person facts under the person, etc
Example Entity Naming Convention:
- Projects/[Name]
- People/[Name]
- History/[Name]
- Science/[Name]
- [Subject]/[Name]
- Class/[Name]/[Chapter]
Use [[WikiLinks]] to express relationships between entities. NEVER create documents just to hold relationships
Keep journal material in the journal; don't turn journal events into entities unless they represent something persistent
Available nodes:
${this.listNodes(store.list).map(n => `- ${n.name}: ${n.description}`).join('\n') || 'None yet.'}
${ghosts.length ? `${ghosts.map(g => `- ${g}: (Ghost)`).join('\n')}` : ''}`,
schema: {
journal: {type: 'string', description: 'Short day-to-day recap; empty if nothing happened.', required: false},
buckets: {type: 'array', description: 'Groups of facts to remember; empty array if nothing worth storing.', items: {
tasks: {
type: 'array', description: 'Concrete tasks mentioned or completed in the conversation.', required: false, items: {
type: 'object', items: {
subject: {type: 'string', description: 'Exact node name or new path (e.g. "People/Sarah", "Projects/Oxide")', required: true},
subject: {type: 'string', description: 'Exact node name / new persistent entity path this task belongs to, or an empty string if this is a personal task with no entity of its own (those go in the journal)', required: true},
task: {type: 'string', description: 'Concise actionable task', required: true},
done: {type: 'boolean', description: 'Whether the task is completed', required: true},
},
}
},
buckets: {
type: 'array', description: 'Groups of facts to remember; empty array if nothing worth storing.', items: {
type: 'object', items: {
subject: {type: 'string', description: 'Exact node name or new persistent entity path', required: true},
facts: {type: 'array', description: 'Facts to store here', items: {type: 'string'}},
},
},
@@ -326,7 +401,7 @@ ${ghosts.length ? `${ghosts.map(g => `- ${g}: (Ghost)`).join('\n')}` : ''}`,
});
const buckets = new Map<string, string[]>();
for (const bucket of response.buckets ?? []) {
for(const bucket of response.buckets ?? []) {
const subject = bucket.subject.trim();
const facts = buckets.get(subject) ?? [];
facts.push(...dedupeFacts(bucket.facts));
@@ -336,10 +411,11 @@ ${ghosts.length ? `${ghosts.map(g => `- ${g}: (Ghost)`).join('\n')}` : ''}`,
return {
buckets: buckets.entries().toArray().map(([subject, facts]) => ({subject, facts})),
journal: (response.journal ?? '').trim(),
tasks: response.tasks ?? [],
};
}
private getWeekMonday(date: Date = new Date()): string {
private getWeekStart(date: Date = new Date()): string {
const d = new Date(Date.UTC(date.getFullYear(), date.getMonth(), date.getDate()));
const day = d.getUTCDay();
const diff = day === 0 ? -6 : 1 - day;
@@ -347,50 +423,92 @@ ${ghosts.length ? `${ghosts.map(g => `- ${g}: (Ghost)`).join('\n')}` : ''}`,
return d.toISOString().slice(0, 10);
}
private journalDescription(journalName?: string): string {
const start = journalName?.split('/').pop() || this.getWeekStart();
const d = new Date(`${start}T00:00:00Z`);
d.setUTCDate(d.getUTCDate() + 6);
const end = d.toISOString().slice(0, 10);
return `Log from ${start} - ${end}`;
}
private getIncompleteTodos(content: string): string[] {
const body = stripHeader(content);
const match = body.match(/## Todo list\n([\s\S]*?)(?=\n## |$)/i);
if(!match) return [];
return match[1].split('\n')
.map(line => line.match(/^\s*-\s*\[([ xX])\]\s+(.+?)\s*$/))
.filter((m): m is RegExpMatchArray => !!m && m[1].toLowerCase() !== 'x')
.map(m => m[2].trim());
}
private listNodes(memories: Memory[]): MemoryRef[] {
return memories.map(m => ({name: m.name, description: m.description}));
}
/** Find the nearest node above the similarity threshold and fold the smaller/less-connected one into
* the other. Journals are exempt — they're partitioned by date, not topic, and merging across weeks
* would wreck the timeline. Returns 'merged' if `node` absorbed another (caller should re-run the doc
* agent), 'absorbed' if `node` itself got folded away (caller should stop touching it), or null. */
private async checkMerge(node: Memory, memories: Memory[] | MemoryCache, options: LLMRequest, threshold = MERGE_THRESHOLD): Promise<Memory | null> {
if (!node.embedding?.length || node.name.startsWith('Journal/')) return null;
const store = this.access(memories);
let closest: Memory | null = null, closestDist = Infinity;
for (const other of store.list) {
if (other.name === node.name || other.name.startsWith('Journal/') || !other.embedding?.length) continue;
const d = cosineDistance(node.embedding, other.embedding);
if (d < closestDist) { closestDist = d; closest = other; }
private async mergeAgent(node: Memory, memories: Memory[] | MemoryCache, options: LLMRequest): Promise<Memory | null> {
function factSimilarity(a: Memory, b: Memory): number {
if(!a.bodyEmbeddings?.length || !b.bodyEmbeddings?.length) return 0;
let best = 0;
for(const av of a.bodyEmbeddings) {
for(const bv of b.bodyEmbeddings) best = Math.max(best, 1 - cosineDistance(av, bv));
}
return best;
}
if (!closest || closestDist > threshold) return null;
const result = await this.mergeAgent(node, closest, options);
const merged: Memory = {name: result.name, description: this.sanitizeDescription(result.description), content: '', embedding: [], links: [], backlinks: []};
merged.content = this.touchHeader(merged, result.content);
const [e] = await this.llm.embedding(`${merged.description}\n\n${result.content}`.trim());
if (e) merged.embedding = e.embedding;
if(!node.embedding?.length || node.name.startsWith('Journal/')) return null;
const store = new MemoryAccessor(memories);
const candidates = store.list
.filter(m => m.name !== node.name && !m.name.startsWith('Journal/'))
.filter(m => factSimilarity(node, m) >= FACT_SIMILARITY_THRESHOLD);
this.relink(store.list, node.name, merged.name);
this.relink(store.list, closest.name, merged.name);
if(!candidates.length) return null;
const closest = candidates.sort((a, b) => factSimilarity(node, b) - factSimilarity(node, a))[0];
const result = await this.llm.ask('', {
model: options.model,
temperature: 0.3,
schema: {
aContent: {type: 'string', description: 'Updated document A body in markdown, without frontmatter.', required: true},
bContent: {type: 'string', description: 'Updated document B body in markdown, without frontmatter.', required: true},
},
system: `Maintain these two persistent knowledge-base documents like a wiki.
this.queues.get(closest.name)?.request?.abort?.();
this.queues.delete(closest.name);
Do NOT merge, rename, or delete either document. Both represent entities that should remain independently addressable.
store.forget(node.name);
store.forget(closest.name);
store.list.push(merged);
store.commit();
The documents were selected because their facts may overlap. Your job is to reconcile duplicated information and connect the documents:
- Decide which document is the HOME for each duplicated fact.
- Keep the authoritative copy in that home document.
- In the other document, replace the information with a short preamble and [[WikiLink]] to the home entity explaining the relationship.
- If the documents are distinct entities but merely related, keep their distinct facts and add useful [[WikiLinks]] between them.
- Do not delete useful entity-specific facts just because they are similar.
- Do not invent relationships or facts.
- Preserve useful history, technical specifics, structure, and existing [[WikiLinks]].
- Most current truth wins when facts conflict.
- Keep both documents concise and information-dense.
- No frontmatter, preamble, filler, or AI commentary.
return merged;
Document A ("${node.name}"):
\`\`\`markdown
${stripHeader(node.content)}
\`\`\`
Document B ("${closest.name}"):
\`\`\`markdown
${stripHeader(closest.content)}
\`\`\``,
});
const a = store.find(node.name);
const b = store.find(closest.name);
if(!a || !b || !result?.aContent || !result?.bContent) return null;
a.content = this.touchHeader(a, result.aContent);
b.content = this.touchHeader(b, result.bContent);
await Promise.all([embedMemoryFields(a, this.llm), embedMemoryFields(b, this.llm)]);
return a;
}
private reconcile(node: Memory, memories: Memory[] | MemoryCache, options: LLMRequest): Promise<void> {
const key = node.name;
const existing = this.queues.get(key);
if (existing) {
if(existing) {
existing.dirty = true;
existing.request?.abort?.();
return existing.task;
@@ -398,28 +516,65 @@ ${ghosts.length ? `${ghosts.map(g => `- ${g}: (Ghost)`).join('\n')}` : ''}`,
const entry = {dirty: false, request: null, task: Promise.resolve()};
this.queues.set(key, entry);
const store = this.access(memories);
const store = new MemoryAccessor(memories);
entry.task = (async () => {
let current = node;
do {
entry.dirty = false;
await this.docAgent(current, store.list, options, entry);
const merged = await this.checkMerge(current, memories, options);
if (merged) { current = merged; entry.dirty = true; }
} while (entry.dirty);
})().finally(() => {
this.queues.delete(key);
store.commit();
});
try {
do {
entry.dirty = false;
await this.docAgent(current, store.list, options, entry);
this.mergeLock = this.mergeLock.then(() => this.mergeAgent(current, memories, options));
const result = await this.mergeLock;
if(result) current = result;
} while(entry.dirty);
} finally {
store.commit([node]);
this.queues.delete(key);
}
})();
return entry.task;
}
private async docAgent(node: Memory, memories: Memory[], options: LLMRequest, entry: {request: {abort?: () => void} | null}): Promise<void> {
if(!memories.includes(node)) return;
const currentBody = stripHeader(node.content);
const journal = node.name.startsWith('Journal/');
const system = (journal
? `You maintain one persistent journal document
Rewrite the ENTIRE journal, folding "## Pending" into the existing content removing the heading
Journal design:
- Preserve the chronological daily log
- Maintain a single \`## Todo list\` section for this entity: reconcile tasks semantically (merge equivalent tasks, remove duplicates, preserve incomplete tasks, check off completed ones), and keep it distinct from the narrative/fact sections
- Group information by day under a date heading
- Keep journal entries high level and concise: what was worked on and the outcome, not a step-by-step record of how — that detail lives in conversation history, not here
- Use [[WikiLinks]] for persistent entities; don't turn ordinary journal events into entities
- No frontmatter, preamble, filler, or AI commentary`
: `You maintain one persistent knowledge-base entity document
Rewrite the ENTIRE document, folding "## Pending" into the existing content. Remove the Pending section when finished.
Document design:
- The document represents one persistent entity. Keep information about that entity together and organized into sections
- Merge any pending information in, newest fact wins conflicts; remove redundant content
- Maintain a single \`## Todo list\` section for this entity: reconcile tasks semantically (merge equivalent tasks, remove duplicates, preserve incomplete tasks, check off completed ones), and keep it distinct from the narrative/fact sections
- Let the structure fit the entity; there is NO fixed template
- Add headings only when they meaningfully organize recurring information; don't create headings for one-off facts
- Keep the document concise and information-dense without removing useful technical specifics
- Current truth wins when facts conflict. Preserve older conflict as context, only when it adds useful meaning
- No frontmatter, preamble, filler, or AI commentary`) + `
Available nodes to link to:
${this.listNodes(memories).filter(n => n.name !== node.name).map(n => n.name).join(', ') || 'none'}
Current document:
\`\`\`markdown
${currentBody}
\`\`\``;
let update;
try {
for (let i = 0; i < 2 && !update?.content; i++) {
for(let i = 0; i < 2 && !update?.content; i++) {
const request = this.llm.ask(currentBody, {
model: options.model,
temperature: 0.3,
@@ -427,93 +582,35 @@ ${ghosts.length ? `${ghosts.map(g => `- ${g}: (Ghost)`).join('\n')}` : ''}`,
description: {type: 'string', description: 'One factual sentence describing the document\'s ENTIRE SUBJECT MATTER — for use as a search/merge fingerprint', required: true},
content: {type: 'string', description: 'Rewritten document body in markdown, without the frontmatter block', required: true},
},
system: `You are a knowledge base editor maintaining one Obsidian-style document.
If it has a "## Pending" section, fold all new material into the appropriate part, resolve overlap, then remove the section entirely. If no section, just tidy per the rules below.
Use this loose structure, adapting headings to what the content needs:
# Title
## Summary
## Details
## Related
Rules:
- Contradictions: newer facts always win — delete outdated statements entirely
- Journals (Journal/...): keep entries as a chronological timeline; clean up grammar within entries but never delete history
- Use Obsidian markdown: # headings, **bold**, bullet/numbered lists, tables for 2D data
- Link specific entities and concepts with [[WikiLink]] (e.g., [[Projects/KiwixServer]]); skip generics
- Keep concise, factual, human-readable
- NO frontmatter, filler, preamble, or AI commentary
Available nodes to link to (don't duplicate their content):
${this.listNodes(memories).filter(n => n.name !== node.name).map(n => n.name).join(', ') || 'none'}
Current document:
\`\`\`markdown
${currentBody}
\`\`\``,
system,
});
entry.request = request;
update = await request;
}
} catch (err: any) {
if (err?.name === 'AbortError') return;
} catch(err: any) {
if(err?.name === 'AbortError') return;
throw err;
} finally {
entry.request = null;
}
if (!update?.content) return;
node.description = node.name !== 'People/User' ? this.sanitizeDescription(update.description) : 'All information about the current user';
if(!update?.content) return;
node.description = node.name.startsWith('Journal/') ? this.journalDescription(node.name) : node.name !== 'People/User' ? update.description.replaceAll(/[\n:]/g, '') : 'All information about the current user';
node.content = this.touchHeader(node, update.content);
const [e] = await this.llm.embedding(`${node.description}\n\n${update.content}`.trim());
if (e) node.embedding = e.embedding;
}
private async mergeAgent(a: Memory, b: Memory, options: LLMRequest): Promise<{name: string, description: string, content: string}> {
return this.llm.ask('', {
model: options.model,
temperature: 0.3,
schema: {
name: {type: 'string', description: 'New path for the merged doc, collection/subject format (e.g. Projects/Oxide) — only reuse an old title if it\'s genuinely the best fit', required: true},
description: {type: 'string', description: 'One factual sentence describing the merged document\'s subject matter', required: true},
content: {type: 'string', description: 'Fully reconciled body in markdown, without frontmatter', required: true},
},
system: `You are a knowledge base editor merging two overlapping Obsidian documents into one. Newer facts win on contradiction.
Structure loosely:
# Title
## Summary
## Details
## Related
Combine both documents, resolve duplication and contradictions.
Document A ("${a.name}"):
\`\`\`markdown
${stripHeader(a.content)}
\`\`\`
Document B ("${b.name}"):
\`\`\`markdown
${stripHeader(b.content)}
\`\`\``,
});
await embedMemoryFields(node, this.llm);
}
private parseFrontmatter(content: string): {fm: Map<string, string>, body: string} {
const match = content.match(/^---\n([\s\S]*?)\n---\n?([\s\S]*)$/);
if (!match) return {fm: new Map(), body: content};
if(!match) return {fm: new Map(), body: content};
const fm = new Map<string, string>();
for (const line of match[1].split('\n')) {
for(const line of match[1].split('\n')) {
const i = line.indexOf(':');
if (i === -1) continue;
if(i === -1) continue;
const key = line.slice(0, i).trim();
const raw = line.slice(i + 1).trim();
let value = raw;
try { value = JSON.parse(raw); } catch { /* legacy unquoted value, keep raw */ }
try { value = JSON.parse(raw); } catch { }
fm.set(key, value);
}
return {fm, body: match[2]};
@@ -522,9 +619,9 @@ ${stripHeader(b.content)}
private touchHeader(node: Memory, body: string): string {
const {fm} = this.parseFrontmatter(node.content);
fm.set('name', node.name);
fm.set('description', node.description || '');
fm.set('description', (node.name.startsWith('Journal/') ? this.journalDescription(node.name) : node.description) || 'Persistent memory document');
fm.set('modified', new Date().toISOString());
return this.writeFrontmatter(fm, body);
return this.writeFrontmatter(fm, stripHeader(body));
}
private writeFrontmatter(fm: Map<string, string>, body: string): string {
@@ -533,8 +630,8 @@ ${stripHeader(b.content)}
}
decay() {
for (const [name, ttl] of this.recentlyTouched) {
if (ttl <= 1) this.recentlyTouched.delete(name);
for(const [name, ttl] of this.recentlyTouched) {
if(ttl <= 1) this.recentlyTouched.delete(name);
else this.recentlyTouched.set(name, ttl - 1);
}
}
@@ -544,30 +641,43 @@ ${stripHeader(b.content)}
}
forget(name: string, memories: Memory[] | MemoryCache): boolean {
return this.access(memories).forget(name);
return new MemoryAccessor(memories).forget(name);
}
async recollect(query: string, memories: Memory[] | MemoryCache, limit = 5, graphDepth = 1): Promise<Memory[]> {
const store = this.access(memories);
if (!store.list.length) return [];
function rank(query: number[], candidates: Memory[], limit: number): Memory[] {
const scored = candidates.map(m => {
const titleSim = m.titleEmbedding?.length ? 1 - cosineDistance(query, m.titleEmbedding) : 0;
const descSim = m.embedding?.length ? 1 - cosineDistance(query, m.embedding) : 0;
const bodySim = m.bodyEmbeddings?.length
? Math.max(...m.bodyEmbeddings.map(b => 1 - cosineDistance(query, b)))
: 0;
return {memory: m, score: titleSim * 0.5 + descSim * 0.35 + bodySim * 0.15};
});
return scored.sort((a, b) => b.score - a.score).slice(0, limit).map(s => s.memory);
}
const store = new MemoryAccessor(memories);
if(!store.list.length) return [];
await store.backfillEmbeddings(this.llm);
const [e] = await this.llm.embedding(query);
if (!e) return [];
if(!e) return [];
const vectorResults = store.search(e.embedding, limit);
const found = new Set<string>(vectorResults.map(r => r.name));
const pool = store.search(e.embedding, Math.max(limit * 3, limit));
const poolMemories = pool.map(r => store.find(r.name)).filter((m): m is Memory => !!m);
const ranked = rank(e.embedding, poolMemories, limit);
const found = new Set<string>(ranked.map(m => m.name));
if (graphDepth > 0) {
if(graphDepth > 0) {
let frontier = [...found];
for (let depth = 0; depth < graphDepth && frontier.length; depth++) {
for(let depth = 0; depth < graphDepth && frontier.length; depth++) {
const next: string[] = [];
for (const name of frontier) {
for(const name of frontier) {
const node = store.find(name);
if (!node) continue;
for (const link of node.links) {
if (!found.has(link) && store.find(link)) {
if(!node) continue;
for(const link of node.links) {
if(!found.has(link) && store.find(link)) {
found.add(link);
next.push(link);
}
@@ -577,56 +687,96 @@ ${stripHeader(b.content)}
}
}
const vectorOrder = vectorResults.map(r => r.name);
const graphExpansions = [...found].filter(n => !vectorOrder.includes(n));
return [...vectorOrder, ...graphExpansions].map(n => store.find(n)!).filter(Boolean);
const rankedOrder = ranked.map(m => m.name);
const graphExpansions = [...found].filter(n => !rankedOrder.includes(n));
return [...rankedOrder, ...graphExpansions].map(n => store.find(n)!).filter(Boolean);
}
async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest): Promise<Memory[]> {
const conversation = history
.filter(h => h.role === 'user' || h.role === 'assistant')
.map(h => `[${h.role}]: ${h.content}`).join('\n\n').trim();
if (!conversation) return [];
if(!conversation) return [];
const uid = `${Date.now()}_${Math.random().toString(36).slice(2)}`;
const pending = {role: 'tool', name: 'memory_process', id: uid, content: conversation} as unknown as LLMMessage;
history.push(pending);
const store = this.access(memories);
const {buckets, journal} = await this.factAgent(conversation, store, options);
const store = new MemoryAccessor(memories);
const {buckets, journal, tasks} = await this.factAgent(conversation, store, options);
const touched: Memory[] = [];
if (journal) {
const journalName = `Journal/${this.getWeekMonday()}`;
const personalTasks = tasks.filter(isPersonalTask);
const entityTasks = tasks.filter(t => !isPersonalTask(t));
if(journal || personalTasks.length) {
const journalName = `Journal/${this.getWeekStart()}`;
let jnode = store.find(journalName);
if (!jnode) {
jnode = {name: journalName, description: '', content: '', embedding: [], links: [], backlinks: []};
const isNew = !jnode;
if(!jnode) {
jnode = {
name: journalName,
description: this.journalDescription(),
content: '',
embedding: [],
links: [],
backlinks: [],
};
store.list.push(jnode);
}
this.stage(jnode, `### ${new Date().toISOString().slice(0, 10)}\n${journal}`);
const blocks: string[] = [];
if(journal) blocks.push(`### ${new Date().toISOString().slice(0, 10)}\n${journal}`);
if(isNew) {
const previousDate = new Date(`${this.getWeekStart()}T00:00:00Z`);
previousDate.setUTCDate(previousDate.getUTCDate() - 7);
const previous = store.find(`Journal/${previousDate.toISOString().slice(0, 10)}`);
if(previous) {
const todos = this.getIncompleteTodos(previous.content);
if(todos.length) blocks.push(`${TODO_HEADING}\n${todos.map(task => `- [ ] ${task}`).join('\n')}`);
}
}
if(personalTasks.length) blocks.push(`${TODO_HEADING}\n${personalTasks.map(task => `- [${task.done ? 'x' : ' '}] ${task.task}`).join('\n')}`);
if(blocks.length) this.stage(jnode, blocks.join('\n\n'));
touched.push(jnode);
}
for (const {subject, facts} of buckets) {
let node = store.find(subject);
if (!node) {
node = {name: subject, description: '', content: '', embedding: [], links: [], backlinks: []};
const entityStaging = new Map<string, {facts: string[], tasks: MemoryTask[]}>();
for(const {subject, facts} of buckets) {
const resolved = this.resolveSubject(subject, store);
const entry = entityStaging.get(resolved) ?? {facts: [], tasks: []};
entry.facts.push(...facts);
entityStaging.set(resolved, entry);
}
for(const task of entityTasks) {
const resolved = this.resolveSubject(task.subject, store);
const entry = entityStaging.get(resolved) ?? {facts: [], tasks: []};
entry.tasks.push(task);
entityStaging.set(resolved, entry);
}
for(const [resolved, {facts, tasks: subjectTasks}] of entityStaging) {
let node = store.find(resolved);
if(!node) {
node = {name: resolved, description: 'Persistent memory document', content: '', embedding: [], links: [], backlinks: []};
store.list.push(node);
}
this.stage(node, facts.map(f => `- ${f}`).join('\n'));
const blocks: string[] = [];
if(facts.length) blocks.push(facts.map(f => `- ${f}`).join('\n'));
if(subjectTasks.length) blocks.push(`${TODO_HEADING}\n${subjectTasks.map(t => `- [${t.done ? 'x' : ' '}] ${t.task}`).join('\n')}`);
if(blocks.length) this.stage(node, blocks.join('\n\n'));
touched.push(node);
}
for (const node of touched) {
const [e] = await this.llm.embedding(`${node.description}\n\n${stripHeader(node.content)}`.trim());
if (e) node.embedding = e.embedding;
await Promise.all(touched.map(async node => {
await embedMemoryFields(node, this.llm);
this.touch(node.name);
}
}));
if (touched.length) {
store.commit();
if(touched.length) {
store.commit(touched);
(pending as any).content = `Saved to ${touched.map(n => `[[${n.name}]]`).join(', ')}`;
await Promise.all(touched.map(node => this.reconcile(node, memories, options).catch(() => {})));
Promise.all(touched.map(node => this.reconcile(node, memories, options).catch(() => {})));
} else {
(pending as any).content = 'Nothing worth remembering.';
}
@@ -636,7 +786,7 @@ ${stripHeader(b.content)}
}
async reconcileAll(memories: Memory[] | MemoryCache, options: LLMRequest, scope: 'touched' | 'all' = 'touched'): Promise<void> {
const store = this.access(memories);
const store = new MemoryAccessor(memories);
const targets = scope === 'all' ? store.list : store.list.filter(m => m.content.includes(PENDING_HEADING));
await Promise.all(targets.map(node => this.reconcile(node, memories, options)));
store.commit();
+118 -41
View File
@@ -36,21 +36,49 @@ export class OpenAi extends LLMProvider {
private toWire(history: LLMMessage[], system?: string): any[] {
const wire: any[] = [];
if(system) wire.push({role: 'system', content: system});
for(const h of history) {
if(h.role === 'tool') {
wire.push({
role: 'assistant',
content: null,
tool_calls: [{id: h.id, type: 'function', function: {name: h.name, arguments: JSON.stringify(h.args)}}],
}, {
role: 'tool',
tool_call_id: h.id,
content: h.error || h.content || '',
});
} else {
for(let i = 0; i < history.length; i++) {
const h = history[i];
if(h.role !== 'tool') {
wire.push({role: h.role, content: this.toWireContent(h.content)});
continue;
}
const calls: any[] = [];
const results: any[] = [];
while(i < history.length && history[i].role === 'tool') {
const tool: any = history[i];
calls.push({
id: tool.id,
type: 'function',
function: {
name: tool.name,
arguments: JSON.stringify(tool.args || {})
}
});
results.push({
role: 'tool',
tool_call_id: tool.id,
content: tool.error || tool.content || ''
});
i++;
}
wire.push({
role: 'assistant',
content: null,
tool_calls: calls
});
wire.push(...results);
i--;
}
return wire;
}
@@ -60,13 +88,12 @@ export class OpenAi extends LLMProvider {
if(!options.history) options.history = [];
const history = options.history;
if(message) history.push({role: 'user', content: message, timestamp: Date.now()});
const tools = options.tools || this.ai.options.llm?.tools || [];
const requestParams: any = {
model: options.model || this.model,
stream: !!options.stream,
max_completion_tokens: options.maxTokens || this.ai.options.llm?.maxTokens || undefined,
temperature: options.temperature || this.ai.options.llm?.temperature || undefined,
max_completion_tokens: options.maxTokens ?? this.ai.options.llm?.maxTokens,
temperature: options.temperature ?? this.ai.options.llm?.temperature,
tools: tools.map(t => ({
type: 'function',
function: {
@@ -74,8 +101,12 @@ export class OpenAi extends LLMProvider {
description: t.description,
parameters: {
type: 'object',
properties: t.args ? objectMap(t.args, (key, value) => ({...value, required: undefined})) : {},
required: t.args ? Object.entries(t.args).filter(t => t[1].required).map(t => t[0]) : []
properties: t.args
? objectMap(t.args, (key, value) => ({...value, required: undefined}))
: {},
required: t.args
? Object.entries(t.args).filter(t => t[1].required).map(t => t[0])
: []
}
}
}))
@@ -83,60 +114,106 @@ export class OpenAi extends LLMProvider {
if(options.schema) {
const schema = convertSchema(options.schema);
requestParams.response_format = {type: 'json_schema', json_schema: {name: 'response', strict: true, schema}};
requestParams.response_format = {
type: 'json_schema',
json_schema: {name: 'response', strict: true, schema}
};
}
if(options.stream) requestParams.stream_options = {include_usage: true};
try {
let terminal = false;
let iteration = 0;
do {
iteration++;
requestParams.messages = this.toWire(history.filter(h => h.role !== 'system'), options.system);
const callStart = Date.now();
const resp: any = await this.tokenPool.run(token => this.getClient(token).chat.completions.create(requestParams)).catch(err => {
const resp: any = await this.tokenPool.run(token =>
this.getClient(token).chat.completions.create(requestParams)
).catch(err => {
err.message += `\n\nMessages:\n${JSON.stringify(requestParams.messages, null, 2)}`;
throw err;
});
let usage: any, msg: any = {content: '', tool_calls: []};
let usage: any;
let finishReason: string | undefined;
let msg: any = {content: '', tool_calls: []};
let streamedChars = 0;
if(options.stream) {
for await (const chunk of resp) {
if(controller.signal.aborted) break;
if(chunk.usage) usage = chunk.usage;
if(chunk.choices[0]?.delta?.content) {
msg.content += chunk.choices[0].delta.content;
options.stream({text: chunk.choices[0].delta.content});
}
if(chunk.choices[0]?.delta?.tool_calls) {
for(const deltaTC of chunk.choices[0].delta.tool_calls) {
const existing = msg.tool_calls.find((tc: any) => tc.index === deltaTC.index);
if(existing) {
let streamCompleted = false;
try {
for await (const chunk of resp) {
if(controller.signal.aborted) break;
if(chunk.usage) usage = chunk.usage;
const choice = chunk.choices?.[0];
if(choice?.finish_reason) finishReason = choice.finish_reason;
if(choice?.delta?.content) {
msg.content += choice.delta.content;
streamedChars += choice.delta.content.length;
options.stream({text: choice.delta.content});
}
if(choice?.delta?.tool_calls) {
for(const deltaTC of choice.delta.tool_calls) {
const index = deltaTC.index ?? msg.tool_calls.length;
let existing = msg.tool_calls.find((tc: any) => tc.index === index);
if(!existing) {
existing = {index, id: '', function: {name: '', arguments: ''}};
msg.tool_calls.push(existing);
}
if(deltaTC.id) existing.id = deltaTC.id;
if(deltaTC.function?.name) existing.function.name = deltaTC.function.name;
if(deltaTC.function?.arguments) existing.function.arguments += deltaTC.function.arguments;
} else {
msg.tool_calls.push({
index: deltaTC.index,
id: deltaTC.id || '',
function: {name: deltaTC.function?.name || '', arguments: deltaTC.function?.arguments || ''}
});
}
}
}
streamCompleted = true;
} catch(err) {
if(!controller.signal.aborted) throw err;
}
if(streamCompleted && !finishReason) finishReason = msg.tool_calls.length ? 'tool_calls' : 'stop';
} else {
usage = resp.usage;
finishReason = resp.choices[0].finish_reason;
msg = resp.choices[0].message;
}
const duration = Date.now() - callStart;
const tps = usage?.completion_tokens && duration > 0 ? usage.completion_tokens / (duration / 1000) : 0;
if(finishReason === 'length' && !controller.signal.aborted) {
if(msg.content?.trim()) history.push({role: 'assistant', content: msg.content.trim(), timestamp: Date.now(), duration, tps});
throw new Error(`[OpenAI] Response hit token limit before completing`);
}
if(!finishReason && !controller.signal.aborted) {
throw new Error('[OpenAI] Completion ended without a usable response');
}
const toolCalls = msg.tool_calls || [];
if(toolCalls.length && !controller.signal.aborted) {
if(msg.content?.trim()) history.push({role: 'assistant', content: msg.content.trim(), timestamp: Date.now(), duration, tps});
const entries = toolCalls.map((tc: any) => {
const entry: any = {role: 'tool', id: tc.id, name: tc.function.name, args: JSONAttemptParse(tc.function.arguments, {}), content: undefined, timestamp: Date.now()};
const entry: any = {
role: 'tool',
id: tc.id,
name: tc.function.name,
args: JSONAttemptParse(tc.function.arguments, {}),
content: undefined,
timestamp: Date.now()
};
history.push(entry);
return {tc, entry};
});
@@ -144,12 +221,13 @@ export class OpenAi extends LLMProvider {
await Promise.all(entries.map(async ({tc, entry}: any) => {
const tool = tools.find(findByProp('name', tc.function.name));
if(options.stream) options.stream({tool: tc.function.name});
if(!tool) { entry.error = 'Tool not found'; return; }
if(!tool) return entry.error = 'Tool not found';
try {
const toolStream = options.stream && ((chunk: any) => {
if(chunk.done) { terminal = true; return; }
if(chunk.done) return;
options.stream!(chunk);
});
const result = await tool.fn(entry.args, toolStream, this.ai, tc.id);
entry.content = typeof result === 'object' ? JSONSanitize(result) : result;
} catch(err: any) {
@@ -164,7 +242,6 @@ export class OpenAi extends LLMProvider {
} while(!terminal && !controller.signal.aborted);
if(options.stream) options.stream({done: true});
const turnStart = history.map(h => h.role).lastIndexOf('user');
const finalContent = history.slice(turnStart + 1).reduce((str, h) => h.role === 'assistant' ? str + (h.content || '') : str, '').trim();
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);